From a1fff9bcb9ec5b4411ae8542e8372669b043eb65 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Mon, 29 Apr 2024 18:53:21 -0700 Subject: [PATCH 01/68] build: Add spark-4.0 profile --- .../apache/comet/shims/ShimBatchReader.scala | 54 ++++++++ .../apache/comet/shims/ShimFileFormat.scala | 35 +++++ .../shims/ShimResolveDefaultColumns.scala | 38 ++++++ pom.xml | 19 ++- .../parquet/CometParquetFileFormat.scala | 9 +- .../CometParquetPartitionReaderFactory.scala | 3 +- .../apache/comet/parquet/ParquetFilters.scala | 8 +- .../org/apache/comet/shims/ShimSQLConf.scala | 4 + .../comet/shims/ShimCometBatchScanExec.scala | 45 +++++++ .../ShimCometBroadcastExchangeExec.scala | 51 +++++++ .../ShimCometBroadcastHashJoinExec.scala | 39 ++++++ .../comet/shims/ShimCometScanExec.scala | 124 ++++++++++++++++++ .../shims/ShimCometShuffleExchangeExec.scala | 39 ++++++ .../ShimCometSparkSessionExtensions.scala | 67 ++++++++++ .../ShimCometTakeOrderedAndProjectExec.scala | 35 +++++ .../comet/shims/ShimQueryPlanSerde.scala | 70 ++++++++++ .../org/apache/comet/shims/ShimSQLConf.scala | 39 ++++++ 17 files changed, 667 insertions(+), 12 deletions(-) create mode 100644 common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala create mode 100644 common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala create mode 100644 common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala create mode 100644 spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBatchScanExec.scala create mode 100644 spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastExchangeExec.scala create mode 100644 spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala create mode 100644 spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala create mode 100644 spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala create mode 100644 spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala create mode 100644 spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala create mode 100644 spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala create mode 100644 spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala new file mode 100644 index 000000000..ece4cfbe5 --- /dev/null +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala @@ -0,0 +1,54 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.execution.datasources.PartitionedFile + +object ShimBatchReader { + + // TODO: remove after dropping Spark 3.2 & 3.3 support and directly call PartitionedFile + def newPartitionedFile(partitionValues: InternalRow, file: String): PartitionedFile = + classOf[PartitionedFile].getDeclaredConstructors + .map(c => + c.getParameterCount match { + case 5 => + c.newInstance( + partitionValues, + file, + Long.box(-1), // -1 means we read the entire file + Long.box(-1), + Array.empty[String]) + case 7 => + c.newInstance( + partitionValues, + c.getParameterTypes()(1) + .getConstructor(classOf[String]) + .newInstance(file) + .asInstanceOf[AnyRef], + Long.box(-1), // -1 means we read the entire file + Long.box(-1), + Array.empty[String], + Long.box(0), + Long.box(0)) + }) + .head + .asInstanceOf[PartitionedFile] +} diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala new file mode 100644 index 000000000..5ab7eaf4f --- /dev/null +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala @@ -0,0 +1,35 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +object ShimFileFormat { + + // TODO: remove after dropping Spark 3.2 & 3.3 support and directly use FileFormat.ROW_INDEX + val ROW_INDEX = "row_index" + + // A name for a temporary column that holds row indexes computed by the file format reader + // until they can be placed in the _metadata struct. + // TODO: remove after dropping Spark 3.2 & 3.3 support and directly use + // FileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME + val ROW_INDEX_TEMPORARY_COLUMN_NAME: String = s"_tmp_metadata_$ROW_INDEX" + + // TODO: remove after dropping Spark 3.2 support and use FileFormat.OPTION_RETURNING_BATCH + val OPTION_RETURNING_BATCH = "returning_batch" +} diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala new file mode 100644 index 000000000..8a30c8e00 --- /dev/null +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala @@ -0,0 +1,38 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import scala.util.Try + +import org.apache.spark.sql.types.{StructField, StructType} + +object ShimResolveDefaultColumns { + // TODO: remove after dropping Spark 3.2 & 3.3 support and directly use ResolveDefaultColumns + def getExistenceDefaultValue(field: StructField): Any = + Try { + // scalastyle:off classforname + Class.forName("org.apache.spark.sql.catalyst.util.ResolveDefaultColumns$") + // scalastyle:on classforname + }.map { objClass => + val objInstance = objClass.getField("MODULE$").get(null) + val method = objClass.getMethod("getExistenceDefaultValues", classOf[StructType]) + method.invoke(objInstance, StructType(Seq(field))).asInstanceOf[Array[Any]].head + }.getOrElse(null) +} diff --git a/pom.xml b/pom.xml index 6d28c8168..82cb01450 100644 --- a/pom.xml +++ b/pom.xml @@ -526,6 +526,23 @@ under the License. + + spark-4.0 + + + 2.13.13 + 2.13 + 4.0.0-SNAPSHOT + 4.0 + 1.13.1 + spark-4.0 + + 17 + ${java.version} + ${java.version} + + + scala-2.13 @@ -601,7 +618,7 @@ under the License. org.scalameta semanticdb-scalac_${scala.version} - 4.7.5 + 4.8.8 diff --git a/spark/src/main/scala/org/apache/comet/parquet/CometParquetFileFormat.scala b/spark/src/main/scala/org/apache/comet/parquet/CometParquetFileFormat.scala index ac871cf60..52d8d09a0 100644 --- a/spark/src/main/scala/org/apache/comet/parquet/CometParquetFileFormat.scala +++ b/spark/src/main/scala/org/apache/comet/parquet/CometParquetFileFormat.scala @@ -37,7 +37,6 @@ import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.datasources.parquet.ParquetReadSupport import org.apache.spark.sql.internal.SQLConf -import org.apache.spark.sql.internal.SQLConf.LegacyBehaviorPolicy import org.apache.spark.sql.sources.Filter import org.apache.spark.sql.types.{DateType, StructType, TimestampType} import org.apache.spark.util.SerializableConfiguration @@ -144,7 +143,7 @@ class CometParquetFileFormat extends ParquetFileFormat with MetricsSupport with isCaseSensitive, useFieldId, ignoreMissingIds, - datetimeRebaseSpec.mode == LegacyBehaviorPolicy.CORRECTED, + datetimeRebaseSpec.mode == CORRECTED, partitionSchema, file.partitionValues, JavaConverters.mapAsJavaMap(metrics)) @@ -161,7 +160,7 @@ class CometParquetFileFormat extends ParquetFileFormat with MetricsSupport with } } -object CometParquetFileFormat extends Logging { +object CometParquetFileFormat extends Logging with ShimSQLConf { /** * Populates Parquet related configurations from the input `sqlConf` to the `hadoopConf` @@ -210,7 +209,7 @@ object CometParquetFileFormat extends Logging { case _ => false }) - if (hasDateOrTimestamp && datetimeRebaseSpec.mode == LegacyBehaviorPolicy.LEGACY) { + if (hasDateOrTimestamp && datetimeRebaseSpec.mode == LEGACY) { if (exceptionOnRebase) { logWarning( s"""Found Parquet file $file that could potentially contain dates/timestamps that were @@ -222,7 +221,7 @@ object CometParquetFileFormat extends Logging { calendar, please disable Comet for this query.""") } else { // do not throw exception on rebase - read as it is - datetimeRebaseSpec = datetimeRebaseSpec.copy(LegacyBehaviorPolicy.CORRECTED) + datetimeRebaseSpec = datetimeRebaseSpec.copy(CORRECTED) } } diff --git a/spark/src/main/scala/org/apache/comet/parquet/CometParquetPartitionReaderFactory.scala b/spark/src/main/scala/org/apache/comet/parquet/CometParquetPartitionReaderFactory.scala index 693af125b..e48d76384 100644 --- a/spark/src/main/scala/org/apache/comet/parquet/CometParquetPartitionReaderFactory.scala +++ b/spark/src/main/scala/org/apache/comet/parquet/CometParquetPartitionReaderFactory.scala @@ -37,7 +37,6 @@ import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.datasources.v2.FilePartitionReaderFactory import org.apache.spark.sql.execution.metric.SQLMetric import org.apache.spark.sql.internal.SQLConf -import org.apache.spark.sql.internal.SQLConf.LegacyBehaviorPolicy import org.apache.spark.sql.sources.Filter import org.apache.spark.sql.types.StructType import org.apache.spark.sql.vectorized.ColumnarBatch @@ -135,7 +134,7 @@ case class CometParquetPartitionReaderFactory( isCaseSensitive, useFieldId, ignoreMissingIds, - datetimeRebaseSpec.mode == LegacyBehaviorPolicy.CORRECTED, + datetimeRebaseSpec.mode == CORRECTED, partitionSchema, file.partitionValues, JavaConverters.mapAsJavaMap(metrics)) diff --git a/spark/src/main/scala/org/apache/comet/parquet/ParquetFilters.scala b/spark/src/main/scala/org/apache/comet/parquet/ParquetFilters.scala index 5994dfb41..507369c9b 100644 --- a/spark/src/main/scala/org/apache/comet/parquet/ParquetFilters.scala +++ b/spark/src/main/scala/org/apache/comet/parquet/ParquetFilters.scala @@ -38,11 +38,11 @@ import org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName._ import org.apache.parquet.schema.Type.Repetition import org.apache.spark.sql.catalyst.util.{quoteIfNeeded, CaseInsensitiveMap, DateTimeUtils, IntervalUtils} import org.apache.spark.sql.catalyst.util.RebaseDateTime.{rebaseGregorianToJulianDays, rebaseGregorianToJulianMicros, RebaseSpec} -import org.apache.spark.sql.internal.SQLConf.LegacyBehaviorPolicy import org.apache.spark.sql.sources import org.apache.spark.unsafe.types.UTF8String import org.apache.comet.CometSparkSessionExtensions.isSpark34Plus +import org.apache.comet.shims.ShimSQLConf /** * Copied from Spark 3.2 & 3.4, in order to fix Parquet shading issue. TODO: find a way to remove @@ -58,7 +58,7 @@ class ParquetFilters( pushDownStringPredicate: Boolean, pushDownInFilterThreshold: Int, caseSensitive: Boolean, - datetimeRebaseSpec: RebaseSpec) { + datetimeRebaseSpec: RebaseSpec) extends ShimSQLConf { // A map which contains parquet field name and data type, if predicate push down applies. // // Each key in `nameToParquetField` represents a column; `dots` are used as separators for @@ -153,7 +153,7 @@ class ParquetFilters( case ld: LocalDate => DateTimeUtils.localDateToDays(ld) } datetimeRebaseSpec.mode match { - case LegacyBehaviorPolicy.LEGACY => rebaseGregorianToJulianDays(gregorianDays) + case LEGACY => rebaseGregorianToJulianDays(gregorianDays) case _ => gregorianDays } } @@ -164,7 +164,7 @@ class ParquetFilters( case t: Timestamp => DateTimeUtils.fromJavaTimestamp(t) } datetimeRebaseSpec.mode match { - case LegacyBehaviorPolicy.LEGACY => + case LEGACY => rebaseGregorianToJulianMicros(datetimeRebaseSpec.timeZone, gregorianMicros) case _ => gregorianMicros } diff --git a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimSQLConf.scala b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimSQLConf.scala index ff60ef964..c3d0c56e5 100644 --- a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimSQLConf.scala +++ b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimSQLConf.scala @@ -20,6 +20,7 @@ package org.apache.comet.shims import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.internal.SQLConf.LegacyBehaviorPolicy trait ShimSQLConf { @@ -39,4 +40,7 @@ trait ShimSQLConf { case _ => None }) .head + + protected val LEGACY = LegacyBehaviorPolicy.LEGACY + protected val CORRECTED = LegacyBehaviorPolicy.CORRECTED } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBatchScanExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBatchScanExec.scala new file mode 100644 index 000000000..9e7cc3ba5 --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBatchScanExec.scala @@ -0,0 +1,45 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import org.apache.spark.sql.catalyst.expressions.{Expression, SortOrder} +import org.apache.spark.sql.connector.read.InputPartition +import org.apache.spark.sql.execution.datasources.v2.BatchScanExec + +trait ShimCometBatchScanExec { + def wrapped: BatchScanExec + + // Only for Spark 3.3+ + def keyGroupedPartitioning: Option[Seq[Expression]] = wrapped.getClass.getDeclaredMethods + .filter(_.getName == "keyGroupedPartitioning") + .flatMap(_.invoke(wrapped).asInstanceOf[Option[Seq[Expression]]]) + .headOption + + // Only for Spark 3.3+ + def inputPartitions: Seq[InputPartition] = wrapped.getClass.getDeclaredMethods + .filter(_.getName == "inputPartitions") + .flatMap(_.invoke(wrapped).asInstanceOf[Seq[InputPartition]]) + + // Only for Spark 3.4+ + def ordering: Option[Seq[SortOrder]] = wrapped.getClass.getDeclaredMethods + .filter(_.getName == "ordering") + .flatMap(_.invoke(wrapped).asInstanceOf[Option[Seq[SortOrder]]]) + .headOption +} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastExchangeExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastExchangeExec.scala new file mode 100644 index 000000000..63ff2a2c1 --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastExchangeExec.scala @@ -0,0 +1,51 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import scala.reflect.ClassTag + +import org.apache.spark.SparkContext +import org.apache.spark.broadcast.Broadcast + +trait ShimCometBroadcastExchangeExec { + // TODO: remove after dropping Spark 3.2 and 3.3 support + protected def doBroadcast[T: ClassTag](sparkContext: SparkContext, value: T): Broadcast[Any] = { + // Spark 3.4 has new API `broadcastInternal` to broadcast the relation without caching the + // unserialized object. + val classTag = implicitly[ClassTag[T]] + val broadcasted = sparkContext.getClass.getDeclaredMethods + .filter(_.getName == "broadcastInternal") + .map { a => a.setAccessible(true); a } + .map { method => + method + .invoke( + sparkContext.asInstanceOf[Object], + value.asInstanceOf[Object], + true.asInstanceOf[Object], + classTag.asInstanceOf[Object]) + .asInstanceOf[Broadcast[Any]] + } + .headOption + // Fallback to the old API if the new API is not available. + broadcasted + .getOrElse(sparkContext.broadcast(value.asInstanceOf[Object])) + .asInstanceOf[Broadcast[Any]] + } +} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala new file mode 100644 index 000000000..eef0ee9d5 --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala @@ -0,0 +1,39 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import org.apache.spark.sql.catalyst.expressions.Expression +import org.apache.spark.sql.catalyst.plans.physical.Partitioning + +trait ShimCometBroadcastHashJoinExec { + + /** + * Returns the expressions that are used for hash partitioning including `HashPartitioning` and + * `CoalescedHashPartitioning`. They shares same trait `HashPartitioningLike` since Spark 3.4, + * but Spark 3.2/3.3 doesn't have `HashPartitioningLike` and `CoalescedHashPartitioning`. + * + * TODO: remove after dropping Spark 3.2 and 3.3 support. + */ + def getHashPartitioningLikeExpressions(partitioning: Partitioning): Seq[Expression] = { + partitioning.getClass.getDeclaredMethods + .filter(_.getName == "expressions") + .flatMap(_.invoke(partitioning).asInstanceOf[Seq[Expression]]) + } +} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala new file mode 100644 index 000000000..18871b814 --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala @@ -0,0 +1,124 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import scala.language.implicitConversions + +import org.apache.spark.{SparkContext, SparkException} +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.expressions.AttributeReference +import org.apache.spark.sql.connector.read.{InputPartition, PartitionReaderFactory} +import org.apache.spark.sql.execution.FileSourceScanExec +import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile} +import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions +import org.apache.spark.sql.execution.datasources.v2.DataSourceRDD +import org.apache.spark.sql.execution.metric.SQLMetric +import org.apache.spark.sql.types.{LongType, StructField, StructType} + +trait ShimCometScanExec { + def wrapped: FileSourceScanExec + + // TODO: remove after dropping Spark 3.2 support and directly call wrapped.metadataColumns + lazy val metadataColumns: Seq[AttributeReference] = wrapped.getClass.getDeclaredMethods + .filter(_.getName == "metadataColumns") + .map { a => a.setAccessible(true); a } + .flatMap(_.invoke(wrapped).asInstanceOf[Seq[AttributeReference]]) + + // TODO: remove after dropping Spark 3.2 and 3.3 support and directly call + // wrapped.fileConstantMetadataColumns + lazy val fileConstantMetadataColumns: Seq[AttributeReference] = + wrapped.getClass.getDeclaredMethods + .filter(_.getName == "fileConstantMetadataColumns") + .map { a => a.setAccessible(true); a } + .flatMap(_.invoke(wrapped).asInstanceOf[Seq[AttributeReference]]) + + // TODO: remove after dropping Spark 3.2 support and directly call new DataSourceRDD + protected def newDataSourceRDD( + sc: SparkContext, + inputPartitions: Seq[Seq[InputPartition]], + partitionReaderFactory: PartitionReaderFactory, + columnarReads: Boolean, + customMetrics: Map[String, SQLMetric]): DataSourceRDD = { + implicit def flattenSeq(p: Seq[Seq[InputPartition]]): Seq[InputPartition] = p.flatten + new DataSourceRDD(sc, inputPartitions, partitionReaderFactory, columnarReads, customMetrics) + } + + // TODO: remove after dropping Spark 3.2 support and directly call new FileScanRDD + protected def newFileScanRDD( + sparkSession: SparkSession, + readFunction: PartitionedFile => Iterator[InternalRow], + filePartitions: Seq[FilePartition], + readSchema: StructType, + options: ParquetOptions): FileScanRDD = + classOf[FileScanRDD].getDeclaredConstructors + .map { c => + c.getParameterCount match { + case 3 => c.newInstance(sparkSession, readFunction, filePartitions) + case 5 => + c.newInstance(sparkSession, readFunction, filePartitions, readSchema, metadataColumns) + case 6 => + c.newInstance( + sparkSession, + readFunction, + filePartitions, + readSchema, + fileConstantMetadataColumns, + options) + } + } + .last + .asInstanceOf[FileScanRDD] + + // TODO: remove after dropping Spark 3.2 and 3.3 support and directly call + // QueryExecutionErrors.SparkException + protected def invalidBucketFile(path: String, sparkVersion: String): Throwable = { + if (sparkVersion >= "3.3") { + val messageParameters = if (sparkVersion >= "3.4") Map("path" -> path) else Array(path) + classOf[SparkException].getDeclaredConstructors + .filter(_.getParameterCount == 3) + .map(_.newInstance("INVALID_BUCKET_FILE", messageParameters, null)) + .last + .asInstanceOf[SparkException] + } else { // Spark 3.2 + new IllegalStateException(s"Invalid bucket file ${path}") + } + } + + // Copied from Spark 3.4 RowIndexUtil due to PARQUET-2161 (tracked in SPARK-39634) + // TODO: remove after PARQUET-2161 becomes available in Parquet + private def findRowIndexColumnIndexInSchema(sparkSchema: StructType): Int = { + sparkSchema.fields.zipWithIndex.find { case (field: StructField, _: Int) => + field.name == ShimFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME + } match { + case Some((field: StructField, idx: Int)) => + if (field.dataType != LongType) { + throw new RuntimeException( + s"${ShimFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME} must be of LongType") + } + idx + case _ => -1 + } + } + + protected def isNeededForSchema(sparkSchema: StructType): Boolean = { + findRowIndexColumnIndexInSchema(sparkSchema) >= 0 + } +} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala new file mode 100644 index 000000000..f89dbb8db --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala @@ -0,0 +1,39 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import org.apache.spark.sql.comet.execution.shuffle.{CometShuffleExchangeExec, ShuffleType} +import org.apache.spark.sql.execution.exchange.ShuffleExchangeExec + +trait ShimCometShuffleExchangeExec { + // TODO: remove after dropping Spark 3.2 and 3.3 support + def apply(s: ShuffleExchangeExec, shuffleType: ShuffleType): CometShuffleExchangeExec = { + val advisoryPartitionSize = s.getClass.getDeclaredMethods + .filter(_.getName == "advisoryPartitionSize") + .flatMap(_.invoke(s).asInstanceOf[Option[Long]]) + .headOption + CometShuffleExchangeExec( + s.outputPartitioning, + s.child, + s.shuffleOrigin, + shuffleType, + advisoryPartitionSize) + } +} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala new file mode 100644 index 000000000..ffec1bd40 --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala @@ -0,0 +1,67 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import org.apache.spark.sql.connector.expressions.aggregate.Aggregation +import org.apache.spark.sql.execution.{LimitExec, QueryExecution, SparkPlan} +import org.apache.spark.sql.execution.datasources.v2.parquet.ParquetScan + +trait ShimCometSparkSessionExtensions { + import org.apache.comet.shims.ShimCometSparkSessionExtensions._ + + /** + * TODO: delete after dropping Spark 3.2.0 support and directly call scan.pushedAggregate + */ + def getPushedAggregate(scan: ParquetScan): Option[Aggregation] = scan.getClass.getDeclaredFields + .filter(_.getName == "pushedAggregate") + .map { a => a.setAccessible(true); a } + .flatMap(_.get(scan).asInstanceOf[Option[Aggregation]]) + .headOption + + /** + * TODO: delete after dropping Spark 3.2 and 3.3 support + */ + def getOffset(limit: LimitExec): Int = getOffsetOpt(limit).getOrElse(0) + +} + +object ShimCometSparkSessionExtensions { + private def getOffsetOpt(plan: SparkPlan): Option[Int] = plan.getClass.getDeclaredFields + .filter(_.getName == "offset") + .map { a => a.setAccessible(true); a.get(plan) } + .filter(_.isInstanceOf[Int]) + .map(_.asInstanceOf[Int]) + .headOption + + // Extended info is available only since Spark 4.0.0 + // (https://issues.apache.org/jira/browse/SPARK-47289) + def supportsExtendedExplainInfo(qe: QueryExecution): Boolean = { + try { + // Look for QueryExecution.extendedExplainInfo(scala.Function1[String, Unit], SparkPlan) + qe.getClass.getDeclaredMethod( + "extendedExplainInfo", + classOf[String => Unit], + classOf[SparkPlan]) + } catch { + case _: NoSuchMethodException | _: SecurityException => return false + } + true + } +} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala new file mode 100644 index 000000000..2e1c681c7 --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala @@ -0,0 +1,35 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import org.apache.spark.sql.execution.TakeOrderedAndProjectExec + +trait ShimCometTakeOrderedAndProjectExec { + + /** + * TODO: delete after dropping Spark 3.2 and 3.3 support + */ + protected def getOffset(plan: TakeOrderedAndProjectExec): Option[Int] = { + plan.getClass.getDeclaredFields + .filter(_.getName == "offset") + .map { a => a.setAccessible(true); a.get(plan).asInstanceOf[Int] } + .headOption + } +} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala new file mode 100644 index 000000000..b92d3fc6a --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala @@ -0,0 +1,70 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import org.apache.spark.sql.catalyst.expressions.{BinaryArithmetic, BinaryExpression} +import org.apache.spark.sql.catalyst.expressions.aggregate.DeclarativeAggregate + +trait ShimQueryPlanSerde { + def getFailOnError(b: BinaryArithmetic): Boolean = + b.getClass.getMethod("failOnError").invoke(b).asInstanceOf[Boolean] + + def getFailOnError(aggregate: DeclarativeAggregate): Boolean = { + val failOnError = aggregate.getClass.getDeclaredMethods.flatMap(m => + m.getName match { + case "failOnError" | "useAnsiAdd" => Some(m.invoke(aggregate).asInstanceOf[Boolean]) + case _ => None + }) + if (failOnError.isEmpty) { + aggregate.getClass.getDeclaredMethods + .flatMap(m => + m.getName match { + case "initQueryContext" => Some(m.invoke(aggregate).asInstanceOf[Option[_]].isDefined) + case _ => None + }) + .head + } else { + failOnError.head + } + } + + // TODO: delete after drop Spark 3.2/3.3 support + // This method is used to check if the aggregate function is in legacy mode. + // EvalMode is an enum object in Spark 3.4. + def isLegacyMode(aggregate: DeclarativeAggregate): Boolean = { + val evalMode = aggregate.getClass.getDeclaredMethods + .flatMap(m => + m.getName match { + case "evalMode" => Some(m.invoke(aggregate)) + case _ => None + }) + + if (evalMode.isEmpty) { + true + } else { + "legacy".equalsIgnoreCase(evalMode.head.toString) + } + } + + // TODO: delete after drop Spark 3.2 support + def isBloomFilterMightContain(binary: BinaryExpression): Boolean = { + binary.getClass.getName == "org.apache.spark.sql.catalyst.expressions.BloomFilterMightContain" + } +} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala new file mode 100644 index 000000000..ef337a0da --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala @@ -0,0 +1,39 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.internal.LegacyBehaviorPolicy + +trait ShimSQLConf { + + /** + * Spark 3.4 renamed parquetFilterPushDownStringStartWith to + * parquetFilterPushDownStringPredicate + * + * TODO: delete after dropping Spark 3.2 & 3.3 support and simply use + * parquetFilterPushDownStringPredicate + */ + protected def getPushDownStringPredicate(sqlConf: SQLConf): Boolean = + sqlConf.parquetFilterPushDownStringPredicate + + protected val LEGACY = LegacyBehaviorPolicy.LEGACY + protected val CORRECTED = LegacyBehaviorPolicy.CORRECTED +} From 465b828fd11db9424cf9a84428d62dd73739cdc1 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 1 May 2024 11:53:10 -0700 Subject: [PATCH 02/68] build: Add spark-4.0 profile --- pom.xml | 1 + .../apache/comet/serde/QueryPlanSerde.scala | 22 +++++++++---------- .../main/scala/org/apache/spark/Plugins.scala | 12 ++++++---- .../spark/sql/comet/CometScanExec.scala | 4 ++-- .../spark/sql/comet/DecimalPrecision.scala | 9 ++++---- .../shuffle/CometShuffleExchangeExec.scala | 4 ++-- .../comet/shims/ShimCometScanExec.scala | 17 ++++++++++++-- .../shims/ShimCometShuffleExchangeExec.scala | 6 +++++ .../comet/shims/ShimCometScanExec.scala | 17 ++++++++++++-- .../shims/ShimCometShuffleExchangeExec.scala | 5 +++++ 10 files changed, 69 insertions(+), 28 deletions(-) diff --git a/pom.xml b/pom.xml index 82cb01450..874d2d72d 100644 --- a/pom.xml +++ b/pom.xml @@ -527,6 +527,7 @@ under the License. + spark-4.0 diff --git a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala index e1e7a7117..66b40ddb5 100644 --- a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala +++ b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala @@ -1884,18 +1884,16 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde { // With Spark 3.4, CharVarcharCodegenUtils.readSidePadding gets called to pad spaces for // char types. Use rpad to achieve the behavior. // See https://github.com/apache/spark/pull/38151 - case StaticInvoke( - _: Class[CharVarcharCodegenUtils], - _: StringType, - "readSidePadding", - arguments, - _, - true, - false, - true) if arguments.size == 2 => + case s: StaticInvoke if s.staticObject.isInstanceOf[Class[CharVarcharCodegenUtils]] && + s.dataType.isInstanceOf[StringType] && + s.functionName == "readSidePadding" && + s.arguments.size == 2 && + s.propagateNull && + !s.returnNullable && + s.isDeterministic => val argsExpr = Seq( - exprToProtoInternal(Cast(arguments(0), StringType), inputs), - exprToProtoInternal(arguments(1), inputs)) + exprToProtoInternal(Cast(s.arguments(0), StringType), inputs), + exprToProtoInternal(s.arguments(1), inputs)) if (argsExpr.forall(_.isDefined)) { val builder = ExprOuterClass.ScalarFunc.newBuilder() @@ -1904,7 +1902,7 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde { Some(ExprOuterClass.Expr.newBuilder().setScalarFunc(builder).build()) } else { - withInfo(expr, arguments: _*) + withInfo(expr, s.arguments: _*) None } diff --git a/spark/src/main/scala/org/apache/spark/Plugins.scala b/spark/src/main/scala/org/apache/spark/Plugins.scala index 97838448a..301281db5 100644 --- a/spark/src/main/scala/org/apache/spark/Plugins.scala +++ b/spark/src/main/scala/org/apache/spark/Plugins.scala @@ -25,7 +25,6 @@ import java.util.Collections import org.apache.spark.api.plugin.{DriverPlugin, ExecutorPlugin, PluginContext, SparkPlugin} import org.apache.spark.internal.Logging import org.apache.spark.internal.config.{EXECUTOR_MEMORY, EXECUTOR_MEMORY_OVERHEAD} -import org.apache.spark.resource.ResourceProfile import org.apache.comet.{CometConf, CometSparkSessionExtensions} @@ -56,10 +55,12 @@ class CometDriverPlugin extends DriverPlugin with Logging { sc.getConf.getDouble( EXECUTOR_MEMORY_OVERHEAD_FACTOR, EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT) + val memoryOverheadMinMib = + sc.getConf.getLong( + EXECUTOR_MIN_MEMORY_OVERHEAD, + EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT) - Math.max( - (executorMemory * memoryOverheadFactor).toInt, - ResourceProfile.MEMORY_OVERHEAD_MIN_MIB) + Math.max((executorMemory * memoryOverheadFactor).toLong, memoryOverheadMinMib) } val cometMemOverhead = CometSparkSessionExtensions.getCometMemoryOverheadInMiB(sc.getConf) @@ -104,6 +105,9 @@ object CometDriverPlugin { // `org.apache.spark.internal.config.EXECUTOR_MEMORY_OVERHEAD_FACTOR` was added since Spark 3.3.0 val EXECUTOR_MEMORY_OVERHEAD_FACTOR = "spark.executor.memoryOverheadFactor" val EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT = 0.1 + // `org.apache.spark.internal.config.EXECUTOR_MIN_MEMORY_OVERHEAD` was added since Spark 4.0.0 + val EXECUTOR_MIN_MEMORY_OVERHEAD = "spark.executor.minMemoryOverhead" + val EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT = 384L } /** diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala b/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala index 42cc96bf5..d2b844985 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala @@ -268,7 +268,7 @@ case class CometScanExec( selectedPartitions .flatMap { p => p.files.map { f => - PartitionedFileUtil.getPartitionedFile(f, f.getPath, p.values) + getPartitionedFile(f, p) } } .groupBy { f => @@ -355,7 +355,7 @@ case class CometScanExec( // SPARK-39634: Allow file splitting in combination with row index generation once // the fix for PARQUET-2161 is available. !isNeededForSchema(requiredSchema) - PartitionedFileUtil.splitFiles( + super.splitFiles( sparkSession = relation.sparkSession, file = file, filePath = filePath, diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala b/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala index 13f26ce58..6e5dde9c7 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala @@ -59,7 +59,7 @@ object DecimalPrecision { } CheckOverflow(add, resultType, nullOnOverflow) - case sub @ Subtract(DecimalType.Expression(p1, s1), DecimalType.Expression(p2, s2), _) => + case sub @ Subtract(DecimalExpression(p1, s1), DecimalExpression(p2, s2), _) => val resultScale = max(s1, s2) val resultType = if (allowPrecisionLoss) { DecimalType.adjustPrecisionScale(max(p1 - s1, p2 - s2) + resultScale + 1, resultScale) @@ -68,7 +68,7 @@ object DecimalPrecision { } CheckOverflow(sub, resultType, nullOnOverflow) - case mul @ Multiply(DecimalType.Expression(p1, s1), DecimalType.Expression(p2, s2), _) => + case mul @ Multiply(DecimalExpression(p1, s1), DecimalExpression(p2, s2), _) => val resultType = if (allowPrecisionLoss) { DecimalType.adjustPrecisionScale(p1 + p2 + 1, s1 + s2) } else { @@ -76,7 +76,7 @@ object DecimalPrecision { } CheckOverflow(mul, resultType, nullOnOverflow) - case div @ Divide(DecimalType.Expression(p1, s1), DecimalType.Expression(p2, s2), _) => + case div @ Divide(DecimalExpression(p1, s1), DecimalExpression(p2, s2), _) => val resultType = if (allowPrecisionLoss) { // Precision: p1 - s1 + s2 + max(6, s1 + p2 + 1) // Scale: max(6, s1 + p2 + 1) @@ -96,7 +96,7 @@ object DecimalPrecision { } CheckOverflow(div, resultType, nullOnOverflow) - case rem @ Remainder(DecimalType.Expression(p1, s1), DecimalType.Expression(p2, s2), _) => + case rem @ Remainder(DecimalExpression(p1, s1), DecimalExpression(p2, s2), _) => val resultType = if (allowPrecisionLoss) { DecimalType.adjustPrecisionScale(min(p1 - s1, p2 - s2) + max(s1, s2), max(s1, s2)) } else { @@ -108,6 +108,7 @@ object DecimalPrecision { } } + // `org.apache.spark.sql.types.DecimalExpression` is added in Spark 3.5 object DecimalExpression { def unapply(e: Expression): Option[(Int, Int)] = e.dataType match { case t: DecimalType => Some((t.precision, t.scale)) diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala b/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala index 232b6bf17..dd99be78a 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala @@ -365,7 +365,7 @@ object CometShuffleExchangeExec extends ShimCometShuffleExchangeExec { val pageSize = SparkEnv.get.memoryManager.pageSizeBytes val sorter = UnsafeExternalRowSorter.createWithRecordComparator( - StructType.fromAttributes(outputAttributes), + fromAttributes(outputAttributes), recordComparatorSupplier, prefixComparator, prefixComputer, @@ -409,7 +409,7 @@ object CometShuffleExchangeExec extends ShimCometShuffleExchangeExec { serializer, shuffleWriterProcessor = ShuffleExchangeExec.createShuffleWriteProcessor(writeMetrics), shuffleType = CometColumnarShuffle, - schema = Some(StructType.fromAttributes(outputAttributes))) + schema = Some(fromAttributes(outputAttributes))) dependency } diff --git a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometScanExec.scala index 18871b814..c2d775889 100644 --- a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometScanExec.scala @@ -21,13 +21,15 @@ package org.apache.comet.shims import scala.language.implicitConversions +import org.apache.hadoop.fs.Path + import org.apache.spark.{SparkContext, SparkException} import org.apache.spark.sql.SparkSession import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.AttributeReference import org.apache.spark.sql.connector.read.{InputPartition, PartitionReaderFactory} -import org.apache.spark.sql.execution.FileSourceScanExec -import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile} +import org.apache.spark.sql.execution.{FileSourceScanExec, PartitionedFileUtil} +import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, FileStatusWithMetadata, PartitionDirectory, PartitionedFile} import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.datasources.v2.DataSourceRDD import org.apache.spark.sql.execution.metric.SQLMetric @@ -121,4 +123,15 @@ trait ShimCometScanExec { protected def isNeededForSchema(sparkSchema: StructType): Boolean = { findRowIndexColumnIndexInSchema(sparkSchema) >= 0 } + + protected def getPartitionedFile(f: FileStatusWithMetadata, p: PartitionDirectory): PartitionedFile = + PartitionedFileUtil.getPartitionedFile(f, f.getPath, p.values) + + protected def splitFiles(sparkSession: SparkSession, + file: FileStatus, + filePath: Path, + isSplitable: Boolean, + maxSplitBytes: Long, + partitionValues: InternalRow): Seq[PartitionedFile] = + PartitionedFileUtil.splitFiles(sparkSession, file, filePath, isSplitable, maxSplitBytes, partitionValues) } diff --git a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala index f89dbb8db..e8acc998e 100644 --- a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala +++ b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala @@ -19,8 +19,10 @@ package org.apache.comet.shims +import org.apache.spark.sql.catalyst.expressions.Attribute import org.apache.spark.sql.comet.execution.shuffle.{CometShuffleExchangeExec, ShuffleType} import org.apache.spark.sql.execution.exchange.ShuffleExchangeExec +import org.apache.spark.sql.types.StructType trait ShimCometShuffleExchangeExec { // TODO: remove after dropping Spark 3.2 and 3.3 support @@ -36,4 +38,8 @@ trait ShimCometShuffleExchangeExec { shuffleType, advisoryPartitionSize) } + + // TODO: remove after dropping Spark 3.x support + protected def fromAttributes(attributes: Seq[Attribute]): StructType = + StructType(attributes.map(a => StructField(a.name, a.dataType, a.nullable, a.metadata))) } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala index 18871b814..bee0527db 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala @@ -21,13 +21,15 @@ package org.apache.comet.shims import scala.language.implicitConversions +import org.apache.hadoop.fs.Path + import org.apache.spark.{SparkContext, SparkException} import org.apache.spark.sql.SparkSession import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.AttributeReference import org.apache.spark.sql.connector.read.{InputPartition, PartitionReaderFactory} -import org.apache.spark.sql.execution.FileSourceScanExec -import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile} +import org.apache.spark.sql.execution.{FileSourceScanExec, PartitionedFileUtil} +import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, FileStatusWithMetadata, PartitionDirectory, PartitionedFile} import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.datasources.v2.DataSourceRDD import org.apache.spark.sql.execution.metric.SQLMetric @@ -121,4 +123,15 @@ trait ShimCometScanExec { protected def isNeededForSchema(sparkSchema: StructType): Boolean = { findRowIndexColumnIndexInSchema(sparkSchema) >= 0 } + + protected def getPartitionedFile(f: FileStatusWithMetadata, p: PartitionDirectory): PartitionedFile = + PartitionedFileUtil.getPartitionedFile(f, p.values, 0, f.getLen) + + protected def splitFiles(sparkSession: SparkSession, + file: FileStatusWithMetadata, + filePath: Path, + isSplitable: Boolean, + maxSplitBytes: Long, + partitionValues: InternalRow): Seq[PartitionedFile] = + PartitionedFileUtil.splitFiles(file, isSplitable, maxSplitBytes, partitionValues) } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala index f89dbb8db..26f3d25e5 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala @@ -19,8 +19,11 @@ package org.apache.comet.shims +import org.apache.spark.sql.catalyst.expressions.Attribute +import org.apache.spark.sql.catalyst.types.DataTypeUtils import org.apache.spark.sql.comet.execution.shuffle.{CometShuffleExchangeExec, ShuffleType} import org.apache.spark.sql.execution.exchange.ShuffleExchangeExec +import org.apache.spark.sql.types.StructType trait ShimCometShuffleExchangeExec { // TODO: remove after dropping Spark 3.2 and 3.3 support @@ -36,4 +39,6 @@ trait ShimCometShuffleExchangeExec { shuffleType, advisoryPartitionSize) } + + protected def fromAttributes(attributes: Seq[Attribute]): StructType = DataTypeUtils.fromAttributes(attributes) } From 62b7d2f6b918fcf340be5742c35b7d37740c1a5f Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Mon, 6 May 2024 18:56:34 -0700 Subject: [PATCH 03/68] build: Add spark-4.0 profile --- pom.xml | 9 -- spark/pom.xml | 1 + .../apache/comet/parquet/ParquetFilters.scala | 3 +- .../apache/comet/serde/QueryPlanSerde.scala | 15 +-- .../main/scala/org/apache/spark/Plugins.scala | 4 +- .../shuffle/CometShuffleExchangeExec.scala | 33 ++++-- .../shims/ShimCometShuffleExchangeExec.scala | 3 + .../shims/ShimCometShuffleExchangeExec.scala | 3 + .../exec/CometColumnarShuffleSuite.scala | 2 +- .../spark/sql/CometTPCDSQuerySuite.scala | 2 +- .../spark/sql/CometTPCHQuerySuite.scala | 5 +- .../comet/shims/ShimCometTPCHQuerySuite.scala | 9 ++ .../comet/CometExpression3_3PlusSuite.scala | 0 .../comet/shims/ShimCometTPCHQuerySuite.scala | 9 ++ .../comet/CometExpression3_3PlusSuite.scala | 106 ++++++++++++++++++ .../comet/shims/ShimCometTPCHQuerySuite.scala | 9 ++ .../comet/CometExpression3_3PlusSuite.scala | 106 ++++++++++++++++++ .../apache/comet/exec/CometExec3_4Suite.scala | 52 +++++++++ .../comet/shims/ShimCometTPCHQuerySuite.scala | 6 + 19 files changed, 343 insertions(+), 34 deletions(-) create mode 100644 spark/src/test/spark-3.2/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala rename spark/src/test/{spark-3.3-plus => spark-3.3}/org/apache/comet/CometExpression3_3PlusSuite.scala (100%) create mode 100644 spark/src/test/spark-3.3/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala create mode 100644 spark/src/test/spark-3.4/org/apache/comet/CometExpression3_3PlusSuite.scala create mode 100644 spark/src/test/spark-3.4/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala create mode 100644 spark/src/test/spark-4.0/org/apache/comet/CometExpression3_3PlusSuite.scala create mode 100644 spark/src/test/spark-4.0/org/apache/comet/exec/CometExec3_4Suite.scala create mode 100644 spark/src/test/spark-4.0/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala diff --git a/pom.xml b/pom.xml index 874d2d72d..a91056b59 100644 --- a/pom.xml +++ b/pom.xml @@ -86,8 +86,6 @@ under the License. -Djdk.reflect.useDirectMethodHandle=false -ea -Xmx4g -Xss4m ${extraJavaTestArgs} - spark-3.3-plus - spark-3.4 spark-3.x @@ -497,9 +495,6 @@ under the License. 3.2.2 3.2 1.12.0 - - not-needed-yet - not-needed-yet @@ -510,8 +505,6 @@ under the License. 3.3.2 3.3 1.12.0 - spark-3.3-plus - not-needed-yet @@ -521,8 +514,6 @@ under the License. 2.12.17 3.4 1.13.1 - spark-3.3-plus - spark-3.4 diff --git a/spark/pom.xml b/spark/pom.xml index 9392b7fe9..f5cd194d7 100644 --- a/spark/pom.xml +++ b/spark/pom.xml @@ -247,6 +247,7 @@ under the License. src/test/${additional.3_3.test.source} src/test/${additional.3_4.test.source} + src/test/${shims.source} diff --git a/spark/src/main/scala/org/apache/comet/parquet/ParquetFilters.scala b/spark/src/main/scala/org/apache/comet/parquet/ParquetFilters.scala index 507369c9b..58c2aeb41 100644 --- a/spark/src/main/scala/org/apache/comet/parquet/ParquetFilters.scala +++ b/spark/src/main/scala/org/apache/comet/parquet/ParquetFilters.scala @@ -58,7 +58,8 @@ class ParquetFilters( pushDownStringPredicate: Boolean, pushDownInFilterThreshold: Int, caseSensitive: Boolean, - datetimeRebaseSpec: RebaseSpec) extends ShimSQLConf { + datetimeRebaseSpec: RebaseSpec) + extends ShimSQLConf { // A map which contains parquet field name and data type, if predicate push down applies. // // Each key in `nameToParquetField` represents a column; `dots` are used as separators for diff --git a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala index 66b40ddb5..2495679d9 100644 --- a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala +++ b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala @@ -1884,13 +1884,14 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde { // With Spark 3.4, CharVarcharCodegenUtils.readSidePadding gets called to pad spaces for // char types. Use rpad to achieve the behavior. // See https://github.com/apache/spark/pull/38151 - case s: StaticInvoke if s.staticObject.isInstanceOf[Class[CharVarcharCodegenUtils]] && - s.dataType.isInstanceOf[StringType] && - s.functionName == "readSidePadding" && - s.arguments.size == 2 && - s.propagateNull && - !s.returnNullable && - s.isDeterministic => + case s: StaticInvoke + if s.staticObject.isInstanceOf[Class[CharVarcharCodegenUtils]] && + s.dataType.isInstanceOf[StringType] && + s.functionName == "readSidePadding" && + s.arguments.size == 2 && + s.propagateNull && + !s.returnNullable && + s.isDeterministic => val argsExpr = Seq( exprToProtoInternal(Cast(s.arguments(0), StringType), inputs), exprToProtoInternal(s.arguments(1), inputs)) diff --git a/spark/src/main/scala/org/apache/spark/Plugins.scala b/spark/src/main/scala/org/apache/spark/Plugins.scala index 301281db5..acfa313f9 100644 --- a/spark/src/main/scala/org/apache/spark/Plugins.scala +++ b/spark/src/main/scala/org/apache/spark/Plugins.scala @@ -56,9 +56,7 @@ class CometDriverPlugin extends DriverPlugin with Logging { EXECUTOR_MEMORY_OVERHEAD_FACTOR, EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT) val memoryOverheadMinMib = - sc.getConf.getLong( - EXECUTOR_MIN_MEMORY_OVERHEAD, - EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT) + sc.getConf.getLong(EXECUTOR_MIN_MEMORY_OVERHEAD, EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT) Math.max((executorMemory * memoryOverheadFactor).toLong, memoryOverheadMinMib) } diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala b/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala index dd99be78a..7896e166d 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala @@ -44,7 +44,6 @@ import org.apache.spark.sql.execution.exchange.{ENSURE_REQUIREMENTS, ShuffleExch import org.apache.spark.sql.execution.exchange.ShuffleExchangeExec import org.apache.spark.sql.execution.metric.{SQLMetric, SQLMetrics, SQLShuffleReadMetricsReporter, SQLShuffleWriteMetricsReporter} import org.apache.spark.sql.internal.SQLConf -import org.apache.spark.sql.types.StructType import org.apache.spark.sql.vectorized.ColumnarBatch import org.apache.spark.util.MutablePair import org.apache.spark.util.collection.unsafe.sort.{PrefixComparators, RecordComparator} @@ -65,7 +64,8 @@ case class CometShuffleExchangeExec( shuffleType: ShuffleType = CometNativeShuffle, advisoryPartitionSize: Option[Long] = None) extends ShuffleExchangeLike - with CometPlan { + with CometPlan + with ShimCometShuffleExchangeExec { private lazy val writeMetrics = SQLShuffleWriteMetricsReporter.createShuffleWriteMetrics(sparkContext) @@ -124,6 +124,9 @@ case class CometShuffleExchangeExec( Statistics(dataSize, Some(rowCount)) } + // TODO: add `override` keyword after dropping Spark-3.x supports + def shuffleId: Int = getShuffleId(shuffleDependency) + /** * A [[ShuffleDependency]] that will partition rows of its child based on the partitioning * scheme defined in `newPartitioning`. Those partitions of the returned ShuffleDependency will @@ -313,7 +316,7 @@ object CometShuffleExchangeExec extends ShimCometShuffleExchangeExec { // seed by hashing will help. Refer to SPARK-21782 for more details. val partitionId = TaskContext.get().partitionId() var position = new XORShiftRandom(partitionId).nextInt(numPartitions) - (row: InternalRow) => { + (_: InternalRow) => { // The HashPartitioner will handle the `mod` by the number of partitions position += 1 position @@ -433,12 +436,27 @@ class CometShuffleWriteProcessor( new SQLShuffleWriteMetricsReporter(context.taskMetrics().shuffleWriteMetrics, metrics) } - override def write( + // For Spark-3.x + def write( rdd: RDD[_], dep: ShuffleDependency[_, _, _], mapId: Long, context: TaskContext, partition: Partition): MapStatus = { + // Getting rid of the fake partitionId + val cometRDD = rdd.asInstanceOf[MapPartitionsRDD[_, _]].prev.asInstanceOf[RDD[ColumnarBatch]] + val rawIter = cometRDD.iterator(partition, context) + write(rawIter, dep, mapId, partition.index, context) + } + + // TODO: add `override` keyword after dropping Spark-3.x supports + // FIXME: we need actually prev of rdd? + def write( + inputs: Iterator[ColumnarBatch], + dep: ShuffleDependency[_, _, _], + mapId: Long, + mapIndex: Int, + context: TaskContext): MapStatus = { val shuffleBlockResolver = SparkEnv.get.shuffleManager.shuffleBlockResolver.asInstanceOf[IndexShuffleBlockResolver] val dataFile = shuffleBlockResolver.getDataFile(dep.shuffleId, mapId) @@ -448,10 +466,6 @@ class CometShuffleWriteProcessor( val tempDataFilePath = Paths.get(tempDataFilename) val tempIndexFilePath = Paths.get(tempIndexFilename) - // Getting rid of the fake partitionId - val cometRDD = - rdd.asInstanceOf[MapPartitionsRDD[_, _]].prev.asInstanceOf[RDD[ColumnarBatch]] - // Call native shuffle write val nativePlan = getNativePlan(tempDataFilename, tempIndexFilename) @@ -461,8 +475,7 @@ class CometShuffleWriteProcessor( "elapsed_compute" -> metrics("shuffleReadElapsedCompute")) val nativeMetrics = CometMetricNode(nativeSQLMetrics) - val rawIter = cometRDD.iterator(partition, context) - val cometIter = CometExec.getCometIterator(Seq(rawIter), nativePlan, nativeMetrics) + val cometIter = CometExec.getCometIterator(Seq(inputs), nativePlan, nativeMetrics) while (cometIter.hasNext) { cometIter.next() diff --git a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala index e8acc998e..d45e0cd5b 100644 --- a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala +++ b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala @@ -42,4 +42,7 @@ trait ShimCometShuffleExchangeExec { // TODO: remove after dropping Spark 3.x support protected def fromAttributes(attributes: Seq[Attribute]): StructType = StructType(attributes.map(a => StructField(a.name, a.dataType, a.nullable, a.metadata))) + + // TODO: remove after dropping Spark 3.x support + protected def getShuffleId(shuffleDependency: ShuffleDependency[Int, _, _]): Int = 0 } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala index 26f3d25e5..826209337 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala @@ -19,6 +19,7 @@ package org.apache.comet.shims +import org.apache.spark.ShuffleDependency import org.apache.spark.sql.catalyst.expressions.Attribute import org.apache.spark.sql.catalyst.types.DataTypeUtils import org.apache.spark.sql.comet.execution.shuffle.{CometShuffleExchangeExec, ShuffleType} @@ -41,4 +42,6 @@ trait ShimCometShuffleExchangeExec { } protected def fromAttributes(attributes: Seq[Attribute]): StructType = DataTypeUtils.fromAttributes(attributes) + + protected def getShuffleId(shuffleDependency: ShuffleDependency[Int, _, _]): Int = shuffleDependency.shuffleId } diff --git a/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala b/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala index 4b4f60a10..baa2e80a5 100644 --- a/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala +++ b/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala @@ -566,7 +566,7 @@ abstract class CometColumnarShuffleSuite extends CometTestBase with AdaptiveSpar } test("columnar shuffle on nested array") { - Seq("false", "true").foreach { execEnabled => + Seq("false", "true").foreach { _ => Seq(10, 201).foreach { numPartitions => Seq("1.0", "10.0").foreach { ratio => withSQLConf(CometConf.COMET_SHUFFLE_PREFER_DICTIONARY_RATIO.key -> ratio) { diff --git a/spark/src/test/scala/org/apache/spark/sql/CometTPCDSQuerySuite.scala b/spark/src/test/scala/org/apache/spark/sql/CometTPCDSQuerySuite.scala index cdbd7194d..fc8c36dd7 100644 --- a/spark/src/test/scala/org/apache/spark/sql/CometTPCDSQuerySuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/CometTPCDSQuerySuite.scala @@ -27,7 +27,7 @@ import org.apache.comet.CometConf class CometTPCDSQuerySuite extends { // This is private in `TPCDSBase`. - val excludedTpcdsQueries: Seq[String] = Seq() + override val excludedTpcdsQueries: Set[String] = Set() // This is private in `TPCDSBase` and `excludedTpcdsQueries` is private too. // So we cannot override `excludedTpcdsQueries` to exclude the queries. diff --git a/spark/src/test/scala/org/apache/spark/sql/CometTPCHQuerySuite.scala b/spark/src/test/scala/org/apache/spark/sql/CometTPCHQuerySuite.scala index 6ec25dd19..64452eb74 100644 --- a/spark/src/test/scala/org/apache/spark/sql/CometTPCHQuerySuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/CometTPCHQuerySuite.scala @@ -33,6 +33,7 @@ import org.apache.spark.sql.test.{SharedSparkSession, TestSparkSession} import org.apache.comet.CometConf import org.apache.comet.CometSparkSessionExtensions.isSpark34Plus +import org.apache.comet.shims.ShimCometTPCHQuerySuite /** * End-to-end tests to check TPCH query results. @@ -49,7 +50,7 @@ import org.apache.comet.CometSparkSessionExtensions.isSpark34Plus * ./mvnw -Dsuites=org.apache.spark.sql.CometTPCHQuerySuite test * }}} */ -class CometTPCHQuerySuite extends QueryTest with CometTPCBase with SQLQueryTestHelper { +class CometTPCHQuerySuite extends QueryTest with CometTPCBase with ShimCometTPCHQuerySuite { private val tpchDataPath = sys.env.get("SPARK_TPCH_DATA") @@ -142,7 +143,7 @@ class CometTPCHQuerySuite extends QueryTest with CometTPCBase with SQLQueryTestH val shouldSortResults = sortMergeJoinConf != conf // Sort for other joins withSQLConf(conf.toSeq: _*) { try { - val (schema, output) = handleExceptions(getNormalizedResult(spark, query)) + val (schema, output) = handleExceptions(getNormalizedQueryExecutionResult(spark, query)) val queryString = query.trim val outputString = output.mkString("\n").replaceAll("\\s+$", "") if (shouldRegenerateGoldenFiles) { diff --git a/spark/src/test/spark-3.2/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala b/spark/src/test/spark-3.2/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala new file mode 100644 index 000000000..15edd486c --- /dev/null +++ b/spark/src/test/spark-3.2/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala @@ -0,0 +1,9 @@ +package org.apache.comet.shims + +import org.apache.spark.sql.{SQLQueryTestHelper, SparkSession} + +trait ShimCometTPCHQuerySuite extends SQLQueryTestHelper { + protected def getNormalizedQueryExecutionResult(session: SparkSession, sql: String): (String, Seq[String]) = { + getNormalizedResult(session, sql) + } +} diff --git a/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala b/spark/src/test/spark-3.3/org/apache/comet/CometExpression3_3PlusSuite.scala similarity index 100% rename from spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala rename to spark/src/test/spark-3.3/org/apache/comet/CometExpression3_3PlusSuite.scala diff --git a/spark/src/test/spark-3.3/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala b/spark/src/test/spark-3.3/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala new file mode 100644 index 000000000..15edd486c --- /dev/null +++ b/spark/src/test/spark-3.3/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala @@ -0,0 +1,9 @@ +package org.apache.comet.shims + +import org.apache.spark.sql.{SQLQueryTestHelper, SparkSession} + +trait ShimCometTPCHQuerySuite extends SQLQueryTestHelper { + protected def getNormalizedQueryExecutionResult(session: SparkSession, sql: String): (String, Seq[String]) = { + getNormalizedResult(session, sql) + } +} diff --git a/spark/src/test/spark-3.4/org/apache/comet/CometExpression3_3PlusSuite.scala b/spark/src/test/spark-3.4/org/apache/comet/CometExpression3_3PlusSuite.scala new file mode 100644 index 000000000..b56ed2953 --- /dev/null +++ b/spark/src/test/spark-3.4/org/apache/comet/CometExpression3_3PlusSuite.scala @@ -0,0 +1,106 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet + +import java.io.ByteArrayOutputStream +import scala.util.Random + +import org.apache.spark.sql.catalyst.FunctionIdentifier +import org.apache.spark.sql.catalyst.expressions.{BloomFilterMightContain, Expression, ExpressionInfo} +import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper +import org.apache.spark.sql.functions.{col, lit} +import org.apache.spark.sql.{Column, CometTestBase} +import org.apache.spark.util.sketch.BloomFilter + +class CometExpression3_3PlusSuite extends CometTestBase with AdaptiveSparkPlanHelper { + import testImplicits._ + + val func_might_contain = new FunctionIdentifier("might_contain") + + override def beforeAll(): Unit = { + super.beforeAll() + // Register 'might_contain' to builtin. + spark.sessionState.functionRegistry.registerFunction(func_might_contain, + new ExpressionInfo(classOf[BloomFilterMightContain].getName, "might_contain"), + (children: Seq[Expression]) => BloomFilterMightContain(children.head, children(1))) + } + + override def afterAll(): Unit = { + spark.sessionState.functionRegistry.dropFunction(func_might_contain) + super.afterAll() + } + + test("test BloomFilterMightContain can take a constant value input") { + val table = "test" + + withTable(table) { + sql(s"create table $table(col1 long, col2 int) using parquet") + sql(s"insert into $table values (201, 1)") + checkSparkAnswerAndOperator( + s""" + |SELECT might_contain( + |X'00000001000000050000000343A2EC6EA8C117E2D3CDB767296B144FC5BFBCED9737F267', col1) FROM $table + |""".stripMargin) + } + } + + test("test NULL inputs for BloomFilterMightContain") { + val table = "test" + + withTable(table) { + sql(s"create table $table(col1 long, col2 int) using parquet") + sql(s"insert into $table values (201, 1), (null, 2)") + checkSparkAnswerAndOperator( + s""" + |SELECT might_contain(null, null) both_null, + | might_contain(null, 1L) null_bf, + | might_contain( + | X'00000001000000050000000343A2EC6EA8C117E2D3CDB767296B144FC5BFBCED9737F267', col1) null_value + | FROM $table + |""".stripMargin) + } + } + + test("test BloomFilterMightContain from random input") { + val (longs, bfBytes) = bloomFilterFromRandomInput(10000, 10000) + val table = "test" + + withTable(table) { + sql(s"create table $table(col1 long, col2 binary) using parquet") + spark.createDataset(longs).map(x => (x, bfBytes)).toDF("col1", "col2").write.insertInto(table) + val df = spark.table(table).select(new Column(BloomFilterMightContain(lit(bfBytes).expr, col("col1").expr))) + checkSparkAnswerAndOperator(df) + // check with scalar subquery + checkSparkAnswerAndOperator( + s""" + |SELECT might_contain((select first(col2) as col2 from $table), col1) FROM $table + |""".stripMargin) + } + } + + private def bloomFilterFromRandomInput(expectedItems: Long, expectedBits: Long): (Seq[Long], Array[Byte]) = { + val bf = BloomFilter.create(expectedItems, expectedBits) + val longs = (0 until expectedItems.toInt).map(_ => Random.nextLong()) + longs.foreach(bf.put) + val os = new ByteArrayOutputStream() + bf.writeTo(os) + (longs, os.toByteArray) + } +} diff --git a/spark/src/test/spark-3.4/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala b/spark/src/test/spark-3.4/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala new file mode 100644 index 000000000..15edd486c --- /dev/null +++ b/spark/src/test/spark-3.4/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala @@ -0,0 +1,9 @@ +package org.apache.comet.shims + +import org.apache.spark.sql.{SQLQueryTestHelper, SparkSession} + +trait ShimCometTPCHQuerySuite extends SQLQueryTestHelper { + protected def getNormalizedQueryExecutionResult(session: SparkSession, sql: String): (String, Seq[String]) = { + getNormalizedResult(session, sql) + } +} diff --git a/spark/src/test/spark-4.0/org/apache/comet/CometExpression3_3PlusSuite.scala b/spark/src/test/spark-4.0/org/apache/comet/CometExpression3_3PlusSuite.scala new file mode 100644 index 000000000..b56ed2953 --- /dev/null +++ b/spark/src/test/spark-4.0/org/apache/comet/CometExpression3_3PlusSuite.scala @@ -0,0 +1,106 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet + +import java.io.ByteArrayOutputStream +import scala.util.Random + +import org.apache.spark.sql.catalyst.FunctionIdentifier +import org.apache.spark.sql.catalyst.expressions.{BloomFilterMightContain, Expression, ExpressionInfo} +import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper +import org.apache.spark.sql.functions.{col, lit} +import org.apache.spark.sql.{Column, CometTestBase} +import org.apache.spark.util.sketch.BloomFilter + +class CometExpression3_3PlusSuite extends CometTestBase with AdaptiveSparkPlanHelper { + import testImplicits._ + + val func_might_contain = new FunctionIdentifier("might_contain") + + override def beforeAll(): Unit = { + super.beforeAll() + // Register 'might_contain' to builtin. + spark.sessionState.functionRegistry.registerFunction(func_might_contain, + new ExpressionInfo(classOf[BloomFilterMightContain].getName, "might_contain"), + (children: Seq[Expression]) => BloomFilterMightContain(children.head, children(1))) + } + + override def afterAll(): Unit = { + spark.sessionState.functionRegistry.dropFunction(func_might_contain) + super.afterAll() + } + + test("test BloomFilterMightContain can take a constant value input") { + val table = "test" + + withTable(table) { + sql(s"create table $table(col1 long, col2 int) using parquet") + sql(s"insert into $table values (201, 1)") + checkSparkAnswerAndOperator( + s""" + |SELECT might_contain( + |X'00000001000000050000000343A2EC6EA8C117E2D3CDB767296B144FC5BFBCED9737F267', col1) FROM $table + |""".stripMargin) + } + } + + test("test NULL inputs for BloomFilterMightContain") { + val table = "test" + + withTable(table) { + sql(s"create table $table(col1 long, col2 int) using parquet") + sql(s"insert into $table values (201, 1), (null, 2)") + checkSparkAnswerAndOperator( + s""" + |SELECT might_contain(null, null) both_null, + | might_contain(null, 1L) null_bf, + | might_contain( + | X'00000001000000050000000343A2EC6EA8C117E2D3CDB767296B144FC5BFBCED9737F267', col1) null_value + | FROM $table + |""".stripMargin) + } + } + + test("test BloomFilterMightContain from random input") { + val (longs, bfBytes) = bloomFilterFromRandomInput(10000, 10000) + val table = "test" + + withTable(table) { + sql(s"create table $table(col1 long, col2 binary) using parquet") + spark.createDataset(longs).map(x => (x, bfBytes)).toDF("col1", "col2").write.insertInto(table) + val df = spark.table(table).select(new Column(BloomFilterMightContain(lit(bfBytes).expr, col("col1").expr))) + checkSparkAnswerAndOperator(df) + // check with scalar subquery + checkSparkAnswerAndOperator( + s""" + |SELECT might_contain((select first(col2) as col2 from $table), col1) FROM $table + |""".stripMargin) + } + } + + private def bloomFilterFromRandomInput(expectedItems: Long, expectedBits: Long): (Seq[Long], Array[Byte]) = { + val bf = BloomFilter.create(expectedItems, expectedBits) + val longs = (0 until expectedItems.toInt).map(_ => Random.nextLong()) + longs.foreach(bf.put) + val os = new ByteArrayOutputStream() + bf.writeTo(os) + (longs, os.toByteArray) + } +} diff --git a/spark/src/test/spark-4.0/org/apache/comet/exec/CometExec3_4Suite.scala b/spark/src/test/spark-4.0/org/apache/comet/exec/CometExec3_4Suite.scala new file mode 100644 index 000000000..7644d54be --- /dev/null +++ b/spark/src/test/spark-4.0/org/apache/comet/exec/CometExec3_4Suite.scala @@ -0,0 +1,52 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.exec + +import org.scalactic.source.Position +import org.scalatest.Tag + +import org.apache.spark.sql.CometTestBase + +import org.apache.comet.CometConf + +/** + * This test suite contains tests for only Spark 3.4. + */ +class CometExec3_4Suite extends CometTestBase { + import testImplicits._ + + override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit + pos: Position): Unit = { + super.test(testName, testTags: _*) { + withSQLConf(CometConf.COMET_EXEC_SHUFFLE_ENABLED.key -> "true") { + testFun + } + } + } + + // Dataset.offset API is not available before Spark 3.4 + test("offset") { + withSQLConf(CometConf.COMET_COLUMNAR_SHUFFLE_ENABLED.key -> "true") { + checkSparkAnswer(testData.offset(90)) + checkSparkAnswer(arrayData.toDF().offset(99)) + checkSparkAnswer(mapData.toDF().offset(99)) + } + } +} diff --git a/spark/src/test/spark-4.0/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala b/spark/src/test/spark-4.0/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala new file mode 100644 index 000000000..3a570e99d --- /dev/null +++ b/spark/src/test/spark-4.0/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala @@ -0,0 +1,6 @@ +package org.apache.comet.shims + +import org.apache.spark.sql.SQLQueryTestHelper + +trait ShimCometTPCHQuerySuite extends SQLQueryTestHelper { +} From 8db78cb105bb27d986ac146db449637b1d0ca715 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 7 May 2024 16:05:35 -0700 Subject: [PATCH 04/68] build: Add spark-4.0 profile --- pom.xml | 6 + .../comet/CometExpression3_3PlusSuite.scala | 0 .../comet/exec/CometExec3_4PlusSuite.scala} | 2 +- .../comet/CometExpression3_3PlusSuite.scala | 106 ------------------ .../comet/CometExpression3_3PlusSuite.scala | 106 ------------------ .../apache/comet/exec/CometExec3_4Suite.scala | 52 --------- 6 files changed, 7 insertions(+), 265 deletions(-) rename spark/src/test/{spark-3.3 => spark-3.3-plus}/org/apache/comet/CometExpression3_3PlusSuite.scala (100%) rename spark/src/test/{spark-3.4/org/apache/comet/exec/CometExec3_4Suite.scala => spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala} (96%) delete mode 100644 spark/src/test/spark-3.4/org/apache/comet/CometExpression3_3PlusSuite.scala delete mode 100644 spark/src/test/spark-4.0/org/apache/comet/CometExpression3_3PlusSuite.scala delete mode 100644 spark/src/test/spark-4.0/org/apache/comet/exec/CometExec3_4Suite.scala diff --git a/pom.xml b/pom.xml index a91056b59..e0f6ce6e3 100644 --- a/pom.xml +++ b/pom.xml @@ -86,6 +86,8 @@ under the License. -Djdk.reflect.useDirectMethodHandle=false -ea -Xmx4g -Xss4m ${extraJavaTestArgs} + spark-3.3-plus + spark-3.4-plus spark-3.x @@ -495,6 +497,9 @@ under the License. 3.2.2 3.2 1.12.0 + + not-needed-yet + not-needed-yet @@ -505,6 +510,7 @@ under the License. 3.3.2 3.3 1.12.0 + not-needed-yet diff --git a/spark/src/test/spark-3.3/org/apache/comet/CometExpression3_3PlusSuite.scala b/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala similarity index 100% rename from spark/src/test/spark-3.3/org/apache/comet/CometExpression3_3PlusSuite.scala rename to spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala diff --git a/spark/src/test/spark-3.4/org/apache/comet/exec/CometExec3_4Suite.scala b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala similarity index 96% rename from spark/src/test/spark-3.4/org/apache/comet/exec/CometExec3_4Suite.scala rename to spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala index 7644d54be..0d5defdae 100644 --- a/spark/src/test/spark-3.4/org/apache/comet/exec/CometExec3_4Suite.scala +++ b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala @@ -29,7 +29,7 @@ import org.apache.comet.CometConf /** * This test suite contains tests for only Spark 3.4. */ -class CometExec3_4Suite extends CometTestBase { +class CometExec3_4PlusSuite extends CometTestBase { import testImplicits._ override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit diff --git a/spark/src/test/spark-3.4/org/apache/comet/CometExpression3_3PlusSuite.scala b/spark/src/test/spark-3.4/org/apache/comet/CometExpression3_3PlusSuite.scala deleted file mode 100644 index b56ed2953..000000000 --- a/spark/src/test/spark-3.4/org/apache/comet/CometExpression3_3PlusSuite.scala +++ /dev/null @@ -1,106 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -package org.apache.comet - -import java.io.ByteArrayOutputStream -import scala.util.Random - -import org.apache.spark.sql.catalyst.FunctionIdentifier -import org.apache.spark.sql.catalyst.expressions.{BloomFilterMightContain, Expression, ExpressionInfo} -import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper -import org.apache.spark.sql.functions.{col, lit} -import org.apache.spark.sql.{Column, CometTestBase} -import org.apache.spark.util.sketch.BloomFilter - -class CometExpression3_3PlusSuite extends CometTestBase with AdaptiveSparkPlanHelper { - import testImplicits._ - - val func_might_contain = new FunctionIdentifier("might_contain") - - override def beforeAll(): Unit = { - super.beforeAll() - // Register 'might_contain' to builtin. - spark.sessionState.functionRegistry.registerFunction(func_might_contain, - new ExpressionInfo(classOf[BloomFilterMightContain].getName, "might_contain"), - (children: Seq[Expression]) => BloomFilterMightContain(children.head, children(1))) - } - - override def afterAll(): Unit = { - spark.sessionState.functionRegistry.dropFunction(func_might_contain) - super.afterAll() - } - - test("test BloomFilterMightContain can take a constant value input") { - val table = "test" - - withTable(table) { - sql(s"create table $table(col1 long, col2 int) using parquet") - sql(s"insert into $table values (201, 1)") - checkSparkAnswerAndOperator( - s""" - |SELECT might_contain( - |X'00000001000000050000000343A2EC6EA8C117E2D3CDB767296B144FC5BFBCED9737F267', col1) FROM $table - |""".stripMargin) - } - } - - test("test NULL inputs for BloomFilterMightContain") { - val table = "test" - - withTable(table) { - sql(s"create table $table(col1 long, col2 int) using parquet") - sql(s"insert into $table values (201, 1), (null, 2)") - checkSparkAnswerAndOperator( - s""" - |SELECT might_contain(null, null) both_null, - | might_contain(null, 1L) null_bf, - | might_contain( - | X'00000001000000050000000343A2EC6EA8C117E2D3CDB767296B144FC5BFBCED9737F267', col1) null_value - | FROM $table - |""".stripMargin) - } - } - - test("test BloomFilterMightContain from random input") { - val (longs, bfBytes) = bloomFilterFromRandomInput(10000, 10000) - val table = "test" - - withTable(table) { - sql(s"create table $table(col1 long, col2 binary) using parquet") - spark.createDataset(longs).map(x => (x, bfBytes)).toDF("col1", "col2").write.insertInto(table) - val df = spark.table(table).select(new Column(BloomFilterMightContain(lit(bfBytes).expr, col("col1").expr))) - checkSparkAnswerAndOperator(df) - // check with scalar subquery - checkSparkAnswerAndOperator( - s""" - |SELECT might_contain((select first(col2) as col2 from $table), col1) FROM $table - |""".stripMargin) - } - } - - private def bloomFilterFromRandomInput(expectedItems: Long, expectedBits: Long): (Seq[Long], Array[Byte]) = { - val bf = BloomFilter.create(expectedItems, expectedBits) - val longs = (0 until expectedItems.toInt).map(_ => Random.nextLong()) - longs.foreach(bf.put) - val os = new ByteArrayOutputStream() - bf.writeTo(os) - (longs, os.toByteArray) - } -} diff --git a/spark/src/test/spark-4.0/org/apache/comet/CometExpression3_3PlusSuite.scala b/spark/src/test/spark-4.0/org/apache/comet/CometExpression3_3PlusSuite.scala deleted file mode 100644 index b56ed2953..000000000 --- a/spark/src/test/spark-4.0/org/apache/comet/CometExpression3_3PlusSuite.scala +++ /dev/null @@ -1,106 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -package org.apache.comet - -import java.io.ByteArrayOutputStream -import scala.util.Random - -import org.apache.spark.sql.catalyst.FunctionIdentifier -import org.apache.spark.sql.catalyst.expressions.{BloomFilterMightContain, Expression, ExpressionInfo} -import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper -import org.apache.spark.sql.functions.{col, lit} -import org.apache.spark.sql.{Column, CometTestBase} -import org.apache.spark.util.sketch.BloomFilter - -class CometExpression3_3PlusSuite extends CometTestBase with AdaptiveSparkPlanHelper { - import testImplicits._ - - val func_might_contain = new FunctionIdentifier("might_contain") - - override def beforeAll(): Unit = { - super.beforeAll() - // Register 'might_contain' to builtin. - spark.sessionState.functionRegistry.registerFunction(func_might_contain, - new ExpressionInfo(classOf[BloomFilterMightContain].getName, "might_contain"), - (children: Seq[Expression]) => BloomFilterMightContain(children.head, children(1))) - } - - override def afterAll(): Unit = { - spark.sessionState.functionRegistry.dropFunction(func_might_contain) - super.afterAll() - } - - test("test BloomFilterMightContain can take a constant value input") { - val table = "test" - - withTable(table) { - sql(s"create table $table(col1 long, col2 int) using parquet") - sql(s"insert into $table values (201, 1)") - checkSparkAnswerAndOperator( - s""" - |SELECT might_contain( - |X'00000001000000050000000343A2EC6EA8C117E2D3CDB767296B144FC5BFBCED9737F267', col1) FROM $table - |""".stripMargin) - } - } - - test("test NULL inputs for BloomFilterMightContain") { - val table = "test" - - withTable(table) { - sql(s"create table $table(col1 long, col2 int) using parquet") - sql(s"insert into $table values (201, 1), (null, 2)") - checkSparkAnswerAndOperator( - s""" - |SELECT might_contain(null, null) both_null, - | might_contain(null, 1L) null_bf, - | might_contain( - | X'00000001000000050000000343A2EC6EA8C117E2D3CDB767296B144FC5BFBCED9737F267', col1) null_value - | FROM $table - |""".stripMargin) - } - } - - test("test BloomFilterMightContain from random input") { - val (longs, bfBytes) = bloomFilterFromRandomInput(10000, 10000) - val table = "test" - - withTable(table) { - sql(s"create table $table(col1 long, col2 binary) using parquet") - spark.createDataset(longs).map(x => (x, bfBytes)).toDF("col1", "col2").write.insertInto(table) - val df = spark.table(table).select(new Column(BloomFilterMightContain(lit(bfBytes).expr, col("col1").expr))) - checkSparkAnswerAndOperator(df) - // check with scalar subquery - checkSparkAnswerAndOperator( - s""" - |SELECT might_contain((select first(col2) as col2 from $table), col1) FROM $table - |""".stripMargin) - } - } - - private def bloomFilterFromRandomInput(expectedItems: Long, expectedBits: Long): (Seq[Long], Array[Byte]) = { - val bf = BloomFilter.create(expectedItems, expectedBits) - val longs = (0 until expectedItems.toInt).map(_ => Random.nextLong()) - longs.foreach(bf.put) - val os = new ByteArrayOutputStream() - bf.writeTo(os) - (longs, os.toByteArray) - } -} diff --git a/spark/src/test/spark-4.0/org/apache/comet/exec/CometExec3_4Suite.scala b/spark/src/test/spark-4.0/org/apache/comet/exec/CometExec3_4Suite.scala deleted file mode 100644 index 7644d54be..000000000 --- a/spark/src/test/spark-4.0/org/apache/comet/exec/CometExec3_4Suite.scala +++ /dev/null @@ -1,52 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -package org.apache.comet.exec - -import org.scalactic.source.Position -import org.scalatest.Tag - -import org.apache.spark.sql.CometTestBase - -import org.apache.comet.CometConf - -/** - * This test suite contains tests for only Spark 3.4. - */ -class CometExec3_4Suite extends CometTestBase { - import testImplicits._ - - override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit - pos: Position): Unit = { - super.test(testName, testTags: _*) { - withSQLConf(CometConf.COMET_EXEC_SHUFFLE_ENABLED.key -> "true") { - testFun - } - } - } - - // Dataset.offset API is not available before Spark 3.4 - test("offset") { - withSQLConf(CometConf.COMET_COLUMNAR_SHUFFLE_ENABLED.key -> "true") { - checkSparkAnswer(testData.offset(90)) - checkSparkAnswer(arrayData.toDF().offset(99)) - checkSparkAnswer(mapData.toDF().offset(99)) - } - } -} From 7251eb2f799712128a746916057b288d5994ca43 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 7 May 2024 17:25:40 -0700 Subject: [PATCH 05/68] build: Add spark-4.0 profile --- .github/workflows/pr_build.yml | 98 +++++++++++++++++++ .../apache/comet/shims/ShimBatchReader.scala | 36 ++----- .../apache/comet/shims/ShimFileFormat.scala | 13 ++- .../shims/ShimResolveDefaultColumns.scala | 12 +-- 4 files changed, 116 insertions(+), 43 deletions(-) diff --git a/.github/workflows/pr_build.yml b/.github/workflows/pr_build.yml index 71eb02a9e..8eaa83d9d 100644 --- a/.github/workflows/pr_build.yml +++ b/.github/workflows/pr_build.yml @@ -75,6 +75,39 @@ jobs: # upload test reports only for java 17 upload-test-reports: ${{ matrix.java_version == '17' }} + linux-test-with-spark4_0: + strategy: + matrix: + os: [ubuntu-latest] + java_version: [17] + test-target: [rust, java] + spark-version: ['4.0'] + is_push_event: + - ${{ github.event_name == 'push' }} + fail-fast: false + name: ${{ matrix.os }}/java ${{ matrix.java_version }}-spark-${{matrix.spark-version}}/${{ matrix.test-target }} + runs-on: ${{ matrix.os }} + container: + image: amd64/rust + steps: + - uses: actions/checkout@v4 + - name: Setup Rust & Java toolchain + uses: ./.github/actions/setup-builder + with: + rust-version: ${{env.RUST_VERSION}} + jdk-version: ${{ matrix.java_version }} + - if: matrix.test-target == 'rust' + name: Rust test steps + uses: ./.github/actions/rust-test + - if: matrix.test-target == 'java' + name: Java test steps + uses: ./.github/actions/java-test + with: + # TODO: remove -DskipTests after fixing tests + maven_opts: "-Pspark-${{ matrix.spark-version }} -DskipTests" + # TODO: upload test reports after enabling tests + upload-test-reports: false + linux-test-with-old-spark: strategy: matrix: @@ -163,6 +196,71 @@ jobs: with: maven_opts: -Pspark-${{ matrix.spark-version }} + macos-test-with-spark4_0: + strategy: + matrix: + os: [macos-13] + java_version: [17] + test-target: [rust, java] + spark-version: ['4.0'] + fail-fast: false + if: github.event_name == 'push' + name: ${{ matrix.os }}/java ${{ matrix.java_version }}-spark-${{matrix.spark-version}}/${{ matrix.test-target }} + runs-on: ${{ matrix.os }} + steps: + - uses: actions/checkout@v4 + - name: Setup Rust & Java toolchain + uses: ./.github/actions/setup-macos-builder + with: + rust-version: ${{env.RUST_VERSION}} + jdk-version: ${{ matrix.java_version }} + - if: matrix.test-target == 'rust' + name: Rust test steps + uses: ./.github/actions/rust-test + - if: matrix.test-target == 'java' + name: Java test steps + uses: ./.github/actions/java-test + with: + # TODO: remove -DskipTests after fixing tests + maven_opts: "-Pspark-${{ matrix.spark-version }} -DskipTests" + # TODO: upload test reports after enabling tests + upload-test-reports: false + + macos-aarch64-test-with-spark4_0: + strategy: + matrix: + java_version: [17] + test-target: [rust, java] + spark-version: ['4.0'] + is_push_event: + - ${{ github.event_name == 'push' }} + exclude: # exclude java 11 for pull_request event + - java_version: 11 + is_push_event: false + fail-fast: false + name: macos-14(Silicon)/java ${{ matrix.java_version }}-spark-${{matrix.spark-version}}/${{ matrix.test-target }} + runs-on: macos-14 + steps: + - uses: actions/checkout@v4 + - name: Setup Rust & Java toolchain + uses: ./.github/actions/setup-macos-builder + with: + rust-version: ${{env.RUST_VERSION}} + jdk-version: ${{ matrix.java_version }} + jdk-architecture: aarch64 + protoc-architecture: aarch_64 + - if: matrix.test-target == 'rust' + name: Rust test steps + uses: ./.github/actions/rust-test + - if: matrix.test-target == 'java' + name: Java test steps + uses: ./.github/actions/java-test + with: + # TODO: remove -DskipTests after fixing tests + maven_opts: "-Pspark-${{ matrix.spark-version }} -DskipTests" + # TODO: upload test reports after enabling tests + upload-test-reports: false + macos-aarch64-test-with-old-spark: strategy: matrix: diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala index ece4cfbe5..1866c8ba7 100644 --- a/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala @@ -19,36 +19,20 @@ package org.apache.comet.shims +import org.apache.spark.paths.SparkPath import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.execution.datasources.PartitionedFile object ShimBatchReader { - // TODO: remove after dropping Spark 3.2 & 3.3 support and directly call PartitionedFile def newPartitionedFile(partitionValues: InternalRow, file: String): PartitionedFile = - classOf[PartitionedFile].getDeclaredConstructors - .map(c => - c.getParameterCount match { - case 5 => - c.newInstance( - partitionValues, - file, - Long.box(-1), // -1 means we read the entire file - Long.box(-1), - Array.empty[String]) - case 7 => - c.newInstance( - partitionValues, - c.getParameterTypes()(1) - .getConstructor(classOf[String]) - .newInstance(file) - .asInstanceOf[AnyRef], - Long.box(-1), // -1 means we read the entire file - Long.box(-1), - Array.empty[String], - Long.box(0), - Long.box(0)) - }) - .head - .asInstanceOf[PartitionedFile] + PartitionedFile( + partitionValues, + SparkPath.fromUrlString(file), + -1, // -1 means we read the entire file + -1, + Array.empty[String], + 0, + 0 + ) } diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala index 5ab7eaf4f..354dacf51 100644 --- a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala @@ -19,17 +19,16 @@ package org.apache.comet.shims +import org.apache.spark.sql.execution.datasources.FileFormat +import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat + object ShimFileFormat { - // TODO: remove after dropping Spark 3.2 & 3.3 support and directly use FileFormat.ROW_INDEX - val ROW_INDEX = "row_index" + val ROW_INDEX = ParquetFileFormat.ROW_INDEX // A name for a temporary column that holds row indexes computed by the file format reader // until they can be placed in the _metadata struct. - // TODO: remove after dropping Spark 3.2 & 3.3 support and directly use - // FileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME - val ROW_INDEX_TEMPORARY_COLUMN_NAME: String = s"_tmp_metadata_$ROW_INDEX" + val ROW_INDEX_TEMPORARY_COLUMN_NAME = ParquetFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME - // TODO: remove after dropping Spark 3.2 support and use FileFormat.OPTION_RETURNING_BATCH - val OPTION_RETURNING_BATCH = "returning_batch" + val OPTION_RETURNING_BATCH = FileFormat.OPTION_RETURNING_BATCH } diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala index 8a30c8e00..d5376a1be 100644 --- a/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala @@ -21,18 +21,10 @@ package org.apache.comet.shims import scala.util.Try +import org.apache.spark.sql.catalyst.util.ResolveDefaultColumns import org.apache.spark.sql.types.{StructField, StructType} object ShimResolveDefaultColumns { - // TODO: remove after dropping Spark 3.2 & 3.3 support and directly use ResolveDefaultColumns def getExistenceDefaultValue(field: StructField): Any = - Try { - // scalastyle:off classforname - Class.forName("org.apache.spark.sql.catalyst.util.ResolveDefaultColumns$") - // scalastyle:on classforname - }.map { objClass => - val objInstance = objClass.getField("MODULE$").get(null) - val method = objClass.getMethod("getExistenceDefaultValues", classOf[StructType]) - method.invoke(objInstance, StructType(Seq(field))).asInstanceOf[Array[Any]].head - }.getOrElse(null) + ResolveDefaultColumns.getExistenceDefaultValues(StructType(Seq(field))).head } From 17a6995e8d9f8afa2c5dcb1d9af7f1b889d3a046 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 7 May 2024 22:51:42 -0700 Subject: [PATCH 06/68] build: Add spark-4.0 profile --- .../comet/parquet/CometParquetUtils.scala | 61 +----------------- .../comet/parquet/ShimCometParquetUtils.scala | 62 +++++++++++++++++++ .../shims/ShimResolveDefaultColumns.scala | 1 - .../comet/parquet/ShimCometParquetUtils.scala | 21 +++++++ .../spark/sql/comet/CometScanExec.scala | 2 +- .../sql/comet}/ShimCometScanExec.scala | 2 +- .../comet/shims/ShimCometBatchScanExec.scala | 17 +---- .../shims/ShimCometShuffleExchangeExec.scala | 7 +-- .../ShimCometSparkSessionExtensions.scala | 24 +------ .../ShimCometTakeOrderedAndProjectExec.scala | 10 +-- .../org/apache/comet/shims/ShimSQLConf.scala | 7 --- .../sql/comet}/ShimCometScanExec.scala | 62 ++++--------------- .../sql/benchmark/CometReadBenchmark.scala | 5 +- .../comet/shims/ShimCometTPCHQuerySuite.scala | 9 --- .../comet/shims/ShimCometTPCHQuerySuite.scala | 9 --- .../comet/shims/ShimCometTPCHQuerySuite.scala | 0 .../apache/spark/comet/ShimTestUtils.scala} | 5 +- .../apache/spark/comet/ShimTestUtils.scala | 28 +++++++++ 18 files changed, 139 insertions(+), 193 deletions(-) create mode 100644 common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala create mode 100644 common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala rename spark/src/main/spark-3.x/org/apache/{comet/shims => spark/sql/comet}/ShimCometScanExec.scala (99%) rename spark/src/main/spark-4.0/org/apache/{comet/shims => spark/sql/comet}/ShimCometScanExec.scala (62%) delete mode 100644 spark/src/test/spark-3.3/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala delete mode 100644 spark/src/test/spark-3.4/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala rename spark/src/test/{spark-3.2 => spark-3.x}/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala (100%) rename spark/src/test/{scala/org/apache/comet/TestUtils.scala => spark-3.x/org/apache/spark/comet/ShimTestUtils.scala} (96%) create mode 100644 spark/src/test/spark-4.0/org/apache/spark/comet/ShimTestUtils.scala diff --git a/common/src/main/scala/org/apache/comet/parquet/CometParquetUtils.scala b/common/src/main/scala/org/apache/comet/parquet/CometParquetUtils.scala index d851067b5..2cb5f141e 100644 --- a/common/src/main/scala/org/apache/comet/parquet/CometParquetUtils.scala +++ b/common/src/main/scala/org/apache/comet/parquet/CometParquetUtils.scala @@ -20,10 +20,10 @@ package org.apache.comet.parquet import org.apache.hadoop.conf.Configuration +import org.apache.spark.sql.comet.parquet.ShimCometParquetUtils import org.apache.spark.sql.internal.SQLConf -import org.apache.spark.sql.types._ -object CometParquetUtils { +object CometParquetUtils extends ShimCometParquetUtils { private val PARQUET_FIELD_ID_WRITE_ENABLED = "spark.sql.parquet.fieldId.write.enabled" private val PARQUET_FIELD_ID_READ_ENABLED = "spark.sql.parquet.fieldId.read.enabled" private val IGNORE_MISSING_PARQUET_FIELD_ID = "spark.sql.parquet.fieldId.read.ignoreMissing" @@ -39,61 +39,4 @@ object CometParquetUtils { def ignoreMissingIds(conf: SQLConf): Boolean = conf.getConfString(IGNORE_MISSING_PARQUET_FIELD_ID, "false").toBoolean - - // The following is copied from QueryExecutionErrors - // TODO: remove after dropping Spark 3.2.0 support and directly use - // QueryExecutionErrors.foundDuplicateFieldInFieldIdLookupModeError - def foundDuplicateFieldInFieldIdLookupModeError( - requiredId: Int, - matchedFields: String): Throwable = { - new RuntimeException(s""" - |Found duplicate field(s) "$requiredId": $matchedFields - |in id mapping mode - """.stripMargin.replaceAll("\n", " ")) - } - - // The followings are copied from org.apache.spark.sql.execution.datasources.parquet.ParquetUtils - // TODO: remove after dropping Spark 3.2.0 support and directly use ParquetUtils - /** - * A StructField metadata key used to set the field id of a column in the Parquet schema. - */ - val FIELD_ID_METADATA_KEY = "parquet.field.id" - - /** - * Whether there exists a field in the schema, whether inner or leaf, has the parquet field ID - * metadata. - */ - def hasFieldIds(schema: StructType): Boolean = { - def recursiveCheck(schema: DataType): Boolean = { - schema match { - case st: StructType => - st.exists(field => hasFieldId(field) || recursiveCheck(field.dataType)) - - case at: ArrayType => recursiveCheck(at.elementType) - - case mt: MapType => recursiveCheck(mt.keyType) || recursiveCheck(mt.valueType) - - case _ => - // No need to really check primitive types, just to terminate the recursion - false - } - } - if (schema.isEmpty) false else recursiveCheck(schema) - } - - def hasFieldId(field: StructField): Boolean = - field.metadata.contains(FIELD_ID_METADATA_KEY) - - def getFieldId(field: StructField): Int = { - require( - hasFieldId(field), - s"The key `$FIELD_ID_METADATA_KEY` doesn't exist in the metadata of " + field) - try { - Math.toIntExact(field.metadata.getLong(FIELD_ID_METADATA_KEY)) - } catch { - case _: ArithmeticException | _: ClassCastException => - throw new IllegalArgumentException( - s"The key `$FIELD_ID_METADATA_KEY` must be a 32-bit integer") - } - } } diff --git a/common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala b/common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala new file mode 100644 index 000000000..bee6a8e8d --- /dev/null +++ b/common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala @@ -0,0 +1,62 @@ +package org.apache.spark.sql.comet.parquet + +import org.apache.spark.sql.types._ + +trait ShimCometParquetUtils { + // The following is copied from QueryExecutionErrors + // TODO: remove after dropping Spark 3.2.0 support and directly use + // QueryExecutionErrors.foundDuplicateFieldInFieldIdLookupModeError + def foundDuplicateFieldInFieldIdLookupModeError( + requiredId: Int, + matchedFields: String): Throwable = { + new RuntimeException(s""" + |Found duplicate field(s) "$requiredId": $matchedFields + |in id mapping mode + """.stripMargin.replaceAll("\n", " ")) + } + + // The followings are copied from org.apache.spark.sql.execution.datasources.parquet.ParquetUtils + // TODO: remove after dropping Spark 3.2.0 support and directly use ParquetUtils + /** + * A StructField metadata key used to set the field id of a column in the Parquet schema. + */ + val FIELD_ID_METADATA_KEY = "parquet.field.id" + + /** + * Whether there exists a field in the schema, whether inner or leaf, has the parquet field ID + * metadata. + */ + def hasFieldIds(schema: StructType): Boolean = { + def recursiveCheck(schema: DataType): Boolean = { + schema match { + case st: StructType => + st.exists(field => hasFieldId(field) || recursiveCheck(field.dataType)) + + case at: ArrayType => recursiveCheck(at.elementType) + + case mt: MapType => recursiveCheck(mt.keyType) || recursiveCheck(mt.valueType) + + case _ => + // No need to really check primitive types, just to terminate the recursion + false + } + } + if (schema.isEmpty) false else recursiveCheck(schema) + } + + def hasFieldId(field: StructField): Boolean = + field.metadata.contains(FIELD_ID_METADATA_KEY) + + def getFieldId(field: StructField): Int = { + require( + hasFieldId(field), + s"The key `$FIELD_ID_METADATA_KEY` doesn't exist in the metadata of " + field) + try { + Math.toIntExact(field.metadata.getLong(FIELD_ID_METADATA_KEY)) + } catch { + case _: ArithmeticException | _: ClassCastException => + throw new IllegalArgumentException( + s"The key `$FIELD_ID_METADATA_KEY` must be a 32-bit integer") + } + } +} diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala index d5376a1be..60e21765b 100644 --- a/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimResolveDefaultColumns.scala @@ -19,7 +19,6 @@ package org.apache.comet.shims -import scala.util.Try import org.apache.spark.sql.catalyst.util.ResolveDefaultColumns import org.apache.spark.sql.types.{StructField, StructType} diff --git a/common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala b/common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala new file mode 100644 index 000000000..0aab00740 --- /dev/null +++ b/common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala @@ -0,0 +1,21 @@ +package org.apache.spark.sql.comet.parquet + +import org.apache.spark.sql.errors.QueryExecutionErrors +import org.apache.spark.sql.execution.datasources.parquet.ParquetUtils +import org.apache.spark.sql.types._ + +trait ShimCometParquetUtils { + def foundDuplicateFieldInFieldIdLookupModeError( + requiredId: Int, + matchedFields: String): Throwable = { + QueryExecutionErrors.foundDuplicateFieldInFieldIdLookupModeError(requiredId, matchedFields) + } + + val FIELD_ID_METADATA_KEY = ParquetUtils.FIELD_ID_METADATA_KEY + + def hasFieldIds(schema: StructType): Boolean = ParquetUtils.hasFieldIds(schema) + + def hasFieldId(field: StructField): Boolean = ParquetUtils.hasFieldId(field) + + def getFieldId(field: StructField): Int = ParquetUtils.getFieldId (field) +} diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala b/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala index d2b844985..544c4c5c6 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala @@ -43,7 +43,7 @@ import org.apache.spark.util.collection._ import org.apache.comet.{CometConf, MetricsSupport} import org.apache.comet.parquet.{CometParquetFileFormat, CometParquetPartitionReaderFactory} -import org.apache.comet.shims.{ShimCometScanExec, ShimFileFormat} +import org.apache.comet.shims.ShimFileFormat /** * Comet physical scan node for DataSource V1. Most of the code here follow Spark's diff --git a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimCometScanExec.scala similarity index 99% rename from spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometScanExec.scala rename to spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimCometScanExec.scala index c2d775889..7525c3a07 100644 --- a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimCometScanExec.scala @@ -17,7 +17,7 @@ * under the License. */ -package org.apache.comet.shims +package org.apache.spark.sql.comet import scala.language.implicitConversions diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBatchScanExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBatchScanExec.scala index 9e7cc3ba5..167b539f8 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBatchScanExec.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBatchScanExec.scala @@ -26,20 +26,9 @@ import org.apache.spark.sql.execution.datasources.v2.BatchScanExec trait ShimCometBatchScanExec { def wrapped: BatchScanExec - // Only for Spark 3.3+ - def keyGroupedPartitioning: Option[Seq[Expression]] = wrapped.getClass.getDeclaredMethods - .filter(_.getName == "keyGroupedPartitioning") - .flatMap(_.invoke(wrapped).asInstanceOf[Option[Seq[Expression]]]) - .headOption + def keyGroupedPartitioning: Option[Seq[Expression]] = wrapped.keyGroupedPartitioning - // Only for Spark 3.3+ - def inputPartitions: Seq[InputPartition] = wrapped.getClass.getDeclaredMethods - .filter(_.getName == "inputPartitions") - .flatMap(_.invoke(wrapped).asInstanceOf[Seq[InputPartition]]) + def inputPartitions: Seq[InputPartition] = wrapped.inputPartitions - // Only for Spark 3.4+ - def ordering: Option[Seq[SortOrder]] = wrapped.getClass.getDeclaredMethods - .filter(_.getName == "ordering") - .flatMap(_.invoke(wrapped).asInstanceOf[Option[Seq[SortOrder]]]) - .headOption + def ordering: Option[Seq[SortOrder]] = wrapped.ordering } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala index c69da2a10..559e327b4 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala @@ -27,19 +27,14 @@ import org.apache.spark.sql.execution.exchange.ShuffleExchangeExec import org.apache.spark.sql.types.StructType trait ShimCometShuffleExchangeExec { - // TODO: remove after dropping Spark 3.2 and 3.3 support def apply(s: ShuffleExchangeExec, shuffleType: ShuffleType): CometShuffleExchangeExec = { - val advisoryPartitionSize = s.getClass.getDeclaredMethods - .filter(_.getName == "advisoryPartitionSize") - .flatMap(_.invoke(s).asInstanceOf[Option[Long]]) - .headOption CometShuffleExchangeExec( s.outputPartitioning, s.child, s, s.shuffleOrigin, shuffleType, - advisoryPartitionSize) + s.advisoryPartitionSize) } protected def fromAttributes(attributes: Seq[Attribute]): StructType = DataTypeUtils.fromAttributes(attributes) diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala index ffec1bd40..4e87559af 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala @@ -26,14 +26,7 @@ import org.apache.spark.sql.execution.datasources.v2.parquet.ParquetScan trait ShimCometSparkSessionExtensions { import org.apache.comet.shims.ShimCometSparkSessionExtensions._ - /** - * TODO: delete after dropping Spark 3.2.0 support and directly call scan.pushedAggregate - */ - def getPushedAggregate(scan: ParquetScan): Option[Aggregation] = scan.getClass.getDeclaredFields - .filter(_.getName == "pushedAggregate") - .map { a => a.setAccessible(true); a } - .flatMap(_.get(scan).asInstanceOf[Option[Aggregation]]) - .headOption + def getPushedAggregate(scan: ParquetScan): Option[Aggregation] = scan.pushedAggregate /** * TODO: delete after dropping Spark 3.2 and 3.3 support @@ -50,18 +43,5 @@ object ShimCometSparkSessionExtensions { .map(_.asInstanceOf[Int]) .headOption - // Extended info is available only since Spark 4.0.0 - // (https://issues.apache.org/jira/browse/SPARK-47289) - def supportsExtendedExplainInfo(qe: QueryExecution): Boolean = { - try { - // Look for QueryExecution.extendedExplainInfo(scala.Function1[String, Unit], SparkPlan) - qe.getClass.getDeclaredMethod( - "extendedExplainInfo", - classOf[String => Unit], - classOf[SparkPlan]) - } catch { - case _: NoSuchMethodException | _: SecurityException => return false - } - true - } + def supportsExtendedExplainInfo(qe: QueryExecution): Boolean = true } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala index 2e1c681c7..c97dbfc88 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala @@ -23,13 +23,5 @@ import org.apache.spark.sql.execution.TakeOrderedAndProjectExec trait ShimCometTakeOrderedAndProjectExec { - /** - * TODO: delete after dropping Spark 3.2 and 3.3 support - */ - protected def getOffset(plan: TakeOrderedAndProjectExec): Option[Int] = { - plan.getClass.getDeclaredFields - .filter(_.getName == "offset") - .map { a => a.setAccessible(true); a.get(plan).asInstanceOf[Int] } - .headOption - } + protected def getOffset(plan: TakeOrderedAndProjectExec): Option[Int] = Some(plan.offset) } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala index ef337a0da..8511721c5 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala @@ -24,13 +24,6 @@ import org.apache.spark.sql.internal.LegacyBehaviorPolicy trait ShimSQLConf { - /** - * Spark 3.4 renamed parquetFilterPushDownStringStartWith to - * parquetFilterPushDownStringPredicate - * - * TODO: delete after dropping Spark 3.2 & 3.3 support and simply use - * parquetFilterPushDownStringPredicate - */ protected def getPushDownStringPredicate(sqlConf: SQLConf): Boolean = sqlConf.parquetFilterPushDownStringPredicate diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimCometScanExec.scala similarity index 62% rename from spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala rename to spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimCometScanExec.scala index bee0527db..634a38407 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimCometScanExec.scala @@ -17,23 +17,22 @@ * under the License. */ -package org.apache.comet.shims - -import scala.language.implicitConversions +package org.apache.spark.sql.comet import org.apache.hadoop.fs.Path -import org.apache.spark.{SparkContext, SparkException} import org.apache.spark.sql.SparkSession import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.AttributeReference import org.apache.spark.sql.connector.read.{InputPartition, PartitionReaderFactory} -import org.apache.spark.sql.execution.{FileSourceScanExec, PartitionedFileUtil} -import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, FileStatusWithMetadata, PartitionDirectory, PartitionedFile} +import org.apache.spark.sql.errors.QueryExecutionErrors import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.datasources.v2.DataSourceRDD +import org.apache.spark.sql.execution.datasources._ import org.apache.spark.sql.execution.metric.SQLMetric -import org.apache.spark.sql.types.{LongType, StructField, StructType} +import org.apache.spark.sql.execution.{FileSourceScanExec, PartitionedFileUtil} +import org.apache.spark.sql.types.StructType +import org.apache.spark.SparkContext trait ShimCometScanExec { def wrapped: FileSourceScanExec @@ -44,24 +43,16 @@ trait ShimCometScanExec { .map { a => a.setAccessible(true); a } .flatMap(_.invoke(wrapped).asInstanceOf[Seq[AttributeReference]]) - // TODO: remove after dropping Spark 3.2 and 3.3 support and directly call - // wrapped.fileConstantMetadataColumns lazy val fileConstantMetadataColumns: Seq[AttributeReference] = - wrapped.getClass.getDeclaredMethods - .filter(_.getName == "fileConstantMetadataColumns") - .map { a => a.setAccessible(true); a } - .flatMap(_.invoke(wrapped).asInstanceOf[Seq[AttributeReference]]) + wrapped.fileConstantMetadataColumns - // TODO: remove after dropping Spark 3.2 support and directly call new DataSourceRDD protected def newDataSourceRDD( sc: SparkContext, inputPartitions: Seq[Seq[InputPartition]], partitionReaderFactory: PartitionReaderFactory, columnarReads: Boolean, - customMetrics: Map[String, SQLMetric]): DataSourceRDD = { - implicit def flattenSeq(p: Seq[Seq[InputPartition]]): Seq[InputPartition] = p.flatten + customMetrics: Map[String, SQLMetric]): DataSourceRDD = new DataSourceRDD(sc, inputPartitions, partitionReaderFactory, columnarReads, customMetrics) - } // TODO: remove after dropping Spark 3.2 support and directly call new FileScanRDD protected def newFileScanRDD( @@ -89,40 +80,11 @@ trait ShimCometScanExec { .last .asInstanceOf[FileScanRDD] - // TODO: remove after dropping Spark 3.2 and 3.3 support and directly call - // QueryExecutionErrors.SparkException - protected def invalidBucketFile(path: String, sparkVersion: String): Throwable = { - if (sparkVersion >= "3.3") { - val messageParameters = if (sparkVersion >= "3.4") Map("path" -> path) else Array(path) - classOf[SparkException].getDeclaredConstructors - .filter(_.getParameterCount == 3) - .map(_.newInstance("INVALID_BUCKET_FILE", messageParameters, null)) - .last - .asInstanceOf[SparkException] - } else { // Spark 3.2 - new IllegalStateException(s"Invalid bucket file ${path}") - } - } - - // Copied from Spark 3.4 RowIndexUtil due to PARQUET-2161 (tracked in SPARK-39634) - // TODO: remove after PARQUET-2161 becomes available in Parquet - private def findRowIndexColumnIndexInSchema(sparkSchema: StructType): Int = { - sparkSchema.fields.zipWithIndex.find { case (field: StructField, _: Int) => - field.name == ShimFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME - } match { - case Some((field: StructField, idx: Int)) => - if (field.dataType != LongType) { - throw new RuntimeException( - s"${ShimFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME} must be of LongType") - } - idx - case _ => -1 - } - } + protected def invalidBucketFile(path: String, sparkVersion: String): Throwable = + QueryExecutionErrors.invalidBucketFile(path) - protected def isNeededForSchema(sparkSchema: StructType): Boolean = { - findRowIndexColumnIndexInSchema(sparkSchema) >= 0 - } + // see SPARK-39634 + protected def isNeededForSchema(sparkSchema: StructType): Boolean = false protected def getPartitionedFile(f: FileStatusWithMetadata, p: PartitionDirectory): PartitionedFile = PartitionedFileUtil.getPartitionedFile(f, p.values, 0, f.getLen) diff --git a/spark/src/test/scala/org/apache/spark/sql/benchmark/CometReadBenchmark.scala b/spark/src/test/scala/org/apache/spark/sql/benchmark/CometReadBenchmark.scala index 4c2f832af..722e6cc3b 100644 --- a/spark/src/test/scala/org/apache/spark/sql/benchmark/CometReadBenchmark.scala +++ b/spark/src/test/scala/org/apache/spark/sql/benchmark/CometReadBenchmark.scala @@ -25,11 +25,12 @@ import scala.collection.JavaConverters._ import scala.util.Random import org.apache.spark.benchmark.Benchmark +import org.apache.spark.comet.ShimTestUtils import org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader import org.apache.spark.sql.types._ import org.apache.spark.sql.vectorized.ColumnVector -import org.apache.comet.{CometConf, TestUtils} +import org.apache.comet.CometConf import org.apache.comet.parquet.BatchReader /** @@ -123,7 +124,7 @@ object CometReadBenchmark extends CometBenchmarkBase { (col: ColumnVector, i: Int) => longSum += col.getUTF8String(i).toLongExact } - val files = TestUtils.listDirectory(new File(dir, "parquetV1")) + val files = ShimTestUtils.listDirectory(new File(dir, "parquetV1")) sqlBenchmark.addCase("ParquetReader Spark") { _ => files.map(_.asInstanceOf[String]).foreach { p => diff --git a/spark/src/test/spark-3.3/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala b/spark/src/test/spark-3.3/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala deleted file mode 100644 index 15edd486c..000000000 --- a/spark/src/test/spark-3.3/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala +++ /dev/null @@ -1,9 +0,0 @@ -package org.apache.comet.shims - -import org.apache.spark.sql.{SQLQueryTestHelper, SparkSession} - -trait ShimCometTPCHQuerySuite extends SQLQueryTestHelper { - protected def getNormalizedQueryExecutionResult(session: SparkSession, sql: String): (String, Seq[String]) = { - getNormalizedResult(session, sql) - } -} diff --git a/spark/src/test/spark-3.4/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala b/spark/src/test/spark-3.4/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala deleted file mode 100644 index 15edd486c..000000000 --- a/spark/src/test/spark-3.4/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala +++ /dev/null @@ -1,9 +0,0 @@ -package org.apache.comet.shims - -import org.apache.spark.sql.{SQLQueryTestHelper, SparkSession} - -trait ShimCometTPCHQuerySuite extends SQLQueryTestHelper { - protected def getNormalizedQueryExecutionResult(session: SparkSession, sql: String): (String, Seq[String]) = { - getNormalizedResult(session, sql) - } -} diff --git a/spark/src/test/spark-3.2/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala b/spark/src/test/spark-3.x/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala similarity index 100% rename from spark/src/test/spark-3.2/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala rename to spark/src/test/spark-3.x/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala diff --git a/spark/src/test/scala/org/apache/comet/TestUtils.scala b/spark/src/test/spark-3.x/org/apache/spark/comet/ShimTestUtils.scala similarity index 96% rename from spark/src/test/scala/org/apache/comet/TestUtils.scala rename to spark/src/test/spark-3.x/org/apache/spark/comet/ShimTestUtils.scala index d4e771568..34cf5b498 100644 --- a/spark/src/test/scala/org/apache/comet/TestUtils.scala +++ b/spark/src/test/spark-3.x/org/apache/spark/comet/ShimTestUtils.scala @@ -17,13 +17,12 @@ * under the License. */ -package org.apache.comet +package org.apache.spark.comet import java.io.File - import scala.collection.mutable.ArrayBuffer -object TestUtils { +object ShimTestUtils { /** * Spark 3.3.0 moved {{{SpecificParquetRecordReaderBase.listDirectory}}} to diff --git a/spark/src/test/spark-4.0/org/apache/spark/comet/ShimTestUtils.scala b/spark/src/test/spark-4.0/org/apache/spark/comet/ShimTestUtils.scala new file mode 100644 index 000000000..fcb8e0a14 --- /dev/null +++ b/spark/src/test/spark-4.0/org/apache/spark/comet/ShimTestUtils.scala @@ -0,0 +1,28 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.spark.comet + +import java.io.File + +object ShimTestUtils { + + def listDirectory(path: File): Array[String] = + org.apache.spark.TestUtils.listDirectory(path) +} From 57d6538ab52008a47827ac10c1d2546af1cad1de Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 8 May 2024 01:59:08 -0700 Subject: [PATCH 07/68] build: Add spark-4.0 profile --- .../main/scala/org/apache/spark/Plugins.scala | 22 ++++--------------- .../spark/sql/comet/DecimalPrecision.scala | 10 +-------- .../spark/comet/ShimCometDriverPlugin.scala | 17 ++++++++++++++ .../sql/comet/ShimDecimalPrecision.scala | 14 ++++++++++++ .../spark/comet/ShimCometDriverPlugin.scala | 13 +++++++++++ .../sql/comet/ShimDecimalPrecision.scala | 10 +++++++++ 6 files changed, 59 insertions(+), 27 deletions(-) create mode 100644 spark/src/main/spark-3.x/org/apache/spark/comet/ShimCometDriverPlugin.scala create mode 100644 spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimDecimalPrecision.scala create mode 100644 spark/src/main/spark-4.0/org/apache/spark/comet/ShimCometDriverPlugin.scala create mode 100644 spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimDecimalPrecision.scala diff --git a/spark/src/main/scala/org/apache/spark/Plugins.scala b/spark/src/main/scala/org/apache/spark/Plugins.scala index acfa313f9..8a7f20932 100644 --- a/spark/src/main/scala/org/apache/spark/Plugins.scala +++ b/spark/src/main/scala/org/apache/spark/Plugins.scala @@ -23,6 +23,7 @@ import java.{util => ju} import java.util.Collections import org.apache.spark.api.plugin.{DriverPlugin, ExecutorPlugin, PluginContext, SparkPlugin} +import org.apache.spark.comet.ShimCometDriverPlugin import org.apache.spark.internal.Logging import org.apache.spark.internal.config.{EXECUTOR_MEMORY, EXECUTOR_MEMORY_OVERHEAD} @@ -39,9 +40,7 @@ import org.apache.comet.{CometConf, CometSparkSessionExtensions} * * To enable this plugin, set the config "spark.plugins" to `org.apache.spark.CometPlugin`. */ -class CometDriverPlugin extends DriverPlugin with Logging { - import CometDriverPlugin._ - +class CometDriverPlugin extends DriverPlugin with Logging with ShimCometDriverPlugin { override def init(sc: SparkContext, pluginContext: PluginContext): ju.Map[String, String] = { logInfo("CometDriverPlugin init") @@ -51,12 +50,8 @@ class CometDriverPlugin extends DriverPlugin with Logging { } else { // By default, executorMemory * spark.executor.memoryOverheadFactor, with minimum of 384MB val executorMemory = sc.getConf.getSizeAsMb(EXECUTOR_MEMORY.key) - val memoryOverheadFactor = - sc.getConf.getDouble( - EXECUTOR_MEMORY_OVERHEAD_FACTOR, - EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT) - val memoryOverheadMinMib = - sc.getConf.getLong(EXECUTOR_MIN_MEMORY_OVERHEAD, EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT) + val memoryOverheadFactor = getMemoryOverheadFactor(sc.getConf) + val memoryOverheadMinMib = getMemoryOverheadMinMib(sc.getConf) Math.max((executorMemory * memoryOverheadFactor).toLong, memoryOverheadMinMib) } @@ -99,15 +94,6 @@ class CometDriverPlugin extends DriverPlugin with Logging { } } -object CometDriverPlugin { - // `org.apache.spark.internal.config.EXECUTOR_MEMORY_OVERHEAD_FACTOR` was added since Spark 3.3.0 - val EXECUTOR_MEMORY_OVERHEAD_FACTOR = "spark.executor.memoryOverheadFactor" - val EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT = 0.1 - // `org.apache.spark.internal.config.EXECUTOR_MIN_MEMORY_OVERHEAD` was added since Spark 4.0.0 - val EXECUTOR_MIN_MEMORY_OVERHEAD = "spark.executor.minMemoryOverhead" - val EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT = 384L -} - /** * The Comet plugin for Spark. To enable this plugin, set the config "spark.plugins" to * `org.apache.spark.CometPlugin` diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala b/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala index 6e5dde9c7..c8a90b258 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala @@ -40,7 +40,7 @@ import org.apache.spark.sql.types.DecimalType * TODO: instead of relying on this rule, it's probably better to enhance arithmetic kernels to * handle different decimal precisions */ -object DecimalPrecision { +object DecimalPrecision extends ShimDecimalPrecision { def promote( allowPrecisionLoss: Boolean, expr: Expression, @@ -107,12 +107,4 @@ object DecimalPrecision { case e => e } } - - // `org.apache.spark.sql.types.DecimalExpression` is added in Spark 3.5 - object DecimalExpression { - def unapply(e: Expression): Option[(Int, Int)] = e.dataType match { - case t: DecimalType => Some((t.precision, t.scale)) - case _ => None - } - } } diff --git a/spark/src/main/spark-3.x/org/apache/spark/comet/ShimCometDriverPlugin.scala b/spark/src/main/spark-3.x/org/apache/spark/comet/ShimCometDriverPlugin.scala new file mode 100644 index 000000000..ebf0c689a --- /dev/null +++ b/spark/src/main/spark-3.x/org/apache/spark/comet/ShimCometDriverPlugin.scala @@ -0,0 +1,17 @@ +package org.apache.spark.comet + +trait ShimCometDriverPlugin { + // `org.apache.spark.internal.config.EXECUTOR_MEMORY_OVERHEAD_FACTOR` was added since Spark 3.3.0 + private val EXECUTOR_MEMORY_OVERHEAD_FACTOR = "spark.executor.memoryOverheadFactor" + private val EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT = 0.1 + // `org.apache.spark.internal.config.EXECUTOR_MIN_MEMORY_OVERHEAD` was added since Spark 4.0.0 + private val EXECUTOR_MIN_MEMORY_OVERHEAD = "spark.executor.minMemoryOverhead" + private val EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT = 384L + + def getMemoryOverheadFactor = + sc.getConf.getDouble( + EXECUTOR_MEMORY_OVERHEAD_FACTOR, + EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT) + def getMemoryOverheadMinMib = + sc.getConf.getLong(EXECUTOR_MIN_MEMORY_OVERHEAD, EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT) +} diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimDecimalPrecision.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimDecimalPrecision.scala new file mode 100644 index 000000000..2cd53ca68 --- /dev/null +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimDecimalPrecision.scala @@ -0,0 +1,14 @@ +package org.apache.spark.sql.comet + +import org.apache.spark.sql.catalyst.expressions.Expression +import org.apache.spark.sql.types.DecimalType + +trait ShimDecimalPrecision { + // `org.apache.spark.sql.types.DecimalExpression` is added in Spark 3.5 + object DecimalExpression { + def unapply(e: Expression): Option[(Int, Int)] = e.dataType match { + case t: DecimalType => Some((t.precision, t.scale)) + case _ => None + } + } +} diff --git a/spark/src/main/spark-4.0/org/apache/spark/comet/ShimCometDriverPlugin.scala b/spark/src/main/spark-4.0/org/apache/spark/comet/ShimCometDriverPlugin.scala new file mode 100644 index 000000000..d97cac15c --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/spark/comet/ShimCometDriverPlugin.scala @@ -0,0 +1,13 @@ +package org.apache.spark.comet + +import org.apache.spark.SparkConf +import org.apache.spark.internal.config.EXECUTOR_MEMORY_OVERHEAD_FACTOR +import org.apache.spark.internal.config.EXECUTOR_MIN_MEMORY_OVERHEAD + +trait ShimCometDriverPlugin { + def getMemoryOverheadFactor(sparkConf: SparkConf): Double = sparkConf.get( + EXECUTOR_MEMORY_OVERHEAD_FACTOR) + + def getMemoryOverheadMinMib(sparkConf: SparkConf): Long = sparkConf.get( + EXECUTOR_MIN_MEMORY_OVERHEAD) +} diff --git a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimDecimalPrecision.scala b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimDecimalPrecision.scala new file mode 100644 index 000000000..5afbde6c8 --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimDecimalPrecision.scala @@ -0,0 +1,10 @@ +package org.apache.spark.sql.comet + +import org.apache.spark.sql.catalyst.expressions.Expression + +trait ShimDecimalPrecision { + object DecimalExpression { + def unapply(e: Expression): Option[(Int, Int)] = + org.apache.spark.sql.types.DecimalExpression.unapply(e) + } +} From d3efeb876711cf6a7dba3e1fc36d7abfac874574 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 8 May 2024 02:30:34 -0700 Subject: [PATCH 08/68] build: Add spark-4.0 profile --- .../comet/parquet/ShimCometParquetUtils.scala | 19 +++++++ .../comet/parquet/ShimCometParquetUtils.scala | 19 +++++++ .../main/scala/org/apache/spark/Plugins.scala | 2 +- .../comet/CometBroadcastExchangeExec.scala | 2 +- .../spark/sql/comet/CometScanExec.scala | 3 +- .../spark/sql/comet/DecimalPrecision.scala | 1 + .../ShimCometSparkSessionExtensions.scala | 5 -- .../spark/comet/ShimCometDriverPlugin.scala | 17 ------- .../ShimCometBroadcastExchangeExec.scala | 2 +- .../comet/shims/ShimCometDriverPlugin.scala | 36 ++++++++++++++ .../sql/comet/ShimDecimalPrecision.scala | 14 ------ .../comet/{ => shims}/ShimCometScanExec.scala | 10 ++-- .../comet/shims/ShimDecimalPrecision.scala | 33 +++++++++++++ .../ShimCometBroadcastHashJoinExec.scala | 20 +++----- .../ShimCometSparkSessionExtensions.scala | 21 ++------ .../ShimCometTakeOrderedAndProjectExec.scala | 1 - .../comet/shims/ShimQueryPlanSerde.scala | 49 +++---------------- .../org/apache/comet/shims/ShimSQLConf.scala | 1 - .../spark/comet/ShimCometDriverPlugin.scala | 13 ----- .../ShimCometBroadcastExchangeExec.scala | 27 ++-------- .../comet/shims/ShimCometDriverPlugin.scala | 32 ++++++++++++ .../sql/comet/ShimDecimalPrecision.scala | 10 ---- .../comet/{ => shims}/ShimCometScanExec.scala | 40 +++++---------- .../comet/shims/ShimDecimalPrecision.scala | 29 +++++++++++ .../org/apache/spark/sql/CometTestBase.scala | 1 - .../comet/shims/ShimCometTPCHQuerySuite.scala | 19 +++++++ .../comet/shims/ShimCometTPCHQuerySuite.scala | 19 +++++++ 27 files changed, 250 insertions(+), 195 deletions(-) delete mode 100644 spark/src/main/spark-3.x/org/apache/spark/comet/ShimCometDriverPlugin.scala rename spark/src/main/spark-3.x/org/apache/{ => spark}/comet/shims/ShimCometBroadcastExchangeExec.scala (98%) create mode 100644 spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala delete mode 100644 spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimDecimalPrecision.scala rename spark/src/main/spark-3.x/org/apache/spark/sql/comet/{ => shims}/ShimCometScanExec.scala (94%) create mode 100644 spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala delete mode 100644 spark/src/main/spark-4.0/org/apache/spark/comet/ShimCometDriverPlugin.scala rename spark/src/main/spark-4.0/org/apache/{ => spark}/comet/shims/ShimCometBroadcastExchangeExec.scala (52%) create mode 100644 spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala delete mode 100644 spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimDecimalPrecision.scala rename spark/src/main/spark-4.0/org/apache/spark/sql/comet/{ => shims}/ShimCometScanExec.scala (73%) create mode 100644 spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala diff --git a/common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala b/common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala index bee6a8e8d..2ca4d2f7e 100644 --- a/common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala +++ b/common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala @@ -1,3 +1,22 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + package org.apache.spark.sql.comet.parquet import org.apache.spark.sql.types._ diff --git a/common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala b/common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala index 0aab00740..7115ba779 100644 --- a/common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala +++ b/common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala @@ -1,3 +1,22 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + package org.apache.spark.sql.comet.parquet import org.apache.spark.sql.errors.QueryExecutionErrors diff --git a/spark/src/main/scala/org/apache/spark/Plugins.scala b/spark/src/main/scala/org/apache/spark/Plugins.scala index 8a7f20932..dcc00f66c 100644 --- a/spark/src/main/scala/org/apache/spark/Plugins.scala +++ b/spark/src/main/scala/org/apache/spark/Plugins.scala @@ -23,7 +23,7 @@ import java.{util => ju} import java.util.Collections import org.apache.spark.api.plugin.{DriverPlugin, ExecutorPlugin, PluginContext, SparkPlugin} -import org.apache.spark.comet.ShimCometDriverPlugin +import org.apache.spark.comet.shims.ShimCometDriverPlugin import org.apache.spark.internal.Logging import org.apache.spark.internal.config.{EXECUTOR_MEMORY, EXECUTOR_MEMORY_OVERHEAD} diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/CometBroadcastExchangeExec.scala b/spark/src/main/scala/org/apache/spark/sql/comet/CometBroadcastExchangeExec.scala index 06c5898f7..e6cd99b82 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/CometBroadcastExchangeExec.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/CometBroadcastExchangeExec.scala @@ -27,6 +27,7 @@ import scala.concurrent.duration.NANOSECONDS import scala.util.control.NonFatal import org.apache.spark.{broadcast, Partition, SparkContext, TaskContext} +import org.apache.spark.comet.shims.ShimCometBroadcastExchangeExec import org.apache.spark.launcher.SparkLauncher import org.apache.spark.rdd.RDD import org.apache.spark.sql.catalyst.InternalRow @@ -44,7 +45,6 @@ import org.apache.spark.util.io.ChunkedByteBuffer import com.google.common.base.Objects import org.apache.comet.CometRuntimeException -import org.apache.comet.shims.ShimCometBroadcastExchangeExec /** * A [[CometBroadcastExchangeExec]] collects, transforms and finally broadcasts the result of a diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala b/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala index 544c4c5c6..aa05f5443 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala @@ -32,6 +32,7 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.QueryPlan import org.apache.spark.sql.catalyst.plans.physical._ import org.apache.spark.sql.catalyst.util.CaseInsensitiveMap +import org.apache.spark.sql.comet.shims.ShimCometScanExec import org.apache.spark.sql.execution._ import org.apache.spark.sql.execution.datasources._ import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions @@ -406,7 +407,7 @@ case class CometScanExec( Map.empty) } else { newFileScanRDD( - fsRelation.sparkSession, + fsRelation, readFile, partitions, new StructType(requiredSchema.fields ++ fsRelation.partitionSchema.fields), diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala b/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala index c8a90b258..baeb4de03 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala @@ -22,6 +22,7 @@ package org.apache.spark.sql.comet import scala.math.{max, min} import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.comet.shims.ShimDecimalPrecision import org.apache.spark.sql.types.DecimalType /** diff --git a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala index ffec1bd40..7171f8190 100644 --- a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala +++ b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala @@ -24,8 +24,6 @@ import org.apache.spark.sql.execution.{LimitExec, QueryExecution, SparkPlan} import org.apache.spark.sql.execution.datasources.v2.parquet.ParquetScan trait ShimCometSparkSessionExtensions { - import org.apache.comet.shims.ShimCometSparkSessionExtensions._ - /** * TODO: delete after dropping Spark 3.2.0 support and directly call scan.pushedAggregate */ @@ -40,9 +38,6 @@ trait ShimCometSparkSessionExtensions { */ def getOffset(limit: LimitExec): Int = getOffsetOpt(limit).getOrElse(0) -} - -object ShimCometSparkSessionExtensions { private def getOffsetOpt(plan: SparkPlan): Option[Int] = plan.getClass.getDeclaredFields .filter(_.getName == "offset") .map { a => a.setAccessible(true); a.get(plan) } diff --git a/spark/src/main/spark-3.x/org/apache/spark/comet/ShimCometDriverPlugin.scala b/spark/src/main/spark-3.x/org/apache/spark/comet/ShimCometDriverPlugin.scala deleted file mode 100644 index ebf0c689a..000000000 --- a/spark/src/main/spark-3.x/org/apache/spark/comet/ShimCometDriverPlugin.scala +++ /dev/null @@ -1,17 +0,0 @@ -package org.apache.spark.comet - -trait ShimCometDriverPlugin { - // `org.apache.spark.internal.config.EXECUTOR_MEMORY_OVERHEAD_FACTOR` was added since Spark 3.3.0 - private val EXECUTOR_MEMORY_OVERHEAD_FACTOR = "spark.executor.memoryOverheadFactor" - private val EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT = 0.1 - // `org.apache.spark.internal.config.EXECUTOR_MIN_MEMORY_OVERHEAD` was added since Spark 4.0.0 - private val EXECUTOR_MIN_MEMORY_OVERHEAD = "spark.executor.minMemoryOverhead" - private val EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT = 384L - - def getMemoryOverheadFactor = - sc.getConf.getDouble( - EXECUTOR_MEMORY_OVERHEAD_FACTOR, - EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT) - def getMemoryOverheadMinMib = - sc.getConf.getLong(EXECUTOR_MIN_MEMORY_OVERHEAD, EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT) -} diff --git a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometBroadcastExchangeExec.scala b/spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometBroadcastExchangeExec.scala similarity index 98% rename from spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometBroadcastExchangeExec.scala rename to spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometBroadcastExchangeExec.scala index 63ff2a2c1..aede47951 100644 --- a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometBroadcastExchangeExec.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometBroadcastExchangeExec.scala @@ -17,7 +17,7 @@ * under the License. */ -package org.apache.comet.shims +package org.apache.spark.comet.shims import scala.reflect.ClassTag diff --git a/spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala b/spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala new file mode 100644 index 000000000..1cdf0108f --- /dev/null +++ b/spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala @@ -0,0 +1,36 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.spark.comet.shims + +trait ShimCometDriverPlugin { + // `org.apache.spark.internal.config.EXECUTOR_MEMORY_OVERHEAD_FACTOR` was added since Spark 3.3.0 + private val EXECUTOR_MEMORY_OVERHEAD_FACTOR = "spark.executor.memoryOverheadFactor" + private val EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT = 0.1 + // `org.apache.spark.internal.config.EXECUTOR_MIN_MEMORY_OVERHEAD` was added since Spark 4.0.0 + private val EXECUTOR_MIN_MEMORY_OVERHEAD = "spark.executor.minMemoryOverhead" + private val EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT = 384L + + def getMemoryOverheadFactor = + sc.getConf.getDouble( + EXECUTOR_MEMORY_OVERHEAD_FACTOR, + EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT) + def getMemoryOverheadMinMib = + sc.getConf.getLong(EXECUTOR_MIN_MEMORY_OVERHEAD, EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT) +} diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimDecimalPrecision.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimDecimalPrecision.scala deleted file mode 100644 index 2cd53ca68..000000000 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimDecimalPrecision.scala +++ /dev/null @@ -1,14 +0,0 @@ -package org.apache.spark.sql.comet - -import org.apache.spark.sql.catalyst.expressions.Expression -import org.apache.spark.sql.types.DecimalType - -trait ShimDecimalPrecision { - // `org.apache.spark.sql.types.DecimalExpression` is added in Spark 3.5 - object DecimalExpression { - def unapply(e: Expression): Option[(Int, Int)] = e.dataType match { - case t: DecimalType => Some((t.precision, t.scale)) - case _ => None - } - } -} diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimCometScanExec.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala similarity index 94% rename from spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimCometScanExec.scala rename to spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala index 7525c3a07..6da114ac2 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/ShimCometScanExec.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala @@ -17,7 +17,7 @@ * under the License. */ -package org.apache.spark.sql.comet +package org.apache.spark.sql.comet.shims import scala.language.implicitConversions @@ -65,7 +65,7 @@ trait ShimCometScanExec { // TODO: remove after dropping Spark 3.2 support and directly call new FileScanRDD protected def newFileScanRDD( - sparkSession: SparkSession, + fsRelation: HadoopFsRelation, readFunction: PartitionedFile => Iterator[InternalRow], filePartitions: Seq[FilePartition], readSchema: StructType, @@ -73,12 +73,12 @@ trait ShimCometScanExec { classOf[FileScanRDD].getDeclaredConstructors .map { c => c.getParameterCount match { - case 3 => c.newInstance(sparkSession, readFunction, filePartitions) + case 3 => c.newInstance(fsRelation.sparkSession, readFunction, filePartitions) case 5 => - c.newInstance(sparkSession, readFunction, filePartitions, readSchema, metadataColumns) + c.newInstance(fsRelation.sparkSession, readFunction, filePartitions, readSchema, metadataColumns) case 6 => c.newInstance( - sparkSession, + fsRelation.sparkSession, readFunction, filePartitions, readSchema, diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala new file mode 100644 index 000000000..28416ff8c --- /dev/null +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala @@ -0,0 +1,33 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.spark.sql.comet.shims + +import org.apache.spark.sql.catalyst.expressions.Expression +import org.apache.spark.sql.types.DecimalType + +trait ShimDecimalPrecision { + // `org.apache.spark.sql.types.DecimalExpression` is added in Spark 3.5 + object DecimalExpression { + def unapply(e: Expression): Option[(Int, Int)] = e.dataType match { + case t: DecimalType => Some((t.precision, t.scale)) + case _ => None + } + } +} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala index eef0ee9d5..2bcd7fd96 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala @@ -20,20 +20,12 @@ package org.apache.comet.shims import org.apache.spark.sql.catalyst.expressions.Expression -import org.apache.spark.sql.catalyst.plans.physical.Partitioning +import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioningLike, Partitioning} trait ShimCometBroadcastHashJoinExec { - - /** - * Returns the expressions that are used for hash partitioning including `HashPartitioning` and - * `CoalescedHashPartitioning`. They shares same trait `HashPartitioningLike` since Spark 3.4, - * but Spark 3.2/3.3 doesn't have `HashPartitioningLike` and `CoalescedHashPartitioning`. - * - * TODO: remove after dropping Spark 3.2 and 3.3 support. - */ - def getHashPartitioningLikeExpressions(partitioning: Partitioning): Seq[Expression] = { - partitioning.getClass.getDeclaredMethods - .filter(_.getName == "expressions") - .flatMap(_.invoke(partitioning).asInstanceOf[Seq[Expression]]) - } + def getHashPartitioningLikeExpressions(partitioning: Partitioning): Seq[Expression] = + partitioning match { + case p: HashPartitioningLike => p.expressions + case _ => Seq() + } } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala index 4e87559af..a33a5fdf9 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala @@ -20,28 +20,15 @@ package org.apache.comet.shims import org.apache.spark.sql.connector.expressions.aggregate.Aggregation -import org.apache.spark.sql.execution.{LimitExec, QueryExecution, SparkPlan} +import org.apache.spark.sql.execution.{CollectLimitExec, GlobalLimitExec, LocalLimitExec, QueryExecution} import org.apache.spark.sql.execution.datasources.v2.parquet.ParquetScan trait ShimCometSparkSessionExtensions { - import org.apache.comet.shims.ShimCometSparkSessionExtensions._ - def getPushedAggregate(scan: ParquetScan): Option[Aggregation] = scan.pushedAggregate - /** - * TODO: delete after dropping Spark 3.2 and 3.3 support - */ - def getOffset(limit: LimitExec): Int = getOffsetOpt(limit).getOrElse(0) - -} - -object ShimCometSparkSessionExtensions { - private def getOffsetOpt(plan: SparkPlan): Option[Int] = plan.getClass.getDeclaredFields - .filter(_.getName == "offset") - .map { a => a.setAccessible(true); a.get(plan) } - .filter(_.isInstanceOf[Int]) - .map(_.asInstanceOf[Int]) - .headOption + def getOffset(limit: LocalLimitExec): Int = 0 + def getOffset(limit: GlobalLimitExec): Int = limit.offset + def getOffset(limit: CollectLimitExec): Int = limit.offset def supportsExtendedExplainInfo(qe: QueryExecution): Boolean = true } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala index c97dbfc88..5a8ac97b3 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometTakeOrderedAndProjectExec.scala @@ -22,6 +22,5 @@ package org.apache.comet.shims import org.apache.spark.sql.execution.TakeOrderedAndProjectExec trait ShimCometTakeOrderedAndProjectExec { - protected def getOffset(plan: TakeOrderedAndProjectExec): Option[Int] = Some(plan.offset) } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala index b92d3fc6a..216d89993 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala @@ -19,52 +19,19 @@ package org.apache.comet.shims -import org.apache.spark.sql.catalyst.expressions.{BinaryArithmetic, BinaryExpression} -import org.apache.spark.sql.catalyst.expressions.aggregate.DeclarativeAggregate +import org.apache.spark.sql.catalyst.expressions.{BinaryArithmetic, BinaryExpression, BloomFilterMightContain, EvalMode} +import org.apache.spark.sql.catalyst.expressions.aggregate.{Average, Sum} trait ShimQueryPlanSerde { def getFailOnError(b: BinaryArithmetic): Boolean = b.getClass.getMethod("failOnError").invoke(b).asInstanceOf[Boolean] - def getFailOnError(aggregate: DeclarativeAggregate): Boolean = { - val failOnError = aggregate.getClass.getDeclaredMethods.flatMap(m => - m.getName match { - case "failOnError" | "useAnsiAdd" => Some(m.invoke(aggregate).asInstanceOf[Boolean]) - case _ => None - }) - if (failOnError.isEmpty) { - aggregate.getClass.getDeclaredMethods - .flatMap(m => - m.getName match { - case "initQueryContext" => Some(m.invoke(aggregate).asInstanceOf[Option[_]].isDefined) - case _ => None - }) - .head - } else { - failOnError.head - } - } + def getFailOnError(aggregate: Sum): Boolean = aggregate.initQueryContext().isDefined + def getFailOnError(aggregate: Average): Boolean = aggregate.initQueryContext().isDefined - // TODO: delete after drop Spark 3.2/3.3 support - // This method is used to check if the aggregate function is in legacy mode. - // EvalMode is an enum object in Spark 3.4. - def isLegacyMode(aggregate: DeclarativeAggregate): Boolean = { - val evalMode = aggregate.getClass.getDeclaredMethods - .flatMap(m => - m.getName match { - case "evalMode" => Some(m.invoke(aggregate)) - case _ => None - }) + def isLegacyMode(aggregate: Sum): Boolean = aggregate.evalMode.equals(EvalMode.LEGACY) + def isLegacyMode(aggregate: Average): Boolean = aggregate.evalMode.equals(EvalMode.LEGACY) - if (evalMode.isEmpty) { - true - } else { - "legacy".equalsIgnoreCase(evalMode.head.toString) - } - } - - // TODO: delete after drop Spark 3.2 support - def isBloomFilterMightContain(binary: BinaryExpression): Boolean = { - binary.getClass.getName == "org.apache.spark.sql.catalyst.expressions.BloomFilterMightContain" - } + def isBloomFilterMightContain(binary: BinaryExpression): Boolean = + binary.isInstanceOf[BloomFilterMightContain] } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala index 8511721c5..574967767 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimSQLConf.scala @@ -23,7 +23,6 @@ import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.internal.LegacyBehaviorPolicy trait ShimSQLConf { - protected def getPushDownStringPredicate(sqlConf: SQLConf): Boolean = sqlConf.parquetFilterPushDownStringPredicate diff --git a/spark/src/main/spark-4.0/org/apache/spark/comet/ShimCometDriverPlugin.scala b/spark/src/main/spark-4.0/org/apache/spark/comet/ShimCometDriverPlugin.scala deleted file mode 100644 index d97cac15c..000000000 --- a/spark/src/main/spark-4.0/org/apache/spark/comet/ShimCometDriverPlugin.scala +++ /dev/null @@ -1,13 +0,0 @@ -package org.apache.spark.comet - -import org.apache.spark.SparkConf -import org.apache.spark.internal.config.EXECUTOR_MEMORY_OVERHEAD_FACTOR -import org.apache.spark.internal.config.EXECUTOR_MIN_MEMORY_OVERHEAD - -trait ShimCometDriverPlugin { - def getMemoryOverheadFactor(sparkConf: SparkConf): Double = sparkConf.get( - EXECUTOR_MEMORY_OVERHEAD_FACTOR) - - def getMemoryOverheadMinMib(sparkConf: SparkConf): Long = sparkConf.get( - EXECUTOR_MIN_MEMORY_OVERHEAD) -} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastExchangeExec.scala b/spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometBroadcastExchangeExec.scala similarity index 52% rename from spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastExchangeExec.scala rename to spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometBroadcastExchangeExec.scala index 63ff2a2c1..ba87a2515 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastExchangeExec.scala +++ b/spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometBroadcastExchangeExec.scala @@ -17,7 +17,7 @@ * under the License. */ -package org.apache.comet.shims +package org.apache.spark.comet.shims import scala.reflect.ClassTag @@ -25,27 +25,6 @@ import org.apache.spark.SparkContext import org.apache.spark.broadcast.Broadcast trait ShimCometBroadcastExchangeExec { - // TODO: remove after dropping Spark 3.2 and 3.3 support - protected def doBroadcast[T: ClassTag](sparkContext: SparkContext, value: T): Broadcast[Any] = { - // Spark 3.4 has new API `broadcastInternal` to broadcast the relation without caching the - // unserialized object. - val classTag = implicitly[ClassTag[T]] - val broadcasted = sparkContext.getClass.getDeclaredMethods - .filter(_.getName == "broadcastInternal") - .map { a => a.setAccessible(true); a } - .map { method => - method - .invoke( - sparkContext.asInstanceOf[Object], - value.asInstanceOf[Object], - true.asInstanceOf[Object], - classTag.asInstanceOf[Object]) - .asInstanceOf[Broadcast[Any]] - } - .headOption - // Fallback to the old API if the new API is not available. - broadcasted - .getOrElse(sparkContext.broadcast(value.asInstanceOf[Object])) - .asInstanceOf[Broadcast[Any]] - } + protected def doBroadcast[T: ClassTag](sparkContext: SparkContext, value: T): Broadcast[Any] = + sparkContext.broadcastInternal(value, true) } diff --git a/spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala b/spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala new file mode 100644 index 000000000..9f3a6cc12 --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala @@ -0,0 +1,32 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.spark.comet.shims + +import org.apache.spark.SparkConf +import org.apache.spark.internal.config.EXECUTOR_MEMORY_OVERHEAD_FACTOR +import org.apache.spark.internal.config.EXECUTOR_MIN_MEMORY_OVERHEAD + +trait ShimCometDriverPlugin { + def getMemoryOverheadFactor(sparkConf: SparkConf): Double = sparkConf.get( + EXECUTOR_MEMORY_OVERHEAD_FACTOR) + + def getMemoryOverheadMinMib(sparkConf: SparkConf): Long = sparkConf.get( + EXECUTOR_MIN_MEMORY_OVERHEAD) +} diff --git a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimDecimalPrecision.scala b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimDecimalPrecision.scala deleted file mode 100644 index 5afbde6c8..000000000 --- a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimDecimalPrecision.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.apache.spark.sql.comet - -import org.apache.spark.sql.catalyst.expressions.Expression - -trait ShimDecimalPrecision { - object DecimalExpression { - def unapply(e: Expression): Option[(Int, Int)] = - org.apache.spark.sql.types.DecimalExpression.unapply(e) - } -} diff --git a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimCometScanExec.scala b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala similarity index 73% rename from spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimCometScanExec.scala rename to spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala index 634a38407..543116c10 100644 --- a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/ShimCometScanExec.scala +++ b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala @@ -17,7 +17,7 @@ * under the License. */ -package org.apache.spark.sql.comet +package org.apache.spark.sql.comet.shims import org.apache.hadoop.fs.Path @@ -37,12 +37,6 @@ import org.apache.spark.SparkContext trait ShimCometScanExec { def wrapped: FileSourceScanExec - // TODO: remove after dropping Spark 3.2 support and directly call wrapped.metadataColumns - lazy val metadataColumns: Seq[AttributeReference] = wrapped.getClass.getDeclaredMethods - .filter(_.getName == "metadataColumns") - .map { a => a.setAccessible(true); a } - .flatMap(_.invoke(wrapped).asInstanceOf[Seq[AttributeReference]]) - lazy val fileConstantMetadataColumns: Seq[AttributeReference] = wrapped.fileConstantMetadataColumns @@ -54,31 +48,21 @@ trait ShimCometScanExec { customMetrics: Map[String, SQLMetric]): DataSourceRDD = new DataSourceRDD(sc, inputPartitions, partitionReaderFactory, columnarReads, customMetrics) - // TODO: remove after dropping Spark 3.2 support and directly call new FileScanRDD protected def newFileScanRDD( - sparkSession: SparkSession, + fsRelation: HadoopFsRelation, readFunction: PartitionedFile => Iterator[InternalRow], filePartitions: Seq[FilePartition], readSchema: StructType, - options: ParquetOptions): FileScanRDD = - classOf[FileScanRDD].getDeclaredConstructors - .map { c => - c.getParameterCount match { - case 3 => c.newInstance(sparkSession, readFunction, filePartitions) - case 5 => - c.newInstance(sparkSession, readFunction, filePartitions, readSchema, metadataColumns) - case 6 => - c.newInstance( - sparkSession, - readFunction, - filePartitions, - readSchema, - fileConstantMetadataColumns, - options) - } - } - .last - .asInstanceOf[FileScanRDD] + options: ParquetOptions): FileScanRDD = { + new FileScanRDD( + fsRelation.sparkSession, + readFunction, + filePartitions, + readSchema, + fileConstantMetadataColumns, + fsRelation.fileFormat.fileConstantMetadataExtractors, + options) + } protected def invalidBucketFile(path: String, sparkVersion: String): Throwable = QueryExecutionErrors.invalidBucketFile(path) diff --git a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala new file mode 100644 index 000000000..ab123695b --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala @@ -0,0 +1,29 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.spark.sql.comet.shims + +import org.apache.spark.sql.catalyst.expressions.Expression + +trait ShimDecimalPrecision { + object DecimalExpression { + def unapply(e: Expression): Option[(Int, Int)] = + org.apache.spark.sql.types.DecimalExpression.unapply(e) + } +} diff --git a/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala b/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala index 8ff287dec..db9547fe7 100644 --- a/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala +++ b/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala @@ -48,7 +48,6 @@ import org.apache.spark.sql.types.StructType import org.apache.comet._ import org.apache.comet.CometSparkSessionExtensions.isSpark34Plus import org.apache.comet.shims.ShimCometSparkSessionExtensions -import org.apache.comet.shims.ShimCometSparkSessionExtensions.supportsExtendedExplainInfo /** * Base class for testing. This exists in `org.apache.spark.sql` since [[SQLTestUtils]] is diff --git a/spark/src/test/spark-3.x/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala b/spark/src/test/spark-3.x/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala index 15edd486c..caa943c26 100644 --- a/spark/src/test/spark-3.x/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala +++ b/spark/src/test/spark-3.x/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala @@ -1,3 +1,22 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + package org.apache.comet.shims import org.apache.spark.sql.{SQLQueryTestHelper, SparkSession} diff --git a/spark/src/test/spark-4.0/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala b/spark/src/test/spark-4.0/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala index 3a570e99d..ec9823e52 100644 --- a/spark/src/test/spark-4.0/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala +++ b/spark/src/test/spark-4.0/org/apache/comet/shims/ShimCometTPCHQuerySuite.scala @@ -1,3 +1,22 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + package org.apache.comet.shims import org.apache.spark.sql.SQLQueryTestHelper From 69ca228919d2780d72edba5bd5868f092e17cd83 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 9 May 2024 10:36:30 -0700 Subject: [PATCH 09/68] build: Add spark-4.0 profile and shims --- .../apache/comet/shims/ShimBatchReader.scala | 1 - .../apache/comet/shims/ShimFileFormat.scala | 1 - .../shuffle/CometShuffleExchangeExec.scala | 30 +++++++------------ .../shims/ShimCometShuffleExchangeExec.scala | 3 +- .../comet/shims/ShimCometDriverPlugin.scala | 10 ++++--- .../sql/comet/shims/ShimCometScanExec.scala | 8 +++-- .../ShimCometShuffleWriteProcessor.scala | 28 +++++++++++++++++ .../apache/comet/shims/CometExprShim.scala | 2 +- .../ShimCometBroadcastHashJoinExec.scala | 2 +- .../ShimCometSparkSessionExtensions.scala | 10 +++---- .../comet/shims/ShimQueryPlanSerde.scala | 12 ++++---- .../comet/shims/ShimCometDriverPlugin.scala | 4 +-- .../ShimCometShuffleWriteProcessor.scala | 7 +++++ .../spark/sql/CometTPCDSQuerySuite.scala | 5 ++-- .../shims/ShimCometTPCDSQuerySuite.scala | 6 ++++ .../spark/comet/shims/ShimTestUtils.scala | 1 - .../shims/ShimCometTPCDSQuerySuite.scala | 5 ++++ 17 files changed, 87 insertions(+), 48 deletions(-) create mode 100644 spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala create mode 100644 spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala create mode 100644 spark/src/test/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala create mode 100644 spark/src/test/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala index 1866c8ba7..448d0886c 100644 --- a/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimBatchReader.scala @@ -24,7 +24,6 @@ import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.execution.datasources.PartitionedFile object ShimBatchReader { - def newPartitionedFile(partitionValues: InternalRow, file: String): PartitionedFile = PartitionedFile( partitionValues, diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala index 354dacf51..dbac0c15c 100644 --- a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala @@ -23,7 +23,6 @@ import org.apache.spark.sql.execution.datasources.FileFormat import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat object ShimFileFormat { - val ROW_INDEX = ParquetFileFormat.ROW_INDEX // A name for a temporary column that holds row indexes computed by the file format reader diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala b/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala index 5ab1e196b..94d3b7cac 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala @@ -28,10 +28,10 @@ import scala.concurrent.Future import org.apache.spark._ import org.apache.spark.internal.config -import org.apache.spark.rdd.{MapPartitionsRDD, RDD} +import org.apache.spark.rdd.RDD import org.apache.spark.scheduler.MapStatus import org.apache.spark.serializer.Serializer -import org.apache.spark.shuffle.{IndexShuffleBlockResolver, ShuffleWriteMetricsReporter, ShuffleWriteProcessor} +import org.apache.spark.shuffle.{IndexShuffleBlockResolver, ShuffleWriteMetricsReporter} import org.apache.spark.shuffle.sort.SortShuffleManager import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.{Attribute, BoundReference, UnsafeProjection, UnsafeRow} @@ -39,6 +39,7 @@ import org.apache.spark.sql.catalyst.expressions.codegen.LazilyGeneratedOrdering import org.apache.spark.sql.catalyst.plans.logical.Statistics import org.apache.spark.sql.catalyst.plans.physical._ import org.apache.spark.sql.comet.{CometExec, CometMetricNode, CometPlan} +import org.apache.spark.sql.comet.shims.ShimCometShuffleWriteProcessor import org.apache.spark.sql.execution._ import org.apache.spark.sql.execution.exchange.{ENSURE_REQUIREMENTS, ShuffleExchangeLike, ShuffleOrigin} import org.apache.spark.sql.execution.exchange.ShuffleExchangeExec @@ -448,7 +449,7 @@ class CometShuffleWriteProcessor( outputPartitioning: Partitioning, outputAttributes: Seq[Attribute], metrics: Map[String, SQLMetric]) - extends ShuffleWriteProcessor { + extends ShimCometShuffleWriteProcessor { private val OFFSET_LENGTH = 8 @@ -457,23 +458,9 @@ class CometShuffleWriteProcessor( new SQLShuffleWriteMetricsReporter(context.taskMetrics().shuffleWriteMetrics, metrics) } - // For Spark-3.x - def write( - rdd: RDD[_], - dep: ShuffleDependency[_, _, _], - mapId: Long, - context: TaskContext, - partition: Partition): MapStatus = { - // Getting rid of the fake partitionId - val cometRDD = rdd.asInstanceOf[MapPartitionsRDD[_, _]].prev.asInstanceOf[RDD[ColumnarBatch]] - val rawIter = cometRDD.iterator(partition, context) - write(rawIter, dep, mapId, partition.index, context) - } - - // TODO: add `override` keyword after dropping Spark-3.x supports // FIXME: we need actually prev of rdd? - def write( - inputs: Iterator[ColumnarBatch], + override def write( + inputs: Iterator[_], dep: ShuffleDependency[_, _, _], mapId: Long, mapIndex: Int, @@ -496,7 +483,10 @@ class CometShuffleWriteProcessor( "elapsed_compute" -> metrics("shuffleReadElapsedCompute")) val nativeMetrics = CometMetricNode(nativeSQLMetrics) - val cometIter = CometExec.getCometIterator(Seq(inputs), nativePlan, nativeMetrics) + val cometIter = CometExec.getCometIterator( + Seq(inputs.asInstanceOf[Iterator[ColumnarBatch]]), + nativePlan, + nativeMetrics) while (cometIter.hasNext) { cometIter.next() diff --git a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala index 76535c2ba..350aeb9f0 100644 --- a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala +++ b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometShuffleExchangeExec.scala @@ -19,10 +19,11 @@ package org.apache.comet.shims +import org.apache.spark.ShuffleDependency import org.apache.spark.sql.catalyst.expressions.Attribute import org.apache.spark.sql.comet.execution.shuffle.{CometShuffleExchangeExec, ShuffleType} import org.apache.spark.sql.execution.exchange.ShuffleExchangeExec -import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.types.{StructField, StructType} trait ShimCometShuffleExchangeExec { // TODO: remove after dropping Spark 3.2 and 3.3 support diff --git a/spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala b/spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala index 1cdf0108f..cfb6a0088 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala @@ -19,6 +19,8 @@ package org.apache.spark.comet.shims +import org.apache.spark.SparkConf + trait ShimCometDriverPlugin { // `org.apache.spark.internal.config.EXECUTOR_MEMORY_OVERHEAD_FACTOR` was added since Spark 3.3.0 private val EXECUTOR_MEMORY_OVERHEAD_FACTOR = "spark.executor.memoryOverheadFactor" @@ -27,10 +29,10 @@ trait ShimCometDriverPlugin { private val EXECUTOR_MIN_MEMORY_OVERHEAD = "spark.executor.minMemoryOverhead" private val EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT = 384L - def getMemoryOverheadFactor = - sc.getConf.getDouble( + def getMemoryOverheadFactor(sc: SparkConf): Double = + sc.getDouble( EXECUTOR_MEMORY_OVERHEAD_FACTOR, EXECUTOR_MEMORY_OVERHEAD_FACTOR_DEFAULT) - def getMemoryOverheadMinMib = - sc.getConf.getLong(EXECUTOR_MIN_MEMORY_OVERHEAD, EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT) + def getMemoryOverheadMinMib(sc: SparkConf): Long = + sc.getLong(EXECUTOR_MIN_MEMORY_OVERHEAD, EXECUTOR_MIN_MEMORY_OVERHEAD_DEFAULT) } diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala index 6da114ac2..27c1615e8 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala @@ -19,9 +19,11 @@ package org.apache.spark.sql.comet.shims +import org.apache.comet.shims.ShimFileFormat + import scala.language.implicitConversions -import org.apache.hadoop.fs.Path +import org.apache.hadoop.fs.{FileStatus, Path} import org.apache.spark.{SparkContext, SparkException} import org.apache.spark.sql.SparkSession @@ -29,7 +31,7 @@ import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.AttributeReference import org.apache.spark.sql.connector.read.{InputPartition, PartitionReaderFactory} import org.apache.spark.sql.execution.{FileSourceScanExec, PartitionedFileUtil} -import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, FileStatusWithMetadata, PartitionDirectory, PartitionedFile} +import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, HadoopFsRelation, PartitionDirectory, PartitionedFile} import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.datasources.v2.DataSourceRDD import org.apache.spark.sql.execution.metric.SQLMetric @@ -124,7 +126,7 @@ trait ShimCometScanExec { findRowIndexColumnIndexInSchema(sparkSchema) >= 0 } - protected def getPartitionedFile(f: FileStatusWithMetadata, p: PartitionDirectory): PartitionedFile = + protected def getPartitionedFile(f: FileStatus, p: PartitionDirectory): PartitionedFile = PartitionedFileUtil.getPartitionedFile(f, f.getPath, p.values) protected def splitFiles(sparkSession: SparkSession, diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala new file mode 100644 index 000000000..569541d48 --- /dev/null +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala @@ -0,0 +1,28 @@ +package org.apache.spark.sql.comet.shims + +import org.apache.spark.{Partition, ShuffleDependency, TaskContext} +import org.apache.spark.rdd.{MapPartitionsRDD, RDD} +import org.apache.spark.scheduler.MapStatus +import org.apache.spark.shuffle.ShuffleWriteProcessor +import org.apache.spark.sql.vectorized.ColumnarBatch + +trait ShimCometShuffleWriteProcessor extends ShuffleWriteProcessor { + override def write( + rdd: RDD[_], + dep: ShuffleDependency[_, _, _], + mapId: Long, + context: TaskContext, + partition: Partition): MapStatus = { + // Getting rid of the fake partitionId + val cometRDD = rdd.asInstanceOf[MapPartitionsRDD[_, _]].prev.asInstanceOf[RDD[ColumnarBatch]] + val rawIter = cometRDD.iterator(partition, context) + write(rawIter, dep, mapId, partition.index, context) + } + + def write( + inputs: Iterator[_], + dep: ShuffleDependency[_, _, _], + mapId: Long, + mapIndex: Int, + context: TaskContext): MapStatus +} diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala index 409e1c94b..7d4ec1537 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala @@ -27,7 +27,7 @@ trait CometExprShim { /** * Returns a tuple of expressions for the `unhex` function. */ - def unhexSerde(unhex: Unhex): (Expression, Expression) = { + protected def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(unhex.failOnError)) } } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala index 2bcd7fd96..1f689b400 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometBroadcastHashJoinExec.scala @@ -23,7 +23,7 @@ import org.apache.spark.sql.catalyst.expressions.Expression import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioningLike, Partitioning} trait ShimCometBroadcastHashJoinExec { - def getHashPartitioningLikeExpressions(partitioning: Partitioning): Seq[Expression] = + protected def getHashPartitioningLikeExpressions(partitioning: Partitioning): Seq[Expression] = partitioning match { case p: HashPartitioningLike => p.expressions case _ => Seq() diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala index a33a5fdf9..6316f51a5 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala @@ -24,11 +24,11 @@ import org.apache.spark.sql.execution.{CollectLimitExec, GlobalLimitExec, LocalL import org.apache.spark.sql.execution.datasources.v2.parquet.ParquetScan trait ShimCometSparkSessionExtensions { - def getPushedAggregate(scan: ParquetScan): Option[Aggregation] = scan.pushedAggregate + protected def getPushedAggregate(scan: ParquetScan): Option[Aggregation] = scan.pushedAggregate - def getOffset(limit: LocalLimitExec): Int = 0 - def getOffset(limit: GlobalLimitExec): Int = limit.offset - def getOffset(limit: CollectLimitExec): Int = limit.offset + protected def getOffset(limit: LocalLimitExec): Int = 0 + protected def getOffset(limit: GlobalLimitExec): Int = limit.offset + protected def getOffset(limit: CollectLimitExec): Int = limit.offset - def supportsExtendedExplainInfo(qe: QueryExecution): Boolean = true + protected def supportsExtendedExplainInfo(qe: QueryExecution): Boolean = true } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala index 216d89993..4d261f3c2 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimQueryPlanSerde.scala @@ -23,15 +23,15 @@ import org.apache.spark.sql.catalyst.expressions.{BinaryArithmetic, BinaryExpres import org.apache.spark.sql.catalyst.expressions.aggregate.{Average, Sum} trait ShimQueryPlanSerde { - def getFailOnError(b: BinaryArithmetic): Boolean = + protected def getFailOnError(b: BinaryArithmetic): Boolean = b.getClass.getMethod("failOnError").invoke(b).asInstanceOf[Boolean] - def getFailOnError(aggregate: Sum): Boolean = aggregate.initQueryContext().isDefined - def getFailOnError(aggregate: Average): Boolean = aggregate.initQueryContext().isDefined + protected def getFailOnError(aggregate: Sum): Boolean = aggregate.initQueryContext().isDefined + protected def getFailOnError(aggregate: Average): Boolean = aggregate.initQueryContext().isDefined - def isLegacyMode(aggregate: Sum): Boolean = aggregate.evalMode.equals(EvalMode.LEGACY) - def isLegacyMode(aggregate: Average): Boolean = aggregate.evalMode.equals(EvalMode.LEGACY) + protected def isLegacyMode(aggregate: Sum): Boolean = aggregate.evalMode.equals(EvalMode.LEGACY) + protected def isLegacyMode(aggregate: Average): Boolean = aggregate.evalMode.equals(EvalMode.LEGACY) - def isBloomFilterMightContain(binary: BinaryExpression): Boolean = + protected def isBloomFilterMightContain(binary: BinaryExpression): Boolean = binary.isInstanceOf[BloomFilterMightContain] } diff --git a/spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala b/spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala index 9f3a6cc12..f7a57a642 100644 --- a/spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala +++ b/spark/src/main/spark-4.0/org/apache/spark/comet/shims/ShimCometDriverPlugin.scala @@ -24,9 +24,9 @@ import org.apache.spark.internal.config.EXECUTOR_MEMORY_OVERHEAD_FACTOR import org.apache.spark.internal.config.EXECUTOR_MIN_MEMORY_OVERHEAD trait ShimCometDriverPlugin { - def getMemoryOverheadFactor(sparkConf: SparkConf): Double = sparkConf.get( + protected def getMemoryOverheadFactor(sparkConf: SparkConf): Double = sparkConf.get( EXECUTOR_MEMORY_OVERHEAD_FACTOR) - def getMemoryOverheadMinMib(sparkConf: SparkConf): Long = sparkConf.get( + protected def getMemoryOverheadMinMib(sparkConf: SparkConf): Long = sparkConf.get( EXECUTOR_MIN_MEMORY_OVERHEAD) } diff --git a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala new file mode 100644 index 000000000..6f3af1bf5 --- /dev/null +++ b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala @@ -0,0 +1,7 @@ +package org.apache.spark.sql.comet.shims + +import org.apache.spark.shuffle.ShuffleWriteProcessor + +trait ShimCometShuffleWriteProcessor extends ShuffleWriteProcessor { + +} diff --git a/spark/src/test/scala/org/apache/spark/sql/CometTPCDSQuerySuite.scala b/spark/src/test/scala/org/apache/spark/sql/CometTPCDSQuerySuite.scala index c3d3788d7..b64343bbb 100644 --- a/spark/src/test/scala/org/apache/spark/sql/CometTPCDSQuerySuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/CometTPCDSQuerySuite.scala @@ -21,12 +21,12 @@ package org.apache.spark.sql import org.apache.spark.SparkConf import org.apache.spark.internal.config.{MEMORY_OFFHEAP_ENABLED, MEMORY_OFFHEAP_SIZE} +import org.apache.spark.sql.comet.shims.ShimCometTPCDSQuerySuite import org.apache.comet.CometConf class CometTPCDSQuerySuite extends { - // This is private in `TPCDSBase`. override val excludedTpcdsQueries: Set[String] = Set() // This is private in `TPCDSBase` and `excludedTpcdsQueries` is private too. @@ -145,7 +145,8 @@ class CometTPCDSQuerySuite override val tpcdsQueries: Seq[String] = tpcdsAllQueries.filterNot(excludedTpcdsQueries.contains) } - with TPCDSQueryTestSuite { + with TPCDSQueryTestSuite + with ShimCometTPCDSQuerySuite { override def sparkConf: SparkConf = { val conf = super.sparkConf conf.set("spark.sql.extensions", "org.apache.comet.CometSparkSessionExtensions") diff --git a/spark/src/test/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala b/spark/src/test/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala new file mode 100644 index 000000000..0fc4ecd95 --- /dev/null +++ b/spark/src/test/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala @@ -0,0 +1,6 @@ +package org.apache.spark.sql.comet.shims + +trait ShimCometTPCDSQuerySuite { + // This is private in `TPCDSBase`. + val excludedTpcdsQueries: Set[String] = Set() +} diff --git a/spark/src/test/spark-4.0/org/apache/spark/comet/shims/ShimTestUtils.scala b/spark/src/test/spark-4.0/org/apache/spark/comet/shims/ShimTestUtils.scala index 9d760fcb6..923ae68f2 100644 --- a/spark/src/test/spark-4.0/org/apache/spark/comet/shims/ShimTestUtils.scala +++ b/spark/src/test/spark-4.0/org/apache/spark/comet/shims/ShimTestUtils.scala @@ -22,7 +22,6 @@ package org.apache.spark.comet.shims import java.io.File object ShimTestUtils { - def listDirectory(path: File): Array[String] = org.apache.spark.TestUtils.listDirectory(path) } diff --git a/spark/src/test/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala b/spark/src/test/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala new file mode 100644 index 000000000..ac60ffb4c --- /dev/null +++ b/spark/src/test/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala @@ -0,0 +1,5 @@ +package org.apache.spark.sql.comet.shims + +trait ShimCometTPCDSQuerySuite { + +} From 3aec9e6643eec24e06ff7108bc5404221bd85d27 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 9 May 2024 15:00:16 -0700 Subject: [PATCH 10/68] build: Add spark-4.0 profile and shims --- .../shims/ShimCometTPCDSQuerySuite.scala | 19 +++++++++++++++++++ .../shims/ShimCometTPCDSQuerySuite.scala | 19 +++++++++++++++++++ 2 files changed, 38 insertions(+) diff --git a/spark/src/test/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala b/spark/src/test/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala index 0fc4ecd95..f8d621c7e 100644 --- a/spark/src/test/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala +++ b/spark/src/test/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala @@ -1,3 +1,22 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + package org.apache.spark.sql.comet.shims trait ShimCometTPCDSQuerySuite { diff --git a/spark/src/test/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala b/spark/src/test/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala index ac60ffb4c..43917df63 100644 --- a/spark/src/test/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala +++ b/spark/src/test/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometTPCDSQuerySuite.scala @@ -1,3 +1,22 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + package org.apache.spark.sql.comet.shims trait ShimCometTPCDSQuerySuite { From d629df1eaa052ea379fe352f2d5eb79f982b77be Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 9 May 2024 16:02:12 -0700 Subject: [PATCH 11/68] build: Add spark-4.0 profile and shims --- .../ShimCometShuffleWriteProcessor.scala | 19 +++++++++++++++++++ .../ShimCometShuffleWriteProcessor.scala | 19 +++++++++++++++++++ 2 files changed, 38 insertions(+) diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala index 569541d48..0712352ff 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala @@ -1,3 +1,22 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + package org.apache.spark.sql.comet.shims import org.apache.spark.{Partition, ShuffleDependency, TaskContext} diff --git a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala index 6f3af1bf5..f875e3f38 100644 --- a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala +++ b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala @@ -1,3 +1,22 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + package org.apache.spark.sql.comet.shims import org.apache.spark.shuffle.ShuffleWriteProcessor From 65628fbdbcf70b50508eadbbd8e915336ec3420f Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 9 May 2024 17:44:46 -0700 Subject: [PATCH 12/68] build: Add spark-4.0 profile and shims --- .../main/scala/org/apache/comet/parquet/CometParquetUtils.scala | 2 +- .../sql/comet/{parquet => shims}/ShimCometParquetUtils.scala | 2 +- .../sql/comet/{parquet => shims}/ShimCometParquetUtils.scala | 2 +- dev/ensure-jars-have-correct-contents.sh | 2 ++ 4 files changed, 5 insertions(+), 3 deletions(-) rename common/src/main/spark-3.x/org/apache/spark/sql/comet/{parquet => shims}/ShimCometParquetUtils.scala (98%) rename common/src/main/spark-4.0/org/apache/spark/sql/comet/{parquet => shims}/ShimCometParquetUtils.scala (97%) diff --git a/common/src/main/scala/org/apache/comet/parquet/CometParquetUtils.scala b/common/src/main/scala/org/apache/comet/parquet/CometParquetUtils.scala index 2cb5f141e..d03252d06 100644 --- a/common/src/main/scala/org/apache/comet/parquet/CometParquetUtils.scala +++ b/common/src/main/scala/org/apache/comet/parquet/CometParquetUtils.scala @@ -20,7 +20,7 @@ package org.apache.comet.parquet import org.apache.hadoop.conf.Configuration -import org.apache.spark.sql.comet.parquet.ShimCometParquetUtils +import org.apache.spark.sql.comet.shims.ShimCometParquetUtils import org.apache.spark.sql.internal.SQLConf object CometParquetUtils extends ShimCometParquetUtils { diff --git a/common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala b/common/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala similarity index 98% rename from common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala rename to common/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala index 2ca4d2f7e..f22ac4060 100644 --- a/common/src/main/spark-3.x/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala +++ b/common/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala @@ -17,7 +17,7 @@ * under the License. */ -package org.apache.spark.sql.comet.parquet +package org.apache.spark.sql.comet.shims import org.apache.spark.sql.types._ diff --git a/common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala b/common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala similarity index 97% rename from common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala rename to common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala index 7115ba779..0f5ce9e6d 100644 --- a/common/src/main/spark-4.0/org/apache/spark/sql/comet/parquet/ShimCometParquetUtils.scala +++ b/common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala @@ -17,7 +17,7 @@ * under the License. */ -package org.apache.spark.sql.comet.parquet +package org.apache.spark.sql.comet.shims import org.apache.spark.sql.errors.QueryExecutionErrors import org.apache.spark.sql.execution.datasources.parquet.ParquetUtils diff --git a/dev/ensure-jars-have-correct-contents.sh b/dev/ensure-jars-have-correct-contents.sh index 1f97d2d4a..12f555b8e 100755 --- a/dev/ensure-jars-have-correct-contents.sh +++ b/dev/ensure-jars-have-correct-contents.sh @@ -40,9 +40,11 @@ allowed_expr="(^org/$|^org/apache/$" # we have to allow the directories that lead to the org/apache/comet dir # We allow all the classes under the following packages: # * org.apache.comet +# * org.apache.spark.comet # * org.apache.spark.sql.comet # * org.apache.arrow.c allowed_expr+="|^org/apache/comet/" +allowed_expr+="|^org/apache/spark/comet/" allowed_expr+="|^org/apache/spark/sql/comet/" allowed_expr+="|^org/apache/arrow/c/" # * whatever in the "META-INF" directory From 328705ff04ab557d86c64342e60d3e7b545a8f53 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Fri, 10 May 2024 19:37:44 -0700 Subject: [PATCH 13/68] build: Add spark-4.0 profile and shims --- .github/workflows/pr_build.yml | 36 ++++++++++++++++++++++++++++++++++ 1 file changed, 36 insertions(+) diff --git a/.github/workflows/pr_build.yml b/.github/workflows/pr_build.yml index 0a5209215..14353ec90 100644 --- a/.github/workflows/pr_build.yml +++ b/.github/workflows/pr_build.yml @@ -100,6 +100,18 @@ jobs: - if: matrix.test-target == 'rust' name: Rust test steps uses: ./.github/actions/rust-test + - if: matrix.test-target == 'java' + name: Clone Spark + uses: actions/checkout@v4 + with: + repository: "apache/spark" + - if: matrix.test-target == 'java' + name: Install Spark + shell: bash + run: | + pushd apache-spark + build/mvn install -Phive -Phadoop-cloud -DskipTests + popd - if: matrix.test-target == 'java' name: Java test steps uses: ./.github/actions/java-test @@ -223,6 +235,18 @@ jobs: - if: matrix.test-target == 'rust' name: Rust test steps uses: ./.github/actions/rust-test + - if: matrix.test-target == 'java' + name: Clone Spark + uses: actions/checkout@v4 + with: + repository: "apache/spark" + - if: matrix.test-target == 'java' + name: Install Spark + shell: bash + run: | + pushd apache-spark + build/mvn install -Phive -Phadoop-cloud -DskipTests + popd - if: matrix.test-target == 'java' name: Java test steps uses: ./.github/actions/java-test @@ -258,6 +282,18 @@ jobs: - if: matrix.test-target == 'rust' name: Rust test steps uses: ./.github/actions/rust-test + - if: matrix.test-target == 'java' + name: Clone Spark + uses: actions/checkout@v4 + with: + repository: "apache/spark" + - if: matrix.test-target == 'java' + name: Install Spark + shell: bash + run: | + pushd apache-spark + build/mvn install -Phive -Phadoop-cloud -DskipTests + popd - if: matrix.test-target == 'java' name: Java test steps uses: ./.github/actions/java-test From b85c712fb73fb88c558fb915cd61601420b7cc06 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Fri, 10 May 2024 20:06:02 -0700 Subject: [PATCH 14/68] build: Add spark-4.0 profile and shims --- .github/workflows/pr_build.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/pr_build.yml b/.github/workflows/pr_build.yml index 14353ec90..364aad7e3 100644 --- a/.github/workflows/pr_build.yml +++ b/.github/workflows/pr_build.yml @@ -291,7 +291,7 @@ jobs: name: Install Spark shell: bash run: | - pushd apache-spark + pushd spark build/mvn install -Phive -Phadoop-cloud -DskipTests popd - if: matrix.test-target == 'java' From 8dc9dba7bd6613e051794d5b733e4c45e099852f Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Fri, 10 May 2024 23:25:18 -0700 Subject: [PATCH 15/68] build: Add spark-4.0 profile and shims --- .github/workflows/pr_build.yml | 30 +++++++++--------------------- 1 file changed, 9 insertions(+), 21 deletions(-) diff --git a/.github/workflows/pr_build.yml b/.github/workflows/pr_build.yml index 364aad7e3..fff777a08 100644 --- a/.github/workflows/pr_build.yml +++ b/.github/workflows/pr_build.yml @@ -105,13 +105,9 @@ jobs: uses: actions/checkout@v4 with: repository: "apache/spark" - - if: matrix.test-target == 'java' - name: Install Spark - shell: bash - run: | - pushd apache-spark - build/mvn install -Phive -Phadoop-cloud -DskipTests - popd + path: "apache-spark" + working-directory: ./apache-spark + run: build/mvn install -Phive -Phadoop-cloud -DskipTests - if: matrix.test-target == 'java' name: Java test steps uses: ./.github/actions/java-test @@ -240,13 +236,9 @@ jobs: uses: actions/checkout@v4 with: repository: "apache/spark" - - if: matrix.test-target == 'java' - name: Install Spark - shell: bash - run: | - pushd apache-spark - build/mvn install -Phive -Phadoop-cloud -DskipTests - popd + path: "apache-spark" + working-directory: ./apache-spark + run: build/mvn install -Phive -Phadoop-cloud -DskipTests - if: matrix.test-target == 'java' name: Java test steps uses: ./.github/actions/java-test @@ -287,13 +279,9 @@ jobs: uses: actions/checkout@v4 with: repository: "apache/spark" - - if: matrix.test-target == 'java' - name: Install Spark - shell: bash - run: | - pushd spark - build/mvn install -Phive -Phadoop-cloud -DskipTests - popd + path: "apache-spark" + working-directory: ./apache-spark + run: build/mvn install -Phive -Phadoop-cloud -DskipTests - if: matrix.test-target == 'java' name: Java test steps uses: ./.github/actions/java-test From 9a4b605243ab6021c08c1336c0b38494df24a850 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Sat, 11 May 2024 00:28:30 -0700 Subject: [PATCH 16/68] build: Add spark-4.0 profile and shims --- .github/workflows/pr_build.yml | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/.github/workflows/pr_build.yml b/.github/workflows/pr_build.yml index fff777a08..483e663a2 100644 --- a/.github/workflows/pr_build.yml +++ b/.github/workflows/pr_build.yml @@ -106,6 +106,9 @@ jobs: with: repository: "apache/spark" path: "apache-spark" + - if: matrix.test-target == 'java' + name: Install Spark + shell: bash working-directory: ./apache-spark run: build/mvn install -Phive -Phadoop-cloud -DskipTests - if: matrix.test-target == 'java' @@ -237,6 +240,9 @@ jobs: with: repository: "apache/spark" path: "apache-spark" + - if: matrix.test-target == 'java' + name: Install Spark + shell: bash working-directory: ./apache-spark run: build/mvn install -Phive -Phadoop-cloud -DskipTests - if: matrix.test-target == 'java' @@ -280,6 +286,9 @@ jobs: with: repository: "apache/spark" path: "apache-spark" + - if: matrix.test-target == 'java' + name: Install Spark + shell: bash working-directory: ./apache-spark run: build/mvn install -Phive -Phadoop-cloud -DskipTests - if: matrix.test-target == 'java' From 8ec2767167a73fbfec326243959be6ac60b4ad3e Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 14 May 2024 01:43:53 -0700 Subject: [PATCH 17/68] build: Enable spark-4.0 tests --- .../comet/CometSparkSessionExtensions.scala | 4 ++++ .../org/apache/comet/serde/QueryPlanSerde.scala | 3 ++- .../scala/org/apache/comet/CometCastSuite.scala | 17 +++++++++++++---- .../apache/comet/parquet/ParquetReadSuite.scala | 1 + 4 files changed, 20 insertions(+), 5 deletions(-) diff --git a/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala b/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala index 73592d785..5d4eba589 100644 --- a/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala +++ b/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala @@ -985,6 +985,10 @@ object CometSparkSessionExtensions extends Logging { org.apache.spark.SPARK_VERSION >= "3.4" } + def isSpark4Plus: Boolean = { + org.apache.spark.SPARK_VERSION >= "4" + } + /** Calculates required memory overhead in MB per executor process for Comet. */ def getCometMemoryOverheadInMiB(sparkConf: SparkConf): Long = { // `spark.executor.memory` default value is 1g diff --git a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala index 5c0553a1b..38180e9c7 100644 --- a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala +++ b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala @@ -2165,7 +2165,8 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde with CometExprShim } def nullIfWhenPrimitive(expression: Expression): Expression = if (isPrimitive(expression)) { - new NullIf(expression, Literal.default(expression.dataType)).child + val zero = Literal.default(expression.dataType) + If(EqualTo(expression, zero), Literal.create(null, expression.dataType), expression) } else { expression } diff --git a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala index 1881c561c..150b7e398 100644 --- a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala @@ -987,12 +987,21 @@ class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper { fail(s"Comet should have failed with ${e.getCause.getMessage}") case (Some(sparkException), Some(cometException)) => // both systems threw an exception so we make sure they are the same - val sparkMessage = sparkException.getCause.getMessage + val sparkMessage = + if (sparkException.getCause != null) sparkException.getCause.getMessage else null // We have to workaround https://github.com/apache/datafusion-comet/issues/293 here by // removing the "Execution error: " error message prefix that is added by DataFusion - val cometMessage = cometException.getCause.getMessage - .replace("Execution error: ", "") - if (CometSparkSessionExtensions.isSpark34Plus) { + val cometMessage = cometException.getCause.getMessage.replace("Execution error: ", "") + if (CometSparkSessionExtensions.isSpark4Plus) { + // for Spark 4 we expect to sparkException carries the message + assert( + cometMessage == sparkException.getMessage + .split("\n") + .head + .replace(".WITH_SUGGESTION] ", "]") + .replace(" SQLSTATE: 22003", "") + .replace(" SQLSTATE: 22018a", "")) + } else if (CometSparkSessionExtensions.isSpark34Plus) { // for Spark 3.4 we expect to reproduce the error message exactly assert(cometMessage == sparkMessage) } else if (CometSparkSessionExtensions.isSpark33Plus) { diff --git a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala index f44752297..ba5849de8 100644 --- a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala +++ b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala @@ -1127,6 +1127,7 @@ abstract class ParquetReadSuite extends CometTestBase { test("row group skipping doesn't overflow when reading into larger type") { assume(isSpark34Plus) + // https://github.com/apache/spark/commit/3361f25dc0ff6e5233903c26ee105711b79ba967 withTempPath { path => Seq(0).toDF("a").write.parquet(path.toString) // Reading integer 'a' as a long isn't supported. Check that an exception is raised instead From 396d077266b74a0579bb5366a850a4acb8fd3113 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 15 May 2024 12:49:21 -0700 Subject: [PATCH 18/68] address review comments --- .../main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala | 2 -- .../apache/spark/sql/comet/shims/ShimCometParquetUtils.scala | 2 -- 2 files changed, 4 deletions(-) diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala index dbac0c15c..2f386869a 100644 --- a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala @@ -23,8 +23,6 @@ import org.apache.spark.sql.execution.datasources.FileFormat import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat object ShimFileFormat { - val ROW_INDEX = ParquetFileFormat.ROW_INDEX - // A name for a temporary column that holds row indexes computed by the file format reader // until they can be placed in the _metadata struct. val ROW_INDEX_TEMPORARY_COLUMN_NAME = ParquetFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME diff --git a/common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala b/common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala index 0f5ce9e6d..d402cd786 100644 --- a/common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala +++ b/common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala @@ -30,8 +30,6 @@ trait ShimCometParquetUtils { QueryExecutionErrors.foundDuplicateFieldInFieldIdLookupModeError(requiredId, matchedFields) } - val FIELD_ID_METADATA_KEY = ParquetUtils.FIELD_ID_METADATA_KEY - def hasFieldIds(schema: StructType): Boolean = ParquetUtils.hasFieldIds(schema) def hasFieldId(field: StructField): Boolean = ParquetUtils.hasFieldId(field) From b819e99381812cf1623488178a197865af66fa25 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 15 May 2024 12:49:21 -0700 Subject: [PATCH 19/68] address review comments --- .../main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala | 2 -- .../apache/spark/sql/comet/shims/ShimCometParquetUtils.scala | 2 -- 2 files changed, 4 deletions(-) diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala index dbac0c15c..2f386869a 100644 --- a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala @@ -23,8 +23,6 @@ import org.apache.spark.sql.execution.datasources.FileFormat import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat object ShimFileFormat { - val ROW_INDEX = ParquetFileFormat.ROW_INDEX - // A name for a temporary column that holds row indexes computed by the file format reader // until they can be placed in the _metadata struct. val ROW_INDEX_TEMPORARY_COLUMN_NAME = ParquetFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME diff --git a/common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala b/common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala index 0f5ce9e6d..d402cd786 100644 --- a/common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala +++ b/common/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometParquetUtils.scala @@ -30,8 +30,6 @@ trait ShimCometParquetUtils { QueryExecutionErrors.foundDuplicateFieldInFieldIdLookupModeError(requiredId, matchedFields) } - val FIELD_ID_METADATA_KEY = ParquetUtils.FIELD_ID_METADATA_KEY - def hasFieldIds(schema: StructType): Boolean = ParquetUtils.hasFieldIds(schema) def hasFieldId(field: StructField): Boolean = ParquetUtils.hasFieldId(field) From 728bf8d8be17a34f83435a17ca27cd674b731844 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 15 May 2024 01:50:11 -0700 Subject: [PATCH 20/68] build: Enable spark-4.0 tests --- .../org/apache/spark/sql/ExtendedExplainGenerator.scala | 0 spark/src/test/scala/org/apache/comet/CometCastSuite.scala | 2 +- 2 files changed, 1 insertion(+), 1 deletion(-) rename spark/src/main/{scala => spark-3.x}/org/apache/spark/sql/ExtendedExplainGenerator.scala (100%) diff --git a/spark/src/main/scala/org/apache/spark/sql/ExtendedExplainGenerator.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/ExtendedExplainGenerator.scala similarity index 100% rename from spark/src/main/scala/org/apache/spark/sql/ExtendedExplainGenerator.scala rename to spark/src/main/spark-3.x/org/apache/spark/sql/ExtendedExplainGenerator.scala diff --git a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala index 150b7e398..d25815447 100644 --- a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala @@ -1000,7 +1000,7 @@ class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper { .head .replace(".WITH_SUGGESTION] ", "]") .replace(" SQLSTATE: 22003", "") - .replace(" SQLSTATE: 22018a", "")) + .replace(" SQLSTATE: 22018", "")) } else if (CometSparkSessionExtensions.isSpark34Plus) { // for Spark 3.4 we expect to reproduce the error message exactly assert(cometMessage == sparkMessage) From 8374f74092ee5132b5ee90afff283109e5238e54 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 15 May 2024 14:56:43 -0700 Subject: [PATCH 21/68] build: Enable spark-4.0 tests --- .../test/scala/org/apache/comet/CometExpressionSuite.scala | 2 +- spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala b/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala index 28027c5cb..bd86d7fd3 100644 --- a/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala @@ -1398,7 +1398,7 @@ class CometExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelper { CometConf.COMET_SHUFFLE_ENFORCE_MODE_ENABLED.key -> "true", CometConf.COMET_EXEC_ALL_EXPR_ENABLED.key -> "true", CometConf.COMET_EXEC_ALL_OPERATOR_ENABLED.key -> "true", - "spark.sql.extendedExplainProvider" -> "org.apache.comet.ExtendedExplainInfo") { + "spark.sql.extendedExplainProviders" -> "org.apache.comet.ExtendedExplainInfo") { val table = "test" withTable(table) { sql(s"create table $table(c0 int, c1 int , c2 float) using parquet") diff --git a/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala b/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala index db9547fe7..ddea4d26a 100644 --- a/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala +++ b/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala @@ -249,7 +249,7 @@ abstract class CometTestBase var dfSpark: Dataset[Row] = null withSQLConf( CometConf.COMET_ENABLED.key -> "false", - "spark.sql.extendedExplainProvider" -> "") { + "spark.sql.extendedExplainProviders" -> "") { dfSpark = Dataset.ofRows(spark, df.logicalPlan) expected = dfSpark.collect() } @@ -259,7 +259,7 @@ abstract class CometTestBase dfSpark.queryExecution.explainString(ExtendedMode), dfComet.queryExecution.explainString(ExtendedMode)) if (supportsExtendedExplainInfo(dfSpark.queryExecution)) { - assert(diff.contains(expectedInfo)) + assert(expectedInfo.exists(s => diff.contains(s))) } val extendedInfo = new ExtendedExplainInfo().generateExtendedInfo(dfComet.queryExecution.executedPlan) From a4d050b6b221ac1e099eaf46a5e33ec72a4f6392 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 15 May 2024 16:04:41 -0700 Subject: [PATCH 22/68] build: Enable spark-4.0 tests --- .../scala/org/apache/comet/parquet/ParquetReadSuite.scala | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala index ba5849de8..17f008e26 100644 --- a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala +++ b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala @@ -1125,9 +1125,10 @@ abstract class ParquetReadSuite extends CometTestBase { } test("row group skipping doesn't overflow when reading into larger type") { - assume(isSpark34Plus) - + // Spark 4.0 no longer fails for widening types // https://github.com/apache/spark/commit/3361f25dc0ff6e5233903c26ee105711b79ba967 + assume(isSpark34Plus && !isSpark34Plus) + withTempPath { path => Seq(0).toDF("a").write.parquet(path.toString) // Reading integer 'a' as a long isn't supported. Check that an exception is raised instead From 0cd48703c1f031c10263c92117108b901293f72b Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 16 May 2024 10:08:27 -0700 Subject: [PATCH 23/68] address review comments --- .../apache/comet/shims/ShimCometSparkSessionExtensions.scala | 2 ++ .../apache/comet/shims/ShimCometSparkSessionExtensions.scala | 3 +++ .../test/scala/org/apache/comet/CometExpressionSuite.scala | 2 +- spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala | 4 ++-- 4 files changed, 8 insertions(+), 3 deletions(-) diff --git a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala index 7171f8190..f8e68ab02 100644 --- a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala +++ b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala @@ -59,4 +59,6 @@ trait ShimCometSparkSessionExtensions { } true } + + protected val EXTENDED_EXPLAIN_PROVIDERS_KEY = "spark.sql.extendedExplainProviders" } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala index 6316f51a5..9fb7355ee 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala @@ -22,6 +22,7 @@ package org.apache.comet.shims import org.apache.spark.sql.connector.expressions.aggregate.Aggregation import org.apache.spark.sql.execution.{CollectLimitExec, GlobalLimitExec, LocalLimitExec, QueryExecution} import org.apache.spark.sql.execution.datasources.v2.parquet.ParquetScan +import org.apache.spark.sql.internal.SQLConf trait ShimCometSparkSessionExtensions { protected def getPushedAggregate(scan: ParquetScan): Option[Aggregation] = scan.pushedAggregate @@ -31,4 +32,6 @@ trait ShimCometSparkSessionExtensions { protected def getOffset(limit: CollectLimitExec): Int = limit.offset protected def supportsExtendedExplainInfo(qe: QueryExecution): Boolean = true + + protected val EXTENDED_EXPLAIN_PROVIDERS_KEY = SQLConf.EXTENDED_EXPLAIN_PROVIDERS.key } diff --git a/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala b/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala index bd86d7fd3..a61badaab 100644 --- a/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala @@ -1398,7 +1398,7 @@ class CometExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelper { CometConf.COMET_SHUFFLE_ENFORCE_MODE_ENABLED.key -> "true", CometConf.COMET_EXEC_ALL_EXPR_ENABLED.key -> "true", CometConf.COMET_EXEC_ALL_OPERATOR_ENABLED.key -> "true", - "spark.sql.extendedExplainProviders" -> "org.apache.comet.ExtendedExplainInfo") { + EXTENDED_EXPLAIN_PROVIDERS_KEY -> "org.apache.comet.ExtendedExplainInfo") { val table = "test" withTable(table) { sql(s"create table $table(c0 int, c1 int , c2 float) using parquet") diff --git a/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala b/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala index ddea4d26a..869c9d513 100644 --- a/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala +++ b/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala @@ -249,7 +249,7 @@ abstract class CometTestBase var dfSpark: Dataset[Row] = null withSQLConf( CometConf.COMET_ENABLED.key -> "false", - "spark.sql.extendedExplainProviders" -> "") { + EXTENDED_EXPLAIN_PROVIDERS_KEY -> "") { dfSpark = Dataset.ofRows(spark, df.logicalPlan) expected = dfSpark.collect() } @@ -259,7 +259,7 @@ abstract class CometTestBase dfSpark.queryExecution.explainString(ExtendedMode), dfComet.queryExecution.explainString(ExtendedMode)) if (supportsExtendedExplainInfo(dfSpark.queryExecution)) { - assert(expectedInfo.exists(s => diff.contains(s))) + assert(expectedInfo.forall(s => diff.contains(s))) } val extendedInfo = new ExtendedExplainInfo().generateExtendedInfo(dfComet.queryExecution.executedPlan) From f91c7bebe9a0baad7e7860fd2d70fc27853d827e Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 16 May 2024 10:25:55 -0700 Subject: [PATCH 24/68] address review comments --- .../comet/shims/ShimCometSparkSessionExtensions.scala | 8 ++++++-- .../test/scala/org/apache/spark/sql/CometTestBase.scala | 4 +--- 2 files changed, 7 insertions(+), 5 deletions(-) diff --git a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala index f8e68ab02..377485335 100644 --- a/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala +++ b/spark/src/main/spark-3.x/org/apache/comet/shims/ShimCometSparkSessionExtensions.scala @@ -38,6 +38,12 @@ trait ShimCometSparkSessionExtensions { */ def getOffset(limit: LimitExec): Int = getOffsetOpt(limit).getOrElse(0) + /** + * TODO: delete after dropping Spark 3.x support and directly call + * SQLConf.EXTENDED_EXPLAIN_PROVIDERS.key + */ + protected val EXTENDED_EXPLAIN_PROVIDERS_KEY = "spark.sql.extendedExplainProviders" + private def getOffsetOpt(plan: SparkPlan): Option[Int] = plan.getClass.getDeclaredFields .filter(_.getName == "offset") .map { a => a.setAccessible(true); a.get(plan) } @@ -59,6 +65,4 @@ trait ShimCometSparkSessionExtensions { } true } - - protected val EXTENDED_EXPLAIN_PROVIDERS_KEY = "spark.sql.extendedExplainProviders" } diff --git a/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala b/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala index 869c9d513..be46e4b17 100644 --- a/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala +++ b/spark/src/test/scala/org/apache/spark/sql/CometTestBase.scala @@ -247,9 +247,7 @@ abstract class CometTestBase expectedInfo: Set[String]): Unit = { var expected: Array[Row] = Array.empty var dfSpark: Dataset[Row] = null - withSQLConf( - CometConf.COMET_ENABLED.key -> "false", - EXTENDED_EXPLAIN_PROVIDERS_KEY -> "") { + withSQLConf(CometConf.COMET_ENABLED.key -> "false", EXTENDED_EXPLAIN_PROVIDERS_KEY -> "") { dfSpark = Dataset.ofRows(spark, df.logicalPlan) expected = dfSpark.collect() } From c1466613de8426787f1f7a5d216a714a078a873f Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 16 May 2024 13:13:28 -0700 Subject: [PATCH 25/68] build: Enable spark-4.0 tests --- .../test/scala/org/apache/comet/exec/CometExecSuite.scala | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala b/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala index 8f022988f..71c4354d1 100644 --- a/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala +++ b/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala @@ -48,7 +48,7 @@ import org.apache.spark.sql.internal.SQLConf.SESSION_LOCAL_TIMEZONE import org.apache.spark.unsafe.types.UTF8String import org.apache.comet.CometConf -import org.apache.comet.CometSparkSessionExtensions.{isSpark33Plus, isSpark34Plus} +import org.apache.comet.CometSparkSessionExtensions.{isSpark33Plus, isSpark34Plus, isSpark4Plus} class CometExecSuite extends CometTestBase { import testImplicits._ @@ -989,7 +989,11 @@ class CometExecSuite extends CometTestBase { val e = intercept[AnalysisException] { sql("CREATE TABLE t2(name STRING, part INTERVAL) USING PARQUET PARTITIONED BY (part)") }.getMessage - assert(e.contains("Cannot use interval")) + if (isSpark4Plus) { + assert(e.contains(" Cannot use \"INTERVAL\"")) + } else { + assert(e.contains("Cannot use interval")) + } } } } From 8c4bf053eb43123fcb79049e40d25041131c4c70 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 16 May 2024 16:36:18 -0700 Subject: [PATCH 26/68] DisableSuite --- .../org/apache/comet/CometCastSuite.scala | 4 +-- .../comet/CometExpressionCoverageSuite.scala | 7 ++-- .../apache/comet/CometExpressionSuite.scala | 4 +-- .../CometSparkSessionExtensionsSuite.scala | 2 +- .../exec/CometColumnarShuffleSuite.scala | 12 +++---- .../comet/parquet/ParquetReadSuite.scala | 8 ++--- .../org/apache/spark/CometPluginsSuite.scala | 4 +-- .../org/apache/spark/sql/DisableSuite.scala | 32 +++++++++++++++++++ .../comet/CometExpression3_3PlusSuite.scala | 5 ++- .../comet/exec/CometExec3_4PlusSuite.scala | 5 ++- 10 files changed, 57 insertions(+), 26 deletions(-) create mode 100644 spark/src/test/scala/org/apache/spark/sql/DisableSuite.scala diff --git a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala index d25815447..b96360dbd 100644 --- a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala @@ -23,7 +23,7 @@ import java.io.File import scala.util.Random -import org.apache.spark.sql.{CometTestBase, DataFrame, SaveMode} +import org.apache.spark.sql.{CometTestBase, DataFrame, DisableSuite, SaveMode} import org.apache.spark.sql.catalyst.expressions.Cast import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper import org.apache.spark.sql.functions.col @@ -32,7 +32,7 @@ import org.apache.spark.sql.types.{DataType, DataTypes, DecimalType} import org.apache.comet.expressions.{CometCast, Compatible} -class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper { +class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper with DisableSuite { import testImplicits._ private val dataSize = 1000 diff --git a/spark/src/test/scala/org/apache/comet/CometExpressionCoverageSuite.scala b/spark/src/test/scala/org/apache/comet/CometExpressionCoverageSuite.scala index 2011dcd4b..1dfd417b8 100644 --- a/spark/src/test/scala/org/apache/comet/CometExpressionCoverageSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometExpressionCoverageSuite.scala @@ -27,7 +27,7 @@ import scala.collection.mutable import org.scalatest.Ignore import org.scalatest.exceptions.TestFailedException -import org.apache.spark.sql.CometTestBase +import org.apache.spark.sql.{CometTestBase, DisableSuite} import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper /** @@ -37,7 +37,10 @@ import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper * doc/spark_builtin_expr_coverage_agg.txt */ @Ignore -class CometExpressionCoverageSuite extends CometTestBase with AdaptiveSparkPlanHelper { +class CometExpressionCoverageSuite + extends CometTestBase + with AdaptiveSparkPlanHelper + with DisableSuite { import testImplicits._ diff --git a/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala b/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala index a61badaab..c39a15c0d 100644 --- a/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala @@ -20,7 +20,7 @@ package org.apache.comet import org.apache.hadoop.fs.Path -import org.apache.spark.sql.{CometTestBase, DataFrame, Row} +import org.apache.spark.sql.{CometTestBase, DataFrame, DisableSuite, Row} import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper import org.apache.spark.sql.functions.expr import org.apache.spark.sql.internal.SQLConf @@ -29,7 +29,7 @@ import org.apache.spark.sql.types.{Decimal, DecimalType} import org.apache.comet.CometSparkSessionExtensions.{isSpark32, isSpark33Plus, isSpark34Plus} -class CometExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelper { +class CometExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelper with DisableSuite { import testImplicits._ test("coalesce should return correct datatype") { diff --git a/spark/src/test/scala/org/apache/comet/CometSparkSessionExtensionsSuite.scala b/spark/src/test/scala/org/apache/comet/CometSparkSessionExtensionsSuite.scala index fdcd307be..426dfa40a 100644 --- a/spark/src/test/scala/org/apache/comet/CometSparkSessionExtensionsSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometSparkSessionExtensionsSuite.scala @@ -24,7 +24,7 @@ import org.apache.spark.sql._ import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.types._ -class CometSparkSessionExtensionsSuite extends CometTestBase { +class CometSparkSessionExtensionsSuite extends CometTestBase with DisableSuite { test("unsupported Spark types") { Seq( NullType -> false, diff --git a/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala b/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala index 114351fd1..e35eac178 100644 --- a/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala +++ b/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala @@ -24,7 +24,7 @@ import org.scalatest.Tag import org.apache.hadoop.fs.Path import org.apache.spark.{Partitioner, SparkConf} -import org.apache.spark.sql.{CometTestBase, DataFrame, Row} +import org.apache.spark.sql.{CometTestBase, DataFrame, DisableSuite, Row} import org.apache.spark.sql.comet.execution.shuffle.{CometShuffleDependency, CometShuffleExchangeExec, CometShuffleManager} import org.apache.spark.sql.execution.adaptive.{AdaptiveSparkPlanHelper, AQEShuffleReadExec, ShuffleQueryStageExec} import org.apache.spark.sql.execution.exchange.ReusedExchangeExec @@ -944,13 +944,13 @@ abstract class CometColumnarShuffleSuite extends CometTestBase with AdaptiveSpar } } -class CometAsyncShuffleSuite extends CometColumnarShuffleSuite { +class CometAsyncShuffleSuite extends CometColumnarShuffleSuite with DisableSuite { override protected val asyncShuffleEnable: Boolean = true protected val adaptiveExecutionEnabled: Boolean = true } -class CometShuffleSuite extends CometColumnarShuffleSuite { +class CometShuffleSuite extends CometColumnarShuffleSuite with DisableSuite { override protected val asyncShuffleEnable: Boolean = false protected val adaptiveExecutionEnabled: Boolean = true @@ -1035,13 +1035,13 @@ class DisableAQECometShuffleSuite extends CometColumnarShuffleSuite { } } -class DisableAQECometAsyncShuffleSuite extends CometColumnarShuffleSuite { +class DisableAQECometAsyncShuffleSuite extends CometColumnarShuffleSuite with DisableSuite { override protected val asyncShuffleEnable: Boolean = true protected val adaptiveExecutionEnabled: Boolean = false } -class CometShuffleEncryptionSuite extends CometTestBase { +class CometShuffleEncryptionSuite extends CometTestBase with DisableSuite { import testImplicits._ override protected def sparkConf: SparkConf = { @@ -1078,7 +1078,7 @@ class CometShuffleEncryptionSuite extends CometTestBase { } } -class CometShuffleManagerSuite extends CometTestBase { +class CometShuffleManagerSuite extends CometTestBase with DisableSuite { test("should not bypass merge sort if executor cores are too high") { withSQLConf(CometConf.COMET_EXEC_SHUFFLE_ASYNC_MAX_THREAD_NUM.key -> "100") { diff --git a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala index 17f008e26..78bc6fc2d 100644 --- a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala +++ b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala @@ -34,9 +34,7 @@ import org.apache.hadoop.fs.Path import org.apache.parquet.example.data.simple.SimpleGroup import org.apache.parquet.schema.MessageTypeParser import org.apache.spark.SparkException -import org.apache.spark.sql.CometTestBase -import org.apache.spark.sql.DataFrame -import org.apache.spark.sql.Row +import org.apache.spark.sql.{CometTestBase, DataFrame, DisableSuite, Row} import org.apache.spark.sql.catalyst.expressions.GenericInternalRow import org.apache.spark.sql.catalyst.util.DateTimeUtils import org.apache.spark.sql.comet.CometBatchScanExec @@ -1289,7 +1287,7 @@ abstract class ParquetReadSuite extends CometTestBase { } } -class ParquetReadV1Suite extends ParquetReadSuite with AdaptiveSparkPlanHelper { +class ParquetReadV1Suite extends ParquetReadSuite with AdaptiveSparkPlanHelper with DisableSuite { override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit pos: Position): Unit = { super.test(testName, testTags: _*)(withSQLConf(SQLConf.USE_V1_SOURCE_LIST.key -> "parquet") { @@ -1320,7 +1318,7 @@ class ParquetReadV1Suite extends ParquetReadSuite with AdaptiveSparkPlanHelper { } } -class ParquetReadV2Suite extends ParquetReadSuite with AdaptiveSparkPlanHelper { +class ParquetReadV2Suite extends ParquetReadSuite with AdaptiveSparkPlanHelper with DisableSuite { override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit pos: Position): Unit = { super.test(testName, testTags: _*)(withSQLConf(SQLConf.USE_V1_SOURCE_LIST.key -> "") { diff --git a/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala b/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala index 2263b2f99..83e1257e4 100644 --- a/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala +++ b/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala @@ -19,7 +19,7 @@ package org.apache.spark -import org.apache.spark.sql.CometTestBase +import org.apache.spark.sql.{CometTestBase, DisableSuite} class CometPluginsSuite extends CometTestBase { override protected def sparkConf: SparkConf = { @@ -74,7 +74,7 @@ class CometPluginsDefaultSuite extends CometTestBase { } } -class CometPluginsNonOverrideSuite extends CometTestBase { +class CometPluginsNonOverrideSuite extends CometTestBase with DisableSuite { override protected def sparkConf: SparkConf = { val conf = new SparkConf() conf.set("spark.driver.memory", "1G") diff --git a/spark/src/test/scala/org/apache/spark/sql/DisableSuite.scala b/spark/src/test/scala/org/apache/spark/sql/DisableSuite.scala new file mode 100644 index 000000000..d6ad298f0 --- /dev/null +++ b/spark/src/test/scala/org/apache/spark/sql/DisableSuite.scala @@ -0,0 +1,32 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.spark.sql + +import org.scalactic.source.Position +import org.scalatest.Tag + +import org.apache.spark.sql.test.SQLTestUtils + +trait DisableSuite extends SQLTestUtils { + override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit + pos: Position): Unit = { + ignore(testName + " (disabled)", testTags: _*)(testFun) + } +} diff --git a/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala b/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala index 6102777fc..179344db9 100644 --- a/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala +++ b/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala @@ -19,17 +19,16 @@ package org.apache.comet -import org.apache.spark.sql.{Column, CometTestBase} +import org.apache.spark.sql.{Column, CometTestBase, DisableSuite} import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper import org.apache.spark.sql.catalyst.FunctionIdentifier import org.apache.spark.sql.catalyst.expressions.{BloomFilterMightContain, Expression, ExpressionInfo} import org.apache.spark.sql.functions.{col, lit} import org.apache.spark.util.sketch.BloomFilter - import java.io.ByteArrayOutputStream import scala.util.Random -class CometExpression3_3PlusSuite extends CometTestBase with AdaptiveSparkPlanHelper { +class CometExpression3_3PlusSuite extends CometTestBase with AdaptiveSparkPlanHelper with DisableSuite { import testImplicits._ val func_might_contain = new FunctionIdentifier("might_contain") diff --git a/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala index 8d1a68176..69fa84dfe 100644 --- a/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala +++ b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala @@ -22,14 +22,13 @@ package org.apache.comet.exec import org.scalactic.source.Position import org.scalatest.Tag -import org.apache.spark.sql.CometTestBase - +import org.apache.spark.sql.{CometTestBase, DisableSuite} import org.apache.comet.CometConf /** * This test suite contains tests for only Spark 3.4. */ -class CometExec3_4PlusSuite extends CometTestBase { +class CometExec3_4PlusSuite extends CometTestBase with DisableSuite { import testImplicits._ override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit From 225858f50442c55476c028cf022353c73bb87dda Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 16 May 2024 17:07:53 -0700 Subject: [PATCH 27/68] build: Enable spark-4.0 tests --- .../org/apache/comet/CometSparkSessionExtensions.scala | 4 ++-- .../test/scala/org/apache/comet/CometCastSuite.scala | 2 +- .../scala/org/apache/comet/exec/CometExecSuite.scala | 4 ++-- .../spark/sql/comet/CometPlanStabilitySuite.scala | 10 +++++++--- 4 files changed, 12 insertions(+), 8 deletions(-) diff --git a/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala b/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala index 5d4eba589..b86ddabae 100644 --- a/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala +++ b/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala @@ -985,8 +985,8 @@ object CometSparkSessionExtensions extends Logging { org.apache.spark.SPARK_VERSION >= "3.4" } - def isSpark4Plus: Boolean = { - org.apache.spark.SPARK_VERSION >= "4" + def isSpark40Plus: Boolean = { + org.apache.spark.SPARK_VERSION >= "4.0" } /** Calculates required memory overhead in MB per executor process for Comet. */ diff --git a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala index b96360dbd..6c04e1e53 100644 --- a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala @@ -992,7 +992,7 @@ class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper with Dis // We have to workaround https://github.com/apache/datafusion-comet/issues/293 here by // removing the "Execution error: " error message prefix that is added by DataFusion val cometMessage = cometException.getCause.getMessage.replace("Execution error: ", "") - if (CometSparkSessionExtensions.isSpark4Plus) { + if (CometSparkSessionExtensions.isSpark40Plus) { // for Spark 4 we expect to sparkException carries the message assert( cometMessage == sparkException.getMessage diff --git a/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala b/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala index 71c4354d1..21e4e6c8e 100644 --- a/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala +++ b/spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala @@ -48,7 +48,7 @@ import org.apache.spark.sql.internal.SQLConf.SESSION_LOCAL_TIMEZONE import org.apache.spark.unsafe.types.UTF8String import org.apache.comet.CometConf -import org.apache.comet.CometSparkSessionExtensions.{isSpark33Plus, isSpark34Plus, isSpark4Plus} +import org.apache.comet.CometSparkSessionExtensions.{isSpark33Plus, isSpark34Plus, isSpark40Plus} class CometExecSuite extends CometTestBase { import testImplicits._ @@ -989,7 +989,7 @@ class CometExecSuite extends CometTestBase { val e = intercept[AnalysisException] { sql("CREATE TABLE t2(name STRING, part INTERVAL) USING PARQUET PARTITIONED BY (part)") }.getMessage - if (isSpark4Plus) { + if (isSpark40Plus) { assert(e.contains(" Cannot use \"INTERVAL\"")) } else { assert(e.contains("Cannot use interval")) diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala index 90ea79473..a116a0dd8 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala @@ -36,7 +36,7 @@ import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.test.TestSparkSession import org.apache.comet.CometConf -import org.apache.comet.CometSparkSessionExtensions.isSpark34Plus +import org.apache.comet.CometSparkSessionExtensions.{isSpark34Plus, isSpark40Plus} /** * Similar to [[org.apache.spark.sql.PlanStabilitySuite]], checks that TPC-DS Comet plans don't @@ -300,8 +300,10 @@ trait CometPlanStabilitySuite extends DisableAdaptiveExecutionSuite with TPCDSBa } class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { + private val planName = if (isSpark40Plus) { "approved-plans-v1_4-spark4_0" } + else { "approved-plans-v1_4" } override val goldenFilePath: String = - new File(baseResourcePath, "approved-plans-v1_4").getAbsolutePath + new File(baseResourcePath, planName).getAbsolutePath tpcdsQueries.foreach { q => test(s"check simplified (tpcds-v1.4/$q)") { @@ -311,8 +313,10 @@ class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { } class CometTPCDSV2_7_PlanStabilitySuite extends CometPlanStabilitySuite { + private val planName = if (isSpark40Plus) { "approved-plans-v2_7-spark4_0" } + else { "approved-plans-v2_7" } override val goldenFilePath: String = - new File(baseResourcePath, "approved-plans-v2_7").getAbsolutePath + new File(baseResourcePath, planName).getAbsolutePath tpcdsQueriesV2_7_0.foreach { q => test(s"check simplified (tpcds-v2.7.0/$q)") { From 7911e52bc976109beae4f3fd7f994b3ff0d1920e Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 16 May 2024 17:25:32 -0700 Subject: [PATCH 28/68] build: Enable spark-4.0 tests --- docs/source/contributor-guide/development.md | 4 + .../q1/explain.txt | 274 +++++ .../q1/simplified.txt | 68 ++ .../q10/explain.txt | 286 +++++ .../q10/simplified.txt | 75 ++ .../q11/explain.txt | 482 ++++++++ .../q11/simplified.txt | 123 ++ .../q12/explain.txt | 150 +++ .../q12/simplified.txt | 40 + .../q13/explain.txt | 232 ++++ .../q13/simplified.txt | 59 + .../q14a/explain.txt | 800 ++++++++++++ .../q14a/simplified.txt | 214 ++++ .../q14b/explain.txt | 759 ++++++++++++ .../q14b/simplified.txt | 204 ++++ .../q15/explain.txt | 164 +++ .../q15/simplified.txt | 41 + .../q16/explain.txt | 260 ++++ .../q16/simplified.txt | 74 ++ .../q17/explain.txt | 298 +++++ .../q17/simplified.txt | 76 ++ .../q18/explain.txt | 281 +++++ .../q18/simplified.txt | 71 ++ .../q19/explain.txt | 227 ++++ .../q19/simplified.txt | 58 + .../q2/explain.txt | 212 ++++ .../q2/simplified.txt | 59 + .../q20/explain.txt | 150 +++ .../q20/simplified.txt | 40 + .../q21/explain.txt | 169 +++ .../q21/simplified.txt | 42 + .../q22/explain.txt | 169 +++ .../q22/simplified.txt | 42 + .../q23a/explain.txt | 570 +++++++++ .../q23a/simplified.txt | 155 +++ .../q23b/explain.txt | 694 +++++++++++ .../q23b/simplified.txt | 188 +++ .../q24a/explain.txt | 427 +++++++ .../q24a/simplified.txt | 118 ++ .../q24b/explain.txt | 427 +++++++ .../q24b/simplified.txt | 118 ++ .../q25/explain.txt | 298 +++++ .../q25/simplified.txt | 76 ++ .../q26/explain.txt | 208 ++++ .../q26/simplified.txt | 52 + .../q27/explain.txt | 208 ++++ .../q27/simplified.txt | 52 + .../q28/explain.txt | 437 +++++++ .../q28/simplified.txt | 111 ++ .../q29/explain.txt | 326 +++++ .../q29/simplified.txt | 83 ++ .../q3/explain.txt | 125 ++ .../q3/simplified.txt | 31 + .../q30/explain.txt | 324 +++++ .../q30/simplified.txt | 81 ++ .../q31/explain.txt | 616 ++++++++++ .../q31/simplified.txt | 159 +++ .../q32/explain.txt | 209 ++++ .../q32/simplified.txt | 52 + .../q33/explain.txt | 405 +++++++ .../q33/simplified.txt | 105 ++ .../q34/explain.txt | 218 ++++ .../q34/simplified.txt | 56 + .../q35/explain.txt | 281 +++++ .../q35/simplified.txt | 74 ++ .../q36/explain.txt | 194 +++ .../q36/simplified.txt | 51 + .../q37/explain.txt | 179 +++ .../q37/simplified.txt | 44 + .../q38/explain.txt | 321 +++++ .../q38/simplified.txt | 81 ++ .../q39a/explain.txt | 318 +++++ .../q39a/simplified.txt | 81 ++ .../q39b/explain.txt | 318 +++++ .../q39b/simplified.txt | 81 ++ .../q4/explain.txt | 698 +++++++++++ .../q4/simplified.txt | 179 +++ .../q40/explain.txt | 218 ++++ .../q40/simplified.txt | 60 + .../q41/explain.txt | 121 ++ .../q41/simplified.txt | 29 + .../q42/explain.txt | 125 ++ .../q42/simplified.txt | 31 + .../q43/explain.txt | 125 ++ .../q43/simplified.txt | 31 + .../q44/explain.txt | 286 +++++ .../q44/simplified.txt | 81 ++ .../q45/explain.txt | 242 ++++ .../q45/simplified.txt | 61 + .../q46/explain.txt | 258 ++++ .../q46/simplified.txt | 65 + .../q47/explain.txt | 279 +++++ .../q47/simplified.txt | 81 ++ .../q48/explain.txt | 198 +++ .../q48/simplified.txt | 50 + .../q49/explain.txt | 471 ++++++++ .../q49/simplified.txt | 133 ++ .../q5/explain.txt | 468 +++++++ .../q5/simplified.txt | 130 ++ .../q50/explain.txt | 199 +++ .../q50/simplified.txt | 50 + .../q51/explain.txt | 245 ++++ .../q51/simplified.txt | 75 ++ .../q52/explain.txt | 125 ++ .../q52/simplified.txt | 31 + .../q53/explain.txt | 194 +++ .../q53/simplified.txt | 51 + .../q54/explain.txt | 489 ++++++++ .../q54/simplified.txt | 128 ++ .../q55/explain.txt | 125 ++ .../q55/simplified.txt | 31 + .../q56/explain.txt | 405 +++++++ .../q56/simplified.txt | 105 ++ .../q57/explain.txt | 279 +++++ .../q57/simplified.txt | 81 ++ .../q58/explain.txt | 386 ++++++ .../q58/simplified.txt | 98 ++ .../q59/explain.txt | 256 ++++ .../q59/simplified.txt | 66 + .../q6/explain.txt | 311 +++++ .../q6/simplified.txt | 79 ++ .../q60/explain.txt | 405 +++++++ .../q60/simplified.txt | 105 ++ .../q61/explain.txt | 417 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311 +++++ .../q6/simplified.txt | 79 ++ .../q64/explain.txt | 1074 +++++++++++++++++ .../q64/simplified.txt | 289 +++++ .../q67a/explain.txt | 466 +++++++ .../q67a/simplified.txt | 127 ++ .../q70a/explain.txt | 368 ++++++ .../q70a/simplified.txt | 100 ++ .../q72/explain.txt | 433 +++++++ .../q72/simplified.txt | 116 ++ .../q74/explain.txt | 477 ++++++++ .../q74/simplified.txt | 122 ++ .../q75/explain.txt | 779 ++++++++++++ .../q75/simplified.txt | 240 ++++ .../q77a/explain.txt | 632 ++++++++++ .../q77a/simplified.txt | 168 +++ .../q78/explain.txt | 431 +++++++ .../q78/simplified.txt | 127 ++ .../q80a/explain.txt | 730 +++++++++++ .../q80a/simplified.txt | 207 ++++ .../q86a/explain.txt | 240 ++++ .../q86a/simplified.txt | 66 + .../q98/explain.txt | 155 +++ .../q98/simplified.txt | 43 + .../sql/comet/CometPlanStabilitySuite.scala | 10 +- 272 files changed, 59418 insertions(+), 4 deletions(-) create mode 100644 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mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt create mode 100644 spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt diff --git a/docs/source/contributor-guide/development.md b/docs/source/contributor-guide/development.md index 0121d9f46..913eea408 100644 --- a/docs/source/contributor-guide/development.md +++ b/docs/source/contributor-guide/development.md @@ -92,11 +92,13 @@ The plan stability testing framework is located in the `spark` module and can be ```sh ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV1_4_PlanStabilitySuite" test +./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV1_4_PlanStabilitySuite" -Pspark-4.0 -nsu test ``` and ```sh ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV2_7_PlanStabilitySuite" test +./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV2_7_PlanStabilitySuite" -Pspark-4.0 -nsu test ``` If your pull request changes the query plans generated by Comet, you should regenerate the golden files. @@ -104,11 +106,13 @@ To regenerate the golden files, you can run the following command: ```sh SPARK_GENERATE_GOLDEN_FILES=1 ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV1_4_PlanStabilitySuite" test +SPARK_GENERATE_GOLDEN_FILES=1 ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV1_4_PlanStabilitySuite" -Pspark-4.0 -nsu test ``` and ```sh SPARK_GENERATE_GOLDEN_FILES=1 ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV2_7_PlanStabilitySuite" test +SPARK_GENERATE_GOLDEN_FILES=1 ./mvnw -pl spark -Dsuites="org.apache.spark.sql.comet.CometTPCDSV2_7_PlanStabilitySuite" -Pspark-4.0 -nsu test ``` ## Benchmark diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt new file mode 100644 index 000000000..d4d5ff424 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt @@ -0,0 +1,274 @@ +== Physical Plan == +TakeOrderedAndProject (40) ++- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (26) + : : +- * BroadcastHashJoin Inner BuildRight (25) + : : :- * Filter (10) + : : : +- * HashAggregate (9) + : : : +- Exchange (8) + : : : +- * HashAggregate (7) + : : : +- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_returns (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (24) + : : +- * Filter (23) + : : +- * HashAggregate (22) + : : +- Exchange (21) + : : +- * HashAggregate (20) + : : +- * HashAggregate (19) + : : +- Exchange (18) + : : +- * HashAggregate (17) + : : +- * Project (16) + : : +- * BroadcastHashJoin Inner BuildRight (15) + : : :- * Filter (13) + : : : +- * ColumnarToRow (12) + : : : +- CometScan parquet spark_catalog.default.store_returns (11) + : : +- ReusedExchange (14) + : +- BroadcastExchange (31) + : +- * Project (30) + : +- * Filter (29) + : +- * ColumnarToRow (28) + : +- CometScan parquet spark_catalog.default.store (27) + +- BroadcastExchange (37) + +- * Filter (36) + +- * ColumnarToRow (35) + +- CometScan parquet spark_catalog.default.customer (34) + + +(1) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#4), dynamicpruningexpression(sr_returned_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(sr_store_sk), IsNotNull(sr_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 2] +Input [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4] + +(3) Filter [codegen id : 2] +Input [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4] +Condition : (isnotnull(sr_store_sk#2) AND isnotnull(sr_customer_sk#1)) + +(4) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [sr_returned_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 2] +Output [3]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3] +Input [5]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4, d_date_sk#6] + +(7) HashAggregate [codegen id : 2] +Input [3]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3] +Keys [2]: [sr_customer_sk#1, sr_store_sk#2] +Functions [1]: [partial_sum(UnscaledValue(sr_return_amt#3))] +Aggregate Attributes [1]: [sum#7] +Results [3]: [sr_customer_sk#1, sr_store_sk#2, sum#8] + +(8) Exchange +Input [3]: [sr_customer_sk#1, sr_store_sk#2, sum#8] +Arguments: hashpartitioning(sr_customer_sk#1, sr_store_sk#2, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(9) HashAggregate [codegen id : 9] +Input [3]: [sr_customer_sk#1, sr_store_sk#2, sum#8] +Keys [2]: [sr_customer_sk#1, sr_store_sk#2] +Functions [1]: [sum(UnscaledValue(sr_return_amt#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(sr_return_amt#3))#9] +Results [3]: [sr_customer_sk#1 AS ctr_customer_sk#10, sr_store_sk#2 AS ctr_store_sk#11, MakeDecimal(sum(UnscaledValue(sr_return_amt#3))#9,17,2) AS ctr_total_return#12] + +(10) Filter [codegen id : 9] +Input [3]: [ctr_customer_sk#10, ctr_store_sk#11, ctr_total_return#12] +Condition : isnotnull(ctr_total_return#12) + +(11) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15, sr_returned_date_sk#16] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#16), dynamicpruningexpression(sr_returned_date_sk#16 IN dynamicpruning#17)] +PushedFilters: [IsNotNull(sr_store_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [4]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15, sr_returned_date_sk#16] + +(13) Filter [codegen id : 4] +Input [4]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15, sr_returned_date_sk#16] +Condition : isnotnull(sr_store_sk#14) + +(14) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#18] + +(15) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [sr_returned_date_sk#16] +Right keys [1]: [d_date_sk#18] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 4] +Output [3]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15] +Input [5]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15, sr_returned_date_sk#16, d_date_sk#18] + +(17) HashAggregate [codegen id : 4] +Input [3]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15] +Keys [2]: [sr_customer_sk#13, sr_store_sk#14] +Functions [1]: [partial_sum(UnscaledValue(sr_return_amt#15))] +Aggregate Attributes [1]: [sum#19] +Results [3]: [sr_customer_sk#13, sr_store_sk#14, sum#20] + +(18) Exchange +Input [3]: [sr_customer_sk#13, sr_store_sk#14, sum#20] +Arguments: hashpartitioning(sr_customer_sk#13, sr_store_sk#14, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(19) HashAggregate [codegen id : 5] +Input [3]: [sr_customer_sk#13, sr_store_sk#14, sum#20] +Keys [2]: [sr_customer_sk#13, sr_store_sk#14] +Functions [1]: [sum(UnscaledValue(sr_return_amt#15))] +Aggregate Attributes [1]: [sum(UnscaledValue(sr_return_amt#15))#9] +Results [2]: [sr_store_sk#14 AS ctr_store_sk#21, MakeDecimal(sum(UnscaledValue(sr_return_amt#15))#9,17,2) AS ctr_total_return#22] + +(20) HashAggregate [codegen id : 5] +Input [2]: [ctr_store_sk#21, ctr_total_return#22] +Keys [1]: [ctr_store_sk#21] +Functions [1]: [partial_avg(ctr_total_return#22)] +Aggregate Attributes [2]: [sum#23, count#24] +Results [3]: [ctr_store_sk#21, sum#25, count#26] + +(21) Exchange +Input [3]: [ctr_store_sk#21, sum#25, count#26] +Arguments: hashpartitioning(ctr_store_sk#21, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 6] +Input [3]: [ctr_store_sk#21, sum#25, count#26] +Keys [1]: [ctr_store_sk#21] +Functions [1]: [avg(ctr_total_return#22)] +Aggregate Attributes [1]: [avg(ctr_total_return#22)#27] +Results [2]: [(avg(ctr_total_return#22)#27 * 1.2) AS (avg(ctr_total_return) * 1.2)#28, ctr_store_sk#21] + +(23) Filter [codegen id : 6] +Input [2]: [(avg(ctr_total_return) * 1.2)#28, ctr_store_sk#21] +Condition : isnotnull((avg(ctr_total_return) * 1.2)#28) + +(24) BroadcastExchange +Input [2]: [(avg(ctr_total_return) * 1.2)#28, ctr_store_sk#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, true] as bigint)),false), [plan_id=4] + +(25) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ctr_store_sk#11] +Right keys [1]: [ctr_store_sk#21] +Join type: Inner +Join condition: (cast(ctr_total_return#12 as decimal(24,7)) > (avg(ctr_total_return) * 1.2)#28) + +(26) Project [codegen id : 9] +Output [2]: [ctr_customer_sk#10, ctr_store_sk#11] +Input [5]: [ctr_customer_sk#10, ctr_store_sk#11, ctr_total_return#12, (avg(ctr_total_return) * 1.2)#28, ctr_store_sk#21] + +(27) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#29, s_state#30] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(28) ColumnarToRow [codegen id : 7] +Input [2]: [s_store_sk#29, s_state#30] + +(29) Filter [codegen id : 7] +Input [2]: [s_store_sk#29, s_state#30] +Condition : ((isnotnull(s_state#30) AND (s_state#30 = TN)) AND isnotnull(s_store_sk#29)) + +(30) Project [codegen id : 7] +Output [1]: [s_store_sk#29] +Input [2]: [s_store_sk#29, s_state#30] + +(31) BroadcastExchange +Input [1]: [s_store_sk#29] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ctr_store_sk#11] +Right keys [1]: [s_store_sk#29] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [1]: [ctr_customer_sk#10] +Input [3]: [ctr_customer_sk#10, ctr_store_sk#11, s_store_sk#29] + +(34) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#31, c_customer_id#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 8] +Input [2]: [c_customer_sk#31, c_customer_id#32] + +(36) Filter [codegen id : 8] +Input [2]: [c_customer_sk#31, c_customer_id#32] +Condition : isnotnull(c_customer_sk#31) + +(37) BroadcastExchange +Input [2]: [c_customer_sk#31, c_customer_id#32] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ctr_customer_sk#10] +Right keys [1]: [c_customer_sk#31] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [1]: [c_customer_id#32] +Input [3]: [ctr_customer_sk#10, c_customer_sk#31, c_customer_id#32] + +(40) TakeOrderedAndProject +Input [1]: [c_customer_id#32] +Arguments: 100, [c_customer_id#32 ASC NULLS FIRST], [c_customer_id#32] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = sr_returned_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (45) ++- * Project (44) + +- * Filter (43) + +- * ColumnarToRow (42) + +- CometScan parquet spark_catalog.default.date_dim (41) + + +(41) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_year#33] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(42) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#6, d_year#33] + +(43) Filter [codegen id : 1] +Input [2]: [d_date_sk#6, d_year#33] +Condition : ((isnotnull(d_year#33) AND (d_year#33 = 2000)) AND isnotnull(d_date_sk#6)) + +(44) Project [codegen id : 1] +Output [1]: [d_date_sk#6] +Input [2]: [d_date_sk#6, d_year#33] + +(45) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 11 Hosting Expression = sr_returned_date_sk#16 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt new file mode 100644 index 000000000..1475a3732 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt @@ -0,0 +1,68 @@ +TakeOrderedAndProject [c_customer_id] + WholeStageCodegen (9) + Project [c_customer_id] + BroadcastHashJoin [ctr_customer_sk,c_customer_sk] + Project [ctr_customer_sk] + BroadcastHashJoin [ctr_store_sk,s_store_sk] + Project [ctr_customer_sk,ctr_store_sk] + BroadcastHashJoin [ctr_store_sk,ctr_store_sk,ctr_total_return,(avg(ctr_total_return) * 1.2)] + Filter [ctr_total_return] + HashAggregate [sr_customer_sk,sr_store_sk,sum] [sum(UnscaledValue(sr_return_amt)),ctr_customer_sk,ctr_store_sk,ctr_total_return,sum] + InputAdapter + Exchange [sr_customer_sk,sr_store_sk] #1 + WholeStageCodegen (2) + HashAggregate [sr_customer_sk,sr_store_sk,sr_return_amt] [sum,sum] + Project [sr_customer_sk,sr_store_sk,sr_return_amt] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Filter [sr_store_sk,sr_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_customer_sk,sr_store_sk,sr_return_amt,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (6) + Filter [(avg(ctr_total_return) * 1.2)] + HashAggregate [ctr_store_sk,sum,count] [avg(ctr_total_return),(avg(ctr_total_return) * 1.2),sum,count] + InputAdapter + Exchange [ctr_store_sk] #4 + WholeStageCodegen (5) + HashAggregate [ctr_store_sk,ctr_total_return] [sum,count,sum,count] + HashAggregate [sr_customer_sk,sr_store_sk,sum] [sum(UnscaledValue(sr_return_amt)),ctr_store_sk,ctr_total_return,sum] + InputAdapter + Exchange [sr_customer_sk,sr_store_sk] #5 + WholeStageCodegen (4) + HashAggregate [sr_customer_sk,sr_store_sk,sr_return_amt] [sum,sum] + Project [sr_customer_sk,sr_store_sk,sr_return_amt] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Filter [sr_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_customer_sk,sr_store_sk,sr_return_amt,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + Project [s_store_sk] + Filter [s_state,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + Filter [c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt new file mode 100644 index 000000000..5c21b8b9b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt @@ -0,0 +1,286 @@ +== Physical Plan == +TakeOrderedAndProject (43) ++- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (26) + : : +- * Filter (25) + : : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (24) + : : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (17) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (9) + : : : : +- * Project (8) + : : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : : :- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : +- ReusedExchange (6) + : : : +- BroadcastExchange (16) + : : : +- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- BroadcastExchange (23) + : : +- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * ColumnarToRow (19) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) + : : +- ReusedExchange (20) + : +- BroadcastExchange (31) + : +- * Project (30) + : +- * Filter (29) + : +- * ColumnarToRow (28) + : +- CometScan parquet spark_catalog.default.customer_address (27) + +- BroadcastExchange (37) + +- * Filter (36) + +- * ColumnarToRow (35) + +- CometScan parquet spark_catalog.default.customer_demographics (34) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] + +(3) Filter [codegen id : 9] +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#6, ss_sold_date_sk#7] + +(6) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#9] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#6] +Input [3]: [ss_customer_sk#6, ss_sold_date_sk#7, d_date_sk#9] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ss_customer_sk#6] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#11), dynamicpruningexpression(ws_sold_date_sk#11 IN dynamicpruning#12)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] + +(13) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#13] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#11] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#10] +Input [3]: [ws_bill_customer_sk#10, ws_sold_date_sk#11, d_date_sk#13] + +(16) BroadcastExchange +Input [1]: [ws_bill_customer_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ws_bill_customer_sk#10] +Join type: ExistenceJoin(exists#2) +Join condition: None + +(18) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#15), dynamicpruningexpression(cs_sold_date_sk#15 IN dynamicpruning#16)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] + +(20) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#17] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#15] +Right keys [1]: [d_date_sk#17] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#14] +Input [3]: [cs_ship_customer_sk#14, cs_sold_date_sk#15, d_date_sk#17] + +(23) BroadcastExchange +Input [1]: [cs_ship_customer_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [cs_ship_customer_sk#14] +Join type: ExistenceJoin(exists#1) +Join condition: None + +(25) Filter [codegen id : 9] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] +Condition : (exists#2 OR exists#1) + +(26) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#4, c_current_addr_sk#5] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#18, ca_county#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_county, [Dona Ana County,Jefferson County,La Porte County,Rush County,Toole County]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_county#19] + +(29) Filter [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_county#19] +Condition : (ca_county#19 IN (Rush County,Toole County,Jefferson County,Dona Ana County,La Porte County) AND isnotnull(ca_address_sk#18)) + +(30) Project [codegen id : 7] +Output [1]: [ca_address_sk#18] +Input [2]: [ca_address_sk#18, ca_county#19] + +(31) BroadcastExchange +Input [1]: [ca_address_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#5] +Right keys [1]: [ca_address_sk#18] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [1]: [c_current_cdemo_sk#4] +Input [3]: [c_current_cdemo_sk#4, c_current_addr_sk#5, ca_address_sk#18] + +(34) Scan parquet spark_catalog.default.customer_demographics +Output [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 8] +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] + +(36) Filter [codegen id : 8] +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Condition : isnotnull(cd_demo_sk#20) + +(37) BroadcastExchange +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#4] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Input [10]: [c_current_cdemo_sk#4, cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] + +(40) HashAggregate [codegen id : 9] +Input [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Keys [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#29] +Results [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] + +(41) Exchange +Input [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] +Arguments: hashpartitioning(cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(42) HashAggregate [codegen id : 10] +Input [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] +Keys [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#31] +Results [14]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, count(1)#31 AS cnt1#32, cd_purchase_estimate#24, count(1)#31 AS cnt2#33, cd_credit_rating#25, count(1)#31 AS cnt3#34, cd_dep_count#26, count(1)#31 AS cnt4#35, cd_dep_employed_count#27, count(1)#31 AS cnt5#36, cd_dep_college_count#28, count(1)#31 AS cnt6#37] + +(43) TakeOrderedAndProject +Input [14]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cnt1#32, cd_purchase_estimate#24, cnt2#33, cd_credit_rating#25, cnt3#34, cd_dep_count#26, cnt4#35, cd_dep_employed_count#27, cnt5#36, cd_dep_college_count#28, cnt6#37] +Arguments: 100, [cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FIRST, cd_education_status#23 ASC NULLS FIRST, cd_purchase_estimate#24 ASC NULLS FIRST, cd_credit_rating#25 ASC NULLS FIRST, cd_dep_count#26 ASC NULLS FIRST, cd_dep_employed_count#27 ASC NULLS FIRST, cd_dep_college_count#28 ASC NULLS FIRST], [cd_gender#21, cd_marital_status#22, cd_education_status#23, cnt1#32, cd_purchase_estimate#24, cnt2#33, cd_credit_rating#25, cnt3#34, cd_dep_count#26, cnt4#35, cd_dep_employed_count#27, cnt5#36, cd_dep_college_count#28, cnt6#37] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (48) ++- * Project (47) + +- * Filter (46) + +- * ColumnarToRow (45) + +- CometScan parquet spark_catalog.default.date_dim (44) + + +(44) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#38, d_moy#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2002), GreaterThanOrEqual(d_moy,1), LessThanOrEqual(d_moy,4), IsNotNull(d_date_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#38, d_moy#39] + +(46) Filter [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#38, d_moy#39] +Condition : (((((isnotnull(d_year#38) AND isnotnull(d_moy#39)) AND (d_year#38 = 2002)) AND (d_moy#39 >= 1)) AND (d_moy#39 <= 4)) AND isnotnull(d_date_sk#9)) + +(47) Project [codegen id : 1] +Output [1]: [d_date_sk#9] +Input [3]: [d_date_sk#9, d_year#38, d_moy#39] + +(48) BroadcastExchange +Input [1]: [d_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#11 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 18 Hosting Expression = cs_sold_date_sk#15 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt new file mode 100644 index 000000000..e31b38b47 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt @@ -0,0 +1,75 @@ +TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,cnt1,cnt2,cnt3,cnt4,cnt5,cnt6] + WholeStageCodegen (10) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,count] [count(1),cnt1,cnt2,cnt3,cnt4,cnt5,cnt6,count] + InputAdapter + Exchange [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] #1 + WholeStageCodegen (9) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] [count,count] + Project [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + Filter [exists,exists] + BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_current_addr_sk,c_current_cdemo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + Project [ca_address_sk] + Filter [ca_county,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + Filter [cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt new file mode 100644 index 000000000..f821d2a67 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt @@ -0,0 +1,482 @@ +== Physical Plan == +TakeOrderedAndProject (72) ++- * Project (71) + +- * BroadcastHashJoin Inner BuildRight (70) + :- * Project (53) + : +- * BroadcastHashJoin Inner BuildRight (52) + : :- * Project (34) + : : +- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * Project (28) + : : +- * BroadcastHashJoin Inner BuildRight (27) + : : :- * Project (25) + : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : :- * Filter (19) + : : : : +- * ColumnarToRow (18) + : : : : +- CometScan parquet spark_catalog.default.customer (17) + : : : +- BroadcastExchange (23) + : : : +- * Filter (22) + : : : +- * ColumnarToRow (21) + : : : +- CometScan parquet spark_catalog.default.store_sales (20) + : : +- ReusedExchange (26) + : +- BroadcastExchange (51) + : +- * Filter (50) + : +- * HashAggregate (49) + : +- Exchange (48) + : +- * HashAggregate (47) + : +- * Project (46) + : +- * BroadcastHashJoin Inner BuildRight (45) + : :- * Project (43) + : : +- * BroadcastHashJoin Inner BuildRight (42) + : : :- * Filter (37) + : : : +- * ColumnarToRow (36) + : : : +- CometScan parquet spark_catalog.default.customer (35) + : : +- BroadcastExchange (41) + : : +- * Filter (40) + : : +- * ColumnarToRow (39) + : : +- CometScan parquet spark_catalog.default.web_sales (38) + : +- ReusedExchange (44) + +- BroadcastExchange (69) + +- * HashAggregate (68) + +- Exchange (67) + +- * HashAggregate (66) + +- * Project (65) + +- * BroadcastHashJoin Inner BuildRight (64) + :- * Project (62) + : +- * BroadcastHashJoin Inner BuildRight (61) + : :- * Filter (56) + : : +- * ColumnarToRow (55) + : : +- CometScan parquet spark_catalog.default.customer (54) + : +- BroadcastExchange (60) + : +- * Filter (59) + : +- * ColumnarToRow (58) + : +- CometScan parquet spark_catalog.default.web_sales (57) + +- ReusedExchange (63) + + +(1) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] + +(3) Filter [codegen id : 3] +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_sold_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] + +(6) Filter [codegen id : 1] +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Condition : isnotnull(ss_customer_sk#9) + +(7) BroadcastExchange +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#9] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Input [12]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] + +(10) ReusedExchange [Reuses operator id: 76] +Output [2]: [d_date_sk#14, d_year#15] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#12] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, d_year#15] +Input [12]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12, d_date_sk#14, d_year#15] + +(13) HashAggregate [codegen id : 3] +Input [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, d_year#15] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Functions [1]: [partial_sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))] +Aggregate Attributes [1]: [sum#16] +Results [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] + +(14) Exchange +Input [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] +Arguments: hashpartitioning(c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 16] +Input [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Functions [1]: [sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))#18] +Results [2]: [c_customer_id#2 AS customer_id#19, MakeDecimal(sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))#18,18,2) AS year_total#20] + +(16) Filter [codegen id : 16] +Input [2]: [customer_id#19, year_total#20] +Condition : (isnotnull(year_total#20) AND (year_total#20 > 0.00)) + +(17) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 6] +Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] + +(19) Filter [codegen id : 6] +Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_customer_id#22)) + +(20) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#32), dynamicpruningexpression(ss_sold_date_sk#32 IN dynamicpruning#33)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] + +(22) Filter [codegen id : 4] +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Condition : isnotnull(ss_customer_sk#29) + +(23) BroadcastExchange +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_customer_sk#21] +Right keys [1]: [ss_customer_sk#29] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Input [12]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] + +(26) ReusedExchange [Reuses operator id: 80] +Output [2]: [d_date_sk#34, d_year#35] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#32] +Right keys [1]: [d_date_sk#34] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, d_year#35] +Input [12]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32, d_date_sk#34, d_year#35] + +(29) HashAggregate [codegen id : 6] +Input [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, d_year#35] +Keys [8]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Functions [1]: [partial_sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))] +Aggregate Attributes [1]: [sum#36] +Results [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] + +(30) Exchange +Input [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] +Arguments: hashpartitioning(c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] +Keys [8]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Functions [1]: [sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))#18] +Results [3]: [c_customer_id#22 AS customer_id#38, c_preferred_cust_flag#25 AS customer_preferred_cust_flag#39, MakeDecimal(sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))#18,18,2) AS year_total#40] + +(32) BroadcastExchange +Input [3]: [customer_id#38, customer_preferred_cust_flag#39, year_total#40] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#38] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 16] +Output [4]: [customer_id#19, year_total#20, customer_preferred_cust_flag#39, year_total#40] +Input [5]: [customer_id#19, year_total#20, customer_id#38, customer_preferred_cust_flag#39, year_total#40] + +(35) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#41, c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(36) ColumnarToRow [codegen id : 10] +Input [8]: [c_customer_sk#41, c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48] + +(37) Filter [codegen id : 10] +Input [8]: [c_customer_sk#41, c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48] +Condition : (isnotnull(c_customer_sk#41) AND isnotnull(c_customer_id#42)) + +(38) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#52), dynamicpruningexpression(ws_sold_date_sk#52 IN dynamicpruning#53)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(39) ColumnarToRow [codegen id : 8] +Input [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] + +(40) Filter [codegen id : 8] +Input [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] +Condition : isnotnull(ws_bill_customer_sk#49) + +(41) BroadcastExchange +Input [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(42) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [c_customer_sk#41] +Right keys [1]: [ws_bill_customer_sk#49] +Join type: Inner +Join condition: None + +(43) Project [codegen id : 10] +Output [10]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] +Input [12]: [c_customer_sk#41, c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] + +(44) ReusedExchange [Reuses operator id: 76] +Output [2]: [d_date_sk#54, d_year#55] + +(45) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#52] +Right keys [1]: [d_date_sk#54] +Join type: Inner +Join condition: None + +(46) Project [codegen id : 10] +Output [10]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, ws_ext_discount_amt#50, ws_ext_list_price#51, d_year#55] +Input [12]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52, d_date_sk#54, d_year#55] + +(47) HashAggregate [codegen id : 10] +Input [10]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, ws_ext_discount_amt#50, ws_ext_list_price#51, d_year#55] +Keys [8]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55] +Functions [1]: [partial_sum(UnscaledValue((ws_ext_list_price#51 - ws_ext_discount_amt#50)))] +Aggregate Attributes [1]: [sum#56] +Results [9]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55, sum#57] + +(48) Exchange +Input [9]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55, sum#57] +Arguments: hashpartitioning(c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(49) HashAggregate [codegen id : 11] +Input [9]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55, sum#57] +Keys [8]: [c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48, d_year#55] +Functions [1]: [sum(UnscaledValue((ws_ext_list_price#51 - ws_ext_discount_amt#50)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ws_ext_list_price#51 - ws_ext_discount_amt#50)))#58] +Results [2]: [c_customer_id#42 AS customer_id#59, MakeDecimal(sum(UnscaledValue((ws_ext_list_price#51 - ws_ext_discount_amt#50)))#58,18,2) AS year_total#60] + +(50) Filter [codegen id : 11] +Input [2]: [customer_id#59, year_total#60] +Condition : (isnotnull(year_total#60) AND (year_total#60 > 0.00)) + +(51) BroadcastExchange +Input [2]: [customer_id#59, year_total#60] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(52) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#59] +Join type: Inner +Join condition: None + +(53) Project [codegen id : 16] +Output [5]: [customer_id#19, year_total#20, customer_preferred_cust_flag#39, year_total#40, year_total#60] +Input [6]: [customer_id#19, year_total#20, customer_preferred_cust_flag#39, year_total#40, customer_id#59, year_total#60] + +(54) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#61, c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(55) ColumnarToRow [codegen id : 14] +Input [8]: [c_customer_sk#61, c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68] + +(56) Filter [codegen id : 14] +Input [8]: [c_customer_sk#61, c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68] +Condition : (isnotnull(c_customer_sk#61) AND isnotnull(c_customer_id#62)) + +(57) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#72), dynamicpruningexpression(ws_sold_date_sk#72 IN dynamicpruning#73)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(58) ColumnarToRow [codegen id : 12] +Input [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] + +(59) Filter [codegen id : 12] +Input [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] +Condition : isnotnull(ws_bill_customer_sk#69) + +(60) BroadcastExchange +Input [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(61) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [c_customer_sk#61] +Right keys [1]: [ws_bill_customer_sk#69] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 14] +Output [10]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] +Input [12]: [c_customer_sk#61, c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] + +(63) ReusedExchange [Reuses operator id: 80] +Output [2]: [d_date_sk#74, d_year#75] + +(64) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_sold_date_sk#72] +Right keys [1]: [d_date_sk#74] +Join type: Inner +Join condition: None + +(65) Project [codegen id : 14] +Output [10]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, ws_ext_discount_amt#70, ws_ext_list_price#71, d_year#75] +Input [12]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72, d_date_sk#74, d_year#75] + +(66) HashAggregate [codegen id : 14] +Input [10]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, ws_ext_discount_amt#70, ws_ext_list_price#71, d_year#75] +Keys [8]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75] +Functions [1]: [partial_sum(UnscaledValue((ws_ext_list_price#71 - ws_ext_discount_amt#70)))] +Aggregate Attributes [1]: [sum#76] +Results [9]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75, sum#77] + +(67) Exchange +Input [9]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75, sum#77] +Arguments: hashpartitioning(c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(68) HashAggregate [codegen id : 15] +Input [9]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75, sum#77] +Keys [8]: [c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68, d_year#75] +Functions [1]: [sum(UnscaledValue((ws_ext_list_price#71 - ws_ext_discount_amt#70)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ws_ext_list_price#71 - ws_ext_discount_amt#70)))#58] +Results [2]: [c_customer_id#62 AS customer_id#78, MakeDecimal(sum(UnscaledValue((ws_ext_list_price#71 - ws_ext_discount_amt#70)))#58,18,2) AS year_total#79] + +(69) BroadcastExchange +Input [2]: [customer_id#78, year_total#79] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=11] + +(70) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#78] +Join type: Inner +Join condition: (CASE WHEN (year_total#60 > 0.00) THEN (year_total#79 / year_total#60) END > CASE WHEN (year_total#20 > 0.00) THEN (year_total#40 / year_total#20) END) + +(71) Project [codegen id : 16] +Output [1]: [customer_preferred_cust_flag#39] +Input [7]: [customer_id#19, year_total#20, customer_preferred_cust_flag#39, year_total#40, year_total#60, customer_id#78, year_total#79] + +(72) TakeOrderedAndProject +Input [1]: [customer_preferred_cust_flag#39] +Arguments: 100, [customer_preferred_cust_flag#39 ASC NULLS FIRST], [customer_preferred_cust_flag#39] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (76) ++- * Filter (75) + +- * ColumnarToRow (74) + +- CometScan parquet spark_catalog.default.date_dim (73) + + +(73) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(74) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#15] + +(75) Filter [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#15] +Condition : ((isnotnull(d_year#15) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#14)) + +(76) BroadcastExchange +Input [2]: [d_date_sk#14, d_year#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#32 IN dynamicpruning#33 +BroadcastExchange (80) ++- * Filter (79) + +- * ColumnarToRow (78) + +- CometScan parquet spark_catalog.default.date_dim (77) + + +(77) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#34, d_year#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(78) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#34, d_year#35] + +(79) Filter [codegen id : 1] +Input [2]: [d_date_sk#34, d_year#35] +Condition : ((isnotnull(d_year#35) AND (d_year#35 = 2002)) AND isnotnull(d_date_sk#34)) + +(80) BroadcastExchange +Input [2]: [d_date_sk#34, d_year#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +Subquery:3 Hosting operator id = 38 Hosting Expression = ws_sold_date_sk#52 IN dynamicpruning#13 + +Subquery:4 Hosting operator id = 57 Hosting Expression = ws_sold_date_sk#72 IN dynamicpruning#33 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt new file mode 100644 index 000000000..55c995970 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt @@ -0,0 +1,123 @@ +TakeOrderedAndProject [customer_preferred_cust_flag] + WholeStageCodegen (16) + Project [customer_preferred_cust_flag] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,year_total,customer_preferred_cust_flag,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + Project [customer_id,year_total,customer_preferred_cust_flag,year_total] + BroadcastHashJoin [customer_id,customer_id] + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,sum] [sum(UnscaledValue((ss_ext_list_price - ss_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] #1 + WholeStageCodegen (3) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_list_price,ss_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,sum] [sum(UnscaledValue((ss_ext_list_price - ss_ext_discount_amt))),customer_id,customer_preferred_cust_flag,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] #5 + WholeStageCodegen (6) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_list_price,ss_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum] [sum(UnscaledValue((ws_ext_list_price - ws_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #9 + WholeStageCodegen (10) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum] [sum(UnscaledValue((ws_ext_list_price - ws_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #12 + WholeStageCodegen (14) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (12) + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt new file mode 100644 index 000000000..49faad274 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt @@ -0,0 +1,150 @@ +== Physical Plan == +TakeOrderedAndProject (20) ++- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.web_sales (1) + : +- BroadcastExchange (7) + : +- * Filter (6) + : +- * ColumnarToRow (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] + +(3) Filter [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(6) Filter [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 25] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [ws_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [ws_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#2))#14] +Results [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#2))#14,17,2) AS _w0#16, i_item_id#6] + +(16) Exchange +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18, i_item_id#6] +Input [8]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6, _we0#17] + +(20) TakeOrderedAndProject +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18, i_item_id#6] +Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (25) ++- * Project (24) + +- * Filter (23) + +- * ColumnarToRow (22) + +- CometScan parquet spark_catalog.default.date_dim (21) + + +(21) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(22) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] + +(23) Filter [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(24) Project [codegen id : 1] +Output [1]: [d_date_sk#11] +Input [2]: [d_date_sk#11, d_date#19] + +(25) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt new file mode 100644 index 000000000..59f27988d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt @@ -0,0 +1,40 @@ +TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_current_price,itemrevenue] + WholeStageCodegen (6) + Project [i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0,i_item_id] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(ws_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #2 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_ext_sales_price,ws_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [i_category,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt new file mode 100644 index 000000000..238d32e1b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt @@ -0,0 +1,232 @@ +== Physical Plan == +* HashAggregate (34) ++- Exchange (33) + +- * HashAggregate (32) + +- * Project (31) + +- * BroadcastHashJoin Inner BuildRight (30) + :- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (19) + : : +- * BroadcastHashJoin Inner BuildRight (18) + : : :- * Project (16) + : : : +- * BroadcastHashJoin Inner BuildRight (15) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store (4) + : : : +- BroadcastExchange (14) + : : : +- * Project (13) + : : : +- * Filter (12) + : : : +- * ColumnarToRow (11) + : : : +- CometScan parquet spark_catalog.default.customer_address (10) + : : +- ReusedExchange (17) + : +- BroadcastExchange (23) + : +- * Filter (22) + : +- * ColumnarToRow (21) + : +- CometScan parquet spark_catalog.default.customer_demographics (20) + +- BroadcastExchange (29) + +- * Filter (28) + +- * ColumnarToRow (27) + +- CometScan parquet spark_catalog.default.household_demographics (26) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#10), dynamicpruningexpression(ss_sold_date_sk#10 IN dynamicpruning#11)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_hdemo_sk), Or(Or(And(GreaterThanOrEqual(ss_net_profit,100.00),LessThanOrEqual(ss_net_profit,200.00)),And(GreaterThanOrEqual(ss_net_profit,150.00),LessThanOrEqual(ss_net_profit,300.00))),And(GreaterThanOrEqual(ss_net_profit,50.00),LessThanOrEqual(ss_net_profit,250.00))), Or(Or(And(GreaterThanOrEqual(ss_sales_price,100.00),LessThanOrEqual(ss_sales_price,150.00)),And(GreaterThanOrEqual(ss_sales_price,50.00),LessThanOrEqual(ss_sales_price,100.00))),And(GreaterThanOrEqual(ss_sales_price,150.00),LessThanOrEqual(ss_sales_price,200.00)))] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 6] +Input [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10] + +(3) Filter [codegen id : 6] +Input [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10] +Condition : (((((isnotnull(ss_store_sk#4) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_cdemo_sk#1)) AND isnotnull(ss_hdemo_sk#2)) AND ((((ss_net_profit#9 >= 100.00) AND (ss_net_profit#9 <= 200.00)) OR ((ss_net_profit#9 >= 150.00) AND (ss_net_profit#9 <= 300.00))) OR ((ss_net_profit#9 >= 50.00) AND (ss_net_profit#9 <= 250.00)))) AND ((((ss_sales_price#6 >= 100.00) AND (ss_sales_price#6 <= 150.00)) OR ((ss_sales_price#6 >= 50.00) AND (ss_sales_price#6 <= 100.00))) OR ((ss_sales_price#6 >= 150.00) AND (ss_sales_price#6 <= 200.00)))) + +(4) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [1]: [s_store_sk#12] + +(6) Filter [codegen id : 1] +Input [1]: [s_store_sk#12] +Condition : isnotnull(s_store_sk#12) + +(7) BroadcastExchange +Input [1]: [s_store_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [s_store_sk#12] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 6] +Output [9]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10] +Input [11]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10, s_store_sk#12] + +(10) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [OH,TX]),In(ca_state, [KY,NM,OR])),In(ca_state, [MS,TX,VA]))] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] + +(12) Filter [codegen id : 2] +Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Condition : (((isnotnull(ca_country#15) AND (ca_country#15 = United States)) AND isnotnull(ca_address_sk#13)) AND ((ca_state#14 IN (TX,OH) OR ca_state#14 IN (OR,NM,KY)) OR ca_state#14 IN (VA,TX,MS))) + +(13) Project [codegen id : 2] +Output [2]: [ca_address_sk#13, ca_state#14] +Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] + +(14) BroadcastExchange +Input [2]: [ca_address_sk#13, ca_state#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_addr_sk#3] +Right keys [1]: [ca_address_sk#13] +Join type: Inner +Join condition: ((((ca_state#14 IN (TX,OH) AND (ss_net_profit#9 >= 100.00)) AND (ss_net_profit#9 <= 200.00)) OR ((ca_state#14 IN (OR,NM,KY) AND (ss_net_profit#9 >= 150.00)) AND (ss_net_profit#9 <= 300.00))) OR ((ca_state#14 IN (VA,TX,MS) AND (ss_net_profit#9 >= 50.00)) AND (ss_net_profit#9 <= 250.00))) + +(16) Project [codegen id : 6] +Output [7]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_sold_date_sk#10] +Input [11]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10, ca_address_sk#13, ca_state#14] + +(17) ReusedExchange [Reuses operator id: 39] +Output [1]: [d_date_sk#16] + +(18) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#10] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 6] +Output [6]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8] +Input [8]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_sold_date_sk#10, d_date_sk#16] + +(20) Scan parquet spark_catalog.default.customer_demographics +Output [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,Advanced Degree )),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College ))),And(EqualTo(cd_marital_status,W),EqualTo(cd_education_status,2 yr Degree )))] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] + +(22) Filter [codegen id : 4] +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Condition : (isnotnull(cd_demo_sk#17) AND ((((cd_marital_status#18 = M) AND (cd_education_status#19 = Advanced Degree )) OR ((cd_marital_status#18 = S) AND (cd_education_status#19 = College ))) OR ((cd_marital_status#18 = W) AND (cd_education_status#19 = 2 yr Degree )))) + +(23) BroadcastExchange +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_cdemo_sk#1] +Right keys [1]: [cd_demo_sk#17] +Join type: Inner +Join condition: ((((((cd_marital_status#18 = M) AND (cd_education_status#19 = Advanced Degree )) AND (ss_sales_price#6 >= 100.00)) AND (ss_sales_price#6 <= 150.00)) OR ((((cd_marital_status#18 = S) AND (cd_education_status#19 = College )) AND (ss_sales_price#6 >= 50.00)) AND (ss_sales_price#6 <= 100.00))) OR ((((cd_marital_status#18 = W) AND (cd_education_status#19 = 2 yr Degree )) AND (ss_sales_price#6 >= 150.00)) AND (ss_sales_price#6 <= 200.00))) + +(25) Project [codegen id : 6] +Output [7]: [ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, cd_marital_status#18, cd_education_status#19] +Input [9]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] + +(26) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#20, hd_dep_count#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_demo_sk), Or(EqualTo(hd_dep_count,3),EqualTo(hd_dep_count,1))] +ReadSchema: struct + +(27) ColumnarToRow [codegen id : 5] +Input [2]: [hd_demo_sk#20, hd_dep_count#21] + +(28) Filter [codegen id : 5] +Input [2]: [hd_demo_sk#20, hd_dep_count#21] +Condition : (isnotnull(hd_demo_sk#20) AND ((hd_dep_count#21 = 3) OR (hd_dep_count#21 = 1))) + +(29) BroadcastExchange +Input [2]: [hd_demo_sk#20, hd_dep_count#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#20] +Join type: Inner +Join condition: (((((((cd_marital_status#18 = M) AND (cd_education_status#19 = Advanced Degree )) AND (ss_sales_price#6 >= 100.00)) AND (ss_sales_price#6 <= 150.00)) AND (hd_dep_count#21 = 3)) OR (((((cd_marital_status#18 = S) AND (cd_education_status#19 = College )) AND (ss_sales_price#6 >= 50.00)) AND (ss_sales_price#6 <= 100.00)) AND (hd_dep_count#21 = 1))) OR (((((cd_marital_status#18 = W) AND (cd_education_status#19 = 2 yr Degree )) AND (ss_sales_price#6 >= 150.00)) AND (ss_sales_price#6 <= 200.00)) AND (hd_dep_count#21 = 1))) + +(31) Project [codegen id : 6] +Output [3]: [ss_quantity#5, ss_ext_sales_price#7, ss_ext_wholesale_cost#8] +Input [9]: [ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, cd_marital_status#18, cd_education_status#19, hd_demo_sk#20, hd_dep_count#21] + +(32) HashAggregate [codegen id : 6] +Input [3]: [ss_quantity#5, ss_ext_sales_price#7, ss_ext_wholesale_cost#8] +Keys: [] +Functions [4]: [partial_avg(ss_quantity#5), partial_avg(UnscaledValue(ss_ext_sales_price#7)), partial_avg(UnscaledValue(ss_ext_wholesale_cost#8)), partial_sum(UnscaledValue(ss_ext_wholesale_cost#8))] +Aggregate Attributes [7]: [sum#22, count#23, sum#24, count#25, sum#26, count#27, sum#28] +Results [7]: [sum#29, count#30, sum#31, count#32, sum#33, count#34, sum#35] + +(33) Exchange +Input [7]: [sum#29, count#30, sum#31, count#32, sum#33, count#34, sum#35] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=5] + +(34) HashAggregate [codegen id : 7] +Input [7]: [sum#29, count#30, sum#31, count#32, sum#33, count#34, sum#35] +Keys: [] +Functions [4]: [avg(ss_quantity#5), avg(UnscaledValue(ss_ext_sales_price#7)), avg(UnscaledValue(ss_ext_wholesale_cost#8)), sum(UnscaledValue(ss_ext_wholesale_cost#8))] +Aggregate Attributes [4]: [avg(ss_quantity#5)#36, avg(UnscaledValue(ss_ext_sales_price#7))#37, avg(UnscaledValue(ss_ext_wholesale_cost#8))#38, sum(UnscaledValue(ss_ext_wholesale_cost#8))#39] +Results [4]: [avg(ss_quantity#5)#36 AS avg(ss_quantity)#40, cast((avg(UnscaledValue(ss_ext_sales_price#7))#37 / 100.0) as decimal(11,6)) AS avg(ss_ext_sales_price)#41, cast((avg(UnscaledValue(ss_ext_wholesale_cost#8))#38 / 100.0) as decimal(11,6)) AS avg(ss_ext_wholesale_cost)#42, MakeDecimal(sum(UnscaledValue(ss_ext_wholesale_cost#8))#39,17,2) AS sum(ss_ext_wholesale_cost)#43] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#10 IN dynamicpruning#11 +BroadcastExchange (39) ++- * Project (38) + +- * Filter (37) + +- * ColumnarToRow (36) + +- CometScan parquet spark_catalog.default.date_dim (35) + + +(35) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#16, d_year#44] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(36) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#16, d_year#44] + +(37) Filter [codegen id : 1] +Input [2]: [d_date_sk#16, d_year#44] +Condition : ((isnotnull(d_year#44) AND (d_year#44 = 2001)) AND isnotnull(d_date_sk#16)) + +(38) Project [codegen id : 1] +Output [1]: [d_date_sk#16] +Input [2]: [d_date_sk#16, d_year#44] + +(39) BroadcastExchange +Input [1]: [d_date_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt new file mode 100644 index 000000000..5e9dda7b9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt @@ -0,0 +1,59 @@ +WholeStageCodegen (7) + HashAggregate [sum,count,sum,count,sum,count,sum] [avg(ss_quantity),avg(UnscaledValue(ss_ext_sales_price)),avg(UnscaledValue(ss_ext_wholesale_cost)),sum(UnscaledValue(ss_ext_wholesale_cost)),avg(ss_quantity),avg(ss_ext_sales_price),avg(ss_ext_wholesale_cost),sum(ss_ext_wholesale_cost),sum,count,sum,count,sum,count,sum] + InputAdapter + Exchange #1 + WholeStageCodegen (6) + HashAggregate [ss_quantity,ss_ext_sales_price,ss_ext_wholesale_cost] [sum,count,sum,count,sum,count,sum,sum,count,sum,count,sum,count,sum] + Project [ss_quantity,ss_ext_sales_price,ss_ext_wholesale_cost] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk,cd_marital_status,cd_education_status,ss_sales_price,hd_dep_count] + Project [ss_hdemo_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost,cd_marital_status,cd_education_status] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk,cd_marital_status,cd_education_status,ss_sales_price] + Project [ss_cdemo_sk,ss_hdemo_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_cdemo_sk,ss_hdemo_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost,ss_sold_date_sk] + BroadcastHashJoin [ss_addr_sk,ca_address_sk,ca_state,ss_net_profit] + Project [ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost,ss_net_profit,ss_sold_date_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Filter [ss_store_sk,ss_addr_sk,ss_cdemo_sk,ss_hdemo_sk,ss_net_profit,ss_sales_price] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [ca_address_sk,ca_state] + Filter [ca_country,ca_address_sk,ca_state] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Filter [cd_demo_sk,cd_marital_status,cd_education_status] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Filter [hd_demo_sk,hd_dep_count] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt new file mode 100644 index 000000000..fc94f648f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt @@ -0,0 +1,800 @@ +== Physical Plan == +TakeOrderedAndProject (105) ++- * HashAggregate (104) + +- Exchange (103) + +- * HashAggregate (102) + +- * Expand (101) + +- Union (100) + :- * Project (67) + : +- * Filter (66) + : +- * HashAggregate (65) + : +- Exchange (64) + : +- * HashAggregate (63) + : +- * Project (62) + : +- * BroadcastHashJoin Inner BuildRight (61) + : :- * Project (59) + : : +- * BroadcastHashJoin Inner BuildRight (58) + : : :- * BroadcastHashJoin LeftSemi BuildRight (51) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (50) + : : : +- * Project (49) + : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : :- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : +- BroadcastExchange (47) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) + : : : :- * HashAggregate (35) + : : : : +- Exchange (34) + : : : : +- * HashAggregate (33) + : : : : +- * Project (32) + : : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : : :- * Project (29) + : : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : : :- * Filter (9) + : : : : : : +- * ColumnarToRow (8) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) + : : : : : +- BroadcastExchange (27) + : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) + : : : : : :- * Filter (12) + : : : : : : +- * ColumnarToRow (11) + : : : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : : : +- BroadcastExchange (25) + : : : : : +- * Project (24) + : : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : : :- * Project (21) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : :- * Filter (15) + : : : : : : : +- * ColumnarToRow (14) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) + : : : : : : +- BroadcastExchange (19) + : : : : : : +- * Filter (18) + : : : : : : +- * ColumnarToRow (17) + : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : +- ReusedExchange (22) + : : : : +- ReusedExchange (30) + : : : +- BroadcastExchange (45) + : : : +- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * Project (41) + : : : : +- * BroadcastHashJoin Inner BuildRight (40) + : : : : :- * Filter (38) + : : : : : +- * ColumnarToRow (37) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) + : : : : +- ReusedExchange (39) + : : : +- ReusedExchange (42) + : : +- BroadcastExchange (57) + : : +- * BroadcastHashJoin LeftSemi BuildRight (56) + : : :- * Filter (54) + : : : +- * ColumnarToRow (53) + : : : +- CometScan parquet spark_catalog.default.item (52) + : : +- ReusedExchange (55) + : +- ReusedExchange (60) + :- * Project (83) + : +- * Filter (82) + : +- * HashAggregate (81) + : +- Exchange (80) + : +- * HashAggregate (79) + : +- * Project (78) + : +- * BroadcastHashJoin Inner BuildRight (77) + : :- * Project (75) + : : +- * BroadcastHashJoin Inner BuildRight (74) + : : :- * BroadcastHashJoin LeftSemi BuildRight (72) + : : : :- * Filter (70) + : : : : +- * ColumnarToRow (69) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (68) + : : : +- ReusedExchange (71) + : : +- ReusedExchange (73) + : +- ReusedExchange (76) + +- * Project (99) + +- * Filter (98) + +- * HashAggregate (97) + +- Exchange (96) + +- * HashAggregate (95) + +- * Project (94) + +- * BroadcastHashJoin Inner BuildRight (93) + :- * Project (91) + : +- * BroadcastHashJoin Inner BuildRight (90) + : :- * BroadcastHashJoin LeftSemi BuildRight (88) + : : :- * Filter (86) + : : : +- * ColumnarToRow (85) + : : : +- CometScan parquet spark_catalog.default.web_sales (84) + : : +- ReusedExchange (87) + : +- ReusedExchange (89) + +- ReusedExchange (92) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] + +(6) Filter [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) + +(7) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] + +(9) Filter [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) + +(10) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(12) Filter [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) + +(13) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] + +(15) Filter [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) + +(16) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(18) Filter [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) + +(19) BroadcastExchange +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(20) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#17] +Right keys [1]: [i_item_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 3] +Output [4]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23] +Input [6]: [cs_item_sk#17, cs_sold_date_sk#18, i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(22) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#24] + +(23) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#18] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 3] +Output [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Input [5]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23, d_date_sk#24] + +(25) BroadcastExchange +Input [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=2] + +(26) BroadcastHashJoin [codegen id : 4] +Left keys [6]: [coalesce(i_brand_id#14, 0), isnull(i_brand_id#14), coalesce(i_class_id#15, 0), isnull(i_class_id#15), coalesce(i_category_id#16, 0), isnull(i_category_id#16)] +Right keys [6]: [coalesce(i_brand_id#21, 0), isnull(i_brand_id#21), coalesce(i_class_id#22, 0), isnull(i_class_id#22), coalesce(i_category_id#23, 0), isnull(i_category_id#23)] +Join type: LeftSemi +Join condition: None + +(27) BroadcastExchange +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_item_sk#10] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [4]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16] +Input [6]: [ss_item_sk#10, ss_sold_date_sk#11, i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(30) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 6] +Output [3]: [i_brand_id#14 AS brand_id#26, i_class_id#15 AS class_id#27, i_category_id#16 AS category_id#28] +Input [5]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16, d_date_sk#25] + +(33) HashAggregate [codegen id : 6] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(34) Exchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: hashpartitioning(brand_id#26, class_id#27, category_id#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(35) HashAggregate [codegen id : 10] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(36) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_sold_date_sk#30 IN dynamicpruning#31)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(37) ColumnarToRow [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] + +(38) Filter [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) + +(39) ReusedExchange [Reuses operator id: 19] +Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(40) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_item_sk#29] +Right keys [1]: [i_item_sk#32] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 9] +Output [4]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35] +Input [6]: [ws_item_sk#29, ws_sold_date_sk#30, i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(42) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#36] + +(43) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_sold_date_sk#30] +Right keys [1]: [d_date_sk#36] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 9] +Output [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Input [5]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35, d_date_sk#36] + +(45) BroadcastExchange +Input [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=5] + +(46) BroadcastHashJoin [codegen id : 10] +Left keys [6]: [coalesce(brand_id#26, 0), isnull(brand_id#26), coalesce(class_id#27, 0), isnull(class_id#27), coalesce(category_id#28, 0), isnull(category_id#28)] +Right keys [6]: [coalesce(i_brand_id#33, 0), isnull(i_brand_id#33), coalesce(i_class_id#34, 0), isnull(i_class_id#34), coalesce(i_category_id#35, 0), isnull(i_category_id#35)] +Join type: LeftSemi +Join condition: None + +(47) BroadcastExchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: HashedRelationBroadcastMode(List(input[0, int, true], input[1, int, true], input[2, int, true]),false), [plan_id=6] + +(48) BroadcastHashJoin [codegen id : 11] +Left keys [3]: [i_brand_id#7, i_class_id#8, i_category_id#9] +Right keys [3]: [brand_id#26, class_id#27, category_id#28] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 11] +Output [1]: [i_item_sk#6 AS ss_item_sk#37] +Input [7]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9, brand_id#26, class_id#27, category_id#28] + +(50) BroadcastExchange +Input [1]: [ss_item_sk#37] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(51) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(52) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(53) ColumnarToRow [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(54) Filter [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : isnotnull(i_item_sk#38) + +(55) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#37] + +(56) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [i_item_sk#38] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(57) BroadcastExchange +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(58) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#38] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 25] +Output [6]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [8]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(60) ReusedExchange [Reuses operator id: 129] +Output [1]: [d_date_sk#42] + +(61) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#42] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 25] +Output [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [7]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41, d_date_sk#42] + +(63) HashAggregate [codegen id : 25] +Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [partial_sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), partial_count(1)] +Aggregate Attributes [3]: [sum#43, isEmpty#44, count#45] +Results [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] + +(64) Exchange +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Arguments: hashpartitioning(i_brand_id#39, i_class_id#40, i_category_id#41, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 26] +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49, count(1)#50] +Results [5]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49 AS sales#51, count(1)#50 AS number_sales#52] + +(66) Filter [codegen id : 26] +Input [5]: [i_brand_id#39, i_class_id#40, i_category_id#41, sales#51, number_sales#52] +Condition : (isnotnull(sales#51) AND (cast(sales#51 as decimal(32,6)) > cast(Subquery scalar-subquery#53, [id=#54] as decimal(32,6)))) + +(67) Project [codegen id : 26] +Output [6]: [sales#51, number_sales#52, store AS channel#55, i_brand_id#39 AS i_brand_id#56, i_class_id#40 AS i_class_id#57, i_category_id#41 AS i_category_id#58] +Input [5]: [i_brand_id#39, i_class_id#40, i_category_id#41, sales#51, number_sales#52] + +(68) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#62), dynamicpruningexpression(cs_sold_date_sk#62 IN dynamicpruning#63)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(69) ColumnarToRow [codegen id : 51] +Input [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62] + +(70) Filter [codegen id : 51] +Input [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62] +Condition : isnotnull(cs_item_sk#59) + +(71) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#64] + +(72) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_item_sk#59] +Right keys [1]: [ss_item_sk#64] +Join type: LeftSemi +Join condition: None + +(73) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#65, i_brand_id#66, i_class_id#67, i_category_id#68] + +(74) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_item_sk#59] +Right keys [1]: [i_item_sk#65] +Join type: Inner +Join condition: None + +(75) Project [codegen id : 51] +Output [6]: [cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_brand_id#66, i_class_id#67, i_category_id#68] +Input [8]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_item_sk#65, i_brand_id#66, i_class_id#67, i_category_id#68] + +(76) ReusedExchange [Reuses operator id: 129] +Output [1]: [d_date_sk#69] + +(77) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_sold_date_sk#62] +Right keys [1]: [d_date_sk#69] +Join type: Inner +Join condition: None + +(78) Project [codegen id : 51] +Output [5]: [cs_quantity#60, cs_list_price#61, i_brand_id#66, i_class_id#67, i_category_id#68] +Input [7]: [cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_brand_id#66, i_class_id#67, i_category_id#68, d_date_sk#69] + +(79) HashAggregate [codegen id : 51] +Input [5]: [cs_quantity#60, cs_list_price#61, i_brand_id#66, i_class_id#67, i_category_id#68] +Keys [3]: [i_brand_id#66, i_class_id#67, i_category_id#68] +Functions [2]: [partial_sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61)), partial_count(1)] +Aggregate Attributes [3]: [sum#70, isEmpty#71, count#72] +Results [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75] + +(80) Exchange +Input [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75] +Arguments: hashpartitioning(i_brand_id#66, i_class_id#67, i_category_id#68, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(81) HashAggregate [codegen id : 52] +Input [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75] +Keys [3]: [i_brand_id#66, i_class_id#67, i_category_id#68] +Functions [2]: [sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61)), count(1)] +Aggregate Attributes [2]: [sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61))#76, count(1)#77] +Results [5]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61))#76 AS sales#78, count(1)#77 AS number_sales#79] + +(82) Filter [codegen id : 52] +Input [5]: [i_brand_id#66, i_class_id#67, i_category_id#68, sales#78, number_sales#79] +Condition : (isnotnull(sales#78) AND (cast(sales#78 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#53, [id=#54] as decimal(32,6)))) + +(83) Project [codegen id : 52] +Output [6]: [sales#78, number_sales#79, catalog AS channel#80, i_brand_id#66, i_class_id#67, i_category_id#68] +Input [5]: [i_brand_id#66, i_class_id#67, i_category_id#68, sales#78, number_sales#79] + +(84) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#84), dynamicpruningexpression(ws_sold_date_sk#84 IN dynamicpruning#85)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(85) ColumnarToRow [codegen id : 77] +Input [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84] + +(86) Filter [codegen id : 77] +Input [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84] +Condition : isnotnull(ws_item_sk#81) + +(87) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#86] + +(88) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_item_sk#81] +Right keys [1]: [ss_item_sk#86] +Join type: LeftSemi +Join condition: None + +(89) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#87, i_brand_id#88, i_class_id#89, i_category_id#90] + +(90) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_item_sk#81] +Right keys [1]: [i_item_sk#87] +Join type: Inner +Join condition: None + +(91) Project [codegen id : 77] +Output [6]: [ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_brand_id#88, i_class_id#89, i_category_id#90] +Input [8]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_item_sk#87, i_brand_id#88, i_class_id#89, i_category_id#90] + +(92) ReusedExchange [Reuses operator id: 129] +Output [1]: [d_date_sk#91] + +(93) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_sold_date_sk#84] +Right keys [1]: [d_date_sk#91] +Join type: Inner +Join condition: None + +(94) Project [codegen id : 77] +Output [5]: [ws_quantity#82, ws_list_price#83, i_brand_id#88, i_class_id#89, i_category_id#90] +Input [7]: [ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_brand_id#88, i_class_id#89, i_category_id#90, d_date_sk#91] + +(95) HashAggregate [codegen id : 77] +Input [5]: [ws_quantity#82, ws_list_price#83, i_brand_id#88, i_class_id#89, i_category_id#90] +Keys [3]: [i_brand_id#88, i_class_id#89, i_category_id#90] +Functions [2]: [partial_sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83)), partial_count(1)] +Aggregate Attributes [3]: [sum#92, isEmpty#93, count#94] +Results [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97] + +(96) Exchange +Input [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97] +Arguments: hashpartitioning(i_brand_id#88, i_class_id#89, i_category_id#90, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(97) HashAggregate [codegen id : 78] +Input [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97] +Keys [3]: [i_brand_id#88, i_class_id#89, i_category_id#90] +Functions [2]: [sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83)), count(1)] +Aggregate Attributes [2]: [sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83))#98, count(1)#99] +Results [5]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83))#98 AS sales#100, count(1)#99 AS number_sales#101] + +(98) Filter [codegen id : 78] +Input [5]: [i_brand_id#88, i_class_id#89, i_category_id#90, sales#100, number_sales#101] +Condition : (isnotnull(sales#100) AND (cast(sales#100 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#53, [id=#54] as decimal(32,6)))) + +(99) Project [codegen id : 78] +Output [6]: [sales#100, number_sales#101, web AS channel#102, i_brand_id#88, i_class_id#89, i_category_id#90] +Input [5]: [i_brand_id#88, i_class_id#89, i_category_id#90, sales#100, number_sales#101] + +(100) Union + +(101) Expand [codegen id : 79] +Input [6]: [sales#51, number_sales#52, channel#55, i_brand_id#56, i_class_id#57, i_category_id#58] +Arguments: [[sales#51, number_sales#52, channel#55, i_brand_id#56, i_class_id#57, i_category_id#58, 0], [sales#51, number_sales#52, channel#55, i_brand_id#56, i_class_id#57, null, 1], [sales#51, number_sales#52, channel#55, i_brand_id#56, null, null, 3], [sales#51, number_sales#52, channel#55, null, null, null, 7], [sales#51, number_sales#52, null, null, null, null, 15]], [sales#51, number_sales#52, channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107] + +(102) HashAggregate [codegen id : 79] +Input [7]: [sales#51, number_sales#52, channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107] +Keys [5]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107] +Functions [2]: [partial_sum(sales#51), partial_sum(number_sales#52)] +Aggregate Attributes [3]: [sum#108, isEmpty#109, sum#110] +Results [8]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107, sum#111, isEmpty#112, sum#113] + +(103) Exchange +Input [8]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107, sum#111, isEmpty#112, sum#113] +Arguments: hashpartitioning(channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(104) HashAggregate [codegen id : 80] +Input [8]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107, sum#111, isEmpty#112, sum#113] +Keys [5]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, spark_grouping_id#107] +Functions [2]: [sum(sales#51), sum(number_sales#52)] +Aggregate Attributes [2]: [sum(sales#51)#114, sum(number_sales#52)#115] +Results [6]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, sum(sales#51)#114 AS sum(sales)#116, sum(number_sales#52)#115 AS sum(number_sales)#117] + +(105) TakeOrderedAndProject +Input [6]: [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, sum(sales)#116, sum(number_sales)#117] +Arguments: 100, [channel#103 ASC NULLS FIRST, i_brand_id#104 ASC NULLS FIRST, i_class_id#105 ASC NULLS FIRST, i_category_id#106 ASC NULLS FIRST], [channel#103, i_brand_id#104, i_class_id#105, i_category_id#106, sum(sales)#116, sum(number_sales)#117] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 66 Hosting Expression = Subquery scalar-subquery#53, [id=#54] +* HashAggregate (124) ++- Exchange (123) + +- * HashAggregate (122) + +- Union (121) + :- * Project (110) + : +- * BroadcastHashJoin Inner BuildRight (109) + : :- * ColumnarToRow (107) + : : +- CometScan parquet spark_catalog.default.store_sales (106) + : +- ReusedExchange (108) + :- * Project (115) + : +- * BroadcastHashJoin Inner BuildRight (114) + : :- * ColumnarToRow (112) + : : +- CometScan parquet spark_catalog.default.catalog_sales (111) + : +- ReusedExchange (113) + +- * Project (120) + +- * BroadcastHashJoin Inner BuildRight (119) + :- * ColumnarToRow (117) + : +- CometScan parquet spark_catalog.default.web_sales (116) + +- ReusedExchange (118) + + +(106) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_quantity#118, ss_list_price#119, ss_sold_date_sk#120] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#120), dynamicpruningexpression(ss_sold_date_sk#120 IN dynamicpruning#121)] +ReadSchema: struct + +(107) ColumnarToRow [codegen id : 2] +Input [3]: [ss_quantity#118, ss_list_price#119, ss_sold_date_sk#120] + +(108) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#122] + +(109) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#120] +Right keys [1]: [d_date_sk#122] +Join type: Inner +Join condition: None + +(110) Project [codegen id : 2] +Output [2]: [ss_quantity#118 AS quantity#123, ss_list_price#119 AS list_price#124] +Input [4]: [ss_quantity#118, ss_list_price#119, ss_sold_date_sk#120, d_date_sk#122] + +(111) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_quantity#125, cs_list_price#126, cs_sold_date_sk#127] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#127), dynamicpruningexpression(cs_sold_date_sk#127 IN dynamicpruning#128)] +ReadSchema: struct + +(112) ColumnarToRow [codegen id : 4] +Input [3]: [cs_quantity#125, cs_list_price#126, cs_sold_date_sk#127] + +(113) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#129] + +(114) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#127] +Right keys [1]: [d_date_sk#129] +Join type: Inner +Join condition: None + +(115) Project [codegen id : 4] +Output [2]: [cs_quantity#125 AS quantity#130, cs_list_price#126 AS list_price#131] +Input [4]: [cs_quantity#125, cs_list_price#126, cs_sold_date_sk#127, d_date_sk#129] + +(116) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_quantity#132, ws_list_price#133, ws_sold_date_sk#134] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#134), dynamicpruningexpression(ws_sold_date_sk#134 IN dynamicpruning#135)] +ReadSchema: struct + +(117) ColumnarToRow [codegen id : 6] +Input [3]: [ws_quantity#132, ws_list_price#133, ws_sold_date_sk#134] + +(118) ReusedExchange [Reuses operator id: 134] +Output [1]: [d_date_sk#136] + +(119) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#134] +Right keys [1]: [d_date_sk#136] +Join type: Inner +Join condition: None + +(120) Project [codegen id : 6] +Output [2]: [ws_quantity#132 AS quantity#137, ws_list_price#133 AS list_price#138] +Input [4]: [ws_quantity#132, ws_list_price#133, ws_sold_date_sk#134, d_date_sk#136] + +(121) Union + +(122) HashAggregate [codegen id : 7] +Input [2]: [quantity#123, list_price#124] +Keys: [] +Functions [1]: [partial_avg((cast(quantity#123 as decimal(10,0)) * list_price#124))] +Aggregate Attributes [2]: [sum#139, count#140] +Results [2]: [sum#141, count#142] + +(123) Exchange +Input [2]: [sum#141, count#142] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=13] + +(124) HashAggregate [codegen id : 8] +Input [2]: [sum#141, count#142] +Keys: [] +Functions [1]: [avg((cast(quantity#123 as decimal(10,0)) * list_price#124))] +Aggregate Attributes [1]: [avg((cast(quantity#123 as decimal(10,0)) * list_price#124))#143] +Results [1]: [avg((cast(quantity#123 as decimal(10,0)) * list_price#124))#143 AS average_sales#144] + +Subquery:2 Hosting operator id = 106 Hosting Expression = ss_sold_date_sk#120 IN dynamicpruning#12 + +Subquery:3 Hosting operator id = 111 Hosting Expression = cs_sold_date_sk#127 IN dynamicpruning#12 + +Subquery:4 Hosting operator id = 116 Hosting Expression = ws_sold_date_sk#134 IN dynamicpruning#12 + +Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (129) ++- * Project (128) + +- * Filter (127) + +- * ColumnarToRow (126) + +- CometScan parquet spark_catalog.default.date_dim (125) + + +(125) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#42, d_year#145, d_moy#146] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,11), IsNotNull(d_date_sk)] +ReadSchema: struct + +(126) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#42, d_year#145, d_moy#146] + +(127) Filter [codegen id : 1] +Input [3]: [d_date_sk#42, d_year#145, d_moy#146] +Condition : ((((isnotnull(d_year#145) AND isnotnull(d_moy#146)) AND (d_year#145 = 2001)) AND (d_moy#146 = 11)) AND isnotnull(d_date_sk#42)) + +(128) Project [codegen id : 1] +Output [1]: [d_date_sk#42] +Input [3]: [d_date_sk#42, d_year#145, d_moy#146] + +(129) BroadcastExchange +Input [1]: [d_date_sk#42] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] + +Subquery:6 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 +BroadcastExchange (134) ++- * Project (133) + +- * Filter (132) + +- * ColumnarToRow (131) + +- CometScan parquet spark_catalog.default.date_dim (130) + + +(130) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#147] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(131) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#147] + +(132) Filter [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#147] +Condition : (((isnotnull(d_year#147) AND (d_year#147 >= 1999)) AND (d_year#147 <= 2001)) AND isnotnull(d_date_sk#25)) + +(133) Project [codegen id : 1] +Output [1]: [d_date_sk#25] +Input [2]: [d_date_sk#25, d_year#147] + +(134) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15] + +Subquery:7 Hosting operator id = 13 Hosting Expression = cs_sold_date_sk#18 IN dynamicpruning#12 + +Subquery:8 Hosting operator id = 36 Hosting Expression = ws_sold_date_sk#30 IN dynamicpruning#12 + +Subquery:9 Hosting operator id = 82 Hosting Expression = ReusedSubquery Subquery scalar-subquery#53, [id=#54] + +Subquery:10 Hosting operator id = 68 Hosting Expression = cs_sold_date_sk#62 IN dynamicpruning#5 + +Subquery:11 Hosting operator id = 98 Hosting Expression = ReusedSubquery Subquery scalar-subquery#53, [id=#54] + +Subquery:12 Hosting operator id = 84 Hosting Expression = ws_sold_date_sk#84 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt new file mode 100644 index 000000000..a76997516 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt @@ -0,0 +1,214 @@ +TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum(sales),sum(number_sales)] + WholeStageCodegen (80) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,spark_grouping_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum(sales),sum(number_sales),sum,isEmpty,sum] + InputAdapter + Exchange [channel,i_brand_id,i_class_id,i_category_id,spark_grouping_id] #1 + WholeStageCodegen (79) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,spark_grouping_id,sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + Expand [sales,number_sales,channel,i_brand_id,i_class_id,i_category_id] + InputAdapter + Union + WholeStageCodegen (26) + Project [sales,number_sales,i_brand_id,i_class_id,i_category_id] + Filter [sales] + Subquery #3 + WholeStageCodegen (8) + HashAggregate [sum,count] [avg((cast(quantity as decimal(10,0)) * list_price)),average_sales,sum,count] + InputAdapter + Exchange #13 + WholeStageCodegen (7) + HashAggregate [quantity,list_price] [sum,count,sum,count] + InputAdapter + Union + WholeStageCodegen (2) + Project [ss_quantity,ss_list_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_list_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #7 + WholeStageCodegen (4) + Project [cs_quantity,cs_list_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_quantity,cs_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #7 + WholeStageCodegen (6) + Project [ws_quantity,ws_list_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #7 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #2 + WholeStageCodegen (25) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (11) + Project [i_item_sk] + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] + Filter [i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (10) + BroadcastHashJoin [brand_id,class_id,category_id,i_brand_id,i_class_id,i_category_id] + HashAggregate [brand_id,class_id,category_id] + InputAdapter + Exchange [brand_id,class_id,category_id] #6 + WholeStageCodegen (6) + HashAggregate [brand_id,class_id,category_id] + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (4) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (3) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (1) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [d_date_sk] #7 + InputAdapter + ReusedExchange [d_date_sk] #7 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (9) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #10 + InputAdapter + ReusedExchange [d_date_sk] #7 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (23) + BroadcastHashJoin [i_item_sk,ss_item_sk] + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [ss_item_sk] #4 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (52) + Project [sales,number_sales,i_brand_id,i_class_id,i_category_id] + Filter [sales] + ReusedSubquery [average_sales] #3 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(cs_quantity as decimal(10,0)) * cs_list_price)),count(1),sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #14 + WholeStageCodegen (51) + HashAggregate [i_brand_id,i_class_id,i_category_id,cs_quantity,cs_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [cs_quantity,cs_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_quantity,cs_list_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + BroadcastHashJoin [cs_item_sk,ss_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [ss_item_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #12 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (78) + Project [sales,number_sales,i_brand_id,i_class_id,i_category_id] + Filter [sales] + ReusedSubquery [average_sales] #3 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ws_quantity as decimal(10,0)) * ws_list_price)),count(1),sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #15 + WholeStageCodegen (77) + HashAggregate [i_brand_id,i_class_id,i_category_id,ws_quantity,ws_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ws_quantity,ws_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_quantity,ws_list_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + BroadcastHashJoin [ws_item_sk,ss_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [ss_item_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #12 + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt new file mode 100644 index 000000000..c6b42f19c --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt @@ -0,0 +1,759 @@ +== Physical Plan == +TakeOrderedAndProject (84) ++- * BroadcastHashJoin Inner BuildRight (83) + :- * Filter (66) + : +- * HashAggregate (65) + : +- Exchange (64) + : +- * HashAggregate (63) + : +- * Project (62) + : +- * BroadcastHashJoin Inner BuildRight (61) + : :- * Project (59) + : : +- * BroadcastHashJoin Inner BuildRight (58) + : : :- * BroadcastHashJoin LeftSemi BuildRight (51) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (50) + : : : +- * Project (49) + : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : :- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : +- BroadcastExchange (47) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) + : : : :- * HashAggregate (35) + : : : : +- Exchange (34) + : : : : +- * HashAggregate (33) + : : : : +- * Project (32) + : : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : : :- * Project (29) + : : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : : :- * Filter (9) + : : : : : : +- * ColumnarToRow (8) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) + : : : : : +- BroadcastExchange (27) + : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) + : : : : : :- * Filter (12) + : : : : : : +- * ColumnarToRow (11) + : : : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : : : +- BroadcastExchange (25) + : : : : : +- * Project (24) + : : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : : :- * Project (21) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : :- * Filter (15) + : : : : : : : +- * ColumnarToRow (14) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) + : : : : : : +- BroadcastExchange (19) + : : : : : : +- * Filter (18) + : : : : : : +- * ColumnarToRow (17) + : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : +- ReusedExchange (22) + : : : : +- ReusedExchange (30) + : : : +- BroadcastExchange (45) + : : : +- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * Project (41) + : : : : +- * BroadcastHashJoin Inner BuildRight (40) + : : : : :- * Filter (38) + : : : : : +- * ColumnarToRow (37) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) + : : : : +- ReusedExchange (39) + : : : +- ReusedExchange (42) + : : +- BroadcastExchange (57) + : : +- * BroadcastHashJoin LeftSemi BuildRight (56) + : : :- * Filter (54) + : : : +- * ColumnarToRow (53) + : : : +- CometScan parquet spark_catalog.default.item (52) + : : +- ReusedExchange (55) + : +- ReusedExchange (60) + +- BroadcastExchange (82) + +- * Filter (81) + +- * HashAggregate (80) + +- Exchange (79) + +- * HashAggregate (78) + +- * Project (77) + +- * BroadcastHashJoin Inner BuildRight (76) + :- * Project (74) + : +- * BroadcastHashJoin Inner BuildRight (73) + : :- * BroadcastHashJoin LeftSemi BuildRight (71) + : : :- * Filter (69) + : : : +- * ColumnarToRow (68) + : : : +- CometScan parquet spark_catalog.default.store_sales (67) + : : +- ReusedExchange (70) + : +- ReusedExchange (72) + +- ReusedExchange (75) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] + +(6) Filter [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) + +(7) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] + +(9) Filter [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) + +(10) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(12) Filter [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) + +(13) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] + +(15) Filter [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) + +(16) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(18) Filter [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) + +(19) BroadcastExchange +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(20) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#17] +Right keys [1]: [i_item_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 3] +Output [4]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23] +Input [6]: [cs_item_sk#17, cs_sold_date_sk#18, i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(22) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#24] + +(23) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#18] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 3] +Output [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Input [5]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23, d_date_sk#24] + +(25) BroadcastExchange +Input [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=2] + +(26) BroadcastHashJoin [codegen id : 4] +Left keys [6]: [coalesce(i_brand_id#14, 0), isnull(i_brand_id#14), coalesce(i_class_id#15, 0), isnull(i_class_id#15), coalesce(i_category_id#16, 0), isnull(i_category_id#16)] +Right keys [6]: [coalesce(i_brand_id#21, 0), isnull(i_brand_id#21), coalesce(i_class_id#22, 0), isnull(i_class_id#22), coalesce(i_category_id#23, 0), isnull(i_category_id#23)] +Join type: LeftSemi +Join condition: None + +(27) BroadcastExchange +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_item_sk#10] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [4]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16] +Input [6]: [ss_item_sk#10, ss_sold_date_sk#11, i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(30) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 6] +Output [3]: [i_brand_id#14 AS brand_id#26, i_class_id#15 AS class_id#27, i_category_id#16 AS category_id#28] +Input [5]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16, d_date_sk#25] + +(33) HashAggregate [codegen id : 6] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(34) Exchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: hashpartitioning(brand_id#26, class_id#27, category_id#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(35) HashAggregate [codegen id : 10] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(36) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_sold_date_sk#30 IN dynamicpruning#31)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(37) ColumnarToRow [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] + +(38) Filter [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) + +(39) ReusedExchange [Reuses operator id: 19] +Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(40) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_item_sk#29] +Right keys [1]: [i_item_sk#32] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 9] +Output [4]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35] +Input [6]: [ws_item_sk#29, ws_sold_date_sk#30, i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(42) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#36] + +(43) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_sold_date_sk#30] +Right keys [1]: [d_date_sk#36] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 9] +Output [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Input [5]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35, d_date_sk#36] + +(45) BroadcastExchange +Input [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=5] + +(46) BroadcastHashJoin [codegen id : 10] +Left keys [6]: [coalesce(brand_id#26, 0), isnull(brand_id#26), coalesce(class_id#27, 0), isnull(class_id#27), coalesce(category_id#28, 0), isnull(category_id#28)] +Right keys [6]: [coalesce(i_brand_id#33, 0), isnull(i_brand_id#33), coalesce(i_class_id#34, 0), isnull(i_class_id#34), coalesce(i_category_id#35, 0), isnull(i_category_id#35)] +Join type: LeftSemi +Join condition: None + +(47) BroadcastExchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: HashedRelationBroadcastMode(List(input[0, int, true], input[1, int, true], input[2, int, true]),false), [plan_id=6] + +(48) BroadcastHashJoin [codegen id : 11] +Left keys [3]: [i_brand_id#7, i_class_id#8, i_category_id#9] +Right keys [3]: [brand_id#26, class_id#27, category_id#28] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 11] +Output [1]: [i_item_sk#6 AS ss_item_sk#37] +Input [7]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9, brand_id#26, class_id#27, category_id#28] + +(50) BroadcastExchange +Input [1]: [ss_item_sk#37] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(51) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(52) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(53) ColumnarToRow [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(54) Filter [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : (((isnotnull(i_item_sk#38) AND isnotnull(i_brand_id#39)) AND isnotnull(i_class_id#40)) AND isnotnull(i_category_id#41)) + +(55) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#37] + +(56) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [i_item_sk#38] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(57) BroadcastExchange +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(58) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#38] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 25] +Output [6]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [8]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(60) ReusedExchange [Reuses operator id: 108] +Output [1]: [d_date_sk#42] + +(61) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#42] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 25] +Output [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [7]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41, d_date_sk#42] + +(63) HashAggregate [codegen id : 25] +Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [partial_sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), partial_count(1)] +Aggregate Attributes [3]: [sum#43, isEmpty#44, count#45] +Results [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] + +(64) Exchange +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Arguments: hashpartitioning(i_brand_id#39, i_class_id#40, i_category_id#41, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 52] +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49, count(1)#50] +Results [6]: [store AS channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49 AS sales#52, count(1)#50 AS number_sales#53] + +(66) Filter [codegen id : 52] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53] +Condition : (isnotnull(sales#52) AND (cast(sales#52 as decimal(32,6)) > cast(Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(67) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#59), dynamicpruningexpression(ss_sold_date_sk#59 IN dynamicpruning#60)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(68) ColumnarToRow [codegen id : 50] +Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] + +(69) Filter [codegen id : 50] +Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] +Condition : isnotnull(ss_item_sk#56) + +(70) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#61] + +(71) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_item_sk#56] +Right keys [1]: [ss_item_sk#61] +Join type: LeftSemi +Join condition: None + +(72) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(73) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_item_sk#56] +Right keys [1]: [i_item_sk#62] +Join type: Inner +Join condition: None + +(74) Project [codegen id : 50] +Output [6]: [ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [8]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(75) ReusedExchange [Reuses operator id: 122] +Output [1]: [d_date_sk#66] + +(76) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_sold_date_sk#59] +Right keys [1]: [d_date_sk#66] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 50] +Output [5]: [ss_quantity#57, ss_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [7]: [ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65, d_date_sk#66] + +(78) HashAggregate [codegen id : 50] +Input [5]: [ss_quantity#57, ss_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [partial_sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58)), partial_count(1)] +Aggregate Attributes [3]: [sum#67, isEmpty#68, count#69] +Results [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] + +(79) Exchange +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Arguments: hashpartitioning(i_brand_id#63, i_class_id#64, i_category_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(80) HashAggregate [codegen id : 51] +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58))#73, count(1)#74] +Results [6]: [store AS channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58))#73 AS sales#76, count(1)#74 AS number_sales#77] + +(81) Filter [codegen id : 51] +Input [6]: [channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Condition : (isnotnull(sales#76) AND (cast(sales#76 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(82) BroadcastExchange +Input [6]: [channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Arguments: HashedRelationBroadcastMode(List(input[1, int, true], input[2, int, true], input[3, int, true]),false), [plan_id=11] + +(83) BroadcastHashJoin [codegen id : 52] +Left keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Right keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Join type: Inner +Join condition: None + +(84) TakeOrderedAndProject +Input [12]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53, channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Arguments: 100, [i_brand_id#39 ASC NULLS FIRST, i_class_id#40 ASC NULLS FIRST, i_category_id#41 ASC NULLS FIRST], [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53, channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 66 Hosting Expression = Subquery scalar-subquery#54, [id=#55] +* HashAggregate (103) ++- Exchange (102) + +- * HashAggregate (101) + +- Union (100) + :- * Project (89) + : +- * BroadcastHashJoin Inner BuildRight (88) + : :- * ColumnarToRow (86) + : : +- CometScan parquet spark_catalog.default.store_sales (85) + : +- ReusedExchange (87) + :- * Project (94) + : +- * BroadcastHashJoin Inner BuildRight (93) + : :- * ColumnarToRow (91) + : : +- CometScan parquet spark_catalog.default.catalog_sales (90) + : +- ReusedExchange (92) + +- * Project (99) + +- * BroadcastHashJoin Inner BuildRight (98) + :- * ColumnarToRow (96) + : +- CometScan parquet spark_catalog.default.web_sales (95) + +- ReusedExchange (97) + + +(85) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#80), dynamicpruningexpression(ss_sold_date_sk#80 IN dynamicpruning#81)] +ReadSchema: struct + +(86) ColumnarToRow [codegen id : 2] +Input [3]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80] + +(87) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#82] + +(88) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#80] +Right keys [1]: [d_date_sk#82] +Join type: Inner +Join condition: None + +(89) Project [codegen id : 2] +Output [2]: [ss_quantity#78 AS quantity#83, ss_list_price#79 AS list_price#84] +Input [4]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80, d_date_sk#82] + +(90) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#87), dynamicpruningexpression(cs_sold_date_sk#87 IN dynamicpruning#88)] +ReadSchema: struct + +(91) ColumnarToRow [codegen id : 4] +Input [3]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87] + +(92) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#89] + +(93) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#87] +Right keys [1]: [d_date_sk#89] +Join type: Inner +Join condition: None + +(94) Project [codegen id : 4] +Output [2]: [cs_quantity#85 AS quantity#90, cs_list_price#86 AS list_price#91] +Input [4]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87, d_date_sk#89] + +(95) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#94), dynamicpruningexpression(ws_sold_date_sk#94 IN dynamicpruning#95)] +ReadSchema: struct + +(96) ColumnarToRow [codegen id : 6] +Input [3]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94] + +(97) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#96] + +(98) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#94] +Right keys [1]: [d_date_sk#96] +Join type: Inner +Join condition: None + +(99) Project [codegen id : 6] +Output [2]: [ws_quantity#92 AS quantity#97, ws_list_price#93 AS list_price#98] +Input [4]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94, d_date_sk#96] + +(100) Union + +(101) HashAggregate [codegen id : 7] +Input [2]: [quantity#83, list_price#84] +Keys: [] +Functions [1]: [partial_avg((cast(quantity#83 as decimal(10,0)) * list_price#84))] +Aggregate Attributes [2]: [sum#99, count#100] +Results [2]: [sum#101, count#102] + +(102) Exchange +Input [2]: [sum#101, count#102] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=12] + +(103) HashAggregate [codegen id : 8] +Input [2]: [sum#101, count#102] +Keys: [] +Functions [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))] +Aggregate Attributes [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))#103] +Results [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))#103 AS average_sales#104] + +Subquery:2 Hosting operator id = 85 Hosting Expression = ss_sold_date_sk#80 IN dynamicpruning#12 + +Subquery:3 Hosting operator id = 90 Hosting Expression = cs_sold_date_sk#87 IN dynamicpruning#12 + +Subquery:4 Hosting operator id = 95 Hosting Expression = ws_sold_date_sk#94 IN dynamicpruning#12 + +Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (108) ++- * Project (107) + +- * Filter (106) + +- * ColumnarToRow (105) + +- CometScan parquet spark_catalog.default.date_dim (104) + + +(104) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#42, d_week_seq#105] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#106), IsNotNull(d_date_sk)] +ReadSchema: struct + +(105) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#42, d_week_seq#105] + +(106) Filter [codegen id : 1] +Input [2]: [d_date_sk#42, d_week_seq#105] +Condition : ((isnotnull(d_week_seq#105) AND (d_week_seq#105 = ReusedSubquery Subquery scalar-subquery#106, [id=#107])) AND isnotnull(d_date_sk#42)) + +(107) Project [codegen id : 1] +Output [1]: [d_date_sk#42] +Input [2]: [d_date_sk#42, d_week_seq#105] + +(108) BroadcastExchange +Input [1]: [d_date_sk#42] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:6 Hosting operator id = 106 Hosting Expression = ReusedSubquery Subquery scalar-subquery#106, [id=#107] + +Subquery:7 Hosting operator id = 104 Hosting Expression = Subquery scalar-subquery#106, [id=#107] +* Project (112) ++- * Filter (111) + +- * ColumnarToRow (110) + +- CometScan parquet spark_catalog.default.date_dim (109) + + +(109) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,2000), EqualTo(d_moy,12), EqualTo(d_dom,11)] +ReadSchema: struct + +(110) ColumnarToRow [codegen id : 1] +Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] + +(111) Filter [codegen id : 1] +Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Condition : (((((isnotnull(d_year#109) AND isnotnull(d_moy#110)) AND isnotnull(d_dom#111)) AND (d_year#109 = 2000)) AND (d_moy#110 = 12)) AND (d_dom#111 = 11)) + +(112) Project [codegen id : 1] +Output [1]: [d_week_seq#108] +Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] + +Subquery:8 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 +BroadcastExchange (117) ++- * Project (116) + +- * Filter (115) + +- * ColumnarToRow (114) + +- CometScan parquet spark_catalog.default.date_dim (113) + + +(113) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#112] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(114) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#112] + +(115) Filter [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#112] +Condition : (((isnotnull(d_year#112) AND (d_year#112 >= 1999)) AND (d_year#112 <= 2001)) AND isnotnull(d_date_sk#25)) + +(116) Project [codegen id : 1] +Output [1]: [d_date_sk#25] +Input [2]: [d_date_sk#25, d_year#112] + +(117) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] + +Subquery:9 Hosting operator id = 13 Hosting Expression = cs_sold_date_sk#18 IN dynamicpruning#12 + +Subquery:10 Hosting operator id = 36 Hosting Expression = ws_sold_date_sk#30 IN dynamicpruning#12 + +Subquery:11 Hosting operator id = 81 Hosting Expression = ReusedSubquery Subquery scalar-subquery#54, [id=#55] + +Subquery:12 Hosting operator id = 67 Hosting Expression = ss_sold_date_sk#59 IN dynamicpruning#60 +BroadcastExchange (122) ++- * Project (121) + +- * Filter (120) + +- * ColumnarToRow (119) + +- CometScan parquet spark_catalog.default.date_dim (118) + + +(118) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#66, d_week_seq#113] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#114), IsNotNull(d_date_sk)] +ReadSchema: struct + +(119) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#66, d_week_seq#113] + +(120) Filter [codegen id : 1] +Input [2]: [d_date_sk#66, d_week_seq#113] +Condition : ((isnotnull(d_week_seq#113) AND (d_week_seq#113 = ReusedSubquery Subquery scalar-subquery#114, [id=#115])) AND isnotnull(d_date_sk#66)) + +(121) Project [codegen id : 1] +Output [1]: [d_date_sk#66] +Input [2]: [d_date_sk#66, d_week_seq#113] + +(122) BroadcastExchange +Input [1]: [d_date_sk#66] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15] + +Subquery:13 Hosting operator id = 120 Hosting Expression = ReusedSubquery Subquery scalar-subquery#114, [id=#115] + +Subquery:14 Hosting operator id = 118 Hosting Expression = Subquery scalar-subquery#114, [id=#115] +* Project (126) ++- * Filter (125) + +- * ColumnarToRow (124) + +- CometScan parquet spark_catalog.default.date_dim (123) + + +(123) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1999), EqualTo(d_moy,12), EqualTo(d_dom,11)] +ReadSchema: struct + +(124) ColumnarToRow [codegen id : 1] +Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] + +(125) Filter [codegen id : 1] +Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Condition : (((((isnotnull(d_year#117) AND isnotnull(d_moy#118)) AND isnotnull(d_dom#119)) AND (d_year#117 = 1999)) AND (d_moy#118 = 12)) AND (d_dom#119 = 11)) + +(126) Project [codegen id : 1] +Output [1]: [d_week_seq#116] +Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt new file mode 100644 index 000000000..64646b717 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt @@ -0,0 +1,204 @@ +TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_sales,channel,i_brand_id,i_class_id,i_category_id,sales,number_sales] + WholeStageCodegen (52) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + Filter [sales] + Subquery #4 + WholeStageCodegen (8) + HashAggregate [sum,count] [avg((cast(quantity as decimal(10,0)) * list_price)),average_sales,sum,count] + InputAdapter + Exchange #12 + WholeStageCodegen (7) + HashAggregate [quantity,list_price] [sum,count,sum,count] + InputAdapter + Union + WholeStageCodegen (2) + Project [ss_quantity,ss_list_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_list_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + WholeStageCodegen (4) + Project [cs_quantity,cs_list_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_quantity,cs_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + WholeStageCodegen (6) + Project [ws_quantity,ws_list_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #1 + WholeStageCodegen (25) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #2 + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + Subquery #2 + WholeStageCodegen (1) + Project [d_week_seq] + Filter [d_year,d_moy,d_dom] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (11) + Project [i_item_sk] + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] + Filter [i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (10) + BroadcastHashJoin [brand_id,class_id,category_id,i_brand_id,i_class_id,i_category_id] + HashAggregate [brand_id,class_id,category_id] + InputAdapter + Exchange [brand_id,class_id,category_id] #5 + WholeStageCodegen (6) + HashAggregate [brand_id,class_id,category_id] + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #3 + BroadcastExchange #6 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (4) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (3) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (1) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (9) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #9 + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (23) + BroadcastHashJoin [i_item_sk,ss_item_sk] + Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [ss_item_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (51) + Filter [sales] + ReusedSubquery [average_sales] #4 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #14 + WholeStageCodegen (50) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #5 + BroadcastExchange #15 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #6 + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + Subquery #6 + WholeStageCodegen (1) + Project [d_week_seq] + Filter [d_year,d_moy,d_dom] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] + InputAdapter + ReusedExchange [ss_item_sk] #3 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #11 + InputAdapter + ReusedExchange [d_date_sk] #15 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt new file mode 100644 index 000000000..10ae4b11b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt @@ -0,0 +1,164 @@ +== Physical Plan == +TakeOrderedAndProject (22) ++- * HashAggregate (21) + +- Exchange (20) + +- * HashAggregate (19) + +- * Project (18) + +- * BroadcastHashJoin Inner BuildRight (17) + :- * Project (15) + : +- * BroadcastHashJoin Inner BuildRight (14) + : :- * Project (9) + : : +- * BroadcastHashJoin Inner BuildRight (8) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : +- BroadcastExchange (7) + : : +- * Filter (6) + : : +- * ColumnarToRow (5) + : : +- CometScan parquet spark_catalog.default.customer (4) + : +- BroadcastExchange (13) + : +- * Filter (12) + : +- * ColumnarToRow (11) + : +- CometScan parquet spark_catalog.default.customer_address (10) + +- ReusedExchange (16) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_bill_customer_sk#1, cs_sales_price#2, cs_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [3]: [cs_bill_customer_sk#1, cs_sales_price#2, cs_sold_date_sk#3] + +(3) Filter [codegen id : 4] +Input [3]: [cs_bill_customer_sk#1, cs_sales_price#2, cs_sold_date_sk#3] +Condition : isnotnull(cs_bill_customer_sk#1) + +(4) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#5, c_current_addr_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [c_customer_sk#5, c_current_addr_sk#6] + +(6) Filter [codegen id : 1] +Input [2]: [c_customer_sk#5, c_current_addr_sk#6] +Condition : (isnotnull(c_customer_sk#5) AND isnotnull(c_current_addr_sk#6)) + +(7) BroadcastExchange +Input [2]: [c_customer_sk#5, c_current_addr_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [3]: [cs_sales_price#2, cs_sold_date_sk#3, c_current_addr_sk#6] +Input [5]: [cs_bill_customer_sk#1, cs_sales_price#2, cs_sold_date_sk#3, c_customer_sk#5, c_current_addr_sk#6] + +(10) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] + +(12) Filter [codegen id : 2] +Input [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] +Condition : isnotnull(ca_address_sk#7) + +(13) BroadcastExchange +Input [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [c_current_addr_sk#6] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: ((substr(ca_zip#9, 1, 5) IN (85669,86197,88274,83405,86475,85392,85460,80348,81792) OR ca_state#8 IN (CA,WA,GA)) OR (cs_sales_price#2 > 500.00)) + +(15) Project [codegen id : 4] +Output [3]: [cs_sales_price#2, cs_sold_date_sk#3, ca_zip#9] +Input [6]: [cs_sales_price#2, cs_sold_date_sk#3, c_current_addr_sk#6, ca_address_sk#7, ca_state#8, ca_zip#9] + +(16) ReusedExchange [Reuses operator id: 27] +Output [1]: [d_date_sk#10] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#3] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [2]: [cs_sales_price#2, ca_zip#9] +Input [4]: [cs_sales_price#2, cs_sold_date_sk#3, ca_zip#9, d_date_sk#10] + +(19) HashAggregate [codegen id : 4] +Input [2]: [cs_sales_price#2, ca_zip#9] +Keys [1]: [ca_zip#9] +Functions [1]: [partial_sum(UnscaledValue(cs_sales_price#2))] +Aggregate Attributes [1]: [sum#11] +Results [2]: [ca_zip#9, sum#12] + +(20) Exchange +Input [2]: [ca_zip#9, sum#12] +Arguments: hashpartitioning(ca_zip#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [2]: [ca_zip#9, sum#12] +Keys [1]: [ca_zip#9] +Functions [1]: [sum(UnscaledValue(cs_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_sales_price#2))#13] +Results [2]: [ca_zip#9, MakeDecimal(sum(UnscaledValue(cs_sales_price#2))#13,17,2) AS sum(cs_sales_price)#14] + +(22) TakeOrderedAndProject +Input [2]: [ca_zip#9, sum(cs_sales_price)#14] +Arguments: 100, [ca_zip#9 ASC NULLS FIRST], [ca_zip#9, sum(cs_sales_price)#14] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (27) ++- * Project (26) + +- * Filter (25) + +- * ColumnarToRow (24) + +- CometScan parquet spark_catalog.default.date_dim (23) + + +(23) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#15, d_qoy#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(24) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#15, d_qoy#16] + +(25) Filter [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#15, d_qoy#16] +Condition : ((((isnotnull(d_qoy#16) AND isnotnull(d_year#15)) AND (d_qoy#16 = 2)) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#10)) + +(26) Project [codegen id : 1] +Output [1]: [d_date_sk#10] +Input [3]: [d_date_sk#10, d_year#15, d_qoy#16] + +(27) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt new file mode 100644 index 000000000..4b916d78f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt @@ -0,0 +1,41 @@ +TakeOrderedAndProject [ca_zip,sum(cs_sales_price)] + WholeStageCodegen (5) + HashAggregate [ca_zip,sum] [sum(UnscaledValue(cs_sales_price)),sum(cs_sales_price),sum] + InputAdapter + Exchange [ca_zip] #1 + WholeStageCodegen (4) + HashAggregate [ca_zip,cs_sales_price] [sum,sum] + Project [cs_sales_price,ca_zip] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sales_price,cs_sold_date_sk,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk,ca_zip,ca_state,cs_sales_price] + Project [cs_sales_price,cs_sold_date_sk,c_current_addr_sk] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Filter [cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_qoy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [c_customer_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_zip] + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt new file mode 100644 index 000000000..d21c24281 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt @@ -0,0 +1,260 @@ +== Physical Plan == +* HashAggregate (45) ++- Exchange (44) + +- * HashAggregate (43) + +- * HashAggregate (42) + +- * HashAggregate (41) + +- * Project (40) + +- * BroadcastHashJoin Inner BuildRight (39) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (26) + : : +- * BroadcastHashJoin Inner BuildRight (25) + : : :- * SortMergeJoin LeftAnti (19) + : : : :- * Project (13) + : : : : +- * SortMergeJoin LeftSemi (12) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * Project (4) + : : : : : +- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : +- * Sort (11) + : : : : +- Exchange (10) + : : : : +- * Project (9) + : : : : +- * ColumnarToRow (8) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (7) + : : : +- * Sort (18) + : : : +- Exchange (17) + : : : +- * Project (16) + : : : +- * ColumnarToRow (15) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (14) + : : +- BroadcastExchange (24) + : : +- * Project (23) + : : +- * Filter (22) + : : +- * ColumnarToRow (21) + : : +- CometScan parquet spark_catalog.default.date_dim (20) + : +- BroadcastExchange (31) + : +- * Project (30) + : +- * Filter (29) + : +- * ColumnarToRow (28) + : +- CometScan parquet spark_catalog.default.customer_address (27) + +- BroadcastExchange (38) + +- * Project (37) + +- * Filter (36) + +- * ColumnarToRow (35) + +- CometScan parquet spark_catalog.default.call_center (34) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [8]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cs_sold_date_sk#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +PushedFilters: [IsNotNull(cs_ship_date_sk), IsNotNull(cs_ship_addr_sk), IsNotNull(cs_call_center_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [8]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cs_sold_date_sk#8] + +(3) Filter [codegen id : 1] +Input [8]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cs_sold_date_sk#8] +Condition : ((isnotnull(cs_ship_date_sk#1) AND isnotnull(cs_ship_addr_sk#2)) AND isnotnull(cs_call_center_sk#3)) + +(4) Project [codegen id : 1] +Output [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Input [8]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cs_sold_date_sk#8] + +(5) Exchange +Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Arguments: hashpartitioning(cs_order_number#5, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Arguments: [cs_order_number#5 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_warehouse_sk#9, cs_order_number#10, cs_sold_date_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 3] +Input [3]: [cs_warehouse_sk#9, cs_order_number#10, cs_sold_date_sk#11] + +(9) Project [codegen id : 3] +Output [2]: [cs_warehouse_sk#9, cs_order_number#10] +Input [3]: [cs_warehouse_sk#9, cs_order_number#10, cs_sold_date_sk#11] + +(10) Exchange +Input [2]: [cs_warehouse_sk#9, cs_order_number#10] +Arguments: hashpartitioning(cs_order_number#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [2]: [cs_warehouse_sk#9, cs_order_number#10] +Arguments: [cs_order_number#10 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 5] +Left keys [1]: [cs_order_number#5] +Right keys [1]: [cs_order_number#10] +Join type: LeftSemi +Join condition: NOT (cs_warehouse_sk#4 = cs_warehouse_sk#9) + +(13) Project [codegen id : 5] +Output [6]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] + +(14) Scan parquet spark_catalog.default.catalog_returns +Output [2]: [cr_order_number#12, cr_returned_date_sk#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 6] +Input [2]: [cr_order_number#12, cr_returned_date_sk#13] + +(16) Project [codegen id : 6] +Output [1]: [cr_order_number#12] +Input [2]: [cr_order_number#12, cr_returned_date_sk#13] + +(17) Exchange +Input [1]: [cr_order_number#12] +Arguments: hashpartitioning(cr_order_number#12, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(18) Sort [codegen id : 7] +Input [1]: [cr_order_number#12] +Arguments: [cr_order_number#12 ASC NULLS FIRST], false, 0 + +(19) SortMergeJoin [codegen id : 11] +Left keys [1]: [cs_order_number#5] +Right keys [1]: [cr_order_number#12] +Join type: LeftAnti +Join condition: None + +(20) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_date#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2002-02-01), LessThanOrEqual(d_date,2002-04-02), IsNotNull(d_date_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 8] +Input [2]: [d_date_sk#14, d_date#15] + +(22) Filter [codegen id : 8] +Input [2]: [d_date_sk#14, d_date#15] +Condition : (((isnotnull(d_date#15) AND (d_date#15 >= 2002-02-01)) AND (d_date#15 <= 2002-04-02)) AND isnotnull(d_date_sk#14)) + +(23) Project [codegen id : 8] +Output [1]: [d_date_sk#14] +Input [2]: [d_date_sk#14, d_date#15] + +(24) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(25) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_ship_date_sk#1] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 11] +Output [5]: [cs_ship_addr_sk#2, cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, d_date_sk#14] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#16, ca_state#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,GA), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) ColumnarToRow [codegen id : 9] +Input [2]: [ca_address_sk#16, ca_state#17] + +(29) Filter [codegen id : 9] +Input [2]: [ca_address_sk#16, ca_state#17] +Condition : ((isnotnull(ca_state#17) AND (ca_state#17 = GA)) AND isnotnull(ca_address_sk#16)) + +(30) Project [codegen id : 9] +Output [1]: [ca_address_sk#16] +Input [2]: [ca_address_sk#16, ca_state#17] + +(31) BroadcastExchange +Input [1]: [ca_address_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_ship_addr_sk#2] +Right keys [1]: [ca_address_sk#16] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 11] +Output [4]: [cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Input [6]: [cs_ship_addr_sk#2, cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, ca_address_sk#16] + +(34) Scan parquet spark_catalog.default.call_center +Output [2]: [cc_call_center_sk#18, cc_county#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/call_center] +PushedFilters: [IsNotNull(cc_county), EqualTo(cc_county,Williamson County), IsNotNull(cc_call_center_sk)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 10] +Input [2]: [cc_call_center_sk#18, cc_county#19] + +(36) Filter [codegen id : 10] +Input [2]: [cc_call_center_sk#18, cc_county#19] +Condition : ((isnotnull(cc_county#19) AND (cc_county#19 = Williamson County)) AND isnotnull(cc_call_center_sk#18)) + +(37) Project [codegen id : 10] +Output [1]: [cc_call_center_sk#18] +Input [2]: [cc_call_center_sk#18, cc_county#19] + +(38) BroadcastExchange +Input [1]: [cc_call_center_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_call_center_sk#3] +Right keys [1]: [cc_call_center_sk#18] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [3]: [cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Input [5]: [cs_call_center_sk#3, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cc_call_center_sk#18] + +(41) HashAggregate [codegen id : 11] +Input [3]: [cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +Keys [1]: [cs_order_number#5] +Functions [2]: [partial_sum(UnscaledValue(cs_ext_ship_cost#6)), partial_sum(UnscaledValue(cs_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_ship_cost#6))#20, sum(UnscaledValue(cs_net_profit#7))#21] +Results [3]: [cs_order_number#5, sum#22, sum#23] + +(42) HashAggregate [codegen id : 11] +Input [3]: [cs_order_number#5, sum#22, sum#23] +Keys [1]: [cs_order_number#5] +Functions [2]: [merge_sum(UnscaledValue(cs_ext_ship_cost#6)), merge_sum(UnscaledValue(cs_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_ship_cost#6))#20, sum(UnscaledValue(cs_net_profit#7))#21] +Results [3]: [cs_order_number#5, sum#22, sum#23] + +(43) HashAggregate [codegen id : 11] +Input [3]: [cs_order_number#5, sum#22, sum#23] +Keys: [] +Functions [3]: [merge_sum(UnscaledValue(cs_ext_ship_cost#6)), merge_sum(UnscaledValue(cs_net_profit#7)), partial_count(distinct cs_order_number#5)] +Aggregate Attributes [3]: [sum(UnscaledValue(cs_ext_ship_cost#6))#20, sum(UnscaledValue(cs_net_profit#7))#21, count(cs_order_number#5)#24] +Results [3]: [sum#22, sum#23, count#25] + +(44) Exchange +Input [3]: [sum#22, sum#23, count#25] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(45) HashAggregate [codegen id : 12] +Input [3]: [sum#22, sum#23, count#25] +Keys: [] +Functions [3]: [sum(UnscaledValue(cs_ext_ship_cost#6)), sum(UnscaledValue(cs_net_profit#7)), count(distinct cs_order_number#5)] +Aggregate Attributes [3]: [sum(UnscaledValue(cs_ext_ship_cost#6))#20, sum(UnscaledValue(cs_net_profit#7))#21, count(cs_order_number#5)#24] +Results [3]: [count(cs_order_number#5)#24 AS order count #26, MakeDecimal(sum(UnscaledValue(cs_ext_ship_cost#6))#20,17,2) AS total shipping cost #27, MakeDecimal(sum(UnscaledValue(cs_net_profit#7))#21,17,2) AS total net profit #28] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt new file mode 100644 index 000000000..5feaa702a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt @@ -0,0 +1,74 @@ +WholeStageCodegen (12) + HashAggregate [sum,sum,count] [sum(UnscaledValue(cs_ext_ship_cost)),sum(UnscaledValue(cs_net_profit)),count(cs_order_number),order count ,total shipping cost ,total net profit ,sum,sum,count] + InputAdapter + Exchange #1 + WholeStageCodegen (11) + HashAggregate [cs_order_number] [sum(UnscaledValue(cs_ext_ship_cost)),sum(UnscaledValue(cs_net_profit)),count(cs_order_number),sum,sum,count,sum,sum,count] + HashAggregate [cs_order_number] [sum(UnscaledValue(cs_ext_ship_cost)),sum(UnscaledValue(cs_net_profit)),sum,sum,sum,sum] + HashAggregate [cs_order_number,cs_ext_ship_cost,cs_net_profit] [sum(UnscaledValue(cs_ext_ship_cost)),sum(UnscaledValue(cs_net_profit)),sum,sum,sum,sum] + Project [cs_order_number,cs_ext_ship_cost,cs_net_profit] + BroadcastHashJoin [cs_call_center_sk,cc_call_center_sk] + Project [cs_call_center_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit] + BroadcastHashJoin [cs_ship_addr_sk,ca_address_sk] + Project [cs_ship_addr_sk,cs_call_center_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit] + BroadcastHashJoin [cs_ship_date_sk,d_date_sk] + SortMergeJoin [cs_order_number,cr_order_number] + InputAdapter + WholeStageCodegen (5) + Project [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit] + SortMergeJoin [cs_order_number,cs_order_number,cs_warehouse_sk,cs_warehouse_sk] + InputAdapter + WholeStageCodegen (2) + Sort [cs_order_number] + InputAdapter + Exchange [cs_order_number] #2 + WholeStageCodegen (1) + Project [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk,cs_warehouse_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit] + Filter [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk,cs_warehouse_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit,cs_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [cs_order_number] + InputAdapter + Exchange [cs_order_number] #3 + WholeStageCodegen (3) + Project [cs_warehouse_sk,cs_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_warehouse_sk,cs_order_number,cs_sold_date_sk] + InputAdapter + WholeStageCodegen (7) + Sort [cr_order_number] + InputAdapter + Exchange [cr_order_number] #4 + WholeStageCodegen (6) + Project [cr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_order_number,cr_returned_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (8) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (9) + Project [ca_address_sk] + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (10) + Project [cc_call_center_sk] + Filter [cc_county,cc_call_center_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_county] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt new file mode 100644 index 000000000..4548704d0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt @@ -0,0 +1,298 @@ +== Physical Plan == +TakeOrderedAndProject (40) ++- * HashAggregate (39) + +- Exchange (38) + +- * HashAggregate (37) + +- * Project (36) + +- * BroadcastHashJoin Inner BuildRight (35) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * Project (24) + : : +- * BroadcastHashJoin Inner BuildRight (23) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (18) + : : : : +- * BroadcastHashJoin Inner BuildRight (17) + : : : : :- * Project (15) + : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : :- * Project (9) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : :- * Filter (3) + : : : : : : : +- * ColumnarToRow (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- BroadcastExchange (7) + : : : : : : +- * Filter (6) + : : : : : : +- * ColumnarToRow (5) + : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : : : +- BroadcastExchange (13) + : : : : : +- * Filter (12) + : : : : : +- * ColumnarToRow (11) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (10) + : : : : +- ReusedExchange (16) + : : : +- ReusedExchange (19) + : : +- ReusedExchange (22) + : +- BroadcastExchange (28) + : +- * Filter (27) + : +- * ColumnarToRow (26) + : +- CometScan parquet spark_catalog.default.store (25) + +- BroadcastExchange (34) + +- * Filter (33) + +- * ColumnarToRow (32) + +- CometScan parquet spark_catalog.default.item (31) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 8] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] + +(3) Filter [codegen id : 8] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) + +(4) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#12), dynamicpruningexpression(sr_returned_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] + +(6) Filter [codegen id : 1] +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) + +(7) BroadcastExchange +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(input[1, int, false], input[0, int, false], input[2, int, false]),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 8] +Left keys [3]: [ss_customer_sk#2, ss_item_sk#1, ss_ticket_number#4] +Right keys [3]: [sr_customer_sk#9, sr_item_sk#8, sr_ticket_number#10] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] + +(10) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_sold_date_sk#17 IN dynamicpruning#18)] +PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] + +(12) Filter [codegen id : 2] +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) + +(13) BroadcastExchange +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[1, int, false] as bigint) & 4294967295))),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 8] +Left keys [2]: [sr_customer_sk#9, sr_item_sk#8] +Right keys [2]: [cs_bill_customer_sk#14, cs_item_sk#15] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17] +Input [12]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12, cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] + +(16) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#19] + +(17) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#6] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 8] +Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17] +Input [9]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#19] + +(19) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#20] + +(20) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [sr_returned_date_sk#12] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 8] +Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#20] + +(22) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#21] + +(23) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#17] +Right keys [1]: [d_date_sk#21] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 8] +Output [5]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16] +Input [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#21] + +(25) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#22, s_state#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 6] +Input [2]: [s_store_sk#22, s_state#23] + +(27) Filter [codegen id : 6] +Input [2]: [s_store_sk#22, s_state#23] +Condition : isnotnull(s_store_sk#22) + +(28) BroadcastExchange +Input [2]: [s_store_sk#22, s_state#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(29) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#22] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 8] +Output [5]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_state#23] +Input [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_sk#22, s_state#23] + +(31) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 7] +Input [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] + +(33) Filter [codegen id : 7] +Input [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] +Condition : isnotnull(i_item_sk#24) + +(34) BroadcastExchange +Input [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(35) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#24] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 8] +Output [6]: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_state#23, i_item_id#25, i_item_desc#26] +Input [8]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_state#23, i_item_sk#24, i_item_id#25, i_item_desc#26] + +(37) HashAggregate [codegen id : 8] +Input [6]: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_state#23, i_item_id#25, i_item_desc#26] +Keys [3]: [i_item_id#25, i_item_desc#26, s_state#23] +Functions [9]: [partial_count(ss_quantity#5), partial_avg(ss_quantity#5), partial_stddev_samp(cast(ss_quantity#5 as double)), partial_count(sr_return_quantity#11), partial_avg(sr_return_quantity#11), partial_stddev_samp(cast(sr_return_quantity#11 as double)), partial_count(cs_quantity#16), partial_avg(cs_quantity#16), partial_stddev_samp(cast(cs_quantity#16 as double))] +Aggregate Attributes [18]: [count#27, sum#28, count#29, n#30, avg#31, m2#32, count#33, sum#34, count#35, n#36, avg#37, m2#38, count#39, sum#40, count#41, n#42, avg#43, m2#44] +Results [21]: [i_item_id#25, i_item_desc#26, s_state#23, count#45, sum#46, count#47, n#48, avg#49, m2#50, count#51, sum#52, count#53, n#54, avg#55, m2#56, count#57, sum#58, count#59, n#60, avg#61, m2#62] + +(38) Exchange +Input [21]: [i_item_id#25, i_item_desc#26, s_state#23, count#45, sum#46, count#47, n#48, avg#49, m2#50, count#51, sum#52, count#53, n#54, avg#55, m2#56, count#57, sum#58, count#59, n#60, avg#61, m2#62] +Arguments: hashpartitioning(i_item_id#25, i_item_desc#26, s_state#23, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(39) HashAggregate [codegen id : 9] +Input [21]: [i_item_id#25, i_item_desc#26, s_state#23, count#45, sum#46, count#47, n#48, avg#49, m2#50, count#51, sum#52, count#53, n#54, avg#55, m2#56, count#57, sum#58, count#59, n#60, avg#61, m2#62] +Keys [3]: [i_item_id#25, i_item_desc#26, s_state#23] +Functions [9]: [count(ss_quantity#5), avg(ss_quantity#5), stddev_samp(cast(ss_quantity#5 as double)), count(sr_return_quantity#11), avg(sr_return_quantity#11), stddev_samp(cast(sr_return_quantity#11 as double)), count(cs_quantity#16), avg(cs_quantity#16), stddev_samp(cast(cs_quantity#16 as double))] +Aggregate Attributes [9]: [count(ss_quantity#5)#63, avg(ss_quantity#5)#64, stddev_samp(cast(ss_quantity#5 as double))#65, count(sr_return_quantity#11)#66, avg(sr_return_quantity#11)#67, stddev_samp(cast(sr_return_quantity#11 as double))#68, count(cs_quantity#16)#69, avg(cs_quantity#16)#70, stddev_samp(cast(cs_quantity#16 as double))#71] +Results [15]: [i_item_id#25, i_item_desc#26, s_state#23, count(ss_quantity#5)#63 AS store_sales_quantitycount#72, avg(ss_quantity#5)#64 AS store_sales_quantityave#73, stddev_samp(cast(ss_quantity#5 as double))#65 AS store_sales_quantitystdev#74, (stddev_samp(cast(ss_quantity#5 as double))#65 / avg(ss_quantity#5)#64) AS store_sales_quantitycov#75, count(sr_return_quantity#11)#66 AS as_store_returns_quantitycount#76, avg(sr_return_quantity#11)#67 AS as_store_returns_quantityave#77, stddev_samp(cast(sr_return_quantity#11 as double))#68 AS as_store_returns_quantitystdev#78, (stddev_samp(cast(sr_return_quantity#11 as double))#68 / avg(sr_return_quantity#11)#67) AS store_returns_quantitycov#79, count(cs_quantity#16)#69 AS catalog_sales_quantitycount#80, avg(cs_quantity#16)#70 AS catalog_sales_quantityave#81, (stddev_samp(cast(cs_quantity#16 as double))#71 / avg(cs_quantity#16)#70) AS catalog_sales_quantitystdev#82, (stddev_samp(cast(cs_quantity#16 as double))#71 / avg(cs_quantity#16)#70) AS catalog_sales_quantitycov#83] + +(40) TakeOrderedAndProject +Input [15]: [i_item_id#25, i_item_desc#26, s_state#23, store_sales_quantitycount#72, store_sales_quantityave#73, store_sales_quantitystdev#74, store_sales_quantitycov#75, as_store_returns_quantitycount#76, as_store_returns_quantityave#77, as_store_returns_quantitystdev#78, store_returns_quantitycov#79, catalog_sales_quantitycount#80, catalog_sales_quantityave#81, catalog_sales_quantitystdev#82, catalog_sales_quantitycov#83] +Arguments: 100, [i_item_id#25 ASC NULLS FIRST, i_item_desc#26 ASC NULLS FIRST, s_state#23 ASC NULLS FIRST], [i_item_id#25, i_item_desc#26, s_state#23, store_sales_quantitycount#72, store_sales_quantityave#73, store_sales_quantitystdev#74, store_sales_quantitycov#75, as_store_returns_quantitycount#76, as_store_returns_quantityave#77, as_store_returns_quantitystdev#78, store_returns_quantitycov#79, catalog_sales_quantitycount#80, catalog_sales_quantityave#81, catalog_sales_quantitystdev#82, catalog_sales_quantitycov#83] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (45) ++- * Project (44) + +- * Filter (43) + +- * ColumnarToRow (42) + +- CometScan parquet spark_catalog.default.date_dim (41) + + +(41) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#19, d_quarter_name#84] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_quarter_name), EqualTo(d_quarter_name,2001Q1), IsNotNull(d_date_sk)] +ReadSchema: struct + +(42) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#19, d_quarter_name#84] + +(43) Filter [codegen id : 1] +Input [2]: [d_date_sk#19, d_quarter_name#84] +Condition : ((isnotnull(d_quarter_name#84) AND (d_quarter_name#84 = 2001Q1)) AND isnotnull(d_date_sk#19)) + +(44) Project [codegen id : 1] +Output [1]: [d_date_sk#19] +Input [2]: [d_date_sk#19, d_quarter_name#84] + +(45) BroadcastExchange +Input [1]: [d_date_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (50) ++- * Project (49) + +- * Filter (48) + +- * ColumnarToRow (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#20, d_quarter_name#85] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_quarter_name, [2001Q1,2001Q2,2001Q3]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#20, d_quarter_name#85] + +(48) Filter [codegen id : 1] +Input [2]: [d_date_sk#20, d_quarter_name#85] +Condition : (d_quarter_name#85 IN (2001Q1,2001Q2,2001Q3) AND isnotnull(d_date_sk#20)) + +(49) Project [codegen id : 1] +Output [1]: [d_date_sk#20] +Input [2]: [d_date_sk#20, d_quarter_name#85] + +(50) BroadcastExchange +Input [1]: [d_date_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:3 Hosting operator id = 10 Hosting Expression = cs_sold_date_sk#17 IN dynamicpruning#13 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt new file mode 100644 index 000000000..2e1e780a7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt @@ -0,0 +1,76 @@ +TakeOrderedAndProject [i_item_id,i_item_desc,s_state,store_sales_quantitycount,store_sales_quantityave,store_sales_quantitystdev,store_sales_quantitycov,as_store_returns_quantitycount,as_store_returns_quantityave,as_store_returns_quantitystdev,store_returns_quantitycov,catalog_sales_quantitycount,catalog_sales_quantityave,catalog_sales_quantitystdev,catalog_sales_quantitycov] + WholeStageCodegen (9) + HashAggregate [i_item_id,i_item_desc,s_state,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2] [count(ss_quantity),avg(ss_quantity),stddev_samp(cast(ss_quantity as double)),count(sr_return_quantity),avg(sr_return_quantity),stddev_samp(cast(sr_return_quantity as double)),count(cs_quantity),avg(cs_quantity),stddev_samp(cast(cs_quantity as double)),store_sales_quantitycount,store_sales_quantityave,store_sales_quantitystdev,store_sales_quantitycov,as_store_returns_quantitycount,as_store_returns_quantityave,as_store_returns_quantitystdev,store_returns_quantitycov,catalog_sales_quantitycount,catalog_sales_quantityave,catalog_sales_quantitystdev,catalog_sales_quantitycov,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2] + InputAdapter + Exchange [i_item_id,i_item_desc,s_state] #1 + WholeStageCodegen (8) + HashAggregate [i_item_id,i_item_desc,s_state,ss_quantity,sr_return_quantity,cs_quantity] [count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2,count,sum,count,n,avg,m2] + Project [ss_quantity,sr_return_quantity,cs_quantity,s_state,i_item_id,i_item_desc] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,sr_return_quantity,cs_quantity,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,cs_quantity] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,sr_returned_date_sk,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sold_date_sk,sr_return_quantity,sr_returned_date_sk,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [sr_customer_sk,sr_item_sk,cs_bill_customer_sk,cs_item_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sold_date_sk,sr_item_sk,sr_customer_sk,sr_return_quantity,sr_returned_date_sk] + BroadcastHashJoin [ss_customer_sk,ss_item_sk,ss_ticket_number,sr_customer_sk,sr_item_sk,sr_ticket_number] + Filter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_quantity,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_quarter_name,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_quarter_name] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [sr_customer_sk,sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_return_quantity,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_quarter_name,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_quarter_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + Filter [cs_bill_customer_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt new file mode 100644 index 000000000..34421b640 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt @@ -0,0 +1,281 @@ +== Physical Plan == +TakeOrderedAndProject (43) ++- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Expand (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (29) + : : +- * BroadcastHashJoin Inner BuildRight (28) + : : :- * Project (23) + : : : +- * BroadcastHashJoin Inner BuildRight (22) + : : : :- * Project (17) + : : : : +- * BroadcastHashJoin Inner BuildRight (16) + : : : : :- * Project (10) + : : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : : :- * Filter (3) + : : : : : : +- * ColumnarToRow (2) + : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : +- BroadcastExchange (8) + : : : : : +- * Project (7) + : : : : : +- * Filter (6) + : : : : : +- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : : : +- BroadcastExchange (15) + : : : : +- * Project (14) + : : : : +- * Filter (13) + : : : : +- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.customer (11) + : : : +- BroadcastExchange (21) + : : : +- * Filter (20) + : : : +- * ColumnarToRow (19) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (18) + : : +- BroadcastExchange (27) + : : +- * Filter (26) + : : +- * ColumnarToRow (25) + : : +- CometScan parquet spark_catalog.default.customer_address (24) + : +- ReusedExchange (30) + +- BroadcastExchange (36) + +- * Filter (35) + +- * ColumnarToRow (34) + +- CometScan parquet spark_catalog.default.item (33) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#9), dynamicpruningexpression(cs_sold_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 7] +Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] + +(3) Filter [codegen id : 7] +Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] +Condition : ((isnotnull(cs_bill_cdemo_sk#2) AND isnotnull(cs_bill_customer_sk#1)) AND isnotnull(cs_item_sk#3)) + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_education_status), EqualTo(cd_gender,F), EqualTo(cd_education_status,Unknown ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] + +(6) Filter [codegen id : 1] +Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Condition : ((((isnotnull(cd_gender#12) AND isnotnull(cd_education_status#13)) AND (cd_gender#12 = F)) AND (cd_education_status#13 = Unknown )) AND isnotnull(cd_demo_sk#11)) + +(7) Project [codegen id : 1] +Output [2]: [cd_demo_sk#11, cd_dep_count#14] +Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] + +(8) BroadcastExchange +Input [2]: [cd_demo_sk#11, cd_dep_count#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_bill_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#11] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 7] +Output [9]: [cs_bill_customer_sk#1, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14] +Input [11]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_demo_sk#11, cd_dep_count#14] + +(11) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [In(c_birth_month, [1,12,2,6,8,9]), IsNotNull(c_customer_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] + +(13) Filter [codegen id : 2] +Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Condition : (((c_birth_month#18 IN (1,6,8,9,12,2) AND isnotnull(c_customer_sk#15)) AND isnotnull(c_current_cdemo_sk#16)) AND isnotnull(c_current_addr_sk#17)) + +(14) Project [codegen id : 2] +Output [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] + +(15) BroadcastExchange +Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#15] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 7] +Output [11]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +Input [13]: [cs_bill_customer_sk#1, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] + +(18) Scan parquet spark_catalog.default.customer_demographics +Output [1]: [cd_demo_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 3] +Input [1]: [cd_demo_sk#20] + +(20) Filter [codegen id : 3] +Input [1]: [cd_demo_sk#20] +Condition : isnotnull(cd_demo_sk#20) + +(21) BroadcastExchange +Input [1]: [cd_demo_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_cdemo_sk#16] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(23) Project [codegen id : 7] +Output [10]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_addr_sk#17, c_birth_year#19] +Input [12]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19, cd_demo_sk#20] + +(24) Scan parquet spark_catalog.default.customer_address +Output [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [IN,MS,ND,NM,OK,VA]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(25) ColumnarToRow [codegen id : 4] +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] + +(26) Filter [codegen id : 4] +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Condition : (ca_state#23 IN (MS,IN,ND,OK,NM,VA) AND isnotnull(ca_address_sk#21)) + +(27) BroadcastExchange +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_addr_sk#17] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 7] +Output [12]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24] +Input [14]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_addr_sk#17, c_birth_year#19, ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] + +(30) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_sold_date_sk#9] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 7] +Output [11]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24] +Input [13]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24, d_date_sk#25] + +(33) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#26, i_item_id#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(34) ColumnarToRow [codegen id : 6] +Input [2]: [i_item_sk#26, i_item_id#27] + +(35) Filter [codegen id : 6] +Input [2]: [i_item_sk#26, i_item_id#27] +Condition : isnotnull(i_item_sk#26) + +(36) BroadcastExchange +Input [2]: [i_item_sk#26, i_item_id#27] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_item_sk#3] +Right keys [1]: [i_item_sk#26] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 7] +Output [11]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, ca_county#22] +Input [13]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24, i_item_sk#26, i_item_id#27] + +(39) Expand [codegen id : 7] +Input [11]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, ca_county#22] +Arguments: [[cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, ca_county#22, 0], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, null, 1], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, null, null, 3], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, null, null, null, 7], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, null, null, null, null, 15]], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32] + +(40) HashAggregate [codegen id : 7] +Input [12]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32] +Keys [5]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32] +Functions [7]: [partial_avg(cast(cs_quantity#4 as decimal(12,2))), partial_avg(cast(cs_list_price#5 as decimal(12,2))), partial_avg(cast(cs_coupon_amt#7 as decimal(12,2))), partial_avg(cast(cs_sales_price#6 as decimal(12,2))), partial_avg(cast(cs_net_profit#8 as decimal(12,2))), partial_avg(cast(c_birth_year#19 as decimal(12,2))), partial_avg(cast(cd_dep_count#14 as decimal(12,2)))] +Aggregate Attributes [14]: [sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40, sum#41, count#42, sum#43, count#44, sum#45, count#46] +Results [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#47, count#48, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60] + +(41) Exchange +Input [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#47, count#48, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60] +Arguments: hashpartitioning(i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(42) HashAggregate [codegen id : 8] +Input [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#47, count#48, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60] +Keys [5]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32] +Functions [7]: [avg(cast(cs_quantity#4 as decimal(12,2))), avg(cast(cs_list_price#5 as decimal(12,2))), avg(cast(cs_coupon_amt#7 as decimal(12,2))), avg(cast(cs_sales_price#6 as decimal(12,2))), avg(cast(cs_net_profit#8 as decimal(12,2))), avg(cast(c_birth_year#19 as decimal(12,2))), avg(cast(cd_dep_count#14 as decimal(12,2)))] +Aggregate Attributes [7]: [avg(cast(cs_quantity#4 as decimal(12,2)))#61, avg(cast(cs_list_price#5 as decimal(12,2)))#62, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#63, avg(cast(cs_sales_price#6 as decimal(12,2)))#64, avg(cast(cs_net_profit#8 as decimal(12,2)))#65, avg(cast(c_birth_year#19 as decimal(12,2)))#66, avg(cast(cd_dep_count#14 as decimal(12,2)))#67] +Results [11]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, avg(cast(cs_quantity#4 as decimal(12,2)))#61 AS agg1#68, avg(cast(cs_list_price#5 as decimal(12,2)))#62 AS agg2#69, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#63 AS agg3#70, avg(cast(cs_sales_price#6 as decimal(12,2)))#64 AS agg4#71, avg(cast(cs_net_profit#8 as decimal(12,2)))#65 AS agg5#72, avg(cast(c_birth_year#19 as decimal(12,2)))#66 AS agg6#73, avg(cast(cd_dep_count#14 as decimal(12,2)))#67 AS agg7#74] + +(43) TakeOrderedAndProject +Input [11]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, agg1#68, agg2#69, agg3#70, agg4#71, agg5#72, agg6#73, agg7#74] +Arguments: 100, [ca_country#29 ASC NULLS FIRST, ca_state#30 ASC NULLS FIRST, ca_county#31 ASC NULLS FIRST, i_item_id#28 ASC NULLS FIRST], [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, agg1#68, agg2#69, agg3#70, agg4#71, agg5#72, agg6#73, agg7#74] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#9 IN dynamicpruning#10 +BroadcastExchange (48) ++- * Project (47) + +- * Filter (46) + +- * ColumnarToRow (45) + +- CometScan parquet spark_catalog.default.date_dim (44) + + +(44) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#75] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1998), IsNotNull(d_date_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#75] + +(46) Filter [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#75] +Condition : ((isnotnull(d_year#75) AND (d_year#75 = 1998)) AND isnotnull(d_date_sk#25)) + +(47) Project [codegen id : 1] +Output [1]: [d_date_sk#25] +Input [2]: [d_date_sk#25, d_year#75] + +(48) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt new file mode 100644 index 000000000..723e30a44 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt @@ -0,0 +1,71 @@ +TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,agg4,agg5,agg6,agg7] + WholeStageCodegen (8) + HashAggregate [i_item_id,ca_country,ca_state,ca_county,spark_grouping_id,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(cast(cs_quantity as decimal(12,2))),avg(cast(cs_list_price as decimal(12,2))),avg(cast(cs_coupon_amt as decimal(12,2))),avg(cast(cs_sales_price as decimal(12,2))),avg(cast(cs_net_profit as decimal(12,2))),avg(cast(c_birth_year as decimal(12,2))),avg(cast(cd_dep_count as decimal(12,2))),agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,ca_country,ca_state,ca_county,spark_grouping_id] #1 + WholeStageCodegen (7) + HashAggregate [i_item_id,ca_country,ca_state,ca_county,spark_grouping_id,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Expand [cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,i_item_id,ca_country,ca_state,ca_county] + Project [cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,i_item_id,ca_country,ca_state,ca_county] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,ca_county,ca_state,ca_country] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year,ca_county,ca_state,ca_country] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [cd_demo_sk,cd_dep_count] + Filter [cd_gender,cd_education_status,cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_education_status,cd_dep_count] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + Filter [c_birth_month,c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_month,c_birth_year] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt new file mode 100644 index 000000000..8a13a8dc7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt @@ -0,0 +1,227 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * HashAggregate (38) + +- Exchange (37) + +- * HashAggregate (36) + +- * Project (35) + +- * BroadcastHashJoin Inner BuildRight (34) + :- * Project (29) + : +- * BroadcastHashJoin Inner BuildRight (28) + : :- * Project (23) + : : +- * BroadcastHashJoin Inner BuildRight (22) + : : :- * Project (17) + : : : +- * BroadcastHashJoin Inner BuildRight (16) + : : : :- * Project (10) + : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : :- * Project (4) + : : : : : +- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.date_dim (1) + : : : : +- BroadcastExchange (8) + : : : : +- * Filter (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometScan parquet spark_catalog.default.store_sales (5) + : : : +- BroadcastExchange (15) + : : : +- * Project (14) + : : : +- * Filter (13) + : : : +- * ColumnarToRow (12) + : : : +- CometScan parquet spark_catalog.default.item (11) + : : +- BroadcastExchange (21) + : : +- * Filter (20) + : : +- * ColumnarToRow (19) + : : +- CometScan parquet spark_catalog.default.customer (18) + : +- BroadcastExchange (27) + : +- * Filter (26) + : +- * ColumnarToRow (25) + : +- CometScan parquet spark_catalog.default.customer_address (24) + +- BroadcastExchange (33) + +- * Filter (32) + +- * ColumnarToRow (31) + +- CometScan parquet spark_catalog.default.store (30) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_moy#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,1998), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 6] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] + +(3) Filter [codegen id : 6] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 1998)) AND isnotnull(d_date_sk#1)) + +(4) Project [codegen id : 6] +Output [1]: [d_date_sk#1] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] + +(5) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] + +(7) Filter [codegen id : 1] +Input [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_item_sk#4) AND isnotnull(ss_customer_sk#5)) AND isnotnull(ss_store_sk#6)) + +(8) BroadcastExchange +Input [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[4, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#8] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 6] +Output [4]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7] +Input [6]: [d_date_sk#1, ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] + +(11) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, i_manager_id#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,8), IsNotNull(i_item_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [6]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, i_manager_id#14] + +(13) Filter [codegen id : 2] +Input [6]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, i_manager_id#14] +Condition : ((isnotnull(i_manager_id#14) AND (i_manager_id#14 = 8)) AND isnotnull(i_item_sk#9)) + +(14) Project [codegen id : 2] +Output [5]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] +Input [6]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, i_manager_id#14] + +(15) BroadcastExchange +Input [5]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_item_sk#4] +Right keys [1]: [i_item_sk#9] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 6] +Output [7]: [ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] +Input [9]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] + +(18) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#15, c_current_addr_sk#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 3] +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] + +(20) Filter [codegen id : 3] +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] +Condition : (isnotnull(c_customer_sk#15) AND isnotnull(c_current_addr_sk#16)) + +(21) BroadcastExchange +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_customer_sk#5] +Right keys [1]: [c_customer_sk#15] +Join type: Inner +Join condition: None + +(23) Project [codegen id : 6] +Output [7]: [ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, c_current_addr_sk#16] +Input [9]: [ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, c_customer_sk#15, c_current_addr_sk#16] + +(24) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#17, ca_zip#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_zip)] +ReadSchema: struct + +(25) ColumnarToRow [codegen id : 4] +Input [2]: [ca_address_sk#17, ca_zip#18] + +(26) Filter [codegen id : 4] +Input [2]: [ca_address_sk#17, ca_zip#18] +Condition : (isnotnull(ca_address_sk#17) AND isnotnull(ca_zip#18)) + +(27) BroadcastExchange +Input [2]: [ca_address_sk#17, ca_zip#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_current_addr_sk#16] +Right keys [1]: [ca_address_sk#17] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [7]: [ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, ca_zip#18] +Input [9]: [ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, c_current_addr_sk#16, ca_address_sk#17, ca_zip#18] + +(30) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#19, s_zip#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_zip), IsNotNull(s_store_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 5] +Input [2]: [s_store_sk#19, s_zip#20] + +(32) Filter [codegen id : 5] +Input [2]: [s_store_sk#19, s_zip#20] +Condition : (isnotnull(s_zip#20) AND isnotnull(s_store_sk#19)) + +(33) BroadcastExchange +Input [2]: [s_store_sk#19, s_zip#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_store_sk#6] +Right keys [1]: [s_store_sk#19] +Join type: Inner +Join condition: NOT (substr(ca_zip#18, 1, 5) = substr(s_zip#20, 1, 5)) + +(35) Project [codegen id : 6] +Output [5]: [ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] +Input [9]: [ss_store_sk#6, ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, ca_zip#18, s_store_sk#19, s_zip#20] + +(36) HashAggregate [codegen id : 6] +Input [5]: [ss_ext_sales_price#7, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] +Keys [4]: [i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#7))] +Aggregate Attributes [1]: [sum#21] +Results [5]: [i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13, sum#22] + +(37) Exchange +Input [5]: [i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13, sum#22] +Arguments: hashpartitioning(i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(38) HashAggregate [codegen id : 7] +Input [5]: [i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13, sum#22] +Keys [4]: [i_brand#11, i_brand_id#10, i_manufact_id#12, i_manufact#13] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#7))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#7))#23] +Results [5]: [i_brand_id#10 AS brand_id#24, i_brand#11 AS brand#25, i_manufact_id#12, i_manufact#13, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#7))#23,17,2) AS ext_price#26] + +(39) TakeOrderedAndProject +Input [5]: [brand_id#24, brand#25, i_manufact_id#12, i_manufact#13, ext_price#26] +Arguments: 100, [ext_price#26 DESC NULLS LAST, brand#25 ASC NULLS FIRST, brand_id#24 ASC NULLS FIRST, i_manufact_id#12 ASC NULLS FIRST, i_manufact#13 ASC NULLS FIRST], [brand_id#24, brand#25, i_manufact_id#12, i_manufact#13, ext_price#26] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt new file mode 100644 index 000000000..85e4886d7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt @@ -0,0 +1,58 @@ +TakeOrderedAndProject [ext_price,brand,brand_id,i_manufact_id,i_manufact] + WholeStageCodegen (7) + HashAggregate [i_brand,i_brand_id,i_manufact_id,i_manufact,sum] [sum(UnscaledValue(ss_ext_sales_price)),brand_id,brand,ext_price,sum] + InputAdapter + Exchange [i_brand,i_brand_id,i_manufact_id,i_manufact] #1 + WholeStageCodegen (6) + HashAggregate [i_brand,i_brand_id,i_manufact_id,i_manufact,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_brand_id,i_brand,i_manufact_id,i_manufact] + BroadcastHashJoin [ss_store_sk,s_store_sk,ca_zip,s_zip] + Project [ss_store_sk,ss_ext_sales_price,i_brand_id,i_brand,i_manufact_id,i_manufact,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_store_sk,ss_ext_sales_price,i_brand_id,i_brand,i_manufact_id,i_manufact,c_current_addr_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_store_sk,ss_ext_sales_price,i_brand_id,i_brand,i_manufact_id,i_manufact] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ext_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + Project [d_date_sk] + Filter [d_moy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_item_sk,ss_customer_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [i_item_sk,i_brand_id,i_brand,i_manufact_id,i_manufact] + Filter [i_manager_id,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manufact_id,i_manufact,i_manager_id] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Filter [c_customer_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Filter [ca_address_sk,ca_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_zip] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Filter [s_zip,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_zip] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt new file mode 100644 index 000000000..4bfb19a38 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt @@ -0,0 +1,212 @@ +== Physical Plan == +* Sort (37) ++- Exchange (36) + +- * Project (35) + +- * BroadcastHashJoin Inner BuildRight (34) + :- * Project (23) + : +- * BroadcastHashJoin Inner BuildRight (22) + : :- * HashAggregate (16) + : : +- Exchange (15) + : : +- * HashAggregate (14) + : : +- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- Union (7) + : : : :- * Project (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : +- * Project (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (4) + : : +- BroadcastExchange (11) + : : +- * Filter (10) + : : +- * ColumnarToRow (9) + : : +- CometScan parquet spark_catalog.default.date_dim (8) + : +- BroadcastExchange (21) + : +- * Project (20) + : +- * Filter (19) + : +- * ColumnarToRow (18) + : +- CometScan parquet spark_catalog.default.date_dim (17) + +- BroadcastExchange (33) + +- * Project (32) + +- * BroadcastHashJoin Inner BuildRight (31) + :- * HashAggregate (25) + : +- ReusedExchange (24) + +- BroadcastExchange (30) + +- * Project (29) + +- * Filter (28) + +- * ColumnarToRow (27) + +- CometScan parquet spark_catalog.default.date_dim (26) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_ext_sales_price#1, ws_sold_date_sk#2] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#2)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [2]: [ws_ext_sales_price#1, ws_sold_date_sk#2] + +(3) Project [codegen id : 1] +Output [2]: [ws_sold_date_sk#2 AS sold_date_sk#3, ws_ext_sales_price#1 AS sales_price#4] +Input [2]: [ws_ext_sales_price#1, ws_sold_date_sk#2] + +(4) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ext_sales_price#5, cs_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#6)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [cs_ext_sales_price#5, cs_sold_date_sk#6] + +(6) Project [codegen id : 2] +Output [2]: [cs_sold_date_sk#6 AS sold_date_sk#7, cs_ext_sales_price#5 AS sales_price#8] +Input [2]: [cs_ext_sales_price#5, cs_sold_date_sk#6] + +(7) Union + +(8) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk), IsNotNull(d_week_seq)] +ReadSchema: struct + +(9) ColumnarToRow [codegen id : 3] +Input [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] + +(10) Filter [codegen id : 3] +Input [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] +Condition : (isnotnull(d_date_sk#9) AND isnotnull(d_week_seq#10)) + +(11) BroadcastExchange +Input [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [sold_date_sk#3] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [3]: [sales_price#4, d_week_seq#10, d_day_name#11] +Input [5]: [sold_date_sk#3, sales_price#4, d_date_sk#9, d_week_seq#10, d_day_name#11] + +(14) HashAggregate [codegen id : 4] +Input [3]: [sales_price#4, d_week_seq#10, d_day_name#11] +Keys [1]: [d_week_seq#10] +Functions [7]: [partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))] +Aggregate Attributes [7]: [sum#12, sum#13, sum#14, sum#15, sum#16, sum#17, sum#18] +Results [8]: [d_week_seq#10, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24, sum#25] + +(15) Exchange +Input [8]: [d_week_seq#10, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24, sum#25] +Arguments: hashpartitioning(d_week_seq#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(16) HashAggregate [codegen id : 12] +Input [8]: [d_week_seq#10, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24, sum#25] +Keys [1]: [d_week_seq#10] +Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))] +Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END))#27, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END))#28, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END))#29, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END))#30, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END))#31, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))#32] +Results [8]: [d_week_seq#10, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END))#26,17,2) AS sun_sales#33, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END))#27,17,2) AS mon_sales#34, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END))#28,17,2) AS tue_sales#35, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END))#29,17,2) AS wed_sales#36, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END))#30,17,2) AS thu_sales#37, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END))#31,17,2) AS fri_sales#38, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))#32,17,2) AS sat_sales#39] + +(17) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_week_seq#40, d_year#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_week_seq)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 5] +Input [2]: [d_week_seq#40, d_year#41] + +(19) Filter [codegen id : 5] +Input [2]: [d_week_seq#40, d_year#41] +Condition : ((isnotnull(d_year#41) AND (d_year#41 = 2001)) AND isnotnull(d_week_seq#40)) + +(20) Project [codegen id : 5] +Output [1]: [d_week_seq#40] +Input [2]: [d_week_seq#40, d_year#41] + +(21) BroadcastExchange +Input [1]: [d_week_seq#40] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 12] +Left keys [1]: [d_week_seq#10] +Right keys [1]: [d_week_seq#40] +Join type: Inner +Join condition: None + +(23) Project [codegen id : 12] +Output [8]: [d_week_seq#10 AS d_week_seq1#42, sun_sales#33 AS sun_sales1#43, mon_sales#34 AS mon_sales1#44, tue_sales#35 AS tue_sales1#45, wed_sales#36 AS wed_sales1#46, thu_sales#37 AS thu_sales1#47, fri_sales#38 AS fri_sales1#48, sat_sales#39 AS sat_sales1#49] +Input [9]: [d_week_seq#10, sun_sales#33, mon_sales#34, tue_sales#35, wed_sales#36, thu_sales#37, fri_sales#38, sat_sales#39, d_week_seq#40] + +(24) ReusedExchange [Reuses operator id: 15] +Output [8]: [d_week_seq#50, sum#51, sum#52, sum#53, sum#54, sum#55, sum#56, sum#57] + +(25) HashAggregate [codegen id : 11] +Input [8]: [d_week_seq#50, sum#51, sum#52, sum#53, sum#54, sum#55, sum#56, sum#57] +Keys [1]: [d_week_seq#50] +Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#58 = Sunday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Monday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Tuesday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Wednesday) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Thursday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Friday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Saturday ) THEN sales_price#59 END))] +Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#58 = Sunday ) THEN sales_price#59 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Monday ) THEN sales_price#59 END))#27, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Tuesday ) THEN sales_price#59 END))#28, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Wednesday) THEN sales_price#59 END))#29, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Thursday ) THEN sales_price#59 END))#30, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Friday ) THEN sales_price#59 END))#31, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Saturday ) THEN sales_price#59 END))#32] +Results [8]: [d_week_seq#50, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Sunday ) THEN sales_price#59 END))#26,17,2) AS sun_sales#60, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Monday ) THEN sales_price#59 END))#27,17,2) AS mon_sales#61, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Tuesday ) THEN sales_price#59 END))#28,17,2) AS tue_sales#62, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Wednesday) THEN sales_price#59 END))#29,17,2) AS wed_sales#63, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Thursday ) THEN sales_price#59 END))#30,17,2) AS thu_sales#64, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Friday ) THEN sales_price#59 END))#31,17,2) AS fri_sales#65, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Saturday ) THEN sales_price#59 END))#32,17,2) AS sat_sales#66] + +(26) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_week_seq#67, d_year#68] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_week_seq)] +ReadSchema: struct + +(27) ColumnarToRow [codegen id : 10] +Input [2]: [d_week_seq#67, d_year#68] + +(28) Filter [codegen id : 10] +Input [2]: [d_week_seq#67, d_year#68] +Condition : ((isnotnull(d_year#68) AND (d_year#68 = 2002)) AND isnotnull(d_week_seq#67)) + +(29) Project [codegen id : 10] +Output [1]: [d_week_seq#67] +Input [2]: [d_week_seq#67, d_year#68] + +(30) BroadcastExchange +Input [1]: [d_week_seq#67] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(31) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [d_week_seq#50] +Right keys [1]: [d_week_seq#67] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 11] +Output [8]: [d_week_seq#50 AS d_week_seq2#69, sun_sales#60 AS sun_sales2#70, mon_sales#61 AS mon_sales2#71, tue_sales#62 AS tue_sales2#72, wed_sales#63 AS wed_sales2#73, thu_sales#64 AS thu_sales2#74, fri_sales#65 AS fri_sales2#75, sat_sales#66 AS sat_sales2#76] +Input [9]: [d_week_seq#50, sun_sales#60, mon_sales#61, tue_sales#62, wed_sales#63, thu_sales#64, fri_sales#65, sat_sales#66, d_week_seq#67] + +(33) BroadcastExchange +Input [8]: [d_week_seq2#69, sun_sales2#70, mon_sales2#71, tue_sales2#72, wed_sales2#73, thu_sales2#74, fri_sales2#75, sat_sales2#76] +Arguments: HashedRelationBroadcastMode(List(cast((input[0, int, true] - 53) as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 12] +Left keys [1]: [d_week_seq1#42] +Right keys [1]: [(d_week_seq2#69 - 53)] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 12] +Output [8]: [d_week_seq1#42, round((sun_sales1#43 / sun_sales2#70), 2) AS round((sun_sales1 / sun_sales2), 2)#77, round((mon_sales1#44 / mon_sales2#71), 2) AS round((mon_sales1 / mon_sales2), 2)#78, round((tue_sales1#45 / tue_sales2#72), 2) AS round((tue_sales1 / tue_sales2), 2)#79, round((wed_sales1#46 / wed_sales2#73), 2) AS round((wed_sales1 / wed_sales2), 2)#80, round((thu_sales1#47 / thu_sales2#74), 2) AS round((thu_sales1 / thu_sales2), 2)#81, round((fri_sales1#48 / fri_sales2#75), 2) AS round((fri_sales1 / fri_sales2), 2)#82, round((sat_sales1#49 / sat_sales2#76), 2) AS round((sat_sales1 / sat_sales2), 2)#83] +Input [16]: [d_week_seq1#42, sun_sales1#43, mon_sales1#44, tue_sales1#45, wed_sales1#46, thu_sales1#47, fri_sales1#48, sat_sales1#49, d_week_seq2#69, sun_sales2#70, mon_sales2#71, tue_sales2#72, wed_sales2#73, thu_sales2#74, fri_sales2#75, sat_sales2#76] + +(36) Exchange +Input [8]: [d_week_seq1#42, round((sun_sales1 / sun_sales2), 2)#77, round((mon_sales1 / mon_sales2), 2)#78, round((tue_sales1 / tue_sales2), 2)#79, round((wed_sales1 / wed_sales2), 2)#80, round((thu_sales1 / thu_sales2), 2)#81, round((fri_sales1 / fri_sales2), 2)#82, round((sat_sales1 / sat_sales2), 2)#83] +Arguments: rangepartitioning(d_week_seq1#42 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(37) Sort [codegen id : 13] +Input [8]: [d_week_seq1#42, round((sun_sales1 / sun_sales2), 2)#77, round((mon_sales1 / mon_sales2), 2)#78, round((tue_sales1 / tue_sales2), 2)#79, round((wed_sales1 / wed_sales2), 2)#80, round((thu_sales1 / thu_sales2), 2)#81, round((fri_sales1 / fri_sales2), 2)#82, round((sat_sales1 / sat_sales2), 2)#83] +Arguments: [d_week_seq1#42 ASC NULLS FIRST], true, 0 + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt new file mode 100644 index 000000000..0008304e8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt @@ -0,0 +1,59 @@ +WholeStageCodegen (13) + Sort [d_week_seq1] + InputAdapter + Exchange [d_week_seq1] #1 + WholeStageCodegen (12) + Project [d_week_seq1,sun_sales1,sun_sales2,mon_sales1,mon_sales2,tue_sales1,tue_sales2,wed_sales1,wed_sales2,thu_sales1,thu_sales2,fri_sales1,fri_sales2,sat_sales1,sat_sales2] + BroadcastHashJoin [d_week_seq1,d_week_seq2] + Project [d_week_seq,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] + BroadcastHashJoin [d_week_seq,d_week_seq] + HashAggregate [d_week_seq,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] + InputAdapter + Exchange [d_week_seq] #2 + WholeStageCodegen (4) + HashAggregate [d_week_seq,d_day_name,sales_price] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,d_week_seq,d_day_name] + BroadcastHashJoin [sold_date_sk,d_date_sk] + InputAdapter + Union + WholeStageCodegen (1) + Project [ws_sold_date_sk,ws_ext_sales_price] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_ext_sales_price,ws_sold_date_sk] + WholeStageCodegen (2) + Project [cs_sold_date_sk,cs_ext_sales_price] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ext_sales_price,cs_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (3) + Filter [d_date_sk,d_week_seq] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq,d_day_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (5) + Project [d_week_seq] + Filter [d_year,d_week_seq] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (11) + Project [d_week_seq,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] + BroadcastHashJoin [d_week_seq,d_week_seq] + HashAggregate [d_week_seq,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] + InputAdapter + ReusedExchange [d_week_seq,sum,sum,sum,sum,sum,sum,sum] #2 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (10) + Project [d_week_seq] + Filter [d_year,d_week_seq] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt new file mode 100644 index 000000000..f5455e62f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt @@ -0,0 +1,150 @@ +== Physical Plan == +TakeOrderedAndProject (20) ++- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : +- BroadcastExchange (7) + : +- * Filter (6) + : +- * ColumnarToRow (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] + +(3) Filter [codegen id : 3] +Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] +Condition : isnotnull(cs_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(6) Filter [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 25] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [cs_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [cs_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#2))#14] +Results [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#2))#14,17,2) AS _w0#16, i_item_id#6] + +(16) Exchange +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18, i_item_id#6] +Input [8]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6, _we0#17] + +(20) TakeOrderedAndProject +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18, i_item_id#6] +Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (25) ++- * Project (24) + +- * Filter (23) + +- * ColumnarToRow (22) + +- CometScan parquet spark_catalog.default.date_dim (21) + + +(21) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(22) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] + +(23) Filter [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(24) Project [codegen id : 1] +Output [1]: [d_date_sk#11] +Input [2]: [d_date_sk#11, d_date#19] + +(25) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt new file mode 100644 index 000000000..fbbf149b5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt @@ -0,0 +1,40 @@ +TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_current_price,itemrevenue] + WholeStageCodegen (6) + Project [i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0,i_item_id] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(cs_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #2 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ext_sales_price,cs_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [i_category,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt new file mode 100644 index 000000000..a5417a5b6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt @@ -0,0 +1,169 @@ +== Physical Plan == +TakeOrderedAndProject (24) ++- * Filter (23) + +- * HashAggregate (22) + +- Exchange (21) + +- * HashAggregate (20) + +- * Project (19) + +- * BroadcastHashJoin Inner BuildRight (18) + :- * Project (16) + : +- * BroadcastHashJoin Inner BuildRight (15) + : :- * Project (9) + : : +- * BroadcastHashJoin Inner BuildRight (8) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : +- BroadcastExchange (7) + : : +- * Filter (6) + : : +- * ColumnarToRow (5) + : : +- CometScan parquet spark_catalog.default.warehouse (4) + : +- BroadcastExchange (14) + : +- * Project (13) + : +- * Filter (12) + : +- * ColumnarToRow (11) + : +- CometScan parquet spark_catalog.default.item (10) + +- ReusedExchange (17) + + +(1) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(inv_warehouse_sk), IsNotNull(inv_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] + +(3) Filter [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_warehouse_sk#2) AND isnotnull(inv_item_sk#1)) + +(4) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] + +(6) Filter [codegen id : 1] +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Condition : isnotnull(w_warehouse_sk#6) + +(7) BroadcastExchange +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_warehouse_sk#2] +Right keys [1]: [w_warehouse_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [4]: [inv_item_sk#1, inv_quantity_on_hand#3, inv_date_sk#4, w_warehouse_name#7] +Input [6]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, w_warehouse_sk#6, w_warehouse_name#7] + +(10) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#8, i_item_id#9, i_current_price#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,0.99), LessThanOrEqual(i_current_price,1.49), IsNotNull(i_item_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#8, i_item_id#9, i_current_price#10] + +(12) Filter [codegen id : 2] +Input [3]: [i_item_sk#8, i_item_id#9, i_current_price#10] +Condition : (((isnotnull(i_current_price#10) AND (i_current_price#10 >= 0.99)) AND (i_current_price#10 <= 1.49)) AND isnotnull(i_item_sk#8)) + +(13) Project [codegen id : 2] +Output [2]: [i_item_sk#8, i_item_id#9] +Input [3]: [i_item_sk#8, i_item_id#9, i_current_price#10] + +(14) BroadcastExchange +Input [2]: [i_item_sk#8, i_item_id#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#8] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 4] +Output [4]: [inv_quantity_on_hand#3, inv_date_sk#4, w_warehouse_name#7, i_item_id#9] +Input [6]: [inv_item_sk#1, inv_quantity_on_hand#3, inv_date_sk#4, w_warehouse_name#7, i_item_sk#8, i_item_id#9] + +(17) ReusedExchange [Reuses operator id: 28] +Output [2]: [d_date_sk#11, d_date#12] + +(18) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#4] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 4] +Output [4]: [inv_quantity_on_hand#3, w_warehouse_name#7, i_item_id#9, d_date#12] +Input [6]: [inv_quantity_on_hand#3, inv_date_sk#4, w_warehouse_name#7, i_item_id#9, d_date_sk#11, d_date#12] + +(20) HashAggregate [codegen id : 4] +Input [4]: [inv_quantity_on_hand#3, w_warehouse_name#7, i_item_id#9, d_date#12] +Keys [2]: [w_warehouse_name#7, i_item_id#9] +Functions [2]: [partial_sum(CASE WHEN (d_date#12 < 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END), partial_sum(CASE WHEN (d_date#12 >= 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)] +Aggregate Attributes [2]: [sum#13, sum#14] +Results [4]: [w_warehouse_name#7, i_item_id#9, sum#15, sum#16] + +(21) Exchange +Input [4]: [w_warehouse_name#7, i_item_id#9, sum#15, sum#16] +Arguments: hashpartitioning(w_warehouse_name#7, i_item_id#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [4]: [w_warehouse_name#7, i_item_id#9, sum#15, sum#16] +Keys [2]: [w_warehouse_name#7, i_item_id#9] +Functions [2]: [sum(CASE WHEN (d_date#12 < 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END), sum(CASE WHEN (d_date#12 >= 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)] +Aggregate Attributes [2]: [sum(CASE WHEN (d_date#12 < 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)#17, sum(CASE WHEN (d_date#12 >= 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)#18] +Results [4]: [w_warehouse_name#7, i_item_id#9, sum(CASE WHEN (d_date#12 < 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)#17 AS inv_before#19, sum(CASE WHEN (d_date#12 >= 2000-03-11) THEN inv_quantity_on_hand#3 ELSE 0 END)#18 AS inv_after#20] + +(23) Filter [codegen id : 5] +Input [4]: [w_warehouse_name#7, i_item_id#9, inv_before#19, inv_after#20] +Condition : (CASE WHEN (inv_before#19 > 0) THEN ((cast(inv_after#20 as double) / cast(inv_before#19 as double)) >= 0.666667) END AND CASE WHEN (inv_before#19 > 0) THEN ((cast(inv_after#20 as double) / cast(inv_before#19 as double)) <= 1.5) END) + +(24) TakeOrderedAndProject +Input [4]: [w_warehouse_name#7, i_item_id#9, inv_before#19, inv_after#20] +Arguments: 100, [w_warehouse_name#7 ASC NULLS FIRST, i_item_id#9 ASC NULLS FIRST], [w_warehouse_name#7, i_item_id#9, inv_before#19, inv_after#20] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (28) ++- * Filter (27) + +- * ColumnarToRow (26) + +- CometScan parquet spark_catalog.default.date_dim (25) + + +(25) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-02-10), LessThanOrEqual(d_date,2000-04-10), IsNotNull(d_date_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#12] + +(27) Filter [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#12] +Condition : (((isnotnull(d_date#12) AND (d_date#12 >= 2000-02-10)) AND (d_date#12 <= 2000-04-10)) AND isnotnull(d_date_sk#11)) + +(28) BroadcastExchange +Input [2]: [d_date_sk#11, d_date#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt new file mode 100644 index 000000000..912965257 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt @@ -0,0 +1,42 @@ +TakeOrderedAndProject [w_warehouse_name,i_item_id,inv_before,inv_after] + WholeStageCodegen (5) + Filter [inv_before,inv_after] + HashAggregate [w_warehouse_name,i_item_id,sum,sum] [sum(CASE WHEN (d_date < 2000-03-11) THEN inv_quantity_on_hand ELSE 0 END),sum(CASE WHEN (d_date >= 2000-03-11) THEN inv_quantity_on_hand ELSE 0 END),inv_before,inv_after,sum,sum] + InputAdapter + Exchange [w_warehouse_name,i_item_id] #1 + WholeStageCodegen (4) + HashAggregate [w_warehouse_name,i_item_id,d_date,inv_quantity_on_hand] [sum,sum,sum,sum] + Project [inv_quantity_on_hand,w_warehouse_name,i_item_id,d_date] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [inv_quantity_on_hand,inv_date_sk,w_warehouse_name,i_item_id] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Project [inv_item_sk,inv_quantity_on_hand,inv_date_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Filter [inv_warehouse_sk,inv_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [i_item_sk,i_item_id] + Filter [i_current_price,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_current_price] + InputAdapter + ReusedExchange [d_date_sk,d_date] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt new file mode 100644 index 000000000..c7f0a8f49 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt @@ -0,0 +1,169 @@ +== Physical Plan == +TakeOrderedAndProject (23) ++- * HashAggregate (22) + +- Exchange (21) + +- * HashAggregate (20) + +- * Expand (19) + +- * Project (18) + +- * BroadcastHashJoin Inner BuildRight (17) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * Filter (9) + : +- * ColumnarToRow (8) + : +- CometScan parquet spark_catalog.default.item (7) + +- BroadcastExchange (16) + +- * Filter (15) + +- * ColumnarToRow (14) + +- CometScan parquet spark_catalog.default.warehouse (13) + + +(1) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] + +(3) Filter [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) + +(4) ReusedExchange [Reuses operator id: 28] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [3]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3] +Input [5]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] + +(9) Filter [codegen id : 2] +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Condition : isnotnull(i_item_sk#7) + +(10) BroadcastExchange +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Input [8]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] + +(13) Scan parquet spark_catalog.default.warehouse +Output [1]: [w_warehouse_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [1]: [w_warehouse_sk#12] + +(15) Filter [codegen id : 3] +Input [1]: [w_warehouse_sk#12] +Condition : isnotnull(w_warehouse_sk#12) + +(16) BroadcastExchange +Input [1]: [w_warehouse_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_warehouse_sk#2] +Right keys [1]: [w_warehouse_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, i_category#10] +Input [7]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11, w_warehouse_sk#12] + +(19) Expand [codegen id : 4] +Input [5]: [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, i_category#10] +Arguments: [[inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, i_category#10, 0], [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, null, 1], [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, null, null, 3], [inv_quantity_on_hand#3, i_product_name#11, null, null, null, 7], [inv_quantity_on_hand#3, null, null, null, null, 15]], [inv_quantity_on_hand#3, i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17] + +(20) HashAggregate [codegen id : 4] +Input [6]: [inv_quantity_on_hand#3, i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17] +Keys [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17] +Functions [1]: [partial_avg(inv_quantity_on_hand#3)] +Aggregate Attributes [2]: [sum#18, count#19] +Results [7]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, sum#20, count#21] + +(21) Exchange +Input [7]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, sum#20, count#21] +Arguments: hashpartitioning(i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [7]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, sum#20, count#21] +Keys [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17] +Functions [1]: [avg(inv_quantity_on_hand#3)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#3)#22] +Results [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, avg(inv_quantity_on_hand#3)#22 AS qoh#23] + +(23) TakeOrderedAndProject +Input [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, qoh#23] +Arguments: 100, [qoh#23 ASC NULLS FIRST, i_product_name#13 ASC NULLS FIRST, i_brand#14 ASC NULLS FIRST, i_class#15 ASC NULLS FIRST, i_category#16 ASC NULLS FIRST], [i_product_name#13, i_brand#14, i_class#15, i_category#16, qoh#23] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (28) ++- * Project (27) + +- * Filter (26) + +- * ColumnarToRow (25) + +- CometScan parquet spark_catalog.default.date_dim (24) + + +(24) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_month_seq#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(25) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#6, d_month_seq#24] + +(26) Filter [codegen id : 1] +Input [2]: [d_date_sk#6, d_month_seq#24] +Condition : (((isnotnull(d_month_seq#24) AND (d_month_seq#24 >= 1200)) AND (d_month_seq#24 <= 1211)) AND isnotnull(d_date_sk#6)) + +(27) Project [codegen id : 1] +Output [1]: [d_date_sk#6] +Input [2]: [d_date_sk#6, d_month_seq#24] + +(28) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt new file mode 100644 index 000000000..495490277 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt @@ -0,0 +1,42 @@ +TakeOrderedAndProject [qoh,i_product_name,i_brand,i_class,i_category] + WholeStageCodegen (5) + HashAggregate [i_product_name,i_brand,i_class,i_category,spark_grouping_id,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + Exchange [i_product_name,i_brand,i_class,i_category,spark_grouping_id] #1 + WholeStageCodegen (4) + HashAggregate [i_product_name,i_brand,i_class,i_category,spark_grouping_id,inv_quantity_on_hand] [sum,count,sum,count] + Expand [inv_quantity_on_hand,i_product_name,i_brand,i_class,i_category] + Project [inv_quantity_on_hand,i_product_name,i_brand,i_class,i_category] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,i_brand,i_class,i_category,i_product_name] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Project [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Filter [inv_item_sk,inv_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt new file mode 100644 index 000000000..2f5140f7f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt @@ -0,0 +1,570 @@ +== Physical Plan == +* HashAggregate (66) ++- Exchange (65) + +- * HashAggregate (64) + +- Union (63) + :- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (42) + : : +- * SortMergeJoin LeftSemi (41) + : : :- * Sort (24) + : : : +- Exchange (23) + : : : +- * Project (22) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (21) + : : : :- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : +- BroadcastExchange (20) + : : : +- * Project (19) + : : : +- * Filter (18) + : : : +- * HashAggregate (17) + : : : +- Exchange (16) + : : : +- * HashAggregate (15) + : : : +- * Project (14) + : : : +- * BroadcastHashJoin Inner BuildRight (13) + : : : :- * Project (8) + : : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : : :- * Filter (5) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (3) + : : : : +- ReusedExchange (6) + : : : +- BroadcastExchange (12) + : : : +- * Filter (11) + : : : +- * ColumnarToRow (10) + : : : +- CometScan parquet spark_catalog.default.item (9) + : : +- * Sort (40) + : : +- * Project (39) + : : +- * Filter (38) + : : +- * HashAggregate (37) + : : +- Exchange (36) + : : +- * HashAggregate (35) + : : +- * Project (34) + : : +- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Project (28) + : : : +- * Filter (27) + : : : +- * ColumnarToRow (26) + : : : +- CometScan parquet spark_catalog.default.store_sales (25) + : : +- BroadcastExchange (32) + : : +- * Filter (31) + : : +- * ColumnarToRow (30) + : : +- CometScan parquet spark_catalog.default.customer (29) + : +- ReusedExchange (43) + +- * Project (62) + +- * BroadcastHashJoin Inner BuildRight (61) + :- * Project (59) + : +- * SortMergeJoin LeftSemi (58) + : :- * Sort (52) + : : +- Exchange (51) + : : +- * Project (50) + : : +- * BroadcastHashJoin LeftSemi BuildRight (49) + : : :- * ColumnarToRow (47) + : : : +- CometScan parquet spark_catalog.default.web_sales (46) + : : +- ReusedExchange (48) + : +- * Sort (57) + : +- * Project (56) + : +- * Filter (55) + : +- * HashAggregate (54) + : +- ReusedExchange (53) + +- ReusedExchange (60) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sold_date_sk#5 IN dynamicpruning#6)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] + +(3) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] + +(5) Filter [codegen id : 3] +Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] +Condition : isnotnull(ss_item_sk#7) + +(6) ReusedExchange [Reuses operator id: 76] +Output [2]: [d_date_sk#10, d_date#11] + +(7) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 3] +Output [2]: [ss_item_sk#7, d_date#11] +Input [4]: [ss_item_sk#7, ss_sold_date_sk#8, d_date_sk#10, d_date#11] + +(9) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#12, i_item_desc#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(10) ColumnarToRow [codegen id : 2] +Input [2]: [i_item_sk#12, i_item_desc#13] + +(11) Filter [codegen id : 2] +Input [2]: [i_item_sk#12, i_item_desc#13] +Condition : isnotnull(i_item_sk#12) + +(12) BroadcastExchange +Input [2]: [i_item_sk#12, i_item_desc#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(13) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#7] +Right keys [1]: [i_item_sk#12] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 3] +Output [3]: [d_date#11, i_item_sk#12, substr(i_item_desc#13, 1, 30) AS _groupingexpression#14] +Input [4]: [ss_item_sk#7, d_date#11, i_item_sk#12, i_item_desc#13] + +(15) HashAggregate [codegen id : 3] +Input [3]: [d_date#11, i_item_sk#12, _groupingexpression#14] +Keys [3]: [_groupingexpression#14, i_item_sk#12, d_date#11] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#15] +Results [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] + +(16) Exchange +Input [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] +Arguments: hashpartitioning(_groupingexpression#14, i_item_sk#12, d_date#11, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(17) HashAggregate [codegen id : 4] +Input [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] +Keys [3]: [_groupingexpression#14, i_item_sk#12, d_date#11] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#17] +Results [2]: [i_item_sk#12 AS item_sk#18, count(1)#17 AS cnt#19] + +(18) Filter [codegen id : 4] +Input [2]: [item_sk#18, cnt#19] +Condition : (cnt#19 > 4) + +(19) Project [codegen id : 4] +Output [1]: [item_sk#18] +Input [2]: [item_sk#18, cnt#19] + +(20) BroadcastExchange +Input [1]: [item_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_item_sk#2] +Right keys [1]: [item_sk#18] +Join type: LeftSemi +Join condition: None + +(22) Project [codegen id : 5] +Output [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] + +(23) Exchange +Input [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Arguments: hashpartitioning(cs_bill_customer_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(24) Sort [codegen id : 6] +Input [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Arguments: [cs_bill_customer_sk#1 ASC NULLS FIRST], false, 0 + +(25) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 8] +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] + +(27) Filter [codegen id : 8] +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Condition : isnotnull(ss_customer_sk#20) + +(28) Project [codegen id : 8] +Output [3]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] + +(29) Scan parquet spark_catalog.default.customer +Output [1]: [c_customer_sk#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 7] +Input [1]: [c_customer_sk#24] + +(31) Filter [codegen id : 7] +Input [1]: [c_customer_sk#24] +Condition : isnotnull(c_customer_sk#24) + +(32) BroadcastExchange +Input [1]: [c_customer_sk#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_customer_sk#20] +Right keys [1]: [c_customer_sk#24] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 8] +Output [3]: [ss_quantity#21, ss_sales_price#22, c_customer_sk#24] +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, c_customer_sk#24] + +(35) HashAggregate [codegen id : 8] +Input [3]: [ss_quantity#21, ss_sales_price#22, c_customer_sk#24] +Keys [1]: [c_customer_sk#24] +Functions [1]: [partial_sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))] +Aggregate Attributes [2]: [sum#25, isEmpty#26] +Results [3]: [c_customer_sk#24, sum#27, isEmpty#28] + +(36) Exchange +Input [3]: [c_customer_sk#24, sum#27, isEmpty#28] +Arguments: hashpartitioning(c_customer_sk#24, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(37) HashAggregate [codegen id : 9] +Input [3]: [c_customer_sk#24, sum#27, isEmpty#28] +Keys [1]: [c_customer_sk#24] +Functions [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29] +Results [2]: [c_customer_sk#24, sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29 AS ssales#30] + +(38) Filter [codegen id : 9] +Input [2]: [c_customer_sk#24, ssales#30] +Condition : (isnotnull(ssales#30) AND (cast(ssales#30 as decimal(38,8)) > (0.500000 * Subquery scalar-subquery#31, [id=#32]))) + +(39) Project [codegen id : 9] +Output [1]: [c_customer_sk#24] +Input [2]: [c_customer_sk#24, ssales#30] + +(40) Sort [codegen id : 9] +Input [1]: [c_customer_sk#24] +Arguments: [c_customer_sk#24 ASC NULLS FIRST], false, 0 + +(41) SortMergeJoin [codegen id : 11] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#24] +Join type: LeftSemi +Join condition: None + +(42) Project [codegen id : 11] +Output [3]: [cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Input [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] + +(43) ReusedExchange [Reuses operator id: 71] +Output [1]: [d_date_sk#33] + +(44) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_date_sk#5] +Right keys [1]: [d_date_sk#33] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 11] +Output [1]: [(cast(cs_quantity#3 as decimal(10,0)) * cs_list_price#4) AS sales#34] +Input [4]: [cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5, d_date_sk#33] + +(46) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#35, ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#39), dynamicpruningexpression(ws_sold_date_sk#39 IN dynamicpruning#40)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 16] +Input [5]: [ws_item_sk#35, ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] + +(48) ReusedExchange [Reuses operator id: 20] +Output [1]: [item_sk#41] + +(49) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [ws_item_sk#35] +Right keys [1]: [item_sk#41] +Join type: LeftSemi +Join condition: None + +(50) Project [codegen id : 16] +Output [4]: [ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] +Input [5]: [ws_item_sk#35, ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] + +(51) Exchange +Input [4]: [ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] +Arguments: hashpartitioning(ws_bill_customer_sk#36, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(52) Sort [codegen id : 17] +Input [4]: [ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] +Arguments: [ws_bill_customer_sk#36 ASC NULLS FIRST], false, 0 + +(53) ReusedExchange [Reuses operator id: 36] +Output [3]: [c_customer_sk#42, sum#43, isEmpty#44] + +(54) HashAggregate [codegen id : 20] +Input [3]: [c_customer_sk#42, sum#43, isEmpty#44] +Keys [1]: [c_customer_sk#42] +Functions [1]: [sum((cast(ss_quantity#45 as decimal(10,0)) * ss_sales_price#46))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#45 as decimal(10,0)) * ss_sales_price#46))#29] +Results [2]: [c_customer_sk#42, sum((cast(ss_quantity#45 as decimal(10,0)) * ss_sales_price#46))#29 AS ssales#47] + +(55) Filter [codegen id : 20] +Input [2]: [c_customer_sk#42, ssales#47] +Condition : (isnotnull(ssales#47) AND (cast(ssales#47 as decimal(38,8)) > (0.500000 * ReusedSubquery Subquery scalar-subquery#31, [id=#32]))) + +(56) Project [codegen id : 20] +Output [1]: [c_customer_sk#42] +Input [2]: [c_customer_sk#42, ssales#47] + +(57) Sort [codegen id : 20] +Input [1]: [c_customer_sk#42] +Arguments: [c_customer_sk#42 ASC NULLS FIRST], false, 0 + +(58) SortMergeJoin [codegen id : 22] +Left keys [1]: [ws_bill_customer_sk#36] +Right keys [1]: [c_customer_sk#42] +Join type: LeftSemi +Join condition: None + +(59) Project [codegen id : 22] +Output [3]: [ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] +Input [4]: [ws_bill_customer_sk#36, ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39] + +(60) ReusedExchange [Reuses operator id: 71] +Output [1]: [d_date_sk#48] + +(61) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [ws_sold_date_sk#39] +Right keys [1]: [d_date_sk#48] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 22] +Output [1]: [(cast(ws_quantity#37 as decimal(10,0)) * ws_list_price#38) AS sales#49] +Input [4]: [ws_quantity#37, ws_list_price#38, ws_sold_date_sk#39, d_date_sk#48] + +(63) Union + +(64) HashAggregate [codegen id : 23] +Input [1]: [sales#34] +Keys: [] +Functions [1]: [partial_sum(sales#34)] +Aggregate Attributes [2]: [sum#50, isEmpty#51] +Results [2]: [sum#52, isEmpty#53] + +(65) Exchange +Input [2]: [sum#52, isEmpty#53] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=8] + +(66) HashAggregate [codegen id : 24] +Input [2]: [sum#52, isEmpty#53] +Keys: [] +Functions [1]: [sum(sales#34)] +Aggregate Attributes [1]: [sum(sales#34)#54] +Results [1]: [sum(sales#34)#54 AS sum(sales)#55] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (71) ++- * Project (70) + +- * Filter (69) + +- * ColumnarToRow (68) + +- CometScan parquet spark_catalog.default.date_dim (67) + + +(67) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#33, d_year#56, d_moy#57] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,2), IsNotNull(d_date_sk)] +ReadSchema: struct + +(68) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#33, d_year#56, d_moy#57] + +(69) Filter [codegen id : 1] +Input [3]: [d_date_sk#33, d_year#56, d_moy#57] +Condition : ((((isnotnull(d_year#56) AND isnotnull(d_moy#57)) AND (d_year#56 = 2000)) AND (d_moy#57 = 2)) AND isnotnull(d_date_sk#33)) + +(70) Project [codegen id : 1] +Output [1]: [d_date_sk#33] +Input [3]: [d_date_sk#33, d_year#56, d_moy#57] + +(71) BroadcastExchange +Input [1]: [d_date_sk#33] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 3 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (76) ++- * Project (75) + +- * Filter (74) + +- * ColumnarToRow (73) + +- CometScan parquet spark_catalog.default.date_dim (72) + + +(72) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_date#11, d_year#58] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(73) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#10, d_date#11, d_year#58] + +(74) Filter [codegen id : 1] +Input [3]: [d_date_sk#10, d_date#11, d_year#58] +Condition : (d_year#58 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#10)) + +(75) Project [codegen id : 1] +Output [2]: [d_date_sk#10, d_date#11] +Input [3]: [d_date_sk#10, d_date#11, d_year#58] + +(76) BroadcastExchange +Input [2]: [d_date_sk#10, d_date#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=10] + +Subquery:3 Hosting operator id = 38 Hosting Expression = Subquery scalar-subquery#31, [id=#32] +* HashAggregate (91) ++- Exchange (90) + +- * HashAggregate (89) + +- * HashAggregate (88) + +- Exchange (87) + +- * HashAggregate (86) + +- * Project (85) + +- * BroadcastHashJoin Inner BuildRight (84) + :- * Project (82) + : +- * BroadcastHashJoin Inner BuildRight (81) + : :- * Filter (79) + : : +- * ColumnarToRow (78) + : : +- CometScan parquet spark_catalog.default.store_sales (77) + : +- ReusedExchange (80) + +- ReusedExchange (83) + + +(77) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#59, ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#62), dynamicpruningexpression(ss_sold_date_sk#62 IN dynamicpruning#63)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(78) ColumnarToRow [codegen id : 3] +Input [4]: [ss_customer_sk#59, ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62] + +(79) Filter [codegen id : 3] +Input [4]: [ss_customer_sk#59, ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62] +Condition : isnotnull(ss_customer_sk#59) + +(80) ReusedExchange [Reuses operator id: 32] +Output [1]: [c_customer_sk#64] + +(81) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_customer_sk#59] +Right keys [1]: [c_customer_sk#64] +Join type: Inner +Join condition: None + +(82) Project [codegen id : 3] +Output [4]: [ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62, c_customer_sk#64] +Input [5]: [ss_customer_sk#59, ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62, c_customer_sk#64] + +(83) ReusedExchange [Reuses operator id: 96] +Output [1]: [d_date_sk#65] + +(84) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#62] +Right keys [1]: [d_date_sk#65] +Join type: Inner +Join condition: None + +(85) Project [codegen id : 3] +Output [3]: [ss_quantity#60, ss_sales_price#61, c_customer_sk#64] +Input [5]: [ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62, c_customer_sk#64, d_date_sk#65] + +(86) HashAggregate [codegen id : 3] +Input [3]: [ss_quantity#60, ss_sales_price#61, c_customer_sk#64] +Keys [1]: [c_customer_sk#64] +Functions [1]: [partial_sum((cast(ss_quantity#60 as decimal(10,0)) * ss_sales_price#61))] +Aggregate Attributes [2]: [sum#66, isEmpty#67] +Results [3]: [c_customer_sk#64, sum#68, isEmpty#69] + +(87) Exchange +Input [3]: [c_customer_sk#64, sum#68, isEmpty#69] +Arguments: hashpartitioning(c_customer_sk#64, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(88) HashAggregate [codegen id : 4] +Input [3]: [c_customer_sk#64, sum#68, isEmpty#69] +Keys [1]: [c_customer_sk#64] +Functions [1]: [sum((cast(ss_quantity#60 as decimal(10,0)) * ss_sales_price#61))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#60 as decimal(10,0)) * ss_sales_price#61))#70] +Results [1]: [sum((cast(ss_quantity#60 as decimal(10,0)) * ss_sales_price#61))#70 AS csales#71] + +(89) HashAggregate [codegen id : 4] +Input [1]: [csales#71] +Keys: [] +Functions [1]: [partial_max(csales#71)] +Aggregate Attributes [1]: [max#72] +Results [1]: [max#73] + +(90) Exchange +Input [1]: [max#73] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=12] + +(91) HashAggregate [codegen id : 5] +Input [1]: [max#73] +Keys: [] +Functions [1]: [max(csales#71)] +Aggregate Attributes [1]: [max(csales#71)#74] +Results [1]: [max(csales#71)#74 AS tpcds_cmax#75] + +Subquery:4 Hosting operator id = 77 Hosting Expression = ss_sold_date_sk#62 IN dynamicpruning#63 +BroadcastExchange (96) ++- * Project (95) + +- * Filter (94) + +- * ColumnarToRow (93) + +- CometScan parquet spark_catalog.default.date_dim (92) + + +(92) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#65, d_year#76] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(93) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#65, d_year#76] + +(94) Filter [codegen id : 1] +Input [2]: [d_date_sk#65, d_year#76] +Condition : (d_year#76 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#65)) + +(95) Project [codegen id : 1] +Output [1]: [d_date_sk#65] +Input [2]: [d_date_sk#65, d_year#76] + +(96) BroadcastExchange +Input [1]: [d_date_sk#65] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:5 Hosting operator id = 46 Hosting Expression = ws_sold_date_sk#39 IN dynamicpruning#6 + +Subquery:6 Hosting operator id = 55 Hosting Expression = ReusedSubquery Subquery scalar-subquery#31, [id=#32] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt new file mode 100644 index 000000000..38098d6a6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt @@ -0,0 +1,155 @@ +WholeStageCodegen (24) + HashAggregate [sum,isEmpty] [sum(sales),sum(sales),sum,isEmpty] + InputAdapter + Exchange #1 + WholeStageCodegen (23) + HashAggregate [sales] [sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (11) + Project [cs_quantity,cs_list_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_quantity,cs_list_price,cs_sold_date_sk] + SortMergeJoin [cs_bill_customer_sk,c_customer_sk] + InputAdapter + WholeStageCodegen (6) + Sort [cs_bill_customer_sk] + InputAdapter + Exchange [cs_bill_customer_sk] #2 + WholeStageCodegen (5) + Project [cs_bill_customer_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + BroadcastHashJoin [cs_item_sk,item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [item_sk] + Filter [cnt] + HashAggregate [_groupingexpression,i_item_sk,d_date,count] [count(1),item_sk,cnt,count] + InputAdapter + Exchange [_groupingexpression,i_item_sk,d_date] #5 + WholeStageCodegen (3) + HashAggregate [_groupingexpression,i_item_sk,d_date] [count,count] + Project [d_date,i_item_sk,i_item_desc] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #6 + WholeStageCodegen (1) + Project [d_date_sk,d_date] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_date] #6 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (2) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] + InputAdapter + WholeStageCodegen (9) + Sort [c_customer_sk] + Project [c_customer_sk] + Filter [ssales] + Subquery #3 + WholeStageCodegen (5) + HashAggregate [max] [max(csales),tpcds_cmax,max] + InputAdapter + Exchange #10 + WholeStageCodegen (4) + HashAggregate [csales] [max,max] + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),csales,sum,isEmpty] + InputAdapter + Exchange [c_customer_sk] #11 + WholeStageCodegen (3) + HashAggregate [c_customer_sk,ss_quantity,ss_sales_price] [sum,isEmpty,sum,isEmpty] + Project [ss_quantity,ss_sales_price,c_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_sales_price,ss_sold_date_sk,c_customer_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #4 + BroadcastExchange #12 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [c_customer_sk] #9 + InputAdapter + ReusedExchange [d_date_sk] #12 + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),ssales,sum,isEmpty] + InputAdapter + Exchange [c_customer_sk] #8 + WholeStageCodegen (8) + HashAggregate [c_customer_sk,ss_quantity,ss_sales_price] [sum,isEmpty,sum,isEmpty] + Project [ss_quantity,ss_sales_price,c_customer_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_quantity,ss_sales_price] + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (7) + Filter [c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk] + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (22) + Project [ws_quantity,ws_list_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_quantity,ws_list_price,ws_sold_date_sk] + SortMergeJoin [ws_bill_customer_sk,c_customer_sk] + InputAdapter + WholeStageCodegen (17) + Sort [ws_bill_customer_sk] + InputAdapter + Exchange [ws_bill_customer_sk] #13 + WholeStageCodegen (16) + Project [ws_bill_customer_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + BroadcastHashJoin [ws_item_sk,item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [item_sk] #4 + InputAdapter + WholeStageCodegen (20) + Sort [c_customer_sk] + Project [c_customer_sk] + Filter [ssales] + ReusedSubquery [tpcds_cmax] #3 + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),ssales,sum,isEmpty] + InputAdapter + ReusedExchange [c_customer_sk,sum,isEmpty] #8 + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt new file mode 100644 index 000000000..7ee05d453 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt @@ -0,0 +1,694 @@ +== Physical Plan == +TakeOrderedAndProject (87) ++- Union (86) + :- * HashAggregate (62) + : +- Exchange (61) + : +- * HashAggregate (60) + : +- * Project (59) + : +- * BroadcastHashJoin Inner BuildRight (58) + : :- * Project (56) + : : +- * BroadcastHashJoin Inner BuildRight (55) + : : :- * SortMergeJoin LeftSemi (42) + : : : :- * Sort (25) + : : : : +- Exchange (24) + : : : : +- * Project (23) + : : : : +- * BroadcastHashJoin LeftSemi BuildRight (22) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : +- BroadcastExchange (21) + : : : : +- * Project (20) + : : : : +- * Filter (19) + : : : : +- * HashAggregate (18) + : : : : +- Exchange (17) + : : : : +- * HashAggregate (16) + : : : : +- * Project (15) + : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : :- * Project (9) + : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : :- * Filter (6) + : : : : : : +- * ColumnarToRow (5) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : : +- ReusedExchange (7) + : : : : +- BroadcastExchange (13) + : : : : +- * Filter (12) + : : : : +- * ColumnarToRow (11) + : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : +- * Sort (41) + : : : +- * Project (40) + : : : +- * Filter (39) + : : : +- * HashAggregate (38) + : : : +- Exchange (37) + : : : +- * HashAggregate (36) + : : : +- * Project (35) + : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : :- * Project (29) + : : : : +- * Filter (28) + : : : : +- * ColumnarToRow (27) + : : : : +- CometScan parquet spark_catalog.default.store_sales (26) + : : : +- BroadcastExchange (33) + : : : +- * Filter (32) + : : : +- * ColumnarToRow (31) + : : : +- CometScan parquet spark_catalog.default.customer (30) + : : +- BroadcastExchange (54) + : : +- * SortMergeJoin LeftSemi (53) + : : :- * Sort (47) + : : : +- Exchange (46) + : : : +- * Filter (45) + : : : +- * ColumnarToRow (44) + : : : +- CometScan parquet spark_catalog.default.customer (43) + : : +- * Sort (52) + : : +- * Project (51) + : : +- * Filter (50) + : : +- * HashAggregate (49) + : : +- ReusedExchange (48) + : +- ReusedExchange (57) + +- * HashAggregate (85) + +- Exchange (84) + +- * HashAggregate (83) + +- * Project (82) + +- * BroadcastHashJoin Inner BuildRight (81) + :- * Project (79) + : +- * BroadcastHashJoin Inner BuildRight (78) + : :- * SortMergeJoin LeftSemi (76) + : : :- * Sort (70) + : : : +- Exchange (69) + : : : +- * Project (68) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (67) + : : : :- * Filter (65) + : : : : +- * ColumnarToRow (64) + : : : : +- CometScan parquet spark_catalog.default.web_sales (63) + : : : +- ReusedExchange (66) + : : +- * Sort (75) + : : +- * Project (74) + : : +- * Filter (73) + : : +- * HashAggregate (72) + : : +- ReusedExchange (71) + : +- ReusedExchange (77) + +- ReusedExchange (80) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] + +(3) Filter [codegen id : 5] +Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Condition : isnotnull(cs_bill_customer_sk#1) + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 3] +Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] + +(6) Filter [codegen id : 3] +Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] +Condition : isnotnull(ss_item_sk#7) + +(7) ReusedExchange [Reuses operator id: 97] +Output [2]: [d_date_sk#10, d_date#11] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [2]: [ss_item_sk#7, d_date#11] +Input [4]: [ss_item_sk#7, ss_sold_date_sk#8, d_date_sk#10, d_date#11] + +(10) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#12, i_item_desc#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [2]: [i_item_sk#12, i_item_desc#13] + +(12) Filter [codegen id : 2] +Input [2]: [i_item_sk#12, i_item_desc#13] +Condition : isnotnull(i_item_sk#12) + +(13) BroadcastExchange +Input [2]: [i_item_sk#12, i_item_desc#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(14) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#7] +Right keys [1]: [i_item_sk#12] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 3] +Output [3]: [d_date#11, i_item_sk#12, substr(i_item_desc#13, 1, 30) AS _groupingexpression#14] +Input [4]: [ss_item_sk#7, d_date#11, i_item_sk#12, i_item_desc#13] + +(16) HashAggregate [codegen id : 3] +Input [3]: [d_date#11, i_item_sk#12, _groupingexpression#14] +Keys [3]: [_groupingexpression#14, i_item_sk#12, d_date#11] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#15] +Results [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] + +(17) Exchange +Input [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] +Arguments: hashpartitioning(_groupingexpression#14, i_item_sk#12, d_date#11, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(18) HashAggregate [codegen id : 4] +Input [4]: [_groupingexpression#14, i_item_sk#12, d_date#11, count#16] +Keys [3]: [_groupingexpression#14, i_item_sk#12, d_date#11] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#17] +Results [2]: [i_item_sk#12 AS item_sk#18, count(1)#17 AS cnt#19] + +(19) Filter [codegen id : 4] +Input [2]: [item_sk#18, cnt#19] +Condition : (cnt#19 > 4) + +(20) Project [codegen id : 4] +Output [1]: [item_sk#18] +Input [2]: [item_sk#18, cnt#19] + +(21) BroadcastExchange +Input [1]: [item_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_item_sk#2] +Right keys [1]: [item_sk#18] +Join type: LeftSemi +Join condition: None + +(23) Project [codegen id : 5] +Output [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] + +(24) Exchange +Input [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Arguments: hashpartitioning(cs_bill_customer_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(25) Sort [codegen id : 6] +Input [4]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Arguments: [cs_bill_customer_sk#1 ASC NULLS FIRST], false, 0 + +(26) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(27) ColumnarToRow [codegen id : 8] +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] + +(28) Filter [codegen id : 8] +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Condition : isnotnull(ss_customer_sk#20) + +(29) Project [codegen id : 8] +Output [3]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] + +(30) Scan parquet spark_catalog.default.customer +Output [1]: [c_customer_sk#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 7] +Input [1]: [c_customer_sk#24] + +(32) Filter [codegen id : 7] +Input [1]: [c_customer_sk#24] +Condition : isnotnull(c_customer_sk#24) + +(33) BroadcastExchange +Input [1]: [c_customer_sk#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_customer_sk#20] +Right keys [1]: [c_customer_sk#24] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [3]: [ss_quantity#21, ss_sales_price#22, c_customer_sk#24] +Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, c_customer_sk#24] + +(36) HashAggregate [codegen id : 8] +Input [3]: [ss_quantity#21, ss_sales_price#22, c_customer_sk#24] +Keys [1]: [c_customer_sk#24] +Functions [1]: [partial_sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))] +Aggregate Attributes [2]: [sum#25, isEmpty#26] +Results [3]: [c_customer_sk#24, sum#27, isEmpty#28] + +(37) Exchange +Input [3]: [c_customer_sk#24, sum#27, isEmpty#28] +Arguments: hashpartitioning(c_customer_sk#24, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(38) HashAggregate [codegen id : 9] +Input [3]: [c_customer_sk#24, sum#27, isEmpty#28] +Keys [1]: [c_customer_sk#24] +Functions [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29] +Results [2]: [c_customer_sk#24, sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29 AS ssales#30] + +(39) Filter [codegen id : 9] +Input [2]: [c_customer_sk#24, ssales#30] +Condition : (isnotnull(ssales#30) AND (cast(ssales#30 as decimal(38,8)) > (0.500000 * Subquery scalar-subquery#31, [id=#32]))) + +(40) Project [codegen id : 9] +Output [1]: [c_customer_sk#24] +Input [2]: [c_customer_sk#24, ssales#30] + +(41) Sort [codegen id : 9] +Input [1]: [c_customer_sk#24] +Arguments: [c_customer_sk#24 ASC NULLS FIRST], false, 0 + +(42) SortMergeJoin [codegen id : 17] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#24] +Join type: LeftSemi +Join condition: None + +(43) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(44) ColumnarToRow [codegen id : 10] +Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] + +(45) Filter [codegen id : 10] +Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Condition : isnotnull(c_customer_sk#33) + +(46) Exchange +Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Arguments: hashpartitioning(c_customer_sk#33, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(47) Sort [codegen id : 11] +Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Arguments: [c_customer_sk#33 ASC NULLS FIRST], false, 0 + +(48) ReusedExchange [Reuses operator id: 37] +Output [3]: [c_customer_sk#24, sum#27, isEmpty#28] + +(49) HashAggregate [codegen id : 14] +Input [3]: [c_customer_sk#24, sum#27, isEmpty#28] +Keys [1]: [c_customer_sk#24] +Functions [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29] +Results [2]: [c_customer_sk#24, sum((cast(ss_quantity#21 as decimal(10,0)) * ss_sales_price#22))#29 AS ssales#30] + +(50) Filter [codegen id : 14] +Input [2]: [c_customer_sk#24, ssales#30] +Condition : (isnotnull(ssales#30) AND (cast(ssales#30 as decimal(38,8)) > (0.500000 * ReusedSubquery Subquery scalar-subquery#31, [id=#32]))) + +(51) Project [codegen id : 14] +Output [1]: [c_customer_sk#24] +Input [2]: [c_customer_sk#24, ssales#30] + +(52) Sort [codegen id : 14] +Input [1]: [c_customer_sk#24] +Arguments: [c_customer_sk#24 ASC NULLS FIRST], false, 0 + +(53) SortMergeJoin [codegen id : 15] +Left keys [1]: [c_customer_sk#33] +Right keys [1]: [c_customer_sk#24] +Join type: LeftSemi +Join condition: None + +(54) BroadcastExchange +Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(55) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#33] +Join type: Inner +Join condition: None + +(56) Project [codegen id : 17] +Output [5]: [cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5, c_first_name#34, c_last_name#35] +Input [7]: [cs_bill_customer_sk#1, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5, c_customer_sk#33, c_first_name#34, c_last_name#35] + +(57) ReusedExchange [Reuses operator id: 92] +Output [1]: [d_date_sk#36] + +(58) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [cs_sold_date_sk#5] +Right keys [1]: [d_date_sk#36] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 17] +Output [4]: [cs_quantity#3, cs_list_price#4, c_first_name#34, c_last_name#35] +Input [6]: [cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5, c_first_name#34, c_last_name#35, d_date_sk#36] + +(60) HashAggregate [codegen id : 17] +Input [4]: [cs_quantity#3, cs_list_price#4, c_first_name#34, c_last_name#35] +Keys [2]: [c_last_name#35, c_first_name#34] +Functions [1]: [partial_sum((cast(cs_quantity#3 as decimal(10,0)) * cs_list_price#4))] +Aggregate Attributes [2]: [sum#37, isEmpty#38] +Results [4]: [c_last_name#35, c_first_name#34, sum#39, isEmpty#40] + +(61) Exchange +Input [4]: [c_last_name#35, c_first_name#34, sum#39, isEmpty#40] +Arguments: hashpartitioning(c_last_name#35, c_first_name#34, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(62) HashAggregate [codegen id : 18] +Input [4]: [c_last_name#35, c_first_name#34, sum#39, isEmpty#40] +Keys [2]: [c_last_name#35, c_first_name#34] +Functions [1]: [sum((cast(cs_quantity#3 as decimal(10,0)) * cs_list_price#4))] +Aggregate Attributes [1]: [sum((cast(cs_quantity#3 as decimal(10,0)) * cs_list_price#4))#41] +Results [3]: [c_last_name#35, c_first_name#34, sum((cast(cs_quantity#3 as decimal(10,0)) * cs_list_price#4))#41 AS sales#42] + +(63) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#43, ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#47), dynamicpruningexpression(ws_sold_date_sk#47 IN dynamicpruning#48)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(64) ColumnarToRow [codegen id : 23] +Input [5]: [ws_item_sk#43, ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] + +(65) Filter [codegen id : 23] +Input [5]: [ws_item_sk#43, ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Condition : isnotnull(ws_bill_customer_sk#44) + +(66) ReusedExchange [Reuses operator id: 21] +Output [1]: [item_sk#49] + +(67) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [ws_item_sk#43] +Right keys [1]: [item_sk#49] +Join type: LeftSemi +Join condition: None + +(68) Project [codegen id : 23] +Output [4]: [ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Input [5]: [ws_item_sk#43, ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] + +(69) Exchange +Input [4]: [ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Arguments: hashpartitioning(ws_bill_customer_sk#44, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(70) Sort [codegen id : 24] +Input [4]: [ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Arguments: [ws_bill_customer_sk#44 ASC NULLS FIRST], false, 0 + +(71) ReusedExchange [Reuses operator id: 37] +Output [3]: [c_customer_sk#50, sum#51, isEmpty#52] + +(72) HashAggregate [codegen id : 27] +Input [3]: [c_customer_sk#50, sum#51, isEmpty#52] +Keys [1]: [c_customer_sk#50] +Functions [1]: [sum((cast(ss_quantity#53 as decimal(10,0)) * ss_sales_price#54))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#53 as decimal(10,0)) * ss_sales_price#54))#29] +Results [2]: [c_customer_sk#50, sum((cast(ss_quantity#53 as decimal(10,0)) * ss_sales_price#54))#29 AS ssales#55] + +(73) Filter [codegen id : 27] +Input [2]: [c_customer_sk#50, ssales#55] +Condition : (isnotnull(ssales#55) AND (cast(ssales#55 as decimal(38,8)) > (0.500000 * ReusedSubquery Subquery scalar-subquery#31, [id=#32]))) + +(74) Project [codegen id : 27] +Output [1]: [c_customer_sk#50] +Input [2]: [c_customer_sk#50, ssales#55] + +(75) Sort [codegen id : 27] +Input [1]: [c_customer_sk#50] +Arguments: [c_customer_sk#50 ASC NULLS FIRST], false, 0 + +(76) SortMergeJoin [codegen id : 35] +Left keys [1]: [ws_bill_customer_sk#44] +Right keys [1]: [c_customer_sk#50] +Join type: LeftSemi +Join condition: None + +(77) ReusedExchange [Reuses operator id: 54] +Output [3]: [c_customer_sk#56, c_first_name#57, c_last_name#58] + +(78) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ws_bill_customer_sk#44] +Right keys [1]: [c_customer_sk#56] +Join type: Inner +Join condition: None + +(79) Project [codegen id : 35] +Output [5]: [ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47, c_first_name#57, c_last_name#58] +Input [7]: [ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47, c_customer_sk#56, c_first_name#57, c_last_name#58] + +(80) ReusedExchange [Reuses operator id: 92] +Output [1]: [d_date_sk#59] + +(81) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ws_sold_date_sk#47] +Right keys [1]: [d_date_sk#59] +Join type: Inner +Join condition: None + +(82) Project [codegen id : 35] +Output [4]: [ws_quantity#45, ws_list_price#46, c_first_name#57, c_last_name#58] +Input [6]: [ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47, c_first_name#57, c_last_name#58, d_date_sk#59] + +(83) HashAggregate [codegen id : 35] +Input [4]: [ws_quantity#45, ws_list_price#46, c_first_name#57, c_last_name#58] +Keys [2]: [c_last_name#58, c_first_name#57] +Functions [1]: [partial_sum((cast(ws_quantity#45 as decimal(10,0)) * ws_list_price#46))] +Aggregate Attributes [2]: [sum#60, isEmpty#61] +Results [4]: [c_last_name#58, c_first_name#57, sum#62, isEmpty#63] + +(84) Exchange +Input [4]: [c_last_name#58, c_first_name#57, sum#62, isEmpty#63] +Arguments: hashpartitioning(c_last_name#58, c_first_name#57, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(85) HashAggregate [codegen id : 36] +Input [4]: [c_last_name#58, c_first_name#57, sum#62, isEmpty#63] +Keys [2]: [c_last_name#58, c_first_name#57] +Functions [1]: [sum((cast(ws_quantity#45 as decimal(10,0)) * ws_list_price#46))] +Aggregate Attributes [1]: [sum((cast(ws_quantity#45 as decimal(10,0)) * ws_list_price#46))#64] +Results [3]: [c_last_name#58, c_first_name#57, sum((cast(ws_quantity#45 as decimal(10,0)) * ws_list_price#46))#64 AS sales#65] + +(86) Union + +(87) TakeOrderedAndProject +Input [3]: [c_last_name#35, c_first_name#34, sales#42] +Arguments: 100, [c_last_name#35 ASC NULLS FIRST, c_first_name#34 ASC NULLS FIRST, sales#42 ASC NULLS FIRST], [c_last_name#35, c_first_name#34, sales#42] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (92) ++- * Project (91) + +- * Filter (90) + +- * ColumnarToRow (89) + +- CometScan parquet spark_catalog.default.date_dim (88) + + +(88) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#36, d_year#66, d_moy#67] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,2), IsNotNull(d_date_sk)] +ReadSchema: struct + +(89) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#36, d_year#66, d_moy#67] + +(90) Filter [codegen id : 1] +Input [3]: [d_date_sk#36, d_year#66, d_moy#67] +Condition : ((((isnotnull(d_year#66) AND isnotnull(d_moy#67)) AND (d_year#66 = 2000)) AND (d_moy#67 = 2)) AND isnotnull(d_date_sk#36)) + +(91) Project [codegen id : 1] +Output [1]: [d_date_sk#36] +Input [3]: [d_date_sk#36, d_year#66, d_moy#67] + +(92) BroadcastExchange +Input [1]: [d_date_sk#36] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (97) ++- * Project (96) + +- * Filter (95) + +- * ColumnarToRow (94) + +- CometScan parquet spark_catalog.default.date_dim (93) + + +(93) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_date#11, d_year#68] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(94) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#10, d_date#11, d_year#68] + +(95) Filter [codegen id : 1] +Input [3]: [d_date_sk#10, d_date#11, d_year#68] +Condition : (d_year#68 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#10)) + +(96) Project [codegen id : 1] +Output [2]: [d_date_sk#10, d_date#11] +Input [3]: [d_date_sk#10, d_date#11, d_year#68] + +(97) BroadcastExchange +Input [2]: [d_date_sk#10, d_date#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:3 Hosting operator id = 39 Hosting Expression = Subquery scalar-subquery#31, [id=#32] +* HashAggregate (112) ++- Exchange (111) + +- * HashAggregate (110) + +- * HashAggregate (109) + +- Exchange (108) + +- * HashAggregate (107) + +- * Project (106) + +- * BroadcastHashJoin Inner BuildRight (105) + :- * Project (103) + : +- * BroadcastHashJoin Inner BuildRight (102) + : :- * Filter (100) + : : +- * ColumnarToRow (99) + : : +- CometScan parquet spark_catalog.default.store_sales (98) + : +- ReusedExchange (101) + +- ReusedExchange (104) + + +(98) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#69, ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#72), dynamicpruningexpression(ss_sold_date_sk#72 IN dynamicpruning#73)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(99) ColumnarToRow [codegen id : 3] +Input [4]: [ss_customer_sk#69, ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72] + +(100) Filter [codegen id : 3] +Input [4]: [ss_customer_sk#69, ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72] +Condition : isnotnull(ss_customer_sk#69) + +(101) ReusedExchange [Reuses operator id: 33] +Output [1]: [c_customer_sk#74] + +(102) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_customer_sk#69] +Right keys [1]: [c_customer_sk#74] +Join type: Inner +Join condition: None + +(103) Project [codegen id : 3] +Output [4]: [ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72, c_customer_sk#74] +Input [5]: [ss_customer_sk#69, ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72, c_customer_sk#74] + +(104) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#75] + +(105) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#72] +Right keys [1]: [d_date_sk#75] +Join type: Inner +Join condition: None + +(106) Project [codegen id : 3] +Output [3]: [ss_quantity#70, ss_sales_price#71, c_customer_sk#74] +Input [5]: [ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72, c_customer_sk#74, d_date_sk#75] + +(107) HashAggregate [codegen id : 3] +Input [3]: [ss_quantity#70, ss_sales_price#71, c_customer_sk#74] +Keys [1]: [c_customer_sk#74] +Functions [1]: [partial_sum((cast(ss_quantity#70 as decimal(10,0)) * ss_sales_price#71))] +Aggregate Attributes [2]: [sum#76, isEmpty#77] +Results [3]: [c_customer_sk#74, sum#78, isEmpty#79] + +(108) Exchange +Input [3]: [c_customer_sk#74, sum#78, isEmpty#79] +Arguments: hashpartitioning(c_customer_sk#74, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(109) HashAggregate [codegen id : 4] +Input [3]: [c_customer_sk#74, sum#78, isEmpty#79] +Keys [1]: [c_customer_sk#74] +Functions [1]: [sum((cast(ss_quantity#70 as decimal(10,0)) * ss_sales_price#71))] +Aggregate Attributes [1]: [sum((cast(ss_quantity#70 as decimal(10,0)) * ss_sales_price#71))#80] +Results [1]: [sum((cast(ss_quantity#70 as decimal(10,0)) * ss_sales_price#71))#80 AS csales#81] + +(110) HashAggregate [codegen id : 4] +Input [1]: [csales#81] +Keys: [] +Functions [1]: [partial_max(csales#81)] +Aggregate Attributes [1]: [max#82] +Results [1]: [max#83] + +(111) Exchange +Input [1]: [max#83] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=15] + +(112) HashAggregate [codegen id : 5] +Input [1]: [max#83] +Keys: [] +Functions [1]: [max(csales#81)] +Aggregate Attributes [1]: [max(csales#81)#84] +Results [1]: [max(csales#81)#84 AS tpcds_cmax#85] + +Subquery:4 Hosting operator id = 98 Hosting Expression = ss_sold_date_sk#72 IN dynamicpruning#73 +BroadcastExchange (117) ++- * Project (116) + +- * Filter (115) + +- * ColumnarToRow (114) + +- CometScan parquet spark_catalog.default.date_dim (113) + + +(113) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#75, d_year#86] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(114) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#75, d_year#86] + +(115) Filter [codegen id : 1] +Input [2]: [d_date_sk#75, d_year#86] +Condition : (d_year#86 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#75)) + +(116) Project [codegen id : 1] +Output [1]: [d_date_sk#75] +Input [2]: [d_date_sk#75, d_year#86] + +(117) BroadcastExchange +Input [1]: [d_date_sk#75] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=16] + +Subquery:5 Hosting operator id = 50 Hosting Expression = ReusedSubquery Subquery scalar-subquery#31, [id=#32] + +Subquery:6 Hosting operator id = 63 Hosting Expression = ws_sold_date_sk#47 IN dynamicpruning#6 + +Subquery:7 Hosting operator id = 73 Hosting Expression = ReusedSubquery Subquery scalar-subquery#31, [id=#32] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt new file mode 100644 index 000000000..cfb8acd14 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt @@ -0,0 +1,188 @@ +TakeOrderedAndProject [c_last_name,c_first_name,sales] + Union + WholeStageCodegen (18) + HashAggregate [c_last_name,c_first_name,sum,isEmpty] [sum((cast(cs_quantity as decimal(10,0)) * cs_list_price)),sales,sum,isEmpty] + InputAdapter + Exchange [c_last_name,c_first_name] #1 + WholeStageCodegen (17) + HashAggregate [c_last_name,c_first_name,cs_quantity,cs_list_price] [sum,isEmpty,sum,isEmpty] + Project [cs_quantity,cs_list_price,c_first_name,c_last_name] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_quantity,cs_list_price,cs_sold_date_sk,c_first_name,c_last_name] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + SortMergeJoin [cs_bill_customer_sk,c_customer_sk] + InputAdapter + WholeStageCodegen (6) + Sort [cs_bill_customer_sk] + InputAdapter + Exchange [cs_bill_customer_sk] #2 + WholeStageCodegen (5) + Project [cs_bill_customer_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + BroadcastHashJoin [cs_item_sk,item_sk] + Filter [cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [item_sk] + Filter [cnt] + HashAggregate [_groupingexpression,i_item_sk,d_date,count] [count(1),item_sk,cnt,count] + InputAdapter + Exchange [_groupingexpression,i_item_sk,d_date] #5 + WholeStageCodegen (3) + HashAggregate [_groupingexpression,i_item_sk,d_date] [count,count] + Project [d_date,i_item_sk,i_item_desc] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #6 + WholeStageCodegen (1) + Project [d_date_sk,d_date] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_date] #6 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (2) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] + InputAdapter + WholeStageCodegen (9) + Sort [c_customer_sk] + Project [c_customer_sk] + Filter [ssales] + Subquery #3 + WholeStageCodegen (5) + HashAggregate [max] [max(csales),tpcds_cmax,max] + InputAdapter + Exchange #10 + WholeStageCodegen (4) + HashAggregate [csales] [max,max] + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),csales,sum,isEmpty] + InputAdapter + Exchange [c_customer_sk] #11 + WholeStageCodegen (3) + HashAggregate [c_customer_sk,ss_quantity,ss_sales_price] [sum,isEmpty,sum,isEmpty] + Project [ss_quantity,ss_sales_price,c_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_sales_price,ss_sold_date_sk,c_customer_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #4 + BroadcastExchange #12 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [c_customer_sk] #9 + InputAdapter + ReusedExchange [d_date_sk] #12 + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),ssales,sum,isEmpty] + InputAdapter + Exchange [c_customer_sk] #8 + WholeStageCodegen (8) + HashAggregate [c_customer_sk,ss_quantity,ss_sales_price] [sum,isEmpty,sum,isEmpty] + Project [ss_quantity,ss_sales_price,c_customer_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_quantity,ss_sales_price] + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (7) + Filter [c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (15) + SortMergeJoin [c_customer_sk,c_customer_sk] + InputAdapter + WholeStageCodegen (11) + Sort [c_customer_sk] + InputAdapter + Exchange [c_customer_sk] #14 + WholeStageCodegen (10) + Filter [c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] + InputAdapter + WholeStageCodegen (14) + Sort [c_customer_sk] + Project [c_customer_sk] + Filter [ssales] + ReusedSubquery [tpcds_cmax] #3 + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),ssales,sum,isEmpty] + InputAdapter + ReusedExchange [c_customer_sk,sum,isEmpty] #8 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (36) + HashAggregate [c_last_name,c_first_name,sum,isEmpty] [sum((cast(ws_quantity as decimal(10,0)) * ws_list_price)),sales,sum,isEmpty] + InputAdapter + Exchange [c_last_name,c_first_name] #15 + WholeStageCodegen (35) + HashAggregate [c_last_name,c_first_name,ws_quantity,ws_list_price] [sum,isEmpty,sum,isEmpty] + Project [ws_quantity,ws_list_price,c_first_name,c_last_name] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_quantity,ws_list_price,ws_sold_date_sk,c_first_name,c_last_name] + BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] + SortMergeJoin [ws_bill_customer_sk,c_customer_sk] + InputAdapter + WholeStageCodegen (24) + Sort [ws_bill_customer_sk] + InputAdapter + Exchange [ws_bill_customer_sk] #16 + WholeStageCodegen (23) + Project [ws_bill_customer_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + BroadcastHashJoin [ws_item_sk,item_sk] + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [item_sk] #4 + InputAdapter + WholeStageCodegen (27) + Sort [c_customer_sk] + Project [c_customer_sk] + Filter [ssales] + ReusedSubquery [tpcds_cmax] #3 + HashAggregate [c_customer_sk,sum,isEmpty] [sum((cast(ss_quantity as decimal(10,0)) * ss_sales_price)),ssales,sum,isEmpty] + InputAdapter + ReusedExchange [c_customer_sk,sum,isEmpty] #8 + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name] #13 + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt new file mode 100644 index 000000000..b27379f24 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt @@ -0,0 +1,427 @@ +== Physical Plan == +* Filter (46) ++- * HashAggregate (45) + +- Exchange (44) + +- * HashAggregate (43) + +- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (27) + : : +- * BroadcastHashJoin Inner BuildRight (26) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (14) + : : : : +- * SortMergeJoin Inner (13) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * Project (4) + : : : : : +- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- * Sort (12) + : : : : +- Exchange (11) + : : : : +- * Project (10) + : : : : +- * Filter (9) + : : : : +- * ColumnarToRow (8) + : : : : +- CometScan parquet spark_catalog.default.store_returns (7) + : : : +- BroadcastExchange (19) + : : : +- * Project (18) + : : : +- * Filter (17) + : : : +- * ColumnarToRow (16) + : : : +- CometScan parquet spark_catalog.default.store (15) + : : +- BroadcastExchange (25) + : : +- * Filter (24) + : : +- * ColumnarToRow (23) + : : +- CometScan parquet spark_catalog.default.item (22) + : +- BroadcastExchange (31) + : +- * Filter (30) + : +- * ColumnarToRow (29) + : +- CometScan parquet spark_catalog.default.customer (28) + +- BroadcastExchange (37) + +- * Filter (36) + +- * ColumnarToRow (35) + +- CometScan parquet spark_catalog.default.customer_address (34) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] + +(3) Filter [codegen id : 1] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_customer_sk#2)) + +(4) Project [codegen id : 1] +Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] + +(5) Exchange +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: hashpartitioning(ss_ticket_number#4, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: [ss_ticket_number#4 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 3] +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] + +(9) Filter [codegen id : 3] +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Condition : (isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#7)) + +(10) Project [codegen id : 3] +Output [2]: [sr_item_sk#7, sr_ticket_number#8] +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] + +(11) Exchange +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: hashpartitioning(sr_ticket_number#8, sr_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 4] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: [sr_ticket_number#8 ASC NULLS FIRST, sr_item_sk#7 ASC NULLS FIRST], false, 0 + +(13) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#4, ss_item_sk#1] +Right keys [2]: [sr_ticket_number#8, sr_item_sk#7] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 9] +Output [4]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, sr_item_sk#7, sr_ticket_number#8] + +(15) Scan parquet spark_catalog.default.store +Output [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_market_id), EqualTo(s_market_id,8), IsNotNull(s_store_sk), IsNotNull(s_zip)] +ReadSchema: struct + +(16) ColumnarToRow [codegen id : 5] +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] + +(17) Filter [codegen id : 5] +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Condition : (((isnotnull(s_market_id#12) AND (s_market_id#12 = 8)) AND isnotnull(s_store_sk#10)) AND isnotnull(s_zip#14)) + +(18) Project [codegen id : 5] +Output [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] + +(19) BroadcastExchange +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#10] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 9] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14] +Input [8]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5, s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(22) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_color), EqualTo(i_color,pale ), IsNotNull(i_item_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(24) Filter [codegen id : 6] +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Condition : ((isnotnull(i_color#18) AND (i_color#18 = pale )) AND isnotnull(i_item_sk#15)) + +(25) BroadcastExchange +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(26) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#15] +Join type: Inner +Join condition: None + +(27) Project [codegen id : 9] +Output [10]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(28) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_birth_country)] +ReadSchema: struct + +(29) ColumnarToRow [codegen id : 7] +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] + +(30) Filter [codegen id : 7] +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_birth_country#24)) + +(31) BroadcastExchange +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#21] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [12]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, c_birth_country#24] +Input [14]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] + +(34) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_state#25, ca_zip#26, ca_country#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_country), IsNotNull(ca_zip)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 8] +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] + +(36) Filter [codegen id : 8] +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] +Condition : (isnotnull(ca_country#27) AND isnotnull(ca_zip#26)) + +(37) BroadcastExchange +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] +Arguments: HashedRelationBroadcastMode(List(upper(input[2, string, false]), input[1, string, false]),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [2]: [c_birth_country#24, s_zip#14] +Right keys [2]: [upper(ca_country#27), ca_zip#26] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, ca_state#25] +Input [15]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, c_birth_country#24, ca_state#25, ca_zip#26, ca_country#27] + +(40) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, ca_state#25] +Keys [10]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum#28] +Results [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] + +(41) Exchange +Input [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] +Arguments: hashpartitioning(c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(42) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] +Keys [10]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#5))#30] +Results [4]: [c_last_name#23, c_first_name#22, s_store_name#11, MakeDecimal(sum(UnscaledValue(ss_net_paid#5))#30,17,2) AS netpaid#31] + +(43) HashAggregate [codegen id : 10] +Input [4]: [c_last_name#23, c_first_name#22, s_store_name#11, netpaid#31] +Keys [3]: [c_last_name#23, c_first_name#22, s_store_name#11] +Functions [1]: [partial_sum(netpaid#31)] +Aggregate Attributes [2]: [sum#32, isEmpty#33] +Results [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] + +(44) Exchange +Input [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] +Arguments: hashpartitioning(c_last_name#23, c_first_name#22, s_store_name#11, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(45) HashAggregate [codegen id : 11] +Input [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] +Keys [3]: [c_last_name#23, c_first_name#22, s_store_name#11] +Functions [1]: [sum(netpaid#31)] +Aggregate Attributes [1]: [sum(netpaid#31)#36] +Results [4]: [c_last_name#23, c_first_name#22, s_store_name#11, sum(netpaid#31)#36 AS paid#37] + +(46) Filter [codegen id : 11] +Input [4]: [c_last_name#23, c_first_name#22, s_store_name#11, paid#37] +Condition : (isnotnull(paid#37) AND (cast(paid#37 as decimal(33,8)) > cast(Subquery scalar-subquery#38, [id=#39] as decimal(33,8)))) + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 46 Hosting Expression = Subquery scalar-subquery#38, [id=#39] +* HashAggregate (73) ++- Exchange (72) + +- * HashAggregate (71) + +- * HashAggregate (70) + +- Exchange (69) + +- * HashAggregate (68) + +- * Project (67) + +- * BroadcastHashJoin Inner BuildRight (66) + :- * Project (64) + : +- * BroadcastHashJoin Inner BuildRight (63) + : :- * Project (61) + : : +- * BroadcastHashJoin Inner BuildRight (60) + : : :- * Project (55) + : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : :- * Project (52) + : : : : +- * SortMergeJoin Inner (51) + : : : : :- * Sort (48) + : : : : : +- ReusedExchange (47) + : : : : +- * Sort (50) + : : : : +- ReusedExchange (49) + : : : +- ReusedExchange (53) + : : +- BroadcastExchange (59) + : : +- * Filter (58) + : : +- * ColumnarToRow (57) + : : +- CometScan parquet spark_catalog.default.item (56) + : +- ReusedExchange (62) + +- ReusedExchange (65) + + +(47) ReusedExchange [Reuses operator id: 5] +Output [5]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44] + +(48) Sort [codegen id : 2] +Input [5]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44] +Arguments: [ss_ticket_number#43 ASC NULLS FIRST, ss_item_sk#40 ASC NULLS FIRST], false, 0 + +(49) ReusedExchange [Reuses operator id: 11] +Output [2]: [sr_item_sk#45, sr_ticket_number#46] + +(50) Sort [codegen id : 4] +Input [2]: [sr_item_sk#45, sr_ticket_number#46] +Arguments: [sr_ticket_number#46 ASC NULLS FIRST, sr_item_sk#45 ASC NULLS FIRST], false, 0 + +(51) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#43, ss_item_sk#40] +Right keys [2]: [sr_ticket_number#46, sr_item_sk#45] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 9] +Output [4]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_net_paid#44] +Input [7]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44, sr_item_sk#45, sr_ticket_number#46] + +(53) ReusedExchange [Reuses operator id: 19] +Output [4]: [s_store_sk#47, s_store_name#48, s_state#49, s_zip#50] + +(54) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#42] +Right keys [1]: [s_store_sk#47] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 9] +Output [6]: [ss_item_sk#40, ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50] +Input [8]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_net_paid#44, s_store_sk#47, s_store_name#48, s_state#49, s_zip#50] + +(56) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(57) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] + +(58) Filter [codegen id : 6] +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Condition : isnotnull(i_item_sk#51) + +(59) BroadcastExchange +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#40] +Right keys [1]: [i_item_sk#51] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 9] +Output [10]: [ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Input [12]: [ss_item_sk#40, ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] + +(62) ReusedExchange [Reuses operator id: 31] +Output [4]: [c_customer_sk#57, c_first_name#58, c_last_name#59, c_birth_country#60] + +(63) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#41] +Right keys [1]: [c_customer_sk#57] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 9] +Output [12]: [ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, c_birth_country#60] +Input [14]: [ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_customer_sk#57, c_first_name#58, c_last_name#59, c_birth_country#60] + +(65) ReusedExchange [Reuses operator id: 37] +Output [3]: [ca_state#61, ca_zip#62, ca_country#63] + +(66) BroadcastHashJoin [codegen id : 9] +Left keys [2]: [c_birth_country#60, s_zip#50] +Right keys [2]: [upper(ca_country#63), ca_zip#62] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 9] +Output [11]: [ss_net_paid#44, s_store_name#48, s_state#49, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, ca_state#61] +Input [15]: [ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, c_birth_country#60, ca_state#61, ca_zip#62, ca_country#63] + +(68) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#44, s_store_name#48, s_state#49, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, ca_state#61] +Keys [10]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#44))] +Aggregate Attributes [1]: [sum#64] +Results [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] + +(69) Exchange +Input [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] +Arguments: hashpartitioning(c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(70) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] +Keys [10]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53] +Functions [1]: [sum(UnscaledValue(ss_net_paid#44))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#44))#30] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_net_paid#44))#30,17,2) AS netpaid#66] + +(71) HashAggregate [codegen id : 10] +Input [1]: [netpaid#66] +Keys: [] +Functions [1]: [partial_avg(netpaid#66)] +Aggregate Attributes [2]: [sum#67, count#68] +Results [2]: [sum#69, count#70] + +(72) Exchange +Input [2]: [sum#69, count#70] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=11] + +(73) HashAggregate [codegen id : 11] +Input [2]: [sum#69, count#70] +Keys: [] +Functions [1]: [avg(netpaid#66)] +Aggregate Attributes [1]: [avg(netpaid#66)#71] +Results [1]: [(0.05 * avg(netpaid#66)#71) AS (0.05 * avg(netpaid))#72] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt new file mode 100644 index 000000000..4cdde1b6f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt @@ -0,0 +1,118 @@ +WholeStageCodegen (11) + Filter [paid] + Subquery #1 + WholeStageCodegen (11) + HashAggregate [sum,count] [avg(netpaid),(0.05 * avg(netpaid)),sum,count] + InputAdapter + Exchange #9 + WholeStageCodegen (10) + HashAggregate [netpaid] [sum,count,sum,count] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #10 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_birth_country,s_zip,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + ReusedExchange [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] #3 + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + ReusedExchange [sr_item_sk,sr_ticket_number] #4 + InputAdapter + ReusedExchange [s_store_sk,s_store_name,s_state,s_zip] #5 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (6) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name,c_birth_country] #7 + InputAdapter + ReusedExchange [ca_state,ca_zip,ca_country] #8 + HashAggregate [c_last_name,c_first_name,s_store_name,sum,isEmpty] [sum(netpaid),paid,sum,isEmpty] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name] #1 + WholeStageCodegen (10) + HashAggregate [c_last_name,c_first_name,s_store_name,netpaid] [sum,isEmpty,sum,isEmpty] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #2 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_birth_country,s_zip,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #3 + WholeStageCodegen (1) + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] + Filter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid,ss_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #4 + WholeStageCodegen (3) + Project [sr_item_sk,sr_ticket_number] + Filter [sr_ticket_number,sr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (5) + Project [s_store_sk,s_store_name,s_state,s_zip] + Filter [s_market_id,s_store_sk,s_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_market_id,s_state,s_zip] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Filter [i_color,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + Filter [c_customer_sk,c_birth_country] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name,c_birth_country] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (8) + Filter [ca_country,ca_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_state,ca_zip,ca_country] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt new file mode 100644 index 000000000..a198578da --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt @@ -0,0 +1,427 @@ +== Physical Plan == +* Filter (46) ++- * HashAggregate (45) + +- Exchange (44) + +- * HashAggregate (43) + +- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (27) + : : +- * BroadcastHashJoin Inner BuildRight (26) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (14) + : : : : +- * SortMergeJoin Inner (13) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * Project (4) + : : : : : +- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- * Sort (12) + : : : : +- Exchange (11) + : : : : +- * Project (10) + : : : : +- * Filter (9) + : : : : +- * ColumnarToRow (8) + : : : : +- CometScan parquet spark_catalog.default.store_returns (7) + : : : +- BroadcastExchange (19) + : : : +- * Project (18) + : : : +- * Filter (17) + : : : +- * ColumnarToRow (16) + : : : +- CometScan parquet spark_catalog.default.store (15) + : : +- BroadcastExchange (25) + : : +- * Filter (24) + : : +- * ColumnarToRow (23) + : : +- CometScan parquet spark_catalog.default.item (22) + : +- BroadcastExchange (31) + : +- * Filter (30) + : +- * ColumnarToRow (29) + : +- CometScan parquet spark_catalog.default.customer (28) + +- BroadcastExchange (37) + +- * Filter (36) + +- * ColumnarToRow (35) + +- CometScan parquet spark_catalog.default.customer_address (34) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] + +(3) Filter [codegen id : 1] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_customer_sk#2)) + +(4) Project [codegen id : 1] +Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] + +(5) Exchange +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: hashpartitioning(ss_ticket_number#4, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: [ss_ticket_number#4 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 3] +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] + +(9) Filter [codegen id : 3] +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Condition : (isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#7)) + +(10) Project [codegen id : 3] +Output [2]: [sr_item_sk#7, sr_ticket_number#8] +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] + +(11) Exchange +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: hashpartitioning(sr_ticket_number#8, sr_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 4] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: [sr_ticket_number#8 ASC NULLS FIRST, sr_item_sk#7 ASC NULLS FIRST], false, 0 + +(13) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#4, ss_item_sk#1] +Right keys [2]: [sr_ticket_number#8, sr_item_sk#7] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 9] +Output [4]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, sr_item_sk#7, sr_ticket_number#8] + +(15) Scan parquet spark_catalog.default.store +Output [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_market_id), EqualTo(s_market_id,8), IsNotNull(s_store_sk), IsNotNull(s_zip)] +ReadSchema: struct + +(16) ColumnarToRow [codegen id : 5] +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] + +(17) Filter [codegen id : 5] +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Condition : (((isnotnull(s_market_id#12) AND (s_market_id#12 = 8)) AND isnotnull(s_store_sk#10)) AND isnotnull(s_zip#14)) + +(18) Project [codegen id : 5] +Output [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] + +(19) BroadcastExchange +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#10] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 9] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14] +Input [8]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5, s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(22) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_color), EqualTo(i_color,chiffon ), IsNotNull(i_item_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(24) Filter [codegen id : 6] +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Condition : ((isnotnull(i_color#18) AND (i_color#18 = chiffon )) AND isnotnull(i_item_sk#15)) + +(25) BroadcastExchange +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(26) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#15] +Join type: Inner +Join condition: None + +(27) Project [codegen id : 9] +Output [10]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(28) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_birth_country)] +ReadSchema: struct + +(29) ColumnarToRow [codegen id : 7] +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] + +(30) Filter [codegen id : 7] +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_birth_country#24)) + +(31) BroadcastExchange +Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#21] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [12]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, c_birth_country#24] +Input [14]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] + +(34) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_state#25, ca_zip#26, ca_country#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_country), IsNotNull(ca_zip)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 8] +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] + +(36) Filter [codegen id : 8] +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] +Condition : (isnotnull(ca_country#27) AND isnotnull(ca_zip#26)) + +(37) BroadcastExchange +Input [3]: [ca_state#25, ca_zip#26, ca_country#27] +Arguments: HashedRelationBroadcastMode(List(upper(input[2, string, false]), input[1, string, false]),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [2]: [c_birth_country#24, s_zip#14] +Right keys [2]: [upper(ca_country#27), ca_zip#26] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, ca_state#25] +Input [15]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, c_birth_country#24, ca_state#25, ca_zip#26, ca_country#27] + +(40) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#22, c_last_name#23, ca_state#25] +Keys [10]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum#28] +Results [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] + +(41) Exchange +Input [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] +Arguments: hashpartitioning(c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(42) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#29] +Keys [10]: [c_last_name#23, c_first_name#22, s_store_name#11, ca_state#25, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#5))#30] +Results [4]: [c_last_name#23, c_first_name#22, s_store_name#11, MakeDecimal(sum(UnscaledValue(ss_net_paid#5))#30,17,2) AS netpaid#31] + +(43) HashAggregate [codegen id : 10] +Input [4]: [c_last_name#23, c_first_name#22, s_store_name#11, netpaid#31] +Keys [3]: [c_last_name#23, c_first_name#22, s_store_name#11] +Functions [1]: [partial_sum(netpaid#31)] +Aggregate Attributes [2]: [sum#32, isEmpty#33] +Results [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] + +(44) Exchange +Input [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] +Arguments: hashpartitioning(c_last_name#23, c_first_name#22, s_store_name#11, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(45) HashAggregate [codegen id : 11] +Input [5]: [c_last_name#23, c_first_name#22, s_store_name#11, sum#34, isEmpty#35] +Keys [3]: [c_last_name#23, c_first_name#22, s_store_name#11] +Functions [1]: [sum(netpaid#31)] +Aggregate Attributes [1]: [sum(netpaid#31)#36] +Results [4]: [c_last_name#23, c_first_name#22, s_store_name#11, sum(netpaid#31)#36 AS paid#37] + +(46) Filter [codegen id : 11] +Input [4]: [c_last_name#23, c_first_name#22, s_store_name#11, paid#37] +Condition : (isnotnull(paid#37) AND (cast(paid#37 as decimal(33,8)) > cast(Subquery scalar-subquery#38, [id=#39] as decimal(33,8)))) + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 46 Hosting Expression = Subquery scalar-subquery#38, [id=#39] +* HashAggregate (73) ++- Exchange (72) + +- * HashAggregate (71) + +- * HashAggregate (70) + +- Exchange (69) + +- * HashAggregate (68) + +- * Project (67) + +- * BroadcastHashJoin Inner BuildRight (66) + :- * Project (64) + : +- * BroadcastHashJoin Inner BuildRight (63) + : :- * Project (61) + : : +- * BroadcastHashJoin Inner BuildRight (60) + : : :- * Project (55) + : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : :- * Project (52) + : : : : +- * SortMergeJoin Inner (51) + : : : : :- * Sort (48) + : : : : : +- ReusedExchange (47) + : : : : +- * Sort (50) + : : : : +- ReusedExchange (49) + : : : +- ReusedExchange (53) + : : +- BroadcastExchange (59) + : : +- * Filter (58) + : : +- * ColumnarToRow (57) + : : +- CometScan parquet spark_catalog.default.item (56) + : +- ReusedExchange (62) + +- ReusedExchange (65) + + +(47) ReusedExchange [Reuses operator id: 5] +Output [5]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44] + +(48) Sort [codegen id : 2] +Input [5]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44] +Arguments: [ss_ticket_number#43 ASC NULLS FIRST, ss_item_sk#40 ASC NULLS FIRST], false, 0 + +(49) ReusedExchange [Reuses operator id: 11] +Output [2]: [sr_item_sk#45, sr_ticket_number#46] + +(50) Sort [codegen id : 4] +Input [2]: [sr_item_sk#45, sr_ticket_number#46] +Arguments: [sr_ticket_number#46 ASC NULLS FIRST, sr_item_sk#45 ASC NULLS FIRST], false, 0 + +(51) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#43, ss_item_sk#40] +Right keys [2]: [sr_ticket_number#46, sr_item_sk#45] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 9] +Output [4]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_net_paid#44] +Input [7]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_ticket_number#43, ss_net_paid#44, sr_item_sk#45, sr_ticket_number#46] + +(53) ReusedExchange [Reuses operator id: 19] +Output [4]: [s_store_sk#47, s_store_name#48, s_state#49, s_zip#50] + +(54) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#42] +Right keys [1]: [s_store_sk#47] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 9] +Output [6]: [ss_item_sk#40, ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50] +Input [8]: [ss_item_sk#40, ss_customer_sk#41, ss_store_sk#42, ss_net_paid#44, s_store_sk#47, s_store_name#48, s_state#49, s_zip#50] + +(56) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(57) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] + +(58) Filter [codegen id : 6] +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Condition : isnotnull(i_item_sk#51) + +(59) BroadcastExchange +Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#40] +Right keys [1]: [i_item_sk#51] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 9] +Output [10]: [ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Input [12]: [ss_item_sk#40, ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] + +(62) ReusedExchange [Reuses operator id: 31] +Output [4]: [c_customer_sk#57, c_first_name#58, c_last_name#59, c_birth_country#60] + +(63) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#41] +Right keys [1]: [c_customer_sk#57] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 9] +Output [12]: [ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, c_birth_country#60] +Input [14]: [ss_customer_sk#41, ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_customer_sk#57, c_first_name#58, c_last_name#59, c_birth_country#60] + +(65) ReusedExchange [Reuses operator id: 37] +Output [3]: [ca_state#61, ca_zip#62, ca_country#63] + +(66) BroadcastHashJoin [codegen id : 9] +Left keys [2]: [c_birth_country#60, s_zip#50] +Right keys [2]: [upper(ca_country#63), ca_zip#62] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 9] +Output [11]: [ss_net_paid#44, s_store_name#48, s_state#49, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, ca_state#61] +Input [15]: [ss_net_paid#44, s_store_name#48, s_state#49, s_zip#50, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, c_birth_country#60, ca_state#61, ca_zip#62, ca_country#63] + +(68) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#44, s_store_name#48, s_state#49, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56, c_first_name#58, c_last_name#59, ca_state#61] +Keys [10]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#44))] +Aggregate Attributes [1]: [sum#64] +Results [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] + +(69) Exchange +Input [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] +Arguments: hashpartitioning(c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(70) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53, sum#65] +Keys [10]: [c_last_name#59, c_first_name#58, s_store_name#48, ca_state#61, s_state#49, i_color#54, i_current_price#52, i_manager_id#56, i_units#55, i_size#53] +Functions [1]: [sum(UnscaledValue(ss_net_paid#44))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#44))#30] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_net_paid#44))#30,17,2) AS netpaid#66] + +(71) HashAggregate [codegen id : 10] +Input [1]: [netpaid#66] +Keys: [] +Functions [1]: [partial_avg(netpaid#66)] +Aggregate Attributes [2]: [sum#67, count#68] +Results [2]: [sum#69, count#70] + +(72) Exchange +Input [2]: [sum#69, count#70] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=11] + +(73) HashAggregate [codegen id : 11] +Input [2]: [sum#69, count#70] +Keys: [] +Functions [1]: [avg(netpaid#66)] +Aggregate Attributes [1]: [avg(netpaid#66)#71] +Results [1]: [(0.05 * avg(netpaid#66)#71) AS (0.05 * avg(netpaid))#72] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt new file mode 100644 index 000000000..4cdde1b6f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt @@ -0,0 +1,118 @@ +WholeStageCodegen (11) + Filter [paid] + Subquery #1 + WholeStageCodegen (11) + HashAggregate [sum,count] [avg(netpaid),(0.05 * avg(netpaid)),sum,count] + InputAdapter + Exchange #9 + WholeStageCodegen (10) + HashAggregate [netpaid] [sum,count,sum,count] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #10 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_birth_country,s_zip,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + ReusedExchange [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] #3 + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + ReusedExchange [sr_item_sk,sr_ticket_number] #4 + InputAdapter + ReusedExchange [s_store_sk,s_store_name,s_state,s_zip] #5 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (6) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name,c_birth_country] #7 + InputAdapter + ReusedExchange [ca_state,ca_zip,ca_country] #8 + HashAggregate [c_last_name,c_first_name,s_store_name,sum,isEmpty] [sum(netpaid),paid,sum,isEmpty] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name] #1 + WholeStageCodegen (10) + HashAggregate [c_last_name,c_first_name,s_store_name,netpaid] [sum,isEmpty,sum,isEmpty] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #2 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_birth_country,s_zip,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #3 + WholeStageCodegen (1) + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] + Filter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid,ss_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #4 + WholeStageCodegen (3) + Project [sr_item_sk,sr_ticket_number] + Filter [sr_ticket_number,sr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (5) + Project [s_store_sk,s_store_name,s_state,s_zip] + Filter [s_market_id,s_store_sk,s_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_market_id,s_state,s_zip] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Filter [i_color,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + Filter [c_customer_sk,c_birth_country] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name,c_birth_country] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (8) + Filter [ca_country,ca_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_state,ca_zip,ca_country] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt new file mode 100644 index 000000000..f2e9a4eaf --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt @@ -0,0 +1,298 @@ +== Physical Plan == +TakeOrderedAndProject (40) ++- * HashAggregate (39) + +- Exchange (38) + +- * HashAggregate (37) + +- * Project (36) + +- * BroadcastHashJoin Inner BuildRight (35) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * Project (24) + : : +- * BroadcastHashJoin Inner BuildRight (23) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (18) + : : : : +- * BroadcastHashJoin Inner BuildRight (17) + : : : : :- * Project (15) + : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : :- * Project (9) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : :- * Filter (3) + : : : : : : : +- * ColumnarToRow (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- BroadcastExchange (7) + : : : : : : +- * Filter (6) + : : : : : : +- * ColumnarToRow (5) + : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : : : +- BroadcastExchange (13) + : : : : : +- * Filter (12) + : : : : : +- * ColumnarToRow (11) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (10) + : : : : +- ReusedExchange (16) + : : : +- ReusedExchange (19) + : : +- ReusedExchange (22) + : +- BroadcastExchange (28) + : +- * Filter (27) + : +- * ColumnarToRow (26) + : +- CometScan parquet spark_catalog.default.store (25) + +- BroadcastExchange (34) + +- * Filter (33) + +- * ColumnarToRow (32) + +- CometScan parquet spark_catalog.default.item (31) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_profit#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 8] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_profit#5, ss_sold_date_sk#6] + +(3) Filter [codegen id : 8] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_profit#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) + +(4) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#12), dynamicpruningexpression(sr_returned_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] + +(6) Filter [codegen id : 1] +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] +Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) + +(7) BroadcastExchange +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(input[1, int, false], input[0, int, false], input[2, int, false]),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 8] +Left keys [3]: [ss_customer_sk#2, ss_item_sk#1, ss_ticket_number#4] +Right keys [3]: [sr_customer_sk#9, sr_item_sk#8, sr_ticket_number#10] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_net_loss#11, sr_returned_date_sk#12] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_profit#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] + +(10) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_sold_date_sk#17 IN dynamicpruning#18)] +PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] + +(12) Filter [codegen id : 2] +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) + +(13) BroadcastExchange +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[1, int, false] as bigint) & 4294967295))),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 8] +Left keys [2]: [sr_customer_sk#9, sr_item_sk#8] +Right keys [2]: [cs_bill_customer_sk#14, cs_item_sk#15] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, ss_sold_date_sk#6, sr_net_loss#11, sr_returned_date_sk#12, cs_net_profit#16, cs_sold_date_sk#17] +Input [12]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_net_loss#11, sr_returned_date_sk#12, cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] + +(16) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#19] + +(17) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#6] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 8] +Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, sr_returned_date_sk#12, cs_net_profit#16, cs_sold_date_sk#17] +Input [9]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, ss_sold_date_sk#6, sr_net_loss#11, sr_returned_date_sk#12, cs_net_profit#16, cs_sold_date_sk#17, d_date_sk#19] + +(19) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#20] + +(20) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [sr_returned_date_sk#12] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 8] +Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, cs_sold_date_sk#17] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, sr_returned_date_sk#12, cs_net_profit#16, cs_sold_date_sk#17, d_date_sk#20] + +(22) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#21] + +(23) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#17] +Right keys [1]: [d_date_sk#21] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 8] +Output [5]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16] +Input [7]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, cs_sold_date_sk#17, d_date_sk#21] + +(25) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 6] +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] + +(27) Filter [codegen id : 6] +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Condition : isnotnull(s_store_sk#22) + +(28) BroadcastExchange +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(29) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#22] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 8] +Output [6]: [ss_item_sk#1, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, s_store_id#23, s_store_name#24] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, s_store_sk#22, s_store_id#23, s_store_name#24] + +(31) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 7] +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] + +(33) Filter [codegen id : 7] +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Condition : isnotnull(i_item_sk#25) + +(34) BroadcastExchange +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(35) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#25] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 8] +Output [7]: [ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, s_store_id#23, s_store_name#24, i_item_id#26, i_item_desc#27] +Input [9]: [ss_item_sk#1, ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, s_store_id#23, s_store_name#24, i_item_sk#25, i_item_id#26, i_item_desc#27] + +(37) HashAggregate [codegen id : 8] +Input [7]: [ss_net_profit#5, sr_net_loss#11, cs_net_profit#16, s_store_id#23, s_store_name#24, i_item_id#26, i_item_desc#27] +Keys [4]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24] +Functions [3]: [partial_sum(UnscaledValue(ss_net_profit#5)), partial_sum(UnscaledValue(sr_net_loss#11)), partial_sum(UnscaledValue(cs_net_profit#16))] +Aggregate Attributes [3]: [sum#28, sum#29, sum#30] +Results [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] + +(38) Exchange +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] +Arguments: hashpartitioning(i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(39) HashAggregate [codegen id : 9] +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] +Keys [4]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24] +Functions [3]: [sum(UnscaledValue(ss_net_profit#5)), sum(UnscaledValue(sr_net_loss#11)), sum(UnscaledValue(cs_net_profit#16))] +Aggregate Attributes [3]: [sum(UnscaledValue(ss_net_profit#5))#34, sum(UnscaledValue(sr_net_loss#11))#35, sum(UnscaledValue(cs_net_profit#16))#36] +Results [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, MakeDecimal(sum(UnscaledValue(ss_net_profit#5))#34,17,2) AS store_sales_profit#37, MakeDecimal(sum(UnscaledValue(sr_net_loss#11))#35,17,2) AS store_returns_loss#38, MakeDecimal(sum(UnscaledValue(cs_net_profit#16))#36,17,2) AS catalog_sales_profit#39] + +(40) TakeOrderedAndProject +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, store_sales_profit#37, store_returns_loss#38, catalog_sales_profit#39] +Arguments: 100, [i_item_id#26 ASC NULLS FIRST, i_item_desc#27 ASC NULLS FIRST, s_store_id#23 ASC NULLS FIRST, s_store_name#24 ASC NULLS FIRST], [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, store_sales_profit#37, store_returns_loss#38, catalog_sales_profit#39] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (45) ++- * Project (44) + +- * Filter (43) + +- * ColumnarToRow (42) + +- CometScan parquet spark_catalog.default.date_dim (41) + + +(41) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#19, d_year#40, d_moy#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,4), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(42) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#19, d_year#40, d_moy#41] + +(43) Filter [codegen id : 1] +Input [3]: [d_date_sk#19, d_year#40, d_moy#41] +Condition : ((((isnotnull(d_moy#41) AND isnotnull(d_year#40)) AND (d_moy#41 = 4)) AND (d_year#40 = 2001)) AND isnotnull(d_date_sk#19)) + +(44) Project [codegen id : 1] +Output [1]: [d_date_sk#19] +Input [3]: [d_date_sk#19, d_year#40, d_moy#41] + +(45) BroadcastExchange +Input [1]: [d_date_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (50) ++- * Project (49) + +- * Filter (48) + +- * ColumnarToRow (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#20, d_year#42, d_moy#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), GreaterThanOrEqual(d_moy,4), LessThanOrEqual(d_moy,10), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#20, d_year#42, d_moy#43] + +(48) Filter [codegen id : 1] +Input [3]: [d_date_sk#20, d_year#42, d_moy#43] +Condition : (((((isnotnull(d_moy#43) AND isnotnull(d_year#42)) AND (d_moy#43 >= 4)) AND (d_moy#43 <= 10)) AND (d_year#42 = 2001)) AND isnotnull(d_date_sk#20)) + +(49) Project [codegen id : 1] +Output [1]: [d_date_sk#20] +Input [3]: [d_date_sk#20, d_year#42, d_moy#43] + +(50) BroadcastExchange +Input [1]: [d_date_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:3 Hosting operator id = 10 Hosting Expression = cs_sold_date_sk#17 IN dynamicpruning#13 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt new file mode 100644 index 000000000..f45de0daf --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt @@ -0,0 +1,76 @@ +TakeOrderedAndProject [i_item_id,i_item_desc,s_store_id,s_store_name,store_sales_profit,store_returns_loss,catalog_sales_profit] + WholeStageCodegen (9) + HashAggregate [i_item_id,i_item_desc,s_store_id,s_store_name,sum,sum,sum] [sum(UnscaledValue(ss_net_profit)),sum(UnscaledValue(sr_net_loss)),sum(UnscaledValue(cs_net_profit)),store_sales_profit,store_returns_loss,catalog_sales_profit,sum,sum,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,s_store_id,s_store_name] #1 + WholeStageCodegen (8) + HashAggregate [i_item_id,i_item_desc,s_store_id,s_store_name,ss_net_profit,sr_net_loss,cs_net_profit] [sum,sum,sum,sum,sum,sum] + Project [ss_net_profit,sr_net_loss,cs_net_profit,s_store_id,s_store_name,i_item_id,i_item_desc] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_net_profit,sr_net_loss,cs_net_profit,s_store_id,s_store_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_net_profit,sr_net_loss,cs_net_profit] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_net_profit,sr_net_loss,cs_net_profit,cs_sold_date_sk] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_net_profit,sr_net_loss,sr_returned_date_sk,cs_net_profit,cs_sold_date_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk,sr_net_loss,sr_returned_date_sk,cs_net_profit,cs_sold_date_sk] + BroadcastHashJoin [sr_customer_sk,sr_item_sk,cs_bill_customer_sk,cs_item_sk] + Project [ss_item_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk,sr_item_sk,sr_customer_sk,sr_net_loss,sr_returned_date_sk] + BroadcastHashJoin [ss_customer_sk,ss_item_sk,ss_ticket_number,sr_customer_sk,sr_item_sk,sr_ticket_number] + Filter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_moy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [sr_customer_sk,sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_net_loss,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_moy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + Filter [cs_bill_customer_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt new file mode 100644 index 000000000..8782d99fb --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt @@ -0,0 +1,208 @@ +== Physical Plan == +TakeOrderedAndProject (30) ++- * HashAggregate (29) + +- Exchange (28) + +- * HashAggregate (27) + +- * Project (26) + +- * BroadcastHashJoin Inner BuildRight (25) + :- * Project (19) + : +- * BroadcastHashJoin Inner BuildRight (18) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (10) + : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : +- BroadcastExchange (8) + : : : +- * Project (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : +- ReusedExchange (11) + : +- BroadcastExchange (17) + : +- * Filter (16) + : +- * ColumnarToRow (15) + : +- CometScan parquet spark_catalog.default.item (14) + +- BroadcastExchange (24) + +- * Project (23) + +- * Filter (22) + +- * ColumnarToRow (21) + +- CometScan parquet spark_catalog.default.promotion (20) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [8]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#8), dynamicpruningexpression(cs_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_item_sk), IsNotNull(cs_promo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [8]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8] + +(3) Filter [codegen id : 5] +Input [8]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8] +Condition : ((isnotnull(cs_bill_cdemo_sk#1) AND isnotnull(cs_item_sk#2)) AND isnotnull(cs_promo_sk#3)) + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] + +(6) Filter [codegen id : 1] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#10)) + +(7) Project [codegen id : 1] +Output [1]: [cd_demo_sk#10] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] + +(8) BroadcastExchange +Input [1]: [cd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_bill_cdemo_sk#1] +Right keys [1]: [cd_demo_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 5] +Output [7]: [cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8] +Input [9]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8, cd_demo_sk#10] + +(11) ReusedExchange [Reuses operator id: 35] +Output [1]: [d_date_sk#14] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_sold_date_sk#8] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [6]: [cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7] +Input [8]: [cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8, d_date_sk#14] + +(14) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#15, i_item_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [2]: [i_item_sk#15, i_item_id#16] + +(16) Filter [codegen id : 3] +Input [2]: [i_item_sk#15, i_item_id#16] +Condition : isnotnull(i_item_sk#15) + +(17) BroadcastExchange +Input [2]: [i_item_sk#15, i_item_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_item_sk#2] +Right keys [1]: [i_item_sk#15] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 5] +Output [6]: [cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_id#16] +Input [8]: [cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_sk#15, i_item_id#16] + +(20) Scan parquet spark_catalog.default.promotion +Output [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [Or(EqualTo(p_channel_email,N),EqualTo(p_channel_event,N)), IsNotNull(p_promo_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] + +(22) Filter [codegen id : 4] +Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Condition : (((p_channel_email#18 = N) OR (p_channel_event#19 = N)) AND isnotnull(p_promo_sk#17)) + +(23) Project [codegen id : 4] +Output [1]: [p_promo_sk#17] +Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] + +(24) BroadcastExchange +Input [1]: [p_promo_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_promo_sk#3] +Right keys [1]: [p_promo_sk#17] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 5] +Output [5]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_id#16] +Input [7]: [cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_id#16, p_promo_sk#17] + +(27) HashAggregate [codegen id : 5] +Input [5]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_id#16] +Keys [1]: [i_item_id#16] +Functions [4]: [partial_avg(cs_quantity#4), partial_avg(UnscaledValue(cs_list_price#5)), partial_avg(UnscaledValue(cs_coupon_amt#7)), partial_avg(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [8]: [sum#20, count#21, sum#22, count#23, sum#24, count#25, sum#26, count#27] +Results [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] + +(28) Exchange +Input [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] +Arguments: hashpartitioning(i_item_id#16, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 6] +Input [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] +Keys [1]: [i_item_id#16] +Functions [4]: [avg(cs_quantity#4), avg(UnscaledValue(cs_list_price#5)), avg(UnscaledValue(cs_coupon_amt#7)), avg(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [4]: [avg(cs_quantity#4)#36, avg(UnscaledValue(cs_list_price#5))#37, avg(UnscaledValue(cs_coupon_amt#7))#38, avg(UnscaledValue(cs_sales_price#6))#39] +Results [5]: [i_item_id#16, avg(cs_quantity#4)#36 AS agg1#40, cast((avg(UnscaledValue(cs_list_price#5))#37 / 100.0) as decimal(11,6)) AS agg2#41, cast((avg(UnscaledValue(cs_coupon_amt#7))#38 / 100.0) as decimal(11,6)) AS agg3#42, cast((avg(UnscaledValue(cs_sales_price#6))#39 / 100.0) as decimal(11,6)) AS agg4#43] + +(30) TakeOrderedAndProject +Input [5]: [i_item_id#16, agg1#40, agg2#41, agg3#42, agg4#43] +Arguments: 100, [i_item_id#16 ASC NULLS FIRST], [i_item_id#16, agg1#40, agg2#41, agg3#42, agg4#43] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (35) ++- * Project (34) + +- * Filter (33) + +- * ColumnarToRow (32) + +- CometScan parquet spark_catalog.default.date_dim (31) + + +(31) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#44] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#44] + +(33) Filter [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#44] +Condition : ((isnotnull(d_year#44) AND (d_year#44 = 2000)) AND isnotnull(d_date_sk#14)) + +(34) Project [codegen id : 1] +Output [1]: [d_date_sk#14] +Input [2]: [d_date_sk#14, d_year#44] + +(35) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt new file mode 100644 index 000000000..41f3e4a7a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt @@ -0,0 +1,52 @@ +TakeOrderedAndProject [i_item_id,agg1,agg2,agg3,agg4] + WholeStageCodegen (6) + HashAggregate [i_item_id,sum,count,sum,count,sum,count,sum,count] [avg(cs_quantity),avg(UnscaledValue(cs_list_price)),avg(UnscaledValue(cs_coupon_amt)),avg(UnscaledValue(cs_sales_price)),agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (5) + HashAggregate [i_item_id,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,i_item_id] + BroadcastHashJoin [cs_promo_sk,p_promo_sk] + Project [cs_promo_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,i_item_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_promo_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_promo_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_sold_date_sk] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Filter [cs_bill_cdemo_sk,cs_item_sk,cs_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_cdemo_sk,cs_item_sk,cs_promo_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [cd_demo_sk] + Filter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Project [p_promo_sk] + Filter [p_channel_email,p_channel_event,p_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_email,p_channel_event] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt new file mode 100644 index 000000000..6c2819610 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt @@ -0,0 +1,208 @@ +== Physical Plan == +TakeOrderedAndProject (30) ++- * HashAggregate (29) + +- Exchange (28) + +- * HashAggregate (27) + +- * Expand (26) + +- * Project (25) + +- * BroadcastHashJoin Inner BuildRight (24) + :- * Project (19) + : +- * BroadcastHashJoin Inner BuildRight (18) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (10) + : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (8) + : : : +- * Project (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : +- ReusedExchange (11) + : +- BroadcastExchange (17) + : +- * Filter (16) + : +- * ColumnarToRow (15) + : +- CometScan parquet spark_catalog.default.store (14) + +- BroadcastExchange (23) + +- * Filter (22) + +- * ColumnarToRow (21) + +- CometScan parquet spark_catalog.default.item (20) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] + +(3) Filter [codegen id : 5] +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_item_sk#1)) + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] + +(6) Filter [codegen id : 1] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#10)) + +(7) Project [codegen id : 1] +Output [1]: [cd_demo_sk#10] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] + +(8) BroadcastExchange +Input [1]: [cd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 5] +Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Input [9]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, cd_demo_sk#10] + +(11) ReusedExchange [Reuses operator id: 35] +Output [1]: [d_date_sk#14] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, d_date_sk#14] + +(14) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#15, s_state#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [2]: [s_store_sk#15, s_state#16] + +(16) Filter [codegen id : 3] +Input [2]: [s_store_sk#15, s_state#16] +Condition : ((isnotnull(s_state#16) AND (s_state#16 = TN)) AND isnotnull(s_store_sk#15)) + +(17) BroadcastExchange +Input [2]: [s_store_sk#15, s_state#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#15] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 5] +Output [6]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#16] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_store_sk#15, s_state#16] + +(20) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#17, i_item_id#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#17, i_item_id#18] + +(22) Filter [codegen id : 4] +Input [2]: [i_item_sk#17, i_item_id#18] +Condition : isnotnull(i_item_sk#17) + +(23) BroadcastExchange +Input [2]: [i_item_sk#17, i_item_id#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [6]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, s_state#16] +Input [8]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#16, i_item_sk#17, i_item_id#18] + +(26) Expand [codegen id : 5] +Input [6]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, s_state#16] +Arguments: [[ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, s_state#16, 0], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, null, 1], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, null, null, 3]], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, s_state#20, spark_grouping_id#21] + +(27) HashAggregate [codegen id : 5] +Input [7]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, s_state#20, spark_grouping_id#21] +Keys [3]: [i_item_id#19, s_state#20, spark_grouping_id#21] +Functions [4]: [partial_avg(ss_quantity#4), partial_avg(UnscaledValue(ss_list_price#5)), partial_avg(UnscaledValue(ss_coupon_amt#7)), partial_avg(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [8]: [sum#22, count#23, sum#24, count#25, sum#26, count#27, sum#28, count#29] +Results [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#30, count#31, sum#32, count#33, sum#34, count#35, sum#36, count#37] + +(28) Exchange +Input [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#30, count#31, sum#32, count#33, sum#34, count#35, sum#36, count#37] +Arguments: hashpartitioning(i_item_id#19, s_state#20, spark_grouping_id#21, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 6] +Input [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#30, count#31, sum#32, count#33, sum#34, count#35, sum#36, count#37] +Keys [3]: [i_item_id#19, s_state#20, spark_grouping_id#21] +Functions [4]: [avg(ss_quantity#4), avg(UnscaledValue(ss_list_price#5)), avg(UnscaledValue(ss_coupon_amt#7)), avg(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [4]: [avg(ss_quantity#4)#38, avg(UnscaledValue(ss_list_price#5))#39, avg(UnscaledValue(ss_coupon_amt#7))#40, avg(UnscaledValue(ss_sales_price#6))#41] +Results [7]: [i_item_id#19, s_state#20, cast((shiftright(spark_grouping_id#21, 0) & 1) as tinyint) AS g_state#42, avg(ss_quantity#4)#38 AS agg1#43, cast((avg(UnscaledValue(ss_list_price#5))#39 / 100.0) as decimal(11,6)) AS agg2#44, cast((avg(UnscaledValue(ss_coupon_amt#7))#40 / 100.0) as decimal(11,6)) AS agg3#45, cast((avg(UnscaledValue(ss_sales_price#6))#41 / 100.0) as decimal(11,6)) AS agg4#46] + +(30) TakeOrderedAndProject +Input [7]: [i_item_id#19, s_state#20, g_state#42, agg1#43, agg2#44, agg3#45, agg4#46] +Arguments: 100, [i_item_id#19 ASC NULLS FIRST, s_state#20 ASC NULLS FIRST], [i_item_id#19, s_state#20, g_state#42, agg1#43, agg2#44, agg3#45, agg4#46] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (35) ++- * Project (34) + +- * Filter (33) + +- * ColumnarToRow (32) + +- CometScan parquet spark_catalog.default.date_dim (31) + + +(31) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#47] + +(33) Filter [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#47] +Condition : ((isnotnull(d_year#47) AND (d_year#47 = 2002)) AND isnotnull(d_date_sk#14)) + +(34) Project [codegen id : 1] +Output [1]: [d_date_sk#14] +Input [2]: [d_date_sk#14, d_year#47] + +(35) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt new file mode 100644 index 000000000..9cecdee29 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt @@ -0,0 +1,52 @@ +TakeOrderedAndProject [i_item_id,s_state,g_state,agg1,agg2,agg3,agg4] + WholeStageCodegen (6) + HashAggregate [i_item_id,s_state,spark_grouping_id,sum,count,sum,count,sum,count,sum,count] [avg(ss_quantity),avg(UnscaledValue(ss_list_price)),avg(UnscaledValue(ss_coupon_amt)),avg(UnscaledValue(ss_sales_price)),g_state,agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,s_state,spark_grouping_id] #1 + WholeStageCodegen (5) + HashAggregate [i_item_id,s_state,spark_grouping_id,ss_quantity,ss_list_price,ss_coupon_amt,ss_sales_price] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Expand [ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,i_item_id,s_state] + Project [ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,i_item_id,s_state] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Filter [ss_cdemo_sk,ss_store_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [cd_demo_sk] + Filter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Filter [s_state,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt new file mode 100644 index 000000000..ccab165e2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt @@ -0,0 +1,437 @@ +== Physical Plan == +* BroadcastNestedLoopJoin Inner BuildRight (70) +:- * BroadcastNestedLoopJoin Inner BuildRight (58) +: :- * BroadcastNestedLoopJoin Inner BuildRight (46) +: : :- * BroadcastNestedLoopJoin Inner BuildRight (34) +: : : :- * BroadcastNestedLoopJoin Inner BuildRight (22) +: : : : :- * HashAggregate (10) +: : : : : +- Exchange (9) +: : : : : +- * HashAggregate (8) +: : : : : +- * HashAggregate (7) +: : : : : +- Exchange (6) +: : : : : +- * HashAggregate (5) +: : : : : +- * Project (4) +: : : : : +- * Filter (3) +: : : : : +- * ColumnarToRow (2) +: : : : : +- CometScan parquet spark_catalog.default.store_sales (1) +: : : : +- BroadcastExchange (21) +: : : : +- * HashAggregate (20) +: : : : +- Exchange (19) +: : : : +- * HashAggregate (18) +: : : : +- * HashAggregate (17) +: : : : +- Exchange (16) +: : : : +- * HashAggregate (15) +: : : : +- * Project (14) +: : : : +- * Filter (13) +: : : : +- * ColumnarToRow (12) +: : : : +- CometScan parquet spark_catalog.default.store_sales (11) +: : : +- BroadcastExchange (33) +: : : +- * HashAggregate (32) +: : : +- Exchange (31) +: : : +- * HashAggregate (30) +: : : +- * HashAggregate (29) +: : : +- Exchange (28) +: : : +- * HashAggregate (27) +: : : +- * Project (26) +: : : +- * Filter (25) +: : : +- * ColumnarToRow (24) +: : : +- CometScan parquet spark_catalog.default.store_sales (23) +: : +- BroadcastExchange (45) +: : +- * HashAggregate (44) +: : +- Exchange (43) +: : +- * HashAggregate (42) +: : +- * HashAggregate (41) +: : +- Exchange (40) +: : +- * HashAggregate (39) +: : +- * Project (38) +: : +- * Filter (37) +: : +- * ColumnarToRow (36) +: : +- CometScan parquet spark_catalog.default.store_sales (35) +: +- BroadcastExchange (57) +: +- * HashAggregate (56) +: +- Exchange (55) +: +- * HashAggregate (54) +: +- * HashAggregate (53) +: +- Exchange (52) +: +- * HashAggregate (51) +: +- * Project (50) +: +- * Filter (49) +: +- * ColumnarToRow (48) +: +- CometScan parquet spark_catalog.default.store_sales (47) ++- BroadcastExchange (69) + +- * HashAggregate (68) + +- Exchange (67) + +- * HashAggregate (66) + +- * HashAggregate (65) + +- Exchange (64) + +- * HashAggregate (63) + +- * Project (62) + +- * Filter (61) + +- * ColumnarToRow (60) + +- CometScan parquet spark_catalog.default.store_sales (59) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#1, ss_wholesale_cost#2, ss_list_price#3, ss_coupon_amt#4, ss_sold_date_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,0), LessThanOrEqual(ss_quantity,5), Or(Or(And(GreaterThanOrEqual(ss_list_price,8.00),LessThanOrEqual(ss_list_price,18.00)),And(GreaterThanOrEqual(ss_coupon_amt,459.00),LessThanOrEqual(ss_coupon_amt,1459.00))),And(GreaterThanOrEqual(ss_wholesale_cost,57.00),LessThanOrEqual(ss_wholesale_cost,77.00)))] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [5]: [ss_quantity#1, ss_wholesale_cost#2, ss_list_price#3, ss_coupon_amt#4, ss_sold_date_sk#5] + +(3) Filter [codegen id : 1] +Input [5]: [ss_quantity#1, ss_wholesale_cost#2, ss_list_price#3, ss_coupon_amt#4, ss_sold_date_sk#5] +Condition : (((isnotnull(ss_quantity#1) AND (ss_quantity#1 >= 0)) AND (ss_quantity#1 <= 5)) AND ((((ss_list_price#3 >= 8.00) AND (ss_list_price#3 <= 18.00)) OR ((ss_coupon_amt#4 >= 459.00) AND (ss_coupon_amt#4 <= 1459.00))) OR ((ss_wholesale_cost#2 >= 57.00) AND (ss_wholesale_cost#2 <= 77.00)))) + +(4) Project [codegen id : 1] +Output [1]: [ss_list_price#3] +Input [5]: [ss_quantity#1, ss_wholesale_cost#2, ss_list_price#3, ss_coupon_amt#4, ss_sold_date_sk#5] + +(5) HashAggregate [codegen id : 1] +Input [1]: [ss_list_price#3] +Keys [1]: [ss_list_price#3] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#3)), partial_count(ss_list_price#3)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#3))#6, count(ss_list_price#3)#7] +Results [4]: [ss_list_price#3, sum#8, count#9, count#10] + +(6) Exchange +Input [4]: [ss_list_price#3, sum#8, count#9, count#10] +Arguments: hashpartitioning(ss_list_price#3, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(7) HashAggregate [codegen id : 2] +Input [4]: [ss_list_price#3, sum#8, count#9, count#10] +Keys [1]: [ss_list_price#3] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#3)), merge_count(ss_list_price#3)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#3))#6, count(ss_list_price#3)#7] +Results [4]: [ss_list_price#3, sum#8, count#9, count#10] + +(8) HashAggregate [codegen id : 2] +Input [4]: [ss_list_price#3, sum#8, count#9, count#10] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#3)), merge_count(ss_list_price#3), partial_count(distinct ss_list_price#3)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#3))#6, count(ss_list_price#3)#7, count(ss_list_price#3)#11] +Results [4]: [sum#8, count#9, count#10, count#12] + +(9) Exchange +Input [4]: [sum#8, count#9, count#10, count#12] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=2] + +(10) HashAggregate [codegen id : 18] +Input [4]: [sum#8, count#9, count#10, count#12] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#3)), count(ss_list_price#3), count(distinct ss_list_price#3)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#3))#6, count(ss_list_price#3)#7, count(ss_list_price#3)#11] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#3))#6 / 100.0) as decimal(11,6)) AS B1_LP#13, count(ss_list_price#3)#7 AS B1_CNT#14, count(ss_list_price#3)#11 AS B1_CNTD#15] + +(11) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#16, ss_wholesale_cost#17, ss_list_price#18, ss_coupon_amt#19, ss_sold_date_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,6), LessThanOrEqual(ss_quantity,10), Or(Or(And(GreaterThanOrEqual(ss_list_price,90.00),LessThanOrEqual(ss_list_price,100.00)),And(GreaterThanOrEqual(ss_coupon_amt,2323.00),LessThanOrEqual(ss_coupon_amt,3323.00))),And(GreaterThanOrEqual(ss_wholesale_cost,31.00),LessThanOrEqual(ss_wholesale_cost,51.00)))] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 3] +Input [5]: [ss_quantity#16, ss_wholesale_cost#17, ss_list_price#18, ss_coupon_amt#19, ss_sold_date_sk#20] + +(13) Filter [codegen id : 3] +Input [5]: [ss_quantity#16, ss_wholesale_cost#17, ss_list_price#18, ss_coupon_amt#19, ss_sold_date_sk#20] +Condition : (((isnotnull(ss_quantity#16) AND (ss_quantity#16 >= 6)) AND (ss_quantity#16 <= 10)) AND ((((ss_list_price#18 >= 90.00) AND (ss_list_price#18 <= 100.00)) OR ((ss_coupon_amt#19 >= 2323.00) AND (ss_coupon_amt#19 <= 3323.00))) OR ((ss_wholesale_cost#17 >= 31.00) AND (ss_wholesale_cost#17 <= 51.00)))) + +(14) Project [codegen id : 3] +Output [1]: [ss_list_price#18] +Input [5]: [ss_quantity#16, ss_wholesale_cost#17, ss_list_price#18, ss_coupon_amt#19, ss_sold_date_sk#20] + +(15) HashAggregate [codegen id : 3] +Input [1]: [ss_list_price#18] +Keys [1]: [ss_list_price#18] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#18)), partial_count(ss_list_price#18)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#18))#21, count(ss_list_price#18)#22] +Results [4]: [ss_list_price#18, sum#23, count#24, count#25] + +(16) Exchange +Input [4]: [ss_list_price#18, sum#23, count#24, count#25] +Arguments: hashpartitioning(ss_list_price#18, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) HashAggregate [codegen id : 4] +Input [4]: [ss_list_price#18, sum#23, count#24, count#25] +Keys [1]: [ss_list_price#18] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#18)), merge_count(ss_list_price#18)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#18))#21, count(ss_list_price#18)#22] +Results [4]: [ss_list_price#18, sum#23, count#24, count#25] + +(18) HashAggregate [codegen id : 4] +Input [4]: [ss_list_price#18, sum#23, count#24, count#25] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#18)), merge_count(ss_list_price#18), partial_count(distinct ss_list_price#18)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#18))#21, count(ss_list_price#18)#22, count(ss_list_price#18)#26] +Results [4]: [sum#23, count#24, count#25, count#27] + +(19) Exchange +Input [4]: [sum#23, count#24, count#25, count#27] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(20) HashAggregate [codegen id : 5] +Input [4]: [sum#23, count#24, count#25, count#27] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#18)), count(ss_list_price#18), count(distinct ss_list_price#18)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#18))#21, count(ss_list_price#18)#22, count(ss_list_price#18)#26] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#18))#21 / 100.0) as decimal(11,6)) AS B2_LP#28, count(ss_list_price#18)#22 AS B2_CNT#29, count(ss_list_price#18)#26 AS B2_CNTD#30] + +(21) BroadcastExchange +Input [3]: [B2_LP#28, B2_CNT#29, B2_CNTD#30] +Arguments: IdentityBroadcastMode, [plan_id=5] + +(22) BroadcastNestedLoopJoin [codegen id : 18] +Join type: Inner +Join condition: None + +(23) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#31, ss_wholesale_cost#32, ss_list_price#33, ss_coupon_amt#34, ss_sold_date_sk#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,11), LessThanOrEqual(ss_quantity,15), Or(Or(And(GreaterThanOrEqual(ss_list_price,142.00),LessThanOrEqual(ss_list_price,152.00)),And(GreaterThanOrEqual(ss_coupon_amt,12214.00),LessThanOrEqual(ss_coupon_amt,13214.00))),And(GreaterThanOrEqual(ss_wholesale_cost,79.00),LessThanOrEqual(ss_wholesale_cost,99.00)))] +ReadSchema: struct + +(24) ColumnarToRow [codegen id : 6] +Input [5]: [ss_quantity#31, ss_wholesale_cost#32, ss_list_price#33, ss_coupon_amt#34, ss_sold_date_sk#35] + +(25) Filter [codegen id : 6] +Input [5]: [ss_quantity#31, ss_wholesale_cost#32, ss_list_price#33, ss_coupon_amt#34, ss_sold_date_sk#35] +Condition : (((isnotnull(ss_quantity#31) AND (ss_quantity#31 >= 11)) AND (ss_quantity#31 <= 15)) AND ((((ss_list_price#33 >= 142.00) AND (ss_list_price#33 <= 152.00)) OR ((ss_coupon_amt#34 >= 12214.00) AND (ss_coupon_amt#34 <= 13214.00))) OR ((ss_wholesale_cost#32 >= 79.00) AND (ss_wholesale_cost#32 <= 99.00)))) + +(26) Project [codegen id : 6] +Output [1]: [ss_list_price#33] +Input [5]: [ss_quantity#31, ss_wholesale_cost#32, ss_list_price#33, ss_coupon_amt#34, ss_sold_date_sk#35] + +(27) HashAggregate [codegen id : 6] +Input [1]: [ss_list_price#33] +Keys [1]: [ss_list_price#33] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#33)), partial_count(ss_list_price#33)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#33))#36, count(ss_list_price#33)#37] +Results [4]: [ss_list_price#33, sum#38, count#39, count#40] + +(28) Exchange +Input [4]: [ss_list_price#33, sum#38, count#39, count#40] +Arguments: hashpartitioning(ss_list_price#33, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(29) HashAggregate [codegen id : 7] +Input [4]: [ss_list_price#33, sum#38, count#39, count#40] +Keys [1]: [ss_list_price#33] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#33)), merge_count(ss_list_price#33)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#33))#36, count(ss_list_price#33)#37] +Results [4]: [ss_list_price#33, sum#38, count#39, count#40] + +(30) HashAggregate [codegen id : 7] +Input [4]: [ss_list_price#33, sum#38, count#39, count#40] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#33)), merge_count(ss_list_price#33), partial_count(distinct ss_list_price#33)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#33))#36, count(ss_list_price#33)#37, count(ss_list_price#33)#41] +Results [4]: [sum#38, count#39, count#40, count#42] + +(31) Exchange +Input [4]: [sum#38, count#39, count#40, count#42] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(32) HashAggregate [codegen id : 8] +Input [4]: [sum#38, count#39, count#40, count#42] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#33)), count(ss_list_price#33), count(distinct ss_list_price#33)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#33))#36, count(ss_list_price#33)#37, count(ss_list_price#33)#41] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#33))#36 / 100.0) as decimal(11,6)) AS B3_LP#43, count(ss_list_price#33)#37 AS B3_CNT#44, count(ss_list_price#33)#41 AS B3_CNTD#45] + +(33) BroadcastExchange +Input [3]: [B3_LP#43, B3_CNT#44, B3_CNTD#45] +Arguments: IdentityBroadcastMode, [plan_id=8] + +(34) BroadcastNestedLoopJoin [codegen id : 18] +Join type: Inner +Join condition: None + +(35) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#46, ss_wholesale_cost#47, ss_list_price#48, ss_coupon_amt#49, ss_sold_date_sk#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,16), LessThanOrEqual(ss_quantity,20), Or(Or(And(GreaterThanOrEqual(ss_list_price,135.00),LessThanOrEqual(ss_list_price,145.00)),And(GreaterThanOrEqual(ss_coupon_amt,6071.00),LessThanOrEqual(ss_coupon_amt,7071.00))),And(GreaterThanOrEqual(ss_wholesale_cost,38.00),LessThanOrEqual(ss_wholesale_cost,58.00)))] +ReadSchema: struct + +(36) ColumnarToRow [codegen id : 9] +Input [5]: [ss_quantity#46, ss_wholesale_cost#47, ss_list_price#48, ss_coupon_amt#49, ss_sold_date_sk#50] + +(37) Filter [codegen id : 9] +Input [5]: [ss_quantity#46, ss_wholesale_cost#47, ss_list_price#48, ss_coupon_amt#49, ss_sold_date_sk#50] +Condition : (((isnotnull(ss_quantity#46) AND (ss_quantity#46 >= 16)) AND (ss_quantity#46 <= 20)) AND ((((ss_list_price#48 >= 135.00) AND (ss_list_price#48 <= 145.00)) OR ((ss_coupon_amt#49 >= 6071.00) AND (ss_coupon_amt#49 <= 7071.00))) OR ((ss_wholesale_cost#47 >= 38.00) AND (ss_wholesale_cost#47 <= 58.00)))) + +(38) Project [codegen id : 9] +Output [1]: [ss_list_price#48] +Input [5]: [ss_quantity#46, ss_wholesale_cost#47, ss_list_price#48, ss_coupon_amt#49, ss_sold_date_sk#50] + +(39) HashAggregate [codegen id : 9] +Input [1]: [ss_list_price#48] +Keys [1]: [ss_list_price#48] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#48)), partial_count(ss_list_price#48)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#48))#51, count(ss_list_price#48)#52] +Results [4]: [ss_list_price#48, sum#53, count#54, count#55] + +(40) Exchange +Input [4]: [ss_list_price#48, sum#53, count#54, count#55] +Arguments: hashpartitioning(ss_list_price#48, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(41) HashAggregate [codegen id : 10] +Input [4]: [ss_list_price#48, sum#53, count#54, count#55] +Keys [1]: [ss_list_price#48] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#48)), merge_count(ss_list_price#48)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#48))#51, count(ss_list_price#48)#52] +Results [4]: [ss_list_price#48, sum#53, count#54, count#55] + +(42) HashAggregate [codegen id : 10] +Input [4]: [ss_list_price#48, sum#53, count#54, count#55] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#48)), merge_count(ss_list_price#48), partial_count(distinct ss_list_price#48)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#48))#51, count(ss_list_price#48)#52, count(ss_list_price#48)#56] +Results [4]: [sum#53, count#54, count#55, count#57] + +(43) Exchange +Input [4]: [sum#53, count#54, count#55, count#57] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=10] + +(44) HashAggregate [codegen id : 11] +Input [4]: [sum#53, count#54, count#55, count#57] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#48)), count(ss_list_price#48), count(distinct ss_list_price#48)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#48))#51, count(ss_list_price#48)#52, count(ss_list_price#48)#56] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#48))#51 / 100.0) as decimal(11,6)) AS B4_LP#58, count(ss_list_price#48)#52 AS B4_CNT#59, count(ss_list_price#48)#56 AS B4_CNTD#60] + +(45) BroadcastExchange +Input [3]: [B4_LP#58, B4_CNT#59, B4_CNTD#60] +Arguments: IdentityBroadcastMode, [plan_id=11] + +(46) BroadcastNestedLoopJoin [codegen id : 18] +Join type: Inner +Join condition: None + +(47) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#61, ss_wholesale_cost#62, ss_list_price#63, ss_coupon_amt#64, ss_sold_date_sk#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,21), LessThanOrEqual(ss_quantity,25), Or(Or(And(GreaterThanOrEqual(ss_list_price,122.00),LessThanOrEqual(ss_list_price,132.00)),And(GreaterThanOrEqual(ss_coupon_amt,836.00),LessThanOrEqual(ss_coupon_amt,1836.00))),And(GreaterThanOrEqual(ss_wholesale_cost,17.00),LessThanOrEqual(ss_wholesale_cost,37.00)))] +ReadSchema: struct + +(48) ColumnarToRow [codegen id : 12] +Input [5]: [ss_quantity#61, ss_wholesale_cost#62, ss_list_price#63, ss_coupon_amt#64, ss_sold_date_sk#65] + +(49) Filter [codegen id : 12] +Input [5]: [ss_quantity#61, ss_wholesale_cost#62, ss_list_price#63, ss_coupon_amt#64, ss_sold_date_sk#65] +Condition : (((isnotnull(ss_quantity#61) AND (ss_quantity#61 >= 21)) AND (ss_quantity#61 <= 25)) AND ((((ss_list_price#63 >= 122.00) AND (ss_list_price#63 <= 132.00)) OR ((ss_coupon_amt#64 >= 836.00) AND (ss_coupon_amt#64 <= 1836.00))) OR ((ss_wholesale_cost#62 >= 17.00) AND (ss_wholesale_cost#62 <= 37.00)))) + +(50) Project [codegen id : 12] +Output [1]: [ss_list_price#63] +Input [5]: [ss_quantity#61, ss_wholesale_cost#62, ss_list_price#63, ss_coupon_amt#64, ss_sold_date_sk#65] + +(51) HashAggregate [codegen id : 12] +Input [1]: [ss_list_price#63] +Keys [1]: [ss_list_price#63] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#63)), partial_count(ss_list_price#63)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#63))#66, count(ss_list_price#63)#67] +Results [4]: [ss_list_price#63, sum#68, count#69, count#70] + +(52) Exchange +Input [4]: [ss_list_price#63, sum#68, count#69, count#70] +Arguments: hashpartitioning(ss_list_price#63, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(53) HashAggregate [codegen id : 13] +Input [4]: [ss_list_price#63, sum#68, count#69, count#70] +Keys [1]: [ss_list_price#63] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#63)), merge_count(ss_list_price#63)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#63))#66, count(ss_list_price#63)#67] +Results [4]: [ss_list_price#63, sum#68, count#69, count#70] + +(54) HashAggregate [codegen id : 13] +Input [4]: [ss_list_price#63, sum#68, count#69, count#70] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#63)), merge_count(ss_list_price#63), partial_count(distinct ss_list_price#63)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#63))#66, count(ss_list_price#63)#67, count(ss_list_price#63)#71] +Results [4]: [sum#68, count#69, count#70, count#72] + +(55) Exchange +Input [4]: [sum#68, count#69, count#70, count#72] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=13] + +(56) HashAggregate [codegen id : 14] +Input [4]: [sum#68, count#69, count#70, count#72] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#63)), count(ss_list_price#63), count(distinct ss_list_price#63)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#63))#66, count(ss_list_price#63)#67, count(ss_list_price#63)#71] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#63))#66 / 100.0) as decimal(11,6)) AS B5_LP#73, count(ss_list_price#63)#67 AS B5_CNT#74, count(ss_list_price#63)#71 AS B5_CNTD#75] + +(57) BroadcastExchange +Input [3]: [B5_LP#73, B5_CNT#74, B5_CNTD#75] +Arguments: IdentityBroadcastMode, [plan_id=14] + +(58) BroadcastNestedLoopJoin [codegen id : 18] +Join type: Inner +Join condition: None + +(59) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_quantity#76, ss_wholesale_cost#77, ss_list_price#78, ss_coupon_amt#79, ss_sold_date_sk#80] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,26), LessThanOrEqual(ss_quantity,30), Or(Or(And(GreaterThanOrEqual(ss_list_price,154.00),LessThanOrEqual(ss_list_price,164.00)),And(GreaterThanOrEqual(ss_coupon_amt,7326.00),LessThanOrEqual(ss_coupon_amt,8326.00))),And(GreaterThanOrEqual(ss_wholesale_cost,7.00),LessThanOrEqual(ss_wholesale_cost,27.00)))] +ReadSchema: struct + +(60) ColumnarToRow [codegen id : 15] +Input [5]: [ss_quantity#76, ss_wholesale_cost#77, ss_list_price#78, ss_coupon_amt#79, ss_sold_date_sk#80] + +(61) Filter [codegen id : 15] +Input [5]: [ss_quantity#76, ss_wholesale_cost#77, ss_list_price#78, ss_coupon_amt#79, ss_sold_date_sk#80] +Condition : (((isnotnull(ss_quantity#76) AND (ss_quantity#76 >= 26)) AND (ss_quantity#76 <= 30)) AND ((((ss_list_price#78 >= 154.00) AND (ss_list_price#78 <= 164.00)) OR ((ss_coupon_amt#79 >= 7326.00) AND (ss_coupon_amt#79 <= 8326.00))) OR ((ss_wholesale_cost#77 >= 7.00) AND (ss_wholesale_cost#77 <= 27.00)))) + +(62) Project [codegen id : 15] +Output [1]: [ss_list_price#78] +Input [5]: [ss_quantity#76, ss_wholesale_cost#77, ss_list_price#78, ss_coupon_amt#79, ss_sold_date_sk#80] + +(63) HashAggregate [codegen id : 15] +Input [1]: [ss_list_price#78] +Keys [1]: [ss_list_price#78] +Functions [2]: [partial_avg(UnscaledValue(ss_list_price#78)), partial_count(ss_list_price#78)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#78))#81, count(ss_list_price#78)#82] +Results [4]: [ss_list_price#78, sum#83, count#84, count#85] + +(64) Exchange +Input [4]: [ss_list_price#78, sum#83, count#84, count#85] +Arguments: hashpartitioning(ss_list_price#78, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(65) HashAggregate [codegen id : 16] +Input [4]: [ss_list_price#78, sum#83, count#84, count#85] +Keys [1]: [ss_list_price#78] +Functions [2]: [merge_avg(UnscaledValue(ss_list_price#78)), merge_count(ss_list_price#78)] +Aggregate Attributes [2]: [avg(UnscaledValue(ss_list_price#78))#81, count(ss_list_price#78)#82] +Results [4]: [ss_list_price#78, sum#83, count#84, count#85] + +(66) HashAggregate [codegen id : 16] +Input [4]: [ss_list_price#78, sum#83, count#84, count#85] +Keys: [] +Functions [3]: [merge_avg(UnscaledValue(ss_list_price#78)), merge_count(ss_list_price#78), partial_count(distinct ss_list_price#78)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#78))#81, count(ss_list_price#78)#82, count(ss_list_price#78)#86] +Results [4]: [sum#83, count#84, count#85, count#87] + +(67) Exchange +Input [4]: [sum#83, count#84, count#85, count#87] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=16] + +(68) HashAggregate [codegen id : 17] +Input [4]: [sum#83, count#84, count#85, count#87] +Keys: [] +Functions [3]: [avg(UnscaledValue(ss_list_price#78)), count(ss_list_price#78), count(distinct ss_list_price#78)] +Aggregate Attributes [3]: [avg(UnscaledValue(ss_list_price#78))#81, count(ss_list_price#78)#82, count(ss_list_price#78)#86] +Results [3]: [cast((avg(UnscaledValue(ss_list_price#78))#81 / 100.0) as decimal(11,6)) AS B6_LP#88, count(ss_list_price#78)#82 AS B6_CNT#89, count(ss_list_price#78)#86 AS B6_CNTD#90] + +(69) BroadcastExchange +Input [3]: [B6_LP#88, B6_CNT#89, B6_CNTD#90] +Arguments: IdentityBroadcastMode, [plan_id=17] + +(70) BroadcastNestedLoopJoin [codegen id : 18] +Join type: Inner +Join condition: None + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt new file mode 100644 index 000000000..7f5641ec2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt @@ -0,0 +1,111 @@ +WholeStageCodegen (18) + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B1_LP,B1_CNT,B1_CNTD,sum,count,count,count] + InputAdapter + Exchange #1 + WholeStageCodegen (2) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #2 + WholeStageCodegen (1) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + Project [ss_list_price] + Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (5) + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B2_LP,B2_CNT,B2_CNTD,sum,count,count,count] + InputAdapter + Exchange #4 + WholeStageCodegen (4) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #5 + WholeStageCodegen (3) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + Project [ss_list_price] + Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (8) + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B3_LP,B3_CNT,B3_CNTD,sum,count,count,count] + InputAdapter + Exchange #7 + WholeStageCodegen (7) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #8 + WholeStageCodegen (6) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + Project [ss_list_price] + Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (11) + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B4_LP,B4_CNT,B4_CNTD,sum,count,count,count] + InputAdapter + Exchange #10 + WholeStageCodegen (10) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #11 + WholeStageCodegen (9) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + Project [ss_list_price] + Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (14) + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B5_LP,B5_CNT,B5_CNTD,sum,count,count,count] + InputAdapter + Exchange #13 + WholeStageCodegen (13) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #14 + WholeStageCodegen (12) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + Project [ss_list_price] + Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + InputAdapter + BroadcastExchange #15 + WholeStageCodegen (17) + HashAggregate [sum,count,count,count] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),B6_LP,B6_CNT,B6_CNTD,sum,count,count,count] + InputAdapter + Exchange #16 + WholeStageCodegen (16) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),count(ss_list_price),sum,count,count,count,sum,count,count,count] + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + InputAdapter + Exchange [ss_list_price] #17 + WholeStageCodegen (15) + HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] + Project [ss_list_price] + Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt new file mode 100644 index 000000000..9a5be8c4d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt @@ -0,0 +1,326 @@ +== Physical Plan == +TakeOrderedAndProject (40) ++- * HashAggregate (39) + +- Exchange (38) + +- * HashAggregate (37) + +- * Project (36) + +- * BroadcastHashJoin Inner BuildRight (35) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * Project (24) + : : +- * BroadcastHashJoin Inner BuildRight (23) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (18) + : : : : +- * BroadcastHashJoin Inner BuildRight (17) + : : : : :- * Project (15) + : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : :- * Project (9) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : :- * Filter (3) + : : : : : : : +- * ColumnarToRow (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- BroadcastExchange (7) + : : : : : : +- * Filter (6) + : : : : : : +- * ColumnarToRow (5) + : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : : : +- BroadcastExchange (13) + : : : : : +- * Filter (12) + : : : : : +- * ColumnarToRow (11) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (10) + : : : : +- ReusedExchange (16) + : : : +- ReusedExchange (19) + : : +- ReusedExchange (22) + : +- BroadcastExchange (28) + : +- * Filter (27) + : +- * ColumnarToRow (26) + : +- CometScan parquet spark_catalog.default.store (25) + +- BroadcastExchange (34) + +- * Filter (33) + +- * ColumnarToRow (32) + +- CometScan parquet spark_catalog.default.item (31) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 8] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] + +(3) Filter [codegen id : 8] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) + +(4) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#12), dynamicpruningexpression(sr_returned_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] + +(6) Filter [codegen id : 1] +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) + +(7) BroadcastExchange +Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(input[1, int, false], input[0, int, false], input[2, int, false]),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 8] +Left keys [3]: [ss_customer_sk#2, ss_item_sk#1, ss_ticket_number#4] +Right keys [3]: [sr_customer_sk#9, sr_item_sk#8, sr_ticket_number#10] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] + +(10) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_sold_date_sk#17 IN dynamicpruning#18)] +PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] + +(12) Filter [codegen id : 2] +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) + +(13) BroadcastExchange +Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[1, int, false] as bigint) & 4294967295))),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 8] +Left keys [2]: [sr_customer_sk#9, sr_item_sk#8] +Right keys [2]: [cs_bill_customer_sk#14, cs_item_sk#15] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 8] +Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17] +Input [12]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12, cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] + +(16) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#19] + +(17) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#6] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 8] +Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17] +Input [9]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#19] + +(19) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#20] + +(20) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [sr_returned_date_sk#12] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 8] +Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#20] + +(22) ReusedExchange [Reuses operator id: 55] +Output [1]: [d_date_sk#21] + +(23) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#17] +Right keys [1]: [d_date_sk#21] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 8] +Output [5]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16] +Input [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#21] + +(25) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 6] +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] + +(27) Filter [codegen id : 6] +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Condition : isnotnull(s_store_sk#22) + +(28) BroadcastExchange +Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(29) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#22] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 8] +Output [6]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#23, s_store_name#24] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_sk#22, s_store_id#23, s_store_name#24] + +(31) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 7] +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] + +(33) Filter [codegen id : 7] +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Condition : isnotnull(i_item_sk#25) + +(34) BroadcastExchange +Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(35) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#25] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 8] +Output [7]: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#23, s_store_name#24, i_item_id#26, i_item_desc#27] +Input [9]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#23, s_store_name#24, i_item_sk#25, i_item_id#26, i_item_desc#27] + +(37) HashAggregate [codegen id : 8] +Input [7]: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#23, s_store_name#24, i_item_id#26, i_item_desc#27] +Keys [4]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24] +Functions [3]: [partial_sum(ss_quantity#5), partial_sum(sr_return_quantity#11), partial_sum(cs_quantity#16)] +Aggregate Attributes [3]: [sum#28, sum#29, sum#30] +Results [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] + +(38) Exchange +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] +Arguments: hashpartitioning(i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(39) HashAggregate [codegen id : 9] +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum#31, sum#32, sum#33] +Keys [4]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24] +Functions [3]: [sum(ss_quantity#5), sum(sr_return_quantity#11), sum(cs_quantity#16)] +Aggregate Attributes [3]: [sum(ss_quantity#5)#34, sum(sr_return_quantity#11)#35, sum(cs_quantity#16)#36] +Results [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, sum(ss_quantity#5)#34 AS store_sales_quantity#37, sum(sr_return_quantity#11)#35 AS store_returns_quantity#38, sum(cs_quantity#16)#36 AS catalog_sales_quantity#39] + +(40) TakeOrderedAndProject +Input [7]: [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, store_sales_quantity#37, store_returns_quantity#38, catalog_sales_quantity#39] +Arguments: 100, [i_item_id#26 ASC NULLS FIRST, i_item_desc#27 ASC NULLS FIRST, s_store_id#23 ASC NULLS FIRST, s_store_name#24 ASC NULLS FIRST], [i_item_id#26, i_item_desc#27, s_store_id#23, s_store_name#24, store_sales_quantity#37, store_returns_quantity#38, catalog_sales_quantity#39] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (45) ++- * Project (44) + +- * Filter (43) + +- * ColumnarToRow (42) + +- CometScan parquet spark_catalog.default.date_dim (41) + + +(41) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#19, d_year#40, d_moy#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,9), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(42) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#19, d_year#40, d_moy#41] + +(43) Filter [codegen id : 1] +Input [3]: [d_date_sk#19, d_year#40, d_moy#41] +Condition : ((((isnotnull(d_moy#41) AND isnotnull(d_year#40)) AND (d_moy#41 = 9)) AND (d_year#40 = 1999)) AND isnotnull(d_date_sk#19)) + +(44) Project [codegen id : 1] +Output [1]: [d_date_sk#19] +Input [3]: [d_date_sk#19, d_year#40, d_moy#41] + +(45) BroadcastExchange +Input [1]: [d_date_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (50) ++- * Project (49) + +- * Filter (48) + +- * ColumnarToRow (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#20, d_year#42, d_moy#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), GreaterThanOrEqual(d_moy,9), LessThanOrEqual(d_moy,12), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#20, d_year#42, d_moy#43] + +(48) Filter [codegen id : 1] +Input [3]: [d_date_sk#20, d_year#42, d_moy#43] +Condition : (((((isnotnull(d_moy#43) AND isnotnull(d_year#42)) AND (d_moy#43 >= 9)) AND (d_moy#43 <= 12)) AND (d_year#42 = 1999)) AND isnotnull(d_date_sk#20)) + +(49) Project [codegen id : 1] +Output [1]: [d_date_sk#20] +Input [3]: [d_date_sk#20, d_year#42, d_moy#43] + +(50) BroadcastExchange +Input [1]: [d_date_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:3 Hosting operator id = 10 Hosting Expression = cs_sold_date_sk#17 IN dynamicpruning#18 +BroadcastExchange (55) ++- * Project (54) + +- * Filter (53) + +- * ColumnarToRow (52) + +- CometScan parquet spark_catalog.default.date_dim (51) + + +(51) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#21, d_year#44] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(52) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#21, d_year#44] + +(53) Filter [codegen id : 1] +Input [2]: [d_date_sk#21, d_year#44] +Condition : (d_year#44 IN (1999,2000,2001) AND isnotnull(d_date_sk#21)) + +(54) Project [codegen id : 1] +Output [1]: [d_date_sk#21] +Input [2]: [d_date_sk#21, d_year#44] + +(55) BroadcastExchange +Input [1]: [d_date_sk#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt new file mode 100644 index 000000000..101893d07 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt @@ -0,0 +1,83 @@ +TakeOrderedAndProject [i_item_id,i_item_desc,s_store_id,s_store_name,store_sales_quantity,store_returns_quantity,catalog_sales_quantity] + WholeStageCodegen (9) + HashAggregate [i_item_id,i_item_desc,s_store_id,s_store_name,sum,sum,sum] [sum(ss_quantity),sum(sr_return_quantity),sum(cs_quantity),store_sales_quantity,store_returns_quantity,catalog_sales_quantity,sum,sum,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,s_store_id,s_store_name] #1 + WholeStageCodegen (8) + HashAggregate [i_item_id,i_item_desc,s_store_id,s_store_name,ss_quantity,sr_return_quantity,cs_quantity] [sum,sum,sum,sum,sum,sum] + Project [ss_quantity,sr_return_quantity,cs_quantity,s_store_id,s_store_name,i_item_id,i_item_desc] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,sr_return_quantity,cs_quantity,s_store_id,s_store_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,cs_quantity] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,sr_return_quantity,sr_returned_date_sk,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sold_date_sk,sr_return_quantity,sr_returned_date_sk,cs_quantity,cs_sold_date_sk] + BroadcastHashJoin [sr_customer_sk,sr_item_sk,cs_bill_customer_sk,cs_item_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sold_date_sk,sr_item_sk,sr_customer_sk,sr_return_quantity,sr_returned_date_sk] + BroadcastHashJoin [ss_customer_sk,ss_item_sk,ss_ticket_number,sr_customer_sk,sr_item_sk,sr_ticket_number] + Filter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_quantity,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_moy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [sr_customer_sk,sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_return_quantity,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_moy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + Filter [cs_bill_customer_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #3 + BroadcastExchange #6 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (7) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt new file mode 100644 index 000000000..6fdc0d461 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt @@ -0,0 +1,125 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * HashAggregate (20) + +- Exchange (19) + +- * HashAggregate (18) + +- * Project (17) + +- * BroadcastHashJoin Inner BuildRight (16) + :- * Project (10) + : +- * BroadcastHashJoin Inner BuildRight (9) + : :- * Project (4) + : : +- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.date_dim (1) + : +- BroadcastExchange (8) + : +- * Filter (7) + : +- * ColumnarToRow (6) + : +- CometScan parquet spark_catalog.default.store_sales (5) + +- BroadcastExchange (15) + +- * Project (14) + +- * Filter (13) + +- * ColumnarToRow (12) + +- CometScan parquet spark_catalog.default.item (11) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_moy#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), EqualTo(d_moy,11), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] + +(3) Filter [codegen id : 3] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Condition : ((isnotnull(d_moy#3) AND (d_moy#3 = 11)) AND isnotnull(d_date_sk#1)) + +(4) Project [codegen id : 3] +Output [2]: [d_date_sk#1, d_year#2] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] + +(5) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(7) Filter [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) + +(8) BroadcastExchange +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#6] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [3]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5] +Input [5]: [d_date_sk#1, d_year#2, ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(11) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manufact_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manufact_id), EqualTo(i_manufact_id,128), IsNotNull(i_item_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manufact_id#10] + +(13) Filter [codegen id : 2] +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manufact_id#10] +Condition : ((isnotnull(i_manufact_id#10) AND (i_manufact_id#10 = 128)) AND isnotnull(i_item_sk#7)) + +(14) Project [codegen id : 2] +Output [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manufact_id#10] + +(15) BroadcastExchange +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#4] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [4]: [d_year#2, ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Input [6]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5, i_item_sk#7, i_brand_id#8, i_brand#9] + +(18) HashAggregate [codegen id : 3] +Input [4]: [d_year#2, ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Keys [3]: [d_year#2, i_brand#9, i_brand_id#8] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum#11] +Results [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] + +(19) Exchange +Input [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] +Arguments: hashpartitioning(d_year#2, i_brand#9, i_brand_id#8, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 4] +Input [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] +Keys [3]: [d_year#2, i_brand#9, i_brand_id#8] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#5))#13] +Results [4]: [d_year#2, i_brand_id#8 AS brand_id#14, i_brand#9 AS brand#15, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#13,17,2) AS sum_agg#16] + +(21) TakeOrderedAndProject +Input [4]: [d_year#2, brand_id#14, brand#15, sum_agg#16] +Arguments: 100, [d_year#2 ASC NULLS FIRST, sum_agg#16 DESC NULLS LAST, brand_id#14 ASC NULLS FIRST], [d_year#2, brand_id#14, brand#15, sum_agg#16] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt new file mode 100644 index 000000000..a869b17dd --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt @@ -0,0 +1,31 @@ +TakeOrderedAndProject [d_year,sum_agg,brand_id,brand] + WholeStageCodegen (4) + HashAggregate [d_year,i_brand,i_brand_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),brand_id,brand,sum_agg,sum] + InputAdapter + Exchange [d_year,i_brand,i_brand_id] #1 + WholeStageCodegen (3) + HashAggregate [d_year,i_brand,i_brand_id,ss_ext_sales_price] [sum,sum] + Project [d_year,ss_ext_sales_price,i_brand_id,i_brand] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [d_year,ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + Project [d_date_sk,d_year] + Filter [d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [i_item_sk,i_brand_id,i_brand] + Filter [i_manufact_id,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manufact_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt new file mode 100644 index 000000000..344c57efd --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt @@ -0,0 +1,324 @@ +== Physical Plan == +TakeOrderedAndProject (49) ++- * Project (48) + +- * BroadcastHashJoin Inner BuildRight (47) + :- * Project (41) + : +- * BroadcastHashJoin Inner BuildRight (40) + : :- * Project (35) + : : +- * BroadcastHashJoin Inner BuildRight (34) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (6) + : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.web_returns (1) + : : : : +- ReusedExchange (4) + : : : +- BroadcastExchange (10) + : : : +- * Filter (9) + : : : +- * ColumnarToRow (8) + : : : +- CometScan parquet spark_catalog.default.customer_address (7) + : : +- BroadcastExchange (33) + : : +- * Filter (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * HashAggregate (28) + : : +- Exchange (27) + : : +- * HashAggregate (26) + : : +- * Project (25) + : : +- * BroadcastHashJoin Inner BuildRight (24) + : : :- * Project (22) + : : : +- * BroadcastHashJoin Inner BuildRight (21) + : : : :- * Filter (19) + : : : : +- * ColumnarToRow (18) + : : : : +- CometScan parquet spark_catalog.default.web_returns (17) + : : : +- ReusedExchange (20) + : : +- ReusedExchange (23) + : +- BroadcastExchange (39) + : +- * Filter (38) + : +- * ColumnarToRow (37) + : +- CometScan parquet spark_catalog.default.customer (36) + +- BroadcastExchange (46) + +- * Project (45) + +- * Filter (44) + +- * ColumnarToRow (43) + +- CometScan parquet spark_catalog.default.customer_address (42) + + +(1) Scan parquet spark_catalog.default.web_returns +Output [4]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, wr_returned_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#4), dynamicpruningexpression(wr_returned_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(wr_returning_addr_sk), IsNotNull(wr_returning_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [4]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, wr_returned_date_sk#4] + +(3) Filter [codegen id : 3] +Input [4]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, wr_returned_date_sk#4] +Condition : (isnotnull(wr_returning_addr_sk#2) AND isnotnull(wr_returning_customer_sk#1)) + +(4) ReusedExchange [Reuses operator id: 54] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [wr_returned_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [3]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3] +Input [5]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, wr_returned_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_state#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_state)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_state#8] + +(9) Filter [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_state#8] +Condition : (isnotnull(ca_address_sk#7) AND isnotnull(ca_state#8)) + +(10) BroadcastExchange +Input [2]: [ca_address_sk#7, ca_state#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [wr_returning_addr_sk#2] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [wr_returning_customer_sk#1, wr_return_amt#3, ca_state#8] +Input [5]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, ca_address_sk#7, ca_state#8] + +(13) HashAggregate [codegen id : 3] +Input [3]: [wr_returning_customer_sk#1, wr_return_amt#3, ca_state#8] +Keys [2]: [wr_returning_customer_sk#1, ca_state#8] +Functions [1]: [partial_sum(UnscaledValue(wr_return_amt#3))] +Aggregate Attributes [1]: [sum#9] +Results [3]: [wr_returning_customer_sk#1, ca_state#8, sum#10] + +(14) Exchange +Input [3]: [wr_returning_customer_sk#1, ca_state#8, sum#10] +Arguments: hashpartitioning(wr_returning_customer_sk#1, ca_state#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 11] +Input [3]: [wr_returning_customer_sk#1, ca_state#8, sum#10] +Keys [2]: [wr_returning_customer_sk#1, ca_state#8] +Functions [1]: [sum(UnscaledValue(wr_return_amt#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(wr_return_amt#3))#11] +Results [3]: [wr_returning_customer_sk#1 AS ctr_customer_sk#12, ca_state#8 AS ctr_state#13, MakeDecimal(sum(UnscaledValue(wr_return_amt#3))#11,17,2) AS ctr_total_return#14] + +(16) Filter [codegen id : 11] +Input [3]: [ctr_customer_sk#12, ctr_state#13, ctr_total_return#14] +Condition : isnotnull(ctr_total_return#14) + +(17) Scan parquet spark_catalog.default.web_returns +Output [4]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, wr_returned_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#18), dynamicpruningexpression(wr_returned_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(wr_returning_addr_sk)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 6] +Input [4]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, wr_returned_date_sk#18] + +(19) Filter [codegen id : 6] +Input [4]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, wr_returned_date_sk#18] +Condition : isnotnull(wr_returning_addr_sk#16) + +(20) ReusedExchange [Reuses operator id: 54] +Output [1]: [d_date_sk#20] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [wr_returned_date_sk#18] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [3]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17] +Input [5]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, wr_returned_date_sk#18, d_date_sk#20] + +(23) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#21, ca_state#22] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [wr_returning_addr_sk#16] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [3]: [wr_returning_customer_sk#15, wr_return_amt#17, ca_state#22] +Input [5]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, ca_address_sk#21, ca_state#22] + +(26) HashAggregate [codegen id : 6] +Input [3]: [wr_returning_customer_sk#15, wr_return_amt#17, ca_state#22] +Keys [2]: [wr_returning_customer_sk#15, ca_state#22] +Functions [1]: [partial_sum(UnscaledValue(wr_return_amt#17))] +Aggregate Attributes [1]: [sum#23] +Results [3]: [wr_returning_customer_sk#15, ca_state#22, sum#24] + +(27) Exchange +Input [3]: [wr_returning_customer_sk#15, ca_state#22, sum#24] +Arguments: hashpartitioning(wr_returning_customer_sk#15, ca_state#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(28) HashAggregate [codegen id : 7] +Input [3]: [wr_returning_customer_sk#15, ca_state#22, sum#24] +Keys [2]: [wr_returning_customer_sk#15, ca_state#22] +Functions [1]: [sum(UnscaledValue(wr_return_amt#17))] +Aggregate Attributes [1]: [sum(UnscaledValue(wr_return_amt#17))#11] +Results [2]: [ca_state#22 AS ctr_state#25, MakeDecimal(sum(UnscaledValue(wr_return_amt#17))#11,17,2) AS ctr_total_return#26] + +(29) HashAggregate [codegen id : 7] +Input [2]: [ctr_state#25, ctr_total_return#26] +Keys [1]: [ctr_state#25] +Functions [1]: [partial_avg(ctr_total_return#26)] +Aggregate Attributes [2]: [sum#27, count#28] +Results [3]: [ctr_state#25, sum#29, count#30] + +(30) Exchange +Input [3]: [ctr_state#25, sum#29, count#30] +Arguments: hashpartitioning(ctr_state#25, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 8] +Input [3]: [ctr_state#25, sum#29, count#30] +Keys [1]: [ctr_state#25] +Functions [1]: [avg(ctr_total_return#26)] +Aggregate Attributes [1]: [avg(ctr_total_return#26)#31] +Results [2]: [(avg(ctr_total_return#26)#31 * 1.2) AS (avg(ctr_total_return) * 1.2)#32, ctr_state#25] + +(32) Filter [codegen id : 8] +Input [2]: [(avg(ctr_total_return) * 1.2)#32, ctr_state#25] +Condition : isnotnull((avg(ctr_total_return) * 1.2)#32) + +(33) BroadcastExchange +Input [2]: [(avg(ctr_total_return) * 1.2)#32, ctr_state#25] +Arguments: HashedRelationBroadcastMode(List(input[1, string, true]),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ctr_state#13] +Right keys [1]: [ctr_state#25] +Join type: Inner +Join condition: (cast(ctr_total_return#14 as decimal(24,7)) > (avg(ctr_total_return) * 1.2)#32) + +(35) Project [codegen id : 11] +Output [2]: [ctr_customer_sk#12, ctr_total_return#14] +Input [5]: [ctr_customer_sk#12, ctr_state#13, ctr_total_return#14, (avg(ctr_total_return) * 1.2)#32, ctr_state#25] + +(36) Scan parquet spark_catalog.default.customer +Output [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(37) ColumnarToRow [codegen id : 9] +Input [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] + +(38) Filter [codegen id : 9] +Input [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] +Condition : (isnotnull(c_customer_sk#33) AND isnotnull(c_current_addr_sk#35)) + +(39) BroadcastExchange +Input [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(40) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ctr_customer_sk#12] +Right keys [1]: [c_customer_sk#33] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 11] +Output [14]: [ctr_total_return#14, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] +Input [16]: [ctr_customer_sk#12, ctr_total_return#14, c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] + +(42) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#47, ca_state#48] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,GA), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(43) ColumnarToRow [codegen id : 10] +Input [2]: [ca_address_sk#47, ca_state#48] + +(44) Filter [codegen id : 10] +Input [2]: [ca_address_sk#47, ca_state#48] +Condition : ((isnotnull(ca_state#48) AND (ca_state#48 = GA)) AND isnotnull(ca_address_sk#47)) + +(45) Project [codegen id : 10] +Output [1]: [ca_address_sk#47] +Input [2]: [ca_address_sk#47, ca_state#48] + +(46) BroadcastExchange +Input [1]: [ca_address_sk#47] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(47) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [c_current_addr_sk#35] +Right keys [1]: [ca_address_sk#47] +Join type: Inner +Join condition: None + +(48) Project [codegen id : 11] +Output [13]: [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46, ctr_total_return#14] +Input [15]: [ctr_total_return#14, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46, ca_address_sk#47] + +(49) TakeOrderedAndProject +Input [13]: [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46, ctr_total_return#14] +Arguments: 100, [c_customer_id#34 ASC NULLS FIRST, c_salutation#36 ASC NULLS FIRST, c_first_name#37 ASC NULLS FIRST, c_last_name#38 ASC NULLS FIRST, c_preferred_cust_flag#39 ASC NULLS FIRST, c_birth_day#40 ASC NULLS FIRST, c_birth_month#41 ASC NULLS FIRST, c_birth_year#42 ASC NULLS FIRST, c_birth_country#43 ASC NULLS FIRST, c_login#44 ASC NULLS FIRST, c_email_address#45 ASC NULLS FIRST, c_last_review_date#46 ASC NULLS FIRST, ctr_total_return#14 ASC NULLS FIRST], [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46, ctr_total_return#14] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = wr_returned_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (54) ++- * Project (53) + +- * Filter (52) + +- * ColumnarToRow (51) + +- CometScan parquet spark_catalog.default.date_dim (50) + + +(50) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_year#49] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(51) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#6, d_year#49] + +(52) Filter [codegen id : 1] +Input [2]: [d_date_sk#6, d_year#49] +Condition : ((isnotnull(d_year#49) AND (d_year#49 = 2002)) AND isnotnull(d_date_sk#6)) + +(53) Project [codegen id : 1] +Output [1]: [d_date_sk#6] +Input [2]: [d_date_sk#6, d_year#49] + +(54) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 17 Hosting Expression = wr_returned_date_sk#18 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/simplified.txt new file mode 100644 index 000000000..b0935ef25 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address,c_last_review_date,ctr_total_return] + WholeStageCodegen (11) + Project [c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address,c_last_review_date,ctr_total_return] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ctr_total_return,c_customer_id,c_current_addr_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address,c_last_review_date] + BroadcastHashJoin [ctr_customer_sk,c_customer_sk] + Project [ctr_customer_sk,ctr_total_return] + BroadcastHashJoin [ctr_state,ctr_state,ctr_total_return,(avg(ctr_total_return) * 1.2)] + Filter [ctr_total_return] + HashAggregate [wr_returning_customer_sk,ca_state,sum] [sum(UnscaledValue(wr_return_amt)),ctr_customer_sk,ctr_state,ctr_total_return,sum] + InputAdapter + Exchange [wr_returning_customer_sk,ca_state] #1 + WholeStageCodegen (3) + HashAggregate [wr_returning_customer_sk,ca_state,wr_return_amt] [sum,sum] + Project [wr_returning_customer_sk,wr_return_amt,ca_state] + BroadcastHashJoin [wr_returning_addr_sk,ca_address_sk] + Project [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt] + BroadcastHashJoin [wr_returned_date_sk,d_date_sk] + Filter [wr_returning_addr_sk,wr_returning_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt,wr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [ca_address_sk,ca_state] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (8) + Filter [(avg(ctr_total_return) * 1.2)] + HashAggregate [ctr_state,sum,count] [avg(ctr_total_return),(avg(ctr_total_return) * 1.2),sum,count] + InputAdapter + Exchange [ctr_state] #5 + WholeStageCodegen (7) + HashAggregate [ctr_state,ctr_total_return] [sum,count,sum,count] + HashAggregate [wr_returning_customer_sk,ca_state,sum] [sum(UnscaledValue(wr_return_amt)),ctr_state,ctr_total_return,sum] + InputAdapter + Exchange [wr_returning_customer_sk,ca_state] #6 + WholeStageCodegen (6) + HashAggregate [wr_returning_customer_sk,ca_state,wr_return_amt] [sum,sum] + Project [wr_returning_customer_sk,wr_return_amt,ca_state] + BroadcastHashJoin [wr_returning_addr_sk,ca_address_sk] + Project [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt] + BroadcastHashJoin [wr_returned_date_sk,d_date_sk] + Filter [wr_returning_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [ca_address_sk,ca_state] #3 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (9) + Filter [c_customer_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_current_addr_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address,c_last_review_date] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (10) + Project [ca_address_sk] + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/explain.txt new file mode 100644 index 000000000..4810517ca --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/explain.txt @@ -0,0 +1,616 @@ +== Physical Plan == +* Sort (90) ++- Exchange (89) + +- * Project (88) + +- * BroadcastHashJoin Inner BuildRight (87) + :- * Project (73) + : +- * BroadcastHashJoin Inner BuildRight (72) + : :- * BroadcastHashJoin Inner BuildRight (58) + : : :- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * BroadcastHashJoin Inner BuildRight (29) + : : : : :- * HashAggregate (15) + : : : : : +- Exchange (14) + : : : : : +- * HashAggregate (13) + : : : : : +- * Project (12) + : : : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : : : :- * Project (6) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : : : :- * Filter (3) + : : : : : : : +- * ColumnarToRow (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- ReusedExchange (4) + : : : : : +- BroadcastExchange (10) + : : : : : +- * Filter (9) + : : : : : +- * ColumnarToRow (8) + : : : : : +- CometScan parquet spark_catalog.default.customer_address (7) + : : : : +- BroadcastExchange (28) + : : : : +- * HashAggregate (27) + : : : : +- Exchange (26) + : : : : +- * HashAggregate (25) + : : : : +- * Project (24) + : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : :- * Project (21) + : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : :- * Filter (18) + : : : : : : +- * ColumnarToRow (17) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (16) + : : : : : +- ReusedExchange (19) + : : : : +- ReusedExchange (22) + : : : +- BroadcastExchange (42) + : : : +- * HashAggregate (41) + : : : +- Exchange (40) + : : : +- * HashAggregate (39) + : : : +- * Project (38) + : : : +- * BroadcastHashJoin Inner BuildRight (37) + : : : :- * Project (35) + : : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : : :- * Filter (32) + : : : : : +- * ColumnarToRow (31) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (30) + : : : : +- ReusedExchange (33) + : : : +- ReusedExchange (36) + : : +- BroadcastExchange (57) + : : +- * HashAggregate (56) + : : +- Exchange (55) + : : +- * HashAggregate (54) + : : +- * Project (53) + : : +- * BroadcastHashJoin Inner BuildRight (52) + : : :- * Project (50) + : : : +- * BroadcastHashJoin Inner BuildRight (49) + : : : :- * Filter (47) + : : : : +- * ColumnarToRow (46) + : : : : +- CometScan parquet spark_catalog.default.web_sales (45) + : : : +- ReusedExchange (48) + : : +- ReusedExchange (51) + : +- BroadcastExchange (71) + : +- * HashAggregate (70) + : +- Exchange (69) + : +- * HashAggregate (68) + : +- * Project (67) + : +- * BroadcastHashJoin Inner BuildRight (66) + : :- * Project (64) + : : +- * BroadcastHashJoin Inner BuildRight (63) + : : :- * Filter (61) + : : : +- * ColumnarToRow (60) + : : : +- CometScan parquet spark_catalog.default.web_sales (59) + : : +- ReusedExchange (62) + : +- ReusedExchange (65) + +- BroadcastExchange (86) + +- * HashAggregate (85) + +- Exchange (84) + +- * HashAggregate (83) + +- * Project (82) + +- * BroadcastHashJoin Inner BuildRight (81) + :- * Project (79) + : +- * BroadcastHashJoin Inner BuildRight (78) + : :- * Filter (76) + : : +- * ColumnarToRow (75) + : : +- CometScan parquet spark_catalog.default.web_sales (74) + : +- ReusedExchange (77) + +- ReusedExchange (80) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_addr_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [ss_addr_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] + +(3) Filter [codegen id : 3] +Input [3]: [ss_addr_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_addr_sk#1) + +(4) ReusedExchange [Reuses operator id: 94] +Output [3]: [d_date_sk#5, d_year#6, d_qoy#7] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [4]: [ss_addr_sk#1, ss_ext_sales_price#2, d_year#6, d_qoy#7] +Input [6]: [ss_addr_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3, d_date_sk#5, d_year#6, d_qoy#7] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#8, ca_county#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_county)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#8, ca_county#9] + +(9) Filter [codegen id : 2] +Input [2]: [ca_address_sk#8, ca_county#9] +Condition : (isnotnull(ca_address_sk#8) AND isnotnull(ca_county#9)) + +(10) BroadcastExchange +Input [2]: [ca_address_sk#8, ca_county#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_addr_sk#1] +Right keys [1]: [ca_address_sk#8] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [4]: [ss_ext_sales_price#2, d_year#6, d_qoy#7, ca_county#9] +Input [6]: [ss_addr_sk#1, ss_ext_sales_price#2, d_year#6, d_qoy#7, ca_address_sk#8, ca_county#9] + +(13) HashAggregate [codegen id : 3] +Input [4]: [ss_ext_sales_price#2, d_year#6, d_qoy#7, ca_county#9] +Keys [3]: [ca_county#9, d_qoy#7, d_year#6] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#10] +Results [4]: [ca_county#9, d_qoy#7, d_year#6, sum#11] + +(14) Exchange +Input [4]: [ca_county#9, d_qoy#7, d_year#6, sum#11] +Arguments: hashpartitioning(ca_county#9, d_qoy#7, d_year#6, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 24] +Input [4]: [ca_county#9, d_qoy#7, d_year#6, sum#11] +Keys [3]: [ca_county#9, d_qoy#7, d_year#6] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#2))#12] +Results [3]: [ca_county#9, d_year#6, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#12,17,2) AS store_sales#13] + +(16) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_addr_sk#14, ss_ext_sales_price#15, ss_sold_date_sk#16] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#16), dynamicpruningexpression(ss_sold_date_sk#16 IN dynamicpruning#17)] +PushedFilters: [IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 6] +Input [3]: [ss_addr_sk#14, ss_ext_sales_price#15, ss_sold_date_sk#16] + +(18) Filter [codegen id : 6] +Input [3]: [ss_addr_sk#14, ss_ext_sales_price#15, ss_sold_date_sk#16] +Condition : isnotnull(ss_addr_sk#14) + +(19) ReusedExchange [Reuses operator id: 98] +Output [3]: [d_date_sk#18, d_year#19, d_qoy#20] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#16] +Right keys [1]: [d_date_sk#18] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [4]: [ss_addr_sk#14, ss_ext_sales_price#15, d_year#19, d_qoy#20] +Input [6]: [ss_addr_sk#14, ss_ext_sales_price#15, ss_sold_date_sk#16, d_date_sk#18, d_year#19, d_qoy#20] + +(22) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#21, ca_county#22] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_addr_sk#14] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [4]: [ss_ext_sales_price#15, d_year#19, d_qoy#20, ca_county#22] +Input [6]: [ss_addr_sk#14, ss_ext_sales_price#15, d_year#19, d_qoy#20, ca_address_sk#21, ca_county#22] + +(25) HashAggregate [codegen id : 6] +Input [4]: [ss_ext_sales_price#15, d_year#19, d_qoy#20, ca_county#22] +Keys [3]: [ca_county#22, d_qoy#20, d_year#19] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#15))] +Aggregate Attributes [1]: [sum#23] +Results [4]: [ca_county#22, d_qoy#20, d_year#19, sum#24] + +(26) Exchange +Input [4]: [ca_county#22, d_qoy#20, d_year#19, sum#24] +Arguments: hashpartitioning(ca_county#22, d_qoy#20, d_year#19, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 7] +Input [4]: [ca_county#22, d_qoy#20, d_year#19, sum#24] +Keys [3]: [ca_county#22, d_qoy#20, d_year#19] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#15))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#15))#12] +Results [2]: [ca_county#22, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#15))#12,17,2) AS store_sales#25] + +(28) BroadcastExchange +Input [2]: [ca_county#22, store_sales#25] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ca_county#9] +Right keys [1]: [ca_county#22] +Join type: Inner +Join condition: None + +(30) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_addr_sk#26, ss_ext_sales_price#27, ss_sold_date_sk#28] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#28), dynamicpruningexpression(ss_sold_date_sk#28 IN dynamicpruning#29)] +PushedFilters: [IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 10] +Input [3]: [ss_addr_sk#26, ss_ext_sales_price#27, ss_sold_date_sk#28] + +(32) Filter [codegen id : 10] +Input [3]: [ss_addr_sk#26, ss_ext_sales_price#27, ss_sold_date_sk#28] +Condition : isnotnull(ss_addr_sk#26) + +(33) ReusedExchange [Reuses operator id: 102] +Output [3]: [d_date_sk#30, d_year#31, d_qoy#32] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_sold_date_sk#28] +Right keys [1]: [d_date_sk#30] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [4]: [ss_addr_sk#26, ss_ext_sales_price#27, d_year#31, d_qoy#32] +Input [6]: [ss_addr_sk#26, ss_ext_sales_price#27, ss_sold_date_sk#28, d_date_sk#30, d_year#31, d_qoy#32] + +(36) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#33, ca_county#34] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_addr_sk#26] +Right keys [1]: [ca_address_sk#33] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [4]: [ss_ext_sales_price#27, d_year#31, d_qoy#32, ca_county#34] +Input [6]: [ss_addr_sk#26, ss_ext_sales_price#27, d_year#31, d_qoy#32, ca_address_sk#33, ca_county#34] + +(39) HashAggregate [codegen id : 10] +Input [4]: [ss_ext_sales_price#27, d_year#31, d_qoy#32, ca_county#34] +Keys [3]: [ca_county#34, d_qoy#32, d_year#31] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#27))] +Aggregate Attributes [1]: [sum#35] +Results [4]: [ca_county#34, d_qoy#32, d_year#31, sum#36] + +(40) Exchange +Input [4]: [ca_county#34, d_qoy#32, d_year#31, sum#36] +Arguments: hashpartitioning(ca_county#34, d_qoy#32, d_year#31, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(41) HashAggregate [codegen id : 11] +Input [4]: [ca_county#34, d_qoy#32, d_year#31, sum#36] +Keys [3]: [ca_county#34, d_qoy#32, d_year#31] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#27))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#27))#12] +Results [2]: [ca_county#34, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#27))#12,17,2) AS store_sales#37] + +(42) BroadcastExchange +Input [2]: [ca_county#34, store_sales#37] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ca_county#22] +Right keys [1]: [ca_county#34] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 24] +Output [5]: [ca_county#9, d_year#6, store_sales#13, store_sales#25, store_sales#37] +Input [7]: [ca_county#9, d_year#6, store_sales#13, ca_county#22, store_sales#25, ca_county#34, store_sales#37] + +(45) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, ws_sold_date_sk#40] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#40), dynamicpruningexpression(ws_sold_date_sk#40 IN dynamicpruning#41)] +PushedFilters: [IsNotNull(ws_bill_addr_sk)] +ReadSchema: struct + +(46) ColumnarToRow [codegen id : 14] +Input [3]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, ws_sold_date_sk#40] + +(47) Filter [codegen id : 14] +Input [3]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, ws_sold_date_sk#40] +Condition : isnotnull(ws_bill_addr_sk#38) + +(48) ReusedExchange [Reuses operator id: 94] +Output [3]: [d_date_sk#42, d_year#43, d_qoy#44] + +(49) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_sold_date_sk#40] +Right keys [1]: [d_date_sk#42] +Join type: Inner +Join condition: None + +(50) Project [codegen id : 14] +Output [4]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, d_year#43, d_qoy#44] +Input [6]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, ws_sold_date_sk#40, d_date_sk#42, d_year#43, d_qoy#44] + +(51) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#45, ca_county#46] + +(52) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_bill_addr_sk#38] +Right keys [1]: [ca_address_sk#45] +Join type: Inner +Join condition: None + +(53) Project [codegen id : 14] +Output [4]: [ws_ext_sales_price#39, d_year#43, d_qoy#44, ca_county#46] +Input [6]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, d_year#43, d_qoy#44, ca_address_sk#45, ca_county#46] + +(54) HashAggregate [codegen id : 14] +Input [4]: [ws_ext_sales_price#39, d_year#43, d_qoy#44, ca_county#46] +Keys [3]: [ca_county#46, d_qoy#44, d_year#43] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#39))] +Aggregate Attributes [1]: [sum#47] +Results [4]: [ca_county#46, d_qoy#44, d_year#43, sum#48] + +(55) Exchange +Input [4]: [ca_county#46, d_qoy#44, d_year#43, sum#48] +Arguments: hashpartitioning(ca_county#46, d_qoy#44, d_year#43, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(56) HashAggregate [codegen id : 15] +Input [4]: [ca_county#46, d_qoy#44, d_year#43, sum#48] +Keys [3]: [ca_county#46, d_qoy#44, d_year#43] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#39))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#39))#49] +Results [2]: [ca_county#46, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#39))#49,17,2) AS web_sales#50] + +(57) BroadcastExchange +Input [2]: [ca_county#46, web_sales#50] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(58) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ca_county#9] +Right keys [1]: [ca_county#46] +Join type: Inner +Join condition: None + +(59) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, ws_sold_date_sk#53] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#53), dynamicpruningexpression(ws_sold_date_sk#53 IN dynamicpruning#54)] +PushedFilters: [IsNotNull(ws_bill_addr_sk)] +ReadSchema: struct + +(60) ColumnarToRow [codegen id : 18] +Input [3]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, ws_sold_date_sk#53] + +(61) Filter [codegen id : 18] +Input [3]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, ws_sold_date_sk#53] +Condition : isnotnull(ws_bill_addr_sk#51) + +(62) ReusedExchange [Reuses operator id: 98] +Output [3]: [d_date_sk#55, d_year#56, d_qoy#57] + +(63) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ws_sold_date_sk#53] +Right keys [1]: [d_date_sk#55] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 18] +Output [4]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, d_year#56, d_qoy#57] +Input [6]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, ws_sold_date_sk#53, d_date_sk#55, d_year#56, d_qoy#57] + +(65) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#58, ca_county#59] + +(66) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ws_bill_addr_sk#51] +Right keys [1]: [ca_address_sk#58] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 18] +Output [4]: [ws_ext_sales_price#52, d_year#56, d_qoy#57, ca_county#59] +Input [6]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, d_year#56, d_qoy#57, ca_address_sk#58, ca_county#59] + +(68) HashAggregate [codegen id : 18] +Input [4]: [ws_ext_sales_price#52, d_year#56, d_qoy#57, ca_county#59] +Keys [3]: [ca_county#59, d_qoy#57, d_year#56] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#52))] +Aggregate Attributes [1]: [sum#60] +Results [4]: [ca_county#59, d_qoy#57, d_year#56, sum#61] + +(69) Exchange +Input [4]: [ca_county#59, d_qoy#57, d_year#56, sum#61] +Arguments: hashpartitioning(ca_county#59, d_qoy#57, d_year#56, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(70) HashAggregate [codegen id : 19] +Input [4]: [ca_county#59, d_qoy#57, d_year#56, sum#61] +Keys [3]: [ca_county#59, d_qoy#57, d_year#56] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#52))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#52))#49] +Results [2]: [ca_county#59, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#52))#49,17,2) AS web_sales#62] + +(71) BroadcastExchange +Input [2]: [ca_county#59, web_sales#62] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=10] + +(72) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ca_county#46] +Right keys [1]: [ca_county#59] +Join type: Inner +Join condition: (CASE WHEN (web_sales#50 > 0.00) THEN (web_sales#62 / web_sales#50) END > CASE WHEN (store_sales#13 > 0.00) THEN (store_sales#25 / store_sales#13) END) + +(73) Project [codegen id : 24] +Output [8]: [ca_county#9, d_year#6, store_sales#13, store_sales#25, store_sales#37, ca_county#46, web_sales#50, web_sales#62] +Input [9]: [ca_county#9, d_year#6, store_sales#13, store_sales#25, store_sales#37, ca_county#46, web_sales#50, ca_county#59, web_sales#62] + +(74) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, ws_sold_date_sk#65] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#65), dynamicpruningexpression(ws_sold_date_sk#65 IN dynamicpruning#66)] +PushedFilters: [IsNotNull(ws_bill_addr_sk)] +ReadSchema: struct + +(75) ColumnarToRow [codegen id : 22] +Input [3]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, ws_sold_date_sk#65] + +(76) Filter [codegen id : 22] +Input [3]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, ws_sold_date_sk#65] +Condition : isnotnull(ws_bill_addr_sk#63) + +(77) ReusedExchange [Reuses operator id: 102] +Output [3]: [d_date_sk#67, d_year#68, d_qoy#69] + +(78) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [ws_sold_date_sk#65] +Right keys [1]: [d_date_sk#67] +Join type: Inner +Join condition: None + +(79) Project [codegen id : 22] +Output [4]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, d_year#68, d_qoy#69] +Input [6]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, ws_sold_date_sk#65, d_date_sk#67, d_year#68, d_qoy#69] + +(80) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#70, ca_county#71] + +(81) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [ws_bill_addr_sk#63] +Right keys [1]: [ca_address_sk#70] +Join type: Inner +Join condition: None + +(82) Project [codegen id : 22] +Output [4]: [ws_ext_sales_price#64, d_year#68, d_qoy#69, ca_county#71] +Input [6]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, d_year#68, d_qoy#69, ca_address_sk#70, ca_county#71] + +(83) HashAggregate [codegen id : 22] +Input [4]: [ws_ext_sales_price#64, d_year#68, d_qoy#69, ca_county#71] +Keys [3]: [ca_county#71, d_qoy#69, d_year#68] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#64))] +Aggregate Attributes [1]: [sum#72] +Results [4]: [ca_county#71, d_qoy#69, d_year#68, sum#73] + +(84) Exchange +Input [4]: [ca_county#71, d_qoy#69, d_year#68, sum#73] +Arguments: hashpartitioning(ca_county#71, d_qoy#69, d_year#68, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(85) HashAggregate [codegen id : 23] +Input [4]: [ca_county#71, d_qoy#69, d_year#68, sum#73] +Keys [3]: [ca_county#71, d_qoy#69, d_year#68] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#64))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#64))#49] +Results [2]: [ca_county#71, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#64))#49,17,2) AS web_sales#74] + +(86) BroadcastExchange +Input [2]: [ca_county#71, web_sales#74] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=12] + +(87) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [ca_county#46] +Right keys [1]: [ca_county#71] +Join type: Inner +Join condition: (CASE WHEN (web_sales#62 > 0.00) THEN (web_sales#74 / web_sales#62) END > CASE WHEN (store_sales#25 > 0.00) THEN (store_sales#37 / store_sales#25) END) + +(88) Project [codegen id : 24] +Output [6]: [ca_county#9, d_year#6, (web_sales#62 / web_sales#50) AS web_q1_q2_increase#75, (store_sales#25 / store_sales#13) AS store_q1_q2_increase#76, (web_sales#74 / web_sales#62) AS web_q2_q3_increase#77, (store_sales#37 / store_sales#25) AS store_q2_q3_increase#78] +Input [10]: [ca_county#9, d_year#6, store_sales#13, store_sales#25, store_sales#37, ca_county#46, web_sales#50, web_sales#62, ca_county#71, web_sales#74] + +(89) Exchange +Input [6]: [ca_county#9, d_year#6, web_q1_q2_increase#75, store_q1_q2_increase#76, web_q2_q3_increase#77, store_q2_q3_increase#78] +Arguments: rangepartitioning(ca_county#9 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(90) Sort [codegen id : 25] +Input [6]: [ca_county#9, d_year#6, web_q1_q2_increase#75, store_q1_q2_increase#76, web_q2_q3_increase#77, store_q2_q3_increase#78] +Arguments: [ca_county#9 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (94) ++- * Filter (93) + +- * ColumnarToRow (92) + +- CometScan parquet spark_catalog.default.date_dim (91) + + +(91) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#5, d_year#6, d_qoy#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,1), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(92) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#5, d_year#6, d_qoy#7] + +(93) Filter [codegen id : 1] +Input [3]: [d_date_sk#5, d_year#6, d_qoy#7] +Condition : ((((isnotnull(d_qoy#7) AND isnotnull(d_year#6)) AND (d_qoy#7 = 1)) AND (d_year#6 = 2000)) AND isnotnull(d_date_sk#5)) + +(94) BroadcastExchange +Input [3]: [d_date_sk#5, d_year#6, d_qoy#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=14] + +Subquery:2 Hosting operator id = 16 Hosting Expression = ss_sold_date_sk#16 IN dynamicpruning#17 +BroadcastExchange (98) ++- * Filter (97) + +- * ColumnarToRow (96) + +- CometScan parquet spark_catalog.default.date_dim (95) + + +(95) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#18, d_year#19, d_qoy#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(96) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#18, d_year#19, d_qoy#20] + +(97) Filter [codegen id : 1] +Input [3]: [d_date_sk#18, d_year#19, d_qoy#20] +Condition : ((((isnotnull(d_qoy#20) AND isnotnull(d_year#19)) AND (d_qoy#20 = 2)) AND (d_year#19 = 2000)) AND isnotnull(d_date_sk#18)) + +(98) BroadcastExchange +Input [3]: [d_date_sk#18, d_year#19, d_qoy#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=15] + +Subquery:3 Hosting operator id = 30 Hosting Expression = ss_sold_date_sk#28 IN dynamicpruning#29 +BroadcastExchange (102) ++- * Filter (101) + +- * ColumnarToRow (100) + +- CometScan parquet spark_catalog.default.date_dim (99) + + +(99) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#30, d_year#31, d_qoy#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,3), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(100) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#30, d_year#31, d_qoy#32] + +(101) Filter [codegen id : 1] +Input [3]: [d_date_sk#30, d_year#31, d_qoy#32] +Condition : ((((isnotnull(d_qoy#32) AND isnotnull(d_year#31)) AND (d_qoy#32 = 3)) AND (d_year#31 = 2000)) AND isnotnull(d_date_sk#30)) + +(102) BroadcastExchange +Input [3]: [d_date_sk#30, d_year#31, d_qoy#32] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=16] + +Subquery:4 Hosting operator id = 45 Hosting Expression = ws_sold_date_sk#40 IN dynamicpruning#4 + +Subquery:5 Hosting operator id = 59 Hosting Expression = ws_sold_date_sk#53 IN dynamicpruning#17 + +Subquery:6 Hosting operator id = 74 Hosting Expression = ws_sold_date_sk#65 IN dynamicpruning#29 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/simplified.txt new file mode 100644 index 000000000..67bc75cd0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/simplified.txt @@ -0,0 +1,159 @@ +WholeStageCodegen (25) + Sort [ca_county] + InputAdapter + Exchange [ca_county] #1 + WholeStageCodegen (24) + Project [ca_county,d_year,web_sales,web_sales,store_sales,store_sales,web_sales,store_sales] + BroadcastHashJoin [ca_county,ca_county,web_sales,web_sales,store_sales,store_sales] + Project [ca_county,d_year,store_sales,store_sales,store_sales,ca_county,web_sales,web_sales] + BroadcastHashJoin [ca_county,ca_county,web_sales,web_sales,store_sales,store_sales] + BroadcastHashJoin [ca_county,ca_county] + Project [ca_county,d_year,store_sales,store_sales,store_sales] + BroadcastHashJoin [ca_county,ca_county] + BroadcastHashJoin [ca_county,ca_county] + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ss_ext_sales_price)),store_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #2 + WholeStageCodegen (3) + HashAggregate [ca_county,d_qoy,d_year,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_addr_sk,ss_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [d_qoy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [ca_address_sk,ca_county] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ss_ext_sales_price)),store_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #6 + WholeStageCodegen (6) + HashAggregate [ca_county,d_qoy,d_year,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_addr_sk,ss_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + Filter [d_qoy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #7 + InputAdapter + ReusedExchange [ca_address_sk,ca_county] #4 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ss_ext_sales_price)),store_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #9 + WholeStageCodegen (10) + HashAggregate [ca_county,d_qoy,d_year,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_addr_sk,ss_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #3 + BroadcastExchange #10 + WholeStageCodegen (1) + Filter [d_qoy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #10 + InputAdapter + ReusedExchange [ca_address_sk,ca_county] #4 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ws_ext_sales_price)),web_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #12 + WholeStageCodegen (14) + HashAggregate [ca_county,d_qoy,d_year,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_bill_addr_sk,ws_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_bill_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #3 + InputAdapter + ReusedExchange [ca_address_sk,ca_county] #4 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (19) + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ws_ext_sales_price)),web_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #14 + WholeStageCodegen (18) + HashAggregate [ca_county,d_qoy,d_year,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_bill_addr_sk,ws_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_bill_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #7 + InputAdapter + ReusedExchange [ca_address_sk,ca_county] #4 + InputAdapter + BroadcastExchange #15 + WholeStageCodegen (23) + HashAggregate [ca_county,d_qoy,d_year,sum] [sum(UnscaledValue(ws_ext_sales_price)),web_sales,sum] + InputAdapter + Exchange [ca_county,d_qoy,d_year] #16 + WholeStageCodegen (22) + HashAggregate [ca_county,d_qoy,d_year,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,d_year,d_qoy,ca_county] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_bill_addr_sk,ws_ext_sales_price,d_year,d_qoy] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_bill_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #10 + InputAdapter + ReusedExchange [ca_address_sk,ca_county] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/explain.txt new file mode 100644 index 000000000..6fbaa6fab --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/explain.txt @@ -0,0 +1,209 @@ +== Physical Plan == +* HashAggregate (29) ++- Exchange (28) + +- * HashAggregate (27) + +- * Project (26) + +- * BroadcastHashJoin Inner BuildRight (25) + :- * Project (23) + : +- * BroadcastHashJoin Inner BuildRight (22) + : :- * Project (10) + : : +- * BroadcastHashJoin Inner BuildRight (9) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : +- BroadcastExchange (8) + : : +- * Project (7) + : : +- * Filter (6) + : : +- * ColumnarToRow (5) + : : +- CometScan parquet spark_catalog.default.item (4) + : +- BroadcastExchange (21) + : +- * Filter (20) + : +- * HashAggregate (19) + : +- Exchange (18) + : +- * HashAggregate (17) + : +- * Project (16) + : +- * BroadcastHashJoin Inner BuildRight (15) + : :- * Filter (13) + : : +- * ColumnarToRow (12) + : : +- CometScan parquet spark_catalog.default.catalog_sales (11) + : +- ReusedExchange (14) + +- ReusedExchange (24) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_item_sk#1, cs_ext_discount_amt#2, cs_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_ext_discount_amt)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 6] +Input [3]: [cs_item_sk#1, cs_ext_discount_amt#2, cs_sold_date_sk#3] + +(3) Filter [codegen id : 6] +Input [3]: [cs_item_sk#1, cs_ext_discount_amt#2, cs_sold_date_sk#3] +Condition : (isnotnull(cs_item_sk#1) AND isnotnull(cs_ext_discount_amt#2)) + +(4) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#5, i_manufact_id#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manufact_id), EqualTo(i_manufact_id,977), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [i_item_sk#5, i_manufact_id#6] + +(6) Filter [codegen id : 1] +Input [2]: [i_item_sk#5, i_manufact_id#6] +Condition : ((isnotnull(i_manufact_id#6) AND (i_manufact_id#6 = 977)) AND isnotnull(i_item_sk#5)) + +(7) Project [codegen id : 1] +Output [1]: [i_item_sk#5] +Input [2]: [i_item_sk#5, i_manufact_id#6] + +(8) BroadcastExchange +Input [1]: [i_item_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 6] +Output [3]: [cs_ext_discount_amt#2, cs_sold_date_sk#3, i_item_sk#5] +Input [4]: [cs_item_sk#1, cs_ext_discount_amt#2, cs_sold_date_sk#3, i_item_sk#5] + +(11) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_item_sk#7, cs_ext_discount_amt#8, cs_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#9), dynamicpruningexpression(cs_sold_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 3] +Input [3]: [cs_item_sk#7, cs_ext_discount_amt#8, cs_sold_date_sk#9] + +(13) Filter [codegen id : 3] +Input [3]: [cs_item_sk#7, cs_ext_discount_amt#8, cs_sold_date_sk#9] +Condition : isnotnull(cs_item_sk#7) + +(14) ReusedExchange [Reuses operator id: 34] +Output [1]: [d_date_sk#11] + +(15) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 3] +Output [2]: [cs_item_sk#7, cs_ext_discount_amt#8] +Input [4]: [cs_item_sk#7, cs_ext_discount_amt#8, cs_sold_date_sk#9, d_date_sk#11] + +(17) HashAggregate [codegen id : 3] +Input [2]: [cs_item_sk#7, cs_ext_discount_amt#8] +Keys [1]: [cs_item_sk#7] +Functions [1]: [partial_avg(UnscaledValue(cs_ext_discount_amt#8))] +Aggregate Attributes [2]: [sum#12, count#13] +Results [3]: [cs_item_sk#7, sum#14, count#15] + +(18) Exchange +Input [3]: [cs_item_sk#7, sum#14, count#15] +Arguments: hashpartitioning(cs_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(19) HashAggregate [codegen id : 4] +Input [3]: [cs_item_sk#7, sum#14, count#15] +Keys [1]: [cs_item_sk#7] +Functions [1]: [avg(UnscaledValue(cs_ext_discount_amt#8))] +Aggregate Attributes [1]: [avg(UnscaledValue(cs_ext_discount_amt#8))#16] +Results [2]: [(1.3 * cast((avg(UnscaledValue(cs_ext_discount_amt#8))#16 / 100.0) as decimal(11,6))) AS (1.3 * avg(cs_ext_discount_amt))#17, cs_item_sk#7] + +(20) Filter [codegen id : 4] +Input [2]: [(1.3 * avg(cs_ext_discount_amt))#17, cs_item_sk#7] +Condition : isnotnull((1.3 * avg(cs_ext_discount_amt))#17) + +(21) BroadcastExchange +Input [2]: [(1.3 * avg(cs_ext_discount_amt))#17, cs_item_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, true] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [i_item_sk#5] +Right keys [1]: [cs_item_sk#7] +Join type: Inner +Join condition: (cast(cs_ext_discount_amt#2 as decimal(14,7)) > (1.3 * avg(cs_ext_discount_amt))#17) + +(23) Project [codegen id : 6] +Output [2]: [cs_ext_discount_amt#2, cs_sold_date_sk#3] +Input [5]: [cs_ext_discount_amt#2, cs_sold_date_sk#3, i_item_sk#5, (1.3 * avg(cs_ext_discount_amt))#17, cs_item_sk#7] + +(24) ReusedExchange [Reuses operator id: 34] +Output [1]: [d_date_sk#18] + +(25) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#3] +Right keys [1]: [d_date_sk#18] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 6] +Output [1]: [cs_ext_discount_amt#2] +Input [3]: [cs_ext_discount_amt#2, cs_sold_date_sk#3, d_date_sk#18] + +(27) HashAggregate [codegen id : 6] +Input [1]: [cs_ext_discount_amt#2] +Keys: [] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_discount_amt#2))] +Aggregate Attributes [1]: [sum#19] +Results [1]: [sum#20] + +(28) Exchange +Input [1]: [sum#20] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 7] +Input [1]: [sum#20] +Keys: [] +Functions [1]: [sum(UnscaledValue(cs_ext_discount_amt#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_discount_amt#2))#21] +Results [1]: [MakeDecimal(sum(UnscaledValue(cs_ext_discount_amt#2))#21,17,2) AS excess discount amount#22] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (34) ++- * Project (33) + +- * Filter (32) + +- * ColumnarToRow (31) + +- CometScan parquet spark_catalog.default.date_dim (30) + + +(30) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#18, d_date#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-01-27), LessThanOrEqual(d_date,2000-04-26), IsNotNull(d_date_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#18, d_date#23] + +(32) Filter [codegen id : 1] +Input [2]: [d_date_sk#18, d_date#23] +Condition : (((isnotnull(d_date#23) AND (d_date#23 >= 2000-01-27)) AND (d_date#23 <= 2000-04-26)) AND isnotnull(d_date_sk#18)) + +(33) Project [codegen id : 1] +Output [1]: [d_date_sk#18] +Input [2]: [d_date_sk#18, d_date#23] + +(34) BroadcastExchange +Input [1]: [d_date_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +Subquery:2 Hosting operator id = 11 Hosting Expression = cs_sold_date_sk#9 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/simplified.txt new file mode 100644 index 000000000..a87a0a7e1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/simplified.txt @@ -0,0 +1,52 @@ +WholeStageCodegen (7) + HashAggregate [sum] [sum(UnscaledValue(cs_ext_discount_amt)),excess discount amount,sum] + InputAdapter + Exchange #1 + WholeStageCodegen (6) + HashAggregate [cs_ext_discount_amt] [sum,sum] + Project [cs_ext_discount_amt] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ext_discount_amt,cs_sold_date_sk] + BroadcastHashJoin [i_item_sk,cs_item_sk,cs_ext_discount_amt,(1.3 * avg(cs_ext_discount_amt))] + Project [cs_ext_discount_amt,cs_sold_date_sk,i_item_sk] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk,cs_ext_discount_amt] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_discount_amt,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [i_item_sk] + Filter [i_manufact_id,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_manufact_id] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Filter [(1.3 * avg(cs_ext_discount_amt))] + HashAggregate [cs_item_sk,sum,count] [avg(UnscaledValue(cs_ext_discount_amt)),(1.3 * avg(cs_ext_discount_amt)),sum,count] + InputAdapter + Exchange [cs_item_sk] #5 + WholeStageCodegen (3) + HashAggregate [cs_item_sk,cs_ext_discount_amt] [sum,count,sum,count] + Project [cs_item_sk,cs_ext_discount_amt] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_discount_amt,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/explain.txt new file mode 100644 index 000000000..940b542a2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/explain.txt @@ -0,0 +1,405 @@ +== Physical Plan == +TakeOrderedAndProject (63) ++- * HashAggregate (62) + +- Exchange (61) + +- * HashAggregate (60) + +- Union (59) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * Project (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.customer_address (7) + : +- BroadcastExchange (23) + : +- * BroadcastHashJoin LeftSemi BuildRight (22) + : :- * Filter (16) + : : +- * ColumnarToRow (15) + : : +- CometScan parquet spark_catalog.default.item (14) + : +- BroadcastExchange (21) + : +- * Project (20) + : +- * Filter (19) + : +- * ColumnarToRow (18) + : +- CometScan parquet spark_catalog.default.item (17) + :- * HashAggregate (43) + : +- Exchange (42) + : +- * HashAggregate (41) + : +- * Project (40) + : +- * BroadcastHashJoin Inner BuildRight (39) + : :- * Project (37) + : : +- * BroadcastHashJoin Inner BuildRight (36) + : : :- * Project (34) + : : : +- * BroadcastHashJoin Inner BuildRight (33) + : : : :- * Filter (31) + : : : : +- * ColumnarToRow (30) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (29) + : : : +- ReusedExchange (32) + : : +- ReusedExchange (35) + : +- ReusedExchange (38) + +- * HashAggregate (58) + +- Exchange (57) + +- * HashAggregate (56) + +- * Project (55) + +- * BroadcastHashJoin Inner BuildRight (54) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * Project (49) + : : +- * BroadcastHashJoin Inner BuildRight (48) + : : :- * Filter (46) + : : : +- * ColumnarToRow (45) + : : : +- CometScan parquet spark_catalog.default.web_sales (44) + : : +- ReusedExchange (47) + : +- ReusedExchange (50) + +- ReusedExchange (53) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_addr_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 5] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) + +(4) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 5] +Output [3]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3] +Input [5]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_gmt_offset#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] + +(9) Filter [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Condition : ((isnotnull(ca_gmt_offset#8) AND (ca_gmt_offset#8 = -5.00)) AND isnotnull(ca_address_sk#7)) + +(10) Project [codegen id : 2] +Output [1]: [ca_address_sk#7] +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] + +(11) BroadcastExchange +Input [1]: [ca_address_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#2] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [2]: [ss_item_sk#1, ss_ext_sales_price#3] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ca_address_sk#7] + +(14) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#9, i_manufact_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#9, i_manufact_id#10] + +(16) Filter [codegen id : 4] +Input [2]: [i_item_sk#9, i_manufact_id#10] +Condition : isnotnull(i_item_sk#9) + +(17) Scan parquet spark_catalog.default.item +Output [2]: [i_category#11, i_manufact_id#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Electronics )] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 3] +Input [2]: [i_category#11, i_manufact_id#12] + +(19) Filter [codegen id : 3] +Input [2]: [i_category#11, i_manufact_id#12] +Condition : (isnotnull(i_category#11) AND (i_category#11 = Electronics )) + +(20) Project [codegen id : 3] +Output [1]: [i_manufact_id#12] +Input [2]: [i_category#11, i_manufact_id#12] + +(21) BroadcastExchange +Input [1]: [i_manufact_id#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(22) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_manufact_id#10] +Right keys [1]: [i_manufact_id#12] +Join type: LeftSemi +Join condition: None + +(23) BroadcastExchange +Input [2]: [i_item_sk#9, i_manufact_id#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#9] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [2]: [ss_ext_sales_price#3, i_manufact_id#10] +Input [4]: [ss_item_sk#1, ss_ext_sales_price#3, i_item_sk#9, i_manufact_id#10] + +(26) HashAggregate [codegen id : 5] +Input [2]: [ss_ext_sales_price#3, i_manufact_id#10] +Keys [1]: [i_manufact_id#10] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum#13] +Results [2]: [i_manufact_id#10, sum#14] + +(27) Exchange +Input [2]: [i_manufact_id#10, sum#14] +Arguments: hashpartitioning(i_manufact_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 6] +Input [2]: [i_manufact_id#10, sum#14] +Keys [1]: [i_manufact_id#10] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#3))#15] +Results [2]: [i_manufact_id#10, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#15,17,2) AS total_sales#16] + +(29) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#20), dynamicpruningexpression(cs_sold_date_sk#20 IN dynamicpruning#21)] +PushedFilters: [IsNotNull(cs_bill_addr_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 11] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] + +(31) Filter [codegen id : 11] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) + +(32) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#22] + +(33) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_date_sk#20] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 11] +Output [3]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19] +Input [5]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20, d_date_sk#22] + +(35) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#23] + +(36) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_bill_addr_sk#17] +Right keys [1]: [ca_address_sk#23] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 11] +Output [2]: [cs_item_sk#18, cs_ext_sales_price#19] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, ca_address_sk#23] + +(38) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#24, i_manufact_id#25] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_item_sk#18] +Right keys [1]: [i_item_sk#24] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [2]: [cs_ext_sales_price#19, i_manufact_id#25] +Input [4]: [cs_item_sk#18, cs_ext_sales_price#19, i_item_sk#24, i_manufact_id#25] + +(41) HashAggregate [codegen id : 11] +Input [2]: [cs_ext_sales_price#19, i_manufact_id#25] +Keys [1]: [i_manufact_id#25] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum#26] +Results [2]: [i_manufact_id#25, sum#27] + +(42) Exchange +Input [2]: [i_manufact_id#25, sum#27] +Arguments: hashpartitioning(i_manufact_id#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(43) HashAggregate [codegen id : 12] +Input [2]: [i_manufact_id#25, sum#27] +Keys [1]: [i_manufact_id#25] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#19))#28] +Results [2]: [i_manufact_id#25, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#19))#28,17,2) AS total_sales#29] + +(44) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_sold_date_sk#33 IN dynamicpruning#34)] +PushedFilters: [IsNotNull(ws_bill_addr_sk), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 17] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] + +(46) Filter [codegen id : 17] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) + +(47) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#35] + +(48) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#33] +Right keys [1]: [d_date_sk#35] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 17] +Output [3]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32] +Input [5]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33, d_date_sk#35] + +(50) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#36] + +(51) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_bill_addr_sk#31] +Right keys [1]: [ca_address_sk#36] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 17] +Output [2]: [ws_item_sk#30, ws_ext_sales_price#32] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ca_address_sk#36] + +(53) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#37, i_manufact_id#38] + +(54) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_item_sk#30] +Right keys [1]: [i_item_sk#37] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 17] +Output [2]: [ws_ext_sales_price#32, i_manufact_id#38] +Input [4]: [ws_item_sk#30, ws_ext_sales_price#32, i_item_sk#37, i_manufact_id#38] + +(56) HashAggregate [codegen id : 17] +Input [2]: [ws_ext_sales_price#32, i_manufact_id#38] +Keys [1]: [i_manufact_id#38] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum#39] +Results [2]: [i_manufact_id#38, sum#40] + +(57) Exchange +Input [2]: [i_manufact_id#38, sum#40] +Arguments: hashpartitioning(i_manufact_id#38, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(58) HashAggregate [codegen id : 18] +Input [2]: [i_manufact_id#38, sum#40] +Keys [1]: [i_manufact_id#38] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#32))#41] +Results [2]: [i_manufact_id#38, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#32))#41,17,2) AS total_sales#42] + +(59) Union + +(60) HashAggregate [codegen id : 19] +Input [2]: [i_manufact_id#10, total_sales#16] +Keys [1]: [i_manufact_id#10] +Functions [1]: [partial_sum(total_sales#16)] +Aggregate Attributes [2]: [sum#43, isEmpty#44] +Results [3]: [i_manufact_id#10, sum#45, isEmpty#46] + +(61) Exchange +Input [3]: [i_manufact_id#10, sum#45, isEmpty#46] +Arguments: hashpartitioning(i_manufact_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(62) HashAggregate [codegen id : 20] +Input [3]: [i_manufact_id#10, sum#45, isEmpty#46] +Keys [1]: [i_manufact_id#10] +Functions [1]: [sum(total_sales#16)] +Aggregate Attributes [1]: [sum(total_sales#16)#47] +Results [2]: [i_manufact_id#10, sum(total_sales#16)#47 AS total_sales#48] + +(63) TakeOrderedAndProject +Input [2]: [i_manufact_id#10, total_sales#48] +Arguments: 100, [total_sales#48 ASC NULLS FIRST], [i_manufact_id#10, total_sales#48] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (68) ++- * Project (67) + +- * Filter (66) + +- * ColumnarToRow (65) + +- CometScan parquet spark_catalog.default.date_dim (64) + + +(64) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#6, d_year#49, d_moy#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,5), IsNotNull(d_date_sk)] +ReadSchema: struct + +(65) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] + +(66) Filter [codegen id : 1] +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#50)) AND (d_year#49 = 1998)) AND (d_moy#50 = 5)) AND isnotnull(d_date_sk#6)) + +(67) Project [codegen id : 1] +Output [1]: [d_date_sk#6] +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] + +(68) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 29 Hosting Expression = cs_sold_date_sk#20 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 44 Hosting Expression = ws_sold_date_sk#33 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/simplified.txt new file mode 100644 index 000000000..007a3be47 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/simplified.txt @@ -0,0 +1,105 @@ +TakeOrderedAndProject [total_sales,i_manufact_id] + WholeStageCodegen (20) + HashAggregate [i_manufact_id,sum,isEmpty] [sum(total_sales),total_sales,sum,isEmpty] + InputAdapter + Exchange [i_manufact_id] #1 + WholeStageCodegen (19) + HashAggregate [i_manufact_id,total_sales] [sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (6) + HashAggregate [i_manufact_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_manufact_id] #2 + WholeStageCodegen (5) + HashAggregate [i_manufact_id,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_manufact_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_addr_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [ca_address_sk] + Filter [ca_gmt_offset,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + BroadcastHashJoin [i_manufact_id,i_manufact_id] + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_manufact_id] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + Project [i_manufact_id] + Filter [i_category] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_category,i_manufact_id] + WholeStageCodegen (12) + HashAggregate [i_manufact_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_manufact_id] #7 + WholeStageCodegen (11) + HashAggregate [i_manufact_id,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_manufact_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_bill_addr_sk,ca_address_sk] + Project [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Filter [cs_bill_addr_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_manufact_id] #5 + WholeStageCodegen (18) + HashAggregate [i_manufact_id,sum] [sum(UnscaledValue(ws_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_manufact_id] #8 + WholeStageCodegen (17) + HashAggregate [i_manufact_id,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_manufact_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_bill_addr_sk,ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_manufact_id] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/explain.txt new file mode 100644 index 000000000..63dacf973 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/explain.txt @@ -0,0 +1,218 @@ +== Physical Plan == +* Sort (32) ++- Exchange (31) + +- * Project (30) + +- * BroadcastHashJoin Inner BuildRight (29) + :- * Filter (24) + : +- * HashAggregate (23) + : +- Exchange (22) + : +- * HashAggregate (21) + : +- * Project (20) + : +- * BroadcastHashJoin Inner BuildRight (19) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * Project (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (18) + : +- * Project (17) + : +- * Filter (16) + : +- * ColumnarToRow (15) + : +- CometScan parquet spark_catalog.default.household_demographics (14) + +- BroadcastExchange (28) + +- * Filter (27) + +- * ColumnarToRow (26) + +- CometScan parquet spark_catalog.default.customer (25) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] + +(3) Filter [codegen id : 4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) + +(4) ReusedExchange [Reuses operator id: 37] +Output [1]: [d_date_sk#7] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4] +Input [6]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5, d_date_sk#7] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#8, s_county#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_county), EqualTo(s_county,Williamson County), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#8, s_county#9] + +(9) Filter [codegen id : 2] +Input [2]: [s_store_sk#8, s_county#9] +Condition : ((isnotnull(s_county#9) AND (s_county#9 = Williamson County)) AND isnotnull(s_store_sk#8)) + +(10) Project [codegen id : 2] +Output [1]: [s_store_sk#8] +Input [2]: [s_store_sk#8, s_county#9] + +(11) BroadcastExchange +Input [1]: [s_store_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#8] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [3]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, s_store_sk#8] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_vehicle_count), Or(EqualTo(hd_buy_potential,>10000 ),EqualTo(hd_buy_potential,unknown )), GreaterThan(hd_vehicle_count,0), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] + +(16) Filter [codegen id : 3] +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Condition : ((((isnotnull(hd_vehicle_count#13) AND ((hd_buy_potential#11 = >10000 ) OR (hd_buy_potential#11 = unknown ))) AND (hd_vehicle_count#13 > 0)) AND CASE WHEN (hd_vehicle_count#13 > 0) THEN ((cast(hd_dep_count#12 as double) / cast(hd_vehicle_count#13 as double)) > 1.2) END) AND isnotnull(hd_demo_sk#10)) + +(17) Project [codegen id : 3] +Output [1]: [hd_demo_sk#10] +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#10] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 4] +Output [2]: [ss_customer_sk#1, ss_ticket_number#4] +Input [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4, hd_demo_sk#10] + +(21) HashAggregate [codegen id : 4] +Input [2]: [ss_customer_sk#1, ss_ticket_number#4] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#14] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] + +(22) Exchange +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Arguments: hashpartitioning(ss_ticket_number#4, ss_customer_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#16] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count(1)#16 AS cnt#17] + +(24) Filter [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17] +Condition : ((cnt#17 >= 15) AND (cnt#17 <= 20)) + +(25) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 5] +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(27) Filter [codegen id : 5] +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Condition : isnotnull(c_customer_sk#18) + +(28) BroadcastExchange +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#18] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 6] +Output [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Input [8]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17, c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(31) Exchange +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: rangepartitioning(c_last_name#21 ASC NULLS FIRST, c_first_name#20 ASC NULLS FIRST, c_salutation#19 ASC NULLS FIRST, c_preferred_cust_flag#22 DESC NULLS LAST, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 7] +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: [c_last_name#21 ASC NULLS FIRST, c_first_name#20 ASC NULLS FIRST, c_salutation#19 ASC NULLS FIRST, c_preferred_cust_flag#22 DESC NULLS LAST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (37) ++- * Project (36) + +- * Filter (35) + +- * ColumnarToRow (34) + +- CometScan parquet spark_catalog.default.date_dim (33) + + +(33) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#23, d_dom#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(And(GreaterThanOrEqual(d_dom,1),LessThanOrEqual(d_dom,3)),And(GreaterThanOrEqual(d_dom,25),LessThanOrEqual(d_dom,28))), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(34) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] + +(35) Filter [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Condition : (((((d_dom#24 >= 1) AND (d_dom#24 <= 3)) OR ((d_dom#24 >= 25) AND (d_dom#24 <= 28))) AND d_year#23 IN (1999,2000,2001)) AND isnotnull(d_date_sk#7)) + +(36) Project [codegen id : 1] +Output [1]: [d_date_sk#7] +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] + +(37) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/simplified.txt new file mode 100644 index 000000000..91e0cbf9a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/simplified.txt @@ -0,0 +1,56 @@ +WholeStageCodegen (7) + Sort [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag] + InputAdapter + Exchange [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag] #1 + WholeStageCodegen (6) + Project [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag,ss_ticket_number,cnt] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Filter [cnt] + HashAggregate [ss_ticket_number,ss_customer_sk,count] [count(1),cnt,count] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk] #2 + WholeStageCodegen (4) + HashAggregate [ss_ticket_number,ss_customer_sk] [count,count] + Project [ss_customer_sk,ss_ticket_number] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_ticket_number] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_dom,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [s_store_sk] + Filter [s_county,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_county] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Project [hd_demo_sk] + Filter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Filter [c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt new file mode 100644 index 000000000..c4a94f735 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt @@ -0,0 +1,281 @@ +== Physical Plan == +TakeOrderedAndProject (42) ++- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (26) + : : +- * Filter (25) + : : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (24) + : : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (17) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (9) + : : : : +- * Project (8) + : : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : : :- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : +- ReusedExchange (6) + : : : +- BroadcastExchange (16) + : : : +- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- BroadcastExchange (23) + : : +- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * ColumnarToRow (19) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) + : : +- ReusedExchange (20) + : +- BroadcastExchange (30) + : +- * Filter (29) + : +- * ColumnarToRow (28) + : +- CometScan parquet spark_catalog.default.customer_address (27) + +- BroadcastExchange (36) + +- * Filter (35) + +- * ColumnarToRow (34) + +- CometScan parquet spark_catalog.default.customer_demographics (33) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] + +(3) Filter [codegen id : 9] +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#6, ss_sold_date_sk#7] + +(6) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#9] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#6] +Input [3]: [ss_customer_sk#6, ss_sold_date_sk#7, d_date_sk#9] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ss_customer_sk#6] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#11), dynamicpruningexpression(ws_sold_date_sk#11 IN dynamicpruning#12)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] + +(13) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#13] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#11] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#10] +Input [3]: [ws_bill_customer_sk#10, ws_sold_date_sk#11, d_date_sk#13] + +(16) BroadcastExchange +Input [1]: [ws_bill_customer_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ws_bill_customer_sk#10] +Join type: ExistenceJoin(exists#2) +Join condition: None + +(18) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#15), dynamicpruningexpression(cs_sold_date_sk#15 IN dynamicpruning#16)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] + +(20) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#17] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#15] +Right keys [1]: [d_date_sk#17] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#14] +Input [3]: [cs_ship_customer_sk#14, cs_sold_date_sk#15, d_date_sk#17] + +(23) BroadcastExchange +Input [1]: [cs_ship_customer_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [cs_ship_customer_sk#14] +Join type: ExistenceJoin(exists#1) +Join condition: None + +(25) Filter [codegen id : 9] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] +Condition : (exists#2 OR exists#1) + +(26) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#4, c_current_addr_sk#5] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#18, ca_state#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_state#19] + +(29) Filter [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_state#19] +Condition : isnotnull(ca_address_sk#18) + +(30) BroadcastExchange +Input [2]: [ca_address_sk#18, ca_state#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(31) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#5] +Right keys [1]: [ca_address_sk#18] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#4, ca_state#19] +Input [4]: [c_current_cdemo_sk#4, c_current_addr_sk#5, ca_address_sk#18, ca_state#19] + +(33) Scan parquet spark_catalog.default.customer_demographics +Output [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(34) ColumnarToRow [codegen id : 8] +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(35) Filter [codegen id : 8] +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Condition : isnotnull(cd_demo_sk#20) + +(36) BroadcastExchange +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#4] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 9] +Output [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Input [8]: [c_current_cdemo_sk#4, ca_state#19, cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(39) HashAggregate [codegen id : 9] +Input [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [partial_count(1), partial_min(cd_dep_count#23), partial_max(cd_dep_count#23), partial_avg(cd_dep_count#23), partial_min(cd_dep_employed_count#24), partial_max(cd_dep_employed_count#24), partial_avg(cd_dep_employed_count#24), partial_min(cd_dep_college_count#25), partial_max(cd_dep_college_count#25), partial_avg(cd_dep_college_count#25)] +Aggregate Attributes [13]: [count#26, min#27, max#28, sum#29, count#30, min#31, max#32, sum#33, count#34, min#35, max#36, sum#37, count#38] +Results [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, min#40, max#41, sum#42, count#43, min#44, max#45, sum#46, count#47, min#48, max#49, sum#50, count#51] + +(40) Exchange +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, min#40, max#41, sum#42, count#43, min#44, max#45, sum#46, count#47, min#48, max#49, sum#50, count#51] +Arguments: hashpartitioning(ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 10] +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, min#40, max#41, sum#42, count#43, min#44, max#45, sum#46, count#47, min#48, max#49, sum#50, count#51] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [count(1), min(cd_dep_count#23), max(cd_dep_count#23), avg(cd_dep_count#23), min(cd_dep_employed_count#24), max(cd_dep_employed_count#24), avg(cd_dep_employed_count#24), min(cd_dep_college_count#25), max(cd_dep_college_count#25), avg(cd_dep_college_count#25)] +Aggregate Attributes [10]: [count(1)#52, min(cd_dep_count#23)#53, max(cd_dep_count#23)#54, avg(cd_dep_count#23)#55, min(cd_dep_employed_count#24)#56, max(cd_dep_employed_count#24)#57, avg(cd_dep_employed_count#24)#58, min(cd_dep_college_count#25)#59, max(cd_dep_college_count#25)#60, avg(cd_dep_college_count#25)#61] +Results [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, count(1)#52 AS cnt1#62, min(cd_dep_count#23)#53 AS min(cd_dep_count)#63, max(cd_dep_count#23)#54 AS max(cd_dep_count)#64, avg(cd_dep_count#23)#55 AS avg(cd_dep_count)#65, cd_dep_employed_count#24, count(1)#52 AS cnt2#66, min(cd_dep_employed_count#24)#56 AS min(cd_dep_employed_count)#67, max(cd_dep_employed_count#24)#57 AS max(cd_dep_employed_count)#68, avg(cd_dep_employed_count#24)#58 AS avg(cd_dep_employed_count)#69, cd_dep_college_count#25, count(1)#52 AS cnt3#70, min(cd_dep_college_count#25)#59 AS min(cd_dep_college_count)#71, max(cd_dep_college_count#25)#60 AS max(cd_dep_college_count)#72, avg(cd_dep_college_count#25)#61 AS avg(cd_dep_college_count)#73, cd_dep_count#23] + +(42) TakeOrderedAndProject +Input [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, cnt1#62, min(cd_dep_count)#63, max(cd_dep_count)#64, avg(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, min(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, avg(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, min(cd_dep_college_count)#71, max(cd_dep_college_count)#72, avg(cd_dep_college_count)#73, cd_dep_count#23] +Arguments: 100, [ca_state#19 ASC NULLS FIRST, cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FIRST, cd_dep_count#23 ASC NULLS FIRST, cd_dep_employed_count#24 ASC NULLS FIRST, cd_dep_college_count#25 ASC NULLS FIRST], [ca_state#19, cd_gender#21, cd_marital_status#22, cnt1#62, min(cd_dep_count)#63, max(cd_dep_count)#64, avg(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, min(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, avg(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, min(cd_dep_college_count)#71, max(cd_dep_college_count)#72, avg(cd_dep_college_count)#73] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (47) ++- * Project (46) + +- * Filter (45) + +- * ColumnarToRow (44) + +- CometScan parquet spark_catalog.default.date_dim (43) + + +(43) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,2002), LessThan(d_qoy,4), IsNotNull(d_date_sk)] +ReadSchema: struct + +(44) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] + +(45) Filter [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Condition : ((((isnotnull(d_year#74) AND isnotnull(d_qoy#75)) AND (d_year#74 = 2002)) AND (d_qoy#75 < 4)) AND isnotnull(d_date_sk#9)) + +(46) Project [codegen id : 1] +Output [1]: [d_date_sk#9] +Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] + +(47) BroadcastExchange +Input [1]: [d_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#11 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 18 Hosting Expression = cs_sold_date_sk#15 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt new file mode 100644 index 000000000..67a9e3d11 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt @@ -0,0 +1,74 @@ +TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,cnt1,min(cd_dep_count),max(cd_dep_count),avg(cd_dep_count),cnt2,min(cd_dep_employed_count),max(cd_dep_employed_count),avg(cd_dep_employed_count),cnt3,min(cd_dep_college_count),max(cd_dep_college_count),avg(cd_dep_college_count)] + WholeStageCodegen (10) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,count,min,max,sum,count,min,max,sum,count,min,max,sum,count] [count(1),min(cd_dep_count),max(cd_dep_count),avg(cd_dep_count),min(cd_dep_employed_count),max(cd_dep_employed_count),avg(cd_dep_employed_count),min(cd_dep_college_count),max(cd_dep_college_count),avg(cd_dep_college_count),cnt1,min(cd_dep_count),max(cd_dep_count),avg(cd_dep_count),cnt2,min(cd_dep_employed_count),max(cd_dep_employed_count),avg(cd_dep_employed_count),cnt3,min(cd_dep_college_count),max(cd_dep_college_count),avg(cd_dep_college_count),count,min,max,sum,count,min,max,sum,count,min,max,sum,count] + InputAdapter + Exchange [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] #1 + WholeStageCodegen (9) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] [count,min,max,sum,count,min,max,sum,count,min,max,sum,count,count,min,max,sum,count,min,max,sum,count,min,max,sum,count] + Project [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk,ca_state] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + Filter [exists,exists] + BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_current_addr_sk,c_current_cdemo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_qoy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + Filter [ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + Filter [cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt new file mode 100644 index 000000000..b82dfae23 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt @@ -0,0 +1,194 @@ +== Physical Plan == +TakeOrderedAndProject (28) ++- * Project (27) + +- Window (26) + +- * Sort (25) + +- Exchange (24) + +- * HashAggregate (23) + +- Exchange (22) + +- * HashAggregate (21) + +- * Expand (20) + +- * Project (19) + +- * BroadcastHashJoin Inner BuildRight (18) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * Filter (9) + : +- * ColumnarToRow (8) + : +- CometScan parquet spark_catalog.default.item (7) + +- BroadcastExchange (17) + +- * Project (16) + +- * Filter (15) + +- * ColumnarToRow (14) + +- CometScan parquet spark_catalog.default.store (13) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] + +(3) Filter [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_store_sk#2)) + +(4) ReusedExchange [Reuses operator id: 33] +Output [1]: [d_date_sk#7] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4] +Input [6]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5, d_date_sk#7] + +(7) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#8, i_class#9, i_category#10] + +(9) Filter [codegen id : 2] +Input [3]: [i_item_sk#8, i_class#9, i_category#10] +Condition : isnotnull(i_item_sk#8) + +(10) BroadcastExchange +Input [3]: [i_item_sk#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#8] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [5]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_item_sk#8, i_class#9, i_category#10] + +(13) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_state#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [2]: [s_store_sk#11, s_state#12] + +(15) Filter [codegen id : 3] +Input [2]: [s_store_sk#11, s_state#12] +Condition : ((isnotnull(s_state#12) AND (s_state#12 = TN)) AND isnotnull(s_store_sk#11)) + +(16) Project [codegen id : 3] +Output [1]: [s_store_sk#11] +Input [2]: [s_store_sk#11, s_state#12] + +(17) BroadcastExchange +Input [1]: [s_store_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 4] +Output [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_category#10, i_class#9] +Input [6]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10, s_store_sk#11] + +(20) Expand [codegen id : 4] +Input [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_category#10, i_class#9] +Arguments: [[ss_ext_sales_price#3, ss_net_profit#4, i_category#10, i_class#9, 0], [ss_ext_sales_price#3, ss_net_profit#4, i_category#10, null, 1], [ss_ext_sales_price#3, ss_net_profit#4, null, null, 3]], [ss_ext_sales_price#3, ss_net_profit#4, i_category#13, i_class#14, spark_grouping_id#15] + +(21) HashAggregate [codegen id : 4] +Input [5]: [ss_ext_sales_price#3, ss_net_profit#4, i_category#13, i_class#14, spark_grouping_id#15] +Keys [3]: [i_category#13, i_class#14, spark_grouping_id#15] +Functions [2]: [partial_sum(UnscaledValue(ss_net_profit#4)), partial_sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [2]: [sum#16, sum#17] +Results [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#18, sum#19] + +(22) Exchange +Input [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#18, sum#19] +Arguments: hashpartitioning(i_category#13, i_class#14, spark_grouping_id#15, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 5] +Input [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#18, sum#19] +Keys [3]: [i_category#13, i_class#14, spark_grouping_id#15] +Functions [2]: [sum(UnscaledValue(ss_net_profit#4)), sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#4))#20, sum(UnscaledValue(ss_ext_sales_price#3))#21] +Results [7]: [(MakeDecimal(sum(UnscaledValue(ss_net_profit#4))#20,17,2) / MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#21,17,2)) AS gross_margin#22, i_category#13, i_class#14, (cast((shiftright(spark_grouping_id#15, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#15, 0) & 1) as tinyint)) AS lochierarchy#23, (MakeDecimal(sum(UnscaledValue(ss_net_profit#4))#20,17,2) / MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#21,17,2)) AS _w0#24, (cast((shiftright(spark_grouping_id#15, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#15, 0) & 1) as tinyint)) AS _w1#25, CASE WHEN (cast((shiftright(spark_grouping_id#15, 0) & 1) as tinyint) = 0) THEN i_category#13 END AS _w2#26] + +(24) Exchange +Input [7]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, _w0#24, _w1#25, _w2#26] +Arguments: hashpartitioning(_w1#25, _w2#26, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(25) Sort [codegen id : 6] +Input [7]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, _w0#24, _w1#25, _w2#26] +Arguments: [_w1#25 ASC NULLS FIRST, _w2#26 ASC NULLS FIRST, _w0#24 ASC NULLS FIRST], false, 0 + +(26) Window +Input [7]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, _w0#24, _w1#25, _w2#26] +Arguments: [rank(_w0#24) windowspecdefinition(_w1#25, _w2#26, _w0#24 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#27], [_w1#25, _w2#26], [_w0#24 ASC NULLS FIRST] + +(27) Project [codegen id : 7] +Output [5]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, rank_within_parent#27] +Input [8]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, _w0#24, _w1#25, _w2#26, rank_within_parent#27] + +(28) TakeOrderedAndProject +Input [5]: [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, rank_within_parent#27] +Arguments: 100, [lochierarchy#23 DESC NULLS LAST, CASE WHEN (lochierarchy#23 = 0) THEN i_category#13 END ASC NULLS FIRST, rank_within_parent#27 ASC NULLS FIRST], [gross_margin#22, i_category#13, i_class#14, lochierarchy#23, rank_within_parent#27] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (33) ++- * Project (32) + +- * Filter (31) + +- * ColumnarToRow (30) + +- CometScan parquet spark_catalog.default.date_dim (29) + + +(29) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#7, d_year#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#7, d_year#28] + +(31) Filter [codegen id : 1] +Input [2]: [d_date_sk#7, d_year#28] +Condition : ((isnotnull(d_year#28) AND (d_year#28 = 2001)) AND isnotnull(d_date_sk#7)) + +(32) Project [codegen id : 1] +Output [1]: [d_date_sk#7] +Input [2]: [d_date_sk#7, d_year#28] + +(33) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt new file mode 100644 index 000000000..acd050607 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt @@ -0,0 +1,51 @@ +TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,gross_margin,i_class] + WholeStageCodegen (7) + Project [gross_margin,i_category,i_class,lochierarchy,rank_within_parent] + InputAdapter + Window [_w0,_w1,_w2] + WholeStageCodegen (6) + Sort [_w1,_w2,_w0] + InputAdapter + Exchange [_w1,_w2] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_class,spark_grouping_id,sum,sum] [sum(UnscaledValue(ss_net_profit)),sum(UnscaledValue(ss_ext_sales_price)),gross_margin,lochierarchy,_w0,_w1,_w2,sum,sum] + InputAdapter + Exchange [i_category,i_class,spark_grouping_id] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,spark_grouping_id,ss_net_profit,ss_ext_sales_price] [sum,sum,sum,sum] + Expand [ss_ext_sales_price,ss_net_profit,i_category,i_class] + Project [ss_ext_sales_price,ss_net_profit,i_category,i_class] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_ext_sales_price,ss_net_profit,i_class,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_item_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Project [s_store_sk] + Filter [s_state,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt new file mode 100644 index 000000000..eeb841412 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt @@ -0,0 +1,179 @@ +== Physical Plan == +TakeOrderedAndProject (25) ++- * HashAggregate (24) + +- Exchange (23) + +- * HashAggregate (22) + +- * Project (21) + +- * BroadcastHashJoin Inner BuildLeft (20) + :- BroadcastExchange (15) + : +- * Project (14) + : +- * BroadcastHashJoin Inner BuildRight (13) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildRight (10) + : : :- * Project (4) + : : : +- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.item (1) + : : +- BroadcastExchange (9) + : : +- * Project (8) + : : +- * Filter (7) + : : +- * ColumnarToRow (6) + : : +- CometScan parquet spark_catalog.default.inventory (5) + : +- ReusedExchange (12) + +- * Project (19) + +- * Filter (18) + +- * ColumnarToRow (17) + +- CometScan parquet spark_catalog.default.catalog_sales (16) + + +(1) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,68.00), LessThanOrEqual(i_current_price,98.00), In(i_manufact_id, [677,694,808,940]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] + +(3) Filter [codegen id : 3] +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Condition : ((((isnotnull(i_current_price#4) AND (i_current_price#4 >= 68.00)) AND (i_current_price#4 <= 98.00)) AND i_manufact_id#5 IN (677,940,694,808)) AND isnotnull(i_item_sk#1)) + +(4) Project [codegen id : 3] +Output [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] + +(5) Scan parquet spark_catalog.default.inventory +Output [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#8), dynamicpruningexpression(inv_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(inv_quantity_on_hand), GreaterThanOrEqual(inv_quantity_on_hand,100), LessThanOrEqual(inv_quantity_on_hand,500), IsNotNull(inv_item_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] + +(7) Filter [codegen id : 1] +Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Condition : (((isnotnull(inv_quantity_on_hand#7) AND (inv_quantity_on_hand#7 >= 100)) AND (inv_quantity_on_hand#7 <= 500)) AND isnotnull(inv_item_sk#6)) + +(8) Project [codegen id : 1] +Output [2]: [inv_item_sk#6, inv_date_sk#8] +Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] + +(9) BroadcastExchange +Input [2]: [inv_item_sk#6, inv_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [inv_item_sk#6] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 3] +Output [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_date_sk#8] +Input [6]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_item_sk#6, inv_date_sk#8] + +(12) ReusedExchange [Reuses operator id: 30] +Output [1]: [d_date_sk#10] + +(13) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [inv_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 3] +Output [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +Input [6]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_date_sk#8, d_date_sk#10] + +(15) BroadcastExchange +Input [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_item_sk#11, cs_sold_date_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow +Input [2]: [cs_item_sk#11, cs_sold_date_sk#12] + +(18) Filter +Input [2]: [cs_item_sk#11, cs_sold_date_sk#12] +Condition : isnotnull(cs_item_sk#11) + +(19) Project +Output [1]: [cs_item_sk#11] +Input [2]: [cs_item_sk#11, cs_sold_date_sk#12] + +(20) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [cs_item_sk#11] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 4] +Output [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, cs_item_sk#11] + +(22) HashAggregate [codegen id : 4] +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Keys [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Functions: [] +Aggregate Attributes: [] +Results [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] + +(23) Exchange +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: hashpartitioning(i_item_id#2, i_item_desc#3, i_current_price#4, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(24) HashAggregate [codegen id : 5] +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Keys [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Functions: [] +Aggregate Attributes: [] +Results [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] + +(25) TakeOrderedAndProject +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: 100, [i_item_id#2 ASC NULLS FIRST], [i_item_id#2, i_item_desc#3, i_current_price#4] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 5 Hosting Expression = inv_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (30) ++- * Project (29) + +- * Filter (28) + +- * ColumnarToRow (27) + +- CometScan parquet spark_catalog.default.date_dim (26) + + +(26) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#10, d_date#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-02-01), LessThanOrEqual(d_date,2000-04-01), IsNotNull(d_date_sk)] +ReadSchema: struct + +(27) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#10, d_date#13] + +(28) Filter [codegen id : 1] +Input [2]: [d_date_sk#10, d_date#13] +Condition : (((isnotnull(d_date#13) AND (d_date#13 >= 2000-02-01)) AND (d_date#13 <= 2000-04-01)) AND isnotnull(d_date_sk#10)) + +(29) Project [codegen id : 1] +Output [1]: [d_date_sk#10] +Input [2]: [d_date_sk#10, d_date#13] + +(30) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt new file mode 100644 index 000000000..1b469ce06 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt @@ -0,0 +1,44 @@ +TakeOrderedAndProject [i_item_id,i_item_desc,i_current_price] + WholeStageCodegen (5) + HashAggregate [i_item_id,i_item_desc,i_current_price] + InputAdapter + Exchange [i_item_id,i_item_desc,i_current_price] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_current_price] + Project [i_item_id,i_item_desc,i_current_price] + BroadcastHashJoin [i_item_sk,cs_item_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (3) + Project [i_item_sk,i_item_id,i_item_desc,i_current_price] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [i_item_sk,i_item_id,i_item_desc,i_current_price,inv_date_sk] + BroadcastHashJoin [i_item_sk,inv_item_sk] + Project [i_item_sk,i_item_id,i_item_desc,i_current_price] + Filter [i_current_price,i_manufact_id,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_manufact_id] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [inv_item_sk,inv_date_sk] + Filter [inv_quantity_on_hand,inv_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + ReusedExchange [d_date_sk] #4 + Project [cs_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt new file mode 100644 index 000000000..66dd23ca6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt @@ -0,0 +1,321 @@ +== Physical Plan == +* HashAggregate (47) ++- Exchange (46) + +- * HashAggregate (45) + +- * Project (44) + +- * BroadcastHashJoin LeftSemi BuildRight (43) + :- * BroadcastHashJoin LeftSemi BuildRight (29) + : :- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.customer (7) + : +- BroadcastExchange (28) + : +- * HashAggregate (27) + : +- Exchange (26) + : +- * HashAggregate (25) + : +- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (21) + : : +- * BroadcastHashJoin Inner BuildRight (20) + : : :- * Filter (18) + : : : +- * ColumnarToRow (17) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) + : : +- ReusedExchange (19) + : +- ReusedExchange (22) + +- BroadcastExchange (42) + +- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (35) + : +- * BroadcastHashJoin Inner BuildRight (34) + : :- * Filter (32) + : : +- * ColumnarToRow (31) + : : +- CometScan parquet spark_catalog.default.web_sales (30) + : +- ReusedExchange (33) + +- ReusedExchange (36) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#1, ss_sold_date_sk#2] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#2), dynamicpruningexpression(ss_sold_date_sk#2 IN dynamicpruning#3)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] + +(3) Filter [codegen id : 3] +Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] +Condition : isnotnull(ss_customer_sk#1) + +(4) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#4, d_date#5] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#2] +Right keys [1]: [d_date_sk#4] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [2]: [ss_customer_sk#1, d_date#5] +Input [4]: [ss_customer_sk#1, ss_sold_date_sk#2, d_date_sk#4, d_date#5] + +(7) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] + +(9) Filter [codegen id : 2] +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Condition : isnotnull(c_customer_sk#6) + +(10) BroadcastExchange +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [c_last_name#8, c_first_name#7, d_date#5] +Input [5]: [ss_customer_sk#1, d_date#5, c_customer_sk#6, c_first_name#7, c_last_name#8] + +(13) HashAggregate [codegen id : 3] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Keys [3]: [c_last_name#8, c_first_name#7, d_date#5] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(14) Exchange +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Arguments: hashpartitioning(c_last_name#8, c_first_name#7, d_date#5, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 12] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Keys [3]: [c_last_name#8, c_first_name#7, d_date#5] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(16) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#10), dynamicpruningexpression(cs_sold_date_sk#10 IN dynamicpruning#11)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 6] +Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] + +(18) Filter [codegen id : 6] +Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] +Condition : isnotnull(cs_bill_customer_sk#9) + +(19) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#12, d_date#13] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#10] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [2]: [cs_bill_customer_sk#9, d_date#13] +Input [4]: [cs_bill_customer_sk#9, cs_sold_date_sk#10, d_date_sk#12, d_date#13] + +(22) ReusedExchange [Reuses operator id: 10] +Output [3]: [c_customer_sk#14, c_first_name#15, c_last_name#16] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_bill_customer_sk#9] +Right keys [1]: [c_customer_sk#14] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [3]: [c_last_name#16, c_first_name#15, d_date#13] +Input [5]: [cs_bill_customer_sk#9, d_date#13, c_customer_sk#14, c_first_name#15, c_last_name#16] + +(25) HashAggregate [codegen id : 6] +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Keys [3]: [c_last_name#16, c_first_name#15, d_date#13] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#16, c_first_name#15, d_date#13] + +(26) Exchange +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Arguments: hashpartitioning(c_last_name#16, c_first_name#15, d_date#13, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 7] +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Keys [3]: [c_last_name#16, c_first_name#15, d_date#13] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#16, c_first_name#15, d_date#13] + +(28) BroadcastExchange +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, string, true], ), isnull(input[0, string, true]), coalesce(input[1, string, true], ), isnull(input[1, string, true]), coalesce(input[2, date, true], 1970-01-01), isnull(input[2, date, true])),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 12] +Left keys [6]: [coalesce(c_last_name#8, ), isnull(c_last_name#8), coalesce(c_first_name#7, ), isnull(c_first_name#7), coalesce(d_date#5, 1970-01-01), isnull(d_date#5)] +Right keys [6]: [coalesce(c_last_name#16, ), isnull(c_last_name#16), coalesce(c_first_name#15, ), isnull(c_first_name#15), coalesce(d_date#13, 1970-01-01), isnull(d_date#13)] +Join type: LeftSemi +Join condition: None + +(30) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#18), dynamicpruningexpression(ws_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 10] +Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] + +(32) Filter [codegen id : 10] +Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] +Condition : isnotnull(ws_bill_customer_sk#17) + +(33) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#20, d_date#21] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#18] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [2]: [ws_bill_customer_sk#17, d_date#21] +Input [4]: [ws_bill_customer_sk#17, ws_sold_date_sk#18, d_date_sk#20, d_date#21] + +(36) ReusedExchange [Reuses operator id: 10] +Output [3]: [c_customer_sk#22, c_first_name#23, c_last_name#24] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_bill_customer_sk#17] +Right keys [1]: [c_customer_sk#22] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [3]: [c_last_name#24, c_first_name#23, d_date#21] +Input [5]: [ws_bill_customer_sk#17, d_date#21, c_customer_sk#22, c_first_name#23, c_last_name#24] + +(39) HashAggregate [codegen id : 10] +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Keys [3]: [c_last_name#24, c_first_name#23, d_date#21] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#24, c_first_name#23, d_date#21] + +(40) Exchange +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Arguments: hashpartitioning(c_last_name#24, c_first_name#23, d_date#21, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(41) HashAggregate [codegen id : 11] +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Keys [3]: [c_last_name#24, c_first_name#23, d_date#21] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#24, c_first_name#23, d_date#21] + +(42) BroadcastExchange +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, string, true], ), isnull(input[0, string, true]), coalesce(input[1, string, true], ), isnull(input[1, string, true]), coalesce(input[2, date, true], 1970-01-01), isnull(input[2, date, true])),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 12] +Left keys [6]: [coalesce(c_last_name#8, ), isnull(c_last_name#8), coalesce(c_first_name#7, ), isnull(c_first_name#7), coalesce(d_date#5, 1970-01-01), isnull(d_date#5)] +Right keys [6]: [coalesce(c_last_name#24, ), isnull(c_last_name#24), coalesce(c_first_name#23, ), isnull(c_first_name#23), coalesce(d_date#21, 1970-01-01), isnull(d_date#21)] +Join type: LeftSemi +Join condition: None + +(44) Project [codegen id : 12] +Output: [] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(45) HashAggregate [codegen id : 12] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#25] +Results [1]: [count#26] + +(46) Exchange +Input [1]: [count#26] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate [codegen id : 13] +Input [1]: [count#26] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#27] +Results [1]: [count(1)#27 AS count(1)#28] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#2 IN dynamicpruning#3 +BroadcastExchange (52) ++- * Project (51) + +- * Filter (50) + +- * ColumnarToRow (49) + +- CometScan parquet spark_catalog.default.date_dim (48) + + +(48) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(49) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] + +(50) Filter [codegen id : 1] +Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Condition : (((isnotnull(d_month_seq#29) AND (d_month_seq#29 >= 1200)) AND (d_month_seq#29 <= 1211)) AND isnotnull(d_date_sk#4)) + +(51) Project [codegen id : 1] +Output [2]: [d_date_sk#4, d_date#5] +Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] + +(52) BroadcastExchange +Input [2]: [d_date_sk#4, d_date#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 16 Hosting Expression = cs_sold_date_sk#10 IN dynamicpruning#3 + +Subquery:3 Hosting operator id = 30 Hosting Expression = ws_sold_date_sk#18 IN dynamicpruning#3 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt new file mode 100644 index 000000000..27489c0a9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt @@ -0,0 +1,81 @@ +WholeStageCodegen (13) + HashAggregate [count] [count(1),count(1),count] + InputAdapter + Exchange #1 + WholeStageCodegen (12) + HashAggregate [count,count] + Project + BroadcastHashJoin [c_last_name,c_first_name,d_date,c_last_name,c_first_name,d_date] + BroadcastHashJoin [c_last_name,c_first_name,d_date,c_last_name,c_first_name,d_date] + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #2 + WholeStageCodegen (3) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk,d_date] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #6 + WholeStageCodegen (6) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,d_date] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Filter [cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name] #4 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (11) + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #8 + WholeStageCodegen (10) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] + Project [ws_bill_customer_sk,d_date] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt new file mode 100644 index 000000000..7dd8fcc08 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt @@ -0,0 +1,318 @@ +== Physical Plan == +* Sort (44) ++- Exchange (43) + +- * BroadcastHashJoin Inner BuildRight (42) + :- * Project (23) + : +- * Filter (22) + : +- * HashAggregate (21) + : +- Exchange (20) + : +- * HashAggregate (19) + : +- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.item (4) + : : +- BroadcastExchange (13) + : : +- * Filter (12) + : : +- * ColumnarToRow (11) + : : +- CometScan parquet spark_catalog.default.warehouse (10) + : +- ReusedExchange (16) + +- BroadcastExchange (41) + +- * Project (40) + +- * Filter (39) + +- * HashAggregate (38) + +- Exchange (37) + +- * HashAggregate (36) + +- * Project (35) + +- * BroadcastHashJoin Inner BuildRight (34) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (29) + : : +- * BroadcastHashJoin Inner BuildRight (28) + : : :- * Filter (26) + : : : +- * ColumnarToRow (25) + : : : +- CometScan parquet spark_catalog.default.inventory (24) + : : +- ReusedExchange (27) + : +- ReusedExchange (30) + +- ReusedExchange (33) + + +(1) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] + +(3) Filter [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) + +(4) Scan parquet spark_catalog.default.item +Output [1]: [i_item_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [1]: [i_item_sk#6] + +(6) Filter [codegen id : 1] +Input [1]: [i_item_sk#6] +Condition : isnotnull(i_item_sk#6) + +(7) BroadcastExchange +Input [1]: [i_item_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [4]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6] +Input [5]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6] + +(10) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] + +(12) Filter [codegen id : 2] +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Condition : isnotnull(w_warehouse_sk#7) + +(13) BroadcastExchange +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_warehouse_sk#2] +Right keys [1]: [w_warehouse_sk#7] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8] +Input [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8] + +(16) ReusedExchange [Reuses operator id: 49] +Output [2]: [d_date_sk#9, d_moy#10] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#4] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#10] +Input [7]: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_date_sk#9, d_moy#10] + +(19) HashAggregate [codegen id : 4] +Input [5]: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#10] +Keys [4]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10] +Functions [2]: [partial_stddev_samp(cast(inv_quantity_on_hand#3 as double)), partial_avg(inv_quantity_on_hand#3)] +Aggregate Attributes [5]: [n#11, avg#12, m2#13, sum#14, count#15] +Results [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] + +(20) Exchange +Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] +Arguments: hashpartitioning(w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 10] +Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] +Keys [4]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10] +Functions [2]: [stddev_samp(cast(inv_quantity_on_hand#3 as double)), avg(inv_quantity_on_hand#3)] +Aggregate Attributes [2]: [stddev_samp(cast(inv_quantity_on_hand#3 as double))#21, avg(inv_quantity_on_hand#3)#22] +Results [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stddev_samp(cast(inv_quantity_on_hand#3 as double))#21 AS stdev#23, avg(inv_quantity_on_hand#3)#22 AS mean#24] + +(22) Filter [codegen id : 10] +Input [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stdev#23, mean#24] +Condition : CASE WHEN (mean#24 = 0.0) THEN false ELSE ((stdev#23 / mean#24) > 1.0) END + +(23) Project [codegen id : 10] +Output [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, CASE WHEN (mean#24 = 0.0) THEN null ELSE (stdev#23 / mean#24) END AS cov#25] +Input [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stdev#23, mean#24] + +(24) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#29), dynamicpruningexpression(inv_date_sk#29 IN dynamicpruning#30)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(25) ColumnarToRow [codegen id : 8] +Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] + +(26) Filter [codegen id : 8] +Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] +Condition : (isnotnull(inv_item_sk#26) AND isnotnull(inv_warehouse_sk#27)) + +(27) ReusedExchange [Reuses operator id: 7] +Output [1]: [i_item_sk#31] + +(28) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_item_sk#26] +Right keys [1]: [i_item_sk#31] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 8] +Output [4]: [inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31] +Input [5]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31] + +(30) ReusedExchange [Reuses operator id: 13] +Output [2]: [w_warehouse_sk#32, w_warehouse_name#33] + +(31) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_warehouse_sk#27] +Right keys [1]: [w_warehouse_sk#32] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 8] +Output [5]: [inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33] +Input [6]: [inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33] + +(33) ReusedExchange [Reuses operator id: 54] +Output [2]: [d_date_sk#34, d_moy#35] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_date_sk#29] +Right keys [1]: [d_date_sk#34] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [5]: [inv_quantity_on_hand#28, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_moy#35] +Input [7]: [inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_date_sk#34, d_moy#35] + +(36) HashAggregate [codegen id : 8] +Input [5]: [inv_quantity_on_hand#28, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_moy#35] +Keys [4]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35] +Functions [2]: [partial_stddev_samp(cast(inv_quantity_on_hand#28 as double)), partial_avg(inv_quantity_on_hand#28)] +Aggregate Attributes [5]: [n#36, avg#37, m2#38, sum#39, count#40] +Results [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] + +(37) Exchange +Input [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] +Arguments: hashpartitioning(w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(38) HashAggregate [codegen id : 9] +Input [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] +Keys [4]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35] +Functions [2]: [stddev_samp(cast(inv_quantity_on_hand#28 as double)), avg(inv_quantity_on_hand#28)] +Aggregate Attributes [2]: [stddev_samp(cast(inv_quantity_on_hand#28 as double))#21, avg(inv_quantity_on_hand#28)#22] +Results [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stddev_samp(cast(inv_quantity_on_hand#28 as double))#21 AS stdev#46, avg(inv_quantity_on_hand#28)#22 AS mean#47] + +(39) Filter [codegen id : 9] +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stdev#46, mean#47] +Condition : CASE WHEN (mean#47 = 0.0) THEN false ELSE ((stdev#46 / mean#47) > 1.0) END + +(40) Project [codegen id : 9] +Output [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, CASE WHEN (mean#47 = 0.0) THEN null ELSE (stdev#46 / mean#47) END AS cov#48] +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stdev#46, mean#47] + +(41) BroadcastExchange +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=5] + +(42) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [i_item_sk#6, w_warehouse_sk#7] +Right keys [2]: [i_item_sk#31, w_warehouse_sk#32] +Join type: Inner +Join condition: None + +(43) Exchange +Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, cov#25, w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: rangepartitioning(w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy#10 ASC NULLS FIRST, mean#24 ASC NULLS FIRST, cov#25 ASC NULLS FIRST, d_moy#35 ASC NULLS FIRST, mean#47 ASC NULLS FIRST, cov#48 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(44) Sort [codegen id : 11] +Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, cov#25, w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: [w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy#10 ASC NULLS FIRST, mean#24 ASC NULLS FIRST, cov#25 ASC NULLS FIRST, d_moy#35 ASC NULLS FIRST, mean#47 ASC NULLS FIRST, cov#48 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (49) ++- * Project (48) + +- * Filter (47) + +- * ColumnarToRow (46) + +- CometScan parquet spark_catalog.default.date_dim (45) + + +(45) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#49, d_moy#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,1), IsNotNull(d_date_sk)] +ReadSchema: struct + +(46) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#49, d_moy#10] + +(47) Filter [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#49, d_moy#10] +Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#10)) AND (d_year#49 = 2001)) AND (d_moy#10 = 1)) AND isnotnull(d_date_sk#9)) + +(48) Project [codegen id : 1] +Output [2]: [d_date_sk#9, d_moy#10] +Input [3]: [d_date_sk#9, d_year#49, d_moy#10] + +(49) BroadcastExchange +Input [2]: [d_date_sk#9, d_moy#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 24 Hosting Expression = inv_date_sk#29 IN dynamicpruning#30 +BroadcastExchange (54) ++- * Project (53) + +- * Filter (52) + +- * ColumnarToRow (51) + +- CometScan parquet spark_catalog.default.date_dim (50) + + +(50) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#34, d_year#50, d_moy#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)] +ReadSchema: struct + +(51) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#34, d_year#50, d_moy#35] + +(52) Filter [codegen id : 1] +Input [3]: [d_date_sk#34, d_year#50, d_moy#35] +Condition : ((((isnotnull(d_year#50) AND isnotnull(d_moy#35)) AND (d_year#50 = 2001)) AND (d_moy#35 = 2)) AND isnotnull(d_date_sk#34)) + +(53) Project [codegen id : 1] +Output [2]: [d_date_sk#34, d_moy#35] +Input [3]: [d_date_sk#34, d_year#50, d_moy#35] + +(54) BroadcastExchange +Input [2]: [d_date_sk#34, d_moy#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/simplified.txt new file mode 100644 index 000000000..138e386cb --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/simplified.txt @@ -0,0 +1,81 @@ +WholeStageCodegen (11) + Sort [w_warehouse_sk,i_item_sk,d_moy,mean,cov,d_moy,mean,cov] + InputAdapter + Exchange [w_warehouse_sk,i_item_sk,d_moy,mean,cov,d_moy,mean,cov] #1 + WholeStageCodegen (10) + BroadcastHashJoin [i_item_sk,w_warehouse_sk,i_item_sk,w_warehouse_sk] + Project [w_warehouse_sk,i_item_sk,d_moy,mean,stdev] + Filter [mean,stdev] + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,n,avg,m2,sum,count] [stddev_samp(cast(inv_quantity_on_hand as double)),avg(inv_quantity_on_hand),stdev,mean,n,avg,m2,sum,count] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,inv_quantity_on_hand] [n,avg,m2,sum,count,n,avg,m2,sum,count] + Project [inv_quantity_on_hand,i_item_sk,w_warehouse_sk,w_warehouse_name,d_moy] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [inv_quantity_on_hand,inv_date_sk,i_item_sk,w_warehouse_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Filter [inv_item_sk,inv_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk,d_moy] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + ReusedExchange [d_date_sk,d_moy] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (9) + Project [w_warehouse_sk,i_item_sk,d_moy,mean,stdev] + Filter [mean,stdev] + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,n,avg,m2,sum,count] [stddev_samp(cast(inv_quantity_on_hand as double)),avg(inv_quantity_on_hand),stdev,mean,n,avg,m2,sum,count] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy] #7 + WholeStageCodegen (8) + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,inv_quantity_on_hand] [n,avg,m2,sum,count,n,avg,m2,sum,count] + Project [inv_quantity_on_hand,i_item_sk,w_warehouse_sk,w_warehouse_name,d_moy] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [inv_quantity_on_hand,inv_date_sk,i_item_sk,w_warehouse_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Filter [inv_item_sk,inv_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #8 + WholeStageCodegen (1) + Project [d_date_sk,d_moy] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [i_item_sk] #4 + InputAdapter + ReusedExchange [w_warehouse_sk,w_warehouse_name] #5 + InputAdapter + ReusedExchange [d_date_sk,d_moy] #8 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/explain.txt new file mode 100644 index 000000000..4befb027a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/explain.txt @@ -0,0 +1,318 @@ +== Physical Plan == +* Sort (44) ++- Exchange (43) + +- * BroadcastHashJoin Inner BuildRight (42) + :- * Project (23) + : +- * Filter (22) + : +- * HashAggregate (21) + : +- Exchange (20) + : +- * HashAggregate (19) + : +- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.item (4) + : : +- BroadcastExchange (13) + : : +- * Filter (12) + : : +- * ColumnarToRow (11) + : : +- CometScan parquet spark_catalog.default.warehouse (10) + : +- ReusedExchange (16) + +- BroadcastExchange (41) + +- * Project (40) + +- * Filter (39) + +- * HashAggregate (38) + +- Exchange (37) + +- * HashAggregate (36) + +- * Project (35) + +- * BroadcastHashJoin Inner BuildRight (34) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (29) + : : +- * BroadcastHashJoin Inner BuildRight (28) + : : :- * Filter (26) + : : : +- * ColumnarToRow (25) + : : : +- CometScan parquet spark_catalog.default.inventory (24) + : : +- ReusedExchange (27) + : +- ReusedExchange (30) + +- ReusedExchange (33) + + +(1) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] + +(3) Filter [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) + +(4) Scan parquet spark_catalog.default.item +Output [1]: [i_item_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [1]: [i_item_sk#6] + +(6) Filter [codegen id : 1] +Input [1]: [i_item_sk#6] +Condition : isnotnull(i_item_sk#6) + +(7) BroadcastExchange +Input [1]: [i_item_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [4]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6] +Input [5]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6] + +(10) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] + +(12) Filter [codegen id : 2] +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Condition : isnotnull(w_warehouse_sk#7) + +(13) BroadcastExchange +Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_warehouse_sk#2] +Right keys [1]: [w_warehouse_sk#7] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8] +Input [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8] + +(16) ReusedExchange [Reuses operator id: 49] +Output [2]: [d_date_sk#9, d_moy#10] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#4] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#10] +Input [7]: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_date_sk#9, d_moy#10] + +(19) HashAggregate [codegen id : 4] +Input [5]: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#10] +Keys [4]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10] +Functions [2]: [partial_stddev_samp(cast(inv_quantity_on_hand#3 as double)), partial_avg(inv_quantity_on_hand#3)] +Aggregate Attributes [5]: [n#11, avg#12, m2#13, sum#14, count#15] +Results [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] + +(20) Exchange +Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] +Arguments: hashpartitioning(w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 10] +Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10, n#16, avg#17, m2#18, sum#19, count#20] +Keys [4]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#10] +Functions [2]: [stddev_samp(cast(inv_quantity_on_hand#3 as double)), avg(inv_quantity_on_hand#3)] +Aggregate Attributes [2]: [stddev_samp(cast(inv_quantity_on_hand#3 as double))#21, avg(inv_quantity_on_hand#3)#22] +Results [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stddev_samp(cast(inv_quantity_on_hand#3 as double))#21 AS stdev#23, avg(inv_quantity_on_hand#3)#22 AS mean#24] + +(22) Filter [codegen id : 10] +Input [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stdev#23, mean#24] +Condition : (CASE WHEN (mean#24 = 0.0) THEN false ELSE ((stdev#23 / mean#24) > 1.0) END AND CASE WHEN (mean#24 = 0.0) THEN false ELSE ((stdev#23 / mean#24) > 1.5) END) + +(23) Project [codegen id : 10] +Output [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, CASE WHEN (mean#24 = 0.0) THEN null ELSE (stdev#23 / mean#24) END AS cov#25] +Input [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, stdev#23, mean#24] + +(24) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#29), dynamicpruningexpression(inv_date_sk#29 IN dynamicpruning#30)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(25) ColumnarToRow [codegen id : 8] +Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] + +(26) Filter [codegen id : 8] +Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] +Condition : (isnotnull(inv_item_sk#26) AND isnotnull(inv_warehouse_sk#27)) + +(27) ReusedExchange [Reuses operator id: 7] +Output [1]: [i_item_sk#31] + +(28) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_item_sk#26] +Right keys [1]: [i_item_sk#31] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 8] +Output [4]: [inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31] +Input [5]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31] + +(30) ReusedExchange [Reuses operator id: 13] +Output [2]: [w_warehouse_sk#32, w_warehouse_name#33] + +(31) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_warehouse_sk#27] +Right keys [1]: [w_warehouse_sk#32] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 8] +Output [5]: [inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33] +Input [6]: [inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33] + +(33) ReusedExchange [Reuses operator id: 54] +Output [2]: [d_date_sk#34, d_moy#35] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [inv_date_sk#29] +Right keys [1]: [d_date_sk#34] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [5]: [inv_quantity_on_hand#28, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_moy#35] +Input [7]: [inv_quantity_on_hand#28, inv_date_sk#29, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_date_sk#34, d_moy#35] + +(36) HashAggregate [codegen id : 8] +Input [5]: [inv_quantity_on_hand#28, i_item_sk#31, w_warehouse_sk#32, w_warehouse_name#33, d_moy#35] +Keys [4]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35] +Functions [2]: [partial_stddev_samp(cast(inv_quantity_on_hand#28 as double)), partial_avg(inv_quantity_on_hand#28)] +Aggregate Attributes [5]: [n#36, avg#37, m2#38, sum#39, count#40] +Results [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] + +(37) Exchange +Input [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] +Arguments: hashpartitioning(w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(38) HashAggregate [codegen id : 9] +Input [9]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35, n#41, avg#42, m2#43, sum#44, count#45] +Keys [4]: [w_warehouse_name#33, w_warehouse_sk#32, i_item_sk#31, d_moy#35] +Functions [2]: [stddev_samp(cast(inv_quantity_on_hand#28 as double)), avg(inv_quantity_on_hand#28)] +Aggregate Attributes [2]: [stddev_samp(cast(inv_quantity_on_hand#28 as double))#21, avg(inv_quantity_on_hand#28)#22] +Results [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stddev_samp(cast(inv_quantity_on_hand#28 as double))#21 AS stdev#46, avg(inv_quantity_on_hand#28)#22 AS mean#47] + +(39) Filter [codegen id : 9] +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stdev#46, mean#47] +Condition : CASE WHEN (mean#47 = 0.0) THEN false ELSE ((stdev#46 / mean#47) > 1.0) END + +(40) Project [codegen id : 9] +Output [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, CASE WHEN (mean#47 = 0.0) THEN null ELSE (stdev#46 / mean#47) END AS cov#48] +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, stdev#46, mean#47] + +(41) BroadcastExchange +Input [5]: [w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=5] + +(42) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [i_item_sk#6, w_warehouse_sk#7] +Right keys [2]: [i_item_sk#31, w_warehouse_sk#32] +Join type: Inner +Join condition: None + +(43) Exchange +Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, cov#25, w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: rangepartitioning(w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy#10 ASC NULLS FIRST, mean#24 ASC NULLS FIRST, cov#25 ASC NULLS FIRST, d_moy#35 ASC NULLS FIRST, mean#47 ASC NULLS FIRST, cov#48 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(44) Sort [codegen id : 11] +Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#10, mean#24, cov#25, w_warehouse_sk#32, i_item_sk#31, d_moy#35, mean#47, cov#48] +Arguments: [w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy#10 ASC NULLS FIRST, mean#24 ASC NULLS FIRST, cov#25 ASC NULLS FIRST, d_moy#35 ASC NULLS FIRST, mean#47 ASC NULLS FIRST, cov#48 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (49) ++- * Project (48) + +- * Filter (47) + +- * ColumnarToRow (46) + +- CometScan parquet spark_catalog.default.date_dim (45) + + +(45) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#49, d_moy#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,1), IsNotNull(d_date_sk)] +ReadSchema: struct + +(46) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#49, d_moy#10] + +(47) Filter [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#49, d_moy#10] +Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#10)) AND (d_year#49 = 2001)) AND (d_moy#10 = 1)) AND isnotnull(d_date_sk#9)) + +(48) Project [codegen id : 1] +Output [2]: [d_date_sk#9, d_moy#10] +Input [3]: [d_date_sk#9, d_year#49, d_moy#10] + +(49) BroadcastExchange +Input [2]: [d_date_sk#9, d_moy#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 24 Hosting Expression = inv_date_sk#29 IN dynamicpruning#30 +BroadcastExchange (54) ++- * Project (53) + +- * Filter (52) + +- * ColumnarToRow (51) + +- CometScan parquet spark_catalog.default.date_dim (50) + + +(50) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#34, d_year#50, d_moy#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)] +ReadSchema: struct + +(51) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#34, d_year#50, d_moy#35] + +(52) Filter [codegen id : 1] +Input [3]: [d_date_sk#34, d_year#50, d_moy#35] +Condition : ((((isnotnull(d_year#50) AND isnotnull(d_moy#35)) AND (d_year#50 = 2001)) AND (d_moy#35 = 2)) AND isnotnull(d_date_sk#34)) + +(53) Project [codegen id : 1] +Output [2]: [d_date_sk#34, d_moy#35] +Input [3]: [d_date_sk#34, d_year#50, d_moy#35] + +(54) BroadcastExchange +Input [2]: [d_date_sk#34, d_moy#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/simplified.txt new file mode 100644 index 000000000..138e386cb --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/simplified.txt @@ -0,0 +1,81 @@ +WholeStageCodegen (11) + Sort [w_warehouse_sk,i_item_sk,d_moy,mean,cov,d_moy,mean,cov] + InputAdapter + Exchange [w_warehouse_sk,i_item_sk,d_moy,mean,cov,d_moy,mean,cov] #1 + WholeStageCodegen (10) + BroadcastHashJoin [i_item_sk,w_warehouse_sk,i_item_sk,w_warehouse_sk] + Project [w_warehouse_sk,i_item_sk,d_moy,mean,stdev] + Filter [mean,stdev] + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,n,avg,m2,sum,count] [stddev_samp(cast(inv_quantity_on_hand as double)),avg(inv_quantity_on_hand),stdev,mean,n,avg,m2,sum,count] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,inv_quantity_on_hand] [n,avg,m2,sum,count,n,avg,m2,sum,count] + Project [inv_quantity_on_hand,i_item_sk,w_warehouse_sk,w_warehouse_name,d_moy] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [inv_quantity_on_hand,inv_date_sk,i_item_sk,w_warehouse_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Filter [inv_item_sk,inv_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk,d_moy] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + ReusedExchange [d_date_sk,d_moy] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (9) + Project [w_warehouse_sk,i_item_sk,d_moy,mean,stdev] + Filter [mean,stdev] + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,n,avg,m2,sum,count] [stddev_samp(cast(inv_quantity_on_hand as double)),avg(inv_quantity_on_hand),stdev,mean,n,avg,m2,sum,count] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy] #7 + WholeStageCodegen (8) + HashAggregate [w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy,inv_quantity_on_hand] [n,avg,m2,sum,count,n,avg,m2,sum,count] + Project [inv_quantity_on_hand,i_item_sk,w_warehouse_sk,w_warehouse_name,d_moy] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [inv_quantity_on_hand,inv_date_sk,i_item_sk,w_warehouse_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Filter [inv_item_sk,inv_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #8 + WholeStageCodegen (1) + Project [d_date_sk,d_moy] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [i_item_sk] #4 + InputAdapter + ReusedExchange [w_warehouse_sk,w_warehouse_name] #5 + InputAdapter + ReusedExchange [d_date_sk,d_moy] #8 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/explain.txt new file mode 100644 index 000000000..3bc53a09a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/explain.txt @@ -0,0 +1,698 @@ +== Physical Plan == +TakeOrderedAndProject (108) ++- * Project (107) + +- * BroadcastHashJoin Inner BuildRight (106) + :- * Project (89) + : +- * BroadcastHashJoin Inner BuildRight (88) + : :- * Project (70) + : : +- * BroadcastHashJoin Inner BuildRight (69) + : : :- * Project (52) + : : : +- * BroadcastHashJoin Inner BuildRight (51) + : : : :- * BroadcastHashJoin Inner BuildRight (33) + : : : : :- * Filter (16) + : : : : : +- * HashAggregate (15) + : : : : : +- Exchange (14) + : : : : : +- * HashAggregate (13) + : : : : : +- * Project (12) + : : : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : : : :- * Project (9) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : :- * Filter (3) + : : : : : : : +- * ColumnarToRow (2) + : : : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : : : +- BroadcastExchange (7) + : : : : : : +- * Filter (6) + : : : : : : +- * ColumnarToRow (5) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : : +- ReusedExchange (10) + : : : : +- BroadcastExchange (32) + : : : : +- * HashAggregate (31) + : : : : +- Exchange (30) + : : : : +- * HashAggregate (29) + : : : : +- * Project (28) + : : : : +- * BroadcastHashJoin Inner BuildRight (27) + : : : : :- * Project (25) + : : : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : : : :- * Filter (19) + : : : : : : +- * ColumnarToRow (18) + : : : : : : +- CometScan parquet spark_catalog.default.customer (17) + : : : : : +- BroadcastExchange (23) + : : : : : +- * Filter (22) + : : : : : +- * ColumnarToRow (21) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (20) + : : : : +- ReusedExchange (26) + : : : +- BroadcastExchange (50) + : : : +- * Filter (49) + : : : +- * HashAggregate (48) + : : : +- Exchange (47) + : : : +- * HashAggregate (46) + : : : +- * Project (45) + : : : +- * BroadcastHashJoin Inner BuildRight (44) + : : : :- * Project (42) + : : : : +- * BroadcastHashJoin Inner BuildRight (41) + : : : : :- * Filter (36) + : : : : : +- * ColumnarToRow (35) + : : : : : +- CometScan parquet spark_catalog.default.customer (34) + : : : : +- BroadcastExchange (40) + : : : : +- * Filter (39) + : : : : +- * ColumnarToRow (38) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (37) + : : : +- ReusedExchange (43) + : : +- BroadcastExchange (68) + : : +- * HashAggregate (67) + : : +- Exchange (66) + : : +- * HashAggregate (65) + : : +- * Project (64) + : : +- * BroadcastHashJoin Inner BuildRight (63) + : : :- * Project (61) + : : : +- * BroadcastHashJoin Inner BuildRight (60) + : : : :- * Filter (55) + : : : : +- * ColumnarToRow (54) + : : : : +- CometScan parquet spark_catalog.default.customer (53) + : : : +- BroadcastExchange (59) + : : : +- * Filter (58) + : : : +- * ColumnarToRow (57) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (56) + : : +- ReusedExchange (62) + : +- BroadcastExchange (87) + : +- * Filter (86) + : +- * HashAggregate (85) + : +- Exchange (84) + : +- * HashAggregate (83) + : +- * Project (82) + : +- * BroadcastHashJoin Inner BuildRight (81) + : :- * Project (79) + : : +- * BroadcastHashJoin Inner BuildRight (78) + : : :- * Filter (73) + : : : +- * ColumnarToRow (72) + : : : +- CometScan parquet spark_catalog.default.customer (71) + : : +- BroadcastExchange (77) + : : +- * Filter (76) + : : +- * ColumnarToRow (75) + : : +- CometScan parquet spark_catalog.default.web_sales (74) + : +- ReusedExchange (80) + +- BroadcastExchange (105) + +- * HashAggregate (104) + +- Exchange (103) + +- * HashAggregate (102) + +- * Project (101) + +- * BroadcastHashJoin Inner BuildRight (100) + :- * Project (98) + : +- * BroadcastHashJoin Inner BuildRight (97) + : :- * Filter (92) + : : +- * ColumnarToRow (91) + : : +- CometScan parquet spark_catalog.default.customer (90) + : +- BroadcastExchange (96) + : +- * Filter (95) + : +- * ColumnarToRow (94) + : +- CometScan parquet spark_catalog.default.web_sales (93) + +- ReusedExchange (99) + + +(1) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] + +(3) Filter [codegen id : 3] +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#14), dynamicpruningexpression(ss_sold_date_sk#14 IN dynamicpruning#15)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] + +(6) Filter [codegen id : 1] +Input [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] +Condition : isnotnull(ss_customer_sk#9) + +(7) BroadcastExchange +Input [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#9] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [12]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] +Input [14]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] + +(10) ReusedExchange [Reuses operator id: 112] +Output [2]: [d_date_sk#16, d_year#17] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#14] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [12]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, d_year#17] +Input [14]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14, d_date_sk#16, d_year#17] + +(13) HashAggregate [codegen id : 3] +Input [12]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, d_year#17] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17] +Functions [1]: [partial_sum(((((ss_ext_list_price#13 - ss_ext_wholesale_cost#12) - ss_ext_discount_amt#10) + ss_ext_sales_price#11) / 2))] +Aggregate Attributes [2]: [sum#18, isEmpty#19] +Results [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17, sum#20, isEmpty#21] + +(14) Exchange +Input [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17, sum#20, isEmpty#21] +Arguments: hashpartitioning(c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 24] +Input [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17, sum#20, isEmpty#21] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, d_year#17] +Functions [1]: [sum(((((ss_ext_list_price#13 - ss_ext_wholesale_cost#12) - ss_ext_discount_amt#10) + ss_ext_sales_price#11) / 2))] +Aggregate Attributes [1]: [sum(((((ss_ext_list_price#13 - ss_ext_wholesale_cost#12) - ss_ext_discount_amt#10) + ss_ext_sales_price#11) / 2))#22] +Results [2]: [c_customer_id#2 AS customer_id#23, sum(((((ss_ext_list_price#13 - ss_ext_wholesale_cost#12) - ss_ext_discount_amt#10) + ss_ext_sales_price#11) / 2))#22 AS year_total#24] + +(16) Filter [codegen id : 24] +Input [2]: [customer_id#23, year_total#24] +Condition : (isnotnull(year_total#24) AND (year_total#24 > 0.000000)) + +(17) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#25, c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 6] +Input [8]: [c_customer_sk#25, c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32] + +(19) Filter [codegen id : 6] +Input [8]: [c_customer_sk#25, c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32] +Condition : (isnotnull(c_customer_sk#25) AND isnotnull(c_customer_id#26)) + +(20) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#38), dynamicpruningexpression(ss_sold_date_sk#38 IN dynamicpruning#39)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] + +(22) Filter [codegen id : 4] +Input [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] +Condition : isnotnull(ss_customer_sk#33) + +(23) BroadcastExchange +Input [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_customer_sk#25] +Right keys [1]: [ss_customer_sk#33] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [12]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] +Input [14]: [c_customer_sk#25, c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] + +(26) ReusedExchange [Reuses operator id: 116] +Output [2]: [d_date_sk#40, d_year#41] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#38] +Right keys [1]: [d_date_sk#40] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [12]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, d_year#41] +Input [14]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38, d_date_sk#40, d_year#41] + +(29) HashAggregate [codegen id : 6] +Input [12]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, d_year#41] +Keys [8]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41] +Functions [1]: [partial_sum(((((ss_ext_list_price#37 - ss_ext_wholesale_cost#36) - ss_ext_discount_amt#34) + ss_ext_sales_price#35) / 2))] +Aggregate Attributes [2]: [sum#42, isEmpty#43] +Results [10]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41, sum#44, isEmpty#45] + +(30) Exchange +Input [10]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41, sum#44, isEmpty#45] +Arguments: hashpartitioning(c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [10]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41, sum#44, isEmpty#45] +Keys [8]: [c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32, d_year#41] +Functions [1]: [sum(((((ss_ext_list_price#37 - ss_ext_wholesale_cost#36) - ss_ext_discount_amt#34) + ss_ext_sales_price#35) / 2))] +Aggregate Attributes [1]: [sum(((((ss_ext_list_price#37 - ss_ext_wholesale_cost#36) - ss_ext_discount_amt#34) + ss_ext_sales_price#35) / 2))#22] +Results [8]: [c_customer_id#26 AS customer_id#46, c_first_name#27 AS customer_first_name#47, c_last_name#28 AS customer_last_name#48, c_preferred_cust_flag#29 AS customer_preferred_cust_flag#49, c_birth_country#30 AS customer_birth_country#50, c_login#31 AS customer_login#51, c_email_address#32 AS customer_email_address#52, sum(((((ss_ext_list_price#37 - ss_ext_wholesale_cost#36) - ss_ext_discount_amt#34) + ss_ext_sales_price#35) / 2))#22 AS year_total#53] + +(32) BroadcastExchange +Input [8]: [customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#53] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [customer_id#23] +Right keys [1]: [customer_id#46] +Join type: Inner +Join condition: None + +(34) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#54, c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 10] +Input [8]: [c_customer_sk#54, c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61] + +(36) Filter [codegen id : 10] +Input [8]: [c_customer_sk#54, c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61] +Condition : (isnotnull(c_customer_sk#54) AND isnotnull(c_customer_id#55)) + +(37) Scan parquet spark_catalog.default.catalog_sales +Output [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#67), dynamicpruningexpression(cs_sold_date_sk#67 IN dynamicpruning#68)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(38) ColumnarToRow [codegen id : 8] +Input [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] + +(39) Filter [codegen id : 8] +Input [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] +Condition : isnotnull(cs_bill_customer_sk#62) + +(40) BroadcastExchange +Input [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(41) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [c_customer_sk#54] +Right keys [1]: [cs_bill_customer_sk#62] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 10] +Output [12]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] +Input [14]: [c_customer_sk#54, c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] + +(43) ReusedExchange [Reuses operator id: 112] +Output [2]: [d_date_sk#69, d_year#70] + +(44) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#67] +Right keys [1]: [d_date_sk#69] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 10] +Output [12]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, d_year#70] +Input [14]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67, d_date_sk#69, d_year#70] + +(46) HashAggregate [codegen id : 10] +Input [12]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, d_year#70] +Keys [8]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70] +Functions [1]: [partial_sum(((((cs_ext_list_price#66 - cs_ext_wholesale_cost#65) - cs_ext_discount_amt#63) + cs_ext_sales_price#64) / 2))] +Aggregate Attributes [2]: [sum#71, isEmpty#72] +Results [10]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70, sum#73, isEmpty#74] + +(47) Exchange +Input [10]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70, sum#73, isEmpty#74] +Arguments: hashpartitioning(c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(48) HashAggregate [codegen id : 11] +Input [10]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70, sum#73, isEmpty#74] +Keys [8]: [c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61, d_year#70] +Functions [1]: [sum(((((cs_ext_list_price#66 - cs_ext_wholesale_cost#65) - cs_ext_discount_amt#63) + cs_ext_sales_price#64) / 2))] +Aggregate Attributes [1]: [sum(((((cs_ext_list_price#66 - cs_ext_wholesale_cost#65) - cs_ext_discount_amt#63) + cs_ext_sales_price#64) / 2))#75] +Results [2]: [c_customer_id#55 AS customer_id#76, sum(((((cs_ext_list_price#66 - cs_ext_wholesale_cost#65) - cs_ext_discount_amt#63) + cs_ext_sales_price#64) / 2))#75 AS year_total#77] + +(49) Filter [codegen id : 11] +Input [2]: [customer_id#76, year_total#77] +Condition : (isnotnull(year_total#77) AND (year_total#77 > 0.000000)) + +(50) BroadcastExchange +Input [2]: [customer_id#76, year_total#77] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(51) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [customer_id#23] +Right keys [1]: [customer_id#76] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 24] +Output [11]: [customer_id#23, year_total#24, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#53, year_total#77] +Input [12]: [customer_id#23, year_total#24, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#53, customer_id#76, year_total#77] + +(53) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#78, c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(54) ColumnarToRow [codegen id : 14] +Input [8]: [c_customer_sk#78, c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85] + +(55) Filter [codegen id : 14] +Input [8]: [c_customer_sk#78, c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85] +Condition : (isnotnull(c_customer_sk#78) AND isnotnull(c_customer_id#79)) + +(56) Scan parquet spark_catalog.default.catalog_sales +Output [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#91), dynamicpruningexpression(cs_sold_date_sk#91 IN dynamicpruning#92)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(57) ColumnarToRow [codegen id : 12] +Input [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] + +(58) Filter [codegen id : 12] +Input [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] +Condition : isnotnull(cs_bill_customer_sk#86) + +(59) BroadcastExchange +Input [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [c_customer_sk#78] +Right keys [1]: [cs_bill_customer_sk#86] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 14] +Output [12]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] +Input [14]: [c_customer_sk#78, c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] + +(62) ReusedExchange [Reuses operator id: 116] +Output [2]: [d_date_sk#93, d_year#94] + +(63) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [cs_sold_date_sk#91] +Right keys [1]: [d_date_sk#93] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 14] +Output [12]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, d_year#94] +Input [14]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91, d_date_sk#93, d_year#94] + +(65) HashAggregate [codegen id : 14] +Input [12]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, d_year#94] +Keys [8]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94] +Functions [1]: [partial_sum(((((cs_ext_list_price#90 - cs_ext_wholesale_cost#89) - cs_ext_discount_amt#87) + cs_ext_sales_price#88) / 2))] +Aggregate Attributes [2]: [sum#95, isEmpty#96] +Results [10]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94, sum#97, isEmpty#98] + +(66) Exchange +Input [10]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94, sum#97, isEmpty#98] +Arguments: hashpartitioning(c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(67) HashAggregate [codegen id : 15] +Input [10]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94, sum#97, isEmpty#98] +Keys [8]: [c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85, d_year#94] +Functions [1]: [sum(((((cs_ext_list_price#90 - cs_ext_wholesale_cost#89) - cs_ext_discount_amt#87) + cs_ext_sales_price#88) / 2))] +Aggregate Attributes [1]: [sum(((((cs_ext_list_price#90 - cs_ext_wholesale_cost#89) - cs_ext_discount_amt#87) + cs_ext_sales_price#88) / 2))#75] +Results [2]: [c_customer_id#79 AS customer_id#99, sum(((((cs_ext_list_price#90 - cs_ext_wholesale_cost#89) - cs_ext_discount_amt#87) + cs_ext_sales_price#88) / 2))#75 AS year_total#100] + +(68) BroadcastExchange +Input [2]: [customer_id#99, year_total#100] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=11] + +(69) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [customer_id#23] +Right keys [1]: [customer_id#99] +Join type: Inner +Join condition: (CASE WHEN (year_total#77 > 0.000000) THEN (year_total#100 / year_total#77) END > CASE WHEN (year_total#24 > 0.000000) THEN (year_total#53 / year_total#24) END) + +(70) Project [codegen id : 24] +Output [10]: [customer_id#23, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#77, year_total#100] +Input [13]: [customer_id#23, year_total#24, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#53, year_total#77, customer_id#99, year_total#100] + +(71) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#101, c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(72) ColumnarToRow [codegen id : 18] +Input [8]: [c_customer_sk#101, c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108] + +(73) Filter [codegen id : 18] +Input [8]: [c_customer_sk#101, c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108] +Condition : (isnotnull(c_customer_sk#101) AND isnotnull(c_customer_id#102)) + +(74) Scan parquet spark_catalog.default.web_sales +Output [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#114), dynamicpruningexpression(ws_sold_date_sk#114 IN dynamicpruning#115)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(75) ColumnarToRow [codegen id : 16] +Input [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] + +(76) Filter [codegen id : 16] +Input [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] +Condition : isnotnull(ws_bill_customer_sk#109) + +(77) BroadcastExchange +Input [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +(78) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [c_customer_sk#101] +Right keys [1]: [ws_bill_customer_sk#109] +Join type: Inner +Join condition: None + +(79) Project [codegen id : 18] +Output [12]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] +Input [14]: [c_customer_sk#101, c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] + +(80) ReusedExchange [Reuses operator id: 112] +Output [2]: [d_date_sk#116, d_year#117] + +(81) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ws_sold_date_sk#114] +Right keys [1]: [d_date_sk#116] +Join type: Inner +Join condition: None + +(82) Project [codegen id : 18] +Output [12]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, d_year#117] +Input [14]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114, d_date_sk#116, d_year#117] + +(83) HashAggregate [codegen id : 18] +Input [12]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, d_year#117] +Keys [8]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117] +Functions [1]: [partial_sum(((((ws_ext_list_price#113 - ws_ext_wholesale_cost#112) - ws_ext_discount_amt#110) + ws_ext_sales_price#111) / 2))] +Aggregate Attributes [2]: [sum#118, isEmpty#119] +Results [10]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117, sum#120, isEmpty#121] + +(84) Exchange +Input [10]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117, sum#120, isEmpty#121] +Arguments: hashpartitioning(c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(85) HashAggregate [codegen id : 19] +Input [10]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117, sum#120, isEmpty#121] +Keys [8]: [c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108, d_year#117] +Functions [1]: [sum(((((ws_ext_list_price#113 - ws_ext_wholesale_cost#112) - ws_ext_discount_amt#110) + ws_ext_sales_price#111) / 2))] +Aggregate Attributes [1]: [sum(((((ws_ext_list_price#113 - ws_ext_wholesale_cost#112) - ws_ext_discount_amt#110) + ws_ext_sales_price#111) / 2))#122] +Results [2]: [c_customer_id#102 AS customer_id#123, sum(((((ws_ext_list_price#113 - ws_ext_wholesale_cost#112) - ws_ext_discount_amt#110) + ws_ext_sales_price#111) / 2))#122 AS year_total#124] + +(86) Filter [codegen id : 19] +Input [2]: [customer_id#123, year_total#124] +Condition : (isnotnull(year_total#124) AND (year_total#124 > 0.000000)) + +(87) BroadcastExchange +Input [2]: [customer_id#123, year_total#124] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=14] + +(88) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [customer_id#23] +Right keys [1]: [customer_id#123] +Join type: Inner +Join condition: None + +(89) Project [codegen id : 24] +Output [11]: [customer_id#23, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#77, year_total#100, year_total#124] +Input [12]: [customer_id#23, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#77, year_total#100, customer_id#123, year_total#124] + +(90) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#125, c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(91) ColumnarToRow [codegen id : 22] +Input [8]: [c_customer_sk#125, c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132] + +(92) Filter [codegen id : 22] +Input [8]: [c_customer_sk#125, c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132] +Condition : (isnotnull(c_customer_sk#125) AND isnotnull(c_customer_id#126)) + +(93) Scan parquet spark_catalog.default.web_sales +Output [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#138), dynamicpruningexpression(ws_sold_date_sk#138 IN dynamicpruning#139)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(94) ColumnarToRow [codegen id : 20] +Input [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] + +(95) Filter [codegen id : 20] +Input [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] +Condition : isnotnull(ws_bill_customer_sk#133) + +(96) BroadcastExchange +Input [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=15] + +(97) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [c_customer_sk#125] +Right keys [1]: [ws_bill_customer_sk#133] +Join type: Inner +Join condition: None + +(98) Project [codegen id : 22] +Output [12]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] +Input [14]: [c_customer_sk#125, c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] + +(99) ReusedExchange [Reuses operator id: 116] +Output [2]: [d_date_sk#140, d_year#141] + +(100) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [ws_sold_date_sk#138] +Right keys [1]: [d_date_sk#140] +Join type: Inner +Join condition: None + +(101) Project [codegen id : 22] +Output [12]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, d_year#141] +Input [14]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138, d_date_sk#140, d_year#141] + +(102) HashAggregate [codegen id : 22] +Input [12]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, d_year#141] +Keys [8]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141] +Functions [1]: [partial_sum(((((ws_ext_list_price#137 - ws_ext_wholesale_cost#136) - ws_ext_discount_amt#134) + ws_ext_sales_price#135) / 2))] +Aggregate Attributes [2]: [sum#142, isEmpty#143] +Results [10]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141, sum#144, isEmpty#145] + +(103) Exchange +Input [10]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141, sum#144, isEmpty#145] +Arguments: hashpartitioning(c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141, 5), ENSURE_REQUIREMENTS, [plan_id=16] + +(104) HashAggregate [codegen id : 23] +Input [10]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141, sum#144, isEmpty#145] +Keys [8]: [c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132, d_year#141] +Functions [1]: [sum(((((ws_ext_list_price#137 - ws_ext_wholesale_cost#136) - ws_ext_discount_amt#134) + ws_ext_sales_price#135) / 2))] +Aggregate Attributes [1]: [sum(((((ws_ext_list_price#137 - ws_ext_wholesale_cost#136) - ws_ext_discount_amt#134) + ws_ext_sales_price#135) / 2))#122] +Results [2]: [c_customer_id#126 AS customer_id#146, sum(((((ws_ext_list_price#137 - ws_ext_wholesale_cost#136) - ws_ext_discount_amt#134) + ws_ext_sales_price#135) / 2))#122 AS year_total#147] + +(105) BroadcastExchange +Input [2]: [customer_id#146, year_total#147] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=17] + +(106) BroadcastHashJoin [codegen id : 24] +Left keys [1]: [customer_id#23] +Right keys [1]: [customer_id#146] +Join type: Inner +Join condition: (CASE WHEN (year_total#77 > 0.000000) THEN (year_total#100 / year_total#77) END > CASE WHEN (year_total#124 > 0.000000) THEN (year_total#147 / year_total#124) END) + +(107) Project [codegen id : 24] +Output [7]: [customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52] +Input [13]: [customer_id#23, customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52, year_total#77, year_total#100, year_total#124, customer_id#146, year_total#147] + +(108) TakeOrderedAndProject +Input [7]: [customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52] +Arguments: 100, [customer_id#46 ASC NULLS FIRST, customer_first_name#47 ASC NULLS FIRST, customer_last_name#48 ASC NULLS FIRST, customer_preferred_cust_flag#49 ASC NULLS FIRST, customer_birth_country#50 ASC NULLS FIRST, customer_login#51 ASC NULLS FIRST, customer_email_address#52 ASC NULLS FIRST], [customer_id#46, customer_first_name#47, customer_last_name#48, customer_preferred_cust_flag#49, customer_birth_country#50, customer_login#51, customer_email_address#52] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#14 IN dynamicpruning#15 +BroadcastExchange (112) ++- * Filter (111) + +- * ColumnarToRow (110) + +- CometScan parquet spark_catalog.default.date_dim (109) + + +(109) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#16, d_year#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(110) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#16, d_year#17] + +(111) Filter [codegen id : 1] +Input [2]: [d_date_sk#16, d_year#17] +Condition : ((isnotnull(d_year#17) AND (d_year#17 = 2001)) AND isnotnull(d_date_sk#16)) + +(112) BroadcastExchange +Input [2]: [d_date_sk#16, d_year#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=18] + +Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#38 IN dynamicpruning#39 +BroadcastExchange (116) ++- * Filter (115) + +- * ColumnarToRow (114) + +- CometScan parquet spark_catalog.default.date_dim (113) + + +(113) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#40, d_year#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(114) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#40, d_year#41] + +(115) Filter [codegen id : 1] +Input [2]: [d_date_sk#40, d_year#41] +Condition : ((isnotnull(d_year#41) AND (d_year#41 = 2002)) AND isnotnull(d_date_sk#40)) + +(116) BroadcastExchange +Input [2]: [d_date_sk#40, d_year#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=19] + +Subquery:3 Hosting operator id = 37 Hosting Expression = cs_sold_date_sk#67 IN dynamicpruning#15 + +Subquery:4 Hosting operator id = 56 Hosting Expression = cs_sold_date_sk#91 IN dynamicpruning#39 + +Subquery:5 Hosting operator id = 74 Hosting Expression = ws_sold_date_sk#114 IN dynamicpruning#15 + +Subquery:6 Hosting operator id = 93 Hosting Expression = ws_sold_date_sk#138 IN dynamicpruning#39 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/simplified.txt new file mode 100644 index 000000000..f21b1c557 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/simplified.txt @@ -0,0 +1,179 @@ +TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address] + WholeStageCodegen (24) + Project [customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address,year_total,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + Project [customer_id,customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,year_total,customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + BroadcastHashJoin [customer_id,customer_id] + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((ss_ext_list_price - ss_ext_wholesale_cost) - ss_ext_discount_amt) + ss_ext_sales_price) / 2)),customer_id,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #1 + WholeStageCodegen (3) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ss_ext_list_price,ss_ext_wholesale_cost,ss_ext_discount_amt,ss_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((ss_ext_list_price - ss_ext_wholesale_cost) - ss_ext_discount_amt) + ss_ext_sales_price) / 2)),customer_id,customer_first_name,customer_last_name,customer_preferred_cust_flag,customer_birth_country,customer_login,customer_email_address,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #5 + WholeStageCodegen (6) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ss_ext_list_price,ss_ext_wholesale_cost,ss_ext_discount_amt,ss_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((cs_ext_list_price - cs_ext_wholesale_cost) - cs_ext_discount_amt) + cs_ext_sales_price) / 2)),customer_id,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #9 + WholeStageCodegen (10) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,cs_ext_list_price,cs_ext_wholesale_cost,cs_ext_discount_amt,cs_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] + BroadcastHashJoin [c_customer_sk,cs_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + Filter [cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((cs_ext_list_price - cs_ext_wholesale_cost) - cs_ext_discount_amt) + cs_ext_sales_price) / 2)),customer_id,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #12 + WholeStageCodegen (14) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,cs_ext_list_price,cs_ext_wholesale_cost,cs_ext_discount_amt,cs_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] + BroadcastHashJoin [c_customer_sk,cs_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (12) + Filter [cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #14 + WholeStageCodegen (19) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((ws_ext_list_price - ws_ext_wholesale_cost) - ws_ext_discount_amt) + ws_ext_sales_price) / 2)),customer_id,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #15 + WholeStageCodegen (18) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_wholesale_cost,ws_ext_discount_amt,ws_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #16 + WholeStageCodegen (16) + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #17 + WholeStageCodegen (23) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum,isEmpty] [sum(((((ws_ext_list_price - ws_ext_wholesale_cost) - ws_ext_discount_amt) + ws_ext_sales_price) / 2)),customer_id,year_total,sum,isEmpty] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #18 + WholeStageCodegen (22) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_wholesale_cost,ws_ext_discount_amt,ws_ext_sales_price] [sum,isEmpty,sum,isEmpty] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #19 + WholeStageCodegen (20) + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/explain.txt new file mode 100644 index 000000000..67e36b91f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/explain.txt @@ -0,0 +1,218 @@ +== Physical Plan == +TakeOrderedAndProject (33) ++- * HashAggregate (32) + +- Exchange (31) + +- * HashAggregate (30) + +- * Project (29) + +- * BroadcastHashJoin Inner BuildRight (28) + :- * Project (26) + : +- * BroadcastHashJoin Inner BuildRight (25) + : :- * Project (19) + : : +- * BroadcastHashJoin Inner BuildRight (18) + : : :- * Project (13) + : : : +- * SortMergeJoin LeftOuter (12) + : : : :- * Sort (5) + : : : : +- Exchange (4) + : : : : +- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : +- * Sort (11) + : : : +- Exchange (10) + : : : +- * Project (9) + : : : +- * Filter (8) + : : : +- * ColumnarToRow (7) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (6) + : : +- BroadcastExchange (17) + : : +- * Filter (16) + : : +- * ColumnarToRow (15) + : : +- CometScan parquet spark_catalog.default.warehouse (14) + : +- BroadcastExchange (24) + : +- * Project (23) + : +- * Filter (22) + : +- * ColumnarToRow (21) + : +- CometScan parquet spark_catalog.default.item (20) + +- ReusedExchange (27) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(cs_warehouse_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] + +(3) Filter [codegen id : 1] +Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] +Condition : (isnotnull(cs_warehouse_sk#1) AND isnotnull(cs_item_sk#2)) + +(4) Exchange +Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] +Arguments: hashpartitioning(cs_order_number#3, cs_item_sk#2, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] +Arguments: [cs_order_number#3 ASC NULLS FIRST, cs_item_sk#2 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9, cr_returned_date_sk#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(7) ColumnarToRow [codegen id : 3] +Input [4]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9, cr_returned_date_sk#10] + +(8) Filter [codegen id : 3] +Input [4]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9, cr_returned_date_sk#10] +Condition : (isnotnull(cr_order_number#8) AND isnotnull(cr_item_sk#7)) + +(9) Project [codegen id : 3] +Output [3]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] +Input [4]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9, cr_returned_date_sk#10] + +(10) Exchange +Input [3]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] +Arguments: hashpartitioning(cr_order_number#8, cr_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [3]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] +Arguments: [cr_order_number#8 ASC NULLS FIRST, cr_item_sk#7 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 8] +Left keys [2]: [cs_order_number#3, cs_item_sk#2] +Right keys [2]: [cr_order_number#8, cr_item_sk#7] +Join type: LeftOuter +Join condition: None + +(13) Project [codegen id : 8] +Output [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9] +Input [8]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5, cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] + +(14) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#11, w_state#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 5] +Input [2]: [w_warehouse_sk#11, w_state#12] + +(16) Filter [codegen id : 5] +Input [2]: [w_warehouse_sk#11, w_state#12] +Condition : isnotnull(w_warehouse_sk#11) + +(17) BroadcastExchange +Input [2]: [w_warehouse_sk#11, w_state#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(18) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_warehouse_sk#1] +Right keys [1]: [w_warehouse_sk#11] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 8] +Output [5]: [cs_item_sk#2, cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9, w_state#12] +Input [7]: [cs_warehouse_sk#1, cs_item_sk#2, cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9, w_warehouse_sk#11, w_state#12] + +(20) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#13, i_item_id#14, i_current_price#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,0.99), LessThanOrEqual(i_current_price,1.49), IsNotNull(i_item_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 6] +Input [3]: [i_item_sk#13, i_item_id#14, i_current_price#15] + +(22) Filter [codegen id : 6] +Input [3]: [i_item_sk#13, i_item_id#14, i_current_price#15] +Condition : (((isnotnull(i_current_price#15) AND (i_current_price#15 >= 0.99)) AND (i_current_price#15 <= 1.49)) AND isnotnull(i_item_sk#13)) + +(23) Project [codegen id : 6] +Output [2]: [i_item_sk#13, i_item_id#14] +Input [3]: [i_item_sk#13, i_item_id#14, i_current_price#15] + +(24) BroadcastExchange +Input [2]: [i_item_sk#13, i_item_id#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(25) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_item_sk#2] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 8] +Output [5]: [cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9, w_state#12, i_item_id#14] +Input [7]: [cs_item_sk#2, cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9, w_state#12, i_item_sk#13, i_item_id#14] + +(27) ReusedExchange [Reuses operator id: 37] +Output [2]: [d_date_sk#16, d_date#17] + +(28) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#5] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 8] +Output [5]: [cs_sales_price#4, cr_refunded_cash#9, w_state#12, i_item_id#14, d_date#17] +Input [7]: [cs_sales_price#4, cs_sold_date_sk#5, cr_refunded_cash#9, w_state#12, i_item_id#14, d_date_sk#16, d_date#17] + +(30) HashAggregate [codegen id : 8] +Input [5]: [cs_sales_price#4, cr_refunded_cash#9, w_state#12, i_item_id#14, d_date#17] +Keys [2]: [w_state#12, i_item_id#14] +Functions [2]: [partial_sum(CASE WHEN (d_date#17 < 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END), partial_sum(CASE WHEN (d_date#17 >= 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)] +Aggregate Attributes [4]: [sum#18, isEmpty#19, sum#20, isEmpty#21] +Results [6]: [w_state#12, i_item_id#14, sum#22, isEmpty#23, sum#24, isEmpty#25] + +(31) Exchange +Input [6]: [w_state#12, i_item_id#14, sum#22, isEmpty#23, sum#24, isEmpty#25] +Arguments: hashpartitioning(w_state#12, i_item_id#14, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) HashAggregate [codegen id : 9] +Input [6]: [w_state#12, i_item_id#14, sum#22, isEmpty#23, sum#24, isEmpty#25] +Keys [2]: [w_state#12, i_item_id#14] +Functions [2]: [sum(CASE WHEN (d_date#17 < 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END), sum(CASE WHEN (d_date#17 >= 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)] +Aggregate Attributes [2]: [sum(CASE WHEN (d_date#17 < 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)#26, sum(CASE WHEN (d_date#17 >= 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)#27] +Results [4]: [w_state#12, i_item_id#14, sum(CASE WHEN (d_date#17 < 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)#26 AS sales_before#28, sum(CASE WHEN (d_date#17 >= 2000-03-11) THEN (cs_sales_price#4 - coalesce(cast(cr_refunded_cash#9 as decimal(12,2)), 0.00)) ELSE 0.00 END)#27 AS sales_after#29] + +(33) TakeOrderedAndProject +Input [4]: [w_state#12, i_item_id#14, sales_before#28, sales_after#29] +Arguments: 100, [w_state#12 ASC NULLS FIRST, i_item_id#14 ASC NULLS FIRST], [w_state#12, i_item_id#14, sales_before#28, sales_after#29] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (37) ++- * Filter (36) + +- * ColumnarToRow (35) + +- CometScan parquet spark_catalog.default.date_dim (34) + + +(34) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#16, d_date#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-02-10), LessThanOrEqual(d_date,2000-04-10), IsNotNull(d_date_sk)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#16, d_date#17] + +(36) Filter [codegen id : 1] +Input [2]: [d_date_sk#16, d_date#17] +Condition : (((isnotnull(d_date#17) AND (d_date#17 >= 2000-02-10)) AND (d_date#17 <= 2000-04-10)) AND isnotnull(d_date_sk#16)) + +(37) BroadcastExchange +Input [2]: [d_date_sk#16, d_date#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/simplified.txt new file mode 100644 index 000000000..6234f2520 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/simplified.txt @@ -0,0 +1,60 @@ +TakeOrderedAndProject [w_state,i_item_id,sales_before,sales_after] + WholeStageCodegen (9) + HashAggregate [w_state,i_item_id,sum,isEmpty,sum,isEmpty] [sum(CASE WHEN (d_date < 2000-03-11) THEN (cs_sales_price - coalesce(cast(cr_refunded_cash as decimal(12,2)), 0.00)) ELSE 0.00 END),sum(CASE WHEN (d_date >= 2000-03-11) THEN (cs_sales_price - coalesce(cast(cr_refunded_cash as decimal(12,2)), 0.00)) ELSE 0.00 END),sales_before,sales_after,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [w_state,i_item_id] #1 + WholeStageCodegen (8) + HashAggregate [w_state,i_item_id,d_date,cs_sales_price,cr_refunded_cash] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Project [cs_sales_price,cr_refunded_cash,w_state,i_item_id,d_date] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sales_price,cs_sold_date_sk,cr_refunded_cash,w_state,i_item_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_sales_price,cs_sold_date_sk,cr_refunded_cash,w_state] + BroadcastHashJoin [cs_warehouse_sk,w_warehouse_sk] + Project [cs_warehouse_sk,cs_item_sk,cs_sales_price,cs_sold_date_sk,cr_refunded_cash] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #2 + WholeStageCodegen (1) + Filter [cs_warehouse_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_warehouse_sk,cs_item_sk,cs_order_number,cs_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + WholeStageCodegen (4) + Sort [cr_order_number,cr_item_sk] + InputAdapter + Exchange [cr_order_number,cr_item_sk] #4 + WholeStageCodegen (3) + Project [cr_item_sk,cr_order_number,cr_refunded_cash] + Filter [cr_order_number,cr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_refunded_cash,cr_returned_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (5) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_state] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Project [i_item_sk,i_item_id] + Filter [i_current_price,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_current_price] + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/explain.txt new file mode 100644 index 000000000..38fe288b5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/explain.txt @@ -0,0 +1,121 @@ +== Physical Plan == +TakeOrderedAndProject (20) ++- * HashAggregate (19) + +- Exchange (18) + +- * HashAggregate (17) + +- * Project (16) + +- * BroadcastHashJoin Inner BuildRight (15) + :- * Project (4) + : +- * Filter (3) + : +- * ColumnarToRow (2) + : +- CometScan parquet spark_catalog.default.item (1) + +- BroadcastExchange (14) + +- * Project (13) + +- * Filter (12) + +- * HashAggregate (11) + +- Exchange (10) + +- * HashAggregate (9) + +- * Project (8) + +- * Filter (7) + +- * ColumnarToRow (6) + +- CometScan parquet spark_catalog.default.item (5) + + +(1) Scan parquet spark_catalog.default.item +Output [3]: [i_manufact_id#1, i_manufact#2, i_product_name#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manufact_id), GreaterThanOrEqual(i_manufact_id,738), LessThanOrEqual(i_manufact_id,778), IsNotNull(i_manufact)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [i_manufact_id#1, i_manufact#2, i_product_name#3] + +(3) Filter [codegen id : 3] +Input [3]: [i_manufact_id#1, i_manufact#2, i_product_name#3] +Condition : (((isnotnull(i_manufact_id#1) AND (i_manufact_id#1 >= 738)) AND (i_manufact_id#1 <= 778)) AND isnotnull(i_manufact#2)) + +(4) Project [codegen id : 3] +Output [2]: [i_manufact#2, i_product_name#3] +Input [3]: [i_manufact_id#1, i_manufact#2, i_product_name#3] + +(5) Scan parquet spark_catalog.default.item +Output [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [Or(Or(And(EqualTo(i_category,Women ),Or(And(And(Or(EqualTo(i_color,powder ),EqualTo(i_color,khaki )),Or(EqualTo(i_units,Ounce ),EqualTo(i_units,Oz ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large ))),And(And(Or(EqualTo(i_color,brown ),EqualTo(i_color,honeydew )),Or(EqualTo(i_units,Bunch ),EqualTo(i_units,Ton ))),Or(EqualTo(i_size,N/A ),EqualTo(i_size,small ))))),And(EqualTo(i_category,Men ),Or(And(And(Or(EqualTo(i_color,floral ),EqualTo(i_color,deep )),Or(EqualTo(i_units,N/A ),EqualTo(i_units,Dozen ))),Or(EqualTo(i_size,petite ),EqualTo(i_size,large ))),And(And(Or(EqualTo(i_color,light ),EqualTo(i_color,cornflower )),Or(EqualTo(i_units,Box ),EqualTo(i_units,Pound ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large )))))),Or(And(EqualTo(i_category,Women ),Or(And(And(Or(EqualTo(i_color,midnight ),EqualTo(i_color,snow )),Or(EqualTo(i_units,Pallet ),EqualTo(i_units,Gross ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large ))),And(And(Or(EqualTo(i_color,cyan ),EqualTo(i_color,papaya )),Or(EqualTo(i_units,Cup ),EqualTo(i_units,Dram ))),Or(EqualTo(i_size,N/A ),EqualTo(i_size,small ))))),And(EqualTo(i_category,Men ),Or(And(And(Or(EqualTo(i_color,orange ),EqualTo(i_color,frosted )),Or(EqualTo(i_units,Each ),EqualTo(i_units,Tbl ))),Or(EqualTo(i_size,petite ),EqualTo(i_size,large ))),And(And(Or(EqualTo(i_color,forest ),EqualTo(i_color,ghost )),Or(EqualTo(i_units,Lb ),EqualTo(i_units,Bundle ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large ))))))), IsNotNull(i_manufact)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] + +(7) Filter [codegen id : 1] +Input [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] +Condition : (((((i_category#4 = Women ) AND (((((i_color#7 = powder ) OR (i_color#7 = khaki )) AND ((i_units#8 = Ounce ) OR (i_units#8 = Oz ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large ))) OR ((((i_color#7 = brown ) OR (i_color#7 = honeydew )) AND ((i_units#8 = Bunch ) OR (i_units#8 = Ton ))) AND ((i_size#6 = N/A ) OR (i_size#6 = small ))))) OR ((i_category#4 = Men ) AND (((((i_color#7 = floral ) OR (i_color#7 = deep )) AND ((i_units#8 = N/A ) OR (i_units#8 = Dozen ))) AND ((i_size#6 = petite ) OR (i_size#6 = large ))) OR ((((i_color#7 = light ) OR (i_color#7 = cornflower )) AND ((i_units#8 = Box ) OR (i_units#8 = Pound ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large )))))) OR (((i_category#4 = Women ) AND (((((i_color#7 = midnight ) OR (i_color#7 = snow )) AND ((i_units#8 = Pallet ) OR (i_units#8 = Gross ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large ))) OR ((((i_color#7 = cyan ) OR (i_color#7 = papaya )) AND ((i_units#8 = Cup ) OR (i_units#8 = Dram ))) AND ((i_size#6 = N/A ) OR (i_size#6 = small ))))) OR ((i_category#4 = Men ) AND (((((i_color#7 = orange ) OR (i_color#7 = frosted )) AND ((i_units#8 = Each ) OR (i_units#8 = Tbl ))) AND ((i_size#6 = petite ) OR (i_size#6 = large ))) OR ((((i_color#7 = forest ) OR (i_color#7 = ghost )) AND ((i_units#8 = Lb ) OR (i_units#8 = Bundle ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large ))))))) AND isnotnull(i_manufact#5)) + +(8) Project [codegen id : 1] +Output [1]: [i_manufact#5] +Input [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] + +(9) HashAggregate [codegen id : 1] +Input [1]: [i_manufact#5] +Keys [1]: [i_manufact#5] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#9] +Results [2]: [i_manufact#5, count#10] + +(10) Exchange +Input [2]: [i_manufact#5, count#10] +Arguments: hashpartitioning(i_manufact#5, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(11) HashAggregate [codegen id : 2] +Input [2]: [i_manufact#5, count#10] +Keys [1]: [i_manufact#5] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#11] +Results [2]: [count(1)#11 AS item_cnt#12, i_manufact#5] + +(12) Filter [codegen id : 2] +Input [2]: [item_cnt#12, i_manufact#5] +Condition : (item_cnt#12 > 0) + +(13) Project [codegen id : 2] +Output [1]: [i_manufact#5] +Input [2]: [item_cnt#12, i_manufact#5] + +(14) BroadcastExchange +Input [1]: [i_manufact#5] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [i_manufact#2] +Right keys [1]: [i_manufact#5] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 3] +Output [1]: [i_product_name#3] +Input [3]: [i_manufact#2, i_product_name#3, i_manufact#5] + +(17) HashAggregate [codegen id : 3] +Input [1]: [i_product_name#3] +Keys [1]: [i_product_name#3] +Functions: [] +Aggregate Attributes: [] +Results [1]: [i_product_name#3] + +(18) Exchange +Input [1]: [i_product_name#3] +Arguments: hashpartitioning(i_product_name#3, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(19) HashAggregate [codegen id : 4] +Input [1]: [i_product_name#3] +Keys [1]: [i_product_name#3] +Functions: [] +Aggregate Attributes: [] +Results [1]: [i_product_name#3] + +(20) TakeOrderedAndProject +Input [1]: [i_product_name#3] +Arguments: 100, [i_product_name#3 ASC NULLS FIRST], [i_product_name#3] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/simplified.txt new file mode 100644 index 000000000..3d12af6f4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/simplified.txt @@ -0,0 +1,29 @@ +TakeOrderedAndProject [i_product_name] + WholeStageCodegen (4) + HashAggregate [i_product_name] + InputAdapter + Exchange [i_product_name] #1 + WholeStageCodegen (3) + HashAggregate [i_product_name] + Project [i_product_name] + BroadcastHashJoin [i_manufact,i_manufact] + Project [i_manufact,i_product_name] + Filter [i_manufact_id,i_manufact] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_manufact_id,i_manufact,i_product_name] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [i_manufact] + Filter [item_cnt] + HashAggregate [i_manufact,count] [count(1),item_cnt,count] + InputAdapter + Exchange [i_manufact] #3 + WholeStageCodegen (1) + HashAggregate [i_manufact] [count,count] + Project [i_manufact] + Filter [i_category,i_color,i_units,i_size,i_manufact] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_category,i_manufact,i_size,i_color,i_units] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/explain.txt new file mode 100644 index 000000000..b458c6b45 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/explain.txt @@ -0,0 +1,125 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * HashAggregate (20) + +- Exchange (19) + +- * HashAggregate (18) + +- * Project (17) + +- * BroadcastHashJoin Inner BuildRight (16) + :- * Project (10) + : +- * BroadcastHashJoin Inner BuildRight (9) + : :- * Project (4) + : : +- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.date_dim (1) + : +- BroadcastExchange (8) + : +- * Filter (7) + : +- * ColumnarToRow (6) + : +- CometScan parquet spark_catalog.default.store_sales (5) + +- BroadcastExchange (15) + +- * Project (14) + +- * Filter (13) + +- * ColumnarToRow (12) + +- CometScan parquet spark_catalog.default.item (11) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_moy#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] + +(3) Filter [codegen id : 3] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 2000)) AND isnotnull(d_date_sk#1)) + +(4) Project [codegen id : 3] +Output [2]: [d_date_sk#1, d_year#2] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] + +(5) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(7) Filter [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) + +(8) BroadcastExchange +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#6] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [3]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5] +Input [5]: [d_date_sk#1, d_year#2, ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(11) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#7, i_category_id#8, i_category#9, i_manager_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,1), IsNotNull(i_item_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [4]: [i_item_sk#7, i_category_id#8, i_category#9, i_manager_id#10] + +(13) Filter [codegen id : 2] +Input [4]: [i_item_sk#7, i_category_id#8, i_category#9, i_manager_id#10] +Condition : ((isnotnull(i_manager_id#10) AND (i_manager_id#10 = 1)) AND isnotnull(i_item_sk#7)) + +(14) Project [codegen id : 2] +Output [3]: [i_item_sk#7, i_category_id#8, i_category#9] +Input [4]: [i_item_sk#7, i_category_id#8, i_category#9, i_manager_id#10] + +(15) BroadcastExchange +Input [3]: [i_item_sk#7, i_category_id#8, i_category#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#4] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [4]: [d_year#2, ss_ext_sales_price#5, i_category_id#8, i_category#9] +Input [6]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5, i_item_sk#7, i_category_id#8, i_category#9] + +(18) HashAggregate [codegen id : 3] +Input [4]: [d_year#2, ss_ext_sales_price#5, i_category_id#8, i_category#9] +Keys [3]: [d_year#2, i_category_id#8, i_category#9] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum#11] +Results [4]: [d_year#2, i_category_id#8, i_category#9, sum#12] + +(19) Exchange +Input [4]: [d_year#2, i_category_id#8, i_category#9, sum#12] +Arguments: hashpartitioning(d_year#2, i_category_id#8, i_category#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 4] +Input [4]: [d_year#2, i_category_id#8, i_category#9, sum#12] +Keys [3]: [d_year#2, i_category_id#8, i_category#9] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#5))#13] +Results [4]: [d_year#2, i_category_id#8, i_category#9, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#13,17,2) AS sum(ss_ext_sales_price)#14] + +(21) TakeOrderedAndProject +Input [4]: [d_year#2, i_category_id#8, i_category#9, sum(ss_ext_sales_price)#14] +Arguments: 100, [sum(ss_ext_sales_price)#14 DESC NULLS LAST, d_year#2 ASC NULLS FIRST, i_category_id#8 ASC NULLS FIRST, i_category#9 ASC NULLS FIRST], [d_year#2, i_category_id#8, i_category#9, sum(ss_ext_sales_price)#14] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/simplified.txt new file mode 100644 index 000000000..2b6ed6411 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/simplified.txt @@ -0,0 +1,31 @@ +TakeOrderedAndProject [sum(ss_ext_sales_price),d_year,i_category_id,i_category] + WholeStageCodegen (4) + HashAggregate [d_year,i_category_id,i_category,sum] [sum(UnscaledValue(ss_ext_sales_price)),sum(ss_ext_sales_price),sum] + InputAdapter + Exchange [d_year,i_category_id,i_category] #1 + WholeStageCodegen (3) + HashAggregate [d_year,i_category_id,i_category,ss_ext_sales_price] [sum,sum] + Project [d_year,ss_ext_sales_price,i_category_id,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [d_year,ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + Project [d_date_sk,d_year] + Filter [d_moy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [i_item_sk,i_category_id,i_category] + Filter [i_manager_id,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_category_id,i_category,i_manager_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/explain.txt new file mode 100644 index 000000000..925d9f3df --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/explain.txt @@ -0,0 +1,125 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * HashAggregate (20) + +- Exchange (19) + +- * HashAggregate (18) + +- * Project (17) + +- * BroadcastHashJoin Inner BuildRight (16) + :- * Project (10) + : +- * BroadcastHashJoin Inner BuildRight (9) + : :- * Project (4) + : : +- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.date_dim (1) + : +- BroadcastExchange (8) + : +- * Filter (7) + : +- * ColumnarToRow (6) + : +- CometScan parquet spark_catalog.default.store_sales (5) + +- BroadcastExchange (15) + +- * Project (14) + +- * Filter (13) + +- * ColumnarToRow (12) + +- CometScan parquet spark_catalog.default.store (11) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_day_name#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [d_date_sk#1, d_year#2, d_day_name#3] + +(3) Filter [codegen id : 3] +Input [3]: [d_date_sk#1, d_year#2, d_day_name#3] +Condition : ((isnotnull(d_year#2) AND (d_year#2 = 2000)) AND isnotnull(d_date_sk#1)) + +(4) Project [codegen id : 3] +Output [2]: [d_date_sk#1, d_day_name#3] +Input [3]: [d_date_sk#1, d_year#2, d_day_name#3] + +(5) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] + +(7) Filter [codegen id : 1] +Input [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_store_sk#4) + +(8) BroadcastExchange +Input [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#6] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [3]: [d_day_name#3, ss_store_sk#4, ss_sales_price#5] +Input [5]: [d_date_sk#1, d_day_name#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] + +(11) Scan parquet spark_catalog.default.store +Output [4]: [s_store_sk#7, s_store_id#8, s_store_name#9, s_gmt_offset#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_gmt_offset), EqualTo(s_gmt_offset,-5.00), IsNotNull(s_store_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [4]: [s_store_sk#7, s_store_id#8, s_store_name#9, s_gmt_offset#10] + +(13) Filter [codegen id : 2] +Input [4]: [s_store_sk#7, s_store_id#8, s_store_name#9, s_gmt_offset#10] +Condition : ((isnotnull(s_gmt_offset#10) AND (s_gmt_offset#10 = -5.00)) AND isnotnull(s_store_sk#7)) + +(14) Project [codegen id : 2] +Output [3]: [s_store_sk#7, s_store_id#8, s_store_name#9] +Input [4]: [s_store_sk#7, s_store_id#8, s_store_name#9, s_gmt_offset#10] + +(15) BroadcastExchange +Input [3]: [s_store_sk#7, s_store_id#8, s_store_name#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [s_store_sk#7] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [4]: [d_day_name#3, ss_sales_price#5, s_store_id#8, s_store_name#9] +Input [6]: [d_day_name#3, ss_store_sk#4, ss_sales_price#5, s_store_sk#7, s_store_id#8, s_store_name#9] + +(18) HashAggregate [codegen id : 3] +Input [4]: [d_day_name#3, ss_sales_price#5, s_store_id#8, s_store_name#9] +Keys [2]: [s_store_name#9, s_store_id#8] +Functions [7]: [partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Sunday ) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Monday ) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Tuesday ) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Wednesday) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Thursday ) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Friday ) THEN ss_sales_price#5 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#3 = Saturday ) THEN ss_sales_price#5 END))] +Aggregate Attributes [7]: [sum#11, sum#12, sum#13, sum#14, sum#15, sum#16, sum#17] +Results [9]: [s_store_name#9, s_store_id#8, sum#18, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24] + +(19) Exchange +Input [9]: [s_store_name#9, s_store_id#8, sum#18, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24] +Arguments: hashpartitioning(s_store_name#9, s_store_id#8, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 4] +Input [9]: [s_store_name#9, s_store_id#8, sum#18, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24] +Keys [2]: [s_store_name#9, s_store_id#8] +Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#3 = Sunday ) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Monday ) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Tuesday ) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Wednesday) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Thursday ) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Friday ) THEN ss_sales_price#5 END)), sum(UnscaledValue(CASE WHEN (d_day_name#3 = Saturday ) THEN ss_sales_price#5 END))] +Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#3 = Sunday ) THEN ss_sales_price#5 END))#25, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Monday ) THEN ss_sales_price#5 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Tuesday ) THEN ss_sales_price#5 END))#27, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Wednesday) THEN ss_sales_price#5 END))#28, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Thursday ) THEN ss_sales_price#5 END))#29, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Friday ) THEN ss_sales_price#5 END))#30, sum(UnscaledValue(CASE WHEN (d_day_name#3 = Saturday ) THEN ss_sales_price#5 END))#31] +Results [9]: [s_store_name#9, s_store_id#8, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Sunday ) THEN ss_sales_price#5 END))#25,17,2) AS sun_sales#32, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Monday ) THEN ss_sales_price#5 END))#26,17,2) AS mon_sales#33, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Tuesday ) THEN ss_sales_price#5 END))#27,17,2) AS tue_sales#34, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Wednesday) THEN ss_sales_price#5 END))#28,17,2) AS wed_sales#35, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Thursday ) THEN ss_sales_price#5 END))#29,17,2) AS thu_sales#36, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Friday ) THEN ss_sales_price#5 END))#30,17,2) AS fri_sales#37, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#3 = Saturday ) THEN ss_sales_price#5 END))#31,17,2) AS sat_sales#38] + +(21) TakeOrderedAndProject +Input [9]: [s_store_name#9, s_store_id#8, sun_sales#32, mon_sales#33, tue_sales#34, wed_sales#35, thu_sales#36, fri_sales#37, sat_sales#38] +Arguments: 100, [s_store_name#9 ASC NULLS FIRST, s_store_id#8 ASC NULLS FIRST, sun_sales#32 ASC NULLS FIRST, mon_sales#33 ASC NULLS FIRST, tue_sales#34 ASC NULLS FIRST, wed_sales#35 ASC NULLS FIRST, thu_sales#36 ASC NULLS FIRST, fri_sales#37 ASC NULLS FIRST, sat_sales#38 ASC NULLS FIRST], [s_store_name#9, s_store_id#8, sun_sales#32, mon_sales#33, tue_sales#34, wed_sales#35, thu_sales#36, fri_sales#37, sat_sales#38] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/simplified.txt new file mode 100644 index 000000000..b00665aed --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/simplified.txt @@ -0,0 +1,31 @@ +TakeOrderedAndProject [s_store_name,s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] + WholeStageCodegen (4) + HashAggregate [s_store_name,s_store_id,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN ss_sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] + InputAdapter + Exchange [s_store_name,s_store_id] #1 + WholeStageCodegen (3) + HashAggregate [s_store_name,s_store_id,d_day_name,ss_sales_price] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [d_day_name,ss_sales_price,s_store_id,s_store_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [d_day_name,ss_store_sk,ss_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + Project [d_date_sk,d_day_name] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_day_name] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [s_store_sk,s_store_id,s_store_name] + Filter [s_gmt_offset,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name,s_gmt_offset] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/explain.txt new file mode 100644 index 000000000..ba9e48ec7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/explain.txt @@ -0,0 +1,286 @@ +== Physical Plan == +TakeOrderedAndProject (43) ++- * Project (42) + +- * BroadcastHashJoin Inner BuildRight (41) + :- * Project (39) + : +- * BroadcastHashJoin Inner BuildRight (38) + : :- * Project (33) + : : +- * SortMergeJoin Inner (32) + : : :- * Sort (18) + : : : +- Exchange (17) + : : : +- * Project (16) + : : : +- * Filter (15) + : : : +- Window (14) + : : : +- WindowGroupLimit (13) + : : : +- * Sort (12) + : : : +- Exchange (11) + : : : +- WindowGroupLimit (10) + : : : +- * Sort (9) + : : : +- * Filter (8) + : : : +- * HashAggregate (7) + : : : +- Exchange (6) + : : : +- * HashAggregate (5) + : : : +- * Project (4) + : : : +- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- * Sort (31) + : : +- Exchange (30) + : : +- * Project (29) + : : +- * Filter (28) + : : +- Window (27) + : : +- WindowGroupLimit (26) + : : +- * Sort (25) + : : +- Exchange (24) + : : +- WindowGroupLimit (23) + : : +- * Sort (22) + : : +- * Filter (21) + : : +- * HashAggregate (20) + : : +- ReusedExchange (19) + : +- BroadcastExchange (37) + : +- * Filter (36) + : +- * ColumnarToRow (35) + : +- CometScan parquet spark_catalog.default.item (34) + +- ReusedExchange (40) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_store_sk#2, ss_net_profit#3, ss_sold_date_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_store_sk), EqualTo(ss_store_sk,4)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_net_profit#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 1] +Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_store_sk#2) AND (ss_store_sk#2 = 4)) + +(4) Project [codegen id : 1] +Output [2]: [ss_item_sk#1, ss_net_profit#3] +Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_net_profit#3, ss_sold_date_sk#4] + +(5) HashAggregate [codegen id : 1] +Input [2]: [ss_item_sk#1, ss_net_profit#3] +Keys [1]: [ss_item_sk#1] +Functions [1]: [partial_avg(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [2]: [sum#5, count#6] +Results [3]: [ss_item_sk#1, sum#7, count#8] + +(6) Exchange +Input [3]: [ss_item_sk#1, sum#7, count#8] +Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(7) HashAggregate [codegen id : 2] +Input [3]: [ss_item_sk#1, sum#7, count#8] +Keys [1]: [ss_item_sk#1] +Functions [1]: [avg(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [1]: [avg(UnscaledValue(ss_net_profit#3))#9] +Results [2]: [ss_item_sk#1 AS item_sk#10, cast((avg(UnscaledValue(ss_net_profit#3))#9 / 100.0) as decimal(11,6)) AS rank_col#11] + +(8) Filter [codegen id : 2] +Input [2]: [item_sk#10, rank_col#11] +Condition : (isnotnull(rank_col#11) AND (cast(rank_col#11 as decimal(13,7)) > (0.9 * Subquery scalar-subquery#12, [id=#13]))) + +(9) Sort [codegen id : 2] +Input [2]: [item_sk#10, rank_col#11] +Arguments: [rank_col#11 ASC NULLS FIRST], false, 0 + +(10) WindowGroupLimit +Input [2]: [item_sk#10, rank_col#11] +Arguments: [rank_col#11 ASC NULLS FIRST], rank(rank_col#11), 10, Partial + +(11) Exchange +Input [2]: [item_sk#10, rank_col#11] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 3] +Input [2]: [item_sk#10, rank_col#11] +Arguments: [rank_col#11 ASC NULLS FIRST], false, 0 + +(13) WindowGroupLimit +Input [2]: [item_sk#10, rank_col#11] +Arguments: [rank_col#11 ASC NULLS FIRST], rank(rank_col#11), 10, Final + +(14) Window +Input [2]: [item_sk#10, rank_col#11] +Arguments: [rank(rank_col#11) windowspecdefinition(rank_col#11 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rnk#14], [rank_col#11 ASC NULLS FIRST] + +(15) Filter [codegen id : 4] +Input [3]: [item_sk#10, rank_col#11, rnk#14] +Condition : ((rnk#14 < 11) AND isnotnull(item_sk#10)) + +(16) Project [codegen id : 4] +Output [2]: [item_sk#10, rnk#14] +Input [3]: [item_sk#10, rank_col#11, rnk#14] + +(17) Exchange +Input [2]: [item_sk#10, rnk#14] +Arguments: hashpartitioning(rnk#14, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(18) Sort [codegen id : 5] +Input [2]: [item_sk#10, rnk#14] +Arguments: [rnk#14 ASC NULLS FIRST], false, 0 + +(19) ReusedExchange [Reuses operator id: 6] +Output [3]: [ss_item_sk#15, sum#16, count#17] + +(20) HashAggregate [codegen id : 7] +Input [3]: [ss_item_sk#15, sum#16, count#17] +Keys [1]: [ss_item_sk#15] +Functions [1]: [avg(UnscaledValue(ss_net_profit#18))] +Aggregate Attributes [1]: [avg(UnscaledValue(ss_net_profit#18))#19] +Results [2]: [ss_item_sk#15 AS item_sk#20, cast((avg(UnscaledValue(ss_net_profit#18))#19 / 100.0) as decimal(11,6)) AS rank_col#21] + +(21) Filter [codegen id : 7] +Input [2]: [item_sk#20, rank_col#21] +Condition : (isnotnull(rank_col#21) AND (cast(rank_col#21 as decimal(13,7)) > (0.9 * ReusedSubquery Subquery scalar-subquery#12, [id=#13]))) + +(22) Sort [codegen id : 7] +Input [2]: [item_sk#20, rank_col#21] +Arguments: [rank_col#21 DESC NULLS LAST], false, 0 + +(23) WindowGroupLimit +Input [2]: [item_sk#20, rank_col#21] +Arguments: [rank_col#21 DESC NULLS LAST], rank(rank_col#21), 10, Partial + +(24) Exchange +Input [2]: [item_sk#20, rank_col#21] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(25) Sort [codegen id : 8] +Input [2]: [item_sk#20, rank_col#21] +Arguments: [rank_col#21 DESC NULLS LAST], false, 0 + +(26) WindowGroupLimit +Input [2]: [item_sk#20, rank_col#21] +Arguments: [rank_col#21 DESC NULLS LAST], rank(rank_col#21), 10, Final + +(27) Window +Input [2]: [item_sk#20, rank_col#21] +Arguments: [rank(rank_col#21) windowspecdefinition(rank_col#21 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rnk#22], [rank_col#21 DESC NULLS LAST] + +(28) Filter [codegen id : 9] +Input [3]: [item_sk#20, rank_col#21, rnk#22] +Condition : ((rnk#22 < 11) AND isnotnull(item_sk#20)) + +(29) Project [codegen id : 9] +Output [2]: [item_sk#20, rnk#22] +Input [3]: [item_sk#20, rank_col#21, rnk#22] + +(30) Exchange +Input [2]: [item_sk#20, rnk#22] +Arguments: hashpartitioning(rnk#22, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(31) Sort [codegen id : 10] +Input [2]: [item_sk#20, rnk#22] +Arguments: [rnk#22 ASC NULLS FIRST], false, 0 + +(32) SortMergeJoin [codegen id : 13] +Left keys [1]: [rnk#14] +Right keys [1]: [rnk#22] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 13] +Output [3]: [item_sk#10, rnk#14, item_sk#20] +Input [4]: [item_sk#10, rnk#14, item_sk#20, rnk#22] + +(34) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#23, i_product_name#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 11] +Input [2]: [i_item_sk#23, i_product_name#24] + +(36) Filter [codegen id : 11] +Input [2]: [i_item_sk#23, i_product_name#24] +Condition : isnotnull(i_item_sk#23) + +(37) BroadcastExchange +Input [2]: [i_item_sk#23, i_product_name#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [item_sk#10] +Right keys [1]: [i_item_sk#23] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 13] +Output [3]: [rnk#14, item_sk#20, i_product_name#24] +Input [5]: [item_sk#10, rnk#14, item_sk#20, i_item_sk#23, i_product_name#24] + +(40) ReusedExchange [Reuses operator id: 37] +Output [2]: [i_item_sk#25, i_product_name#26] + +(41) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [item_sk#20] +Right keys [1]: [i_item_sk#25] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 13] +Output [3]: [rnk#14, i_product_name#24 AS best_performing#27, i_product_name#26 AS worst_performing#28] +Input [5]: [rnk#14, item_sk#20, i_product_name#24, i_item_sk#25, i_product_name#26] + +(43) TakeOrderedAndProject +Input [3]: [rnk#14, best_performing#27, worst_performing#28] +Arguments: 100, [rnk#14 ASC NULLS FIRST], [rnk#14, best_performing#27, worst_performing#28] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 8 Hosting Expression = Subquery scalar-subquery#12, [id=#13] +* HashAggregate (50) ++- Exchange (49) + +- * HashAggregate (48) + +- * Project (47) + +- * Filter (46) + +- * ColumnarToRow (45) + +- CometScan parquet spark_catalog.default.store_sales (44) + + +(44) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_addr_sk#29, ss_store_sk#30, ss_net_profit#31, ss_sold_date_sk#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_store_sk), EqualTo(ss_store_sk,4), IsNull(ss_addr_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 1] +Input [4]: [ss_addr_sk#29, ss_store_sk#30, ss_net_profit#31, ss_sold_date_sk#32] + +(46) Filter [codegen id : 1] +Input [4]: [ss_addr_sk#29, ss_store_sk#30, ss_net_profit#31, ss_sold_date_sk#32] +Condition : ((isnotnull(ss_store_sk#30) AND (ss_store_sk#30 = 4)) AND isnull(ss_addr_sk#29)) + +(47) Project [codegen id : 1] +Output [2]: [ss_store_sk#30, ss_net_profit#31] +Input [4]: [ss_addr_sk#29, ss_store_sk#30, ss_net_profit#31, ss_sold_date_sk#32] + +(48) HashAggregate [codegen id : 1] +Input [2]: [ss_store_sk#30, ss_net_profit#31] +Keys [1]: [ss_store_sk#30] +Functions [1]: [partial_avg(UnscaledValue(ss_net_profit#31))] +Aggregate Attributes [2]: [sum#33, count#34] +Results [3]: [ss_store_sk#30, sum#35, count#36] + +(49) Exchange +Input [3]: [ss_store_sk#30, sum#35, count#36] +Arguments: hashpartitioning(ss_store_sk#30, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(50) HashAggregate [codegen id : 2] +Input [3]: [ss_store_sk#30, sum#35, count#36] +Keys [1]: [ss_store_sk#30] +Functions [1]: [avg(UnscaledValue(ss_net_profit#31))] +Aggregate Attributes [1]: [avg(UnscaledValue(ss_net_profit#31))#37] +Results [1]: [cast((avg(UnscaledValue(ss_net_profit#31))#37 / 100.0) as decimal(11,6)) AS rank_col#38] + +Subquery:2 Hosting operator id = 21 Hosting Expression = ReusedSubquery Subquery scalar-subquery#12, [id=#13] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/simplified.txt new file mode 100644 index 000000000..adcad1417 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [rnk,best_performing,worst_performing] + WholeStageCodegen (13) + Project [rnk,i_product_name,i_product_name] + BroadcastHashJoin [item_sk,i_item_sk] + Project [rnk,item_sk,i_product_name] + BroadcastHashJoin [item_sk,i_item_sk] + Project [item_sk,rnk,item_sk] + SortMergeJoin [rnk,rnk] + InputAdapter + WholeStageCodegen (5) + Sort [rnk] + InputAdapter + Exchange [rnk] #1 + WholeStageCodegen (4) + Project [item_sk,rnk] + Filter [rnk,item_sk] + InputAdapter + Window [rank_col] + WindowGroupLimit [rank_col] + WholeStageCodegen (3) + Sort [rank_col] + InputAdapter + Exchange #2 + WindowGroupLimit [rank_col] + WholeStageCodegen (2) + Sort [rank_col] + Filter [rank_col] + Subquery #1 + WholeStageCodegen (2) + HashAggregate [ss_store_sk,sum,count] [avg(UnscaledValue(ss_net_profit)),rank_col,sum,count] + InputAdapter + Exchange [ss_store_sk] #4 + WholeStageCodegen (1) + HashAggregate [ss_store_sk,ss_net_profit] [sum,count,sum,count] + Project [ss_store_sk,ss_net_profit] + Filter [ss_store_sk,ss_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk] + HashAggregate [ss_item_sk,sum,count] [avg(UnscaledValue(ss_net_profit)),item_sk,rank_col,sum,count] + InputAdapter + Exchange [ss_item_sk] #3 + WholeStageCodegen (1) + HashAggregate [ss_item_sk,ss_net_profit] [sum,count,sum,count] + Project [ss_item_sk,ss_net_profit] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk] + InputAdapter + WholeStageCodegen (10) + Sort [rnk] + InputAdapter + Exchange [rnk] #5 + WholeStageCodegen (9) + Project [item_sk,rnk] + Filter [rnk,item_sk] + InputAdapter + Window [rank_col] + WindowGroupLimit [rank_col] + WholeStageCodegen (8) + Sort [rank_col] + InputAdapter + Exchange #6 + WindowGroupLimit [rank_col] + WholeStageCodegen (7) + Sort [rank_col] + Filter [rank_col] + ReusedSubquery [rank_col] #1 + HashAggregate [ss_item_sk,sum,count] [avg(UnscaledValue(ss_net_profit)),item_sk,rank_col,sum,count] + InputAdapter + ReusedExchange [ss_item_sk,sum,count] #3 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (11) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_product_name] + InputAdapter + ReusedExchange [i_item_sk,i_product_name] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/explain.txt new file mode 100644 index 000000000..aaf17cf45 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/explain.txt @@ -0,0 +1,242 @@ +== Physical Plan == +TakeOrderedAndProject (36) ++- * HashAggregate (35) + +- Exchange (34) + +- * HashAggregate (33) + +- * Project (32) + +- * Filter (31) + +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (30) + :- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.customer (4) + : : : +- BroadcastExchange (13) + : : : +- * Filter (12) + : : : +- * ColumnarToRow (11) + : : : +- CometScan parquet spark_catalog.default.customer_address (10) + : : +- ReusedExchange (16) + : +- BroadcastExchange (22) + : +- * Filter (21) + : +- * ColumnarToRow (20) + : +- CometScan parquet spark_catalog.default.item (19) + +- BroadcastExchange (29) + +- * Project (28) + +- * Filter (27) + +- * ColumnarToRow (26) + +- CometScan parquet spark_catalog.default.item (25) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#2, ws_bill_customer_sk#3, ws_sales_price#4, ws_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#5), dynamicpruningexpression(ws_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ws_bill_customer_sk), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 6] +Input [4]: [ws_item_sk#2, ws_bill_customer_sk#3, ws_sales_price#4, ws_sold_date_sk#5] + +(3) Filter [codegen id : 6] +Input [4]: [ws_item_sk#2, ws_bill_customer_sk#3, ws_sales_price#4, ws_sold_date_sk#5] +Condition : (isnotnull(ws_bill_customer_sk#3) AND isnotnull(ws_item_sk#2)) + +(4) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#7, c_current_addr_sk#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [c_customer_sk#7, c_current_addr_sk#8] + +(6) Filter [codegen id : 1] +Input [2]: [c_customer_sk#7, c_current_addr_sk#8] +Condition : (isnotnull(c_customer_sk#7) AND isnotnull(c_current_addr_sk#8)) + +(7) BroadcastExchange +Input [2]: [c_customer_sk#7, c_current_addr_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_bill_customer_sk#3] +Right keys [1]: [c_customer_sk#7] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 6] +Output [4]: [ws_item_sk#2, ws_sales_price#4, ws_sold_date_sk#5, c_current_addr_sk#8] +Input [6]: [ws_item_sk#2, ws_bill_customer_sk#3, ws_sales_price#4, ws_sold_date_sk#5, c_customer_sk#7, c_current_addr_sk#8] + +(10) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] + +(12) Filter [codegen id : 2] +Input [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] +Condition : isnotnull(ca_address_sk#9) + +(13) BroadcastExchange +Input [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_current_addr_sk#8] +Right keys [1]: [ca_address_sk#9] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 6] +Output [5]: [ws_item_sk#2, ws_sales_price#4, ws_sold_date_sk#5, ca_city#10, ca_zip#11] +Input [7]: [ws_item_sk#2, ws_sales_price#4, ws_sold_date_sk#5, c_current_addr_sk#8, ca_address_sk#9, ca_city#10, ca_zip#11] + +(16) ReusedExchange [Reuses operator id: 41] +Output [1]: [d_date_sk#12] + +(17) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#5] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 6] +Output [4]: [ws_item_sk#2, ws_sales_price#4, ca_city#10, ca_zip#11] +Input [6]: [ws_item_sk#2, ws_sales_price#4, ws_sold_date_sk#5, ca_city#10, ca_zip#11, d_date_sk#12] + +(19) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#13, i_item_id#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(20) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#13, i_item_id#14] + +(21) Filter [codegen id : 4] +Input [2]: [i_item_sk#13, i_item_id#14] +Condition : isnotnull(i_item_sk#13) + +(22) BroadcastExchange +Input [2]: [i_item_sk#13, i_item_id#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_item_sk#2] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [4]: [ws_sales_price#4, ca_city#10, ca_zip#11, i_item_id#14] +Input [6]: [ws_item_sk#2, ws_sales_price#4, ca_city#10, ca_zip#11, i_item_sk#13, i_item_id#14] + +(25) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#15, i_item_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_item_sk, [11,13,17,19,2,23,29,3,5,7])] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 5] +Input [2]: [i_item_sk#15, i_item_id#16] + +(27) Filter [codegen id : 5] +Input [2]: [i_item_sk#15, i_item_id#16] +Condition : i_item_sk#15 IN (2,3,5,7,11,13,17,19,23,29) + +(28) Project [codegen id : 5] +Output [1]: [i_item_id#16] +Input [2]: [i_item_sk#15, i_item_id#16] + +(29) BroadcastExchange +Input [1]: [i_item_id#16] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [i_item_id#14] +Right keys [1]: [i_item_id#16] +Join type: ExistenceJoin(exists#1) +Join condition: None + +(31) Filter [codegen id : 6] +Input [5]: [ws_sales_price#4, ca_city#10, ca_zip#11, i_item_id#14, exists#1] +Condition : (substr(ca_zip#11, 1, 5) IN (85669,86197,88274,83405,86475,85392,85460,80348,81792) OR exists#1) + +(32) Project [codegen id : 6] +Output [3]: [ws_sales_price#4, ca_city#10, ca_zip#11] +Input [5]: [ws_sales_price#4, ca_city#10, ca_zip#11, i_item_id#14, exists#1] + +(33) HashAggregate [codegen id : 6] +Input [3]: [ws_sales_price#4, ca_city#10, ca_zip#11] +Keys [2]: [ca_zip#11, ca_city#10] +Functions [1]: [partial_sum(UnscaledValue(ws_sales_price#4))] +Aggregate Attributes [1]: [sum#17] +Results [3]: [ca_zip#11, ca_city#10, sum#18] + +(34) Exchange +Input [3]: [ca_zip#11, ca_city#10, sum#18] +Arguments: hashpartitioning(ca_zip#11, ca_city#10, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(35) HashAggregate [codegen id : 7] +Input [3]: [ca_zip#11, ca_city#10, sum#18] +Keys [2]: [ca_zip#11, ca_city#10] +Functions [1]: [sum(UnscaledValue(ws_sales_price#4))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_sales_price#4))#19] +Results [3]: [ca_zip#11, ca_city#10, MakeDecimal(sum(UnscaledValue(ws_sales_price#4))#19,17,2) AS sum(ws_sales_price)#20] + +(36) TakeOrderedAndProject +Input [3]: [ca_zip#11, ca_city#10, sum(ws_sales_price)#20] +Arguments: 100, [ca_zip#11 ASC NULLS FIRST, ca_city#10 ASC NULLS FIRST], [ca_zip#11, ca_city#10, sum(ws_sales_price)#20] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (41) ++- * Project (40) + +- * Filter (39) + +- * ColumnarToRow (38) + +- CometScan parquet spark_catalog.default.date_dim (37) + + +(37) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#12, d_year#21, d_qoy#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(38) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#12, d_year#21, d_qoy#22] + +(39) Filter [codegen id : 1] +Input [3]: [d_date_sk#12, d_year#21, d_qoy#22] +Condition : ((((isnotnull(d_qoy#22) AND isnotnull(d_year#21)) AND (d_qoy#22 = 2)) AND (d_year#21 = 2001)) AND isnotnull(d_date_sk#12)) + +(40) Project [codegen id : 1] +Output [1]: [d_date_sk#12] +Input [3]: [d_date_sk#12, d_year#21, d_qoy#22] + +(41) BroadcastExchange +Input [1]: [d_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/simplified.txt new file mode 100644 index 000000000..05579f166 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/simplified.txt @@ -0,0 +1,61 @@ +TakeOrderedAndProject [ca_zip,ca_city,sum(ws_sales_price)] + WholeStageCodegen (7) + HashAggregate [ca_zip,ca_city,sum] [sum(UnscaledValue(ws_sales_price)),sum(ws_sales_price),sum] + InputAdapter + Exchange [ca_zip,ca_city] #1 + WholeStageCodegen (6) + HashAggregate [ca_zip,ca_city,ws_sales_price] [sum,sum] + Project [ws_sales_price,ca_city,ca_zip] + Filter [ca_zip,exists] + BroadcastHashJoin [i_item_id,i_item_id] + Project [ws_sales_price,ca_city,ca_zip,i_item_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_sales_price,ca_city,ca_zip] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_sales_price,ws_sold_date_sk,ca_city,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ws_item_sk,ws_sales_price,ws_sold_date_sk,c_current_addr_sk] + BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] + Filter [ws_bill_customer_sk,ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_qoy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [c_customer_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city,ca_zip] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Project [i_item_id] + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/explain.txt new file mode 100644 index 000000000..d51633680 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/explain.txt @@ -0,0 +1,258 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (35) + : +- * BroadcastHashJoin Inner BuildRight (34) + : :- * HashAggregate (29) + : : +- Exchange (28) + : : +- * HashAggregate (27) + : : +- * Project (26) + : : +- * BroadcastHashJoin Inner BuildRight (25) + : : :- * Project (20) + : : : +- * BroadcastHashJoin Inner BuildRight (19) + : : : :- * Project (13) + : : : : +- * BroadcastHashJoin Inner BuildRight (12) + : : : : :- * Project (6) + : : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : : :- * Filter (3) + : : : : : : +- * ColumnarToRow (2) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : +- ReusedExchange (4) + : : : : +- BroadcastExchange (11) + : : : : +- * Project (10) + : : : : +- * Filter (9) + : : : : +- * ColumnarToRow (8) + : : : : +- CometScan parquet spark_catalog.default.store (7) + : : : +- BroadcastExchange (18) + : : : +- * Project (17) + : : : +- * Filter (16) + : : : +- * ColumnarToRow (15) + : : : +- CometScan parquet spark_catalog.default.household_demographics (14) + : : +- BroadcastExchange (24) + : : +- * Filter (23) + : : +- * ColumnarToRow (22) + : : +- CometScan parquet spark_catalog.default.customer_address (21) + : +- BroadcastExchange (33) + : +- * Filter (32) + : +- * ColumnarToRow (31) + : +- CometScan parquet spark_catalog.default.customer (30) + +- ReusedExchange (36) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] + +(3) Filter [codegen id : 5] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] +Condition : (((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_customer_sk#1)) + +(4) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#10] + +(5) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 5] +Output [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8, d_date_sk#10] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_city#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [In(s_city, [Fairview,Midway]), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#11, s_city#12] + +(9) Filter [codegen id : 2] +Input [2]: [s_store_sk#11, s_city#12] +Condition : (s_city#12 IN (Fairview,Midway) AND isnotnull(s_store_sk#11)) + +(10) Project [codegen id : 2] +Output [1]: [s_store_sk#11] +Input [2]: [s_store_sk#11, s_city#12] + +(11) BroadcastExchange +Input [1]: [s_store_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [6]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_store_sk#11] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [3]: [hd_demo_sk#13, hd_dep_count#14, hd_vehicle_count#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [Or(EqualTo(hd_dep_count,4),EqualTo(hd_vehicle_count,3)), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [hd_demo_sk#13, hd_dep_count#14, hd_vehicle_count#15] + +(16) Filter [codegen id : 3] +Input [3]: [hd_demo_sk#13, hd_dep_count#14, hd_vehicle_count#15] +Condition : (((hd_dep_count#14 = 4) OR (hd_vehicle_count#15 = 3)) AND isnotnull(hd_demo_sk#13)) + +(17) Project [codegen id : 3] +Output [1]: [hd_demo_sk#13] +Input [3]: [hd_demo_sk#13, hd_dep_count#14, hd_vehicle_count#15] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#13] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 5] +Output [5]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7] +Input [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, hd_demo_sk#13] + +(21) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#16, ca_city#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_city)] +ReadSchema: struct + +(22) ColumnarToRow [codegen id : 4] +Input [2]: [ca_address_sk#16, ca_city#17] + +(23) Filter [codegen id : 4] +Input [2]: [ca_address_sk#16, ca_city#17] +Condition : (isnotnull(ca_address_sk#16) AND isnotnull(ca_city#17)) + +(24) BroadcastExchange +Input [2]: [ca_address_sk#16, ca_city#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#3] +Right keys [1]: [ca_address_sk#16] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 5] +Output [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ca_city#17] +Input [7]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ca_address_sk#16, ca_city#17] + +(27) HashAggregate [codegen id : 5] +Input [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ca_city#17] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17] +Functions [2]: [partial_sum(UnscaledValue(ss_coupon_amt#6)), partial_sum(UnscaledValue(ss_net_profit#7))] +Aggregate Attributes [2]: [sum#18, sum#19] +Results [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17, sum#20, sum#21] + +(28) Exchange +Input [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17, sum#20, sum#21] +Arguments: hashpartitioning(ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 8] +Input [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17, sum#20, sum#21] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#17] +Functions [2]: [sum(UnscaledValue(ss_coupon_amt#6)), sum(UnscaledValue(ss_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_coupon_amt#6))#22, sum(UnscaledValue(ss_net_profit#7))#23] +Results [5]: [ss_ticket_number#5, ss_customer_sk#1, ca_city#17 AS bought_city#24, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#6))#22,17,2) AS amt#25, MakeDecimal(sum(UnscaledValue(ss_net_profit#7))#23,17,2) AS profit#26] + +(30) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 6] +Input [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] + +(32) Filter [codegen id : 6] +Input [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] +Condition : (isnotnull(c_customer_sk#27) AND isnotnull(c_current_addr_sk#28)) + +(33) BroadcastExchange +Input [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#27] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [7]: [ss_ticket_number#5, bought_city#24, amt#25, profit#26, c_current_addr_sk#28, c_first_name#29, c_last_name#30] +Input [9]: [ss_ticket_number#5, ss_customer_sk#1, bought_city#24, amt#25, profit#26, c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] + +(36) ReusedExchange [Reuses operator id: 24] +Output [2]: [ca_address_sk#31, ca_city#32] + +(37) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [c_current_addr_sk#28] +Right keys [1]: [ca_address_sk#31] +Join type: Inner +Join condition: NOT (ca_city#32 = bought_city#24) + +(38) Project [codegen id : 8] +Output [7]: [c_last_name#30, c_first_name#29, ca_city#32, bought_city#24, ss_ticket_number#5, amt#25, profit#26] +Input [9]: [ss_ticket_number#5, bought_city#24, amt#25, profit#26, c_current_addr_sk#28, c_first_name#29, c_last_name#30, ca_address_sk#31, ca_city#32] + +(39) TakeOrderedAndProject +Input [7]: [c_last_name#30, c_first_name#29, ca_city#32, bought_city#24, ss_ticket_number#5, amt#25, profit#26] +Arguments: 100, [c_last_name#30 ASC NULLS FIRST, c_first_name#29 ASC NULLS FIRST, ca_city#32 ASC NULLS FIRST, bought_city#24 ASC NULLS FIRST, ss_ticket_number#5 ASC NULLS FIRST], [c_last_name#30, c_first_name#29, ca_city#32, bought_city#24, ss_ticket_number#5, amt#25, profit#26] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (44) ++- * Project (43) + +- * Filter (42) + +- * ColumnarToRow (41) + +- CometScan parquet spark_catalog.default.date_dim (40) + + +(40) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#33, d_dow#34] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_dow, [0,6]), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#33, d_dow#34] + +(42) Filter [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#33, d_dow#34] +Condition : ((d_dow#34 IN (6,0) AND d_year#33 IN (1999,2000,2001)) AND isnotnull(d_date_sk#10)) + +(43) Project [codegen id : 1] +Output [1]: [d_date_sk#10] +Input [3]: [d_date_sk#10, d_year#33, d_dow#34] + +(44) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/simplified.txt new file mode 100644 index 000000000..376fc2f62 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/simplified.txt @@ -0,0 +1,65 @@ +TakeOrderedAndProject [c_last_name,c_first_name,ca_city,bought_city,ss_ticket_number,amt,profit] + WholeStageCodegen (8) + Project [c_last_name,c_first_name,ca_city,bought_city,ss_ticket_number,amt,profit] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk,ca_city,bought_city] + Project [ss_ticket_number,bought_city,amt,profit,c_current_addr_sk,c_first_name,c_last_name] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city,sum,sum] [sum(UnscaledValue(ss_coupon_amt)),sum(UnscaledValue(ss_net_profit)),bought_city,amt,profit,sum,sum] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city] #1 + WholeStageCodegen (5) + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city,ss_coupon_amt,ss_net_profit] [sum,sum,sum,sum] + Project [ss_customer_sk,ss_addr_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,ca_city] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_customer_sk,ss_addr_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk,ss_hdemo_sk,ss_addr_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_dow,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dow] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [s_store_sk] + Filter [s_city,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_city] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Project [hd_demo_sk] + Filter [hd_dep_count,hd_vehicle_count,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Filter [ca_address_sk,ca_city] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Filter [c_customer_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name] + InputAdapter + ReusedExchange [ca_address_sk,ca_city] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/explain.txt new file mode 100644 index 000000000..74b0ed8ff --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/explain.txt @@ -0,0 +1,279 @@ +== Physical Plan == +TakeOrderedAndProject (45) ++- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (28) + : : +- * Filter (27) + : : +- Window (26) + : : +- * Filter (25) + : : +- Window (24) + : : +- * Sort (23) + : : +- Exchange (22) + : : +- * HashAggregate (21) + : : +- Exchange (20) + : : +- * HashAggregate (19) + : : +- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.item (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (16) + : : +- * Filter (15) + : : +- * ColumnarToRow (14) + : : +- CometScan parquet spark_catalog.default.store (13) + : +- BroadcastExchange (35) + : +- * Project (34) + : +- Window (33) + : +- * Sort (32) + : +- Exchange (31) + : +- * HashAggregate (30) + : +- ReusedExchange (29) + +- BroadcastExchange (42) + +- * Project (41) + +- Window (40) + +- * Sort (39) + +- ReusedExchange (38) + + +(1) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#1, i_brand#2, i_category#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] + +(3) Filter [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] + +(6) Filter [codegen id : 1] +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#4) AND isnotnull(ss_store_sk#5)) + +(7) BroadcastExchange +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#4] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [5]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Input [7]: [i_item_sk#1, i_brand#2, i_category#3, ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 49] +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, d_year#10, d_moy#11] +Input [8]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7, d_date_sk#9, d_year#10, d_moy#11] + +(13) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_company_name)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] + +(15) Filter [codegen id : 3] +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Condition : ((isnotnull(s_store_sk#12) AND isnotnull(s_store_name#13)) AND isnotnull(s_company_name#14)) + +(16) BroadcastExchange +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#5] +Right keys [1]: [s_store_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [7]: [i_brand#2, i_category#3, ss_sales_price#6, d_year#10, d_moy#11, s_store_name#13, s_company_name#14] +Input [9]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, d_year#10, d_moy#11, s_store_sk#12, s_store_name#13, s_company_name#14] + +(19) HashAggregate [codegen id : 4] +Input [7]: [i_brand#2, i_category#3, ss_sales_price#6, d_year#10, d_moy#11, s_store_name#13, s_company_name#14] +Keys [6]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [1]: [sum#15] +Results [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] + +(20) Exchange +Input [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] +Arguments: hashpartitioning(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] +Keys [6]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11] +Functions [1]: [sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#6))#17] +Results [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#17,17,2) AS sum_sales#18, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#17,17,2) AS _w0#19] + +(22) Exchange +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: hashpartitioning(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) Sort [codegen id : 6] +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: [i_category#3 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST, s_company_name#14 ASC NULLS FIRST, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST], false, 0 + +(24) Window +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: [rank(d_year#10, d_moy#11) windowspecdefinition(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#20], [i_category#3, i_brand#2, s_store_name#13, s_company_name#14], [d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST] + +(25) Filter [codegen id : 7] +Input [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20] +Condition : (isnotnull(d_year#10) AND (d_year#10 = 1999)) + +(26) Window +Input [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20] +Arguments: [avg(_w0#19) windowspecdefinition(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#21], [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10] + +(27) Filter [codegen id : 22] +Input [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20, avg_monthly_sales#21] +Condition : ((isnotnull(avg_monthly_sales#21) AND (avg_monthly_sales#21 > 0.000000)) AND CASE WHEN (avg_monthly_sales#21 > 0.000000) THEN ((abs((sum_sales#18 - avg_monthly_sales#21)) / avg_monthly_sales#21) > 0.1000000000000000) END) + +(28) Project [codegen id : 22] +Output [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20] +Input [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20, avg_monthly_sales#21] + +(29) ReusedExchange [Reuses operator id: 20] +Output [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum#28] + +(30) HashAggregate [codegen id : 12] +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum#28] +Keys [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27] +Functions [1]: [sum(UnscaledValue(ss_sales_price#29))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#29))#17] +Results [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, MakeDecimal(sum(UnscaledValue(ss_sales_price#29))#17,17,2) AS sum_sales#30] + +(31) Exchange +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: hashpartitioning(i_category#22, i_brand#23, s_store_name#24, s_company_name#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 13] +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: [i_category#22 ASC NULLS FIRST, i_brand#23 ASC NULLS FIRST, s_store_name#24 ASC NULLS FIRST, s_company_name#25 ASC NULLS FIRST, d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST], false, 0 + +(33) Window +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: [rank(d_year#26, d_moy#27) windowspecdefinition(i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#31], [i_category#22, i_brand#23, s_store_name#24, s_company_name#25], [d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST] + +(34) Project [codegen id : 14] +Output [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] +Input [8]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30, rn#31] + +(35) BroadcastExchange +Input [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], input[3, string, true], (input[5, int, false] + 1)),false), [plan_id=6] + +(36) BroadcastHashJoin [codegen id : 22] +Left keys [5]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, rn#20] +Right keys [5]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, (rn#31 + 1)] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 22] +Output [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, sum_sales#30] +Input [15]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] + +(38) ReusedExchange [Reuses operator id: 31] +Output [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] + +(39) Sort [codegen id : 20] +Input [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] +Arguments: [i_category#32 ASC NULLS FIRST, i_brand#33 ASC NULLS FIRST, s_store_name#34 ASC NULLS FIRST, s_company_name#35 ASC NULLS FIRST, d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST], false, 0 + +(40) Window +Input [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] +Arguments: [rank(d_year#36, d_moy#37) windowspecdefinition(i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#39], [i_category#32, i_brand#33, s_store_name#34, s_company_name#35], [d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST] + +(41) Project [codegen id : 21] +Output [6]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] +Input [8]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38, rn#39] + +(42) BroadcastExchange +Input [6]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], input[3, string, true], (input[5, int, false] - 1)),false), [plan_id=7] + +(43) BroadcastHashJoin [codegen id : 22] +Left keys [5]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, rn#20] +Right keys [5]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, (rn#39 - 1)] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 22] +Output [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, sum_sales#30 AS psum#40, sum_sales#38 AS nsum#41] +Input [16]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, sum_sales#30, i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] + +(45) TakeOrderedAndProject +Input [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, psum#40, nsum#41] +Arguments: 100, [(sum_sales#18 - avg_monthly_sales#21) ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST], [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, psum#40, nsum#41] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (49) ++- * Filter (48) + +- * ColumnarToRow (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(48) Filter [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) + +(49) BroadcastExchange +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/simplified.txt new file mode 100644 index 000000000..5dba00296 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [sum_sales,avg_monthly_sales,s_store_name,i_category,i_brand,s_company_name,d_year,d_moy,psum,nsum] + WholeStageCodegen (22) + Project [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,avg_monthly_sales,sum_sales,sum_sales,sum_sales] + BroadcastHashJoin [i_category,i_brand,s_store_name,s_company_name,rn,i_category,i_brand,s_store_name,s_company_name,rn] + Project [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn,sum_sales] + BroadcastHashJoin [i_category,i_brand,s_store_name,s_company_name,rn,i_category,i_brand,s_store_name,s_company_name,rn] + Project [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_category,i_brand,s_store_name,s_company_name,d_year] + WholeStageCodegen (7) + Filter [d_year] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (6) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,ss_sales_price] [sum,sum] + Project [i_brand,i_category,ss_sales_price,d_year,d_moy,s_store_name,s_company_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [i_brand,i_category,ss_store_sk,ss_sales_price,d_year,d_moy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [i_brand,i_category,ss_store_sk,ss_sales_price,ss_sold_date_sk] + BroadcastHashJoin [i_item_sk,ss_item_sk] + Filter [i_item_sk,i_category,i_brand] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [ss_item_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [s_store_sk,s_store_name,s_company_name] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (14) + Project [i_category,i_brand,s_store_name,s_company_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (13) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name] #7 + WholeStageCodegen (12) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,sum] + InputAdapter + ReusedExchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] #2 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (21) + Project [i_category,i_brand,s_store_name,s_company_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (20) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + ReusedExchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/explain.txt new file mode 100644 index 000000000..c2b675c34 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/explain.txt @@ -0,0 +1,198 @@ +== Physical Plan == +* HashAggregate (28) ++- Exchange (27) + +- * HashAggregate (26) + +- * Project (25) + +- * BroadcastHashJoin Inner BuildRight (24) + :- * Project (22) + : +- * BroadcastHashJoin Inner BuildRight (21) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.store (4) + : : +- BroadcastExchange (13) + : : +- * Filter (12) + : : +- * ColumnarToRow (11) + : : +- CometScan parquet spark_catalog.default.customer_demographics (10) + : +- BroadcastExchange (20) + : +- * Project (19) + : +- * Filter (18) + : +- * ColumnarToRow (17) + : +- CometScan parquet spark_catalog.default.customer_address (16) + +- ReusedExchange (23) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [7]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_addr_sk), Or(Or(And(GreaterThanOrEqual(ss_sales_price,100.00),LessThanOrEqual(ss_sales_price,150.00)),And(GreaterThanOrEqual(ss_sales_price,50.00),LessThanOrEqual(ss_sales_price,100.00))),And(GreaterThanOrEqual(ss_sales_price,150.00),LessThanOrEqual(ss_sales_price,200.00))), Or(Or(And(GreaterThanOrEqual(ss_net_profit,0.00),LessThanOrEqual(ss_net_profit,2000.00)),And(GreaterThanOrEqual(ss_net_profit,150.00),LessThanOrEqual(ss_net_profit,3000.00))),And(GreaterThanOrEqual(ss_net_profit,50.00),LessThanOrEqual(ss_net_profit,25000.00)))] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [7]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] + +(3) Filter [codegen id : 5] +Input [7]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Condition : ((((isnotnull(ss_store_sk#3) AND isnotnull(ss_cdemo_sk#1)) AND isnotnull(ss_addr_sk#2)) AND ((((ss_sales_price#5 >= 100.00) AND (ss_sales_price#5 <= 150.00)) OR ((ss_sales_price#5 >= 50.00) AND (ss_sales_price#5 <= 100.00))) OR ((ss_sales_price#5 >= 150.00) AND (ss_sales_price#5 <= 200.00)))) AND ((((ss_net_profit#6 >= 0.00) AND (ss_net_profit#6 <= 2000.00)) OR ((ss_net_profit#6 >= 150.00) AND (ss_net_profit#6 <= 3000.00))) OR ((ss_net_profit#6 >= 50.00) AND (ss_net_profit#6 <= 25000.00)))) + +(4) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [1]: [s_store_sk#9] + +(6) Filter [codegen id : 1] +Input [1]: [s_store_sk#9] +Condition : isnotnull(s_store_sk#9) + +(7) BroadcastExchange +Input [1]: [s_store_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#9] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [6]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Input [8]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, s_store_sk#9] + +(10) Scan parquet spark_catalog.default.customer_demographics +Output [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,4 yr Degree )),And(EqualTo(cd_marital_status,D),EqualTo(cd_education_status,2 yr Degree ))),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College )))] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] + +(12) Filter [codegen id : 2] +Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] +Condition : (isnotnull(cd_demo_sk#10) AND ((((cd_marital_status#11 = M) AND (cd_education_status#12 = 4 yr Degree )) OR ((cd_marital_status#11 = D) AND (cd_education_status#12 = 2 yr Degree ))) OR ((cd_marital_status#11 = S) AND (cd_education_status#12 = College )))) + +(13) BroadcastExchange +Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_cdemo_sk#1] +Right keys [1]: [cd_demo_sk#10] +Join type: Inner +Join condition: ((((((cd_marital_status#11 = M) AND (cd_education_status#12 = 4 yr Degree )) AND (ss_sales_price#5 >= 100.00)) AND (ss_sales_price#5 <= 150.00)) OR ((((cd_marital_status#11 = D) AND (cd_education_status#12 = 2 yr Degree )) AND (ss_sales_price#5 >= 50.00)) AND (ss_sales_price#5 <= 100.00))) OR ((((cd_marital_status#11 = S) AND (cd_education_status#12 = College )) AND (ss_sales_price#5 >= 150.00)) AND (ss_sales_price#5 <= 200.00))) + +(15) Project [codegen id : 5] +Output [4]: [ss_addr_sk#2, ss_quantity#4, ss_net_profit#6, ss_sold_date_sk#7] +Input [9]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] + +(16) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [CO,OH,TX]),In(ca_state, [KY,MN,OR])),In(ca_state, [CA,MS,VA]))] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 3] +Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] + +(18) Filter [codegen id : 3] +Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Condition : (((isnotnull(ca_country#15) AND (ca_country#15 = United States)) AND isnotnull(ca_address_sk#13)) AND ((ca_state#14 IN (CO,OH,TX) OR ca_state#14 IN (OR,MN,KY)) OR ca_state#14 IN (VA,CA,MS))) + +(19) Project [codegen id : 3] +Output [2]: [ca_address_sk#13, ca_state#14] +Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] + +(20) BroadcastExchange +Input [2]: [ca_address_sk#13, ca_state#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#2] +Right keys [1]: [ca_address_sk#13] +Join type: Inner +Join condition: ((((ca_state#14 IN (CO,OH,TX) AND (ss_net_profit#6 >= 0.00)) AND (ss_net_profit#6 <= 2000.00)) OR ((ca_state#14 IN (OR,MN,KY) AND (ss_net_profit#6 >= 150.00)) AND (ss_net_profit#6 <= 3000.00))) OR ((ca_state#14 IN (VA,CA,MS) AND (ss_net_profit#6 >= 50.00)) AND (ss_net_profit#6 <= 25000.00))) + +(22) Project [codegen id : 5] +Output [2]: [ss_quantity#4, ss_sold_date_sk#7] +Input [6]: [ss_addr_sk#2, ss_quantity#4, ss_net_profit#6, ss_sold_date_sk#7, ca_address_sk#13, ca_state#14] + +(23) ReusedExchange [Reuses operator id: 33] +Output [1]: [d_date_sk#16] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [1]: [ss_quantity#4] +Input [3]: [ss_quantity#4, ss_sold_date_sk#7, d_date_sk#16] + +(26) HashAggregate [codegen id : 5] +Input [1]: [ss_quantity#4] +Keys: [] +Functions [1]: [partial_sum(ss_quantity#4)] +Aggregate Attributes [1]: [sum#17] +Results [1]: [sum#18] + +(27) Exchange +Input [1]: [sum#18] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 6] +Input [1]: [sum#18] +Keys: [] +Functions [1]: [sum(ss_quantity#4)] +Aggregate Attributes [1]: [sum(ss_quantity#4)#19] +Results [1]: [sum(ss_quantity#4)#19 AS sum(ss_quantity)#20] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (33) ++- * Project (32) + +- * Filter (31) + +- * ColumnarToRow (30) + +- CometScan parquet spark_catalog.default.date_dim (29) + + +(29) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#16, d_year#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#16, d_year#21] + +(31) Filter [codegen id : 1] +Input [2]: [d_date_sk#16, d_year#21] +Condition : ((isnotnull(d_year#21) AND (d_year#21 = 2001)) AND isnotnull(d_date_sk#16)) + +(32) Project [codegen id : 1] +Output [1]: [d_date_sk#16] +Input [2]: [d_date_sk#16, d_year#21] + +(33) BroadcastExchange +Input [1]: [d_date_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/simplified.txt new file mode 100644 index 000000000..5cc7040fb --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/simplified.txt @@ -0,0 +1,50 @@ +WholeStageCodegen (6) + HashAggregate [sum] [sum(ss_quantity),sum(ss_quantity),sum] + InputAdapter + Exchange #1 + WholeStageCodegen (5) + HashAggregate [ss_quantity] [sum,sum] + Project [ss_quantity] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_sold_date_sk] + BroadcastHashJoin [ss_addr_sk,ca_address_sk,ca_state,ss_net_profit] + Project [ss_addr_sk,ss_quantity,ss_net_profit,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk,cd_marital_status,cd_education_status,ss_sales_price] + Project [ss_cdemo_sk,ss_addr_sk,ss_quantity,ss_sales_price,ss_net_profit,ss_sold_date_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Filter [ss_store_sk,ss_cdemo_sk,ss_addr_sk,ss_sales_price,ss_net_profit] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_cdemo_sk,ss_addr_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [cd_demo_sk,cd_marital_status,cd_education_status] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Project [ca_address_sk,ca_state] + Filter [ca_country,ca_address_sk,ca_state] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/explain.txt new file mode 100644 index 000000000..1ad84da7d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/explain.txt @@ -0,0 +1,471 @@ +== Physical Plan == +TakeOrderedAndProject (77) ++- * HashAggregate (76) + +- Exchange (75) + +- * HashAggregate (74) + +- Union (73) + :- * Project (24) + : +- * Filter (23) + : +- Window (22) + : +- * Sort (21) + : +- Window (20) + : +- * Sort (19) + : +- Exchange (18) + : +- * HashAggregate (17) + : +- Exchange (16) + : +- * HashAggregate (15) + : +- * Project (14) + : +- * BroadcastHashJoin Inner BuildRight (13) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildLeft (10) + : : :- BroadcastExchange (5) + : : : +- * Project (4) + : : : +- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : +- * Project (9) + : : +- * Filter (8) + : : +- * ColumnarToRow (7) + : : +- CometScan parquet spark_catalog.default.web_returns (6) + : +- ReusedExchange (12) + :- * Project (48) + : +- * Filter (47) + : +- Window (46) + : +- * Sort (45) + : +- Window (44) + : +- * Sort (43) + : +- Exchange (42) + : +- * HashAggregate (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * Project (35) + : : +- * BroadcastHashJoin Inner BuildLeft (34) + : : :- BroadcastExchange (29) + : : : +- * Project (28) + : : : +- * Filter (27) + : : : +- * ColumnarToRow (26) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (25) + : : +- * Project (33) + : : +- * Filter (32) + : : +- * ColumnarToRow (31) + : : +- CometScan parquet spark_catalog.default.catalog_returns (30) + : +- ReusedExchange (36) + +- * Project (72) + +- * Filter (71) + +- Window (70) + +- * Sort (69) + +- Window (68) + +- * Sort (67) + +- Exchange (66) + +- * HashAggregate (65) + +- Exchange (64) + +- * HashAggregate (63) + +- * Project (62) + +- * BroadcastHashJoin Inner BuildRight (61) + :- * Project (59) + : +- * BroadcastHashJoin Inner BuildLeft (58) + : :- BroadcastExchange (53) + : : +- * Project (52) + : : +- * Filter (51) + : : +- * ColumnarToRow (50) + : : +- CometScan parquet spark_catalog.default.store_sales (49) + : +- * Project (57) + : +- * Filter (56) + : +- * ColumnarToRow (55) + : +- CometScan parquet spark_catalog.default.store_returns (54) + +- ReusedExchange (60) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#6), dynamicpruningexpression(ws_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ws_net_profit), IsNotNull(ws_net_paid), IsNotNull(ws_quantity), GreaterThan(ws_net_profit,1.00), GreaterThan(ws_net_paid,0.00), GreaterThan(ws_quantity,0), IsNotNull(ws_order_number), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] + +(3) Filter [codegen id : 1] +Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Condition : (((((((isnotnull(ws_net_profit#5) AND isnotnull(ws_net_paid#4)) AND isnotnull(ws_quantity#3)) AND (ws_net_profit#5 > 1.00)) AND (ws_net_paid#4 > 0.00)) AND (ws_quantity#3 > 0)) AND isnotnull(ws_order_number#2)) AND isnotnull(ws_item_sk#1)) + +(4) Project [codegen id : 1] +Output [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] + +(5) BroadcastExchange +Input [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=1] + +(6) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_return_amt), GreaterThan(wr_return_amt,10000.00), IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(7) ColumnarToRow +Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] + +(8) Filter +Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Condition : (((isnotnull(wr_return_amt#11) AND (wr_return_amt#11 > 10000.00)) AND isnotnull(wr_order_number#9)) AND isnotnull(wr_item_sk#8)) + +(9) Project +Output [4]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] + +(10) BroadcastHashJoin [codegen id : 3] +Left keys [2]: [ws_order_number#2, ws_item_sk#1] +Right keys [2]: [wr_order_number#9, wr_item_sk#8] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 3] +Output [6]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] +Input [9]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] + +(12) ReusedExchange [Reuses operator id: 82] +Output [1]: [d_date_sk#13] + +(13) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#6] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 3] +Output [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] +Input [7]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11, d_date_sk#13] + +(15) HashAggregate [codegen id : 3] +Input [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] +Keys [1]: [ws_item_sk#1] +Functions [4]: [partial_sum(coalesce(wr_return_quantity#10, 0)), partial_sum(coalesce(ws_quantity#3, 0)), partial_sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#14, sum#15, sum#16, isEmpty#17, sum#18, isEmpty#19] +Results [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] + +(16) Exchange +Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(17) HashAggregate [codegen id : 4] +Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Keys [1]: [ws_item_sk#1] +Functions [4]: [sum(coalesce(wr_return_quantity#10, 0)), sum(coalesce(ws_quantity#3, 0)), sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(wr_return_quantity#10, 0))#26, sum(coalesce(ws_quantity#3, 0))#27, sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28, sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29] +Results [3]: [ws_item_sk#1 AS item#30, (cast(sum(coalesce(wr_return_quantity#10, 0))#26 as decimal(15,4)) / cast(sum(coalesce(ws_quantity#3, 0))#27 as decimal(15,4))) AS return_ratio#31, (cast(sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28 as decimal(15,4)) / cast(sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29 as decimal(15,4))) AS currency_ratio#32] + +(18) Exchange +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=3] + +(19) Sort [codegen id : 5] +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: [return_ratio#31 ASC NULLS FIRST], false, 0 + +(20) Window +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: [rank(return_ratio#31) windowspecdefinition(return_ratio#31 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#33], [return_ratio#31 ASC NULLS FIRST] + +(21) Sort [codegen id : 6] +Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] +Arguments: [currency_ratio#32 ASC NULLS FIRST], false, 0 + +(22) Window +Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] +Arguments: [rank(currency_ratio#32) windowspecdefinition(currency_ratio#32 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#34], [currency_ratio#32 ASC NULLS FIRST] + +(23) Filter [codegen id : 7] +Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] +Condition : ((return_rank#33 <= 10) OR (currency_rank#34 <= 10)) + +(24) Project [codegen id : 7] +Output [5]: [web AS channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] + +(25) Scan parquet spark_catalog.default.catalog_sales +Output [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#41), dynamicpruningexpression(cs_sold_date_sk#41 IN dynamicpruning#42)] +PushedFilters: [IsNotNull(cs_net_profit), IsNotNull(cs_net_paid), IsNotNull(cs_quantity), GreaterThan(cs_net_profit,1.00), GreaterThan(cs_net_paid,0.00), GreaterThan(cs_quantity,0), IsNotNull(cs_order_number), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 8] +Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] + +(27) Filter [codegen id : 8] +Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Condition : (((((((isnotnull(cs_net_profit#40) AND isnotnull(cs_net_paid#39)) AND isnotnull(cs_quantity#38)) AND (cs_net_profit#40 > 1.00)) AND (cs_net_paid#39 > 0.00)) AND (cs_quantity#38 > 0)) AND isnotnull(cs_order_number#37)) AND isnotnull(cs_item_sk#36)) + +(28) Project [codegen id : 8] +Output [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] + +(29) BroadcastExchange +Input [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=4] + +(30) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_return_amount), GreaterThan(cr_return_amount,10000.00), IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(31) ColumnarToRow +Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] + +(32) Filter +Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Condition : (((isnotnull(cr_return_amount#46) AND (cr_return_amount#46 > 10000.00)) AND isnotnull(cr_order_number#44)) AND isnotnull(cr_item_sk#43)) + +(33) Project +Output [4]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [cs_order_number#37, cs_item_sk#36] +Right keys [2]: [cr_order_number#44, cr_item_sk#43] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [6]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] +Input [9]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] + +(36) ReusedExchange [Reuses operator id: 82] +Output [1]: [d_date_sk#48] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#41] +Right keys [1]: [d_date_sk#48] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] +Input [7]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46, d_date_sk#48] + +(39) HashAggregate [codegen id : 10] +Input [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] +Keys [1]: [cs_item_sk#36] +Functions [4]: [partial_sum(coalesce(cr_return_quantity#45, 0)), partial_sum(coalesce(cs_quantity#38, 0)), partial_sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#49, sum#50, sum#51, isEmpty#52, sum#53, isEmpty#54] +Results [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] + +(40) Exchange +Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] +Arguments: hashpartitioning(cs_item_sk#36, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(41) HashAggregate [codegen id : 11] +Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] +Keys [1]: [cs_item_sk#36] +Functions [4]: [sum(coalesce(cr_return_quantity#45, 0)), sum(coalesce(cs_quantity#38, 0)), sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(cr_return_quantity#45, 0))#61, sum(coalesce(cs_quantity#38, 0))#62, sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63, sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64] +Results [3]: [cs_item_sk#36 AS item#65, (cast(sum(coalesce(cr_return_quantity#45, 0))#61 as decimal(15,4)) / cast(sum(coalesce(cs_quantity#38, 0))#62 as decimal(15,4))) AS return_ratio#66, (cast(sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63 as decimal(15,4)) / cast(sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64 as decimal(15,4))) AS currency_ratio#67] + +(42) Exchange +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] + +(43) Sort [codegen id : 12] +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: [return_ratio#66 ASC NULLS FIRST], false, 0 + +(44) Window +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: [rank(return_ratio#66) windowspecdefinition(return_ratio#66 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#68], [return_ratio#66 ASC NULLS FIRST] + +(45) Sort [codegen id : 13] +Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] +Arguments: [currency_ratio#67 ASC NULLS FIRST], false, 0 + +(46) Window +Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] +Arguments: [rank(currency_ratio#67) windowspecdefinition(currency_ratio#67 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#69], [currency_ratio#67 ASC NULLS FIRST] + +(47) Filter [codegen id : 14] +Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] +Condition : ((return_rank#68 <= 10) OR (currency_rank#69 <= 10)) + +(48) Project [codegen id : 14] +Output [5]: [catalog AS channel#70, item#65, return_ratio#66, return_rank#68, currency_rank#69] +Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] + +(49) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#76), dynamicpruningexpression(ss_sold_date_sk#76 IN dynamicpruning#77)] +PushedFilters: [IsNotNull(ss_net_profit), IsNotNull(ss_net_paid), IsNotNull(ss_quantity), GreaterThan(ss_net_profit,1.00), GreaterThan(ss_net_paid,0.00), GreaterThan(ss_quantity,0), IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(50) ColumnarToRow [codegen id : 15] +Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] + +(51) Filter [codegen id : 15] +Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Condition : (((((((isnotnull(ss_net_profit#75) AND isnotnull(ss_net_paid#74)) AND isnotnull(ss_quantity#73)) AND (ss_net_profit#75 > 1.00)) AND (ss_net_paid#74 > 0.00)) AND (ss_quantity#73 > 0)) AND isnotnull(ss_ticket_number#72)) AND isnotnull(ss_item_sk#71)) + +(52) Project [codegen id : 15] +Output [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] + +(53) BroadcastExchange +Input [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=7] + +(54) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_return_amt), GreaterThan(sr_return_amt,10000.00), IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(55) ColumnarToRow +Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] + +(56) Filter +Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Condition : (((isnotnull(sr_return_amt#81) AND (sr_return_amt#81 > 10000.00)) AND isnotnull(sr_ticket_number#79)) AND isnotnull(sr_item_sk#78)) + +(57) Project +Output [4]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] + +(58) BroadcastHashJoin [codegen id : 17] +Left keys [2]: [ss_ticket_number#72, ss_item_sk#71] +Right keys [2]: [sr_ticket_number#79, sr_item_sk#78] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 17] +Output [6]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] +Input [9]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] + +(60) ReusedExchange [Reuses operator id: 82] +Output [1]: [d_date_sk#83] + +(61) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ss_sold_date_sk#76] +Right keys [1]: [d_date_sk#83] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 17] +Output [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] +Input [7]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81, d_date_sk#83] + +(63) HashAggregate [codegen id : 17] +Input [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] +Keys [1]: [ss_item_sk#71] +Functions [4]: [partial_sum(coalesce(sr_return_quantity#80, 0)), partial_sum(coalesce(ss_quantity#73, 0)), partial_sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#84, sum#85, sum#86, isEmpty#87, sum#88, isEmpty#89] +Results [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] + +(64) Exchange +Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] +Arguments: hashpartitioning(ss_item_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(65) HashAggregate [codegen id : 18] +Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] +Keys [1]: [ss_item_sk#71] +Functions [4]: [sum(coalesce(sr_return_quantity#80, 0)), sum(coalesce(ss_quantity#73, 0)), sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(sr_return_quantity#80, 0))#96, sum(coalesce(ss_quantity#73, 0))#97, sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98, sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99] +Results [3]: [ss_item_sk#71 AS item#100, (cast(sum(coalesce(sr_return_quantity#80, 0))#96 as decimal(15,4)) / cast(sum(coalesce(ss_quantity#73, 0))#97 as decimal(15,4))) AS return_ratio#101, (cast(sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98 as decimal(15,4)) / cast(sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99 as decimal(15,4))) AS currency_ratio#102] + +(66) Exchange +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=9] + +(67) Sort [codegen id : 19] +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: [return_ratio#101 ASC NULLS FIRST], false, 0 + +(68) Window +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: [rank(return_ratio#101) windowspecdefinition(return_ratio#101 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#103], [return_ratio#101 ASC NULLS FIRST] + +(69) Sort [codegen id : 20] +Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] +Arguments: [currency_ratio#102 ASC NULLS FIRST], false, 0 + +(70) Window +Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] +Arguments: [rank(currency_ratio#102) windowspecdefinition(currency_ratio#102 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#104], [currency_ratio#102 ASC NULLS FIRST] + +(71) Filter [codegen id : 21] +Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] +Condition : ((return_rank#103 <= 10) OR (currency_rank#104 <= 10)) + +(72) Project [codegen id : 21] +Output [5]: [store AS channel#105, item#100, return_ratio#101, return_rank#103, currency_rank#104] +Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] + +(73) Union + +(74) HashAggregate [codegen id : 22] +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +(75) Exchange +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Arguments: hashpartitioning(channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(76) HashAggregate [codegen id : 23] +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +(77) TakeOrderedAndProject +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Arguments: 100, [channel#35 ASC NULLS FIRST, return_rank#33 ASC NULLS FIRST, currency_rank#34 ASC NULLS FIRST], [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (82) ++- * Project (81) + +- * Filter (80) + +- * ColumnarToRow (79) + +- CometScan parquet spark_catalog.default.date_dim (78) + + +(78) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#13, d_year#106, d_moy#107] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,12), IsNotNull(d_date_sk)] +ReadSchema: struct + +(79) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#13, d_year#106, d_moy#107] + +(80) Filter [codegen id : 1] +Input [3]: [d_date_sk#13, d_year#106, d_moy#107] +Condition : ((((isnotnull(d_year#106) AND isnotnull(d_moy#107)) AND (d_year#106 = 2001)) AND (d_moy#107 = 12)) AND isnotnull(d_date_sk#13)) + +(81) Project [codegen id : 1] +Output [1]: [d_date_sk#13] +Input [3]: [d_date_sk#13, d_year#106, d_moy#107] + +(82) BroadcastExchange +Input [1]: [d_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +Subquery:2 Hosting operator id = 25 Hosting Expression = cs_sold_date_sk#41 IN dynamicpruning#7 + +Subquery:3 Hosting operator id = 49 Hosting Expression = ss_sold_date_sk#76 IN dynamicpruning#7 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/simplified.txt new file mode 100644 index 000000000..b707750da --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/simplified.txt @@ -0,0 +1,133 @@ +TakeOrderedAndProject [channel,return_rank,currency_rank,item,return_ratio] + WholeStageCodegen (23) + HashAggregate [channel,item,return_ratio,return_rank,currency_rank] + InputAdapter + Exchange [channel,item,return_ratio,return_rank,currency_rank] #1 + WholeStageCodegen (22) + HashAggregate [channel,item,return_ratio,return_rank,currency_rank] + InputAdapter + Union + WholeStageCodegen (7) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (6) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (5) + Sort [return_ratio] + InputAdapter + Exchange #2 + WholeStageCodegen (4) + HashAggregate [ws_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(wr_return_quantity, 0)),sum(coalesce(ws_quantity, 0)),sum(coalesce(cast(wr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ws_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [ws_item_sk] #3 + WholeStageCodegen (3) + HashAggregate [ws_item_sk,wr_return_quantity,ws_quantity,wr_return_amt,ws_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [ws_item_sk,ws_quantity,ws_net_paid,wr_return_quantity,wr_return_amt] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_quantity,ws_net_paid,ws_sold_date_sk,wr_return_quantity,wr_return_amt] + BroadcastHashJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Project [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_sold_date_sk] + Filter [ws_net_profit,ws_net_paid,ws_quantity,ws_order_number,ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_net_profit,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + Project [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + Filter [wr_return_amt,wr_order_number,wr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + WholeStageCodegen (14) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (13) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (12) + Sort [return_ratio] + InputAdapter + Exchange #6 + WholeStageCodegen (11) + HashAggregate [cs_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(cr_return_quantity, 0)),sum(coalesce(cs_quantity, 0)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum(coalesce(cast(cs_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [cs_item_sk] #7 + WholeStageCodegen (10) + HashAggregate [cs_item_sk,cr_return_quantity,cs_quantity,cr_return_amount,cs_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [cs_item_sk,cs_quantity,cs_net_paid,cr_return_quantity,cr_return_amount] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_net_paid,cs_sold_date_sk,cr_return_quantity,cr_return_amount] + BroadcastHashJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (8) + Project [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_sold_date_sk] + Filter [cs_net_profit,cs_net_paid,cs_quantity,cs_order_number,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + Project [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + Filter [cr_return_amount,cr_order_number,cr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + WholeStageCodegen (21) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (20) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (19) + Sort [return_ratio] + InputAdapter + Exchange #9 + WholeStageCodegen (18) + HashAggregate [ss_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(sr_return_quantity, 0)),sum(coalesce(ss_quantity, 0)),sum(coalesce(cast(sr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ss_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [ss_item_sk] #10 + WholeStageCodegen (17) + HashAggregate [ss_item_sk,sr_return_quantity,ss_quantity,sr_return_amt,ss_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [ss_item_sk,ss_quantity,ss_net_paid,sr_return_quantity,sr_return_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_quantity,ss_net_paid,ss_sold_date_sk,sr_return_quantity,sr_return_amt] + BroadcastHashJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_sold_date_sk] + Filter [ss_net_profit,ss_net_paid,ss_quantity,ss_ticket_number,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_net_profit,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + Project [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + Filter [sr_return_amt,sr_ticket_number,sr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/explain.txt new file mode 100644 index 000000000..b62cad834 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/explain.txt @@ -0,0 +1,468 @@ +== Physical Plan == +TakeOrderedAndProject (74) ++- * HashAggregate (73) + +- Exchange (72) + +- * HashAggregate (71) + +- * Expand (70) + +- Union (69) + :- * HashAggregate (21) + : +- Exchange (20) + : +- * HashAggregate (19) + : +- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- Union (9) + : : : :- * Project (4) + : : : : +- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- * Project (8) + : : : +- * Filter (7) + : : : +- * ColumnarToRow (6) + : : : +- CometScan parquet spark_catalog.default.store_returns (5) + : : +- ReusedExchange (10) + : +- BroadcastExchange (16) + : +- * Filter (15) + : +- * ColumnarToRow (14) + : +- CometScan parquet spark_catalog.default.store (13) + :- * HashAggregate (42) + : +- Exchange (41) + : +- * HashAggregate (40) + : +- * Project (39) + : +- * BroadcastHashJoin Inner BuildRight (38) + : :- * Project (33) + : : +- * BroadcastHashJoin Inner BuildRight (32) + : : :- Union (30) + : : : :- * Project (25) + : : : : +- * Filter (24) + : : : : +- * ColumnarToRow (23) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (22) + : : : +- * Project (29) + : : : +- * Filter (28) + : : : +- * ColumnarToRow (27) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (26) + : : +- ReusedExchange (31) + : +- BroadcastExchange (37) + : +- * Filter (36) + : +- * ColumnarToRow (35) + : +- CometScan parquet spark_catalog.default.catalog_page (34) + +- * HashAggregate (68) + +- Exchange (67) + +- * HashAggregate (66) + +- * Project (65) + +- * BroadcastHashJoin Inner BuildRight (64) + :- * Project (59) + : +- * BroadcastHashJoin Inner BuildRight (58) + : :- Union (56) + : : :- * Project (46) + : : : +- * Filter (45) + : : : +- * ColumnarToRow (44) + : : : +- CometScan parquet spark_catalog.default.web_sales (43) + : : +- * Project (55) + : : +- * BroadcastHashJoin Inner BuildLeft (54) + : : :- BroadcastExchange (49) + : : : +- * ColumnarToRow (48) + : : : +- CometScan parquet spark_catalog.default.web_returns (47) + : : +- * Project (53) + : : +- * Filter (52) + : : +- * ColumnarToRow (51) + : : +- CometScan parquet spark_catalog.default.web_sales (50) + : +- ReusedExchange (57) + +- BroadcastExchange (63) + +- * Filter (62) + +- * ColumnarToRow (61) + +- CometScan parquet spark_catalog.default.web_site (60) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 1] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_store_sk#1) + +(4) Project [codegen id : 1] +Output [6]: [ss_store_sk#1 AS store_sk#6, ss_sold_date_sk#4 AS date_sk#7, ss_ext_sales_price#2 AS sales_price#8, ss_net_profit#3 AS profit#9, 0.00 AS return_amt#10, 0.00 AS net_loss#11] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] + +(5) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#15), dynamicpruningexpression(sr_returned_date_sk#15 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(sr_store_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 2] +Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] + +(7) Filter [codegen id : 2] +Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Condition : isnotnull(sr_store_sk#12) + +(8) Project [codegen id : 2] +Output [6]: [sr_store_sk#12 AS store_sk#16, sr_returned_date_sk#15 AS date_sk#17, 0.00 AS sales_price#18, 0.00 AS profit#19, sr_return_amt#13 AS return_amt#20, sr_net_loss#14 AS net_loss#21] +Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] + +(9) Union + +(10) ReusedExchange [Reuses operator id: 79] +Output [1]: [d_date_sk#22] + +(11) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [date_sk#7] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 5] +Output [5]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11] +Input [7]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11, d_date_sk#22] + +(13) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#23, s_store_id#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 4] +Input [2]: [s_store_sk#23, s_store_id#24] + +(15) Filter [codegen id : 4] +Input [2]: [s_store_sk#23, s_store_id#24] +Condition : isnotnull(s_store_sk#23) + +(16) BroadcastExchange +Input [2]: [s_store_sk#23, s_store_id#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(17) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [store_sk#6] +Right keys [1]: [s_store_sk#23] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 5] +Output [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] +Input [7]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_sk#23, s_store_id#24] + +(19) HashAggregate [codegen id : 5] +Input [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] +Keys [1]: [s_store_id#24] +Functions [4]: [partial_sum(UnscaledValue(sales_price#8)), partial_sum(UnscaledValue(return_amt#10)), partial_sum(UnscaledValue(profit#9)), partial_sum(UnscaledValue(net_loss#11))] +Aggregate Attributes [4]: [sum#25, sum#26, sum#27, sum#28] +Results [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] + +(20) Exchange +Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] +Arguments: hashpartitioning(s_store_id#24, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(21) HashAggregate [codegen id : 6] +Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] +Keys [1]: [s_store_id#24] +Functions [4]: [sum(UnscaledValue(sales_price#8)), sum(UnscaledValue(return_amt#10)), sum(UnscaledValue(profit#9)), sum(UnscaledValue(net_loss#11))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#8))#33, sum(UnscaledValue(return_amt#10))#34, sum(UnscaledValue(profit#9))#35, sum(UnscaledValue(net_loss#11))#36] +Results [5]: [MakeDecimal(sum(UnscaledValue(sales_price#8))#33,17,2) AS sales#37, MakeDecimal(sum(UnscaledValue(return_amt#10))#34,17,2) AS returns#38, (MakeDecimal(sum(UnscaledValue(profit#9))#35,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#11))#36,17,2)) AS profit#39, store channel AS channel#40, concat(store, s_store_id#24) AS id#41] + +(22) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_sold_date_sk#45 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cs_catalog_page_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 7] +Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] + +(24) Filter [codegen id : 7] +Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Condition : isnotnull(cs_catalog_page_sk#42) + +(25) Project [codegen id : 7] +Output [6]: [cs_catalog_page_sk#42 AS page_sk#47, cs_sold_date_sk#45 AS date_sk#48, cs_ext_sales_price#43 AS sales_price#49, cs_net_profit#44 AS profit#50, 0.00 AS return_amt#51, 0.00 AS net_loss#52] +Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] + +(26) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#56), dynamicpruningexpression(cr_returned_date_sk#56 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cr_catalog_page_sk)] +ReadSchema: struct + +(27) ColumnarToRow [codegen id : 8] +Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] + +(28) Filter [codegen id : 8] +Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Condition : isnotnull(cr_catalog_page_sk#53) + +(29) Project [codegen id : 8] +Output [6]: [cr_catalog_page_sk#53 AS page_sk#57, cr_returned_date_sk#56 AS date_sk#58, 0.00 AS sales_price#59, 0.00 AS profit#60, cr_return_amount#54 AS return_amt#61, cr_net_loss#55 AS net_loss#62] +Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] + +(30) Union + +(31) ReusedExchange [Reuses operator id: 79] +Output [1]: [d_date_sk#63] + +(32) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [date_sk#48] +Right keys [1]: [d_date_sk#63] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 11] +Output [5]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52] +Input [7]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52, d_date_sk#63] + +(34) Scan parquet spark_catalog.default.catalog_page +Output [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_page] +PushedFilters: [IsNotNull(cp_catalog_page_sk)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 10] +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] + +(36) Filter [codegen id : 10] +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Condition : isnotnull(cp_catalog_page_sk#64) + +(37) BroadcastExchange +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(38) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [page_sk#47] +Right keys [1]: [cp_catalog_page_sk#64] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 11] +Output [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] +Input [7]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_sk#64, cp_catalog_page_id#65] + +(40) HashAggregate [codegen id : 11] +Input [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] +Keys [1]: [cp_catalog_page_id#65] +Functions [4]: [partial_sum(UnscaledValue(sales_price#49)), partial_sum(UnscaledValue(return_amt#51)), partial_sum(UnscaledValue(profit#50)), partial_sum(UnscaledValue(net_loss#52))] +Aggregate Attributes [4]: [sum#66, sum#67, sum#68, sum#69] +Results [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] + +(41) Exchange +Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] +Arguments: hashpartitioning(cp_catalog_page_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(42) HashAggregate [codegen id : 12] +Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] +Keys [1]: [cp_catalog_page_id#65] +Functions [4]: [sum(UnscaledValue(sales_price#49)), sum(UnscaledValue(return_amt#51)), sum(UnscaledValue(profit#50)), sum(UnscaledValue(net_loss#52))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#49))#74, sum(UnscaledValue(return_amt#51))#75, sum(UnscaledValue(profit#50))#76, sum(UnscaledValue(net_loss#52))#77] +Results [5]: [MakeDecimal(sum(UnscaledValue(sales_price#49))#74,17,2) AS sales#78, MakeDecimal(sum(UnscaledValue(return_amt#51))#75,17,2) AS returns#79, (MakeDecimal(sum(UnscaledValue(profit#50))#76,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#52))#77,17,2)) AS profit#80, catalog channel AS channel#81, concat(catalog_page, cp_catalog_page_id#65) AS id#82] + +(43) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#86), dynamicpruningexpression(ws_sold_date_sk#86 IN dynamicpruning#87)] +PushedFilters: [IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(44) ColumnarToRow [codegen id : 13] +Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] + +(45) Filter [codegen id : 13] +Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Condition : isnotnull(ws_web_site_sk#83) + +(46) Project [codegen id : 13] +Output [6]: [ws_web_site_sk#83 AS wsr_web_site_sk#88, ws_sold_date_sk#86 AS date_sk#89, ws_ext_sales_price#84 AS sales_price#90, ws_net_profit#85 AS profit#91, 0.00 AS return_amt#92, 0.00 AS net_loss#93] +Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] + +(47) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#98), dynamicpruningexpression(wr_returned_date_sk#98 IN dynamicpruning#87)] +ReadSchema: struct + +(48) ColumnarToRow [codegen id : 14] +Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] + +(49) BroadcastExchange +Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, true] as bigint), 32) | (cast(input[1, int, true] as bigint) & 4294967295))),false), [plan_id=5] + +(50) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(51) ColumnarToRow +Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] + +(52) Filter +Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Condition : ((isnotnull(ws_item_sk#99) AND isnotnull(ws_order_number#101)) AND isnotnull(ws_web_site_sk#100)) + +(53) Project +Output [3]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] + +(54) BroadcastHashJoin [codegen id : 15] +Left keys [2]: [wr_item_sk#94, wr_order_number#95] +Right keys [2]: [ws_item_sk#99, ws_order_number#101] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 15] +Output [6]: [ws_web_site_sk#100 AS wsr_web_site_sk#103, wr_returned_date_sk#98 AS date_sk#104, 0.00 AS sales_price#105, 0.00 AS profit#106, wr_return_amt#96 AS return_amt#107, wr_net_loss#97 AS net_loss#108] +Input [8]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98, ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] + +(56) Union + +(57) ReusedExchange [Reuses operator id: 79] +Output [1]: [d_date_sk#109] + +(58) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [date_sk#89] +Right keys [1]: [d_date_sk#109] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 18] +Output [5]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93] +Input [7]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93, d_date_sk#109] + +(60) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#110, web_site_id#111] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_site_sk)] +ReadSchema: struct + +(61) ColumnarToRow [codegen id : 17] +Input [2]: [web_site_sk#110, web_site_id#111] + +(62) Filter [codegen id : 17] +Input [2]: [web_site_sk#110, web_site_id#111] +Condition : isnotnull(web_site_sk#110) + +(63) BroadcastExchange +Input [2]: [web_site_sk#110, web_site_id#111] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(64) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [wsr_web_site_sk#88] +Right keys [1]: [web_site_sk#110] +Join type: Inner +Join condition: None + +(65) Project [codegen id : 18] +Output [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] +Input [7]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_sk#110, web_site_id#111] + +(66) HashAggregate [codegen id : 18] +Input [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] +Keys [1]: [web_site_id#111] +Functions [4]: [partial_sum(UnscaledValue(sales_price#90)), partial_sum(UnscaledValue(return_amt#92)), partial_sum(UnscaledValue(profit#91)), partial_sum(UnscaledValue(net_loss#93))] +Aggregate Attributes [4]: [sum#112, sum#113, sum#114, sum#115] +Results [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] + +(67) Exchange +Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] +Arguments: hashpartitioning(web_site_id#111, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(68) HashAggregate [codegen id : 19] +Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] +Keys [1]: [web_site_id#111] +Functions [4]: [sum(UnscaledValue(sales_price#90)), sum(UnscaledValue(return_amt#92)), sum(UnscaledValue(profit#91)), sum(UnscaledValue(net_loss#93))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#90))#120, sum(UnscaledValue(return_amt#92))#121, sum(UnscaledValue(profit#91))#122, sum(UnscaledValue(net_loss#93))#123] +Results [5]: [MakeDecimal(sum(UnscaledValue(sales_price#90))#120,17,2) AS sales#124, MakeDecimal(sum(UnscaledValue(return_amt#92))#121,17,2) AS returns#125, (MakeDecimal(sum(UnscaledValue(profit#91))#122,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#93))#123,17,2)) AS profit#126, web channel AS channel#127, concat(web_site, web_site_id#111) AS id#128] + +(69) Union + +(70) Expand [codegen id : 20] +Input [5]: [sales#37, returns#38, profit#39, channel#40, id#41] +Arguments: [[sales#37, returns#38, profit#39, channel#40, id#41, 0], [sales#37, returns#38, profit#39, channel#40, null, 1], [sales#37, returns#38, profit#39, null, null, 3]], [sales#37, returns#38, profit#39, channel#129, id#130, spark_grouping_id#131] + +(71) HashAggregate [codegen id : 20] +Input [6]: [sales#37, returns#38, profit#39, channel#129, id#130, spark_grouping_id#131] +Keys [3]: [channel#129, id#130, spark_grouping_id#131] +Functions [3]: [partial_sum(sales#37), partial_sum(returns#38), partial_sum(profit#39)] +Aggregate Attributes [6]: [sum#132, isEmpty#133, sum#134, isEmpty#135, sum#136, isEmpty#137] +Results [9]: [channel#129, id#130, spark_grouping_id#131, sum#138, isEmpty#139, sum#140, isEmpty#141, sum#142, isEmpty#143] + +(72) Exchange +Input [9]: [channel#129, id#130, spark_grouping_id#131, sum#138, isEmpty#139, sum#140, isEmpty#141, sum#142, isEmpty#143] +Arguments: hashpartitioning(channel#129, id#130, spark_grouping_id#131, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(73) HashAggregate [codegen id : 21] +Input [9]: [channel#129, id#130, spark_grouping_id#131, sum#138, isEmpty#139, sum#140, isEmpty#141, sum#142, isEmpty#143] +Keys [3]: [channel#129, id#130, spark_grouping_id#131] +Functions [3]: [sum(sales#37), sum(returns#38), sum(profit#39)] +Aggregate Attributes [3]: [sum(sales#37)#144, sum(returns#38)#145, sum(profit#39)#146] +Results [5]: [channel#129, id#130, sum(sales#37)#144 AS sales#147, sum(returns#38)#145 AS returns#148, sum(profit#39)#146 AS profit#149] + +(74) TakeOrderedAndProject +Input [5]: [channel#129, id#130, sales#147, returns#148, profit#149] +Arguments: 100, [channel#129 ASC NULLS FIRST, id#130 ASC NULLS FIRST], [channel#129, id#130, sales#147, returns#148, profit#149] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (79) ++- * Project (78) + +- * Filter (77) + +- * ColumnarToRow (76) + +- CometScan parquet spark_catalog.default.date_dim (75) + + +(75) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#22, d_date#150] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-08-23), LessThanOrEqual(d_date,2000-09-06), IsNotNull(d_date_sk)] +ReadSchema: struct + +(76) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#22, d_date#150] + +(77) Filter [codegen id : 1] +Input [2]: [d_date_sk#22, d_date#150] +Condition : (((isnotnull(d_date#150) AND (d_date#150 >= 2000-08-23)) AND (d_date#150 <= 2000-09-06)) AND isnotnull(d_date_sk#22)) + +(78) Project [codegen id : 1] +Output [1]: [d_date_sk#22] +Input [2]: [d_date_sk#22, d_date#150] + +(79) BroadcastExchange +Input [1]: [d_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 5 Hosting Expression = sr_returned_date_sk#15 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 22 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#5 + +Subquery:4 Hosting operator id = 26 Hosting Expression = cr_returned_date_sk#56 IN dynamicpruning#5 + +Subquery:5 Hosting operator id = 43 Hosting Expression = ws_sold_date_sk#86 IN dynamicpruning#5 + +Subquery:6 Hosting operator id = 47 Hosting Expression = wr_returned_date_sk#98 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/simplified.txt new file mode 100644 index 000000000..cf9a7db64 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/simplified.txt @@ -0,0 +1,130 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (21) + HashAggregate [channel,id,spark_grouping_id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id,spark_grouping_id] #1 + WholeStageCodegen (20) + HashAggregate [channel,id,spark_grouping_id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Expand [sales,returns,profit,channel,id] + InputAdapter + Union + WholeStageCodegen (6) + HashAggregate [s_store_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),sales,returns,profit,channel,id,sum,sum,sum,sum] + InputAdapter + Exchange [s_store_id] #2 + WholeStageCodegen (5) + HashAggregate [s_store_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,s_store_id] + BroadcastHashJoin [store_sk,s_store_sk] + Project [store_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + InputAdapter + Union + WholeStageCodegen (1) + Project [ss_store_sk,ss_sold_date_sk,ss_ext_sales_price,ss_net_profit] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + WholeStageCodegen (2) + Project [sr_store_sk,sr_returned_date_sk,sr_return_amt,sr_net_loss] + Filter [sr_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + WholeStageCodegen (12) + HashAggregate [cp_catalog_page_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),sales,returns,profit,channel,id,sum,sum,sum,sum] + InputAdapter + Exchange [cp_catalog_page_id] #5 + WholeStageCodegen (11) + HashAggregate [cp_catalog_page_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,cp_catalog_page_id] + BroadcastHashJoin [page_sk,cp_catalog_page_sk] + Project [page_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + InputAdapter + Union + WholeStageCodegen (7) + Project [cs_catalog_page_sk,cs_sold_date_sk,cs_ext_sales_price,cs_net_profit] + Filter [cs_catalog_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + WholeStageCodegen (8) + Project [cr_catalog_page_sk,cr_returned_date_sk,cr_return_amount,cr_net_loss] + Filter [cr_catalog_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_catalog_page_sk,cr_return_amount,cr_net_loss,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (10) + Filter [cp_catalog_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] + WholeStageCodegen (19) + HashAggregate [web_site_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),sales,returns,profit,channel,id,sum,sum,sum,sum] + InputAdapter + Exchange [web_site_id] #7 + WholeStageCodegen (18) + HashAggregate [web_site_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,web_site_id] + BroadcastHashJoin [wsr_web_site_sk,web_site_sk] + Project [wsr_web_site_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + InputAdapter + Union + WholeStageCodegen (13) + Project [ws_web_site_sk,ws_sold_date_sk,ws_ext_sales_price,ws_net_profit] + Filter [ws_web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_web_site_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + WholeStageCodegen (15) + Project [ws_web_site_sk,wr_returned_date_sk,wr_return_amt,wr_net_loss] + BroadcastHashJoin [wr_item_sk,wr_order_number,ws_item_sk,ws_order_number] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (14) + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + Project [ws_item_sk,ws_web_site_sk,ws_order_number] + Filter [ws_item_sk,ws_order_number,ws_web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_order_number,ws_sold_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (17) + Filter [web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/explain.txt new file mode 100644 index 000000000..8422950c2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/explain.txt @@ -0,0 +1,199 @@ +== Physical Plan == +TakeOrderedAndProject (28) ++- * HashAggregate (27) + +- Exchange (26) + +- * HashAggregate (25) + +- * Project (24) + +- * BroadcastHashJoin Inner BuildRight (23) + :- * Project (21) + : +- * BroadcastHashJoin Inner BuildRight (20) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : +- BroadcastExchange (13) + : : +- * Filter (12) + : : +- * ColumnarToRow (11) + : : +- CometScan parquet spark_catalog.default.store (10) + : +- BroadcastExchange (19) + : +- * Filter (18) + : +- * ColumnarToRow (17) + : +- CometScan parquet spark_catalog.default.date_dim (16) + +- ReusedExchange (22) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5)] +PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] + +(3) Filter [codegen id : 5] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_store_sk#3)) + +(4) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#9), dynamicpruningexpression(sr_returned_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk), IsNotNull(sr_customer_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] + +(6) Filter [codegen id : 1] +Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Condition : ((isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#6)) AND isnotnull(sr_customer_sk#7)) + +(7) BroadcastExchange +Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(input[2, int, false], input[0, int, false], input[1, int, false]),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [3]: [ss_ticket_number#4, ss_item_sk#1, ss_customer_sk#2] +Right keys [3]: [sr_ticket_number#8, sr_item_sk#6, sr_customer_sk#7] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [3]: [ss_store_sk#3, ss_sold_date_sk#5, sr_returned_date_sk#9] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5, sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] + +(10) Scan parquet spark_catalog.default.store +Output [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] + +(12) Filter [codegen id : 2] +Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Condition : isnotnull(s_store_sk#11) + +(13) BroadcastExchange +Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 5] +Output [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Input [14]: [ss_store_sk#3, ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] + +(16) Scan parquet spark_catalog.default.date_dim +Output [1]: [d_date_sk#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [d_date_sk#22] + +(18) Filter [codegen id : 3] +Input [1]: [d_date_sk#22] +Condition : isnotnull(d_date_sk#22) + +(19) BroadcastExchange +Input [1]: [d_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 5] +Output [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Input [13]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, d_date_sk#22] + +(22) ReusedExchange [Reuses operator id: 33] +Output [1]: [d_date_sk#23] + +(23) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [sr_returned_date_sk#9] +Right keys [1]: [d_date_sk#23] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 5] +Output [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Input [13]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, d_date_sk#23] + +(25) HashAggregate [codegen id : 5] +Input [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Keys [10]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Functions [5]: [partial_sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum#24, sum#25, sum#26, sum#27, sum#28] +Results [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, sum#29, sum#30, sum#31, sum#32, sum#33] + +(26) Exchange +Input [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, sum#29, sum#30, sum#31, sum#32, sum#33] +Arguments: hashpartitioning(s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(27) HashAggregate [codegen id : 6] +Input [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, sum#29, sum#30, sum#31, sum#32, sum#33] +Keys [10]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Functions [5]: [sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#34, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#35, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#36, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#37, sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#38] +Results [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#34 AS 30 days #39, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#35 AS 31 - 60 days #40, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#36 AS 61 - 90 days #41, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#37 AS 91 - 120 days #42, sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#38 AS >120 days #43] + +(28) TakeOrderedAndProject +Input [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, 30 days #39, 31 - 60 days #40, 61 - 90 days #41, 91 - 120 days #42, >120 days #43] +Arguments: 100, [s_store_name#12 ASC NULLS FIRST, s_company_id#13 ASC NULLS FIRST, s_street_number#14 ASC NULLS FIRST, s_street_name#15 ASC NULLS FIRST, s_street_type#16 ASC NULLS FIRST, s_suite_number#17 ASC NULLS FIRST, s_city#18 ASC NULLS FIRST, s_county#19 ASC NULLS FIRST, s_state#20 ASC NULLS FIRST, s_zip#21 ASC NULLS FIRST], [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21, 30 days #39, 31 - 60 days #40, 61 - 90 days #41, 91 - 120 days #42, >120 days #43] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#9 IN dynamicpruning#10 +BroadcastExchange (33) ++- * Project (32) + +- * Filter (31) + +- * ColumnarToRow (30) + +- CometScan parquet spark_catalog.default.date_dim (29) + + +(29) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#23, d_year#44, d_moy#45] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,8), IsNotNull(d_date_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#23, d_year#44, d_moy#45] + +(31) Filter [codegen id : 1] +Input [3]: [d_date_sk#23, d_year#44, d_moy#45] +Condition : ((((isnotnull(d_year#44) AND isnotnull(d_moy#45)) AND (d_year#44 = 2001)) AND (d_moy#45 = 8)) AND isnotnull(d_date_sk#23)) + +(32) Project [codegen id : 1] +Output [1]: [d_date_sk#23] +Input [3]: [d_date_sk#23, d_year#44, d_moy#45] + +(33) BroadcastExchange +Input [1]: [d_date_sk#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/simplified.txt new file mode 100644 index 000000000..67c991f71 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/simplified.txt @@ -0,0 +1,50 @@ +TakeOrderedAndProject [s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip,30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ] + WholeStageCodegen (6) + HashAggregate [s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip,sum,sum,sum,sum,sum] [sum(CASE WHEN ((sr_returned_date_sk - ss_sold_date_sk) <= 30) THEN 1 ELSE 0 END),sum(CASE WHEN (((sr_returned_date_sk - ss_sold_date_sk) > 30) AND ((sr_returned_date_sk - ss_sold_date_sk) <= 60)) THEN 1 ELSE 0 END),sum(CASE WHEN (((sr_returned_date_sk - ss_sold_date_sk) > 60) AND ((sr_returned_date_sk - ss_sold_date_sk) <= 90)) THEN 1 ELSE 0 END),sum(CASE WHEN (((sr_returned_date_sk - ss_sold_date_sk) > 90) AND ((sr_returned_date_sk - ss_sold_date_sk) <= 120)) THEN 1 ELSE 0 END),sum(CASE WHEN ((sr_returned_date_sk - ss_sold_date_sk) > 120) THEN 1 ELSE 0 END),30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ,sum,sum,sum,sum,sum] + InputAdapter + Exchange [s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] #1 + WholeStageCodegen (5) + HashAggregate [s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip,sr_returned_date_sk,ss_sold_date_sk] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [ss_sold_date_sk,sr_returned_date_sk,s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Project [ss_sold_date_sk,sr_returned_date_sk,s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_sold_date_sk,sr_returned_date_sk,s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_sold_date_sk,sr_returned_date_sk] + BroadcastHashJoin [ss_ticket_number,ss_item_sk,ss_customer_sk,sr_ticket_number,sr_item_sk,sr_customer_sk] + Filter [ss_ticket_number,ss_item_sk,ss_customer_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [sr_ticket_number,sr_item_sk,sr_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/explain.txt new file mode 100644 index 000000000..dd0fdb3f0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/explain.txt @@ -0,0 +1,245 @@ +== Physical Plan == +TakeOrderedAndProject (37) ++- * Filter (36) + +- Window (35) + +- * Sort (34) + +- Exchange (33) + +- * Project (32) + +- * SortMergeJoin FullOuter (31) + :- * Sort (15) + : +- Exchange (14) + : +- * Project (13) + : +- Window (12) + : +- * Sort (11) + : +- Exchange (10) + : +- * HashAggregate (9) + : +- Exchange (8) + : +- * HashAggregate (7) + : +- * Project (6) + : +- * BroadcastHashJoin Inner BuildRight (5) + : :- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.web_sales (1) + : +- ReusedExchange (4) + +- * Sort (30) + +- Exchange (29) + +- * Project (28) + +- Window (27) + +- * Sort (26) + +- Exchange (25) + +- * HashAggregate (24) + +- Exchange (23) + +- * HashAggregate (22) + +- * Project (21) + +- * BroadcastHashJoin Inner BuildRight (20) + :- * Filter (18) + : +- * ColumnarToRow (17) + : +- CometScan parquet spark_catalog.default.store_sales (16) + +- ReusedExchange (19) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 2] +Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] + +(3) Filter [codegen id : 2] +Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(4) ReusedExchange [Reuses operator id: 42] +Output [2]: [d_date_sk#5, d_date#6] + +(5) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 2] +Output [3]: [ws_item_sk#1, ws_sales_price#2, d_date#6] +Input [5]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3, d_date_sk#5, d_date#6] + +(7) HashAggregate [codegen id : 2] +Input [3]: [ws_item_sk#1, ws_sales_price#2, d_date#6] +Keys [2]: [ws_item_sk#1, d_date#6] +Functions [1]: [partial_sum(UnscaledValue(ws_sales_price#2))] +Aggregate Attributes [1]: [sum#7] +Results [3]: [ws_item_sk#1, d_date#6, sum#8] + +(8) Exchange +Input [3]: [ws_item_sk#1, d_date#6, sum#8] +Arguments: hashpartitioning(ws_item_sk#1, d_date#6, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(9) HashAggregate [codegen id : 3] +Input [3]: [ws_item_sk#1, d_date#6, sum#8] +Keys [2]: [ws_item_sk#1, d_date#6] +Functions [1]: [sum(UnscaledValue(ws_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_sales_price#2))#9] +Results [4]: [ws_item_sk#1 AS item_sk#10, d_date#6, MakeDecimal(sum(UnscaledValue(ws_sales_price#2))#9,17,2) AS _w0#11, ws_item_sk#1] + +(10) Exchange +Input [4]: [item_sk#10, d_date#6, _w0#11, ws_item_sk#1] +Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [4]: [item_sk#10, d_date#6, _w0#11, ws_item_sk#1] +Arguments: [ws_item_sk#1 ASC NULLS FIRST, d_date#6 ASC NULLS FIRST], false, 0 + +(12) Window +Input [4]: [item_sk#10, d_date#6, _w0#11, ws_item_sk#1] +Arguments: [sum(_w0#11) windowspecdefinition(ws_item_sk#1, d_date#6 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS cume_sales#12], [ws_item_sk#1], [d_date#6 ASC NULLS FIRST] + +(13) Project [codegen id : 5] +Output [3]: [item_sk#10, d_date#6, cume_sales#12] +Input [5]: [item_sk#10, d_date#6, _w0#11, ws_item_sk#1, cume_sales#12] + +(14) Exchange +Input [3]: [item_sk#10, d_date#6, cume_sales#12] +Arguments: hashpartitioning(item_sk#10, d_date#6, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(15) Sort [codegen id : 6] +Input [3]: [item_sk#10, d_date#6, cume_sales#12] +Arguments: [item_sk#10 ASC NULLS FIRST, d_date#6 ASC NULLS FIRST], false, 0 + +(16) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#13, ss_sales_price#14, ss_sold_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#15), dynamicpruningexpression(ss_sold_date_sk#15 IN dynamicpruning#16)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 8] +Input [3]: [ss_item_sk#13, ss_sales_price#14, ss_sold_date_sk#15] + +(18) Filter [codegen id : 8] +Input [3]: [ss_item_sk#13, ss_sales_price#14, ss_sold_date_sk#15] +Condition : isnotnull(ss_item_sk#13) + +(19) ReusedExchange [Reuses operator id: 42] +Output [2]: [d_date_sk#17, d_date#18] + +(20) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#15] +Right keys [1]: [d_date_sk#17] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 8] +Output [3]: [ss_item_sk#13, ss_sales_price#14, d_date#18] +Input [5]: [ss_item_sk#13, ss_sales_price#14, ss_sold_date_sk#15, d_date_sk#17, d_date#18] + +(22) HashAggregate [codegen id : 8] +Input [3]: [ss_item_sk#13, ss_sales_price#14, d_date#18] +Keys [2]: [ss_item_sk#13, d_date#18] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#14))] +Aggregate Attributes [1]: [sum#19] +Results [3]: [ss_item_sk#13, d_date#18, sum#20] + +(23) Exchange +Input [3]: [ss_item_sk#13, d_date#18, sum#20] +Arguments: hashpartitioning(ss_item_sk#13, d_date#18, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(24) HashAggregate [codegen id : 9] +Input [3]: [ss_item_sk#13, d_date#18, sum#20] +Keys [2]: [ss_item_sk#13, d_date#18] +Functions [1]: [sum(UnscaledValue(ss_sales_price#14))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#14))#21] +Results [4]: [ss_item_sk#13 AS item_sk#22, d_date#18, MakeDecimal(sum(UnscaledValue(ss_sales_price#14))#21,17,2) AS _w0#23, ss_item_sk#13] + +(25) Exchange +Input [4]: [item_sk#22, d_date#18, _w0#23, ss_item_sk#13] +Arguments: hashpartitioning(ss_item_sk#13, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(26) Sort [codegen id : 10] +Input [4]: [item_sk#22, d_date#18, _w0#23, ss_item_sk#13] +Arguments: [ss_item_sk#13 ASC NULLS FIRST, d_date#18 ASC NULLS FIRST], false, 0 + +(27) Window +Input [4]: [item_sk#22, d_date#18, _w0#23, ss_item_sk#13] +Arguments: [sum(_w0#23) windowspecdefinition(ss_item_sk#13, d_date#18 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS cume_sales#24], [ss_item_sk#13], [d_date#18 ASC NULLS FIRST] + +(28) Project [codegen id : 11] +Output [3]: [item_sk#22, d_date#18, cume_sales#24] +Input [5]: [item_sk#22, d_date#18, _w0#23, ss_item_sk#13, cume_sales#24] + +(29) Exchange +Input [3]: [item_sk#22, d_date#18, cume_sales#24] +Arguments: hashpartitioning(item_sk#22, d_date#18, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(30) Sort [codegen id : 12] +Input [3]: [item_sk#22, d_date#18, cume_sales#24] +Arguments: [item_sk#22 ASC NULLS FIRST, d_date#18 ASC NULLS FIRST], false, 0 + +(31) SortMergeJoin [codegen id : 13] +Left keys [2]: [item_sk#10, d_date#6] +Right keys [2]: [item_sk#22, d_date#18] +Join type: FullOuter +Join condition: None + +(32) Project [codegen id : 13] +Output [4]: [CASE WHEN isnotnull(item_sk#10) THEN item_sk#10 ELSE item_sk#22 END AS item_sk#25, CASE WHEN isnotnull(d_date#6) THEN d_date#6 ELSE d_date#18 END AS d_date#26, cume_sales#12 AS web_sales#27, cume_sales#24 AS store_sales#28] +Input [6]: [item_sk#10, d_date#6, cume_sales#12, item_sk#22, d_date#18, cume_sales#24] + +(33) Exchange +Input [4]: [item_sk#25, d_date#26, web_sales#27, store_sales#28] +Arguments: hashpartitioning(item_sk#25, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(34) Sort [codegen id : 14] +Input [4]: [item_sk#25, d_date#26, web_sales#27, store_sales#28] +Arguments: [item_sk#25 ASC NULLS FIRST, d_date#26 ASC NULLS FIRST], false, 0 + +(35) Window +Input [4]: [item_sk#25, d_date#26, web_sales#27, store_sales#28] +Arguments: [max(web_sales#27) windowspecdefinition(item_sk#25, d_date#26 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS web_cumulative#29, max(store_sales#28) windowspecdefinition(item_sk#25, d_date#26 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS store_cumulative#30], [item_sk#25], [d_date#26 ASC NULLS FIRST] + +(36) Filter [codegen id : 15] +Input [6]: [item_sk#25, d_date#26, web_sales#27, store_sales#28, web_cumulative#29, store_cumulative#30] +Condition : ((isnotnull(web_cumulative#29) AND isnotnull(store_cumulative#30)) AND (web_cumulative#29 > store_cumulative#30)) + +(37) TakeOrderedAndProject +Input [6]: [item_sk#25, d_date#26, web_sales#27, store_sales#28, web_cumulative#29, store_cumulative#30] +Arguments: 100, [item_sk#25 ASC NULLS FIRST, d_date#26 ASC NULLS FIRST], [item_sk#25, d_date#26, web_sales#27, store_sales#28, web_cumulative#29, store_cumulative#30] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (42) ++- * Project (41) + +- * Filter (40) + +- * ColumnarToRow (39) + +- CometScan parquet spark_catalog.default.date_dim (38) + + +(38) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#5, d_date#6, d_month_seq#31] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(39) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#5, d_date#6, d_month_seq#31] + +(40) Filter [codegen id : 1] +Input [3]: [d_date_sk#5, d_date#6, d_month_seq#31] +Condition : (((isnotnull(d_month_seq#31) AND (d_month_seq#31 >= 1200)) AND (d_month_seq#31 <= 1211)) AND isnotnull(d_date_sk#5)) + +(41) Project [codegen id : 1] +Output [2]: [d_date_sk#5, d_date#6] +Input [3]: [d_date_sk#5, d_date#6, d_month_seq#31] + +(42) BroadcastExchange +Input [2]: [d_date_sk#5, d_date#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 16 Hosting Expression = ss_sold_date_sk#15 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/simplified.txt new file mode 100644 index 000000000..a6ce8a445 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/simplified.txt @@ -0,0 +1,75 @@ +TakeOrderedAndProject [item_sk,d_date,web_sales,store_sales,web_cumulative,store_cumulative] + WholeStageCodegen (15) + Filter [web_cumulative,store_cumulative] + InputAdapter + Window [web_sales,item_sk,d_date,store_sales] + WholeStageCodegen (14) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk] #1 + WholeStageCodegen (13) + Project [item_sk,item_sk,d_date,d_date,cume_sales,cume_sales] + SortMergeJoin [item_sk,d_date,item_sk,d_date] + InputAdapter + WholeStageCodegen (6) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk,d_date] #2 + WholeStageCodegen (5) + Project [item_sk,d_date,cume_sales] + InputAdapter + Window [_w0,ws_item_sk,d_date] + WholeStageCodegen (4) + Sort [ws_item_sk,d_date] + InputAdapter + Exchange [ws_item_sk] #3 + WholeStageCodegen (3) + HashAggregate [ws_item_sk,d_date,sum] [sum(UnscaledValue(ws_sales_price)),item_sk,_w0,sum] + InputAdapter + Exchange [ws_item_sk,d_date] #4 + WholeStageCodegen (2) + HashAggregate [ws_item_sk,d_date,ws_sales_price] [sum,sum] + Project [ws_item_sk,ws_sales_price,d_date] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + Project [d_date_sk,d_date] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk,d_date] #5 + InputAdapter + WholeStageCodegen (12) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk,d_date] #6 + WholeStageCodegen (11) + Project [item_sk,d_date,cume_sales] + InputAdapter + Window [_w0,ss_item_sk,d_date] + WholeStageCodegen (10) + Sort [ss_item_sk,d_date] + InputAdapter + Exchange [ss_item_sk] #7 + WholeStageCodegen (9) + HashAggregate [ss_item_sk,d_date,sum] [sum(UnscaledValue(ss_sales_price)),item_sk,_w0,sum] + InputAdapter + Exchange [ss_item_sk,d_date] #8 + WholeStageCodegen (8) + HashAggregate [ss_item_sk,d_date,ss_sales_price] [sum,sum] + Project [ss_item_sk,ss_sales_price,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/explain.txt new file mode 100644 index 000000000..f8131fa11 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/explain.txt @@ -0,0 +1,125 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * HashAggregate (20) + +- Exchange (19) + +- * HashAggregate (18) + +- * Project (17) + +- * BroadcastHashJoin Inner BuildRight (16) + :- * Project (10) + : +- * BroadcastHashJoin Inner BuildRight (9) + : :- * Project (4) + : : +- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.date_dim (1) + : +- BroadcastExchange (8) + : +- * Filter (7) + : +- * ColumnarToRow (6) + : +- CometScan parquet spark_catalog.default.store_sales (5) + +- BroadcastExchange (15) + +- * Project (14) + +- * Filter (13) + +- * ColumnarToRow (12) + +- CometScan parquet spark_catalog.default.item (11) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_moy#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] + +(3) Filter [codegen id : 3] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 2000)) AND isnotnull(d_date_sk#1)) + +(4) Project [codegen id : 3] +Output [2]: [d_date_sk#1, d_year#2] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] + +(5) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(7) Filter [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) + +(8) BroadcastExchange +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#6] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [3]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5] +Input [5]: [d_date_sk#1, d_year#2, ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(11) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,1), IsNotNull(i_item_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] + +(13) Filter [codegen id : 2] +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Condition : ((isnotnull(i_manager_id#10) AND (i_manager_id#10 = 1)) AND isnotnull(i_item_sk#7)) + +(14) Project [codegen id : 2] +Output [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] + +(15) BroadcastExchange +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#4] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [4]: [d_year#2, ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Input [6]: [d_year#2, ss_item_sk#4, ss_ext_sales_price#5, i_item_sk#7, i_brand_id#8, i_brand#9] + +(18) HashAggregate [codegen id : 3] +Input [4]: [d_year#2, ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Keys [3]: [d_year#2, i_brand#9, i_brand_id#8] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum#11] +Results [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] + +(19) Exchange +Input [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] +Arguments: hashpartitioning(d_year#2, i_brand#9, i_brand_id#8, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 4] +Input [4]: [d_year#2, i_brand#9, i_brand_id#8, sum#12] +Keys [3]: [d_year#2, i_brand#9, i_brand_id#8] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#5))#13] +Results [4]: [d_year#2, i_brand_id#8 AS brand_id#14, i_brand#9 AS brand#15, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#13,17,2) AS ext_price#16] + +(21) TakeOrderedAndProject +Input [4]: [d_year#2, brand_id#14, brand#15, ext_price#16] +Arguments: 100, [d_year#2 ASC NULLS FIRST, ext_price#16 DESC NULLS LAST, brand_id#14 ASC NULLS FIRST], [d_year#2, brand_id#14, brand#15, ext_price#16] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/simplified.txt new file mode 100644 index 000000000..591ba96c2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/simplified.txt @@ -0,0 +1,31 @@ +TakeOrderedAndProject [d_year,ext_price,brand_id,brand] + WholeStageCodegen (4) + HashAggregate [d_year,i_brand,i_brand_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),brand_id,brand,ext_price,sum] + InputAdapter + Exchange [d_year,i_brand,i_brand_id] #1 + WholeStageCodegen (3) + HashAggregate [d_year,i_brand,i_brand_id,ss_ext_sales_price] [sum,sum] + Project [d_year,ss_ext_sales_price,i_brand_id,i_brand] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [d_year,ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + Project [d_date_sk,d_year] + Filter [d_moy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [i_item_sk,i_brand_id,i_brand] + Filter [i_manager_id,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manager_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/explain.txt new file mode 100644 index 000000000..741e1e050 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/explain.txt @@ -0,0 +1,194 @@ +== Physical Plan == +TakeOrderedAndProject (28) ++- * Project (27) + +- * Filter (26) + +- Window (25) + +- * Sort (24) + +- Exchange (23) + +- * HashAggregate (22) + +- Exchange (21) + +- * HashAggregate (20) + +- * Project (19) + +- * BroadcastHashJoin Inner BuildRight (18) + :- * Project (13) + : +- * BroadcastHashJoin Inner BuildRight (12) + : :- * Project (10) + : : +- * BroadcastHashJoin Inner BuildRight (9) + : : :- * Project (4) + : : : +- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.item (1) + : : +- BroadcastExchange (8) + : : +- * Filter (7) + : : +- * ColumnarToRow (6) + : : +- CometScan parquet spark_catalog.default.store_sales (5) + : +- ReusedExchange (11) + +- BroadcastExchange (17) + +- * Filter (16) + +- * ColumnarToRow (15) + +- CometScan parquet spark_catalog.default.store (14) + + +(1) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [Or(And(And(In(i_category, [Books ,Children ,Electronics ]),In(i_class, [personal ,portable ,reference ,self-help ])),In(i_brand, [exportiunivamalg #6 ,scholaramalgamalg #7 ,scholaramalgamalg #8 ,scholaramalgamalg #6 ])),And(And(In(i_category, [Men ,Music ,Women ]),In(i_class, [accessories ,classical ,fragrances ,pants ])),In(i_brand, [amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ]))), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5] + +(3) Filter [codegen id : 4] +Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5] +Condition : ((((i_category#4 IN (Books ,Children ,Electronics ) AND i_class#3 IN (personal ,portable ,reference ,self-help )) AND i_brand#2 IN (scholaramalgamalg #7 ,scholaramalgamalg #8 ,exportiunivamalg #6 ,scholaramalgamalg #6 )) OR ((i_category#4 IN (Women ,Music ,Men ) AND i_class#3 IN (accessories ,classical ,fragrances ,pants )) AND i_brand#2 IN (amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ))) AND isnotnull(i_item_sk#1)) + +(4) Project [codegen id : 4] +Output [2]: [i_item_sk#1, i_manufact_id#5] +Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5] + +(5) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#13), dynamicpruningexpression(ss_sold_date_sk#13 IN dynamicpruning#14)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] + +(7) Filter [codegen id : 1] +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Condition : (isnotnull(ss_item_sk#10) AND isnotnull(ss_store_sk#11)) + +(8) BroadcastExchange +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 4] +Output [4]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Input [6]: [i_item_sk#1, i_manufact_id#5, ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] + +(11) ReusedExchange [Reuses operator id: 33] +Output [2]: [d_date_sk#15, d_qoy#16] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#13] +Right keys [1]: [d_date_sk#15] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [4]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, d_qoy#16] +Input [6]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13, d_date_sk#15, d_qoy#16] + +(14) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#17] + +(16) Filter [codegen id : 3] +Input [1]: [s_store_sk#17] +Condition : isnotnull(s_store_sk#17) + +(17) BroadcastExchange +Input [1]: [s_store_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#11] +Right keys [1]: [s_store_sk#17] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 4] +Output [3]: [i_manufact_id#5, ss_sales_price#12, d_qoy#16] +Input [5]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, d_qoy#16, s_store_sk#17] + +(20) HashAggregate [codegen id : 4] +Input [3]: [i_manufact_id#5, ss_sales_price#12, d_qoy#16] +Keys [2]: [i_manufact_id#5, d_qoy#16] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#12))] +Aggregate Attributes [1]: [sum#18] +Results [3]: [i_manufact_id#5, d_qoy#16, sum#19] + +(21) Exchange +Input [3]: [i_manufact_id#5, d_qoy#16, sum#19] +Arguments: hashpartitioning(i_manufact_id#5, d_qoy#16, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [3]: [i_manufact_id#5, d_qoy#16, sum#19] +Keys [2]: [i_manufact_id#5, d_qoy#16] +Functions [1]: [sum(UnscaledValue(ss_sales_price#12))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#12))#20] +Results [3]: [i_manufact_id#5, MakeDecimal(sum(UnscaledValue(ss_sales_price#12))#20,17,2) AS sum_sales#21, MakeDecimal(sum(UnscaledValue(ss_sales_price#12))#20,17,2) AS _w0#22] + +(23) Exchange +Input [3]: [i_manufact_id#5, sum_sales#21, _w0#22] +Arguments: hashpartitioning(i_manufact_id#5, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(24) Sort [codegen id : 6] +Input [3]: [i_manufact_id#5, sum_sales#21, _w0#22] +Arguments: [i_manufact_id#5 ASC NULLS FIRST], false, 0 + +(25) Window +Input [3]: [i_manufact_id#5, sum_sales#21, _w0#22] +Arguments: [avg(_w0#22) windowspecdefinition(i_manufact_id#5, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_quarterly_sales#23], [i_manufact_id#5] + +(26) Filter [codegen id : 7] +Input [4]: [i_manufact_id#5, sum_sales#21, _w0#22, avg_quarterly_sales#23] +Condition : CASE WHEN (avg_quarterly_sales#23 > 0.000000) THEN ((abs((sum_sales#21 - avg_quarterly_sales#23)) / avg_quarterly_sales#23) > 0.1000000000000000) ELSE false END + +(27) Project [codegen id : 7] +Output [3]: [i_manufact_id#5, sum_sales#21, avg_quarterly_sales#23] +Input [4]: [i_manufact_id#5, sum_sales#21, _w0#22, avg_quarterly_sales#23] + +(28) TakeOrderedAndProject +Input [3]: [i_manufact_id#5, sum_sales#21, avg_quarterly_sales#23] +Arguments: 100, [avg_quarterly_sales#23 ASC NULLS FIRST, sum_sales#21 ASC NULLS FIRST, i_manufact_id#5 ASC NULLS FIRST], [i_manufact_id#5, sum_sales#21, avg_quarterly_sales#23] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 5 Hosting Expression = ss_sold_date_sk#13 IN dynamicpruning#14 +BroadcastExchange (33) ++- * Project (32) + +- * Filter (31) + +- * ColumnarToRow (30) + +- CometScan parquet spark_catalog.default.date_dim (29) + + +(29) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#15, d_month_seq#24, d_qoy#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_month_seq, [1200,1201,1202,1203,1204,1205,1206,1207,1208,1209,1210,1211]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#15, d_month_seq#24, d_qoy#16] + +(31) Filter [codegen id : 1] +Input [3]: [d_date_sk#15, d_month_seq#24, d_qoy#16] +Condition : (d_month_seq#24 INSET 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211 AND isnotnull(d_date_sk#15)) + +(32) Project [codegen id : 1] +Output [2]: [d_date_sk#15, d_qoy#16] +Input [3]: [d_date_sk#15, d_month_seq#24, d_qoy#16] + +(33) BroadcastExchange +Input [2]: [d_date_sk#15, d_qoy#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/simplified.txt new file mode 100644 index 000000000..5e254d2ac --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/simplified.txt @@ -0,0 +1,51 @@ +TakeOrderedAndProject [avg_quarterly_sales,sum_sales,i_manufact_id] + WholeStageCodegen (7) + Project [i_manufact_id,sum_sales,avg_quarterly_sales] + Filter [avg_quarterly_sales,sum_sales] + InputAdapter + Window [_w0,i_manufact_id] + WholeStageCodegen (6) + Sort [i_manufact_id] + InputAdapter + Exchange [i_manufact_id] #1 + WholeStageCodegen (5) + HashAggregate [i_manufact_id,d_qoy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_manufact_id,d_qoy] #2 + WholeStageCodegen (4) + HashAggregate [i_manufact_id,d_qoy,ss_sales_price] [sum,sum] + Project [i_manufact_id,ss_sales_price,d_qoy] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [i_manufact_id,ss_store_sk,ss_sales_price,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [i_manufact_id,ss_store_sk,ss_sales_price,ss_sold_date_sk] + BroadcastHashJoin [i_item_sk,ss_item_sk] + Project [i_item_sk,i_manufact_id] + Filter [i_category,i_class,i_brand,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_manufact_id] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [ss_item_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk,d_qoy] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_qoy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/explain.txt new file mode 100644 index 000000000..7ceab6eaa --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/explain.txt @@ -0,0 +1,489 @@ +== Physical Plan == +TakeOrderedAndProject (56) ++- * HashAggregate (55) + +- Exchange (54) + +- * HashAggregate (53) + +- * HashAggregate (52) + +- Exchange (51) + +- * HashAggregate (50) + +- * Project (49) + +- * BroadcastHashJoin Inner BuildRight (48) + :- * Project (46) + : +- * BroadcastHashJoin Inner BuildRight (45) + : :- * Project (40) + : : +- * BroadcastHashJoin Inner BuildRight (39) + : : :- * Project (34) + : : : +- * BroadcastHashJoin Inner BuildRight (33) + : : : :- * HashAggregate (28) + : : : : +- Exchange (27) + : : : : +- * HashAggregate (26) + : : : : +- * Project (25) + : : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : : :- * Project (19) + : : : : : +- * BroadcastHashJoin Inner BuildRight (18) + : : : : : :- * Project (16) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (15) + : : : : : : :- Union (9) + : : : : : : : :- * Project (4) + : : : : : : : : +- * Filter (3) + : : : : : : : : +- * ColumnarToRow (2) + : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : : : +- * Project (8) + : : : : : : : +- * Filter (7) + : : : : : : : +- * ColumnarToRow (6) + : : : : : : : +- CometScan parquet spark_catalog.default.web_sales (5) + : : : : : : +- BroadcastExchange (14) + : : : : : : +- * Project (13) + : : : : : : +- * Filter (12) + : : : : : : +- * ColumnarToRow (11) + : : : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : : : +- ReusedExchange (17) + : : : : +- BroadcastExchange (23) + : : : : +- * Filter (22) + : : : : +- * ColumnarToRow (21) + : : : : +- CometScan parquet spark_catalog.default.customer (20) + : : : +- BroadcastExchange (32) + : : : +- * Filter (31) + : : : +- * ColumnarToRow (30) + : : : +- CometScan parquet spark_catalog.default.store_sales (29) + : : +- BroadcastExchange (38) + : : +- * Filter (37) + : : +- * ColumnarToRow (36) + : : +- CometScan parquet spark_catalog.default.customer_address (35) + : +- BroadcastExchange (44) + : +- * Filter (43) + : +- * ColumnarToRow (42) + : +- CometScan parquet spark_catalog.default.store (41) + +- ReusedExchange (47) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [3]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_sold_date_sk#3] + +(3) Filter [codegen id : 1] +Input [3]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_sold_date_sk#3] +Condition : (isnotnull(cs_item_sk#2) AND isnotnull(cs_bill_customer_sk#1)) + +(4) Project [codegen id : 1] +Output [3]: [cs_sold_date_sk#3 AS sold_date_sk#5, cs_bill_customer_sk#1 AS customer_sk#6, cs_item_sk#2 AS item_sk#7] +Input [3]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_sold_date_sk#3] + +(5) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#10), dynamicpruningexpression(ws_sold_date_sk#10 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 2] +Input [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] + +(7) Filter [codegen id : 2] +Input [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] +Condition : (isnotnull(ws_item_sk#8) AND isnotnull(ws_bill_customer_sk#9)) + +(8) Project [codegen id : 2] +Output [3]: [ws_sold_date_sk#10 AS sold_date_sk#11, ws_bill_customer_sk#9 AS customer_sk#12, ws_item_sk#8 AS item_sk#13] +Input [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] + +(9) Union + +(10) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#14, i_class#15, i_category#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), IsNotNull(i_class), EqualTo(i_category,Women ), EqualTo(i_class,maternity ), IsNotNull(i_item_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 3] +Input [3]: [i_item_sk#14, i_class#15, i_category#16] + +(12) Filter [codegen id : 3] +Input [3]: [i_item_sk#14, i_class#15, i_category#16] +Condition : ((((isnotnull(i_category#16) AND isnotnull(i_class#15)) AND (i_category#16 = Women )) AND (i_class#15 = maternity )) AND isnotnull(i_item_sk#14)) + +(13) Project [codegen id : 3] +Output [1]: [i_item_sk#14] +Input [3]: [i_item_sk#14, i_class#15, i_category#16] + +(14) BroadcastExchange +Input [1]: [i_item_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(15) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [item_sk#7] +Right keys [1]: [i_item_sk#14] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 6] +Output [2]: [sold_date_sk#5, customer_sk#6] +Input [4]: [sold_date_sk#5, customer_sk#6, item_sk#7, i_item_sk#14] + +(17) ReusedExchange [Reuses operator id: 61] +Output [1]: [d_date_sk#17] + +(18) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sold_date_sk#5] +Right keys [1]: [d_date_sk#17] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 6] +Output [1]: [customer_sk#6] +Input [3]: [sold_date_sk#5, customer_sk#6, d_date_sk#17] + +(20) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#18, c_current_addr_sk#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 5] +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] + +(22) Filter [codegen id : 5] +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Condition : (isnotnull(c_customer_sk#18) AND isnotnull(c_current_addr_sk#19)) + +(23) BroadcastExchange +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [customer_sk#6] +Right keys [1]: [c_customer_sk#18] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [2]: [c_customer_sk#18, c_current_addr_sk#19] +Input [3]: [customer_sk#6, c_customer_sk#18, c_current_addr_sk#19] + +(26) HashAggregate [codegen id : 6] +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Keys [2]: [c_customer_sk#18, c_current_addr_sk#19] +Functions: [] +Aggregate Attributes: [] +Results [2]: [c_customer_sk#18, c_current_addr_sk#19] + +(27) Exchange +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Arguments: hashpartitioning(c_customer_sk#18, c_current_addr_sk#19, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(28) HashAggregate [codegen id : 11] +Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Keys [2]: [c_customer_sk#18, c_current_addr_sk#19] +Functions: [] +Aggregate Attributes: [] +Results [2]: [c_customer_sk#18, c_current_addr_sk#19] + +(29) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#22), dynamicpruningexpression(ss_sold_date_sk#22 IN dynamicpruning#23)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 7] +Input [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] + +(31) Filter [codegen id : 7] +Input [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] +Condition : isnotnull(ss_customer_sk#20) + +(32) BroadcastExchange +Input [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(33) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [c_customer_sk#18] +Right keys [1]: [ss_customer_sk#20] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 11] +Output [4]: [c_customer_sk#18, c_current_addr_sk#19, ss_ext_sales_price#21, ss_sold_date_sk#22] +Input [5]: [c_customer_sk#18, c_current_addr_sk#19, ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] + +(35) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#24, ca_county#25, ca_state#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_county), IsNotNull(ca_state)] +ReadSchema: struct + +(36) ColumnarToRow [codegen id : 8] +Input [3]: [ca_address_sk#24, ca_county#25, ca_state#26] + +(37) Filter [codegen id : 8] +Input [3]: [ca_address_sk#24, ca_county#25, ca_state#26] +Condition : ((isnotnull(ca_address_sk#24) AND isnotnull(ca_county#25)) AND isnotnull(ca_state#26)) + +(38) BroadcastExchange +Input [3]: [ca_address_sk#24, ca_county#25, ca_state#26] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [c_current_addr_sk#19] +Right keys [1]: [ca_address_sk#24] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [5]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22, ca_county#25, ca_state#26] +Input [7]: [c_customer_sk#18, c_current_addr_sk#19, ss_ext_sales_price#21, ss_sold_date_sk#22, ca_address_sk#24, ca_county#25, ca_state#26] + +(41) Scan parquet spark_catalog.default.store +Output [2]: [s_county#27, s_state#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_county), IsNotNull(s_state)] +ReadSchema: struct + +(42) ColumnarToRow [codegen id : 9] +Input [2]: [s_county#27, s_state#28] + +(43) Filter [codegen id : 9] +Input [2]: [s_county#27, s_state#28] +Condition : (isnotnull(s_county#27) AND isnotnull(s_state#28)) + +(44) BroadcastExchange +Input [2]: [s_county#27, s_state#28] +Arguments: HashedRelationBroadcastMode(List(input[0, string, false], input[1, string, false]),false), [plan_id=6] + +(45) BroadcastHashJoin [codegen id : 11] +Left keys [2]: [ca_county#25, ca_state#26] +Right keys [2]: [s_county#27, s_state#28] +Join type: Inner +Join condition: None + +(46) Project [codegen id : 11] +Output [3]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22] +Input [7]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22, ca_county#25, ca_state#26, s_county#27, s_state#28] + +(47) ReusedExchange [Reuses operator id: 66] +Output [1]: [d_date_sk#29] + +(48) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ss_sold_date_sk#22] +Right keys [1]: [d_date_sk#29] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 11] +Output [2]: [c_customer_sk#18, ss_ext_sales_price#21] +Input [4]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22, d_date_sk#29] + +(50) HashAggregate [codegen id : 11] +Input [2]: [c_customer_sk#18, ss_ext_sales_price#21] +Keys [1]: [c_customer_sk#18] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#21))] +Aggregate Attributes [1]: [sum#30] +Results [2]: [c_customer_sk#18, sum#31] + +(51) Exchange +Input [2]: [c_customer_sk#18, sum#31] +Arguments: hashpartitioning(c_customer_sk#18, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(52) HashAggregate [codegen id : 12] +Input [2]: [c_customer_sk#18, sum#31] +Keys [1]: [c_customer_sk#18] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#21))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#21))#32] +Results [1]: [cast((MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#21))#32,17,2) / 50) as int) AS segment#33] + +(53) HashAggregate [codegen id : 12] +Input [1]: [segment#33] +Keys [1]: [segment#33] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#34] +Results [2]: [segment#33, count#35] + +(54) Exchange +Input [2]: [segment#33, count#35] +Arguments: hashpartitioning(segment#33, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(55) HashAggregate [codegen id : 13] +Input [2]: [segment#33, count#35] +Keys [1]: [segment#33] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#36] +Results [3]: [segment#33, count(1)#36 AS num_customers#37, (segment#33 * 50) AS segment_base#38] + +(56) TakeOrderedAndProject +Input [3]: [segment#33, num_customers#37, segment_base#38] +Arguments: 100, [segment#33 ASC NULLS FIRST, num_customers#37 ASC NULLS FIRST], [segment#33, num_customers#37, segment_base#38] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (61) ++- * Project (60) + +- * Filter (59) + +- * ColumnarToRow (58) + +- CometScan parquet spark_catalog.default.date_dim (57) + + +(57) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#17, d_year#39, d_moy#40] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,12), EqualTo(d_year,1998), IsNotNull(d_date_sk)] +ReadSchema: struct + +(58) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#17, d_year#39, d_moy#40] + +(59) Filter [codegen id : 1] +Input [3]: [d_date_sk#17, d_year#39, d_moy#40] +Condition : ((((isnotnull(d_moy#40) AND isnotnull(d_year#39)) AND (d_moy#40 = 12)) AND (d_year#39 = 1998)) AND isnotnull(d_date_sk#17)) + +(60) Project [codegen id : 1] +Output [1]: [d_date_sk#17] +Input [3]: [d_date_sk#17, d_year#39, d_moy#40] + +(61) BroadcastExchange +Input [1]: [d_date_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 5 Hosting Expression = ws_sold_date_sk#10 IN dynamicpruning#4 + +Subquery:3 Hosting operator id = 29 Hosting Expression = ss_sold_date_sk#22 IN dynamicpruning#23 +BroadcastExchange (66) ++- * Project (65) + +- * Filter (64) + +- * ColumnarToRow (63) + +- CometScan parquet spark_catalog.default.date_dim (62) + + +(62) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#29, d_month_seq#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,ScalarSubquery#42), LessThanOrEqual(d_month_seq,ScalarSubquery#43), IsNotNull(d_date_sk)] +ReadSchema: struct + +(63) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#29, d_month_seq#41] + +(64) Filter [codegen id : 1] +Input [2]: [d_date_sk#29, d_month_seq#41] +Condition : (((isnotnull(d_month_seq#41) AND (d_month_seq#41 >= ReusedSubquery Subquery scalar-subquery#42, [id=#44])) AND (d_month_seq#41 <= ReusedSubquery Subquery scalar-subquery#43, [id=#45])) AND isnotnull(d_date_sk#29)) + +(65) Project [codegen id : 1] +Output [1]: [d_date_sk#29] +Input [2]: [d_date_sk#29, d_month_seq#41] + +(66) BroadcastExchange +Input [1]: [d_date_sk#29] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=10] + +Subquery:4 Hosting operator id = 64 Hosting Expression = ReusedSubquery Subquery scalar-subquery#42, [id=#44] + +Subquery:5 Hosting operator id = 64 Hosting Expression = ReusedSubquery Subquery scalar-subquery#43, [id=#45] + +Subquery:6 Hosting operator id = 62 Hosting Expression = Subquery scalar-subquery#42, [id=#44] +* HashAggregate (73) ++- Exchange (72) + +- * HashAggregate (71) + +- * Project (70) + +- * Filter (69) + +- * ColumnarToRow (68) + +- CometScan parquet spark_catalog.default.date_dim (67) + + +(67) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_month_seq#46, d_year#47, d_moy#48] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,12)] +ReadSchema: struct + +(68) ColumnarToRow [codegen id : 1] +Input [3]: [d_month_seq#46, d_year#47, d_moy#48] + +(69) Filter [codegen id : 1] +Input [3]: [d_month_seq#46, d_year#47, d_moy#48] +Condition : (((isnotnull(d_year#47) AND isnotnull(d_moy#48)) AND (d_year#47 = 1998)) AND (d_moy#48 = 12)) + +(70) Project [codegen id : 1] +Output [1]: [(d_month_seq#46 + 1) AS (d_month_seq + 1)#49] +Input [3]: [d_month_seq#46, d_year#47, d_moy#48] + +(71) HashAggregate [codegen id : 1] +Input [1]: [(d_month_seq + 1)#49] +Keys [1]: [(d_month_seq + 1)#49] +Functions: [] +Aggregate Attributes: [] +Results [1]: [(d_month_seq + 1)#49] + +(72) Exchange +Input [1]: [(d_month_seq + 1)#49] +Arguments: hashpartitioning((d_month_seq + 1)#49, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(73) HashAggregate [codegen id : 2] +Input [1]: [(d_month_seq + 1)#49] +Keys [1]: [(d_month_seq + 1)#49] +Functions: [] +Aggregate Attributes: [] +Results [1]: [(d_month_seq + 1)#49] + +Subquery:7 Hosting operator id = 62 Hosting Expression = Subquery scalar-subquery#43, [id=#45] +* HashAggregate (80) ++- Exchange (79) + +- * HashAggregate (78) + +- * Project (77) + +- * Filter (76) + +- * ColumnarToRow (75) + +- CometScan parquet spark_catalog.default.date_dim (74) + + +(74) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_month_seq#50, d_year#51, d_moy#52] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,12)] +ReadSchema: struct + +(75) ColumnarToRow [codegen id : 1] +Input [3]: [d_month_seq#50, d_year#51, d_moy#52] + +(76) Filter [codegen id : 1] +Input [3]: [d_month_seq#50, d_year#51, d_moy#52] +Condition : (((isnotnull(d_year#51) AND isnotnull(d_moy#52)) AND (d_year#51 = 1998)) AND (d_moy#52 = 12)) + +(77) Project [codegen id : 1] +Output [1]: [(d_month_seq#50 + 3) AS (d_month_seq + 3)#53] +Input [3]: [d_month_seq#50, d_year#51, d_moy#52] + +(78) HashAggregate [codegen id : 1] +Input [1]: [(d_month_seq + 3)#53] +Keys [1]: [(d_month_seq + 3)#53] +Functions: [] +Aggregate Attributes: [] +Results [1]: [(d_month_seq + 3)#53] + +(79) Exchange +Input [1]: [(d_month_seq + 3)#53] +Arguments: hashpartitioning((d_month_seq + 3)#53, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(80) HashAggregate [codegen id : 2] +Input [1]: [(d_month_seq + 3)#53] +Keys [1]: [(d_month_seq + 3)#53] +Functions: [] +Aggregate Attributes: [] +Results [1]: [(d_month_seq + 3)#53] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/simplified.txt new file mode 100644 index 000000000..fa7a009d3 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/simplified.txt @@ -0,0 +1,128 @@ +TakeOrderedAndProject [segment,num_customers,segment_base] + WholeStageCodegen (13) + HashAggregate [segment,count] [count(1),num_customers,segment_base,count] + InputAdapter + Exchange [segment] #1 + WholeStageCodegen (12) + HashAggregate [segment] [count,count] + HashAggregate [c_customer_sk,sum] [sum(UnscaledValue(ss_ext_sales_price)),segment,sum] + InputAdapter + Exchange [c_customer_sk] #2 + WholeStageCodegen (11) + HashAggregate [c_customer_sk,ss_ext_sales_price] [sum,sum] + Project [c_customer_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_sk,ss_ext_sales_price,ss_sold_date_sk] + BroadcastHashJoin [ca_county,ca_state,s_county,s_state] + Project [c_customer_sk,ss_ext_sales_price,ss_sold_date_sk,ca_county,ca_state] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_customer_sk,c_current_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + HashAggregate [c_customer_sk,c_current_addr_sk] + InputAdapter + Exchange [c_customer_sk,c_current_addr_sk] #3 + WholeStageCodegen (6) + HashAggregate [c_customer_sk,c_current_addr_sk] + Project [c_customer_sk,c_current_addr_sk] + BroadcastHashJoin [customer_sk,c_customer_sk] + Project [customer_sk] + BroadcastHashJoin [sold_date_sk,d_date_sk] + Project [sold_date_sk,customer_sk] + BroadcastHashJoin [item_sk,i_item_sk] + InputAdapter + Union + WholeStageCodegen (1) + Project [cs_sold_date_sk,cs_bill_customer_sk,cs_item_sk] + Filter [cs_item_sk,cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_moy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + WholeStageCodegen (2) + Project [ws_sold_date_sk,ws_bill_customer_sk,ws_item_sk] + Filter [ws_item_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Project [i_item_sk] + Filter [i_category,i_class,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Filter [c_customer_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #8 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ReusedSubquery [(d_month_seq + 1)] #3 + ReusedSubquery [(d_month_seq + 3)] #4 + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + Subquery #3 + WholeStageCodegen (2) + HashAggregate [(d_month_seq + 1)] + InputAdapter + Exchange [(d_month_seq + 1)] #9 + WholeStageCodegen (1) + HashAggregate [(d_month_seq + 1)] + Project [d_month_seq] + Filter [d_year,d_moy] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] + Subquery #4 + WholeStageCodegen (2) + HashAggregate [(d_month_seq + 3)] + InputAdapter + Exchange [(d_month_seq + 3)] #10 + WholeStageCodegen (1) + HashAggregate [(d_month_seq + 3)] + Project [d_month_seq] + Filter [d_year,d_moy] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (8) + Filter [ca_address_sk,ca_county,ca_state] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county,ca_state] + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (9) + Filter [s_county,s_state] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_county,s_state] + InputAdapter + ReusedExchange [d_date_sk] #8 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/explain.txt new file mode 100644 index 000000000..0deabf94b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/explain.txt @@ -0,0 +1,125 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * HashAggregate (20) + +- Exchange (19) + +- * HashAggregate (18) + +- * Project (17) + +- * BroadcastHashJoin Inner BuildRight (16) + :- * Project (10) + : +- * BroadcastHashJoin Inner BuildRight (9) + : :- * Project (4) + : : +- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.date_dim (1) + : +- BroadcastExchange (8) + : +- * Filter (7) + : +- * ColumnarToRow (6) + : +- CometScan parquet spark_catalog.default.store_sales (5) + +- BroadcastExchange (15) + +- * Project (14) + +- * Filter (13) + +- * ColumnarToRow (12) + +- CometScan parquet spark_catalog.default.item (11) + + +(1) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#1, d_year#2, d_moy#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] + +(3) Filter [codegen id : 3] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 1999)) AND isnotnull(d_date_sk#1)) + +(4) Project [codegen id : 3] +Output [1]: [d_date_sk#1] +Input [3]: [d_date_sk#1, d_year#2, d_moy#3] + +(5) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(7) Filter [codegen id : 1] +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) + +(8) BroadcastExchange +Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date_sk#1] +Right keys [1]: [ss_sold_date_sk#6] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [2]: [ss_item_sk#4, ss_ext_sales_price#5] +Input [4]: [d_date_sk#1, ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(11) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,28), IsNotNull(i_item_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] + +(13) Filter [codegen id : 2] +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Condition : ((isnotnull(i_manager_id#10) AND (i_manager_id#10 = 28)) AND isnotnull(i_item_sk#7)) + +(14) Project [codegen id : 2] +Output [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] + +(15) BroadcastExchange +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#4] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 3] +Output [3]: [ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Input [5]: [ss_item_sk#4, ss_ext_sales_price#5, i_item_sk#7, i_brand_id#8, i_brand#9] + +(18) HashAggregate [codegen id : 3] +Input [3]: [ss_ext_sales_price#5, i_brand_id#8, i_brand#9] +Keys [2]: [i_brand#9, i_brand_id#8] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum#11] +Results [3]: [i_brand#9, i_brand_id#8, sum#12] + +(19) Exchange +Input [3]: [i_brand#9, i_brand_id#8, sum#12] +Arguments: hashpartitioning(i_brand#9, i_brand_id#8, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 4] +Input [3]: [i_brand#9, i_brand_id#8, sum#12] +Keys [2]: [i_brand#9, i_brand_id#8] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#5))#13] +Results [3]: [i_brand_id#8 AS brand_id#14, i_brand#9 AS brand#15, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#13,17,2) AS ext_price#16] + +(21) TakeOrderedAndProject +Input [3]: [brand_id#14, brand#15, ext_price#16] +Arguments: 100, [ext_price#16 DESC NULLS LAST, brand_id#14 ASC NULLS FIRST], [brand_id#14, brand#15, ext_price#16] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/simplified.txt new file mode 100644 index 000000000..911fe96b3 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/simplified.txt @@ -0,0 +1,31 @@ +TakeOrderedAndProject [ext_price,brand_id,brand] + WholeStageCodegen (4) + HashAggregate [i_brand,i_brand_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),brand_id,brand,ext_price,sum] + InputAdapter + Exchange [i_brand,i_brand_id] #1 + WholeStageCodegen (3) + HashAggregate [i_brand,i_brand_id,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_brand_id,i_brand] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [d_date_sk,ss_sold_date_sk] + Project [d_date_sk] + Filter [d_moy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [i_item_sk,i_brand_id,i_brand] + Filter [i_manager_id,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manager_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/explain.txt new file mode 100644 index 000000000..fef08c190 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/explain.txt @@ -0,0 +1,405 @@ +== Physical Plan == +TakeOrderedAndProject (63) ++- * HashAggregate (62) + +- Exchange (61) + +- * HashAggregate (60) + +- Union (59) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * Project (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.customer_address (7) + : +- BroadcastExchange (23) + : +- * BroadcastHashJoin LeftSemi BuildRight (22) + : :- * Filter (16) + : : +- * ColumnarToRow (15) + : : +- CometScan parquet spark_catalog.default.item (14) + : +- BroadcastExchange (21) + : +- * Project (20) + : +- * Filter (19) + : +- * ColumnarToRow (18) + : +- CometScan parquet spark_catalog.default.item (17) + :- * HashAggregate (43) + : +- Exchange (42) + : +- * HashAggregate (41) + : +- * Project (40) + : +- * BroadcastHashJoin Inner BuildRight (39) + : :- * Project (37) + : : +- * BroadcastHashJoin Inner BuildRight (36) + : : :- * Project (34) + : : : +- * BroadcastHashJoin Inner BuildRight (33) + : : : :- * Filter (31) + : : : : +- * ColumnarToRow (30) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (29) + : : : +- ReusedExchange (32) + : : +- ReusedExchange (35) + : +- ReusedExchange (38) + +- * HashAggregate (58) + +- Exchange (57) + +- * HashAggregate (56) + +- * Project (55) + +- * BroadcastHashJoin Inner BuildRight (54) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * Project (49) + : : +- * BroadcastHashJoin Inner BuildRight (48) + : : :- * Filter (46) + : : : +- * ColumnarToRow (45) + : : : +- CometScan parquet spark_catalog.default.web_sales (44) + : : +- ReusedExchange (47) + : +- ReusedExchange (50) + +- ReusedExchange (53) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_addr_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 5] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) + +(4) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 5] +Output [3]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3] +Input [5]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_gmt_offset#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] + +(9) Filter [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Condition : ((isnotnull(ca_gmt_offset#8) AND (ca_gmt_offset#8 = -5.00)) AND isnotnull(ca_address_sk#7)) + +(10) Project [codegen id : 2] +Output [1]: [ca_address_sk#7] +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] + +(11) BroadcastExchange +Input [1]: [ca_address_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#2] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [2]: [ss_item_sk#1, ss_ext_sales_price#3] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ca_address_sk#7] + +(14) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#9, i_item_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#9, i_item_id#10] + +(16) Filter [codegen id : 4] +Input [2]: [i_item_sk#9, i_item_id#10] +Condition : isnotnull(i_item_sk#9) + +(17) Scan parquet spark_catalog.default.item +Output [2]: [i_item_id#11, i_color#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_color, [blanched ,burnished ,slate ])] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 3] +Input [2]: [i_item_id#11, i_color#12] + +(19) Filter [codegen id : 3] +Input [2]: [i_item_id#11, i_color#12] +Condition : i_color#12 IN (slate ,blanched ,burnished ) + +(20) Project [codegen id : 3] +Output [1]: [i_item_id#11] +Input [2]: [i_item_id#11, i_color#12] + +(21) BroadcastExchange +Input [1]: [i_item_id#11] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=2] + +(22) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_id#10] +Right keys [1]: [i_item_id#11] +Join type: LeftSemi +Join condition: None + +(23) BroadcastExchange +Input [2]: [i_item_sk#9, i_item_id#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#9] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [2]: [ss_ext_sales_price#3, i_item_id#10] +Input [4]: [ss_item_sk#1, ss_ext_sales_price#3, i_item_sk#9, i_item_id#10] + +(26) HashAggregate [codegen id : 5] +Input [2]: [ss_ext_sales_price#3, i_item_id#10] +Keys [1]: [i_item_id#10] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum#13] +Results [2]: [i_item_id#10, sum#14] + +(27) Exchange +Input [2]: [i_item_id#10, sum#14] +Arguments: hashpartitioning(i_item_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 6] +Input [2]: [i_item_id#10, sum#14] +Keys [1]: [i_item_id#10] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#3))#15] +Results [2]: [i_item_id#10, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#15,17,2) AS total_sales#16] + +(29) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#20), dynamicpruningexpression(cs_sold_date_sk#20 IN dynamicpruning#21)] +PushedFilters: [IsNotNull(cs_bill_addr_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 11] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] + +(31) Filter [codegen id : 11] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) + +(32) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#22] + +(33) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_date_sk#20] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 11] +Output [3]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19] +Input [5]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20, d_date_sk#22] + +(35) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#23] + +(36) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_bill_addr_sk#17] +Right keys [1]: [ca_address_sk#23] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 11] +Output [2]: [cs_item_sk#18, cs_ext_sales_price#19] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, ca_address_sk#23] + +(38) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#24, i_item_id#25] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_item_sk#18] +Right keys [1]: [i_item_sk#24] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [2]: [cs_ext_sales_price#19, i_item_id#25] +Input [4]: [cs_item_sk#18, cs_ext_sales_price#19, i_item_sk#24, i_item_id#25] + +(41) HashAggregate [codegen id : 11] +Input [2]: [cs_ext_sales_price#19, i_item_id#25] +Keys [1]: [i_item_id#25] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum#26] +Results [2]: [i_item_id#25, sum#27] + +(42) Exchange +Input [2]: [i_item_id#25, sum#27] +Arguments: hashpartitioning(i_item_id#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(43) HashAggregate [codegen id : 12] +Input [2]: [i_item_id#25, sum#27] +Keys [1]: [i_item_id#25] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#19))#28] +Results [2]: [i_item_id#25, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#19))#28,17,2) AS total_sales#29] + +(44) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_sold_date_sk#33 IN dynamicpruning#34)] +PushedFilters: [IsNotNull(ws_bill_addr_sk), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 17] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] + +(46) Filter [codegen id : 17] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) + +(47) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#35] + +(48) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#33] +Right keys [1]: [d_date_sk#35] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 17] +Output [3]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32] +Input [5]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33, d_date_sk#35] + +(50) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#36] + +(51) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_bill_addr_sk#31] +Right keys [1]: [ca_address_sk#36] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 17] +Output [2]: [ws_item_sk#30, ws_ext_sales_price#32] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ca_address_sk#36] + +(53) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#37, i_item_id#38] + +(54) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_item_sk#30] +Right keys [1]: [i_item_sk#37] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 17] +Output [2]: [ws_ext_sales_price#32, i_item_id#38] +Input [4]: [ws_item_sk#30, ws_ext_sales_price#32, i_item_sk#37, i_item_id#38] + +(56) HashAggregate [codegen id : 17] +Input [2]: [ws_ext_sales_price#32, i_item_id#38] +Keys [1]: [i_item_id#38] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum#39] +Results [2]: [i_item_id#38, sum#40] + +(57) Exchange +Input [2]: [i_item_id#38, sum#40] +Arguments: hashpartitioning(i_item_id#38, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(58) HashAggregate [codegen id : 18] +Input [2]: [i_item_id#38, sum#40] +Keys [1]: [i_item_id#38] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#32))#41] +Results [2]: [i_item_id#38, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#32))#41,17,2) AS total_sales#42] + +(59) Union + +(60) HashAggregate [codegen id : 19] +Input [2]: [i_item_id#10, total_sales#16] +Keys [1]: [i_item_id#10] +Functions [1]: [partial_sum(total_sales#16)] +Aggregate Attributes [2]: [sum#43, isEmpty#44] +Results [3]: [i_item_id#10, sum#45, isEmpty#46] + +(61) Exchange +Input [3]: [i_item_id#10, sum#45, isEmpty#46] +Arguments: hashpartitioning(i_item_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(62) HashAggregate [codegen id : 20] +Input [3]: [i_item_id#10, sum#45, isEmpty#46] +Keys [1]: [i_item_id#10] +Functions [1]: [sum(total_sales#16)] +Aggregate Attributes [1]: [sum(total_sales#16)#47] +Results [2]: [i_item_id#10, sum(total_sales#16)#47 AS total_sales#48] + +(63) TakeOrderedAndProject +Input [2]: [i_item_id#10, total_sales#48] +Arguments: 100, [total_sales#48 ASC NULLS FIRST], [i_item_id#10, total_sales#48] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (68) ++- * Project (67) + +- * Filter (66) + +- * ColumnarToRow (65) + +- CometScan parquet spark_catalog.default.date_dim (64) + + +(64) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#6, d_year#49, d_moy#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)] +ReadSchema: struct + +(65) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] + +(66) Filter [codegen id : 1] +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#50)) AND (d_year#49 = 2001)) AND (d_moy#50 = 2)) AND isnotnull(d_date_sk#6)) + +(67) Project [codegen id : 1] +Output [1]: [d_date_sk#6] +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] + +(68) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 29 Hosting Expression = cs_sold_date_sk#20 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 44 Hosting Expression = ws_sold_date_sk#33 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/simplified.txt new file mode 100644 index 000000000..42b2cbfd3 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/simplified.txt @@ -0,0 +1,105 @@ +TakeOrderedAndProject [total_sales,i_item_id] + WholeStageCodegen (20) + HashAggregate [i_item_id,sum,isEmpty] [sum(total_sales),total_sales,sum,isEmpty] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (19) + HashAggregate [i_item_id,total_sales] [sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (6) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #2 + WholeStageCodegen (5) + HashAggregate [i_item_id,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_item_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_addr_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [ca_address_sk] + Filter [ca_gmt_offset,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + BroadcastHashJoin [i_item_id,i_item_id] + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + Project [i_item_id] + Filter [i_color] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_id,i_color] + WholeStageCodegen (12) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #7 + WholeStageCodegen (11) + HashAggregate [i_item_id,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_item_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_bill_addr_sk,ca_address_sk] + Project [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Filter [cs_bill_addr_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 + WholeStageCodegen (18) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ws_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #8 + WholeStageCodegen (17) + HashAggregate [i_item_id,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_item_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_bill_addr_sk,ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/explain.txt new file mode 100644 index 000000000..e7e6e9367 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/explain.txt @@ -0,0 +1,279 @@ +== Physical Plan == +TakeOrderedAndProject (45) ++- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (28) + : : +- * Filter (27) + : : +- Window (26) + : : +- * Filter (25) + : : +- Window (24) + : : +- * Sort (23) + : : +- Exchange (22) + : : +- * HashAggregate (21) + : : +- Exchange (20) + : : +- * HashAggregate (19) + : : +- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.item (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (16) + : : +- * Filter (15) + : : +- * ColumnarToRow (14) + : : +- CometScan parquet spark_catalog.default.call_center (13) + : +- BroadcastExchange (35) + : +- * Project (34) + : +- Window (33) + : +- * Sort (32) + : +- Exchange (31) + : +- * HashAggregate (30) + : +- ReusedExchange (29) + +- BroadcastExchange (42) + +- * Project (41) + +- Window (40) + +- * Sort (39) + +- ReusedExchange (38) + + +(1) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#1, i_brand#2, i_category#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] + +(3) Filter [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) + +(4) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#7), dynamicpruningexpression(cs_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_call_center_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] + +(6) Filter [codegen id : 1] +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Condition : (isnotnull(cs_item_sk#5) AND isnotnull(cs_call_center_sk#4)) + +(7) BroadcastExchange +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [cs_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [5]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, cs_sold_date_sk#7] +Input [7]: [i_item_sk#1, i_brand#2, i_category#3, cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 49] +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, d_year#10, d_moy#11] +Input [8]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, cs_sold_date_sk#7, d_date_sk#9, d_year#10, d_moy#11] + +(13) Scan parquet spark_catalog.default.call_center +Output [2]: [cc_call_center_sk#12, cc_name#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/call_center] +PushedFilters: [IsNotNull(cc_call_center_sk), IsNotNull(cc_name)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [2]: [cc_call_center_sk#12, cc_name#13] + +(15) Filter [codegen id : 3] +Input [2]: [cc_call_center_sk#12, cc_name#13] +Condition : (isnotnull(cc_call_center_sk#12) AND isnotnull(cc_name#13)) + +(16) BroadcastExchange +Input [2]: [cc_call_center_sk#12, cc_name#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_call_center_sk#4] +Right keys [1]: [cc_call_center_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, cs_sales_price#6, d_year#10, d_moy#11, cc_name#13] +Input [8]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, d_year#10, d_moy#11, cc_call_center_sk#12, cc_name#13] + +(19) HashAggregate [codegen id : 4] +Input [6]: [i_brand#2, i_category#3, cs_sales_price#6, d_year#10, d_moy#11, cc_name#13] +Keys [5]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11] +Functions [1]: [partial_sum(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [1]: [sum#14] +Results [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] + +(20) Exchange +Input [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] +Arguments: hashpartitioning(i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] +Keys [5]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11] +Functions [1]: [sum(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_sales_price#6))#16] +Results [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, MakeDecimal(sum(UnscaledValue(cs_sales_price#6))#16,17,2) AS sum_sales#17, MakeDecimal(sum(UnscaledValue(cs_sales_price#6))#16,17,2) AS _w0#18] + +(22) Exchange +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: hashpartitioning(i_category#3, i_brand#2, cc_name#13, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) Sort [codegen id : 6] +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: [i_category#3 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, cc_name#13 ASC NULLS FIRST, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST], false, 0 + +(24) Window +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: [rank(d_year#10, d_moy#11) windowspecdefinition(i_category#3, i_brand#2, cc_name#13, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#19], [i_category#3, i_brand#2, cc_name#13], [d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST] + +(25) Filter [codegen id : 7] +Input [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19] +Condition : (isnotnull(d_year#10) AND (d_year#10 = 1999)) + +(26) Window +Input [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19] +Arguments: [avg(_w0#18) windowspecdefinition(i_category#3, i_brand#2, cc_name#13, d_year#10, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#20], [i_category#3, i_brand#2, cc_name#13, d_year#10] + +(27) Filter [codegen id : 22] +Input [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19, avg_monthly_sales#20] +Condition : ((isnotnull(avg_monthly_sales#20) AND (avg_monthly_sales#20 > 0.000000)) AND CASE WHEN (avg_monthly_sales#20 > 0.000000) THEN ((abs((sum_sales#17 - avg_monthly_sales#20)) / avg_monthly_sales#20) > 0.1000000000000000) END) + +(28) Project [codegen id : 22] +Output [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19] +Input [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19, avg_monthly_sales#20] + +(29) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum#26] + +(30) HashAggregate [codegen id : 12] +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum#26] +Keys [5]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25] +Functions [1]: [sum(UnscaledValue(cs_sales_price#27))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_sales_price#27))#16] +Results [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, MakeDecimal(sum(UnscaledValue(cs_sales_price#27))#16,17,2) AS sum_sales#28] + +(31) Exchange +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: hashpartitioning(i_category#21, i_brand#22, cc_name#23, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 13] +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: [i_category#21 ASC NULLS FIRST, i_brand#22 ASC NULLS FIRST, cc_name#23 ASC NULLS FIRST, d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST], false, 0 + +(33) Window +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: [rank(d_year#24, d_moy#25) windowspecdefinition(i_category#21, i_brand#22, cc_name#23, d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#29], [i_category#21, i_brand#22, cc_name#23], [d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST] + +(34) Project [codegen id : 14] +Output [5]: [i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] +Input [7]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28, rn#29] + +(35) BroadcastExchange +Input [5]: [i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], (input[4, int, false] + 1)),false), [plan_id=6] + +(36) BroadcastHashJoin [codegen id : 22] +Left keys [4]: [i_category#3, i_brand#2, cc_name#13, rn#19] +Right keys [4]: [i_category#21, i_brand#22, cc_name#23, (rn#29 + 1)] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 22] +Output [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, sum_sales#28] +Input [13]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] + +(38) ReusedExchange [Reuses operator id: 31] +Output [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] + +(39) Sort [codegen id : 20] +Input [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] +Arguments: [i_category#30 ASC NULLS FIRST, i_brand#31 ASC NULLS FIRST, cc_name#32 ASC NULLS FIRST, d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST], false, 0 + +(40) Window +Input [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] +Arguments: [rank(d_year#33, d_moy#34) windowspecdefinition(i_category#30, i_brand#31, cc_name#32, d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#36], [i_category#30, i_brand#31, cc_name#32], [d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST] + +(41) Project [codegen id : 21] +Output [5]: [i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] +Input [7]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35, rn#36] + +(42) BroadcastExchange +Input [5]: [i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], (input[4, int, false] - 1)),false), [plan_id=7] + +(43) BroadcastHashJoin [codegen id : 22] +Left keys [4]: [i_category#3, i_brand#2, cc_name#13, rn#19] +Right keys [4]: [i_category#30, i_brand#31, cc_name#32, (rn#36 - 1)] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 22] +Output [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, sum_sales#28 AS psum#37, sum_sales#35 AS nsum#38] +Input [14]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, sum_sales#28, i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] + +(45) TakeOrderedAndProject +Input [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, psum#37, nsum#38] +Arguments: 100, [(sum_sales#17 - avg_monthly_sales#20) ASC NULLS FIRST, cc_name#13 ASC NULLS FIRST], [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, psum#37, nsum#38] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = cs_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (49) ++- * Filter (48) + +- * ColumnarToRow (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(48) Filter [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) + +(49) BroadcastExchange +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/simplified.txt new file mode 100644 index 000000000..84c5c5f83 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [sum_sales,avg_monthly_sales,cc_name,i_category,i_brand,d_year,d_moy,psum,nsum] + WholeStageCodegen (22) + Project [i_category,i_brand,cc_name,d_year,d_moy,avg_monthly_sales,sum_sales,sum_sales,sum_sales] + BroadcastHashJoin [i_category,i_brand,cc_name,rn,i_category,i_brand,cc_name,rn] + Project [i_category,i_brand,cc_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn,sum_sales] + BroadcastHashJoin [i_category,i_brand,cc_name,rn,i_category,i_brand,cc_name,rn] + Project [i_category,i_brand,cc_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_category,i_brand,cc_name,d_year] + WholeStageCodegen (7) + Filter [d_year] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (6) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,cc_name] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,sum] [sum(UnscaledValue(cs_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_category,i_brand,cc_name,d_year,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,cs_sales_price] [sum,sum] + Project [i_brand,i_category,cs_sales_price,d_year,d_moy,cc_name] + BroadcastHashJoin [cs_call_center_sk,cc_call_center_sk] + Project [i_brand,i_category,cs_call_center_sk,cs_sales_price,d_year,d_moy] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [i_brand,i_category,cs_call_center_sk,cs_sales_price,cs_sold_date_sk] + BroadcastHashJoin [i_item_sk,cs_item_sk] + Filter [i_item_sk,i_category,i_brand] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [cs_item_sk,cs_call_center_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_call_center_sk,cs_item_sk,cs_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [cc_call_center_sk,cc_name] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (14) + Project [i_category,i_brand,cc_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (13) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,cc_name] #7 + WholeStageCodegen (12) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,sum] [sum(UnscaledValue(cs_sales_price)),sum_sales,sum] + InputAdapter + ReusedExchange [i_category,i_brand,cc_name,d_year,d_moy,sum] #2 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (21) + Project [i_category,i_brand,cc_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (20) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + ReusedExchange [i_category,i_brand,cc_name,d_year,d_moy,sum_sales] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/explain.txt new file mode 100644 index 000000000..bd7b775d6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/explain.txt @@ -0,0 +1,386 @@ +== Physical Plan == +TakeOrderedAndProject (49) ++- * Project (48) + +- * BroadcastHashJoin Inner BuildRight (47) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Filter (16) + : : +- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.item (4) + : : +- ReusedExchange (10) + : +- BroadcastExchange (30) + : +- * Filter (29) + : +- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * Filter (19) + : : : +- * ColumnarToRow (18) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (17) + : : +- ReusedExchange (20) + : +- ReusedExchange (23) + +- BroadcastExchange (46) + +- * Filter (45) + +- * HashAggregate (44) + +- Exchange (43) + +- * HashAggregate (42) + +- * Project (41) + +- * BroadcastHashJoin Inner BuildRight (40) + :- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * Filter (35) + : : +- * ColumnarToRow (34) + : : +- CometScan parquet spark_catalog.default.web_sales (33) + : +- ReusedExchange (36) + +- ReusedExchange (39) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] + +(3) Filter [codegen id : 4] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#5, i_item_id#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_item_id)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [i_item_sk#5, i_item_id#6] + +(6) Filter [codegen id : 1] +Input [2]: [i_item_sk#5, i_item_id#6] +Condition : (isnotnull(i_item_sk#5) AND isnotnull(i_item_id#6)) + +(7) BroadcastExchange +Input [2]: [i_item_sk#5, i_item_id#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [3]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6] +Input [5]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_sk#5, i_item_id#6] + +(10) ReusedExchange [Reuses operator id: 60] +Output [1]: [d_date_sk#7] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [2]: [ss_ext_sales_price#2, i_item_id#6] +Input [4]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6, d_date_sk#7] + +(13) HashAggregate [codegen id : 4] +Input [2]: [ss_ext_sales_price#2, i_item_id#6] +Keys [1]: [i_item_id#6] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#8] +Results [2]: [i_item_id#6, sum#9] + +(14) Exchange +Input [2]: [i_item_id#6, sum#9] +Arguments: hashpartitioning(i_item_id#6, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 15] +Input [2]: [i_item_id#6, sum#9] +Keys [1]: [i_item_id#6] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#2))#10] +Results [2]: [i_item_id#6 AS item_id#11, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#10,17,2) AS ss_item_rev#12] + +(16) Filter [codegen id : 15] +Input [2]: [item_id#11, ss_item_rev#12] +Condition : isnotnull(ss_item_rev#12) + +(17) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_item_sk#13, cs_ext_sales_price#14, cs_sold_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#15), dynamicpruningexpression(cs_sold_date_sk#15 IN dynamicpruning#16)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 8] +Input [3]: [cs_item_sk#13, cs_ext_sales_price#14, cs_sold_date_sk#15] + +(19) Filter [codegen id : 8] +Input [3]: [cs_item_sk#13, cs_ext_sales_price#14, cs_sold_date_sk#15] +Condition : isnotnull(cs_item_sk#13) + +(20) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#17, i_item_id#18] + +(21) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_item_sk#13] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 8] +Output [3]: [cs_ext_sales_price#14, cs_sold_date_sk#15, i_item_id#18] +Input [5]: [cs_item_sk#13, cs_ext_sales_price#14, cs_sold_date_sk#15, i_item_sk#17, i_item_id#18] + +(23) ReusedExchange [Reuses operator id: 60] +Output [1]: [d_date_sk#19] + +(24) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [cs_sold_date_sk#15] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 8] +Output [2]: [cs_ext_sales_price#14, i_item_id#18] +Input [4]: [cs_ext_sales_price#14, cs_sold_date_sk#15, i_item_id#18, d_date_sk#19] + +(26) HashAggregate [codegen id : 8] +Input [2]: [cs_ext_sales_price#14, i_item_id#18] +Keys [1]: [i_item_id#18] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#14))] +Aggregate Attributes [1]: [sum#20] +Results [2]: [i_item_id#18, sum#21] + +(27) Exchange +Input [2]: [i_item_id#18, sum#21] +Arguments: hashpartitioning(i_item_id#18, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(28) HashAggregate [codegen id : 9] +Input [2]: [i_item_id#18, sum#21] +Keys [1]: [i_item_id#18] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#14))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#14))#22] +Results [2]: [i_item_id#18 AS item_id#23, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#14))#22,17,2) AS cs_item_rev#24] + +(29) Filter [codegen id : 9] +Input [2]: [item_id#23, cs_item_rev#24] +Condition : isnotnull(cs_item_rev#24) + +(30) BroadcastExchange +Input [2]: [item_id#23, cs_item_rev#24] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=4] + +(31) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [item_id#11] +Right keys [1]: [item_id#23] +Join type: Inner +Join condition: ((((cast(ss_item_rev#12 as decimal(19,3)) >= (0.9 * cs_item_rev#24)) AND (cast(ss_item_rev#12 as decimal(20,3)) <= (1.1 * cs_item_rev#24))) AND (cast(cs_item_rev#24 as decimal(19,3)) >= (0.9 * ss_item_rev#12))) AND (cast(cs_item_rev#24 as decimal(20,3)) <= (1.1 * ss_item_rev#12))) + +(32) Project [codegen id : 15] +Output [3]: [item_id#11, ss_item_rev#12, cs_item_rev#24] +Input [4]: [item_id#11, ss_item_rev#12, item_id#23, cs_item_rev#24] + +(33) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#25, ws_ext_sales_price#26, ws_sold_date_sk#27] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#27), dynamicpruningexpression(ws_sold_date_sk#27 IN dynamicpruning#28)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(34) ColumnarToRow [codegen id : 13] +Input [3]: [ws_item_sk#25, ws_ext_sales_price#26, ws_sold_date_sk#27] + +(35) Filter [codegen id : 13] +Input [3]: [ws_item_sk#25, ws_ext_sales_price#26, ws_sold_date_sk#27] +Condition : isnotnull(ws_item_sk#25) + +(36) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#29, i_item_id#30] + +(37) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ws_item_sk#25] +Right keys [1]: [i_item_sk#29] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 13] +Output [3]: [ws_ext_sales_price#26, ws_sold_date_sk#27, i_item_id#30] +Input [5]: [ws_item_sk#25, ws_ext_sales_price#26, ws_sold_date_sk#27, i_item_sk#29, i_item_id#30] + +(39) ReusedExchange [Reuses operator id: 60] +Output [1]: [d_date_sk#31] + +(40) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ws_sold_date_sk#27] +Right keys [1]: [d_date_sk#31] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 13] +Output [2]: [ws_ext_sales_price#26, i_item_id#30] +Input [4]: [ws_ext_sales_price#26, ws_sold_date_sk#27, i_item_id#30, d_date_sk#31] + +(42) HashAggregate [codegen id : 13] +Input [2]: [ws_ext_sales_price#26, i_item_id#30] +Keys [1]: [i_item_id#30] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#26))] +Aggregate Attributes [1]: [sum#32] +Results [2]: [i_item_id#30, sum#33] + +(43) Exchange +Input [2]: [i_item_id#30, sum#33] +Arguments: hashpartitioning(i_item_id#30, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(44) HashAggregate [codegen id : 14] +Input [2]: [i_item_id#30, sum#33] +Keys [1]: [i_item_id#30] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#26))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#26))#34] +Results [2]: [i_item_id#30 AS item_id#35, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#26))#34,17,2) AS ws_item_rev#36] + +(45) Filter [codegen id : 14] +Input [2]: [item_id#35, ws_item_rev#36] +Condition : isnotnull(ws_item_rev#36) + +(46) BroadcastExchange +Input [2]: [item_id#35, ws_item_rev#36] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=6] + +(47) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [item_id#11] +Right keys [1]: [item_id#35] +Join type: Inner +Join condition: ((((((((cast(ss_item_rev#12 as decimal(19,3)) >= (0.9 * ws_item_rev#36)) AND (cast(ss_item_rev#12 as decimal(20,3)) <= (1.1 * ws_item_rev#36))) AND (cast(cs_item_rev#24 as decimal(19,3)) >= (0.9 * ws_item_rev#36))) AND (cast(cs_item_rev#24 as decimal(20,3)) <= (1.1 * ws_item_rev#36))) AND (cast(ws_item_rev#36 as decimal(19,3)) >= (0.9 * ss_item_rev#12))) AND (cast(ws_item_rev#36 as decimal(20,3)) <= (1.1 * ss_item_rev#12))) AND (cast(ws_item_rev#36 as decimal(19,3)) >= (0.9 * cs_item_rev#24))) AND (cast(ws_item_rev#36 as decimal(20,3)) <= (1.1 * cs_item_rev#24))) + +(48) Project [codegen id : 15] +Output [8]: [item_id#11, ss_item_rev#12, (((ss_item_rev#12 / ((ss_item_rev#12 + cs_item_rev#24) + ws_item_rev#36)) / 3) * 100) AS ss_dev#37, cs_item_rev#24, (((cs_item_rev#24 / ((ss_item_rev#12 + cs_item_rev#24) + ws_item_rev#36)) / 3) * 100) AS cs_dev#38, ws_item_rev#36, (((ws_item_rev#36 / ((ss_item_rev#12 + cs_item_rev#24) + ws_item_rev#36)) / 3) * 100) AS ws_dev#39, (((ss_item_rev#12 + cs_item_rev#24) + ws_item_rev#36) / 3) AS average#40] +Input [5]: [item_id#11, ss_item_rev#12, cs_item_rev#24, item_id#35, ws_item_rev#36] + +(49) TakeOrderedAndProject +Input [8]: [item_id#11, ss_item_rev#12, ss_dev#37, cs_item_rev#24, cs_dev#38, ws_item_rev#36, ws_dev#39, average#40] +Arguments: 100, [item_id#11 ASC NULLS FIRST, ss_item_rev#12 ASC NULLS FIRST], [item_id#11, ss_item_rev#12, ss_dev#37, cs_item_rev#24, cs_dev#38, ws_item_rev#36, ws_dev#39, average#40] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (60) ++- * Project (59) + +- * BroadcastHashJoin LeftSemi BuildRight (58) + :- * Filter (52) + : +- * ColumnarToRow (51) + : +- CometScan parquet spark_catalog.default.date_dim (50) + +- BroadcastExchange (57) + +- * Project (56) + +- * Filter (55) + +- * ColumnarToRow (54) + +- CometScan parquet spark_catalog.default.date_dim (53) + + +(50) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#7, d_date#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(51) ColumnarToRow [codegen id : 2] +Input [2]: [d_date_sk#7, d_date#41] + +(52) Filter [codegen id : 2] +Input [2]: [d_date_sk#7, d_date#41] +Condition : isnotnull(d_date_sk#7) + +(53) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date#42, d_week_seq#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#44)] +ReadSchema: struct + +(54) ColumnarToRow [codegen id : 1] +Input [2]: [d_date#42, d_week_seq#43] + +(55) Filter [codegen id : 1] +Input [2]: [d_date#42, d_week_seq#43] +Condition : (isnotnull(d_week_seq#43) AND (d_week_seq#43 = ReusedSubquery Subquery scalar-subquery#44, [id=#45])) + +(56) Project [codegen id : 1] +Output [1]: [d_date#42] +Input [2]: [d_date#42, d_week_seq#43] + +(57) BroadcastExchange +Input [1]: [d_date#42] +Arguments: HashedRelationBroadcastMode(List(input[0, date, true]),false), [plan_id=7] + +(58) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [d_date#41] +Right keys [1]: [d_date#42] +Join type: LeftSemi +Join condition: None + +(59) Project [codegen id : 2] +Output [1]: [d_date_sk#7] +Input [2]: [d_date_sk#7, d_date#41] + +(60) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 55 Hosting Expression = ReusedSubquery Subquery scalar-subquery#44, [id=#45] + +Subquery:3 Hosting operator id = 53 Hosting Expression = Subquery scalar-subquery#44, [id=#45] +* Project (64) ++- * Filter (63) + +- * ColumnarToRow (62) + +- CometScan parquet spark_catalog.default.date_dim (61) + + +(61) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date#46, d_week_seq#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), EqualTo(d_date,2000-01-03)] +ReadSchema: struct + +(62) ColumnarToRow [codegen id : 1] +Input [2]: [d_date#46, d_week_seq#47] + +(63) Filter [codegen id : 1] +Input [2]: [d_date#46, d_week_seq#47] +Condition : (isnotnull(d_date#46) AND (d_date#46 = 2000-01-03)) + +(64) Project [codegen id : 1] +Output [1]: [d_week_seq#47] +Input [2]: [d_date#46, d_week_seq#47] + +Subquery:4 Hosting operator id = 17 Hosting Expression = cs_sold_date_sk#15 IN dynamicpruning#4 + +Subquery:5 Hosting operator id = 33 Hosting Expression = ws_sold_date_sk#27 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/simplified.txt new file mode 100644 index 000000000..007ac0887 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/simplified.txt @@ -0,0 +1,98 @@ +TakeOrderedAndProject [item_id,ss_item_rev,ss_dev,cs_item_rev,cs_dev,ws_item_rev,ws_dev,average] + WholeStageCodegen (15) + Project [item_id,ss_item_rev,cs_item_rev,ws_item_rev] + BroadcastHashJoin [item_id,item_id,ss_item_rev,ws_item_rev,cs_item_rev] + Project [item_id,ss_item_rev,cs_item_rev] + BroadcastHashJoin [item_id,item_id,ss_item_rev,cs_item_rev] + Filter [ss_item_rev] + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),item_id,ss_item_rev,sum] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_item_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_ext_sales_price,ss_sold_date_sk,i_item_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (2) + Project [d_date_sk] + BroadcastHashJoin [d_date,d_date] + Filter [d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date] + Filter [d_week_seq] + ReusedSubquery [d_week_seq] #2 + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] + Subquery #2 + WholeStageCodegen (1) + Project [d_week_seq] + Filter [d_date] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [i_item_sk,i_item_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (9) + Filter [cs_item_rev] + HashAggregate [i_item_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),item_id,cs_item_rev,sum] + InputAdapter + Exchange [i_item_id] #6 + WholeStageCodegen (8) + HashAggregate [i_item_id,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_item_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ext_sales_price,cs_sold_date_sk,i_item_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #4 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (14) + Filter [ws_item_rev] + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ws_ext_sales_price)),item_id,ws_item_rev,sum] + InputAdapter + Exchange [i_item_id] #8 + WholeStageCodegen (13) + HashAggregate [i_item_id,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_item_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_ext_sales_price,ws_sold_date_sk,i_item_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #4 + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/explain.txt new file mode 100644 index 000000000..aaea9f38f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/explain.txt @@ -0,0 +1,256 @@ +== Physical Plan == +TakeOrderedAndProject (44) ++- * Project (43) + +- * BroadcastHashJoin Inner BuildRight (42) + :- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * HashAggregate (12) + : : : +- Exchange (11) + : : : +- * HashAggregate (10) + : : : +- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.date_dim (4) + : : +- BroadcastExchange (16) + : : +- * Filter (15) + : : +- * ColumnarToRow (14) + : : +- CometScan parquet spark_catalog.default.store (13) + : +- BroadcastExchange (23) + : +- * Project (22) + : +- * Filter (21) + : +- * ColumnarToRow (20) + : +- CometScan parquet spark_catalog.default.date_dim (19) + +- BroadcastExchange (41) + +- * Project (40) + +- * BroadcastHashJoin Inner BuildRight (39) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * HashAggregate (27) + : : +- ReusedExchange (26) + : +- BroadcastExchange (31) + : +- * Filter (30) + : +- * ColumnarToRow (29) + : +- CometScan parquet spark_catalog.default.store (28) + +- BroadcastExchange (38) + +- * Project (37) + +- * Filter (36) + +- * ColumnarToRow (35) + +- CometScan parquet spark_catalog.default.date_dim (34) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 2] +Input [3]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3] + +(3) Filter [codegen id : 2] +Input [3]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) + +(4) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk), IsNotNull(d_week_seq)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] + +(6) Filter [codegen id : 1] +Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] +Condition : (isnotnull(d_date_sk#4) AND isnotnull(d_week_seq#5)) + +(7) BroadcastExchange +Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#4] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 2] +Output [4]: [ss_store_sk#1, ss_sales_price#2, d_week_seq#5, d_day_name#6] +Input [6]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3, d_date_sk#4, d_week_seq#5, d_day_name#6] + +(10) HashAggregate [codegen id : 2] +Input [4]: [ss_store_sk#1, ss_sales_price#2, d_week_seq#5, d_day_name#6] +Keys [2]: [d_week_seq#5, ss_store_sk#1] +Functions [7]: [partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))] +Aggregate Attributes [7]: [sum#7, sum#8, sum#9, sum#10, sum#11, sum#12, sum#13] +Results [9]: [d_week_seq#5, ss_store_sk#1, sum#14, sum#15, sum#16, sum#17, sum#18, sum#19, sum#20] + +(11) Exchange +Input [9]: [d_week_seq#5, ss_store_sk#1, sum#14, sum#15, sum#16, sum#17, sum#18, sum#19, sum#20] +Arguments: hashpartitioning(d_week_seq#5, ss_store_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) HashAggregate [codegen id : 10] +Input [9]: [d_week_seq#5, ss_store_sk#1, sum#14, sum#15, sum#16, sum#17, sum#18, sum#19, sum#20] +Keys [2]: [d_week_seq#5, ss_store_sk#1] +Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))] +Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday ) THEN ss_sales_price#2 END))#21, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday ) THEN ss_sales_price#2 END))#22, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday ) THEN ss_sales_price#2 END))#23, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END))#24, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END))#25, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday ) THEN ss_sales_price#2 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))#27] +Results [9]: [d_week_seq#5, ss_store_sk#1, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday ) THEN ss_sales_price#2 END))#21,17,2) AS sun_sales#28, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday ) THEN ss_sales_price#2 END))#22,17,2) AS mon_sales#29, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday ) THEN ss_sales_price#2 END))#23,17,2) AS tue_sales#30, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END))#24,17,2) AS wed_sales#31, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END))#25,17,2) AS thu_sales#32, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday ) THEN ss_sales_price#2 END))#26,17,2) AS fri_sales#33, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))#27,17,2) AS sat_sales#34] + +(13) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_id)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] + +(15) Filter [codegen id : 3] +Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] +Condition : (isnotnull(s_store_sk#35) AND isnotnull(s_store_id#36)) + +(16) BroadcastExchange +Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(17) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#35] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 10] +Output [10]: [d_week_seq#5, sun_sales#28, mon_sales#29, tue_sales#30, wed_sales#31, thu_sales#32, fri_sales#33, sat_sales#34, s_store_id#36, s_store_name#37] +Input [12]: [d_week_seq#5, ss_store_sk#1, sun_sales#28, mon_sales#29, tue_sales#30, wed_sales#31, thu_sales#32, fri_sales#33, sat_sales#34, s_store_sk#35, s_store_id#36, s_store_name#37] + +(19) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_month_seq#38, d_week_seq#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_week_seq)] +ReadSchema: struct + +(20) ColumnarToRow [codegen id : 4] +Input [2]: [d_month_seq#38, d_week_seq#39] + +(21) Filter [codegen id : 4] +Input [2]: [d_month_seq#38, d_week_seq#39] +Condition : (((isnotnull(d_month_seq#38) AND (d_month_seq#38 >= 1212)) AND (d_month_seq#38 <= 1223)) AND isnotnull(d_week_seq#39)) + +(22) Project [codegen id : 4] +Output [1]: [d_week_seq#39] +Input [2]: [d_month_seq#38, d_week_seq#39] + +(23) BroadcastExchange +Input [1]: [d_week_seq#39] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(24) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [d_week_seq#5] +Right keys [1]: [d_week_seq#39] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 10] +Output [10]: [s_store_name#37 AS s_store_name1#40, d_week_seq#5 AS d_week_seq1#41, s_store_id#36 AS s_store_id1#42, sun_sales#28 AS sun_sales1#43, mon_sales#29 AS mon_sales1#44, tue_sales#30 AS tue_sales1#45, wed_sales#31 AS wed_sales1#46, thu_sales#32 AS thu_sales1#47, fri_sales#33 AS fri_sales1#48, sat_sales#34 AS sat_sales1#49] +Input [11]: [d_week_seq#5, sun_sales#28, mon_sales#29, tue_sales#30, wed_sales#31, thu_sales#32, fri_sales#33, sat_sales#34, s_store_id#36, s_store_name#37, d_week_seq#39] + +(26) ReusedExchange [Reuses operator id: 11] +Output [9]: [d_week_seq#50, ss_store_sk#51, sum#52, sum#53, sum#54, sum#55, sum#56, sum#57, sum#58] + +(27) HashAggregate [codegen id : 9] +Input [9]: [d_week_seq#50, ss_store_sk#51, sum#52, sum#53, sum#54, sum#55, sum#56, sum#57, sum#58] +Keys [2]: [d_week_seq#50, ss_store_sk#51] +Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#59 = Sunday ) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Monday ) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Tuesday ) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Wednesday) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Thursday ) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Friday ) THEN ss_sales_price#60 END)), sum(UnscaledValue(CASE WHEN (d_day_name#59 = Saturday ) THEN ss_sales_price#60 END))] +Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#59 = Sunday ) THEN ss_sales_price#60 END))#21, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Monday ) THEN ss_sales_price#60 END))#22, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Tuesday ) THEN ss_sales_price#60 END))#23, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Wednesday) THEN ss_sales_price#60 END))#24, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Thursday ) THEN ss_sales_price#60 END))#25, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Friday ) THEN ss_sales_price#60 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#59 = Saturday ) THEN ss_sales_price#60 END))#27] +Results [9]: [d_week_seq#50, ss_store_sk#51, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Sunday ) THEN ss_sales_price#60 END))#21,17,2) AS sun_sales#61, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Monday ) THEN ss_sales_price#60 END))#22,17,2) AS mon_sales#62, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Tuesday ) THEN ss_sales_price#60 END))#23,17,2) AS tue_sales#63, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Wednesday) THEN ss_sales_price#60 END))#24,17,2) AS wed_sales#64, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Thursday ) THEN ss_sales_price#60 END))#25,17,2) AS thu_sales#65, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Friday ) THEN ss_sales_price#60 END))#26,17,2) AS fri_sales#66, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#59 = Saturday ) THEN ss_sales_price#60 END))#27,17,2) AS sat_sales#67] + +(28) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#68, s_store_id#69] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_id)] +ReadSchema: struct + +(29) ColumnarToRow [codegen id : 7] +Input [2]: [s_store_sk#68, s_store_id#69] + +(30) Filter [codegen id : 7] +Input [2]: [s_store_sk#68, s_store_id#69] +Condition : (isnotnull(s_store_sk#68) AND isnotnull(s_store_id#69)) + +(31) BroadcastExchange +Input [2]: [s_store_sk#68, s_store_id#69] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#51] +Right keys [1]: [s_store_sk#68] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [9]: [d_week_seq#50, sun_sales#61, mon_sales#62, tue_sales#63, wed_sales#64, thu_sales#65, fri_sales#66, sat_sales#67, s_store_id#69] +Input [11]: [d_week_seq#50, ss_store_sk#51, sun_sales#61, mon_sales#62, tue_sales#63, wed_sales#64, thu_sales#65, fri_sales#66, sat_sales#67, s_store_sk#68, s_store_id#69] + +(34) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_month_seq#70, d_week_seq#71] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1224), LessThanOrEqual(d_month_seq,1235), IsNotNull(d_week_seq)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 8] +Input [2]: [d_month_seq#70, d_week_seq#71] + +(36) Filter [codegen id : 8] +Input [2]: [d_month_seq#70, d_week_seq#71] +Condition : (((isnotnull(d_month_seq#70) AND (d_month_seq#70 >= 1224)) AND (d_month_seq#70 <= 1235)) AND isnotnull(d_week_seq#71)) + +(37) Project [codegen id : 8] +Output [1]: [d_week_seq#71] +Input [2]: [d_month_seq#70, d_week_seq#71] + +(38) BroadcastExchange +Input [1]: [d_week_seq#71] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +(39) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [d_week_seq#50] +Right keys [1]: [d_week_seq#71] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 9] +Output [9]: [d_week_seq#50 AS d_week_seq2#72, s_store_id#69 AS s_store_id2#73, sun_sales#61 AS sun_sales2#74, mon_sales#62 AS mon_sales2#75, tue_sales#63 AS tue_sales2#76, wed_sales#64 AS wed_sales2#77, thu_sales#65 AS thu_sales2#78, fri_sales#66 AS fri_sales2#79, sat_sales#67 AS sat_sales2#80] +Input [10]: [d_week_seq#50, sun_sales#61, mon_sales#62, tue_sales#63, wed_sales#64, thu_sales#65, fri_sales#66, sat_sales#67, s_store_id#69, d_week_seq#71] + +(41) BroadcastExchange +Input [9]: [d_week_seq2#72, s_store_id2#73, sun_sales2#74, mon_sales2#75, tue_sales2#76, wed_sales2#77, thu_sales2#78, fri_sales2#79, sat_sales2#80] +Arguments: HashedRelationBroadcastMode(List(input[1, string, true], (input[0, int, true] - 52)),false), [plan_id=7] + +(42) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [s_store_id1#42, d_week_seq1#41] +Right keys [2]: [s_store_id2#73, (d_week_seq2#72 - 52)] +Join type: Inner +Join condition: None + +(43) Project [codegen id : 10] +Output [10]: [s_store_name1#40, s_store_id1#42, d_week_seq1#41, (sun_sales1#43 / sun_sales2#74) AS (sun_sales1 / sun_sales2)#81, (mon_sales1#44 / mon_sales2#75) AS (mon_sales1 / mon_sales2)#82, (tue_sales1#45 / tue_sales2#76) AS (tue_sales1 / tue_sales2)#83, (wed_sales1#46 / wed_sales2#77) AS (wed_sales1 / wed_sales2)#84, (thu_sales1#47 / thu_sales2#78) AS (thu_sales1 / thu_sales2)#85, (fri_sales1#48 / fri_sales2#79) AS (fri_sales1 / fri_sales2)#86, (sat_sales1#49 / sat_sales2#80) AS (sat_sales1 / sat_sales2)#87] +Input [19]: [s_store_name1#40, d_week_seq1#41, s_store_id1#42, sun_sales1#43, mon_sales1#44, tue_sales1#45, wed_sales1#46, thu_sales1#47, fri_sales1#48, sat_sales1#49, d_week_seq2#72, s_store_id2#73, sun_sales2#74, mon_sales2#75, tue_sales2#76, wed_sales2#77, thu_sales2#78, fri_sales2#79, sat_sales2#80] + +(44) TakeOrderedAndProject +Input [10]: [s_store_name1#40, s_store_id1#42, d_week_seq1#41, (sun_sales1 / sun_sales2)#81, (mon_sales1 / mon_sales2)#82, (tue_sales1 / tue_sales2)#83, (wed_sales1 / wed_sales2)#84, (thu_sales1 / thu_sales2)#85, (fri_sales1 / fri_sales2)#86, (sat_sales1 / sat_sales2)#87] +Arguments: 100, [s_store_name1#40 ASC NULLS FIRST, s_store_id1#42 ASC NULLS FIRST, d_week_seq1#41 ASC NULLS FIRST], [s_store_name1#40, s_store_id1#42, d_week_seq1#41, (sun_sales1 / sun_sales2)#81, (mon_sales1 / mon_sales2)#82, (tue_sales1 / tue_sales2)#83, (wed_sales1 / wed_sales2)#84, (thu_sales1 / thu_sales2)#85, (fri_sales1 / fri_sales2)#86, (sat_sales1 / sat_sales2)#87] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/simplified.txt new file mode 100644 index 000000000..53d4d0b92 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/simplified.txt @@ -0,0 +1,66 @@ +TakeOrderedAndProject [s_store_name1,s_store_id1,d_week_seq1,(sun_sales1 / sun_sales2),(mon_sales1 / mon_sales2),(tue_sales1 / tue_sales2),(wed_sales1 / wed_sales2),(thu_sales1 / thu_sales2),(fri_sales1 / fri_sales2),(sat_sales1 / sat_sales2)] + WholeStageCodegen (10) + Project [s_store_name1,s_store_id1,d_week_seq1,sun_sales1,sun_sales2,mon_sales1,mon_sales2,tue_sales1,tue_sales2,wed_sales1,wed_sales2,thu_sales1,thu_sales2,fri_sales1,fri_sales2,sat_sales1,sat_sales2] + BroadcastHashJoin [s_store_id1,d_week_seq1,s_store_id2,d_week_seq2] + Project [s_store_name,d_week_seq,s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] + BroadcastHashJoin [d_week_seq,d_week_seq] + Project [d_week_seq,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,s_store_id,s_store_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + HashAggregate [d_week_seq,ss_store_sk,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN ss_sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] + InputAdapter + Exchange [d_week_seq,ss_store_sk] #1 + WholeStageCodegen (2) + HashAggregate [d_week_seq,ss_store_sk,d_day_name,ss_sales_price] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [ss_store_sk,ss_sales_price,d_week_seq,d_day_name] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [d_date_sk,d_week_seq] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq,d_day_name] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (3) + Filter [s_store_sk,s_store_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [d_week_seq] + Filter [d_month_seq,d_week_seq] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_week_seq] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (9) + Project [d_week_seq,s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] + BroadcastHashJoin [d_week_seq,d_week_seq] + Project [d_week_seq,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,s_store_id] + BroadcastHashJoin [ss_store_sk,s_store_sk] + HashAggregate [d_week_seq,ss_store_sk,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN ss_sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN ss_sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] + InputAdapter + ReusedExchange [d_week_seq,ss_store_sk,sum,sum,sum,sum,sum,sum,sum] #1 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + Filter [s_store_sk,s_store_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + Project [d_week_seq] + Filter [d_month_seq,d_week_seq] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_week_seq] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/explain.txt new file mode 100644 index 000000000..6b4318918 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/explain.txt @@ -0,0 +1,311 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * Filter (38) + +- * HashAggregate (37) + +- Exchange (36) + +- * HashAggregate (35) + +- * Project (34) + +- * BroadcastHashJoin Inner BuildRight (33) + :- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.customer_address (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.customer (4) + : : +- BroadcastExchange (13) + : : +- * Filter (12) + : : +- * ColumnarToRow (11) + : : +- CometScan parquet spark_catalog.default.store_sales (10) + : +- ReusedExchange (16) + +- BroadcastExchange (32) + +- * Project (31) + +- * BroadcastHashJoin Inner BuildRight (30) + :- * Filter (21) + : +- * ColumnarToRow (20) + : +- CometScan parquet spark_catalog.default.item (19) + +- BroadcastExchange (29) + +- * Filter (28) + +- * HashAggregate (27) + +- Exchange (26) + +- * HashAggregate (25) + +- * Filter (24) + +- * ColumnarToRow (23) + +- CometScan parquet spark_catalog.default.item (22) + + +(1) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#1, ca_state#2] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#1, ca_state#2] + +(3) Filter [codegen id : 7] +Input [2]: [ca_address_sk#1, ca_state#2] +Condition : isnotnull(ca_address_sk#1) + +(4) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#3, c_current_addr_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_customer_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] + +(6) Filter [codegen id : 1] +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] +Condition : (isnotnull(c_current_addr_sk#4) AND isnotnull(c_customer_sk#3)) + +(7) BroadcastExchange +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ca_address_sk#1] +Right keys [1]: [c_current_addr_sk#4] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 7] +Output [2]: [ca_state#2, c_customer_sk#3] +Input [4]: [ca_address_sk#1, ca_state#2, c_customer_sk#3, c_current_addr_sk#4] + +(10) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] + +(12) Filter [codegen id : 2] +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_customer_sk#6) AND isnotnull(ss_item_sk#5)) + +(13) BroadcastExchange +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ss_customer_sk#6] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 7] +Output [3]: [ca_state#2, ss_item_sk#5, ss_sold_date_sk#7] +Input [5]: [ca_state#2, c_customer_sk#3, ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] + +(16) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#9] + +(17) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 7] +Output [2]: [ca_state#2, ss_item_sk#5] +Input [4]: [ca_state#2, ss_item_sk#5, ss_sold_date_sk#7, d_date_sk#9] + +(19) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#10, i_current_price#11, i_category#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), IsNotNull(i_category), IsNotNull(i_item_sk)] +ReadSchema: struct + +(20) ColumnarToRow [codegen id : 6] +Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] + +(21) Filter [codegen id : 6] +Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] +Condition : ((isnotnull(i_current_price#11) AND isnotnull(i_category#12)) AND isnotnull(i_item_sk#10)) + +(22) Scan parquet spark_catalog.default.item +Output [2]: [i_current_price#13, i_category#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 4] +Input [2]: [i_current_price#13, i_category#14] + +(24) Filter [codegen id : 4] +Input [2]: [i_current_price#13, i_category#14] +Condition : isnotnull(i_category#14) + +(25) HashAggregate [codegen id : 4] +Input [2]: [i_current_price#13, i_category#14] +Keys [1]: [i_category#14] +Functions [1]: [partial_avg(UnscaledValue(i_current_price#13))] +Aggregate Attributes [2]: [sum#15, count#16] +Results [3]: [i_category#14, sum#17, count#18] + +(26) Exchange +Input [3]: [i_category#14, sum#17, count#18] +Arguments: hashpartitioning(i_category#14, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 5] +Input [3]: [i_category#14, sum#17, count#18] +Keys [1]: [i_category#14] +Functions [1]: [avg(UnscaledValue(i_current_price#13))] +Aggregate Attributes [1]: [avg(UnscaledValue(i_current_price#13))#19] +Results [2]: [cast((avg(UnscaledValue(i_current_price#13))#19 / 100.0) as decimal(11,6)) AS avg(i_current_price)#20, i_category#14] + +(28) Filter [codegen id : 5] +Input [2]: [avg(i_current_price)#20, i_category#14] +Condition : isnotnull(avg(i_current_price)#20) + +(29) BroadcastExchange +Input [2]: [avg(i_current_price)#20, i_category#14] +Arguments: HashedRelationBroadcastMode(List(input[1, string, true]),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [i_category#12] +Right keys [1]: [i_category#14] +Join type: Inner +Join condition: (cast(i_current_price#11 as decimal(14,7)) > (1.2 * avg(i_current_price)#20)) + +(31) Project [codegen id : 6] +Output [1]: [i_item_sk#10] +Input [5]: [i_item_sk#10, i_current_price#11, i_category#12, avg(i_current_price)#20, i_category#14] + +(32) BroadcastExchange +Input [1]: [i_item_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_item_sk#5] +Right keys [1]: [i_item_sk#10] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 7] +Output [1]: [ca_state#2] +Input [3]: [ca_state#2, ss_item_sk#5, i_item_sk#10] + +(35) HashAggregate [codegen id : 7] +Input [1]: [ca_state#2] +Keys [1]: [ca_state#2] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#21] +Results [2]: [ca_state#2, count#22] + +(36) Exchange +Input [2]: [ca_state#2, count#22] +Arguments: hashpartitioning(ca_state#2, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(37) HashAggregate [codegen id : 8] +Input [2]: [ca_state#2, count#22] +Keys [1]: [ca_state#2] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#23] +Results [2]: [ca_state#2 AS state#24, count(1)#23 AS cnt#25] + +(38) Filter [codegen id : 8] +Input [2]: [state#24, cnt#25] +Condition : (cnt#25 >= 10) + +(39) TakeOrderedAndProject +Input [2]: [state#24, cnt#25] +Arguments: 100, [cnt#25 ASC NULLS FIRST], [state#24, cnt#25] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (44) ++- * Project (43) + +- * Filter (42) + +- * ColumnarToRow (41) + +- CometScan parquet spark_catalog.default.date_dim (40) + + +(40) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#9, d_month_seq#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), EqualTo(d_month_seq,ScalarSubquery#27), IsNotNull(d_date_sk)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#9, d_month_seq#26] + +(42) Filter [codegen id : 1] +Input [2]: [d_date_sk#9, d_month_seq#26] +Condition : ((isnotnull(d_month_seq#26) AND (d_month_seq#26 = ReusedSubquery Subquery scalar-subquery#27, [id=#28])) AND isnotnull(d_date_sk#9)) + +(43) Project [codegen id : 1] +Output [1]: [d_date_sk#9] +Input [2]: [d_date_sk#9, d_month_seq#26] + +(44) BroadcastExchange +Input [1]: [d_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 42 Hosting Expression = ReusedSubquery Subquery scalar-subquery#27, [id=#28] + +Subquery:3 Hosting operator id = 40 Hosting Expression = Subquery scalar-subquery#27, [id=#28] +* HashAggregate (51) ++- Exchange (50) + +- * HashAggregate (49) + +- * Project (48) + +- * Filter (47) + +- * ColumnarToRow (46) + +- CometScan parquet spark_catalog.default.date_dim (45) + + +(45) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_month_seq#29, d_year#30, d_moy#31] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,1)] +ReadSchema: struct + +(46) ColumnarToRow [codegen id : 1] +Input [3]: [d_month_seq#29, d_year#30, d_moy#31] + +(47) Filter [codegen id : 1] +Input [3]: [d_month_seq#29, d_year#30, d_moy#31] +Condition : (((isnotnull(d_year#30) AND isnotnull(d_moy#31)) AND (d_year#30 = 2000)) AND (d_moy#31 = 1)) + +(48) Project [codegen id : 1] +Output [1]: [d_month_seq#29] +Input [3]: [d_month_seq#29, d_year#30, d_moy#31] + +(49) HashAggregate [codegen id : 1] +Input [1]: [d_month_seq#29] +Keys [1]: [d_month_seq#29] +Functions: [] +Aggregate Attributes: [] +Results [1]: [d_month_seq#29] + +(50) Exchange +Input [1]: [d_month_seq#29] +Arguments: hashpartitioning(d_month_seq#29, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(51) HashAggregate [codegen id : 2] +Input [1]: [d_month_seq#29] +Keys [1]: [d_month_seq#29] +Functions: [] +Aggregate Attributes: [] +Results [1]: [d_month_seq#29] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/simplified.txt new file mode 100644 index 000000000..7078a77e4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/simplified.txt @@ -0,0 +1,79 @@ +TakeOrderedAndProject [cnt,state] + WholeStageCodegen (8) + Filter [cnt] + HashAggregate [ca_state,count] [count(1),state,cnt,count] + InputAdapter + Exchange [ca_state] #1 + WholeStageCodegen (7) + HashAggregate [ca_state] [count,count] + Project [ca_state] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ca_state,ss_item_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ca_state,ss_item_sk,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Project [ca_state,c_customer_sk] + BroadcastHashJoin [ca_address_sk,c_current_addr_sk] + Filter [ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [c_current_addr_sk,c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [ss_customer_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ReusedSubquery [d_month_seq] #2 + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + Subquery #2 + WholeStageCodegen (2) + HashAggregate [d_month_seq] + InputAdapter + Exchange [d_month_seq] #5 + WholeStageCodegen (1) + HashAggregate [d_month_seq] + Project [d_month_seq] + Filter [d_year,d_moy] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Project [i_item_sk] + BroadcastHashJoin [i_category,i_category,i_current_price,avg(i_current_price)] + Filter [i_current_price,i_category,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_category] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (5) + Filter [avg(i_current_price)] + HashAggregate [i_category,sum,count] [avg(UnscaledValue(i_current_price)),avg(i_current_price),sum,count] + InputAdapter + Exchange [i_category] #8 + WholeStageCodegen (4) + HashAggregate [i_category,i_current_price] [sum,count,sum,count] + Filter [i_category] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_current_price,i_category] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/explain.txt new file mode 100644 index 000000000..98fb9f2f6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/explain.txt @@ -0,0 +1,405 @@ +== Physical Plan == +TakeOrderedAndProject (63) ++- * HashAggregate (62) + +- Exchange (61) + +- * HashAggregate (60) + +- Union (59) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * Project (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.customer_address (7) + : +- BroadcastExchange (23) + : +- * BroadcastHashJoin LeftSemi BuildRight (22) + : :- * Filter (16) + : : +- * ColumnarToRow (15) + : : +- CometScan parquet spark_catalog.default.item (14) + : +- BroadcastExchange (21) + : +- * Project (20) + : +- * Filter (19) + : +- * ColumnarToRow (18) + : +- CometScan parquet spark_catalog.default.item (17) + :- * HashAggregate (43) + : +- Exchange (42) + : +- * HashAggregate (41) + : +- * Project (40) + : +- * BroadcastHashJoin Inner BuildRight (39) + : :- * Project (37) + : : +- * BroadcastHashJoin Inner BuildRight (36) + : : :- * Project (34) + : : : +- * BroadcastHashJoin Inner BuildRight (33) + : : : :- * Filter (31) + : : : : +- * ColumnarToRow (30) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (29) + : : : +- ReusedExchange (32) + : : +- ReusedExchange (35) + : +- ReusedExchange (38) + +- * HashAggregate (58) + +- Exchange (57) + +- * HashAggregate (56) + +- * Project (55) + +- * BroadcastHashJoin Inner BuildRight (54) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * Project (49) + : : +- * BroadcastHashJoin Inner BuildRight (48) + : : :- * Filter (46) + : : : +- * ColumnarToRow (45) + : : : +- CometScan parquet spark_catalog.default.web_sales (44) + : : +- ReusedExchange (47) + : +- ReusedExchange (50) + +- ReusedExchange (53) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_addr_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 5] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) + +(4) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 5] +Output [3]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3] +Input [5]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_gmt_offset#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] + +(9) Filter [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Condition : ((isnotnull(ca_gmt_offset#8) AND (ca_gmt_offset#8 = -5.00)) AND isnotnull(ca_address_sk#7)) + +(10) Project [codegen id : 2] +Output [1]: [ca_address_sk#7] +Input [2]: [ca_address_sk#7, ca_gmt_offset#8] + +(11) BroadcastExchange +Input [1]: [ca_address_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#2] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [2]: [ss_item_sk#1, ss_ext_sales_price#3] +Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ca_address_sk#7] + +(14) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#9, i_item_id#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#9, i_item_id#10] + +(16) Filter [codegen id : 4] +Input [2]: [i_item_sk#9, i_item_id#10] +Condition : isnotnull(i_item_sk#9) + +(17) Scan parquet spark_catalog.default.item +Output [2]: [i_item_id#11, i_category#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Music )] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 3] +Input [2]: [i_item_id#11, i_category#12] + +(19) Filter [codegen id : 3] +Input [2]: [i_item_id#11, i_category#12] +Condition : (isnotnull(i_category#12) AND (i_category#12 = Music )) + +(20) Project [codegen id : 3] +Output [1]: [i_item_id#11] +Input [2]: [i_item_id#11, i_category#12] + +(21) BroadcastExchange +Input [1]: [i_item_id#11] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=2] + +(22) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_id#10] +Right keys [1]: [i_item_id#11] +Join type: LeftSemi +Join condition: None + +(23) BroadcastExchange +Input [2]: [i_item_sk#9, i_item_id#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#9] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [2]: [ss_ext_sales_price#3, i_item_id#10] +Input [4]: [ss_item_sk#1, ss_ext_sales_price#3, i_item_sk#9, i_item_id#10] + +(26) HashAggregate [codegen id : 5] +Input [2]: [ss_ext_sales_price#3, i_item_id#10] +Keys [1]: [i_item_id#10] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum#13] +Results [2]: [i_item_id#10, sum#14] + +(27) Exchange +Input [2]: [i_item_id#10, sum#14] +Arguments: hashpartitioning(i_item_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 6] +Input [2]: [i_item_id#10, sum#14] +Keys [1]: [i_item_id#10] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#3))#15] +Results [2]: [i_item_id#10, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#15,17,2) AS total_sales#16] + +(29) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#20), dynamicpruningexpression(cs_sold_date_sk#20 IN dynamicpruning#21)] +PushedFilters: [IsNotNull(cs_bill_addr_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 11] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] + +(31) Filter [codegen id : 11] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) + +(32) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#22] + +(33) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_date_sk#20] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 11] +Output [3]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19] +Input [5]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20, d_date_sk#22] + +(35) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#23] + +(36) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_bill_addr_sk#17] +Right keys [1]: [ca_address_sk#23] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 11] +Output [2]: [cs_item_sk#18, cs_ext_sales_price#19] +Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, ca_address_sk#23] + +(38) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#24, i_item_id#25] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_item_sk#18] +Right keys [1]: [i_item_sk#24] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [2]: [cs_ext_sales_price#19, i_item_id#25] +Input [4]: [cs_item_sk#18, cs_ext_sales_price#19, i_item_sk#24, i_item_id#25] + +(41) HashAggregate [codegen id : 11] +Input [2]: [cs_ext_sales_price#19, i_item_id#25] +Keys [1]: [i_item_id#25] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum#26] +Results [2]: [i_item_id#25, sum#27] + +(42) Exchange +Input [2]: [i_item_id#25, sum#27] +Arguments: hashpartitioning(i_item_id#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(43) HashAggregate [codegen id : 12] +Input [2]: [i_item_id#25, sum#27] +Keys [1]: [i_item_id#25] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#19))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#19))#28] +Results [2]: [i_item_id#25, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#19))#28,17,2) AS total_sales#29] + +(44) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_sold_date_sk#33 IN dynamicpruning#34)] +PushedFilters: [IsNotNull(ws_bill_addr_sk), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 17] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] + +(46) Filter [codegen id : 17] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) + +(47) ReusedExchange [Reuses operator id: 68] +Output [1]: [d_date_sk#35] + +(48) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#33] +Right keys [1]: [d_date_sk#35] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 17] +Output [3]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32] +Input [5]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33, d_date_sk#35] + +(50) ReusedExchange [Reuses operator id: 11] +Output [1]: [ca_address_sk#36] + +(51) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_bill_addr_sk#31] +Right keys [1]: [ca_address_sk#36] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 17] +Output [2]: [ws_item_sk#30, ws_ext_sales_price#32] +Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ca_address_sk#36] + +(53) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#37, i_item_id#38] + +(54) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_item_sk#30] +Right keys [1]: [i_item_sk#37] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 17] +Output [2]: [ws_ext_sales_price#32, i_item_id#38] +Input [4]: [ws_item_sk#30, ws_ext_sales_price#32, i_item_sk#37, i_item_id#38] + +(56) HashAggregate [codegen id : 17] +Input [2]: [ws_ext_sales_price#32, i_item_id#38] +Keys [1]: [i_item_id#38] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum#39] +Results [2]: [i_item_id#38, sum#40] + +(57) Exchange +Input [2]: [i_item_id#38, sum#40] +Arguments: hashpartitioning(i_item_id#38, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(58) HashAggregate [codegen id : 18] +Input [2]: [i_item_id#38, sum#40] +Keys [1]: [i_item_id#38] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#32))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#32))#41] +Results [2]: [i_item_id#38, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#32))#41,17,2) AS total_sales#42] + +(59) Union + +(60) HashAggregate [codegen id : 19] +Input [2]: [i_item_id#10, total_sales#16] +Keys [1]: [i_item_id#10] +Functions [1]: [partial_sum(total_sales#16)] +Aggregate Attributes [2]: [sum#43, isEmpty#44] +Results [3]: [i_item_id#10, sum#45, isEmpty#46] + +(61) Exchange +Input [3]: [i_item_id#10, sum#45, isEmpty#46] +Arguments: hashpartitioning(i_item_id#10, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(62) HashAggregate [codegen id : 20] +Input [3]: [i_item_id#10, sum#45, isEmpty#46] +Keys [1]: [i_item_id#10] +Functions [1]: [sum(total_sales#16)] +Aggregate Attributes [1]: [sum(total_sales#16)#47] +Results [2]: [i_item_id#10, sum(total_sales#16)#47 AS total_sales#48] + +(63) TakeOrderedAndProject +Input [2]: [i_item_id#10, total_sales#48] +Arguments: 100, [i_item_id#10 ASC NULLS FIRST, total_sales#48 ASC NULLS FIRST], [i_item_id#10, total_sales#48] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (68) ++- * Project (67) + +- * Filter (66) + +- * ColumnarToRow (65) + +- CometScan parquet spark_catalog.default.date_dim (64) + + +(64) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#6, d_year#49, d_moy#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,9), IsNotNull(d_date_sk)] +ReadSchema: struct + +(65) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] + +(66) Filter [codegen id : 1] +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#50)) AND (d_year#49 = 1998)) AND (d_moy#50 = 9)) AND isnotnull(d_date_sk#6)) + +(67) Project [codegen id : 1] +Output [1]: [d_date_sk#6] +Input [3]: [d_date_sk#6, d_year#49, d_moy#50] + +(68) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 29 Hosting Expression = cs_sold_date_sk#20 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 44 Hosting Expression = ws_sold_date_sk#33 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/simplified.txt new file mode 100644 index 000000000..0af0fd412 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/simplified.txt @@ -0,0 +1,105 @@ +TakeOrderedAndProject [i_item_id,total_sales] + WholeStageCodegen (20) + HashAggregate [i_item_id,sum,isEmpty] [sum(total_sales),total_sales,sum,isEmpty] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (19) + HashAggregate [i_item_id,total_sales] [sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (6) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ss_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #2 + WholeStageCodegen (5) + HashAggregate [i_item_id,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_item_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_addr_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [ca_address_sk] + Filter [ca_gmt_offset,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + BroadcastHashJoin [i_item_id,i_item_id] + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + Project [i_item_id] + Filter [i_category] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_id,i_category] + WholeStageCodegen (12) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #7 + WholeStageCodegen (11) + HashAggregate [i_item_id,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_item_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_bill_addr_sk,ca_address_sk] + Project [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Filter [cs_bill_addr_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 + WholeStageCodegen (18) + HashAggregate [i_item_id,sum] [sum(UnscaledValue(ws_ext_sales_price)),total_sales,sum] + InputAdapter + Exchange [i_item_id] #8 + WholeStageCodegen (17) + HashAggregate [i_item_id,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_item_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] + Project [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_bill_addr_sk,ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [ca_address_sk] #4 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/explain.txt new file mode 100644 index 000000000..b70ffc460 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/explain.txt @@ -0,0 +1,417 @@ +== Physical Plan == +* Project (67) ++- * BroadcastNestedLoopJoin Inner BuildRight (66) + :- * HashAggregate (43) + : +- Exchange (42) + : +- * HashAggregate (41) + : +- * Project (40) + : +- * BroadcastHashJoin Inner BuildRight (39) + : :- * Project (33) + : : +- * BroadcastHashJoin Inner BuildRight (32) + : : :- * Project (26) + : : : +- * BroadcastHashJoin Inner BuildRight (25) + : : : :- * Project (20) + : : : : +- * BroadcastHashJoin Inner BuildRight (19) + : : : : :- * Project (17) + : : : : : +- * BroadcastHashJoin Inner BuildRight (16) + : : : : : :- * Project (10) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : : : :- * Filter (3) + : : : : : : : +- * ColumnarToRow (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- BroadcastExchange (8) + : : : : : : +- * Project (7) + : : : : : : +- * Filter (6) + : : : : : : +- * ColumnarToRow (5) + : : : : : : +- CometScan parquet spark_catalog.default.store (4) + : : : : : +- BroadcastExchange (15) + : : : : : +- * Project (14) + : : : : : +- * Filter (13) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometScan parquet spark_catalog.default.promotion (11) + : : : : +- ReusedExchange (18) + : : : +- BroadcastExchange (24) + : : : +- * Filter (23) + : : : +- * ColumnarToRow (22) + : : : +- CometScan parquet spark_catalog.default.customer (21) + : : +- BroadcastExchange (31) + : : +- * Project (30) + : : +- * Filter (29) + : : +- * ColumnarToRow (28) + : : +- CometScan parquet spark_catalog.default.customer_address (27) + : +- BroadcastExchange (38) + : +- * Project (37) + : +- * Filter (36) + : +- * ColumnarToRow (35) + : +- CometScan parquet spark_catalog.default.item (34) + +- BroadcastExchange (65) + +- * HashAggregate (64) + +- Exchange (63) + +- * HashAggregate (62) + +- * Project (61) + +- * BroadcastHashJoin Inner BuildRight (60) + :- * Project (58) + : +- * BroadcastHashJoin Inner BuildRight (57) + : :- * Project (55) + : : +- * BroadcastHashJoin Inner BuildRight (54) + : : :- * Project (52) + : : : +- * BroadcastHashJoin Inner BuildRight (51) + : : : :- * Project (49) + : : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : : :- * Filter (46) + : : : : : +- * ColumnarToRow (45) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (44) + : : : : +- ReusedExchange (47) + : : : +- ReusedExchange (50) + : : +- ReusedExchange (53) + : +- ReusedExchange (56) + +- ReusedExchange (59) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 7] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] + +(3) Filter [codegen id : 7] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_store_sk#3) AND isnotnull(ss_promo_sk#4)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_item_sk#1)) + +(4) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#8, s_gmt_offset#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_gmt_offset), EqualTo(s_gmt_offset,-5.00), IsNotNull(s_store_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [s_store_sk#8, s_gmt_offset#9] + +(6) Filter [codegen id : 1] +Input [2]: [s_store_sk#8, s_gmt_offset#9] +Condition : ((isnotnull(s_gmt_offset#9) AND (s_gmt_offset#9 = -5.00)) AND isnotnull(s_store_sk#8)) + +(7) Project [codegen id : 1] +Output [1]: [s_store_sk#8] +Input [2]: [s_store_sk#8, s_gmt_offset#9] + +(8) BroadcastExchange +Input [1]: [s_store_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#8] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 7] +Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6, s_store_sk#8] + +(11) Scan parquet spark_catalog.default.promotion +Output [4]: [p_promo_sk#10, p_channel_dmail#11, p_channel_email#12, p_channel_tv#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [Or(Or(EqualTo(p_channel_dmail,Y),EqualTo(p_channel_email,Y)),EqualTo(p_channel_tv,Y)), IsNotNull(p_promo_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [4]: [p_promo_sk#10, p_channel_dmail#11, p_channel_email#12, p_channel_tv#13] + +(13) Filter [codegen id : 2] +Input [4]: [p_promo_sk#10, p_channel_dmail#11, p_channel_email#12, p_channel_tv#13] +Condition : ((((p_channel_dmail#11 = Y) OR (p_channel_email#12 = Y)) OR (p_channel_tv#13 = Y)) AND isnotnull(p_promo_sk#10)) + +(14) Project [codegen id : 2] +Output [1]: [p_promo_sk#10] +Input [4]: [p_promo_sk#10, p_channel_dmail#11, p_channel_email#12, p_channel_tv#13] + +(15) BroadcastExchange +Input [1]: [p_promo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_promo_sk#4] +Right keys [1]: [p_promo_sk#10] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 7] +Output [4]: [ss_item_sk#1, ss_customer_sk#2, ss_ext_sales_price#5, ss_sold_date_sk#6] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6, p_promo_sk#10] + +(18) ReusedExchange [Reuses operator id: 72] +Output [1]: [d_date_sk#14] + +(19) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_sold_date_sk#6] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 7] +Output [3]: [ss_item_sk#1, ss_customer_sk#2, ss_ext_sales_price#5] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ext_sales_price#5, ss_sold_date_sk#6, d_date_sk#14] + +(21) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#15, c_current_addr_sk#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(22) ColumnarToRow [codegen id : 4] +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] + +(23) Filter [codegen id : 4] +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] +Condition : (isnotnull(c_customer_sk#15) AND isnotnull(c_current_addr_sk#16)) + +(24) BroadcastExchange +Input [2]: [c_customer_sk#15, c_current_addr_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#15] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 7] +Output [3]: [ss_item_sk#1, ss_ext_sales_price#5, c_current_addr_sk#16] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ext_sales_price#5, c_customer_sk#15, c_current_addr_sk#16] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#17, ca_gmt_offset#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) ColumnarToRow [codegen id : 5] +Input [2]: [ca_address_sk#17, ca_gmt_offset#18] + +(29) Filter [codegen id : 5] +Input [2]: [ca_address_sk#17, ca_gmt_offset#18] +Condition : ((isnotnull(ca_gmt_offset#18) AND (ca_gmt_offset#18 = -5.00)) AND isnotnull(ca_address_sk#17)) + +(30) Project [codegen id : 5] +Output [1]: [ca_address_sk#17] +Input [2]: [ca_address_sk#17, ca_gmt_offset#18] + +(31) BroadcastExchange +Input [1]: [ca_address_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(32) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_addr_sk#16] +Right keys [1]: [ca_address_sk#17] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 7] +Output [2]: [ss_item_sk#1, ss_ext_sales_price#5] +Input [4]: [ss_item_sk#1, ss_ext_sales_price#5, c_current_addr_sk#16, ca_address_sk#17] + +(34) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#19, i_category#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Jewelry ), IsNotNull(i_item_sk)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 6] +Input [2]: [i_item_sk#19, i_category#20] + +(36) Filter [codegen id : 6] +Input [2]: [i_item_sk#19, i_category#20] +Condition : ((isnotnull(i_category#20) AND (i_category#20 = Jewelry )) AND isnotnull(i_item_sk#19)) + +(37) Project [codegen id : 6] +Output [1]: [i_item_sk#19] +Input [2]: [i_item_sk#19, i_category#20] + +(38) BroadcastExchange +Input [1]: [i_item_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(39) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#19] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 7] +Output [1]: [ss_ext_sales_price#5] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#5, i_item_sk#19] + +(41) HashAggregate [codegen id : 7] +Input [1]: [ss_ext_sales_price#5] +Keys: [] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum#21] +Results [1]: [sum#22] + +(42) Exchange +Input [1]: [sum#22] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] + +(43) HashAggregate [codegen id : 15] +Input [1]: [sum#22] +Keys: [] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#5))#23] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#23,17,2) AS promotions#24] + +(44) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#25, ss_customer_sk#26, ss_store_sk#27, ss_ext_sales_price#28, ss_sold_date_sk#29] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#29), dynamicpruningexpression(ss_sold_date_sk#29 IN dynamicpruning#30)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 13] +Input [5]: [ss_item_sk#25, ss_customer_sk#26, ss_store_sk#27, ss_ext_sales_price#28, ss_sold_date_sk#29] + +(46) Filter [codegen id : 13] +Input [5]: [ss_item_sk#25, ss_customer_sk#26, ss_store_sk#27, ss_ext_sales_price#28, ss_sold_date_sk#29] +Condition : ((isnotnull(ss_store_sk#27) AND isnotnull(ss_customer_sk#26)) AND isnotnull(ss_item_sk#25)) + +(47) ReusedExchange [Reuses operator id: 8] +Output [1]: [s_store_sk#31] + +(48) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_store_sk#27] +Right keys [1]: [s_store_sk#31] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 13] +Output [4]: [ss_item_sk#25, ss_customer_sk#26, ss_ext_sales_price#28, ss_sold_date_sk#29] +Input [6]: [ss_item_sk#25, ss_customer_sk#26, ss_store_sk#27, ss_ext_sales_price#28, ss_sold_date_sk#29, s_store_sk#31] + +(50) ReusedExchange [Reuses operator id: 72] +Output [1]: [d_date_sk#32] + +(51) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_sold_date_sk#29] +Right keys [1]: [d_date_sk#32] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 13] +Output [3]: [ss_item_sk#25, ss_customer_sk#26, ss_ext_sales_price#28] +Input [5]: [ss_item_sk#25, ss_customer_sk#26, ss_ext_sales_price#28, ss_sold_date_sk#29, d_date_sk#32] + +(53) ReusedExchange [Reuses operator id: 24] +Output [2]: [c_customer_sk#33, c_current_addr_sk#34] + +(54) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_customer_sk#26] +Right keys [1]: [c_customer_sk#33] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 13] +Output [3]: [ss_item_sk#25, ss_ext_sales_price#28, c_current_addr_sk#34] +Input [5]: [ss_item_sk#25, ss_customer_sk#26, ss_ext_sales_price#28, c_customer_sk#33, c_current_addr_sk#34] + +(56) ReusedExchange [Reuses operator id: 31] +Output [1]: [ca_address_sk#35] + +(57) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [c_current_addr_sk#34] +Right keys [1]: [ca_address_sk#35] +Join type: Inner +Join condition: None + +(58) Project [codegen id : 13] +Output [2]: [ss_item_sk#25, ss_ext_sales_price#28] +Input [4]: [ss_item_sk#25, ss_ext_sales_price#28, c_current_addr_sk#34, ca_address_sk#35] + +(59) ReusedExchange [Reuses operator id: 38] +Output [1]: [i_item_sk#36] + +(60) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_item_sk#25] +Right keys [1]: [i_item_sk#36] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 13] +Output [1]: [ss_ext_sales_price#28] +Input [3]: [ss_item_sk#25, ss_ext_sales_price#28, i_item_sk#36] + +(62) HashAggregate [codegen id : 13] +Input [1]: [ss_ext_sales_price#28] +Keys: [] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#28))] +Aggregate Attributes [1]: [sum#37] +Results [1]: [sum#38] + +(63) Exchange +Input [1]: [sum#38] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(64) HashAggregate [codegen id : 14] +Input [1]: [sum#38] +Keys: [] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#28))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#28))#39] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#28))#39,17,2) AS total#40] + +(65) BroadcastExchange +Input [1]: [total#40] +Arguments: IdentityBroadcastMode, [plan_id=8] + +(66) BroadcastNestedLoopJoin [codegen id : 15] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 15] +Output [3]: [promotions#24, total#40, ((cast(promotions#24 as decimal(15,4)) / cast(total#40 as decimal(15,4))) * 100) AS ((CAST(promotions AS DECIMAL(15,4)) / CAST(total AS DECIMAL(15,4))) * 100)#41] +Input [2]: [promotions#24, total#40] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (72) ++- * Project (71) + +- * Filter (70) + +- * ColumnarToRow (69) + +- CometScan parquet spark_catalog.default.date_dim (68) + + +(68) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#14, d_year#42, d_moy#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,11), IsNotNull(d_date_sk)] +ReadSchema: struct + +(69) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#14, d_year#42, d_moy#43] + +(70) Filter [codegen id : 1] +Input [3]: [d_date_sk#14, d_year#42, d_moy#43] +Condition : ((((isnotnull(d_year#42) AND isnotnull(d_moy#43)) AND (d_year#42 = 1998)) AND (d_moy#43 = 11)) AND isnotnull(d_date_sk#14)) + +(71) Project [codegen id : 1] +Output [1]: [d_date_sk#14] +Input [3]: [d_date_sk#14, d_year#42, d_moy#43] + +(72) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 44 Hosting Expression = ss_sold_date_sk#29 IN dynamicpruning#7 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/simplified.txt new file mode 100644 index 000000000..2272a80ba --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/simplified.txt @@ -0,0 +1,106 @@ +WholeStageCodegen (15) + Project [promotions,total] + BroadcastNestedLoopJoin + HashAggregate [sum] [sum(UnscaledValue(ss_ext_sales_price)),promotions,sum] + InputAdapter + Exchange #1 + WholeStageCodegen (7) + HashAggregate [ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_ext_sales_price,c_current_addr_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_ext_sales_price,ss_sold_date_sk] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_item_sk,ss_customer_sk,ss_promo_sk,ss_ext_sales_price,ss_sold_date_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Filter [ss_store_sk,ss_promo_sk,ss_customer_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [s_store_sk] + Filter [s_gmt_offset,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_gmt_offset] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [p_promo_sk] + Filter [p_channel_dmail,p_channel_email,p_channel_tv,p_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_dmail,p_channel_email,p_channel_tv] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Filter [c_customer_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Project [ca_address_sk] + Filter [ca_gmt_offset,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + Project [i_item_sk] + Filter [i_category,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_category] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (14) + HashAggregate [sum] [sum(UnscaledValue(ss_ext_sales_price)),total,sum] + InputAdapter + Exchange #9 + WholeStageCodegen (13) + HashAggregate [ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_ext_sales_price] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_ext_sales_price,c_current_addr_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_ext_sales_price,ss_sold_date_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Filter [ss_store_sk,ss_customer_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [s_store_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [c_customer_sk,c_current_addr_sk] #5 + InputAdapter + ReusedExchange [ca_address_sk] #6 + InputAdapter + ReusedExchange [i_item_sk] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/explain.txt new file mode 100644 index 000000000..55423bcd1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/explain.txt @@ -0,0 +1,187 @@ +== Physical Plan == +TakeOrderedAndProject (32) ++- * HashAggregate (31) + +- Exchange (30) + +- * HashAggregate (29) + +- * Project (28) + +- * BroadcastHashJoin Inner BuildRight (27) + :- * Project (21) + : +- * BroadcastHashJoin Inner BuildRight (20) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.warehouse (4) + : : +- BroadcastExchange (13) + : : +- * Filter (12) + : : +- * ColumnarToRow (11) + : : +- CometScan parquet spark_catalog.default.ship_mode (10) + : +- BroadcastExchange (19) + : +- * Filter (18) + : +- * ColumnarToRow (17) + : +- CometScan parquet spark_catalog.default.web_site (16) + +- BroadcastExchange (26) + +- * Project (25) + +- * Filter (24) + +- * ColumnarToRow (23) + +- CometScan parquet spark_catalog.default.date_dim (22) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_warehouse_sk#4, ws_sold_date_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_warehouse_sk), IsNotNull(ws_ship_mode_sk), IsNotNull(ws_web_site_sk), IsNotNull(ws_ship_date_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_warehouse_sk#4, ws_sold_date_sk#5] + +(3) Filter [codegen id : 5] +Input [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_warehouse_sk#4, ws_sold_date_sk#5] +Condition : (((isnotnull(ws_warehouse_sk#4) AND isnotnull(ws_ship_mode_sk#3)) AND isnotnull(ws_web_site_sk#2)) AND isnotnull(ws_ship_date_sk#1)) + +(4) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] + +(6) Filter [codegen id : 1] +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Condition : isnotnull(w_warehouse_sk#6) + +(7) BroadcastExchange +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_warehouse_sk#4] +Right keys [1]: [w_warehouse_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_sold_date_sk#5, w_warehouse_name#7] +Input [7]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_warehouse_sk#4, ws_sold_date_sk#5, w_warehouse_sk#6, w_warehouse_name#7] + +(10) Scan parquet spark_catalog.default.ship_mode +Output [2]: [sm_ship_mode_sk#8, sm_type#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/ship_mode] +PushedFilters: [IsNotNull(sm_ship_mode_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [2]: [sm_ship_mode_sk#8, sm_type#9] + +(12) Filter [codegen id : 2] +Input [2]: [sm_ship_mode_sk#8, sm_type#9] +Condition : isnotnull(sm_ship_mode_sk#8) + +(13) BroadcastExchange +Input [2]: [sm_ship_mode_sk#8, sm_type#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_ship_mode_sk#3] +Right keys [1]: [sm_ship_mode_sk#8] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 5] +Output [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_sold_date_sk#5, w_warehouse_name#7, sm_type#9] +Input [7]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_sold_date_sk#5, w_warehouse_name#7, sm_ship_mode_sk#8, sm_type#9] + +(16) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#10, web_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_site_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 3] +Input [2]: [web_site_sk#10, web_name#11] + +(18) Filter [codegen id : 3] +Input [2]: [web_site_sk#10, web_name#11] +Condition : isnotnull(web_site_sk#10) + +(19) BroadcastExchange +Input [2]: [web_site_sk#10, web_name#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_web_site_sk#2] +Right keys [1]: [web_site_sk#10] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 5] +Output [5]: [ws_ship_date_sk#1, ws_sold_date_sk#5, w_warehouse_name#7, sm_type#9, web_name#11] +Input [7]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_sold_date_sk#5, w_warehouse_name#7, sm_type#9, web_site_sk#10, web_name#11] + +(22) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#12, d_month_seq#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 4] +Input [2]: [d_date_sk#12, d_month_seq#13] + +(24) Filter [codegen id : 4] +Input [2]: [d_date_sk#12, d_month_seq#13] +Condition : (((isnotnull(d_month_seq#13) AND (d_month_seq#13 >= 1200)) AND (d_month_seq#13 <= 1211)) AND isnotnull(d_date_sk#12)) + +(25) Project [codegen id : 4] +Output [1]: [d_date_sk#12] +Input [2]: [d_date_sk#12, d_month_seq#13] + +(26) BroadcastExchange +Input [1]: [d_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(27) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_ship_date_sk#1] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 5] +Output [5]: [ws_ship_date_sk#1, ws_sold_date_sk#5, sm_type#9, web_name#11, substr(w_warehouse_name#7, 1, 20) AS _groupingexpression#14] +Input [6]: [ws_ship_date_sk#1, ws_sold_date_sk#5, w_warehouse_name#7, sm_type#9, web_name#11, d_date_sk#12] + +(29) HashAggregate [codegen id : 5] +Input [5]: [ws_ship_date_sk#1, ws_sold_date_sk#5, sm_type#9, web_name#11, _groupingexpression#14] +Keys [3]: [_groupingexpression#14, sm_type#9, web_name#11] +Functions [5]: [partial_sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 30) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 60) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 90) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum#15, sum#16, sum#17, sum#18, sum#19] +Results [8]: [_groupingexpression#14, sm_type#9, web_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] + +(30) Exchange +Input [8]: [_groupingexpression#14, sm_type#9, web_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] +Arguments: hashpartitioning(_groupingexpression#14, sm_type#9, web_name#11, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(31) HashAggregate [codegen id : 6] +Input [8]: [_groupingexpression#14, sm_type#9, web_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] +Keys [3]: [_groupingexpression#14, sm_type#9, web_name#11] +Functions [5]: [sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 30) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 60) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 90) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#25, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 30) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#26, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 60) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#27, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 90) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#28, sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#29] +Results [8]: [_groupingexpression#14 AS substr(w_warehouse_name, 1, 20)#30, sm_type#9, web_name#11, sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#25 AS 30 days #31, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 30) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#26 AS 31 - 60 days #32, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 60) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#27 AS 61 - 90 days #33, sum(CASE WHEN (((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 90) AND ((ws_ship_date_sk#1 - ws_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#28 AS 91 - 120 days #34, sum(CASE WHEN ((ws_ship_date_sk#1 - ws_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#29 AS >120 days #35] + +(32) TakeOrderedAndProject +Input [8]: [substr(w_warehouse_name, 1, 20)#30, sm_type#9, web_name#11, 30 days #31, 31 - 60 days #32, 61 - 90 days #33, 91 - 120 days #34, >120 days #35] +Arguments: 100, [substr(w_warehouse_name, 1, 20)#30 ASC NULLS FIRST, sm_type#9 ASC NULLS FIRST, web_name#11 ASC NULLS FIRST], [substr(w_warehouse_name, 1, 20)#30, sm_type#9, web_name#11, 30 days #31, 31 - 60 days #32, 61 - 90 days #33, 91 - 120 days #34, >120 days #35] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/simplified.txt new file mode 100644 index 000000000..a49361cb6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/simplified.txt @@ -0,0 +1,48 @@ +TakeOrderedAndProject [substr(w_warehouse_name, 1, 20),sm_type,web_name,30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ] + WholeStageCodegen (6) + HashAggregate [_groupingexpression,sm_type,web_name,sum,sum,sum,sum,sum] [sum(CASE WHEN ((ws_ship_date_sk - ws_sold_date_sk) <= 30) THEN 1 ELSE 0 END),sum(CASE WHEN (((ws_ship_date_sk - ws_sold_date_sk) > 30) AND ((ws_ship_date_sk - ws_sold_date_sk) <= 60)) THEN 1 ELSE 0 END),sum(CASE WHEN (((ws_ship_date_sk - ws_sold_date_sk) > 60) AND ((ws_ship_date_sk - ws_sold_date_sk) <= 90)) THEN 1 ELSE 0 END),sum(CASE WHEN (((ws_ship_date_sk - ws_sold_date_sk) > 90) AND ((ws_ship_date_sk - ws_sold_date_sk) <= 120)) THEN 1 ELSE 0 END),sum(CASE WHEN ((ws_ship_date_sk - ws_sold_date_sk) > 120) THEN 1 ELSE 0 END),substr(w_warehouse_name, 1, 20),30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ,sum,sum,sum,sum,sum] + InputAdapter + Exchange [_groupingexpression,sm_type,web_name] #1 + WholeStageCodegen (5) + HashAggregate [_groupingexpression,sm_type,web_name,ws_ship_date_sk,ws_sold_date_sk] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [ws_ship_date_sk,ws_sold_date_sk,sm_type,web_name,w_warehouse_name] + BroadcastHashJoin [ws_ship_date_sk,d_date_sk] + Project [ws_ship_date_sk,ws_sold_date_sk,w_warehouse_name,sm_type,web_name] + BroadcastHashJoin [ws_web_site_sk,web_site_sk] + Project [ws_ship_date_sk,ws_web_site_sk,ws_sold_date_sk,w_warehouse_name,sm_type] + BroadcastHashJoin [ws_ship_mode_sk,sm_ship_mode_sk] + Project [ws_ship_date_sk,ws_web_site_sk,ws_ship_mode_sk,ws_sold_date_sk,w_warehouse_name] + BroadcastHashJoin [ws_warehouse_sk,w_warehouse_sk] + Filter [ws_warehouse_sk,ws_ship_mode_sk,ws_web_site_sk,ws_ship_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_ship_date_sk,ws_web_site_sk,ws_ship_mode_sk,ws_warehouse_sk,ws_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [sm_ship_mode_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.ship_mode [sm_ship_mode_sk,sm_type] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Filter [web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/explain.txt new file mode 100644 index 000000000..78baf2df8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/explain.txt @@ -0,0 +1,194 @@ +== Physical Plan == +TakeOrderedAndProject (28) ++- * Project (27) + +- * Filter (26) + +- Window (25) + +- * Sort (24) + +- Exchange (23) + +- * HashAggregate (22) + +- Exchange (21) + +- * HashAggregate (20) + +- * Project (19) + +- * BroadcastHashJoin Inner BuildRight (18) + :- * Project (13) + : +- * BroadcastHashJoin Inner BuildRight (12) + : :- * Project (10) + : : +- * BroadcastHashJoin Inner BuildRight (9) + : : :- * Project (4) + : : : +- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.item (1) + : : +- BroadcastExchange (8) + : : +- * Filter (7) + : : +- * ColumnarToRow (6) + : : +- CometScan parquet spark_catalog.default.store_sales (5) + : +- ReusedExchange (11) + +- BroadcastExchange (17) + +- * Filter (16) + +- * ColumnarToRow (15) + +- CometScan parquet spark_catalog.default.store (14) + + +(1) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manager_id#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [Or(And(And(In(i_category, [Books ,Children ,Electronics ]),In(i_class, [personal ,portable ,refernece ,self-help ])),In(i_brand, [exportiunivamalg #6 ,scholaramalgamalg #7 ,scholaramalgamalg #8 ,scholaramalgamalg #6 ])),And(And(In(i_category, [Men ,Music ,Women ]),In(i_class, [accessories ,classical ,fragrances ,pants ])),In(i_brand, [amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ]))), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manager_id#5] + +(3) Filter [codegen id : 4] +Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manager_id#5] +Condition : ((((i_category#4 IN (Books ,Children ,Electronics ) AND i_class#3 IN (personal ,portable ,refernece ,self-help )) AND i_brand#2 IN (scholaramalgamalg #7 ,scholaramalgamalg #8 ,exportiunivamalg #6 ,scholaramalgamalg #6 )) OR ((i_category#4 IN (Women ,Music ,Men ) AND i_class#3 IN (accessories ,classical ,fragrances ,pants )) AND i_brand#2 IN (amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ))) AND isnotnull(i_item_sk#1)) + +(4) Project [codegen id : 4] +Output [2]: [i_item_sk#1, i_manager_id#5] +Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manager_id#5] + +(5) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#13), dynamicpruningexpression(ss_sold_date_sk#13 IN dynamicpruning#14)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] + +(7) Filter [codegen id : 1] +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Condition : (isnotnull(ss_item_sk#10) AND isnotnull(ss_store_sk#11)) + +(8) BroadcastExchange +Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 4] +Output [4]: [i_manager_id#5, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Input [6]: [i_item_sk#1, i_manager_id#5, ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] + +(11) ReusedExchange [Reuses operator id: 33] +Output [2]: [d_date_sk#15, d_moy#16] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#13] +Right keys [1]: [d_date_sk#15] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [4]: [i_manager_id#5, ss_store_sk#11, ss_sales_price#12, d_moy#16] +Input [6]: [i_manager_id#5, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13, d_date_sk#15, d_moy#16] + +(14) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#17] + +(16) Filter [codegen id : 3] +Input [1]: [s_store_sk#17] +Condition : isnotnull(s_store_sk#17) + +(17) BroadcastExchange +Input [1]: [s_store_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#11] +Right keys [1]: [s_store_sk#17] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 4] +Output [3]: [i_manager_id#5, ss_sales_price#12, d_moy#16] +Input [5]: [i_manager_id#5, ss_store_sk#11, ss_sales_price#12, d_moy#16, s_store_sk#17] + +(20) HashAggregate [codegen id : 4] +Input [3]: [i_manager_id#5, ss_sales_price#12, d_moy#16] +Keys [2]: [i_manager_id#5, d_moy#16] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#12))] +Aggregate Attributes [1]: [sum#18] +Results [3]: [i_manager_id#5, d_moy#16, sum#19] + +(21) Exchange +Input [3]: [i_manager_id#5, d_moy#16, sum#19] +Arguments: hashpartitioning(i_manager_id#5, d_moy#16, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [3]: [i_manager_id#5, d_moy#16, sum#19] +Keys [2]: [i_manager_id#5, d_moy#16] +Functions [1]: [sum(UnscaledValue(ss_sales_price#12))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#12))#20] +Results [3]: [i_manager_id#5, MakeDecimal(sum(UnscaledValue(ss_sales_price#12))#20,17,2) AS sum_sales#21, MakeDecimal(sum(UnscaledValue(ss_sales_price#12))#20,17,2) AS _w0#22] + +(23) Exchange +Input [3]: [i_manager_id#5, sum_sales#21, _w0#22] +Arguments: hashpartitioning(i_manager_id#5, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(24) Sort [codegen id : 6] +Input [3]: [i_manager_id#5, sum_sales#21, _w0#22] +Arguments: [i_manager_id#5 ASC NULLS FIRST], false, 0 + +(25) Window +Input [3]: [i_manager_id#5, sum_sales#21, _w0#22] +Arguments: [avg(_w0#22) windowspecdefinition(i_manager_id#5, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#23], [i_manager_id#5] + +(26) Filter [codegen id : 7] +Input [4]: [i_manager_id#5, sum_sales#21, _w0#22, avg_monthly_sales#23] +Condition : CASE WHEN (avg_monthly_sales#23 > 0.000000) THEN ((abs((sum_sales#21 - avg_monthly_sales#23)) / avg_monthly_sales#23) > 0.1000000000000000) ELSE false END + +(27) Project [codegen id : 7] +Output [3]: [i_manager_id#5, sum_sales#21, avg_monthly_sales#23] +Input [4]: [i_manager_id#5, sum_sales#21, _w0#22, avg_monthly_sales#23] + +(28) TakeOrderedAndProject +Input [3]: [i_manager_id#5, sum_sales#21, avg_monthly_sales#23] +Arguments: 100, [i_manager_id#5 ASC NULLS FIRST, avg_monthly_sales#23 ASC NULLS FIRST, sum_sales#21 ASC NULLS FIRST], [i_manager_id#5, sum_sales#21, avg_monthly_sales#23] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 5 Hosting Expression = ss_sold_date_sk#13 IN dynamicpruning#14 +BroadcastExchange (33) ++- * Project (32) + +- * Filter (31) + +- * ColumnarToRow (30) + +- CometScan parquet spark_catalog.default.date_dim (29) + + +(29) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#15, d_month_seq#24, d_moy#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_month_seq, [1200,1201,1202,1203,1204,1205,1206,1207,1208,1209,1210,1211]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#15, d_month_seq#24, d_moy#16] + +(31) Filter [codegen id : 1] +Input [3]: [d_date_sk#15, d_month_seq#24, d_moy#16] +Condition : (d_month_seq#24 INSET 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211 AND isnotnull(d_date_sk#15)) + +(32) Project [codegen id : 1] +Output [2]: [d_date_sk#15, d_moy#16] +Input [3]: [d_date_sk#15, d_month_seq#24, d_moy#16] + +(33) BroadcastExchange +Input [2]: [d_date_sk#15, d_moy#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/simplified.txt new file mode 100644 index 000000000..2520efac5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/simplified.txt @@ -0,0 +1,51 @@ +TakeOrderedAndProject [i_manager_id,avg_monthly_sales,sum_sales] + WholeStageCodegen (7) + Project [i_manager_id,sum_sales,avg_monthly_sales] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_manager_id] + WholeStageCodegen (6) + Sort [i_manager_id] + InputAdapter + Exchange [i_manager_id] #1 + WholeStageCodegen (5) + HashAggregate [i_manager_id,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_manager_id,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_manager_id,d_moy,ss_sales_price] [sum,sum] + Project [i_manager_id,ss_sales_price,d_moy] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [i_manager_id,ss_store_sk,ss_sales_price,d_moy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [i_manager_id,ss_store_sk,ss_sales_price,ss_sold_date_sk] + BroadcastHashJoin [i_item_sk,ss_item_sk] + Project [i_item_sk,i_manager_id] + Filter [i_category,i_class,i_brand,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_manager_id] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [ss_item_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk,d_moy] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/explain.txt new file mode 100644 index 000000000..b4a82aa37 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/explain.txt @@ -0,0 +1,1074 @@ +== Physical Plan == +* Sort (183) ++- Exchange (182) + +- * Project (181) + +- * SortMergeJoin Inner (180) + :- * Sort (111) + : +- Exchange (110) + : +- * HashAggregate (109) + : +- * HashAggregate (108) + : +- * Project (107) + : +- * BroadcastHashJoin Inner BuildRight (106) + : :- * Project (100) + : : +- * BroadcastHashJoin Inner BuildRight (99) + : : :- * Project (97) + : : : +- * BroadcastHashJoin Inner BuildRight (96) + : : : :- * Project (91) + : : : : +- * BroadcastHashJoin Inner BuildRight (90) + : : : : :- * Project (88) + : : : : : +- * BroadcastHashJoin Inner BuildRight (87) + : : : : : :- * Project (82) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (81) + : : : : : : :- * Project (79) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (78) + : : : : : : : :- * Project (73) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (72) + : : : : : : : : :- * Project (67) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (66) + : : : : : : : : : :- * Project (64) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (63) + : : : : : : : : : : :- * Project (58) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (57) + : : : : : : : : : : : :- * Project (55) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : : : : : : : : : : :- * Project (49) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : : : : : : : : : : : :- * Project (43) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (42) + : : : : : : : : : : : : : : :- * Project (37) + : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (36) + : : : : : : : : : : : : : : : :- * Project (34) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (33) + : : : : : : : : : : : : : : : : :- * Sort (12) + : : : : : : : : : : : : : : : : : +- Exchange (11) + : : : : : : : : : : : : : : : : : +- * Project (10) + : : : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildLeft (9) + : : : : : : : : : : : : : : : : : :- BroadcastExchange (4) + : : : : : : : : : : : : : : : : : : +- * Filter (3) + : : : : : : : : : : : : : : : : : : +- * ColumnarToRow (2) + : : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : : : : : : : : : : : : +- * Project (8) + : : : : : : : : : : : : : : : : : +- * Filter (7) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (6) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (5) + : : : : : : : : : : : : : : : : +- * Sort (32) + : : : : : : : : : : : : : : : : +- * Project (31) + : : : : : : : : : : : : : : : : +- * Filter (30) + : : : : : : : : : : : : : : : : +- * HashAggregate (29) + : : : : : : : : : : : : : : : : +- Exchange (28) + : : : : : : : : : : : : : : : : +- * HashAggregate (27) + : : : : : : : : : : : : : : : : +- * Project (26) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (25) + : : : : : : : : : : : : : : : : :- * Sort (18) + : : : : : : : : : : : : : : : : : +- Exchange (17) + : : : : : : : : : : : : : : : : : +- * Project (16) + : : : : : : : : : : : : : : : : : +- * Filter (15) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (14) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) + : : : : : : : : : : : : : : : : +- * Sort (24) + : : : : : : : : : : : : : : : : +- Exchange (23) + : : : : : : : : : : : : : : : : +- * Project (22) + : : : : : : : : : : : : : : : : +- * Filter (21) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (20) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (19) + : : : : : : : : : : : : : : : +- ReusedExchange (35) + : : : : : : : : : : : : : : +- BroadcastExchange (41) + : : : : : : : : : : : : : : +- * Filter (40) + : : : : : : : : : : : : : : +- * ColumnarToRow (39) + : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store (38) + : : : : : : : : : : : : : +- BroadcastExchange (47) + : : : : : : : : : : : : : +- * Filter (46) + : : : : : : : : : : : : : +- * ColumnarToRow (45) + : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer (44) + : : : : : : : : : : : : +- BroadcastExchange (53) + : : : : : : : : : : : : +- * Filter (52) + : : : : : : : : : : : : +- * ColumnarToRow (51) + : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.date_dim (50) + : : : : : : : : : : : +- ReusedExchange (56) + : : : : : : : : : : +- BroadcastExchange (62) + : : : : : : : : : : +- * Filter (61) + : : : : : : : : : : +- * ColumnarToRow (60) + : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (59) + : : : : : : : : : +- ReusedExchange (65) + : : : : : : : : +- BroadcastExchange (71) + : : : : : : : : +- * Filter (70) + : : : : : : : : +- * ColumnarToRow (69) + : : : : : : : : +- CometScan parquet spark_catalog.default.promotion (68) + : : : : : : : +- BroadcastExchange (77) + : : : : : : : +- * Filter (76) + : : : : : : : +- * ColumnarToRow (75) + : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (74) + : : : : : : +- ReusedExchange (80) + : : : : : +- BroadcastExchange (86) + : : : : : +- * Filter (85) + : : : : : +- * ColumnarToRow (84) + : : : : : +- CometScan parquet spark_catalog.default.customer_address (83) + : : : : +- ReusedExchange (89) + : : : +- BroadcastExchange (95) + : : : +- * Filter (94) + : : : +- * ColumnarToRow (93) + : : : +- CometScan parquet spark_catalog.default.income_band (92) + : : +- ReusedExchange (98) + : +- BroadcastExchange (105) + : +- * Project (104) + : +- * Filter (103) + : +- * ColumnarToRow (102) + : +- CometScan parquet spark_catalog.default.item (101) + +- * Sort (179) + +- Exchange (178) + +- * HashAggregate (177) + +- * HashAggregate (176) + +- * Project (175) + +- * BroadcastHashJoin Inner BuildRight (174) + :- * Project (172) + : +- * BroadcastHashJoin Inner BuildRight (171) + : :- * Project (169) + : : +- * BroadcastHashJoin Inner BuildRight (168) + : : :- * Project (166) + : : : +- * BroadcastHashJoin Inner BuildRight (165) + : : : :- * Project (163) + : : : : +- * BroadcastHashJoin Inner BuildRight (162) + : : : : :- * Project (160) + : : : : : +- * BroadcastHashJoin Inner BuildRight (159) + : : : : : :- * Project (157) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (156) + : : : : : : :- * Project (154) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (153) + : : : : : : : :- * Project (151) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (150) + : : : : : : : : :- * Project (148) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (147) + : : : : : : : : : :- * Project (145) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (144) + : : : : : : : : : : :- * Project (142) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (141) + : : : : : : : : : : : :- * Project (139) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (138) + : : : : : : : : : : : : :- * Project (136) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (135) + : : : : : : : : : : : : : :- * Project (133) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (132) + : : : : : : : : : : : : : : :- * Project (130) + : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (129) + : : : : : : : : : : : : : : : :- * Sort (123) + : : : : : : : : : : : : : : : : +- Exchange (122) + : : : : : : : : : : : : : : : : +- * Project (121) + : : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildLeft (120) + : : : : : : : : : : : : : : : : :- BroadcastExchange (115) + : : : : : : : : : : : : : : : : : +- * Filter (114) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (113) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (112) + : : : : : : : : : : : : : : : : +- * Project (119) + : : : : : : : : : : : : : : : : +- * Filter (118) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (117) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (116) + : : : : : : : : : : : : : : : +- * Sort (128) + : : : : : : : : : : : : : : : +- * Project (127) + : : : : : : : : : : : : : : : +- * Filter (126) + : : : : : : : : : : : : : : : +- * HashAggregate (125) + : : : : : : : : : : : : : : : +- ReusedExchange (124) + : : : : : : : : : : : : : : +- ReusedExchange (131) + : : : : : : : : : : : : : +- ReusedExchange (134) + : : : : : : : : : : : : +- ReusedExchange (137) + : : : : : : : : : : : +- ReusedExchange (140) + : : : : : : : : : : +- ReusedExchange (143) + : : : : : : : : : +- ReusedExchange (146) + : : : : : : : : +- ReusedExchange (149) + : : : : : : : +- ReusedExchange (152) + : : : : : : +- ReusedExchange (155) + : : : : : +- ReusedExchange (158) + : : : : +- ReusedExchange (161) + : : : +- ReusedExchange (164) + : : +- ReusedExchange (167) + : +- ReusedExchange (170) + +- ReusedExchange (173) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_sold_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] + +(3) Filter [codegen id : 1] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Condition : (((((((isnotnull(ss_item_sk#1) AND isnotnull(ss_ticket_number#8)) AND isnotnull(ss_store_sk#6)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_cdemo_sk#3)) AND isnotnull(ss_promo_sk#7)) AND isnotnull(ss_hdemo_sk#4)) AND isnotnull(ss_addr_sk#5)) + +(4) BroadcastExchange +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[7, int, false] as bigint) & 4294967295))),false), [plan_id=1] + +(5) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(6) ColumnarToRow +Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] + +(7) Filter +Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Condition : (isnotnull(sr_item_sk#14) AND isnotnull(sr_ticket_number#15)) + +(8) Project +Output [2]: [sr_item_sk#14, sr_ticket_number#15] +Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] + +(9) BroadcastHashJoin [codegen id : 2] +Left keys [2]: [ss_item_sk#1, ss_ticket_number#8] +Right keys [2]: [sr_item_sk#14, sr_ticket_number#15] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 2] +Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, sr_item_sk#14, sr_ticket_number#15] + +(11) Exchange +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 3] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: [ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(13) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_order_number)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 4] +Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] + +(15) Filter [codegen id : 4] +Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_item_sk#17) AND isnotnull(cs_order_number#18)) + +(16) Project [codegen id : 4] +Output [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] + +(17) Exchange +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +Arguments: hashpartitioning(cs_item_sk#17, cs_order_number#18, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(18) Sort [codegen id : 5] +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +Arguments: [cs_item_sk#17 ASC NULLS FIRST, cs_order_number#18 ASC NULLS FIRST], false, 0 + +(19) Scan parquet spark_catalog.default.catalog_returns +Output [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(20) ColumnarToRow [codegen id : 6] +Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] + +(21) Filter [codegen id : 6] +Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Condition : (isnotnull(cr_item_sk#21) AND isnotnull(cr_order_number#22)) + +(22) Project [codegen id : 6] +Output [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] + +(23) Exchange +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Arguments: hashpartitioning(cr_item_sk#21, cr_order_number#22, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(24) Sort [codegen id : 7] +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Arguments: [cr_item_sk#21 ASC NULLS FIRST, cr_order_number#22 ASC NULLS FIRST], false, 0 + +(25) SortMergeJoin [codegen id : 8] +Left keys [2]: [cs_item_sk#17, cs_order_number#18] +Right keys [2]: [cr_item_sk#21, cr_order_number#22] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 8] +Output [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Input [8]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] + +(27) HashAggregate [codegen id : 8] +Input [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Keys [1]: [cs_item_sk#17] +Functions [2]: [partial_sum(UnscaledValue(cs_ext_list_price#19)), partial_sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] +Aggregate Attributes [3]: [sum#27, sum#28, isEmpty#29] +Results [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] + +(28) Exchange +Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] +Arguments: hashpartitioning(cs_item_sk#17, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(29) HashAggregate [codegen id : 9] +Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] +Keys [1]: [cs_item_sk#17] +Functions [2]: [sum(UnscaledValue(cs_ext_list_price#19)), sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#19))#33, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34] +Results [3]: [cs_item_sk#17, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#19))#33,17,2) AS sale#35, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34 AS refund#36] + +(30) Filter [codegen id : 9] +Input [3]: [cs_item_sk#17, sale#35, refund#36] +Condition : ((isnotnull(sale#35) AND isnotnull(refund#36)) AND (cast(sale#35 as decimal(21,2)) > (2 * refund#36))) + +(31) Project [codegen id : 9] +Output [1]: [cs_item_sk#17] +Input [3]: [cs_item_sk#17, sale#35, refund#36] + +(32) Sort [codegen id : 9] +Input [1]: [cs_item_sk#17] +Arguments: [cs_item_sk#17 ASC NULLS FIRST], false, 0 + +(33) SortMergeJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [cs_item_sk#17] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 25] +Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, cs_item_sk#17] + +(35) ReusedExchange [Reuses operator id: 187] +Output [2]: [d_date_sk#37, d_year#38] + +(36) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_sold_date_sk#12] +Right keys [1]: [d_date_sk#37] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 25] +Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38] +Input [13]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, d_date_sk#37, d_year#38] + +(38) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_zip)] +ReadSchema: struct + +(39) ColumnarToRow [codegen id : 11] +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] + +(40) Filter [codegen id : 11] +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Condition : ((isnotnull(s_store_sk#39) AND isnotnull(s_store_name#40)) AND isnotnull(s_zip#41)) + +(41) BroadcastExchange +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(42) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_store_sk#6] +Right keys [1]: [s_store_sk#39] +Join type: Inner +Join condition: None + +(43) Project [codegen id : 25] +Output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41] +Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_sk#39, s_store_name#40, s_zip#41] + +(44) Scan parquet spark_catalog.default.customer +Output [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_first_sales_date_sk), IsNotNull(c_first_shipto_date_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 12] +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] + +(46) Filter [codegen id : 12] +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Condition : (((((isnotnull(c_customer_sk#42) AND isnotnull(c_first_sales_date_sk#47)) AND isnotnull(c_first_shipto_date_sk#46)) AND isnotnull(c_current_cdemo_sk#43)) AND isnotnull(c_current_hdemo_sk#44)) AND isnotnull(c_current_addr_sk#45)) + +(47) BroadcastExchange +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(48) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#42] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 25] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Input [18]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] + +(50) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#48, d_year#49] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(51) ColumnarToRow [codegen id : 13] +Input [2]: [d_date_sk#48, d_year#49] + +(52) Filter [codegen id : 13] +Input [2]: [d_date_sk#48, d_year#49] +Condition : isnotnull(d_date_sk#48) + +(53) BroadcastExchange +Input [2]: [d_date_sk#48, d_year#49] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(54) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [c_first_sales_date_sk#47] +Right keys [1]: [d_date_sk#48] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 25] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47, d_date_sk#48, d_year#49] + +(56) ReusedExchange [Reuses operator id: 53] +Output [2]: [d_date_sk#50, d_year#51] + +(57) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [c_first_shipto_date_sk#46] +Right keys [1]: [d_date_sk#50] +Join type: Inner +Join condition: None + +(58) Project [codegen id : 25] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49, d_date_sk#50, d_year#51] + +(59) Scan parquet spark_catalog.default.customer_demographics +Output [2]: [cd_demo_sk#52, cd_marital_status#53] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status)] +ReadSchema: struct + +(60) ColumnarToRow [codegen id : 15] +Input [2]: [cd_demo_sk#52, cd_marital_status#53] + +(61) Filter [codegen id : 15] +Input [2]: [cd_demo_sk#52, cd_marital_status#53] +Condition : (isnotnull(cd_demo_sk#52) AND isnotnull(cd_marital_status#53)) + +(62) BroadcastExchange +Input [2]: [cd_demo_sk#52, cd_marital_status#53] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(63) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_cdemo_sk#3] +Right keys [1]: [cd_demo_sk#52] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 25] +Output [16]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_demo_sk#52, cd_marital_status#53] + +(65) ReusedExchange [Reuses operator id: 62] +Output [2]: [cd_demo_sk#54, cd_marital_status#55] + +(66) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [c_current_cdemo_sk#43] +Right keys [1]: [cd_demo_sk#54] +Join type: Inner +Join condition: NOT (cd_marital_status#53 = cd_marital_status#55) + +(67) Project [codegen id : 25] +Output [14]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [18]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53, cd_demo_sk#54, cd_marital_status#55] + +(68) Scan parquet spark_catalog.default.promotion +Output [1]: [p_promo_sk#56] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_promo_sk)] +ReadSchema: struct + +(69) ColumnarToRow [codegen id : 17] +Input [1]: [p_promo_sk#56] + +(70) Filter [codegen id : 17] +Input [1]: [p_promo_sk#56] +Condition : isnotnull(p_promo_sk#56) + +(71) BroadcastExchange +Input [1]: [p_promo_sk#56] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] + +(72) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_promo_sk#7] +Right keys [1]: [p_promo_sk#56] +Join type: Inner +Join condition: None + +(73) Project [codegen id : 25] +Output [13]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, p_promo_sk#56] + +(74) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_demo_sk), IsNotNull(hd_income_band_sk)] +ReadSchema: struct + +(75) ColumnarToRow [codegen id : 18] +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] + +(76) Filter [codegen id : 18] +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Condition : (isnotnull(hd_demo_sk#57) AND isnotnull(hd_income_band_sk#58)) + +(77) BroadcastExchange +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=11] + +(78) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_hdemo_sk#4] +Right keys [1]: [hd_demo_sk#57] +Join type: Inner +Join condition: None + +(79) Project [codegen id : 25] +Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58] +Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_demo_sk#57, hd_income_band_sk#58] + +(80) ReusedExchange [Reuses operator id: 77] +Output [2]: [hd_demo_sk#59, hd_income_band_sk#60] + +(81) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [c_current_hdemo_sk#44] +Right keys [1]: [hd_demo_sk#59] +Join type: Inner +Join condition: None + +(82) Project [codegen id : 25] +Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60] +Input [15]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_demo_sk#59, hd_income_band_sk#60] + +(83) Scan parquet spark_catalog.default.customer_address +Output [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(84) ColumnarToRow [codegen id : 20] +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] + +(85) Filter [codegen id : 20] +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Condition : isnotnull(ca_address_sk#61) + +(86) BroadcastExchange +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +(87) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_addr_sk#5] +Right keys [1]: [ca_address_sk#61] +Join type: Inner +Join condition: None + +(88) Project [codegen id : 25] +Output [16]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Input [18]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] + +(89) ReusedExchange [Reuses operator id: 86] +Output [5]: [ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] + +(90) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [c_current_addr_sk#45] +Right keys [1]: [ca_address_sk#66] +Join type: Inner +Join condition: None + +(91) Project [codegen id : 25] +Output [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [21]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] + +(92) Scan parquet spark_catalog.default.income_band +Output [1]: [ib_income_band_sk#71] +Batched: true +Location [not included in comparison]/{warehouse_dir}/income_band] +PushedFilters: [IsNotNull(ib_income_band_sk)] +ReadSchema: struct + +(93) ColumnarToRow [codegen id : 22] +Input [1]: [ib_income_band_sk#71] + +(94) Filter [codegen id : 22] +Input [1]: [ib_income_band_sk#71] +Condition : isnotnull(ib_income_band_sk#71) + +(95) BroadcastExchange +Input [1]: [ib_income_band_sk#71] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +(96) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [hd_income_band_sk#58] +Right keys [1]: [ib_income_band_sk#71] +Join type: Inner +Join condition: None + +(97) Project [codegen id : 25] +Output [18]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [20]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#71] + +(98) ReusedExchange [Reuses operator id: 95] +Output [1]: [ib_income_band_sk#72] + +(99) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [hd_income_band_sk#60] +Right keys [1]: [ib_income_band_sk#72] +Join type: Inner +Join condition: None + +(100) Project [codegen id : 25] +Output [17]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#72] + +(101) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), In(i_color, [burlywood ,floral ,indian ,medium ,purple ,spring ]), GreaterThanOrEqual(i_current_price,64.00), LessThanOrEqual(i_current_price,74.00), GreaterThanOrEqual(i_current_price,65.00), LessThanOrEqual(i_current_price,79.00), IsNotNull(i_item_sk)] +ReadSchema: struct + +(102) ColumnarToRow [codegen id : 24] +Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] + +(103) Filter [codegen id : 24] +Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Condition : ((((((isnotnull(i_current_price#74) AND i_color#75 IN (purple ,burlywood ,indian ,spring ,floral ,medium )) AND (i_current_price#74 >= 64.00)) AND (i_current_price#74 <= 74.00)) AND (i_current_price#74 >= 65.00)) AND (i_current_price#74 <= 79.00)) AND isnotnull(i_item_sk#73)) + +(104) Project [codegen id : 24] +Output [2]: [i_item_sk#73, i_product_name#76] +Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] + +(105) BroadcastExchange +Input [2]: [i_item_sk#73, i_product_name#76] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] + +(106) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#73] +Join type: Inner +Join condition: None + +(107) Project [codegen id : 25] +Output [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] +Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] + +(108) HashAggregate [codegen id : 25] +Input [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] +Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] +Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#9)), partial_sum(UnscaledValue(ss_list_price#10)), partial_sum(UnscaledValue(ss_coupon_amt#11))] +Aggregate Attributes [4]: [count#77, sum#78, sum#79, sum#80] +Results [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] + +(109) HashAggregate [codegen id : 25] +Input [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] +Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] +Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#9)), sum(UnscaledValue(ss_list_price#10)), sum(UnscaledValue(ss_coupon_amt#11))] +Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#9))#86, sum(UnscaledValue(ss_list_price#10))#87, sum(UnscaledValue(ss_coupon_amt#11))#88] +Results [17]: [i_product_name#76 AS product_name#89, i_item_sk#73 AS item_sk#90, s_store_name#40 AS store_name#91, s_zip#41 AS store_zip#92, ca_street_number#62 AS b_street_number#93, ca_street_name#63 AS b_streen_name#94, ca_city#64 AS b_city#95, ca_zip#65 AS b_zip#96, ca_street_number#67 AS c_street_number#97, ca_street_name#68 AS c_street_name#98, ca_city#69 AS c_city#99, ca_zip#70 AS c_zip#100, d_year#38 AS syear#101, count(1)#85 AS cnt#102, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#9))#86,17,2) AS s1#103, MakeDecimal(sum(UnscaledValue(ss_list_price#10))#87,17,2) AS s2#104, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#11))#88,17,2) AS s3#105] + +(110) Exchange +Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] +Arguments: hashpartitioning(item_sk#90, store_name#91, store_zip#92, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(111) Sort [codegen id : 26] +Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] +Arguments: [item_sk#90 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, store_zip#92 ASC NULLS FIRST], false, 0 + +(112) Scan parquet spark_catalog.default.store_sales +Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#117), dynamicpruningexpression(ss_sold_date_sk#117 IN dynamicpruning#118)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(113) ColumnarToRow [codegen id : 27] +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] + +(114) Filter [codegen id : 27] +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Condition : (((((((isnotnull(ss_item_sk#106) AND isnotnull(ss_ticket_number#113)) AND isnotnull(ss_store_sk#111)) AND isnotnull(ss_customer_sk#107)) AND isnotnull(ss_cdemo_sk#108)) AND isnotnull(ss_promo_sk#112)) AND isnotnull(ss_hdemo_sk#109)) AND isnotnull(ss_addr_sk#110)) + +(115) BroadcastExchange +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[7, int, false] as bigint) & 4294967295))),false), [plan_id=16] + +(116) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(117) ColumnarToRow +Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] + +(118) Filter +Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Condition : (isnotnull(sr_item_sk#119) AND isnotnull(sr_ticket_number#120)) + +(119) Project +Output [2]: [sr_item_sk#119, sr_ticket_number#120] +Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] + +(120) BroadcastHashJoin [codegen id : 28] +Left keys [2]: [ss_item_sk#106, ss_ticket_number#113] +Right keys [2]: [sr_item_sk#119, sr_ticket_number#120] +Join type: Inner +Join condition: None + +(121) Project [codegen id : 28] +Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, sr_item_sk#119, sr_ticket_number#120] + +(122) Exchange +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: hashpartitioning(ss_item_sk#106, 5), ENSURE_REQUIREMENTS, [plan_id=17] + +(123) Sort [codegen id : 29] +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: [ss_item_sk#106 ASC NULLS FIRST], false, 0 + +(124) ReusedExchange [Reuses operator id: 28] +Output [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] + +(125) HashAggregate [codegen id : 35] +Input [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] +Keys [1]: [cs_item_sk#122] +Functions [2]: [sum(UnscaledValue(cs_ext_list_price#126)), sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#126))#33, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34] +Results [3]: [cs_item_sk#122, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#126))#33,17,2) AS sale#130, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34 AS refund#131] + +(126) Filter [codegen id : 35] +Input [3]: [cs_item_sk#122, sale#130, refund#131] +Condition : ((isnotnull(sale#130) AND isnotnull(refund#131)) AND (cast(sale#130 as decimal(21,2)) > (2 * refund#131))) + +(127) Project [codegen id : 35] +Output [1]: [cs_item_sk#122] +Input [3]: [cs_item_sk#122, sale#130, refund#131] + +(128) Sort [codegen id : 35] +Input [1]: [cs_item_sk#122] +Arguments: [cs_item_sk#122 ASC NULLS FIRST], false, 0 + +(129) SortMergeJoin [codegen id : 51] +Left keys [1]: [ss_item_sk#106] +Right keys [1]: [cs_item_sk#122] +Join type: Inner +Join condition: None + +(130) Project [codegen id : 51] +Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, cs_item_sk#122] + +(131) ReusedExchange [Reuses operator id: 191] +Output [2]: [d_date_sk#132, d_year#133] + +(132) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_sold_date_sk#117] +Right keys [1]: [d_date_sk#132] +Join type: Inner +Join condition: None + +(133) Project [codegen id : 51] +Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133] +Input [13]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, d_date_sk#132, d_year#133] + +(134) ReusedExchange [Reuses operator id: 41] +Output [3]: [s_store_sk#134, s_store_name#135, s_zip#136] + +(135) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_store_sk#111] +Right keys [1]: [s_store_sk#134] +Join type: Inner +Join condition: None + +(136) Project [codegen id : 51] +Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136] +Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_sk#134, s_store_name#135, s_zip#136] + +(137) ReusedExchange [Reuses operator id: 47] +Output [6]: [c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] + +(138) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_customer_sk#107] +Right keys [1]: [c_customer_sk#137] +Join type: Inner +Join condition: None + +(139) Project [codegen id : 51] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] +Input [18]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] + +(140) ReusedExchange [Reuses operator id: 53] +Output [2]: [d_date_sk#143, d_year#144] + +(141) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [c_first_sales_date_sk#142] +Right keys [1]: [d_date_sk#143] +Join type: Inner +Join condition: None + +(142) Project [codegen id : 51] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142, d_date_sk#143, d_year#144] + +(143) ReusedExchange [Reuses operator id: 53] +Output [2]: [d_date_sk#145, d_year#146] + +(144) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [c_first_shipto_date_sk#141] +Right keys [1]: [d_date_sk#145] +Join type: Inner +Join condition: None + +(145) Project [codegen id : 51] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144, d_date_sk#145, d_year#146] + +(146) ReusedExchange [Reuses operator id: 62] +Output [2]: [cd_demo_sk#147, cd_marital_status#148] + +(147) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_cdemo_sk#108] +Right keys [1]: [cd_demo_sk#147] +Join type: Inner +Join condition: None + +(148) Project [codegen id : 51] +Output [16]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_demo_sk#147, cd_marital_status#148] + +(149) ReusedExchange [Reuses operator id: 62] +Output [2]: [cd_demo_sk#149, cd_marital_status#150] + +(150) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [c_current_cdemo_sk#138] +Right keys [1]: [cd_demo_sk#149] +Join type: Inner +Join condition: NOT (cd_marital_status#148 = cd_marital_status#150) + +(151) Project [codegen id : 51] +Output [14]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [18]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148, cd_demo_sk#149, cd_marital_status#150] + +(152) ReusedExchange [Reuses operator id: 71] +Output [1]: [p_promo_sk#151] + +(153) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_promo_sk#112] +Right keys [1]: [p_promo_sk#151] +Join type: Inner +Join condition: None + +(154) Project [codegen id : 51] +Output [13]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, p_promo_sk#151] + +(155) ReusedExchange [Reuses operator id: 77] +Output [2]: [hd_demo_sk#152, hd_income_band_sk#153] + +(156) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_hdemo_sk#109] +Right keys [1]: [hd_demo_sk#152] +Join type: Inner +Join condition: None + +(157) Project [codegen id : 51] +Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153] +Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_demo_sk#152, hd_income_band_sk#153] + +(158) ReusedExchange [Reuses operator id: 77] +Output [2]: [hd_demo_sk#154, hd_income_band_sk#155] + +(159) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [c_current_hdemo_sk#139] +Right keys [1]: [hd_demo_sk#154] +Join type: Inner +Join condition: None + +(160) Project [codegen id : 51] +Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155] +Input [15]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_demo_sk#154, hd_income_band_sk#155] + +(161) ReusedExchange [Reuses operator id: 86] +Output [5]: [ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] + +(162) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_addr_sk#110] +Right keys [1]: [ca_address_sk#156] +Join type: Inner +Join condition: None + +(163) Project [codegen id : 51] +Output [16]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] +Input [18]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] + +(164) ReusedExchange [Reuses operator id: 86] +Output [5]: [ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] + +(165) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [c_current_addr_sk#140] +Right keys [1]: [ca_address_sk#161] +Join type: Inner +Join condition: None + +(166) Project [codegen id : 51] +Output [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [21]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] + +(167) ReusedExchange [Reuses operator id: 95] +Output [1]: [ib_income_band_sk#166] + +(168) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [hd_income_band_sk#153] +Right keys [1]: [ib_income_band_sk#166] +Join type: Inner +Join condition: None + +(169) Project [codegen id : 51] +Output [18]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [20]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#166] + +(170) ReusedExchange [Reuses operator id: 95] +Output [1]: [ib_income_band_sk#167] + +(171) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [hd_income_band_sk#155] +Right keys [1]: [ib_income_band_sk#167] +Join type: Inner +Join condition: None + +(172) Project [codegen id : 51] +Output [17]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#167] + +(173) ReusedExchange [Reuses operator id: 105] +Output [2]: [i_item_sk#168, i_product_name#169] + +(174) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_item_sk#106] +Right keys [1]: [i_item_sk#168] +Join type: Inner +Join condition: None + +(175) Project [codegen id : 51] +Output [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] +Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] + +(176) HashAggregate [codegen id : 51] +Input [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] +Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] +Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#114)), partial_sum(UnscaledValue(ss_list_price#115)), partial_sum(UnscaledValue(ss_coupon_amt#116))] +Aggregate Attributes [4]: [count#77, sum#170, sum#171, sum#172] +Results [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] + +(177) HashAggregate [codegen id : 51] +Input [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] +Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] +Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#114)), sum(UnscaledValue(ss_list_price#115)), sum(UnscaledValue(ss_coupon_amt#116))] +Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#114))#86, sum(UnscaledValue(ss_list_price#115))#87, sum(UnscaledValue(ss_coupon_amt#116))#88] +Results [8]: [i_item_sk#168 AS item_sk#176, s_store_name#135 AS store_name#177, s_zip#136 AS store_zip#178, d_year#133 AS syear#179, count(1)#85 AS cnt#180, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#114))#86,17,2) AS s1#181, MakeDecimal(sum(UnscaledValue(ss_list_price#115))#87,17,2) AS s2#182, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#116))#88,17,2) AS s3#183] + +(178) Exchange +Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] +Arguments: hashpartitioning(item_sk#176, store_name#177, store_zip#178, 5), ENSURE_REQUIREMENTS, [plan_id=18] + +(179) Sort [codegen id : 52] +Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] +Arguments: [item_sk#176 ASC NULLS FIRST, store_name#177 ASC NULLS FIRST, store_zip#178 ASC NULLS FIRST], false, 0 + +(180) SortMergeJoin [codegen id : 53] +Left keys [3]: [item_sk#90, store_name#91, store_zip#92] +Right keys [3]: [item_sk#176, store_name#177, store_zip#178] +Join type: Inner +Join condition: (cnt#180 <= cnt#102) + +(181) Project [codegen id : 53] +Output [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Input [25]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] + +(182) Exchange +Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Arguments: rangepartitioning(product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=19] + +(183) Sort [codegen id : 54] +Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Arguments: [product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (187) ++- * Filter (186) + +- * ColumnarToRow (185) + +- CometScan parquet spark_catalog.default.date_dim (184) + + +(184) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#37, d_year#38] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(185) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#37, d_year#38] + +(186) Filter [codegen id : 1] +Input [2]: [d_date_sk#37, d_year#38] +Condition : ((isnotnull(d_year#38) AND (d_year#38 = 1999)) AND isnotnull(d_date_sk#37)) + +(187) BroadcastExchange +Input [2]: [d_date_sk#37, d_year#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=20] + +Subquery:2 Hosting operator id = 112 Hosting Expression = ss_sold_date_sk#117 IN dynamicpruning#118 +BroadcastExchange (191) ++- * Filter (190) + +- * ColumnarToRow (189) + +- CometScan parquet spark_catalog.default.date_dim (188) + + +(188) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#132, d_year#133] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(189) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#132, d_year#133] + +(190) Filter [codegen id : 1] +Input [2]: [d_date_sk#132, d_year#133] +Condition : ((isnotnull(d_year#133) AND (d_year#133 = 2000)) AND isnotnull(d_date_sk#132)) + +(191) BroadcastExchange +Input [2]: [d_date_sk#132, d_year#133] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=21] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/simplified.txt new file mode 100644 index 000000000..76cac39ea --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/simplified.txt @@ -0,0 +1,289 @@ +WholeStageCodegen (54) + Sort [product_name,store_name,cnt] + InputAdapter + Exchange [product_name,store_name,cnt] #1 + WholeStageCodegen (53) + Project [product_name,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,s1,s2,s3,syear,cnt] + SortMergeJoin [item_sk,store_name,store_zip,item_sk,store_name,store_zip,cnt,cnt] + InputAdapter + WholeStageCodegen (26) + Sort [item_sk,store_name,store_zip] + InputAdapter + Exchange [item_sk,store_name,store_zip] #2 + WholeStageCodegen (25) + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),product_name,item_sk,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] + Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,hd_income_band_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk,cd_marital_status,cd_marital_status] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,cd_marital_status] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_first_shipto_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,d_year] + BroadcastHashJoin [c_first_sales_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SortMergeJoin [ss_item_sk,cs_item_sk] + InputAdapter + WholeStageCodegen (3) + Sort [ss_item_sk] + InputAdapter + Exchange [ss_item_sk] #3 + WholeStageCodegen (2) + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + Project [sr_item_sk,sr_ticket_number] + Filter [sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + WholeStageCodegen (9) + Sort [cs_item_sk] + Project [cs_item_sk] + Filter [sale,refund] + HashAggregate [cs_item_sk,sum,sum,isEmpty] [sum(UnscaledValue(cs_ext_list_price)),sum(((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)),sale,refund,sum,sum,isEmpty] + InputAdapter + Exchange [cs_item_sk] #6 + WholeStageCodegen (8) + HashAggregate [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] [sum,sum,isEmpty,sum,sum,isEmpty] + Project [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (5) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #7 + WholeStageCodegen (4) + Project [cs_item_sk,cs_order_number,cs_ext_list_price] + Filter [cs_item_sk,cs_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_ext_list_price,cs_sold_date_sk] + InputAdapter + WholeStageCodegen (7) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #8 + WholeStageCodegen (6) + Project [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit] + Filter [cr_item_sk,cr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (11) + Filter [s_store_sk,s_store_name,s_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_zip] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (12) + Filter [c_customer_sk,c_first_sales_date_sk,c_first_shipto_date_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (13) + Filter [d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (15) + Filter [cd_demo_sk,cd_marital_status] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (17) + Filter [p_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.promotion [p_promo_sk] + InputAdapter + BroadcastExchange #14 + WholeStageCodegen (18) + Filter [hd_demo_sk,hd_income_band_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_income_band_sk] + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + BroadcastExchange #15 + WholeStageCodegen (20) + Filter [ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + BroadcastExchange #16 + WholeStageCodegen (22) + Filter [ib_income_band_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.income_band [ib_income_band_sk] + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + BroadcastExchange #17 + WholeStageCodegen (24) + Project [i_item_sk,i_product_name] + Filter [i_current_price,i_color,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_color,i_product_name] + InputAdapter + WholeStageCodegen (52) + Sort [item_sk,store_name,store_zip] + InputAdapter + Exchange [item_sk,store_name,store_zip] #18 + WholeStageCodegen (51) + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),item_sk,store_name,store_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] + Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,hd_income_band_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk,cd_marital_status,cd_marital_status] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,cd_marital_status] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_first_shipto_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,d_year] + BroadcastHashJoin [c_first_sales_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SortMergeJoin [ss_item_sk,cs_item_sk] + InputAdapter + WholeStageCodegen (29) + Sort [ss_item_sk] + InputAdapter + Exchange [ss_item_sk] #19 + WholeStageCodegen (28) + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + InputAdapter + BroadcastExchange #20 + WholeStageCodegen (27) + Filter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #21 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + Project [sr_item_sk,sr_ticket_number] + Filter [sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + WholeStageCodegen (35) + Sort [cs_item_sk] + Project [cs_item_sk] + Filter [sale,refund] + HashAggregate [cs_item_sk,sum,sum,isEmpty] [sum(UnscaledValue(cs_ext_list_price)),sum(((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)),sale,refund,sum,sum,isEmpty] + InputAdapter + ReusedExchange [cs_item_sk,sum,sum,isEmpty] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #21 + InputAdapter + ReusedExchange [s_store_sk,s_store_name,s_zip] #9 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] #10 + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + ReusedExchange [p_promo_sk] #13 + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + ReusedExchange [i_item_sk,i_product_name] #17 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/explain.txt new file mode 100644 index 000000000..b9107a072 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/explain.txt @@ -0,0 +1,269 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (22) + : +- * BroadcastHashJoin Inner BuildRight (21) + : :- * Project (16) + : : +- * BroadcastHashJoin Inner BuildRight (15) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.store (1) + : : +- BroadcastExchange (14) + : : +- * Filter (13) + : : +- * HashAggregate (12) + : : +- Exchange (11) + : : +- * HashAggregate (10) + : : +- * Project (9) + : : +- * BroadcastHashJoin Inner BuildRight (8) + : : :- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : +- ReusedExchange (7) + : +- BroadcastExchange (20) + : +- * Filter (19) + : +- * ColumnarToRow (18) + : +- CometScan parquet spark_catalog.default.item (17) + +- BroadcastExchange (36) + +- * Filter (35) + +- * HashAggregate (34) + +- Exchange (33) + +- * HashAggregate (32) + +- * HashAggregate (31) + +- Exchange (30) + +- * HashAggregate (29) + +- * Project (28) + +- * BroadcastHashJoin Inner BuildRight (27) + :- * Filter (25) + : +- * ColumnarToRow (24) + : +- CometScan parquet spark_catalog.default.store_sales (23) + +- ReusedExchange (26) + + +(1) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#1, s_store_name#2] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 9] +Input [2]: [s_store_sk#1, s_store_name#2] + +(3) Filter [codegen id : 9] +Input [2]: [s_store_sk#1, s_store_name#2] +Condition : isnotnull(s_store_sk#1) + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [4]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] + +(6) Filter [codegen id : 2] +Input [4]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Condition : (isnotnull(ss_store_sk#4) AND isnotnull(ss_item_sk#3)) + +(7) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#8] + +(8) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#6] +Right keys [1]: [d_date_sk#8] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 2] +Output [3]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5] +Input [5]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6, d_date_sk#8] + +(10) HashAggregate [codegen id : 2] +Input [3]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5] +Keys [2]: [ss_store_sk#4, ss_item_sk#3] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#5))] +Aggregate Attributes [1]: [sum#9] +Results [3]: [ss_store_sk#4, ss_item_sk#3, sum#10] + +(11) Exchange +Input [3]: [ss_store_sk#4, ss_item_sk#3, sum#10] +Arguments: hashpartitioning(ss_store_sk#4, ss_item_sk#3, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(12) HashAggregate [codegen id : 3] +Input [3]: [ss_store_sk#4, ss_item_sk#3, sum#10] +Keys [2]: [ss_store_sk#4, ss_item_sk#3] +Functions [1]: [sum(UnscaledValue(ss_sales_price#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#5))#11] +Results [3]: [ss_store_sk#4, ss_item_sk#3, MakeDecimal(sum(UnscaledValue(ss_sales_price#5))#11,17,2) AS revenue#12] + +(13) Filter [codegen id : 3] +Input [3]: [ss_store_sk#4, ss_item_sk#3, revenue#12] +Condition : isnotnull(revenue#12) + +(14) BroadcastExchange +Input [3]: [ss_store_sk#4, ss_item_sk#3, revenue#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [s_store_sk#1] +Right keys [1]: [ss_store_sk#4] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 9] +Output [4]: [s_store_name#2, ss_store_sk#4, ss_item_sk#3, revenue#12] +Input [5]: [s_store_sk#1, s_store_name#2, ss_store_sk#4, ss_item_sk#3, revenue#12] + +(17) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 4] +Input [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] + +(19) Filter [codegen id : 4] +Input [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Condition : isnotnull(i_item_sk#13) + +(20) BroadcastExchange +Input [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#3] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 9] +Output [7]: [s_store_name#2, ss_store_sk#4, revenue#12, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Input [9]: [s_store_name#2, ss_store_sk#4, ss_item_sk#3, revenue#12, i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] + +(23) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20, ss_sold_date_sk#21] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#21), dynamicpruningexpression(ss_sold_date_sk#21 IN dynamicpruning#22)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(24) ColumnarToRow [codegen id : 6] +Input [4]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20, ss_sold_date_sk#21] + +(25) Filter [codegen id : 6] +Input [4]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20, ss_sold_date_sk#21] +Condition : isnotnull(ss_store_sk#19) + +(26) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#23] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#21] +Right keys [1]: [d_date_sk#23] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [3]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20] +Input [5]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20, ss_sold_date_sk#21, d_date_sk#23] + +(29) HashAggregate [codegen id : 6] +Input [3]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20] +Keys [2]: [ss_store_sk#19, ss_item_sk#18] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#20))] +Aggregate Attributes [1]: [sum#24] +Results [3]: [ss_store_sk#19, ss_item_sk#18, sum#25] + +(30) Exchange +Input [3]: [ss_store_sk#19, ss_item_sk#18, sum#25] +Arguments: hashpartitioning(ss_store_sk#19, ss_item_sk#18, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [3]: [ss_store_sk#19, ss_item_sk#18, sum#25] +Keys [2]: [ss_store_sk#19, ss_item_sk#18] +Functions [1]: [sum(UnscaledValue(ss_sales_price#20))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#20))#26] +Results [2]: [ss_store_sk#19, MakeDecimal(sum(UnscaledValue(ss_sales_price#20))#26,17,2) AS revenue#27] + +(32) HashAggregate [codegen id : 7] +Input [2]: [ss_store_sk#19, revenue#27] +Keys [1]: [ss_store_sk#19] +Functions [1]: [partial_avg(revenue#27)] +Aggregate Attributes [2]: [sum#28, count#29] +Results [3]: [ss_store_sk#19, sum#30, count#31] + +(33) Exchange +Input [3]: [ss_store_sk#19, sum#30, count#31] +Arguments: hashpartitioning(ss_store_sk#19, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(34) HashAggregate [codegen id : 8] +Input [3]: [ss_store_sk#19, sum#30, count#31] +Keys [1]: [ss_store_sk#19] +Functions [1]: [avg(revenue#27)] +Aggregate Attributes [1]: [avg(revenue#27)#32] +Results [2]: [ss_store_sk#19, avg(revenue#27)#32 AS ave#33] + +(35) Filter [codegen id : 8] +Input [2]: [ss_store_sk#19, ave#33] +Condition : isnotnull(ave#33) + +(36) BroadcastExchange +Input [2]: [ss_store_sk#19, ave#33] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +(37) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [ss_store_sk#19] +Join type: Inner +Join condition: (cast(revenue#12 as decimal(23,7)) <= (0.1 * ave#33)) + +(38) Project [codegen id : 9] +Output [6]: [s_store_name#2, i_item_desc#14, revenue#12, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Input [9]: [s_store_name#2, ss_store_sk#4, revenue#12, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17, ss_store_sk#19, ave#33] + +(39) TakeOrderedAndProject +Input [6]: [s_store_name#2, i_item_desc#14, revenue#12, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Arguments: 100, [s_store_name#2 ASC NULLS FIRST, i_item_desc#14 ASC NULLS FIRST], [s_store_name#2, i_item_desc#14, revenue#12, i_current_price#15, i_wholesale_cost#16, i_brand#17] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (44) ++- * Project (43) + +- * Filter (42) + +- * ColumnarToRow (41) + +- CometScan parquet spark_catalog.default.date_dim (40) + + +(40) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#8, d_month_seq#34] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1176), LessThanOrEqual(d_month_seq,1187), IsNotNull(d_date_sk)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#8, d_month_seq#34] + +(42) Filter [codegen id : 1] +Input [2]: [d_date_sk#8, d_month_seq#34] +Condition : (((isnotnull(d_month_seq#34) AND (d_month_seq#34 >= 1176)) AND (d_month_seq#34 <= 1187)) AND isnotnull(d_date_sk#8)) + +(43) Project [codegen id : 1] +Output [1]: [d_date_sk#8] +Input [2]: [d_date_sk#8, d_month_seq#34] + +(44) BroadcastExchange +Input [1]: [d_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 23 Hosting Expression = ss_sold_date_sk#21 IN dynamicpruning#7 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/simplified.txt new file mode 100644 index 000000000..6670cbdac --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/simplified.txt @@ -0,0 +1,67 @@ +TakeOrderedAndProject [s_store_name,i_item_desc,revenue,i_current_price,i_wholesale_cost,i_brand] + WholeStageCodegen (9) + Project [s_store_name,i_item_desc,revenue,i_current_price,i_wholesale_cost,i_brand] + BroadcastHashJoin [ss_store_sk,ss_store_sk,revenue,ave] + Project [s_store_name,ss_store_sk,revenue,i_item_desc,i_current_price,i_wholesale_cost,i_brand] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [s_store_name,ss_store_sk,ss_item_sk,revenue] + BroadcastHashJoin [s_store_sk,ss_store_sk] + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name] + InputAdapter + BroadcastExchange #1 + WholeStageCodegen (3) + Filter [revenue] + HashAggregate [ss_store_sk,ss_item_sk,sum] [sum(UnscaledValue(ss_sales_price)),revenue,sum] + InputAdapter + Exchange [ss_store_sk,ss_item_sk] #2 + WholeStageCodegen (2) + HashAggregate [ss_store_sk,ss_item_sk,ss_sales_price] [sum,sum] + Project [ss_item_sk,ss_store_sk,ss_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc,i_current_price,i_wholesale_cost,i_brand] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (8) + Filter [ave] + HashAggregate [ss_store_sk,sum,count] [avg(revenue),ave,sum,count] + InputAdapter + Exchange [ss_store_sk] #6 + WholeStageCodegen (7) + HashAggregate [ss_store_sk,revenue] [sum,count,sum,count] + HashAggregate [ss_store_sk,ss_item_sk,sum] [sum(UnscaledValue(ss_sales_price)),revenue,sum] + InputAdapter + Exchange [ss_store_sk,ss_item_sk] #7 + WholeStageCodegen (6) + HashAggregate [ss_store_sk,ss_item_sk,ss_sales_price] [sum,sum] + Project [ss_item_sk,ss_store_sk,ss_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/explain.txt new file mode 100644 index 000000000..b3e8005c9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/explain.txt @@ -0,0 +1,332 @@ +== Physical Plan == +TakeOrderedAndProject (52) ++- * HashAggregate (51) + +- Exchange (50) + +- * HashAggregate (49) + +- Union (48) + :- * HashAggregate (29) + : +- Exchange (28) + : +- * HashAggregate (27) + : +- * Project (26) + : +- * BroadcastHashJoin Inner BuildRight (25) + : :- * Project (19) + : : +- * BroadcastHashJoin Inner BuildRight (18) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.warehouse (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (17) + : : +- * Project (16) + : : +- * Filter (15) + : : +- * ColumnarToRow (14) + : : +- CometScan parquet spark_catalog.default.time_dim (13) + : +- BroadcastExchange (24) + : +- * Project (23) + : +- * Filter (22) + : +- * ColumnarToRow (21) + : +- CometScan parquet spark_catalog.default.ship_mode (20) + +- * HashAggregate (47) + +- Exchange (46) + +- * HashAggregate (45) + +- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (41) + : +- * BroadcastHashJoin Inner BuildRight (40) + : :- * Project (38) + : : +- * BroadcastHashJoin Inner BuildRight (37) + : : :- * Project (35) + : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : :- * Filter (32) + : : : : +- * ColumnarToRow (31) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (30) + : : : +- ReusedExchange (33) + : : +- ReusedExchange (36) + : +- ReusedExchange (39) + +- ReusedExchange (42) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_warehouse_sk#3, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#7), dynamicpruningexpression(ws_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ws_warehouse_sk), IsNotNull(ws_sold_time_sk), IsNotNull(ws_ship_mode_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [7]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_warehouse_sk#3, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7] + +(3) Filter [codegen id : 5] +Input [7]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_warehouse_sk#3, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7] +Condition : ((isnotnull(ws_warehouse_sk#3) AND isnotnull(ws_sold_time_sk#1)) AND isnotnull(ws_ship_mode_sk#2)) + +(4) Scan parquet spark_catalog.default.warehouse +Output [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] + +(6) Filter [codegen id : 1] +Input [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] +Condition : isnotnull(w_warehouse_sk#9) + +(7) BroadcastExchange +Input [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_warehouse_sk#3] +Right keys [1]: [w_warehouse_sk#9] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [12]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] +Input [14]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_warehouse_sk#3, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7, w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] + +(10) ReusedExchange [Reuses operator id: 56] +Output [3]: [d_date_sk#16, d_year#17, d_moy#18] + +(11) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_sold_date_sk#7] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 5] +Output [13]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18] +Input [15]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_date_sk#16, d_year#17, d_moy#18] + +(13) Scan parquet spark_catalog.default.time_dim +Output [2]: [t_time_sk#19, t_time#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_time), GreaterThanOrEqual(t_time,30838), LessThanOrEqual(t_time,59638), IsNotNull(t_time_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [2]: [t_time_sk#19, t_time#20] + +(15) Filter [codegen id : 3] +Input [2]: [t_time_sk#19, t_time#20] +Condition : (((isnotnull(t_time#20) AND (t_time#20 >= 30838)) AND (t_time#20 <= 59638)) AND isnotnull(t_time_sk#19)) + +(16) Project [codegen id : 3] +Output [1]: [t_time_sk#19] +Input [2]: [t_time_sk#19, t_time#20] + +(17) BroadcastExchange +Input [1]: [t_time_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_sold_time_sk#1] +Right keys [1]: [t_time_sk#19] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 5] +Output [12]: [ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18] +Input [14]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18, t_time_sk#19] + +(20) Scan parquet spark_catalog.default.ship_mode +Output [2]: [sm_ship_mode_sk#21, sm_carrier#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/ship_mode] +PushedFilters: [In(sm_carrier, [BARIAN ,DHL ]), IsNotNull(sm_ship_mode_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [2]: [sm_ship_mode_sk#21, sm_carrier#22] + +(22) Filter [codegen id : 4] +Input [2]: [sm_ship_mode_sk#21, sm_carrier#22] +Condition : (sm_carrier#22 IN (DHL ,BARIAN ) AND isnotnull(sm_ship_mode_sk#21)) + +(23) Project [codegen id : 4] +Output [1]: [sm_ship_mode_sk#21] +Input [2]: [sm_ship_mode_sk#21, sm_carrier#22] + +(24) BroadcastExchange +Input [1]: [sm_ship_mode_sk#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ws_ship_mode_sk#2] +Right keys [1]: [sm_ship_mode_sk#21] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 5] +Output [11]: [ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18] +Input [13]: [ws_ship_mode_sk#2, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18, sm_ship_mode_sk#21] + +(27) HashAggregate [codegen id : 5] +Input [11]: [ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, d_moy#18] +Keys [7]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17] +Functions [24]: [partial_sum(CASE WHEN (d_moy#18 = 1) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 2) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 3) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 4) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 5) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 6) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 7) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 8) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 9) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 10) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 11) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 12) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 1) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 2) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 3) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 4) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 5) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 6) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 7) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 8) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 9) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 10) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 11) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#18 = 12) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)] +Aggregate Attributes [48]: [sum#23, isEmpty#24, sum#25, isEmpty#26, sum#27, isEmpty#28, sum#29, isEmpty#30, sum#31, isEmpty#32, sum#33, isEmpty#34, sum#35, isEmpty#36, sum#37, isEmpty#38, sum#39, isEmpty#40, sum#41, isEmpty#42, sum#43, isEmpty#44, sum#45, isEmpty#46, sum#47, isEmpty#48, sum#49, isEmpty#50, sum#51, isEmpty#52, sum#53, isEmpty#54, sum#55, isEmpty#56, sum#57, isEmpty#58, sum#59, isEmpty#60, sum#61, isEmpty#62, sum#63, isEmpty#64, sum#65, isEmpty#66, sum#67, isEmpty#68, sum#69, isEmpty#70] +Results [55]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, sum#71, isEmpty#72, sum#73, isEmpty#74, sum#75, isEmpty#76, sum#77, isEmpty#78, sum#79, isEmpty#80, sum#81, isEmpty#82, sum#83, isEmpty#84, sum#85, isEmpty#86, sum#87, isEmpty#88, sum#89, isEmpty#90, sum#91, isEmpty#92, sum#93, isEmpty#94, sum#95, isEmpty#96, sum#97, isEmpty#98, sum#99, isEmpty#100, sum#101, isEmpty#102, sum#103, isEmpty#104, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110, sum#111, isEmpty#112, sum#113, isEmpty#114, sum#115, isEmpty#116, sum#117, isEmpty#118] + +(28) Exchange +Input [55]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, sum#71, isEmpty#72, sum#73, isEmpty#74, sum#75, isEmpty#76, sum#77, isEmpty#78, sum#79, isEmpty#80, sum#81, isEmpty#82, sum#83, isEmpty#84, sum#85, isEmpty#86, sum#87, isEmpty#88, sum#89, isEmpty#90, sum#91, isEmpty#92, sum#93, isEmpty#94, sum#95, isEmpty#96, sum#97, isEmpty#98, sum#99, isEmpty#100, sum#101, isEmpty#102, sum#103, isEmpty#104, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110, sum#111, isEmpty#112, sum#113, isEmpty#114, sum#115, isEmpty#116, sum#117, isEmpty#118] +Arguments: hashpartitioning(w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 6] +Input [55]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17, sum#71, isEmpty#72, sum#73, isEmpty#74, sum#75, isEmpty#76, sum#77, isEmpty#78, sum#79, isEmpty#80, sum#81, isEmpty#82, sum#83, isEmpty#84, sum#85, isEmpty#86, sum#87, isEmpty#88, sum#89, isEmpty#90, sum#91, isEmpty#92, sum#93, isEmpty#94, sum#95, isEmpty#96, sum#97, isEmpty#98, sum#99, isEmpty#100, sum#101, isEmpty#102, sum#103, isEmpty#104, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110, sum#111, isEmpty#112, sum#113, isEmpty#114, sum#115, isEmpty#116, sum#117, isEmpty#118] +Keys [7]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, d_year#17] +Functions [24]: [sum(CASE WHEN (d_moy#18 = 1) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 2) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 3) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 4) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 5) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 6) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 7) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 8) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 9) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 10) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 11) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 12) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 1) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 2) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 3) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 4) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 5) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 6) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 7) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 8) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 9) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 10) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 11) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#18 = 12) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)] +Aggregate Attributes [24]: [sum(CASE WHEN (d_moy#18 = 1) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#119, sum(CASE WHEN (d_moy#18 = 2) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#120, sum(CASE WHEN (d_moy#18 = 3) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#121, sum(CASE WHEN (d_moy#18 = 4) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#122, sum(CASE WHEN (d_moy#18 = 5) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#123, sum(CASE WHEN (d_moy#18 = 6) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#124, sum(CASE WHEN (d_moy#18 = 7) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#125, sum(CASE WHEN (d_moy#18 = 8) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#126, sum(CASE WHEN (d_moy#18 = 9) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#127, sum(CASE WHEN (d_moy#18 = 10) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#128, sum(CASE WHEN (d_moy#18 = 11) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#129, sum(CASE WHEN (d_moy#18 = 12) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#130, sum(CASE WHEN (d_moy#18 = 1) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#131, sum(CASE WHEN (d_moy#18 = 2) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#132, sum(CASE WHEN (d_moy#18 = 3) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#133, sum(CASE WHEN (d_moy#18 = 4) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#134, sum(CASE WHEN (d_moy#18 = 5) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#135, sum(CASE WHEN (d_moy#18 = 6) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#136, sum(CASE WHEN (d_moy#18 = 7) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#137, sum(CASE WHEN (d_moy#18 = 8) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#138, sum(CASE WHEN (d_moy#18 = 9) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#139, sum(CASE WHEN (d_moy#18 = 10) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#140, sum(CASE WHEN (d_moy#18 = 11) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#141, sum(CASE WHEN (d_moy#18 = 12) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#142] +Results [32]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, DHL,BARIAN AS ship_carriers#143, d_year#17 AS year#144, sum(CASE WHEN (d_moy#18 = 1) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#119 AS jan_sales#145, sum(CASE WHEN (d_moy#18 = 2) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#120 AS feb_sales#146, sum(CASE WHEN (d_moy#18 = 3) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#121 AS mar_sales#147, sum(CASE WHEN (d_moy#18 = 4) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#122 AS apr_sales#148, sum(CASE WHEN (d_moy#18 = 5) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#123 AS may_sales#149, sum(CASE WHEN (d_moy#18 = 6) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#124 AS jun_sales#150, sum(CASE WHEN (d_moy#18 = 7) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#125 AS jul_sales#151, sum(CASE WHEN (d_moy#18 = 8) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#126 AS aug_sales#152, sum(CASE WHEN (d_moy#18 = 9) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#127 AS sep_sales#153, sum(CASE WHEN (d_moy#18 = 10) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#128 AS oct_sales#154, sum(CASE WHEN (d_moy#18 = 11) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#129 AS nov_sales#155, sum(CASE WHEN (d_moy#18 = 12) THEN (ws_ext_sales_price#5 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#130 AS dec_sales#156, sum(CASE WHEN (d_moy#18 = 1) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#131 AS jan_net#157, sum(CASE WHEN (d_moy#18 = 2) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#132 AS feb_net#158, sum(CASE WHEN (d_moy#18 = 3) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#133 AS mar_net#159, sum(CASE WHEN (d_moy#18 = 4) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#134 AS apr_net#160, sum(CASE WHEN (d_moy#18 = 5) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#135 AS may_net#161, sum(CASE WHEN (d_moy#18 = 6) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#136 AS jun_net#162, sum(CASE WHEN (d_moy#18 = 7) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#137 AS jul_net#163, sum(CASE WHEN (d_moy#18 = 8) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#138 AS aug_net#164, sum(CASE WHEN (d_moy#18 = 9) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#139 AS sep_net#165, sum(CASE WHEN (d_moy#18 = 10) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#140 AS oct_net#166, sum(CASE WHEN (d_moy#18 = 11) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#141 AS nov_net#167, sum(CASE WHEN (d_moy#18 = 12) THEN (ws_net_paid#6 * cast(ws_quantity#4 as decimal(10,0))) ELSE 0.00 END)#142 AS dec_net#168] + +(30) Scan parquet spark_catalog.default.catalog_sales +Output [7]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_warehouse_sk#171, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#175), dynamicpruningexpression(cs_sold_date_sk#175 IN dynamicpruning#176)] +PushedFilters: [IsNotNull(cs_warehouse_sk), IsNotNull(cs_sold_time_sk), IsNotNull(cs_ship_mode_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 11] +Input [7]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_warehouse_sk#171, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175] + +(32) Filter [codegen id : 11] +Input [7]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_warehouse_sk#171, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175] +Condition : ((isnotnull(cs_warehouse_sk#171) AND isnotnull(cs_sold_time_sk#169)) AND isnotnull(cs_ship_mode_sk#170)) + +(33) ReusedExchange [Reuses operator id: 7] +Output [7]: [w_warehouse_sk#177, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183] + +(34) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_warehouse_sk#171] +Right keys [1]: [w_warehouse_sk#177] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 11] +Output [12]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183] +Input [14]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_warehouse_sk#171, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175, w_warehouse_sk#177, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183] + +(36) ReusedExchange [Reuses operator id: 56] +Output [3]: [d_date_sk#184, d_year#185, d_moy#186] + +(37) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_date_sk#175] +Right keys [1]: [d_date_sk#184] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 11] +Output [13]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186] +Input [15]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_date_sk#184, d_year#185, d_moy#186] + +(39) ReusedExchange [Reuses operator id: 17] +Output [1]: [t_time_sk#187] + +(40) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_sold_time_sk#169] +Right keys [1]: [t_time_sk#187] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 11] +Output [12]: [cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186] +Input [14]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186, t_time_sk#187] + +(42) ReusedExchange [Reuses operator id: 24] +Output [1]: [sm_ship_mode_sk#188] + +(43) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [cs_ship_mode_sk#170] +Right keys [1]: [sm_ship_mode_sk#188] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 11] +Output [11]: [cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186] +Input [13]: [cs_ship_mode_sk#170, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186, sm_ship_mode_sk#188] + +(45) HashAggregate [codegen id : 11] +Input [11]: [cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, d_moy#186] +Keys [7]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185] +Functions [24]: [partial_sum(CASE WHEN (d_moy#186 = 1) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 2) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 3) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 4) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 5) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 6) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 7) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 8) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 9) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 10) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 11) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 12) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 1) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 2) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 3) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 4) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 5) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 6) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 7) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 8) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 9) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 10) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 11) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), partial_sum(CASE WHEN (d_moy#186 = 12) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)] +Aggregate Attributes [48]: [sum#189, isEmpty#190, sum#191, isEmpty#192, sum#193, isEmpty#194, sum#195, isEmpty#196, sum#197, isEmpty#198, sum#199, isEmpty#200, sum#201, isEmpty#202, sum#203, isEmpty#204, sum#205, isEmpty#206, sum#207, isEmpty#208, sum#209, isEmpty#210, sum#211, isEmpty#212, sum#213, isEmpty#214, sum#215, isEmpty#216, sum#217, isEmpty#218, sum#219, isEmpty#220, sum#221, isEmpty#222, sum#223, isEmpty#224, sum#225, isEmpty#226, sum#227, isEmpty#228, sum#229, isEmpty#230, sum#231, isEmpty#232, sum#233, isEmpty#234, sum#235, isEmpty#236] +Results [55]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, sum#237, isEmpty#238, sum#239, isEmpty#240, sum#241, isEmpty#242, sum#243, isEmpty#244, sum#245, isEmpty#246, sum#247, isEmpty#248, sum#249, isEmpty#250, sum#251, isEmpty#252, sum#253, isEmpty#254, sum#255, isEmpty#256, sum#257, isEmpty#258, sum#259, isEmpty#260, sum#261, isEmpty#262, sum#263, isEmpty#264, sum#265, isEmpty#266, sum#267, isEmpty#268, sum#269, isEmpty#270, sum#271, isEmpty#272, sum#273, isEmpty#274, sum#275, isEmpty#276, sum#277, isEmpty#278, sum#279, isEmpty#280, sum#281, isEmpty#282, sum#283, isEmpty#284] + +(46) Exchange +Input [55]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, sum#237, isEmpty#238, sum#239, isEmpty#240, sum#241, isEmpty#242, sum#243, isEmpty#244, sum#245, isEmpty#246, sum#247, isEmpty#248, sum#249, isEmpty#250, sum#251, isEmpty#252, sum#253, isEmpty#254, sum#255, isEmpty#256, sum#257, isEmpty#258, sum#259, isEmpty#260, sum#261, isEmpty#262, sum#263, isEmpty#264, sum#265, isEmpty#266, sum#267, isEmpty#268, sum#269, isEmpty#270, sum#271, isEmpty#272, sum#273, isEmpty#274, sum#275, isEmpty#276, sum#277, isEmpty#278, sum#279, isEmpty#280, sum#281, isEmpty#282, sum#283, isEmpty#284] +Arguments: hashpartitioning(w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(47) HashAggregate [codegen id : 12] +Input [55]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185, sum#237, isEmpty#238, sum#239, isEmpty#240, sum#241, isEmpty#242, sum#243, isEmpty#244, sum#245, isEmpty#246, sum#247, isEmpty#248, sum#249, isEmpty#250, sum#251, isEmpty#252, sum#253, isEmpty#254, sum#255, isEmpty#256, sum#257, isEmpty#258, sum#259, isEmpty#260, sum#261, isEmpty#262, sum#263, isEmpty#264, sum#265, isEmpty#266, sum#267, isEmpty#268, sum#269, isEmpty#270, sum#271, isEmpty#272, sum#273, isEmpty#274, sum#275, isEmpty#276, sum#277, isEmpty#278, sum#279, isEmpty#280, sum#281, isEmpty#282, sum#283, isEmpty#284] +Keys [7]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, d_year#185] +Functions [24]: [sum(CASE WHEN (d_moy#186 = 1) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 2) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 3) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 4) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 5) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 6) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 7) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 8) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 9) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 10) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 11) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 12) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 1) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 2) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 3) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 4) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 5) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 6) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 7) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 8) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 9) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 10) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 11) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END), sum(CASE WHEN (d_moy#186 = 12) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)] +Aggregate Attributes [24]: [sum(CASE WHEN (d_moy#186 = 1) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#285, sum(CASE WHEN (d_moy#186 = 2) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#286, sum(CASE WHEN (d_moy#186 = 3) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#287, sum(CASE WHEN (d_moy#186 = 4) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#288, sum(CASE WHEN (d_moy#186 = 5) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#289, sum(CASE WHEN (d_moy#186 = 6) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#290, sum(CASE WHEN (d_moy#186 = 7) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#291, sum(CASE WHEN (d_moy#186 = 8) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#292, sum(CASE WHEN (d_moy#186 = 9) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#293, sum(CASE WHEN (d_moy#186 = 10) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#294, sum(CASE WHEN (d_moy#186 = 11) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#295, sum(CASE WHEN (d_moy#186 = 12) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#296, sum(CASE WHEN (d_moy#186 = 1) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#297, sum(CASE WHEN (d_moy#186 = 2) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#298, sum(CASE WHEN (d_moy#186 = 3) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#299, sum(CASE WHEN (d_moy#186 = 4) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#300, sum(CASE WHEN (d_moy#186 = 5) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#301, sum(CASE WHEN (d_moy#186 = 6) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#302, sum(CASE WHEN (d_moy#186 = 7) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#303, sum(CASE WHEN (d_moy#186 = 8) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#304, sum(CASE WHEN (d_moy#186 = 9) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#305, sum(CASE WHEN (d_moy#186 = 10) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#306, sum(CASE WHEN (d_moy#186 = 11) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#307, sum(CASE WHEN (d_moy#186 = 12) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#308] +Results [32]: [w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183, DHL,BARIAN AS ship_carriers#309, d_year#185 AS year#310, sum(CASE WHEN (d_moy#186 = 1) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#285 AS jan_sales#311, sum(CASE WHEN (d_moy#186 = 2) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#286 AS feb_sales#312, sum(CASE WHEN (d_moy#186 = 3) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#287 AS mar_sales#313, sum(CASE WHEN (d_moy#186 = 4) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#288 AS apr_sales#314, sum(CASE WHEN (d_moy#186 = 5) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#289 AS may_sales#315, sum(CASE WHEN (d_moy#186 = 6) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#290 AS jun_sales#316, sum(CASE WHEN (d_moy#186 = 7) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#291 AS jul_sales#317, sum(CASE WHEN (d_moy#186 = 8) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#292 AS aug_sales#318, sum(CASE WHEN (d_moy#186 = 9) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#293 AS sep_sales#319, sum(CASE WHEN (d_moy#186 = 10) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#294 AS oct_sales#320, sum(CASE WHEN (d_moy#186 = 11) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#295 AS nov_sales#321, sum(CASE WHEN (d_moy#186 = 12) THEN (cs_sales_price#173 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#296 AS dec_sales#322, sum(CASE WHEN (d_moy#186 = 1) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#297 AS jan_net#323, sum(CASE WHEN (d_moy#186 = 2) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#298 AS feb_net#324, sum(CASE WHEN (d_moy#186 = 3) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#299 AS mar_net#325, sum(CASE WHEN (d_moy#186 = 4) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#300 AS apr_net#326, sum(CASE WHEN (d_moy#186 = 5) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#301 AS may_net#327, sum(CASE WHEN (d_moy#186 = 6) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#302 AS jun_net#328, sum(CASE WHEN (d_moy#186 = 7) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#303 AS jul_net#329, sum(CASE WHEN (d_moy#186 = 8) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#304 AS aug_net#330, sum(CASE WHEN (d_moy#186 = 9) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#305 AS sep_net#331, sum(CASE WHEN (d_moy#186 = 10) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#306 AS oct_net#332, sum(CASE WHEN (d_moy#186 = 11) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#307 AS nov_net#333, sum(CASE WHEN (d_moy#186 = 12) THEN (cs_net_paid_inc_tax#174 * cast(cs_quantity#172 as decimal(10,0))) ELSE 0.00 END)#308 AS dec_net#334] + +(48) Union + +(49) HashAggregate [codegen id : 13] +Input [32]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, jan_sales#145, feb_sales#146, mar_sales#147, apr_sales#148, may_sales#149, jun_sales#150, jul_sales#151, aug_sales#152, sep_sales#153, oct_sales#154, nov_sales#155, dec_sales#156, jan_net#157, feb_net#158, mar_net#159, apr_net#160, may_net#161, jun_net#162, jul_net#163, aug_net#164, sep_net#165, oct_net#166, nov_net#167, dec_net#168] +Keys [8]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144] +Functions [36]: [partial_sum(jan_sales#145), partial_sum(feb_sales#146), partial_sum(mar_sales#147), partial_sum(apr_sales#148), partial_sum(may_sales#149), partial_sum(jun_sales#150), partial_sum(jul_sales#151), partial_sum(aug_sales#152), partial_sum(sep_sales#153), partial_sum(oct_sales#154), partial_sum(nov_sales#155), partial_sum(dec_sales#156), partial_sum((jan_sales#145 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((feb_sales#146 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((mar_sales#147 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((apr_sales#148 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((may_sales#149 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((jun_sales#150 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((jul_sales#151 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((aug_sales#152 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((sep_sales#153 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((oct_sales#154 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((nov_sales#155 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum((dec_sales#156 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), partial_sum(jan_net#157), partial_sum(feb_net#158), partial_sum(mar_net#159), partial_sum(apr_net#160), partial_sum(may_net#161), partial_sum(jun_net#162), partial_sum(jul_net#163), partial_sum(aug_net#164), partial_sum(sep_net#165), partial_sum(oct_net#166), partial_sum(nov_net#167), partial_sum(dec_net#168)] +Aggregate Attributes [72]: [sum#335, isEmpty#336, sum#337, isEmpty#338, sum#339, isEmpty#340, sum#341, isEmpty#342, sum#343, isEmpty#344, sum#345, isEmpty#346, sum#347, isEmpty#348, sum#349, isEmpty#350, sum#351, isEmpty#352, sum#353, isEmpty#354, sum#355, isEmpty#356, sum#357, isEmpty#358, sum#359, isEmpty#360, sum#361, isEmpty#362, sum#363, isEmpty#364, sum#365, isEmpty#366, sum#367, isEmpty#368, sum#369, isEmpty#370, sum#371, isEmpty#372, sum#373, isEmpty#374, sum#375, isEmpty#376, sum#377, isEmpty#378, sum#379, isEmpty#380, sum#381, isEmpty#382, sum#383, isEmpty#384, sum#385, isEmpty#386, sum#387, isEmpty#388, sum#389, isEmpty#390, sum#391, isEmpty#392, sum#393, isEmpty#394, sum#395, isEmpty#396, sum#397, isEmpty#398, sum#399, isEmpty#400, sum#401, isEmpty#402, sum#403, isEmpty#404, sum#405, isEmpty#406] +Results [80]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, sum#407, isEmpty#408, sum#409, isEmpty#410, sum#411, isEmpty#412, sum#413, isEmpty#414, sum#415, isEmpty#416, sum#417, isEmpty#418, sum#419, isEmpty#420, sum#421, isEmpty#422, sum#423, isEmpty#424, sum#425, isEmpty#426, sum#427, isEmpty#428, sum#429, isEmpty#430, sum#431, isEmpty#432, sum#433, isEmpty#434, sum#435, isEmpty#436, sum#437, isEmpty#438, sum#439, isEmpty#440, sum#441, isEmpty#442, sum#443, isEmpty#444, sum#445, isEmpty#446, sum#447, isEmpty#448, sum#449, isEmpty#450, sum#451, isEmpty#452, sum#453, isEmpty#454, sum#455, isEmpty#456, sum#457, isEmpty#458, sum#459, isEmpty#460, sum#461, isEmpty#462, sum#463, isEmpty#464, sum#465, isEmpty#466, sum#467, isEmpty#468, sum#469, isEmpty#470, sum#471, isEmpty#472, sum#473, isEmpty#474, sum#475, isEmpty#476, sum#477, isEmpty#478] + +(50) Exchange +Input [80]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, sum#407, isEmpty#408, sum#409, isEmpty#410, sum#411, isEmpty#412, sum#413, isEmpty#414, sum#415, isEmpty#416, sum#417, isEmpty#418, sum#419, isEmpty#420, sum#421, isEmpty#422, sum#423, isEmpty#424, sum#425, isEmpty#426, sum#427, isEmpty#428, sum#429, isEmpty#430, sum#431, isEmpty#432, sum#433, isEmpty#434, sum#435, isEmpty#436, sum#437, isEmpty#438, sum#439, isEmpty#440, sum#441, isEmpty#442, sum#443, isEmpty#444, sum#445, isEmpty#446, sum#447, isEmpty#448, sum#449, isEmpty#450, sum#451, isEmpty#452, sum#453, isEmpty#454, sum#455, isEmpty#456, sum#457, isEmpty#458, sum#459, isEmpty#460, sum#461, isEmpty#462, sum#463, isEmpty#464, sum#465, isEmpty#466, sum#467, isEmpty#468, sum#469, isEmpty#470, sum#471, isEmpty#472, sum#473, isEmpty#474, sum#475, isEmpty#476, sum#477, isEmpty#478] +Arguments: hashpartitioning(w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(51) HashAggregate [codegen id : 14] +Input [80]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, sum#407, isEmpty#408, sum#409, isEmpty#410, sum#411, isEmpty#412, sum#413, isEmpty#414, sum#415, isEmpty#416, sum#417, isEmpty#418, sum#419, isEmpty#420, sum#421, isEmpty#422, sum#423, isEmpty#424, sum#425, isEmpty#426, sum#427, isEmpty#428, sum#429, isEmpty#430, sum#431, isEmpty#432, sum#433, isEmpty#434, sum#435, isEmpty#436, sum#437, isEmpty#438, sum#439, isEmpty#440, sum#441, isEmpty#442, sum#443, isEmpty#444, sum#445, isEmpty#446, sum#447, isEmpty#448, sum#449, isEmpty#450, sum#451, isEmpty#452, sum#453, isEmpty#454, sum#455, isEmpty#456, sum#457, isEmpty#458, sum#459, isEmpty#460, sum#461, isEmpty#462, sum#463, isEmpty#464, sum#465, isEmpty#466, sum#467, isEmpty#468, sum#469, isEmpty#470, sum#471, isEmpty#472, sum#473, isEmpty#474, sum#475, isEmpty#476, sum#477, isEmpty#478] +Keys [8]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144] +Functions [36]: [sum(jan_sales#145), sum(feb_sales#146), sum(mar_sales#147), sum(apr_sales#148), sum(may_sales#149), sum(jun_sales#150), sum(jul_sales#151), sum(aug_sales#152), sum(sep_sales#153), sum(oct_sales#154), sum(nov_sales#155), sum(dec_sales#156), sum((jan_sales#145 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((feb_sales#146 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((mar_sales#147 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((apr_sales#148 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((may_sales#149 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((jun_sales#150 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((jul_sales#151 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((aug_sales#152 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((sep_sales#153 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((oct_sales#154 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((nov_sales#155 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum((dec_sales#156 / cast(w_warehouse_sq_ft#11 as decimal(10,0)))), sum(jan_net#157), sum(feb_net#158), sum(mar_net#159), sum(apr_net#160), sum(may_net#161), sum(jun_net#162), sum(jul_net#163), sum(aug_net#164), sum(sep_net#165), sum(oct_net#166), sum(nov_net#167), sum(dec_net#168)] +Aggregate Attributes [36]: [sum(jan_sales#145)#479, sum(feb_sales#146)#480, sum(mar_sales#147)#481, sum(apr_sales#148)#482, sum(may_sales#149)#483, sum(jun_sales#150)#484, sum(jul_sales#151)#485, sum(aug_sales#152)#486, sum(sep_sales#153)#487, sum(oct_sales#154)#488, sum(nov_sales#155)#489, sum(dec_sales#156)#490, sum((jan_sales#145 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#491, sum((feb_sales#146 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#492, sum((mar_sales#147 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#493, sum((apr_sales#148 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#494, sum((may_sales#149 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#495, sum((jun_sales#150 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#496, sum((jul_sales#151 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#497, sum((aug_sales#152 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#498, sum((sep_sales#153 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#499, sum((oct_sales#154 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#500, sum((nov_sales#155 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#501, sum((dec_sales#156 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#502, sum(jan_net#157)#503, sum(feb_net#158)#504, sum(mar_net#159)#505, sum(apr_net#160)#506, sum(may_net#161)#507, sum(jun_net#162)#508, sum(jul_net#163)#509, sum(aug_net#164)#510, sum(sep_net#165)#511, sum(oct_net#166)#512, sum(nov_net#167)#513, sum(dec_net#168)#514] +Results [44]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, sum(jan_sales#145)#479 AS jan_sales#515, sum(feb_sales#146)#480 AS feb_sales#516, sum(mar_sales#147)#481 AS mar_sales#517, sum(apr_sales#148)#482 AS apr_sales#518, sum(may_sales#149)#483 AS may_sales#519, sum(jun_sales#150)#484 AS jun_sales#520, sum(jul_sales#151)#485 AS jul_sales#521, sum(aug_sales#152)#486 AS aug_sales#522, sum(sep_sales#153)#487 AS sep_sales#523, sum(oct_sales#154)#488 AS oct_sales#524, sum(nov_sales#155)#489 AS nov_sales#525, sum(dec_sales#156)#490 AS dec_sales#526, sum((jan_sales#145 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#491 AS jan_sales_per_sq_foot#527, sum((feb_sales#146 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#492 AS feb_sales_per_sq_foot#528, sum((mar_sales#147 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#493 AS mar_sales_per_sq_foot#529, sum((apr_sales#148 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#494 AS apr_sales_per_sq_foot#530, sum((may_sales#149 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#495 AS may_sales_per_sq_foot#531, sum((jun_sales#150 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#496 AS jun_sales_per_sq_foot#532, sum((jul_sales#151 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#497 AS jul_sales_per_sq_foot#533, sum((aug_sales#152 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#498 AS aug_sales_per_sq_foot#534, sum((sep_sales#153 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#499 AS sep_sales_per_sq_foot#535, sum((oct_sales#154 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#500 AS oct_sales_per_sq_foot#536, sum((nov_sales#155 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#501 AS nov_sales_per_sq_foot#537, sum((dec_sales#156 / cast(w_warehouse_sq_ft#11 as decimal(10,0))))#502 AS dec_sales_per_sq_foot#538, sum(jan_net#157)#503 AS jan_net#539, sum(feb_net#158)#504 AS feb_net#540, sum(mar_net#159)#505 AS mar_net#541, sum(apr_net#160)#506 AS apr_net#542, sum(may_net#161)#507 AS may_net#543, sum(jun_net#162)#508 AS jun_net#544, sum(jul_net#163)#509 AS jul_net#545, sum(aug_net#164)#510 AS aug_net#546, sum(sep_net#165)#511 AS sep_net#547, sum(oct_net#166)#512 AS oct_net#548, sum(nov_net#167)#513 AS nov_net#549, sum(dec_net#168)#514 AS dec_net#550] + +(52) TakeOrderedAndProject +Input [44]: [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, jan_sales#515, feb_sales#516, mar_sales#517, apr_sales#518, may_sales#519, jun_sales#520, jul_sales#521, aug_sales#522, sep_sales#523, oct_sales#524, nov_sales#525, dec_sales#526, jan_sales_per_sq_foot#527, feb_sales_per_sq_foot#528, mar_sales_per_sq_foot#529, apr_sales_per_sq_foot#530, may_sales_per_sq_foot#531, jun_sales_per_sq_foot#532, jul_sales_per_sq_foot#533, aug_sales_per_sq_foot#534, sep_sales_per_sq_foot#535, oct_sales_per_sq_foot#536, nov_sales_per_sq_foot#537, dec_sales_per_sq_foot#538, jan_net#539, feb_net#540, mar_net#541, apr_net#542, may_net#543, jun_net#544, jul_net#545, aug_net#546, sep_net#547, oct_net#548, nov_net#549, dec_net#550] +Arguments: 100, [w_warehouse_name#10 ASC NULLS FIRST], [w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15, ship_carriers#143, year#144, jan_sales#515, feb_sales#516, mar_sales#517, apr_sales#518, may_sales#519, jun_sales#520, jul_sales#521, aug_sales#522, sep_sales#523, oct_sales#524, nov_sales#525, dec_sales#526, jan_sales_per_sq_foot#527, feb_sales_per_sq_foot#528, mar_sales_per_sq_foot#529, apr_sales_per_sq_foot#530, may_sales_per_sq_foot#531, jun_sales_per_sq_foot#532, jul_sales_per_sq_foot#533, aug_sales_per_sq_foot#534, sep_sales_per_sq_foot#535, oct_sales_per_sq_foot#536, nov_sales_per_sq_foot#537, dec_sales_per_sq_foot#538, jan_net#539, feb_net#540, mar_net#541, apr_net#542, may_net#543, jun_net#544, jul_net#545, aug_net#546, sep_net#547, oct_net#548, nov_net#549, dec_net#550] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (56) ++- * Filter (55) + +- * ColumnarToRow (54) + +- CometScan parquet spark_catalog.default.date_dim (53) + + +(53) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#16, d_year#17, d_moy#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(54) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#16, d_year#17, d_moy#18] + +(55) Filter [codegen id : 1] +Input [3]: [d_date_sk#16, d_year#17, d_moy#18] +Condition : ((isnotnull(d_year#17) AND (d_year#17 = 2001)) AND isnotnull(d_date_sk#16)) + +(56) BroadcastExchange +Input [3]: [d_date_sk#16, d_year#17, d_moy#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 30 Hosting Expression = cs_sold_date_sk#175 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/simplified.txt new file mode 100644 index 000000000..4c2daaa3e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/simplified.txt @@ -0,0 +1,86 @@ +TakeOrderedAndProject [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,ship_carriers,year,jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_sales_per_sq_foot,feb_sales_per_sq_foot,mar_sales_per_sq_foot,apr_sales_per_sq_foot,may_sales_per_sq_foot,jun_sales_per_sq_foot,jul_sales_per_sq_foot,aug_sales_per_sq_foot,sep_sales_per_sq_foot,oct_sales_per_sq_foot,nov_sales_per_sq_foot,dec_sales_per_sq_foot,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net] + WholeStageCodegen (14) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,ship_carriers,year,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(jan_sales),sum(feb_sales),sum(mar_sales),sum(apr_sales),sum(may_sales),sum(jun_sales),sum(jul_sales),sum(aug_sales),sum(sep_sales),sum(oct_sales),sum(nov_sales),sum(dec_sales),sum((jan_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((feb_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((mar_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((apr_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((may_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((jun_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((jul_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((aug_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((sep_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((oct_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((nov_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum((dec_sales / cast(w_warehouse_sq_ft as decimal(10,0)))),sum(jan_net),sum(feb_net),sum(mar_net),sum(apr_net),sum(may_net),sum(jun_net),sum(jul_net),sum(aug_net),sum(sep_net),sum(oct_net),sum(nov_net),sum(dec_net),jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_sales_per_sq_foot,feb_sales_per_sq_foot,mar_sales_per_sq_foot,apr_sales_per_sq_foot,may_sales_per_sq_foot,jun_sales_per_sq_foot,jul_sales_per_sq_foot,aug_sales_per_sq_foot,sep_sales_per_sq_foot,oct_sales_per_sq_foot,nov_sales_per_sq_foot,dec_sales_per_sq_foot,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,ship_carriers,year] #1 + WholeStageCodegen (13) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,ship_carriers,year,jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (6) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(CASE WHEN (d_moy = 1) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 2) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 3) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 4) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 5) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 6) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 7) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 8) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 9) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 10) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 11) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 12) THEN (ws_ext_sales_price * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 1) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 2) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 3) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 4) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 5) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 6) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 7) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 8) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 9) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 10) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 11) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 12) THEN (ws_net_paid * cast(ws_quantity as decimal(10,0))) ELSE 0.00 END),ship_carriers,year,jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year] #2 + WholeStageCodegen (5) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy,ws_ext_sales_price,ws_quantity,ws_net_paid] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Project [ws_quantity,ws_ext_sales_price,ws_net_paid,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [ws_ship_mode_sk,sm_ship_mode_sk] + Project [ws_ship_mode_sk,ws_quantity,ws_ext_sales_price,ws_net_paid,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [ws_sold_time_sk,t_time_sk] + Project [ws_sold_time_sk,ws_ship_mode_sk,ws_quantity,ws_ext_sales_price,ws_net_paid,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_sold_time_sk,ws_ship_mode_sk,ws_quantity,ws_ext_sales_price,ws_net_paid,ws_sold_date_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] + BroadcastHashJoin [ws_warehouse_sk,w_warehouse_sk] + Filter [ws_warehouse_sk,ws_sold_time_sk,ws_ship_mode_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_ship_mode_sk,ws_warehouse_sk,ws_quantity,ws_ext_sales_price,ws_net_paid,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Project [t_time_sk] + Filter [t_time,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_time] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + Project [sm_ship_mode_sk] + Filter [sm_carrier,sm_ship_mode_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.ship_mode [sm_ship_mode_sk,sm_carrier] + WholeStageCodegen (12) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(CASE WHEN (d_moy = 1) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 2) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 3) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 4) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 5) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 6) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 7) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 8) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 9) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 10) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 11) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 12) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 1) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 2) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 3) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 4) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 5) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 6) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 7) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 8) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 9) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 10) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 11) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 12) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),ship_carriers,year,jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year] #7 + WholeStageCodegen (11) + HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy,cs_sales_price,cs_quantity,cs_net_paid_inc_tax] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Project [cs_quantity,cs_sales_price,cs_net_paid_inc_tax,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [cs_ship_mode_sk,sm_ship_mode_sk] + Project [cs_ship_mode_sk,cs_quantity,cs_sales_price,cs_net_paid_inc_tax,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [cs_sold_time_sk,t_time_sk] + Project [cs_sold_time_sk,cs_ship_mode_sk,cs_quantity,cs_sales_price,cs_net_paid_inc_tax,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,d_moy] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sold_time_sk,cs_ship_mode_sk,cs_quantity,cs_sales_price,cs_net_paid_inc_tax,cs_sold_date_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] + BroadcastHashJoin [cs_warehouse_sk,w_warehouse_sk] + Filter [cs_warehouse_sk,cs_sold_time_sk,cs_ship_mode_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_sold_time_sk,cs_ship_mode_sk,cs_warehouse_sk,cs_quantity,cs_sales_price,cs_net_paid_inc_tax,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [w_warehouse_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] #4 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #3 + InputAdapter + ReusedExchange [t_time_sk] #5 + InputAdapter + ReusedExchange [sm_ship_mode_sk] #6 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/explain.txt new file mode 100644 index 000000000..192e065e5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/explain.txt @@ -0,0 +1,204 @@ +== Physical Plan == +TakeOrderedAndProject (30) ++- * Filter (29) + +- Window (28) + +- WindowGroupLimit (27) + +- * Sort (26) + +- Exchange (25) + +- WindowGroupLimit (24) + +- * Sort (23) + +- * HashAggregate (22) + +- Exchange (21) + +- * HashAggregate (20) + +- * Expand (19) + +- * Project (18) + +- * BroadcastHashJoin Inner BuildRight (17) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * Filter (9) + : +- * ColumnarToRow (8) + : +- CometScan parquet spark_catalog.default.store (7) + +- BroadcastExchange (16) + +- * Filter (15) + +- * ColumnarToRow (14) + +- CometScan parquet spark_catalog.default.item (13) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] + +(3) Filter [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) + +(4) ReusedExchange [Reuses operator id: 35] +Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5, d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_store_id#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#11, s_store_id#12] + +(9) Filter [codegen id : 2] +Input [2]: [s_store_sk#11, s_store_id#12] +Condition : isnotnull(s_store_sk#11) + +(10) BroadcastExchange +Input [2]: [s_store_sk#11, s_store_id#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [7]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_sk#11, s_store_id#12] + +(13) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] + +(15) Filter [codegen id : 3] +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Condition : isnotnull(i_item_sk#13) + +(16) BroadcastExchange +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [10]: [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12] +Input [12]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12, i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] + +(19) Expand [codegen id : 4] +Input [10]: [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12] +Arguments: [[ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, 0], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, null, 1], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, null, null, 3], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, null, null, null, 7], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, i_product_name#17, null, null, null, null, 15], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, i_brand#14, null, null, null, null, null, 31], [ss_quantity#3, ss_sales_price#4, i_category#16, i_class#15, null, null, null, null, null, null, 63], [ss_quantity#3, ss_sales_price#4, i_category#16, null, null, null, null, null, null, null, 127], [ss_quantity#3, ss_sales_price#4, null, null, null, null, null, null, null, null, 255]], [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26] + +(20) HashAggregate [codegen id : 4] +Input [11]: [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26] +Keys [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26] +Functions [1]: [partial_sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))] +Aggregate Attributes [2]: [sum#27, isEmpty#28] +Results [11]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26, sum#29, isEmpty#30] + +(21) Exchange +Input [11]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26, sum#29, isEmpty#30] +Arguments: hashpartitioning(i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [11]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26, sum#29, isEmpty#30] +Keys [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, spark_grouping_id#26] +Functions [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))#31] +Results [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))#31 AS sumsales#32] + +(23) Sort [codegen id : 5] +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: [i_category#18 ASC NULLS FIRST, sumsales#32 DESC NULLS LAST], false, 0 + +(24) WindowGroupLimit +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: [i_category#18], [sumsales#32 DESC NULLS LAST], rank(sumsales#32), 100, Partial + +(25) Exchange +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: hashpartitioning(i_category#18, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(26) Sort [codegen id : 6] +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: [i_category#18 ASC NULLS FIRST, sumsales#32 DESC NULLS LAST], false, 0 + +(27) WindowGroupLimit +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: [i_category#18], [sumsales#32 DESC NULLS LAST], rank(sumsales#32), 100, Final + +(28) Window +Input [9]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32] +Arguments: [rank(sumsales#32) windowspecdefinition(i_category#18, sumsales#32 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#33], [i_category#18], [sumsales#32 DESC NULLS LAST] + +(29) Filter [codegen id : 7] +Input [10]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32, rk#33] +Condition : (rk#33 <= 100) + +(30) TakeOrderedAndProject +Input [10]: [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32, rk#33] +Arguments: 100, [i_category#18 ASC NULLS FIRST, i_class#19 ASC NULLS FIRST, i_brand#20 ASC NULLS FIRST, i_product_name#21 ASC NULLS FIRST, d_year#22 ASC NULLS FIRST, d_qoy#23 ASC NULLS FIRST, d_moy#24 ASC NULLS FIRST, s_store_id#25 ASC NULLS FIRST, sumsales#32 ASC NULLS FIRST, rk#33 ASC NULLS FIRST], [i_category#18, i_class#19, i_brand#20, i_product_name#21, d_year#22, d_qoy#23, d_moy#24, s_store_id#25, sumsales#32, rk#33] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (35) ++- * Project (34) + +- * Filter (33) + +- * ColumnarToRow (32) + +- CometScan parquet spark_catalog.default.date_dim (31) + + +(31) Scan parquet spark_catalog.default.date_dim +Output [5]: [d_date_sk#7, d_month_seq#34, d_year#8, d_moy#9, d_qoy#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 1] +Input [5]: [d_date_sk#7, d_month_seq#34, d_year#8, d_moy#9, d_qoy#10] + +(33) Filter [codegen id : 1] +Input [5]: [d_date_sk#7, d_month_seq#34, d_year#8, d_moy#9, d_qoy#10] +Condition : (((isnotnull(d_month_seq#34) AND (d_month_seq#34 >= 1200)) AND (d_month_seq#34 <= 1211)) AND isnotnull(d_date_sk#7)) + +(34) Project [codegen id : 1] +Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] +Input [5]: [d_date_sk#7, d_month_seq#34, d_year#8, d_moy#9, d_qoy#10] + +(35) BroadcastExchange +Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/simplified.txt new file mode 100644 index 000000000..ecc706b76 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/simplified.txt @@ -0,0 +1,53 @@ +TakeOrderedAndProject [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,rk] + WholeStageCodegen (7) + Filter [rk] + InputAdapter + Window [sumsales,i_category] + WindowGroupLimit [i_category,sumsales] + WholeStageCodegen (6) + Sort [i_category,sumsales] + InputAdapter + Exchange [i_category] #1 + WindowGroupLimit [i_category,sumsales] + WholeStageCodegen (5) + Sort [i_category,sumsales] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,spark_grouping_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,spark_grouping_id] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,spark_grouping_id,ss_sales_price,ss_quantity] [sum,isEmpty,sum,isEmpty] + Expand [ss_quantity,ss_sales_price,i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id] + Project [ss_quantity,ss_sales_price,i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_sales_price,d_year,d_moy,d_qoy,s_store_id] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,d_year,d_moy,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk,d_year,d_moy,d_qoy] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_year,d_moy,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy,d_qoy] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/explain.txt new file mode 100644 index 000000000..48b46fab5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/explain.txt @@ -0,0 +1,258 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (35) + : +- * BroadcastHashJoin Inner BuildRight (34) + : :- * HashAggregate (29) + : : +- Exchange (28) + : : +- * HashAggregate (27) + : : +- * Project (26) + : : +- * BroadcastHashJoin Inner BuildRight (25) + : : :- * Project (20) + : : : +- * BroadcastHashJoin Inner BuildRight (19) + : : : :- * Project (13) + : : : : +- * BroadcastHashJoin Inner BuildRight (12) + : : : : :- * Project (6) + : : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : : :- * Filter (3) + : : : : : : +- * ColumnarToRow (2) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : +- ReusedExchange (4) + : : : : +- BroadcastExchange (11) + : : : : +- * Project (10) + : : : : +- * Filter (9) + : : : : +- * ColumnarToRow (8) + : : : : +- CometScan parquet spark_catalog.default.store (7) + : : : +- BroadcastExchange (18) + : : : +- * Project (17) + : : : +- * Filter (16) + : : : +- * ColumnarToRow (15) + : : : +- CometScan parquet spark_catalog.default.household_demographics (14) + : : +- BroadcastExchange (24) + : : +- * Filter (23) + : : +- * ColumnarToRow (22) + : : +- CometScan parquet spark_catalog.default.customer_address (21) + : +- BroadcastExchange (33) + : +- * Filter (32) + : +- * ColumnarToRow (31) + : +- CometScan parquet spark_catalog.default.customer (30) + +- ReusedExchange (36) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ss_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#9), dynamicpruningexpression(ss_sold_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ss_sold_date_sk#9] + +(3) Filter [codegen id : 5] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ss_sold_date_sk#9] +Condition : (((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_customer_sk#1)) + +(4) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#11] + +(5) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 5] +Output [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8] +Input [10]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ss_sold_date_sk#9, d_date_sk#11] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#12, s_city#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [In(s_city, [Fairview,Midway]), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#12, s_city#13] + +(9) Filter [codegen id : 2] +Input [2]: [s_store_sk#12, s_city#13] +Condition : (s_city#13 IN (Midway,Fairview) AND isnotnull(s_store_sk#12)) + +(10) Project [codegen id : 2] +Output [1]: [s_store_sk#12] +Input [2]: [s_store_sk#12, s_city#13] + +(11) BroadcastExchange +Input [1]: [s_store_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [s_store_sk#12] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, s_store_sk#12] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [Or(EqualTo(hd_dep_count,4),EqualTo(hd_vehicle_count,3)), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] + +(16) Filter [codegen id : 3] +Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Condition : (((hd_dep_count#15 = 4) OR (hd_vehicle_count#16 = 3)) AND isnotnull(hd_demo_sk#14)) + +(17) Project [codegen id : 3] +Output [1]: [hd_demo_sk#14] +Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#14] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 5] +Output [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, hd_demo_sk#14] + +(21) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#17, ca_city#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_city)] +ReadSchema: struct + +(22) ColumnarToRow [codegen id : 4] +Input [2]: [ca_address_sk#17, ca_city#18] + +(23) Filter [codegen id : 4] +Input [2]: [ca_address_sk#17, ca_city#18] +Condition : (isnotnull(ca_address_sk#17) AND isnotnull(ca_city#18)) + +(24) BroadcastExchange +Input [2]: [ca_address_sk#17, ca_city#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_addr_sk#3] +Right keys [1]: [ca_address_sk#17] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 5] +Output [7]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ca_city#18] +Input [8]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ca_address_sk#17, ca_city#18] + +(27) HashAggregate [codegen id : 5] +Input [7]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ca_city#18] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18] +Functions [3]: [partial_sum(UnscaledValue(ss_ext_sales_price#6)), partial_sum(UnscaledValue(ss_ext_list_price#7)), partial_sum(UnscaledValue(ss_ext_tax#8))] +Aggregate Attributes [3]: [sum#19, sum#20, sum#21] +Results [7]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, sum#22, sum#23, sum#24] + +(28) Exchange +Input [7]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, sum#22, sum#23, sum#24] +Arguments: hashpartitioning(ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 8] +Input [7]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, sum#22, sum#23, sum#24] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18] +Functions [3]: [sum(UnscaledValue(ss_ext_sales_price#6)), sum(UnscaledValue(ss_ext_list_price#7)), sum(UnscaledValue(ss_ext_tax#8))] +Aggregate Attributes [3]: [sum(UnscaledValue(ss_ext_sales_price#6))#25, sum(UnscaledValue(ss_ext_list_price#7))#26, sum(UnscaledValue(ss_ext_tax#8))#27] +Results [6]: [ss_ticket_number#5, ss_customer_sk#1, ca_city#18 AS bought_city#28, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#6))#25,17,2) AS extended_price#29, MakeDecimal(sum(UnscaledValue(ss_ext_list_price#7))#26,17,2) AS list_price#30, MakeDecimal(sum(UnscaledValue(ss_ext_tax#8))#27,17,2) AS extended_tax#31] + +(30) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 6] +Input [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] + +(32) Filter [codegen id : 6] +Input [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] +Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_current_addr_sk#33)) + +(33) BroadcastExchange +Input [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#32] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [8]: [ss_ticket_number#5, bought_city#28, extended_price#29, list_price#30, extended_tax#31, c_current_addr_sk#33, c_first_name#34, c_last_name#35] +Input [10]: [ss_ticket_number#5, ss_customer_sk#1, bought_city#28, extended_price#29, list_price#30, extended_tax#31, c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] + +(36) ReusedExchange [Reuses operator id: 24] +Output [2]: [ca_address_sk#36, ca_city#37] + +(37) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [c_current_addr_sk#33] +Right keys [1]: [ca_address_sk#36] +Join type: Inner +Join condition: NOT (ca_city#37 = bought_city#28) + +(38) Project [codegen id : 8] +Output [8]: [c_last_name#35, c_first_name#34, ca_city#37, bought_city#28, ss_ticket_number#5, extended_price#29, extended_tax#31, list_price#30] +Input [10]: [ss_ticket_number#5, bought_city#28, extended_price#29, list_price#30, extended_tax#31, c_current_addr_sk#33, c_first_name#34, c_last_name#35, ca_address_sk#36, ca_city#37] + +(39) TakeOrderedAndProject +Input [8]: [c_last_name#35, c_first_name#34, ca_city#37, bought_city#28, ss_ticket_number#5, extended_price#29, extended_tax#31, list_price#30] +Arguments: 100, [c_last_name#35 ASC NULLS FIRST, ss_ticket_number#5 ASC NULLS FIRST], [c_last_name#35, c_first_name#34, ca_city#37, bought_city#28, ss_ticket_number#5, extended_price#29, extended_tax#31, list_price#30] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#9 IN dynamicpruning#10 +BroadcastExchange (44) ++- * Project (43) + +- * Filter (42) + +- * ColumnarToRow (41) + +- CometScan parquet spark_catalog.default.date_dim (40) + + +(40) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#11, d_year#38, d_dom#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_dom), GreaterThanOrEqual(d_dom,1), LessThanOrEqual(d_dom,2), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#11, d_year#38, d_dom#39] + +(42) Filter [codegen id : 1] +Input [3]: [d_date_sk#11, d_year#38, d_dom#39] +Condition : ((((isnotnull(d_dom#39) AND (d_dom#39 >= 1)) AND (d_dom#39 <= 2)) AND d_year#38 IN (1999,2000,2001)) AND isnotnull(d_date_sk#11)) + +(43) Project [codegen id : 1] +Output [1]: [d_date_sk#11] +Input [3]: [d_date_sk#11, d_year#38, d_dom#39] + +(44) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/simplified.txt new file mode 100644 index 000000000..20d9432d1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/simplified.txt @@ -0,0 +1,65 @@ +TakeOrderedAndProject [c_last_name,ss_ticket_number,c_first_name,ca_city,bought_city,extended_price,extended_tax,list_price] + WholeStageCodegen (8) + Project [c_last_name,c_first_name,ca_city,bought_city,ss_ticket_number,extended_price,extended_tax,list_price] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk,ca_city,bought_city] + Project [ss_ticket_number,bought_city,extended_price,list_price,extended_tax,c_current_addr_sk,c_first_name,c_last_name] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city,sum,sum,sum] [sum(UnscaledValue(ss_ext_sales_price)),sum(UnscaledValue(ss_ext_list_price)),sum(UnscaledValue(ss_ext_tax)),bought_city,extended_price,list_price,extended_tax,sum,sum,sum] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city] #1 + WholeStageCodegen (5) + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax] [sum,sum,sum,sum,sum,sum] + Project [ss_customer_sk,ss_addr_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax,ca_city] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_customer_sk,ss_addr_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk,ss_hdemo_sk,ss_addr_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_dom,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [s_store_sk] + Filter [s_city,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_city] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Project [hd_demo_sk] + Filter [hd_dep_count,hd_vehicle_count,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Filter [ca_address_sk,ca_city] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Filter [c_customer_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name] + InputAdapter + ReusedExchange [ca_address_sk,ca_city] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/explain.txt new file mode 100644 index 000000000..522bd93e5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/explain.txt @@ -0,0 +1,281 @@ +== Physical Plan == +TakeOrderedAndProject (42) ++- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (25) + : : +- * BroadcastHashJoin LeftAnti BuildRight (24) + : : :- * BroadcastHashJoin LeftAnti BuildRight (17) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (9) + : : : : +- * Project (8) + : : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : : :- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : +- ReusedExchange (6) + : : : +- BroadcastExchange (16) + : : : +- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- BroadcastExchange (23) + : : +- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * ColumnarToRow (19) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) + : : +- ReusedExchange (20) + : +- BroadcastExchange (30) + : +- * Project (29) + : +- * Filter (28) + : +- * ColumnarToRow (27) + : +- CometScan parquet spark_catalog.default.customer_address (26) + +- BroadcastExchange (36) + +- * Filter (35) + +- * ColumnarToRow (34) + +- CometScan parquet spark_catalog.default.customer_demographics (33) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(3) Filter [codegen id : 9] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#4, ss_sold_date_sk#5] + +(6) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#7] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#4] +Input [3]: [ss_customer_sk#4, ss_sold_date_sk#5, d_date_sk#7] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#4] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#9), dynamicpruningexpression(ws_sold_date_sk#9 IN dynamicpruning#10)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] + +(13) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#11] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#8] +Input [3]: [ws_bill_customer_sk#8, ws_sold_date_sk#9, d_date_sk#11] + +(16) BroadcastExchange +Input [1]: [ws_bill_customer_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ws_bill_customer_sk#8] +Join type: LeftAnti +Join condition: None + +(18) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#12, cs_sold_date_sk#13] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#13), dynamicpruningexpression(cs_sold_date_sk#13 IN dynamicpruning#14)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#12, cs_sold_date_sk#13] + +(20) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#15] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#13] +Right keys [1]: [d_date_sk#15] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#12] +Input [3]: [cs_ship_customer_sk#12, cs_sold_date_sk#13, d_date_sk#15] + +(23) BroadcastExchange +Input [1]: [cs_ship_customer_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [cs_ship_customer_sk#12] +Join type: LeftAnti +Join condition: None + +(25) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#2, c_current_addr_sk#3] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(26) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#16, ca_state#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [GA,KY,NM]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(27) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#16, ca_state#17] + +(28) Filter [codegen id : 7] +Input [2]: [ca_address_sk#16, ca_state#17] +Condition : (ca_state#17 IN (KY,GA,NM) AND isnotnull(ca_address_sk#16)) + +(29) Project [codegen id : 7] +Output [1]: [ca_address_sk#16] +Input [2]: [ca_address_sk#16, ca_state#17] + +(30) BroadcastExchange +Input [1]: [ca_address_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(31) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#3] +Right keys [1]: [ca_address_sk#16] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 9] +Output [1]: [c_current_cdemo_sk#2] +Input [3]: [c_current_cdemo_sk#2, c_current_addr_sk#3, ca_address_sk#16] + +(33) Scan parquet spark_catalog.default.customer_demographics +Output [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(34) ColumnarToRow [codegen id : 8] +Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] + +(35) Filter [codegen id : 8] +Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Condition : isnotnull(cd_demo_sk#18) + +(36) BroadcastExchange +Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#18] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 9] +Output [5]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Input [7]: [c_current_cdemo_sk#2, cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] + +(39) HashAggregate [codegen id : 9] +Input [5]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Keys [5]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#24] +Results [6]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23, count#25] + +(40) Exchange +Input [6]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23, count#25] +Arguments: hashpartitioning(cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 10] +Input [6]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23, count#25] +Keys [5]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#26] +Results [8]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, count(1)#26 AS cnt1#27, cd_purchase_estimate#22, count(1)#26 AS cnt2#28, cd_credit_rating#23, count(1)#26 AS cnt3#29] + +(42) TakeOrderedAndProject +Input [8]: [cd_gender#19, cd_marital_status#20, cd_education_status#21, cnt1#27, cd_purchase_estimate#22, cnt2#28, cd_credit_rating#23, cnt3#29] +Arguments: 100, [cd_gender#19 ASC NULLS FIRST, cd_marital_status#20 ASC NULLS FIRST, cd_education_status#21 ASC NULLS FIRST, cd_purchase_estimate#22 ASC NULLS FIRST, cd_credit_rating#23 ASC NULLS FIRST], [cd_gender#19, cd_marital_status#20, cd_education_status#21, cnt1#27, cd_purchase_estimate#22, cnt2#28, cd_credit_rating#23, cnt3#29] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (47) ++- * Project (46) + +- * Filter (45) + +- * ColumnarToRow (44) + +- CometScan parquet spark_catalog.default.date_dim (43) + + +(43) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#30, d_moy#31] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), GreaterThanOrEqual(d_moy,4), LessThanOrEqual(d_moy,6), IsNotNull(d_date_sk)] +ReadSchema: struct + +(44) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#30, d_moy#31] + +(45) Filter [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#30, d_moy#31] +Condition : (((((isnotnull(d_year#30) AND isnotnull(d_moy#31)) AND (d_year#30 = 2001)) AND (d_moy#31 >= 4)) AND (d_moy#31 <= 6)) AND isnotnull(d_date_sk#7)) + +(46) Project [codegen id : 1] +Output [1]: [d_date_sk#7] +Input [3]: [d_date_sk#7, d_year#30, d_moy#31] + +(47) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#9 IN dynamicpruning#6 + +Subquery:3 Hosting operator id = 18 Hosting Expression = cs_sold_date_sk#13 IN dynamicpruning#6 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/simplified.txt new file mode 100644 index 000000000..90f6fc876 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/simplified.txt @@ -0,0 +1,74 @@ +TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cnt1,cnt2,cnt3] + WholeStageCodegen (10) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,count] [count(1),cnt1,cnt2,cnt3,count] + InputAdapter + Exchange [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating] #1 + WholeStageCodegen (9) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating] [count,count] + Project [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_current_addr_sk,c_current_cdemo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + Project [ca_address_sk] + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + Filter [cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/explain.txt new file mode 100644 index 000000000..47e7253dd --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/explain.txt @@ -0,0 +1,208 @@ +== Physical Plan == +TakeOrderedAndProject (30) ++- * HashAggregate (29) + +- Exchange (28) + +- * HashAggregate (27) + +- * Project (26) + +- * BroadcastHashJoin Inner BuildRight (25) + :- * Project (19) + : +- * BroadcastHashJoin Inner BuildRight (18) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (10) + : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (8) + : : : +- * Project (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : +- ReusedExchange (11) + : +- BroadcastExchange (17) + : +- * Filter (16) + : +- * ColumnarToRow (15) + : +- CometScan parquet spark_catalog.default.item (14) + +- BroadcastExchange (24) + +- * Project (23) + +- * Filter (22) + +- * ColumnarToRow (21) + +- CometScan parquet spark_catalog.default.promotion (20) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_item_sk), IsNotNull(ss_promo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] + +(3) Filter [codegen id : 5] +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] + +(6) Filter [codegen id : 1] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#10)) + +(7) Project [codegen id : 1] +Output [1]: [cd_demo_sk#10] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] + +(8) BroadcastExchange +Input [1]: [cd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 5] +Output [7]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Input [9]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, cd_demo_sk#10] + +(11) ReusedExchange [Reuses operator id: 35] +Output [1]: [d_date_sk#14] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [6]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7] +Input [8]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, d_date_sk#14] + +(14) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#15, i_item_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [2]: [i_item_sk#15, i_item_id#16] + +(16) Filter [codegen id : 3] +Input [2]: [i_item_sk#15, i_item_id#16] +Condition : isnotnull(i_item_sk#15) + +(17) BroadcastExchange +Input [2]: [i_item_sk#15, i_item_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#15] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 5] +Output [6]: [ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#16] +Input [8]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_sk#15, i_item_id#16] + +(20) Scan parquet spark_catalog.default.promotion +Output [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [Or(EqualTo(p_channel_email,N),EqualTo(p_channel_event,N)), IsNotNull(p_promo_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] + +(22) Filter [codegen id : 4] +Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Condition : (((p_channel_email#18 = N) OR (p_channel_event#19 = N)) AND isnotnull(p_promo_sk#17)) + +(23) Project [codegen id : 4] +Output [1]: [p_promo_sk#17] +Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] + +(24) BroadcastExchange +Input [1]: [p_promo_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(25) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_promo_sk#3] +Right keys [1]: [p_promo_sk#17] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 5] +Output [5]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#16] +Input [7]: [ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#16, p_promo_sk#17] + +(27) HashAggregate [codegen id : 5] +Input [5]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#16] +Keys [1]: [i_item_id#16] +Functions [4]: [partial_avg(ss_quantity#4), partial_avg(UnscaledValue(ss_list_price#5)), partial_avg(UnscaledValue(ss_coupon_amt#7)), partial_avg(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [8]: [sum#20, count#21, sum#22, count#23, sum#24, count#25, sum#26, count#27] +Results [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] + +(28) Exchange +Input [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] +Arguments: hashpartitioning(i_item_id#16, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 6] +Input [9]: [i_item_id#16, sum#28, count#29, sum#30, count#31, sum#32, count#33, sum#34, count#35] +Keys [1]: [i_item_id#16] +Functions [4]: [avg(ss_quantity#4), avg(UnscaledValue(ss_list_price#5)), avg(UnscaledValue(ss_coupon_amt#7)), avg(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [4]: [avg(ss_quantity#4)#36, avg(UnscaledValue(ss_list_price#5))#37, avg(UnscaledValue(ss_coupon_amt#7))#38, avg(UnscaledValue(ss_sales_price#6))#39] +Results [5]: [i_item_id#16, avg(ss_quantity#4)#36 AS agg1#40, cast((avg(UnscaledValue(ss_list_price#5))#37 / 100.0) as decimal(11,6)) AS agg2#41, cast((avg(UnscaledValue(ss_coupon_amt#7))#38 / 100.0) as decimal(11,6)) AS agg3#42, cast((avg(UnscaledValue(ss_sales_price#6))#39 / 100.0) as decimal(11,6)) AS agg4#43] + +(30) TakeOrderedAndProject +Input [5]: [i_item_id#16, agg1#40, agg2#41, agg3#42, agg4#43] +Arguments: 100, [i_item_id#16 ASC NULLS FIRST], [i_item_id#16, agg1#40, agg2#41, agg3#42, agg4#43] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (35) ++- * Project (34) + +- * Filter (33) + +- * ColumnarToRow (32) + +- CometScan parquet spark_catalog.default.date_dim (31) + + +(31) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#44] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#44] + +(33) Filter [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#44] +Condition : ((isnotnull(d_year#44) AND (d_year#44 = 2000)) AND isnotnull(d_date_sk#14)) + +(34) Project [codegen id : 1] +Output [1]: [d_date_sk#14] +Input [2]: [d_date_sk#14, d_year#44] + +(35) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/simplified.txt new file mode 100644 index 000000000..c09f5ad55 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/simplified.txt @@ -0,0 +1,52 @@ +TakeOrderedAndProject [i_item_id,agg1,agg2,agg3,agg4] + WholeStageCodegen (6) + HashAggregate [i_item_id,sum,count,sum,count,sum,count,sum,count] [avg(ss_quantity),avg(UnscaledValue(ss_list_price)),avg(UnscaledValue(ss_coupon_amt)),avg(UnscaledValue(ss_sales_price)),agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (5) + HashAggregate [i_item_id,ss_quantity,ss_list_price,ss_coupon_amt,ss_sales_price] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,i_item_id] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_promo_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,i_item_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_promo_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_promo_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Filter [ss_cdemo_sk,ss_item_sk,ss_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_promo_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [cd_demo_sk] + Filter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Project [p_promo_sk] + Filter [p_channel_email,p_channel_event,p_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_email,p_channel_event] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/explain.txt new file mode 100644 index 000000000..f96ee1932 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/explain.txt @@ -0,0 +1,283 @@ +== Physical Plan == +TakeOrderedAndProject (43) ++- * Project (42) + +- Window (41) + +- * Sort (40) + +- Exchange (39) + +- * HashAggregate (38) + +- Exchange (37) + +- * HashAggregate (36) + +- * Expand (35) + +- * Project (34) + +- * BroadcastHashJoin Inner BuildRight (33) + :- * Project (6) + : +- * BroadcastHashJoin Inner BuildRight (5) + : :- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.store_sales (1) + : +- ReusedExchange (4) + +- BroadcastExchange (32) + +- * BroadcastHashJoin LeftSemi BuildRight (31) + :- * Filter (9) + : +- * ColumnarToRow (8) + : +- CometScan parquet spark_catalog.default.store (7) + +- BroadcastExchange (30) + +- * Project (29) + +- * Filter (28) + +- Window (27) + +- WindowGroupLimit (26) + +- * Sort (25) + +- * HashAggregate (24) + +- Exchange (23) + +- * HashAggregate (22) + +- * Project (21) + +- * BroadcastHashJoin Inner BuildRight (20) + :- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Filter (12) + : : +- * ColumnarToRow (11) + : : +- CometScan parquet spark_catalog.default.store_sales (10) + : +- BroadcastExchange (16) + : +- * Filter (15) + : +- * ColumnarToRow (14) + : +- CometScan parquet spark_catalog.default.store (13) + +- ReusedExchange (19) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 8] +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] + +(3) Filter [codegen id : 8] +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) + +(4) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 8] +Output [2]: [ss_store_sk#1, ss_net_profit#2] +Input [4]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#6, s_county#7, s_state#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 7] +Input [3]: [s_store_sk#6, s_county#7, s_state#8] + +(9) Filter [codegen id : 7] +Input [3]: [s_store_sk#6, s_county#7, s_state#8] +Condition : isnotnull(s_store_sk#6) + +(10) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 4] +Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] + +(12) Filter [codegen id : 4] +Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_store_sk#9) + +(13) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#13, s_state#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#13, s_state#14] + +(15) Filter [codegen id : 2] +Input [2]: [s_store_sk#13, s_state#14] +Condition : isnotnull(s_store_sk#13) + +(16) BroadcastExchange +Input [2]: [s_store_sk#13, s_state#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#9] +Right keys [1]: [s_store_sk#13] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [3]: [ss_net_profit#10, ss_sold_date_sk#11, s_state#14] +Input [5]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11, s_store_sk#13, s_state#14] + +(19) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#15] + +(20) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#15] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 4] +Output [2]: [ss_net_profit#10, s_state#14] +Input [4]: [ss_net_profit#10, ss_sold_date_sk#11, s_state#14, d_date_sk#15] + +(22) HashAggregate [codegen id : 4] +Input [2]: [ss_net_profit#10, s_state#14] +Keys [1]: [s_state#14] +Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#10))] +Aggregate Attributes [1]: [sum#16] +Results [2]: [s_state#14, sum#17] + +(23) Exchange +Input [2]: [s_state#14, sum#17] +Arguments: hashpartitioning(s_state#14, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(24) HashAggregate [codegen id : 5] +Input [2]: [s_state#14, sum#17] +Keys [1]: [s_state#14] +Functions [1]: [sum(UnscaledValue(ss_net_profit#10))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#10))#18] +Results [3]: [s_state#14, MakeDecimal(sum(UnscaledValue(ss_net_profit#10))#18,17,2) AS _w0#19, s_state#14] + +(25) Sort [codegen id : 5] +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [s_state#14 ASC NULLS FIRST, _w0#19 DESC NULLS LAST], false, 0 + +(26) WindowGroupLimit +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [s_state#14], [_w0#19 DESC NULLS LAST], rank(_w0#19), 5, Final + +(27) Window +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [rank(_w0#19) windowspecdefinition(s_state#14, _w0#19 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS ranking#20], [s_state#14], [_w0#19 DESC NULLS LAST] + +(28) Filter [codegen id : 6] +Input [4]: [s_state#14, _w0#19, s_state#14, ranking#20] +Condition : (ranking#20 <= 5) + +(29) Project [codegen id : 6] +Output [1]: [s_state#14] +Input [4]: [s_state#14, _w0#19, s_state#14, ranking#20] + +(30) BroadcastExchange +Input [1]: [s_state#14] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=3] + +(31) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [s_state#8] +Right keys [1]: [s_state#14] +Join type: LeftSemi +Join condition: None + +(32) BroadcastExchange +Input [3]: [s_store_sk#6, s_county#7, s_state#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(33) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#6] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 8] +Output [3]: [ss_net_profit#2, s_state#8, s_county#7] +Input [5]: [ss_store_sk#1, ss_net_profit#2, s_store_sk#6, s_county#7, s_state#8] + +(35) Expand [codegen id : 8] +Input [3]: [ss_net_profit#2, s_state#8, s_county#7] +Arguments: [[ss_net_profit#2, s_state#8, s_county#7, 0], [ss_net_profit#2, s_state#8, null, 1], [ss_net_profit#2, null, null, 3]], [ss_net_profit#2, s_state#21, s_county#22, spark_grouping_id#23] + +(36) HashAggregate [codegen id : 8] +Input [4]: [ss_net_profit#2, s_state#21, s_county#22, spark_grouping_id#23] +Keys [3]: [s_state#21, s_county#22, spark_grouping_id#23] +Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum#24] +Results [4]: [s_state#21, s_county#22, spark_grouping_id#23, sum#25] + +(37) Exchange +Input [4]: [s_state#21, s_county#22, spark_grouping_id#23, sum#25] +Arguments: hashpartitioning(s_state#21, s_county#22, spark_grouping_id#23, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(38) HashAggregate [codegen id : 9] +Input [4]: [s_state#21, s_county#22, spark_grouping_id#23, sum#25] +Keys [3]: [s_state#21, s_county#22, spark_grouping_id#23] +Functions [1]: [sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#2))#26] +Results [7]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#2))#26,17,2) AS total_sum#27, s_state#21, s_county#22, (cast((shiftright(spark_grouping_id#23, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#23, 0) & 1) as tinyint)) AS lochierarchy#28, MakeDecimal(sum(UnscaledValue(ss_net_profit#2))#26,17,2) AS _w0#29, (cast((shiftright(spark_grouping_id#23, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#23, 0) & 1) as tinyint)) AS _w1#30, CASE WHEN (cast((shiftright(spark_grouping_id#23, 0) & 1) as tinyint) = 0) THEN s_state#21 END AS _w2#31] + +(39) Exchange +Input [7]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, _w0#29, _w1#30, _w2#31] +Arguments: hashpartitioning(_w1#30, _w2#31, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(40) Sort [codegen id : 10] +Input [7]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, _w0#29, _w1#30, _w2#31] +Arguments: [_w1#30 ASC NULLS FIRST, _w2#31 ASC NULLS FIRST, _w0#29 DESC NULLS LAST], false, 0 + +(41) Window +Input [7]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, _w0#29, _w1#30, _w2#31] +Arguments: [rank(_w0#29) windowspecdefinition(_w1#30, _w2#31, _w0#29 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#32], [_w1#30, _w2#31], [_w0#29 DESC NULLS LAST] + +(42) Project [codegen id : 11] +Output [5]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, rank_within_parent#32] +Input [8]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, _w0#29, _w1#30, _w2#31, rank_within_parent#32] + +(43) TakeOrderedAndProject +Input [5]: [total_sum#27, s_state#21, s_county#22, lochierarchy#28, rank_within_parent#32] +Arguments: 100, [lochierarchy#28 DESC NULLS LAST, CASE WHEN (lochierarchy#28 = 0) THEN s_state#21 END ASC NULLS FIRST, rank_within_parent#32 ASC NULLS FIRST], [total_sum#27, s_state#21, s_county#22, lochierarchy#28, rank_within_parent#32] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (48) ++- * Project (47) + +- * Filter (46) + +- * ColumnarToRow (45) + +- CometScan parquet spark_catalog.default.date_dim (44) + + +(44) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#33] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#33] + +(46) Filter [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#33] +Condition : (((isnotnull(d_month_seq#33) AND (d_month_seq#33 >= 1200)) AND (d_month_seq#33 <= 1211)) AND isnotnull(d_date_sk#5)) + +(47) Project [codegen id : 1] +Output [1]: [d_date_sk#5] +Input [2]: [d_date_sk#5, d_month_seq#33] + +(48) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/simplified.txt new file mode 100644 index 000000000..a15af5f94 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/simplified.txt @@ -0,0 +1,75 @@ +TakeOrderedAndProject [lochierarchy,s_state,rank_within_parent,total_sum,s_county] + WholeStageCodegen (11) + Project [total_sum,s_state,s_county,lochierarchy,rank_within_parent] + InputAdapter + Window [_w0,_w1,_w2] + WholeStageCodegen (10) + Sort [_w1,_w2,_w0] + InputAdapter + Exchange [_w1,_w2] #1 + WholeStageCodegen (9) + HashAggregate [s_state,s_county,spark_grouping_id,sum] [sum(UnscaledValue(ss_net_profit)),total_sum,lochierarchy,_w0,_w1,_w2,sum] + InputAdapter + Exchange [s_state,s_county,spark_grouping_id] #2 + WholeStageCodegen (8) + HashAggregate [s_state,s_county,spark_grouping_id,ss_net_profit] [sum,sum] + Expand [ss_net_profit,s_state,s_county] + Project [ss_net_profit,s_state,s_county] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + BroadcastHashJoin [s_state,s_state] + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_county,s_state] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (6) + Project [s_state] + Filter [ranking] + InputAdapter + Window [_w0,s_state] + WindowGroupLimit [s_state,_w0] + WholeStageCodegen (5) + Sort [s_state,_w0] + HashAggregate [sum] [sum(UnscaledValue(ss_net_profit)),_w0,s_state,sum] + InputAdapter + Exchange [s_state] #6 + WholeStageCodegen (4) + HashAggregate [s_state,ss_net_profit] [sum,sum] + Project [ss_net_profit,s_state] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_net_profit,ss_sold_date_sk,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (2) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/explain.txt new file mode 100644 index 000000000..8bf7d4c97 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/explain.txt @@ -0,0 +1,254 @@ +== Physical Plan == +* Sort (38) ++- Exchange (37) + +- * HashAggregate (36) + +- Exchange (35) + +- * HashAggregate (34) + +- * Project (33) + +- * BroadcastHashJoin Inner BuildRight (32) + :- * Project (26) + : +- * BroadcastHashJoin Inner BuildLeft (25) + : :- BroadcastExchange (5) + : : +- * Project (4) + : : +- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.item (1) + : +- Union (24) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildRight (10) + : : :- * Filter (8) + : : : +- * ColumnarToRow (7) + : : : +- CometScan parquet spark_catalog.default.web_sales (6) + : : +- ReusedExchange (9) + : :- * Project (17) + : : +- * BroadcastHashJoin Inner BuildRight (16) + : : :- * Filter (14) + : : : +- * ColumnarToRow (13) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (12) + : : +- ReusedExchange (15) + : +- * Project (23) + : +- * BroadcastHashJoin Inner BuildRight (22) + : :- * Filter (20) + : : +- * ColumnarToRow (19) + : : +- CometScan parquet spark_catalog.default.store_sales (18) + : +- ReusedExchange (21) + +- BroadcastExchange (31) + +- * Project (30) + +- * Filter (29) + +- * ColumnarToRow (28) + +- CometScan parquet spark_catalog.default.time_dim (27) + + +(1) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#1, i_brand_id#2, i_brand#3, i_manager_id#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,1), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [4]: [i_item_sk#1, i_brand_id#2, i_brand#3, i_manager_id#4] + +(3) Filter [codegen id : 1] +Input [4]: [i_item_sk#1, i_brand_id#2, i_brand#3, i_manager_id#4] +Condition : ((isnotnull(i_manager_id#4) AND (i_manager_id#4 = 1)) AND isnotnull(i_item_sk#1)) + +(4) Project [codegen id : 1] +Output [3]: [i_item_sk#1, i_brand_id#2, i_brand#3] +Input [4]: [i_item_sk#1, i_brand_id#2, i_brand#3, i_manager_id#4] + +(5) BroadcastExchange +Input [3]: [i_item_sk#1, i_brand_id#2, i_brand#3] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(6) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_sold_time_sk#5, ws_item_sk#6, ws_ext_sales_price#7, ws_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#8), dynamicpruningexpression(ws_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_sold_time_sk)] +ReadSchema: struct + +(7) ColumnarToRow [codegen id : 3] +Input [4]: [ws_sold_time_sk#5, ws_item_sk#6, ws_ext_sales_price#7, ws_sold_date_sk#8] + +(8) Filter [codegen id : 3] +Input [4]: [ws_sold_time_sk#5, ws_item_sk#6, ws_ext_sales_price#7, ws_sold_date_sk#8] +Condition : (isnotnull(ws_item_sk#6) AND isnotnull(ws_sold_time_sk#5)) + +(9) ReusedExchange [Reuses operator id: 43] +Output [1]: [d_date_sk#10] + +(10) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 3] +Output [3]: [ws_ext_sales_price#7 AS ext_price#11, ws_item_sk#6 AS sold_item_sk#12, ws_sold_time_sk#5 AS time_sk#13] +Input [5]: [ws_sold_time_sk#5, ws_item_sk#6, ws_ext_sales_price#7, ws_sold_date_sk#8, d_date_sk#10] + +(12) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_sold_time_sk#14, cs_item_sk#15, cs_ext_sales_price#16, cs_sold_date_sk#17] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_sold_date_sk#17 IN dynamicpruning#18)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_sold_time_sk)] +ReadSchema: struct + +(13) ColumnarToRow [codegen id : 5] +Input [4]: [cs_sold_time_sk#14, cs_item_sk#15, cs_ext_sales_price#16, cs_sold_date_sk#17] + +(14) Filter [codegen id : 5] +Input [4]: [cs_sold_time_sk#14, cs_item_sk#15, cs_ext_sales_price#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_item_sk#15) AND isnotnull(cs_sold_time_sk#14)) + +(15) ReusedExchange [Reuses operator id: 43] +Output [1]: [d_date_sk#19] + +(16) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_sold_date_sk#17] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 5] +Output [3]: [cs_ext_sales_price#16 AS ext_price#20, cs_item_sk#15 AS sold_item_sk#21, cs_sold_time_sk#14 AS time_sk#22] +Input [5]: [cs_sold_time_sk#14, cs_item_sk#15, cs_ext_sales_price#16, cs_sold_date_sk#17, d_date_sk#19] + +(18) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#23, ss_item_sk#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_sold_date_sk#26 IN dynamicpruning#27)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_sold_time_sk)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 7] +Input [4]: [ss_sold_time_sk#23, ss_item_sk#24, ss_ext_sales_price#25, ss_sold_date_sk#26] + +(20) Filter [codegen id : 7] +Input [4]: [ss_sold_time_sk#23, ss_item_sk#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Condition : (isnotnull(ss_item_sk#24) AND isnotnull(ss_sold_time_sk#23)) + +(21) ReusedExchange [Reuses operator id: 43] +Output [1]: [d_date_sk#28] + +(22) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_sold_date_sk#26] +Right keys [1]: [d_date_sk#28] +Join type: Inner +Join condition: None + +(23) Project [codegen id : 7] +Output [3]: [ss_ext_sales_price#25 AS ext_price#29, ss_item_sk#24 AS sold_item_sk#30, ss_sold_time_sk#23 AS time_sk#31] +Input [5]: [ss_sold_time_sk#23, ss_item_sk#24, ss_ext_sales_price#25, ss_sold_date_sk#26, d_date_sk#28] + +(24) Union + +(25) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [sold_item_sk#12] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 9] +Output [4]: [i_brand_id#2, i_brand#3, ext_price#11, time_sk#13] +Input [6]: [i_item_sk#1, i_brand_id#2, i_brand#3, ext_price#11, sold_item_sk#12, time_sk#13] + +(27) Scan parquet spark_catalog.default.time_dim +Output [4]: [t_time_sk#32, t_hour#33, t_minute#34, t_meal_time#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [Or(EqualTo(t_meal_time,breakfast ),EqualTo(t_meal_time,dinner )), IsNotNull(t_time_sk)] +ReadSchema: struct + +(28) ColumnarToRow [codegen id : 8] +Input [4]: [t_time_sk#32, t_hour#33, t_minute#34, t_meal_time#35] + +(29) Filter [codegen id : 8] +Input [4]: [t_time_sk#32, t_hour#33, t_minute#34, t_meal_time#35] +Condition : (((t_meal_time#35 = breakfast ) OR (t_meal_time#35 = dinner )) AND isnotnull(t_time_sk#32)) + +(30) Project [codegen id : 8] +Output [3]: [t_time_sk#32, t_hour#33, t_minute#34] +Input [4]: [t_time_sk#32, t_hour#33, t_minute#34, t_meal_time#35] + +(31) BroadcastExchange +Input [3]: [t_time_sk#32, t_hour#33, t_minute#34] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [time_sk#13] +Right keys [1]: [t_time_sk#32] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [5]: [i_brand_id#2, i_brand#3, ext_price#11, t_hour#33, t_minute#34] +Input [7]: [i_brand_id#2, i_brand#3, ext_price#11, time_sk#13, t_time_sk#32, t_hour#33, t_minute#34] + +(34) HashAggregate [codegen id : 9] +Input [5]: [i_brand_id#2, i_brand#3, ext_price#11, t_hour#33, t_minute#34] +Keys [4]: [i_brand#3, i_brand_id#2, t_hour#33, t_minute#34] +Functions [1]: [partial_sum(UnscaledValue(ext_price#11))] +Aggregate Attributes [1]: [sum#36] +Results [5]: [i_brand#3, i_brand_id#2, t_hour#33, t_minute#34, sum#37] + +(35) Exchange +Input [5]: [i_brand#3, i_brand_id#2, t_hour#33, t_minute#34, sum#37] +Arguments: hashpartitioning(i_brand#3, i_brand_id#2, t_hour#33, t_minute#34, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(36) HashAggregate [codegen id : 10] +Input [5]: [i_brand#3, i_brand_id#2, t_hour#33, t_minute#34, sum#37] +Keys [4]: [i_brand#3, i_brand_id#2, t_hour#33, t_minute#34] +Functions [1]: [sum(UnscaledValue(ext_price#11))] +Aggregate Attributes [1]: [sum(UnscaledValue(ext_price#11))#38] +Results [5]: [i_brand_id#2 AS brand_id#39, i_brand#3 AS brand#40, t_hour#33, t_minute#34, MakeDecimal(sum(UnscaledValue(ext_price#11))#38,17,2) AS ext_price#41] + +(37) Exchange +Input [5]: [brand_id#39, brand#40, t_hour#33, t_minute#34, ext_price#41] +Arguments: rangepartitioning(ext_price#41 DESC NULLS LAST, brand_id#39 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(38) Sort [codegen id : 11] +Input [5]: [brand_id#39, brand#40, t_hour#33, t_minute#34, ext_price#41] +Arguments: [ext_price#41 DESC NULLS LAST, brand_id#39 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 6 Hosting Expression = ws_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (43) ++- * Project (42) + +- * Filter (41) + +- * ColumnarToRow (40) + +- CometScan parquet spark_catalog.default.date_dim (39) + + +(39) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#42, d_moy#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(40) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#42, d_moy#43] + +(41) Filter [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#42, d_moy#43] +Condition : ((((isnotnull(d_moy#43) AND isnotnull(d_year#42)) AND (d_moy#43 = 11)) AND (d_year#42 = 1999)) AND isnotnull(d_date_sk#10)) + +(42) Project [codegen id : 1] +Output [1]: [d_date_sk#10] +Input [3]: [d_date_sk#10, d_year#42, d_moy#43] + +(43) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +Subquery:2 Hosting operator id = 12 Hosting Expression = cs_sold_date_sk#17 IN dynamicpruning#9 + +Subquery:3 Hosting operator id = 18 Hosting Expression = ss_sold_date_sk#26 IN dynamicpruning#9 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/simplified.txt new file mode 100644 index 000000000..c47e3e146 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/simplified.txt @@ -0,0 +1,69 @@ +WholeStageCodegen (11) + Sort [ext_price,brand_id] + InputAdapter + Exchange [ext_price,brand_id] #1 + WholeStageCodegen (10) + HashAggregate [i_brand,i_brand_id,t_hour,t_minute,sum] [sum(UnscaledValue(ext_price)),brand_id,brand,ext_price,sum] + InputAdapter + Exchange [i_brand,i_brand_id,t_hour,t_minute] #2 + WholeStageCodegen (9) + HashAggregate [i_brand,i_brand_id,t_hour,t_minute,ext_price] [sum,sum] + Project [i_brand_id,i_brand,ext_price,t_hour,t_minute] + BroadcastHashJoin [time_sk,t_time_sk] + Project [i_brand_id,i_brand,ext_price,time_sk] + BroadcastHashJoin [i_item_sk,sold_item_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [i_item_sk,i_brand_id,i_brand] + Filter [i_manager_id,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manager_id] + InputAdapter + Union + WholeStageCodegen (3) + Project [ws_ext_sales_price,ws_item_sk,ws_sold_time_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_item_sk,ws_sold_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_moy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (5) + Project [cs_ext_sales_price,cs_item_sk,cs_sold_time_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Filter [cs_item_sk,cs_sold_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_sold_time_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (7) + Project [ss_ext_sales_price,ss_item_sk,ss_sold_time_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_item_sk,ss_sold_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (8) + Project [t_time_sk,t_hour,t_minute] + Filter [t_meal_time,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute,t_meal_time] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/explain.txt new file mode 100644 index 000000000..35cc300bf --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/explain.txt @@ -0,0 +1,433 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * HashAggregate (69) + +- Exchange (68) + +- * HashAggregate (67) + +- * Project (66) + +- * SortMergeJoin LeftOuter (65) + :- * Sort (58) + : +- Exchange (57) + : +- * Project (56) + : +- * BroadcastHashJoin LeftOuter BuildRight (55) + : :- * Project (50) + : : +- * BroadcastHashJoin Inner BuildRight (49) + : : :- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * Project (38) + : : : : +- * BroadcastHashJoin Inner BuildRight (37) + : : : : :- * Project (35) + : : : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : : : :- * Project (28) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (27) + : : : : : : :- * Project (21) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : : :- * Project (15) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : : : : :- * Project (9) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : : : : :- * Filter (3) + : : : : : : : : : : +- * ColumnarToRow (2) + : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : : : : : +- BroadcastExchange (7) + : : : : : : : : : +- * Filter (6) + : : : : : : : : : +- * ColumnarToRow (5) + : : : : : : : : : +- CometScan parquet spark_catalog.default.inventory (4) + : : : : : : : : +- BroadcastExchange (13) + : : : : : : : : +- * Filter (12) + : : : : : : : : +- * ColumnarToRow (11) + : : : : : : : : +- CometScan parquet spark_catalog.default.warehouse (10) + : : : : : : : +- BroadcastExchange (19) + : : : : : : : +- * Filter (18) + : : : : : : : +- * ColumnarToRow (17) + : : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : : +- BroadcastExchange (26) + : : : : : : +- * Project (25) + : : : : : : +- * Filter (24) + : : : : : : +- * ColumnarToRow (23) + : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (22) + : : : : : +- BroadcastExchange (33) + : : : : : +- * Project (32) + : : : : : +- * Filter (31) + : : : : : +- * ColumnarToRow (30) + : : : : : +- CometScan parquet spark_catalog.default.household_demographics (29) + : : : : +- ReusedExchange (36) + : : : +- BroadcastExchange (42) + : : : +- * Filter (41) + : : : +- * ColumnarToRow (40) + : : : +- CometScan parquet spark_catalog.default.date_dim (39) + : : +- BroadcastExchange (48) + : : +- * Filter (47) + : : +- * ColumnarToRow (46) + : : +- CometScan parquet spark_catalog.default.date_dim (45) + : +- BroadcastExchange (54) + : +- * Filter (53) + : +- * ColumnarToRow (52) + : +- CometScan parquet spark_catalog.default.promotion (51) + +- * Sort (64) + +- Exchange (63) + +- * Project (62) + +- * Filter (61) + +- * ColumnarToRow (60) + +- CometScan parquet spark_catalog.default.catalog_returns (59) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#8), dynamicpruningexpression(cs_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(cs_quantity), IsNotNull(cs_item_sk), IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_hdemo_sk), IsNotNull(cs_ship_date_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 10] +Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] + +(3) Filter [codegen id : 10] +Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] +Condition : ((((isnotnull(cs_quantity#7) AND isnotnull(cs_item_sk#4)) AND isnotnull(cs_bill_cdemo_sk#2)) AND isnotnull(cs_bill_hdemo_sk#3)) AND isnotnull(cs_ship_date_sk#1)) + +(4) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#13)] +PushedFilters: [IsNotNull(inv_quantity_on_hand), IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] + +(6) Filter [codegen id : 1] +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Condition : ((isnotnull(inv_quantity_on_hand#12) AND isnotnull(inv_item_sk#10)) AND isnotnull(inv_warehouse_sk#11)) + +(7) BroadcastExchange +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_item_sk#4] +Right keys [1]: [inv_item_sk#10] +Join type: Inner +Join condition: (inv_quantity_on_hand#12 < cs_quantity#7) + +(9) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_warehouse_sk#11, inv_date_sk#13] +Input [12]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8, inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] + +(10) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] + +(12) Filter [codegen id : 2] +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Condition : isnotnull(w_warehouse_sk#14) + +(13) BroadcastExchange +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [inv_warehouse_sk#11] +Right keys [1]: [w_warehouse_sk#14] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_warehouse_sk#11, inv_date_sk#13, w_warehouse_sk#14, w_warehouse_name#15] + +(16) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#16, i_item_desc#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 3] +Input [2]: [i_item_sk#16, i_item_desc#17] + +(18) Filter [codegen id : 3] +Input [2]: [i_item_sk#16, i_item_desc#17] +Condition : isnotnull(i_item_sk#16) + +(19) BroadcastExchange +Input [2]: [i_item_sk#16, i_item_desc#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_item_sk#4] +Right keys [1]: [i_item_sk#16] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 10] +Output [10]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_sk#16, i_item_desc#17] + +(22) Scan parquet spark_catalog.default.customer_demographics +Output [2]: [cd_demo_sk#18, cd_marital_status#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_marital_status), EqualTo(cd_marital_status,D), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 4] +Input [2]: [cd_demo_sk#18, cd_marital_status#19] + +(24) Filter [codegen id : 4] +Input [2]: [cd_demo_sk#18, cd_marital_status#19] +Condition : ((isnotnull(cd_marital_status#19) AND (cd_marital_status#19 = D)) AND isnotnull(cd_demo_sk#18)) + +(25) Project [codegen id : 4] +Output [1]: [cd_demo_sk#18] +Input [2]: [cd_demo_sk#18, cd_marital_status#19] + +(26) BroadcastExchange +Input [1]: [cd_demo_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(27) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_bill_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#18] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, cd_demo_sk#18] + +(29) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#20, hd_buy_potential#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_buy_potential), EqualTo(hd_buy_potential,>10000 ), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 5] +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] + +(31) Filter [codegen id : 5] +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Condition : ((isnotnull(hd_buy_potential#21) AND (hd_buy_potential#21 = >10000 )) AND isnotnull(hd_demo_sk#20)) + +(32) Project [codegen id : 5] +Output [1]: [hd_demo_sk#20] +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] + +(33) BroadcastExchange +Input [1]: [hd_demo_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_bill_hdemo_sk#3] +Right keys [1]: [hd_demo_sk#20] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [8]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [10]: [cs_ship_date_sk#1, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, hd_demo_sk#20] + +(36) ReusedExchange [Reuses operator id: 75] +Output [3]: [d_date_sk#22, d_date#23, d_week_seq#24] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#8] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24] +Input [11]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date_sk#22, d_date#23, d_week_seq#24] + +(39) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_week_seq#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), IsNotNull(d_date_sk)] +ReadSchema: struct + +(40) ColumnarToRow [codegen id : 7] +Input [2]: [d_date_sk#25, d_week_seq#26] + +(41) Filter [codegen id : 7] +Input [2]: [d_date_sk#25, d_week_seq#26] +Condition : (isnotnull(d_week_seq#26) AND isnotnull(d_date_sk#25)) + +(42) BroadcastExchange +Input [2]: [d_date_sk#25, d_week_seq#26] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, false] as bigint), 32) | (cast(input[0, int, false] as bigint) & 4294967295))),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [d_week_seq#24, inv_date_sk#13] +Right keys [2]: [d_week_seq#26, d_date_sk#25] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 10] +Output [8]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24] +Input [11]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24, d_date_sk#25, d_week_seq#26] + +(45) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#27, d_date#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), IsNotNull(d_date_sk)] +ReadSchema: struct + +(46) ColumnarToRow [codegen id : 8] +Input [2]: [d_date_sk#27, d_date#28] + +(47) Filter [codegen id : 8] +Input [2]: [d_date_sk#27, d_date#28] +Condition : (isnotnull(d_date#28) AND isnotnull(d_date_sk#27)) + +(48) BroadcastExchange +Input [2]: [d_date_sk#27, d_date#28] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(49) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_ship_date_sk#1] +Right keys [1]: [d_date_sk#27] +Join type: Inner +Join condition: (d_date#28 > date_add(d_date#23, 5)) + +(50) Project [codegen id : 10] +Output [6]: [cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [10]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24, d_date_sk#27, d_date#28] + +(51) Scan parquet spark_catalog.default.promotion +Output [1]: [p_promo_sk#29] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_promo_sk)] +ReadSchema: struct + +(52) ColumnarToRow [codegen id : 9] +Input [1]: [p_promo_sk#29] + +(53) Filter [codegen id : 9] +Input [1]: [p_promo_sk#29] +Condition : isnotnull(p_promo_sk#29) + +(54) BroadcastExchange +Input [1]: [p_promo_sk#29] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(55) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_promo_sk#5] +Right keys [1]: [p_promo_sk#29] +Join type: LeftOuter +Join condition: None + +(56) Project [codegen id : 10] +Output [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [7]: [cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24, p_promo_sk#29] + +(57) Exchange +Input [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Arguments: hashpartitioning(cs_item_sk#4, cs_order_number#6, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(58) Sort [codegen id : 11] +Input [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Arguments: [cs_item_sk#4 ASC NULLS FIRST, cs_order_number#6 ASC NULLS FIRST], false, 0 + +(59) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(60) ColumnarToRow [codegen id : 12] +Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] + +(61) Filter [codegen id : 12] +Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Condition : (isnotnull(cr_item_sk#30) AND isnotnull(cr_order_number#31)) + +(62) Project [codegen id : 12] +Output [2]: [cr_item_sk#30, cr_order_number#31] +Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] + +(63) Exchange +Input [2]: [cr_item_sk#30, cr_order_number#31] +Arguments: hashpartitioning(cr_item_sk#30, cr_order_number#31, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(64) Sort [codegen id : 13] +Input [2]: [cr_item_sk#30, cr_order_number#31] +Arguments: [cr_item_sk#30 ASC NULLS FIRST, cr_order_number#31 ASC NULLS FIRST], false, 0 + +(65) SortMergeJoin [codegen id : 14] +Left keys [2]: [cs_item_sk#4, cs_order_number#6] +Right keys [2]: [cr_item_sk#30, cr_order_number#31] +Join type: LeftOuter +Join condition: None + +(66) Project [codegen id : 14] +Output [3]: [w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [7]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24, cr_item_sk#30, cr_order_number#31] + +(67) HashAggregate [codegen id : 14] +Input [3]: [w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Keys [3]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#33] +Results [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] + +(68) Exchange +Input [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] +Arguments: hashpartitioning(i_item_desc#17, w_warehouse_name#15, d_week_seq#24, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(69) HashAggregate [codegen id : 15] +Input [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] +Keys [3]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#35] +Results [6]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count(1)#35 AS no_promo#36, count(1)#35 AS promo#37, count(1)#35 AS total_cnt#38] + +(70) TakeOrderedAndProject +Input [6]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, no_promo#36, promo#37, total_cnt#38] +Arguments: 100, [total_cnt#38 DESC NULLS LAST, i_item_desc#17 ASC NULLS FIRST, w_warehouse_name#15 ASC NULLS FIRST, d_week_seq#24 ASC NULLS FIRST], [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, no_promo#36, promo#37, total_cnt#38] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (75) ++- * Project (74) + +- * Filter (73) + +- * ColumnarToRow (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk), IsNotNull(d_week_seq), IsNotNull(d_date)] +ReadSchema: struct + +(72) ColumnarToRow [codegen id : 1] +Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] + +(73) Filter [codegen id : 1] +Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Condition : ((((isnotnull(d_year#39) AND (d_year#39 = 1999)) AND isnotnull(d_date_sk#22)) AND isnotnull(d_week_seq#24)) AND isnotnull(d_date#23)) + +(74) Project [codegen id : 1] +Output [3]: [d_date_sk#22, d_date#23, d_week_seq#24] +Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] + +(75) BroadcastExchange +Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/simplified.txt new file mode 100644 index 000000000..59e1279ae --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/simplified.txt @@ -0,0 +1,116 @@ +TakeOrderedAndProject [total_cnt,i_item_desc,w_warehouse_name,d_week_seq,no_promo,promo] + WholeStageCodegen (15) + HashAggregate [i_item_desc,w_warehouse_name,d_week_seq,count] [count(1),no_promo,promo,total_cnt,count] + InputAdapter + Exchange [i_item_desc,w_warehouse_name,d_week_seq] #1 + WholeStageCodegen (14) + HashAggregate [i_item_desc,w_warehouse_name,d_week_seq] [count,count] + Project [w_warehouse_name,i_item_desc,d_week_seq] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (11) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #2 + WholeStageCodegen (10) + Project [cs_item_sk,cs_order_number,w_warehouse_name,i_item_desc,d_week_seq] + BroadcastHashJoin [cs_promo_sk,p_promo_sk] + Project [cs_item_sk,cs_promo_sk,cs_order_number,w_warehouse_name,i_item_desc,d_week_seq] + BroadcastHashJoin [cs_ship_date_sk,d_date_sk,d_date,d_date] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,w_warehouse_name,i_item_desc,d_date,d_week_seq] + BroadcastHashJoin [d_week_seq,inv_date_sk,d_week_seq,d_date_sk] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,inv_date_sk,w_warehouse_name,i_item_desc,d_date,d_week_seq] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_bill_hdemo_sk,hd_demo_sk] + Project [cs_ship_date_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_warehouse_sk,inv_date_sk] + BroadcastHashJoin [cs_item_sk,inv_item_sk,inv_quantity_on_hand,cs_quantity] + Filter [cs_quantity,cs_item_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_ship_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_quantity,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk,d_date,d_week_seq] + Filter [d_year,d_date_sk,d_week_seq,d_date] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_week_seq,d_year] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [inv_quantity_on_hand,inv_item_sk,inv_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (4) + Project [cd_demo_sk] + Filter [cd_marital_status,cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (5) + Project [hd_demo_sk] + Filter [hd_buy_potential,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential] + InputAdapter + ReusedExchange [d_date_sk,d_date,d_week_seq] #3 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (7) + Filter [d_week_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (9) + Filter [p_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.promotion [p_promo_sk] + InputAdapter + WholeStageCodegen (13) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #12 + WholeStageCodegen (12) + Project [cr_item_sk,cr_order_number] + Filter [cr_item_sk,cr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/explain.txt new file mode 100644 index 000000000..fb1ac906d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/explain.txt @@ -0,0 +1,218 @@ +== Physical Plan == +* Sort (32) ++- Exchange (31) + +- * Project (30) + +- * BroadcastHashJoin Inner BuildRight (29) + :- * Filter (24) + : +- * HashAggregate (23) + : +- Exchange (22) + : +- * HashAggregate (21) + : +- * Project (20) + : +- * BroadcastHashJoin Inner BuildRight (19) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * Project (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (18) + : +- * Project (17) + : +- * Filter (16) + : +- * ColumnarToRow (15) + : +- CometScan parquet spark_catalog.default.household_demographics (14) + +- BroadcastExchange (28) + +- * Filter (27) + +- * ColumnarToRow (26) + +- CometScan parquet spark_catalog.default.customer (25) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] + +(3) Filter [codegen id : 4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) + +(4) ReusedExchange [Reuses operator id: 37] +Output [1]: [d_date_sk#7] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4] +Input [6]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5, d_date_sk#7] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#8, s_county#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [In(s_county, [Bronx County,Franklin Parish,Orange County,Williamson County]), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#8, s_county#9] + +(9) Filter [codegen id : 2] +Input [2]: [s_store_sk#8, s_county#9] +Condition : (s_county#9 IN (Williamson County,Franklin Parish,Bronx County,Orange County) AND isnotnull(s_store_sk#8)) + +(10) Project [codegen id : 2] +Output [1]: [s_store_sk#8] +Input [2]: [s_store_sk#8, s_county#9] + +(11) BroadcastExchange +Input [1]: [s_store_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#8] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [3]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, s_store_sk#8] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_vehicle_count), Or(EqualTo(hd_buy_potential,>10000 ),EqualTo(hd_buy_potential,unknown )), GreaterThan(hd_vehicle_count,0), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] + +(16) Filter [codegen id : 3] +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Condition : ((((isnotnull(hd_vehicle_count#13) AND ((hd_buy_potential#11 = >10000 ) OR (hd_buy_potential#11 = unknown ))) AND (hd_vehicle_count#13 > 0)) AND CASE WHEN (hd_vehicle_count#13 > 0) THEN ((cast(hd_dep_count#12 as double) / cast(hd_vehicle_count#13 as double)) > 1.0) END) AND isnotnull(hd_demo_sk#10)) + +(17) Project [codegen id : 3] +Output [1]: [hd_demo_sk#10] +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#10] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 4] +Output [2]: [ss_customer_sk#1, ss_ticket_number#4] +Input [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4, hd_demo_sk#10] + +(21) HashAggregate [codegen id : 4] +Input [2]: [ss_customer_sk#1, ss_ticket_number#4] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#14] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] + +(22) Exchange +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Arguments: hashpartitioning(ss_ticket_number#4, ss_customer_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#16] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count(1)#16 AS cnt#17] + +(24) Filter [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17] +Condition : ((cnt#17 >= 1) AND (cnt#17 <= 5)) + +(25) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 5] +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(27) Filter [codegen id : 5] +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Condition : isnotnull(c_customer_sk#18) + +(28) BroadcastExchange +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#18] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 6] +Output [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Input [8]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17, c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(31) Exchange +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: rangepartitioning(cnt#17 DESC NULLS LAST, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 7] +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: [cnt#17 DESC NULLS LAST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (37) ++- * Project (36) + +- * Filter (35) + +- * ColumnarToRow (34) + +- CometScan parquet spark_catalog.default.date_dim (33) + + +(33) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#23, d_dom#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_dom), GreaterThanOrEqual(d_dom,1), LessThanOrEqual(d_dom,2), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(34) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] + +(35) Filter [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Condition : ((((isnotnull(d_dom#24) AND (d_dom#24 >= 1)) AND (d_dom#24 <= 2)) AND d_year#23 IN (1999,2000,2001)) AND isnotnull(d_date_sk#7)) + +(36) Project [codegen id : 1] +Output [1]: [d_date_sk#7] +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] + +(37) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/simplified.txt new file mode 100644 index 000000000..a2c50bb62 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/simplified.txt @@ -0,0 +1,56 @@ +WholeStageCodegen (7) + Sort [cnt] + InputAdapter + Exchange [cnt] #1 + WholeStageCodegen (6) + Project [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag,ss_ticket_number,cnt] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Filter [cnt] + HashAggregate [ss_ticket_number,ss_customer_sk,count] [count(1),cnt,count] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk] #2 + WholeStageCodegen (4) + HashAggregate [ss_ticket_number,ss_customer_sk] [count,count] + Project [ss_customer_sk,ss_ticket_number] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_ticket_number] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_dom,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [s_store_sk] + Filter [s_county,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_county] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Project [hd_demo_sk] + Filter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Filter [c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/explain.txt new file mode 100644 index 000000000..93c71adc4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/explain.txt @@ -0,0 +1,477 @@ +== Physical Plan == +TakeOrderedAndProject (71) ++- * Project (70) + +- * BroadcastHashJoin Inner BuildRight (69) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * Project (28) + : : +- * BroadcastHashJoin Inner BuildRight (27) + : : :- * Project (25) + : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : :- * Filter (19) + : : : : +- * ColumnarToRow (18) + : : : : +- CometScan parquet spark_catalog.default.customer (17) + : : : +- BroadcastExchange (23) + : : : +- * Filter (22) + : : : +- * ColumnarToRow (21) + : : : +- CometScan parquet spark_catalog.default.store_sales (20) + : : +- ReusedExchange (26) + : +- BroadcastExchange (50) + : +- * Filter (49) + : +- * HashAggregate (48) + : +- Exchange (47) + : +- * HashAggregate (46) + : +- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (42) + : : +- * BroadcastHashJoin Inner BuildRight (41) + : : :- * Filter (36) + : : : +- * ColumnarToRow (35) + : : : +- CometScan parquet spark_catalog.default.customer (34) + : : +- BroadcastExchange (40) + : : +- * Filter (39) + : : +- * ColumnarToRow (38) + : : +- CometScan parquet spark_catalog.default.web_sales (37) + : +- ReusedExchange (43) + +- BroadcastExchange (68) + +- * HashAggregate (67) + +- Exchange (66) + +- * HashAggregate (65) + +- * Project (64) + +- * BroadcastHashJoin Inner BuildRight (63) + :- * Project (61) + : +- * BroadcastHashJoin Inner BuildRight (60) + : :- * Filter (55) + : : +- * ColumnarToRow (54) + : : +- CometScan parquet spark_catalog.default.customer (53) + : +- BroadcastExchange (59) + : +- * Filter (58) + : +- * ColumnarToRow (57) + : +- CometScan parquet spark_catalog.default.web_sales (56) + +- ReusedExchange (62) + + +(1) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] + +(3) Filter [codegen id : 3] +Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] + +(6) Filter [codegen id : 1] +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Condition : isnotnull(ss_customer_sk#5) + +(7) BroadcastExchange +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, ss_sold_date_sk#7] +Input [7]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#9, d_year#10] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, d_year#10] +Input [7]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, ss_sold_date_sk#7, d_date_sk#9, d_year#10] + +(13) HashAggregate [codegen id : 3] +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, d_year#10] +Keys [4]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#6))] +Aggregate Attributes [1]: [sum#11] +Results [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] + +(14) Exchange +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] +Arguments: hashpartitioning(c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 16] +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] +Keys [4]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10] +Functions [1]: [sum(UnscaledValue(ss_net_paid#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#6))#13] +Results [2]: [c_customer_id#2 AS customer_id#14, MakeDecimal(sum(UnscaledValue(ss_net_paid#6))#13,17,2) AS year_total#15] + +(16) Filter [codegen id : 16] +Input [2]: [customer_id#14, year_total#15] +Condition : (isnotnull(year_total#15) AND (year_total#15 > 0.00)) + +(17) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 6] +Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] + +(19) Filter [codegen id : 6] +Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] +Condition : (isnotnull(c_customer_sk#16) AND isnotnull(c_customer_id#17)) + +(20) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#22), dynamicpruningexpression(ss_sold_date_sk#22 IN dynamicpruning#23)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] + +(22) Filter [codegen id : 4] +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Condition : isnotnull(ss_customer_sk#20) + +(23) BroadcastExchange +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_customer_sk#16] +Right keys [1]: [ss_customer_sk#20] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, ss_sold_date_sk#22] +Input [7]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19, ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] + +(26) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#24, d_year#25] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#22] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, d_year#25] +Input [7]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, ss_sold_date_sk#22, d_date_sk#24, d_year#25] + +(29) HashAggregate [codegen id : 6] +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, d_year#25] +Keys [4]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#21))] +Aggregate Attributes [1]: [sum#26] +Results [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] + +(30) Exchange +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] +Arguments: hashpartitioning(c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] +Keys [4]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25] +Functions [1]: [sum(UnscaledValue(ss_net_paid#21))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#21))#13] +Results [4]: [c_customer_id#17 AS customer_id#28, c_first_name#18 AS customer_first_name#29, c_last_name#19 AS customer_last_name#30, MakeDecimal(sum(UnscaledValue(ss_net_paid#21))#13,17,2) AS year_total#31] + +(32) BroadcastExchange +Input [4]: [customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#28] +Join type: Inner +Join condition: None + +(34) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 10] +Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] + +(36) Filter [codegen id : 10] +Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] +Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_customer_id#33)) + +(37) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#38), dynamicpruningexpression(ws_sold_date_sk#38 IN dynamicpruning#39)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(38) ColumnarToRow [codegen id : 8] +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] + +(39) Filter [codegen id : 8] +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Condition : isnotnull(ws_bill_customer_sk#36) + +(40) BroadcastExchange +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(41) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [c_customer_sk#32] +Right keys [1]: [ws_bill_customer_sk#36] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 10] +Output [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, ws_sold_date_sk#38] +Input [7]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35, ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] + +(43) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#40, d_year#41] + +(44) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#38] +Right keys [1]: [d_date_sk#40] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 10] +Output [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, d_year#41] +Input [7]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, ws_sold_date_sk#38, d_date_sk#40, d_year#41] + +(46) HashAggregate [codegen id : 10] +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, d_year#41] +Keys [4]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#37))] +Aggregate Attributes [1]: [sum#42] +Results [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] + +(47) Exchange +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] +Arguments: hashpartitioning(c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(48) HashAggregate [codegen id : 11] +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] +Keys [4]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41] +Functions [1]: [sum(UnscaledValue(ws_net_paid#37))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#37))#44] +Results [2]: [c_customer_id#33 AS customer_id#45, MakeDecimal(sum(UnscaledValue(ws_net_paid#37))#44,17,2) AS year_total#46] + +(49) Filter [codegen id : 11] +Input [2]: [customer_id#45, year_total#46] +Condition : (isnotnull(year_total#46) AND (year_total#46 > 0.00)) + +(50) BroadcastExchange +Input [2]: [customer_id#45, year_total#46] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(51) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#45] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 16] +Output [7]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, year_total#46] +Input [8]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, customer_id#45, year_total#46] + +(53) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(54) ColumnarToRow [codegen id : 14] +Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] + +(55) Filter [codegen id : 14] +Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] +Condition : (isnotnull(c_customer_sk#47) AND isnotnull(c_customer_id#48)) + +(56) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#53), dynamicpruningexpression(ws_sold_date_sk#53 IN dynamicpruning#54)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(57) ColumnarToRow [codegen id : 12] +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] + +(58) Filter [codegen id : 12] +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Condition : isnotnull(ws_bill_customer_sk#51) + +(59) BroadcastExchange +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [c_customer_sk#47] +Right keys [1]: [ws_bill_customer_sk#51] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 14] +Output [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, ws_sold_date_sk#53] +Input [7]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50, ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] + +(62) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#55, d_year#56] + +(63) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_sold_date_sk#53] +Right keys [1]: [d_date_sk#55] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 14] +Output [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, d_year#56] +Input [7]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, ws_sold_date_sk#53, d_date_sk#55, d_year#56] + +(65) HashAggregate [codegen id : 14] +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, d_year#56] +Keys [4]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#52))] +Aggregate Attributes [1]: [sum#57] +Results [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] + +(66) Exchange +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] +Arguments: hashpartitioning(c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(67) HashAggregate [codegen id : 15] +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] +Keys [4]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56] +Functions [1]: [sum(UnscaledValue(ws_net_paid#52))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#52))#44] +Results [2]: [c_customer_id#48 AS customer_id#59, MakeDecimal(sum(UnscaledValue(ws_net_paid#52))#44,17,2) AS year_total#60] + +(68) BroadcastExchange +Input [2]: [customer_id#59, year_total#60] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=11] + +(69) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#59] +Join type: Inner +Join condition: (CASE WHEN (year_total#46 > 0.00) THEN (year_total#60 / year_total#46) END > CASE WHEN (year_total#15 > 0.00) THEN (year_total#31 / year_total#15) END) + +(70) Project [codegen id : 16] +Output [3]: [customer_id#28, customer_first_name#29, customer_last_name#30] +Input [9]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, year_total#46, customer_id#59, year_total#60] + +(71) TakeOrderedAndProject +Input [3]: [customer_id#28, customer_first_name#29, customer_last_name#30] +Arguments: 100, [customer_id#28 ASC NULLS FIRST, customer_id#28 ASC NULLS FIRST, customer_id#28 ASC NULLS FIRST], [customer_id#28, customer_first_name#29, customer_last_name#30] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (75) ++- * Filter (74) + +- * ColumnarToRow (73) + +- CometScan parquet spark_catalog.default.date_dim (72) + + +(72) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#9, d_year#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(73) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#9, d_year#10] + +(74) Filter [codegen id : 1] +Input [2]: [d_date_sk#9, d_year#10] +Condition : (((isnotnull(d_year#10) AND (d_year#10 = 2001)) AND d_year#10 IN (2001,2002)) AND isnotnull(d_date_sk#9)) + +(75) BroadcastExchange +Input [2]: [d_date_sk#9, d_year#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#22 IN dynamicpruning#23 +BroadcastExchange (79) ++- * Filter (78) + +- * ColumnarToRow (77) + +- CometScan parquet spark_catalog.default.date_dim (76) + + +(76) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#24, d_year#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(77) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#24, d_year#25] + +(78) Filter [codegen id : 1] +Input [2]: [d_date_sk#24, d_year#25] +Condition : (((isnotnull(d_year#25) AND (d_year#25 = 2002)) AND d_year#25 IN (2001,2002)) AND isnotnull(d_date_sk#24)) + +(79) BroadcastExchange +Input [2]: [d_date_sk#24, d_year#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +Subquery:3 Hosting operator id = 37 Hosting Expression = ws_sold_date_sk#38 IN dynamicpruning#8 + +Subquery:4 Hosting operator id = 56 Hosting Expression = ws_sold_date_sk#53 IN dynamicpruning#23 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/simplified.txt new file mode 100644 index 000000000..e66974fba --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/simplified.txt @@ -0,0 +1,122 @@ +TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name] + WholeStageCodegen (16) + Project [customer_id,customer_first_name,customer_last_name] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,year_total,customer_id,customer_first_name,customer_last_name,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + BroadcastHashJoin [customer_id,customer_id] + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ss_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #1 + WholeStageCodegen (3) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ss_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ss_net_paid)),customer_id,customer_first_name,customer_last_name,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #5 + WholeStageCodegen (6) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ss_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ws_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #9 + WholeStageCodegen (10) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ws_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ws_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #12 + WholeStageCodegen (14) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ws_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (12) + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/explain.txt new file mode 100644 index 000000000..b18c8bbbf --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/explain.txt @@ -0,0 +1,779 @@ +== Physical Plan == +TakeOrderedAndProject (129) ++- * Project (128) + +- * SortMergeJoin Inner (127) + :- * Sort (71) + : +- Exchange (70) + : +- * Filter (69) + : +- * HashAggregate (68) + : +- Exchange (67) + : +- * HashAggregate (66) + : +- * HashAggregate (65) + : +- Exchange (64) + : +- * HashAggregate (63) + : +- Union (62) + : :- * Project (23) + : : +- * SortMergeJoin LeftOuter (22) + : : :- * Sort (15) + : : : +- Exchange (14) + : : : +- * Project (13) + : : : +- * BroadcastHashJoin Inner BuildRight (12) + : : : :- * Project (10) + : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : +- BroadcastExchange (8) + : : : : +- * Project (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : +- ReusedExchange (11) + : : +- * Sort (21) + : : +- Exchange (20) + : : +- * Project (19) + : : +- * Filter (18) + : : +- * ColumnarToRow (17) + : : +- CometScan parquet spark_catalog.default.catalog_returns (16) + : :- * Project (42) + : : +- * SortMergeJoin LeftOuter (41) + : : :- * Sort (34) + : : : +- Exchange (33) + : : : +- * Project (32) + : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : :- * Project (29) + : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : :- * Filter (26) + : : : : : +- * ColumnarToRow (25) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (24) + : : : : +- ReusedExchange (27) + : : : +- ReusedExchange (30) + : : +- * Sort (40) + : : +- Exchange (39) + : : +- * Project (38) + : : +- * Filter (37) + : : +- * ColumnarToRow (36) + : : +- CometScan parquet spark_catalog.default.store_returns (35) + : +- * Project (61) + : +- * SortMergeJoin LeftOuter (60) + : :- * Sort (53) + : : +- Exchange (52) + : : +- * Project (51) + : : +- * BroadcastHashJoin Inner BuildRight (50) + : : :- * Project (48) + : : : +- * BroadcastHashJoin Inner BuildRight (47) + : : : :- * Filter (45) + : : : : +- * ColumnarToRow (44) + : : : : +- CometScan parquet spark_catalog.default.web_sales (43) + : : : +- ReusedExchange (46) + : : +- ReusedExchange (49) + : +- * Sort (59) + : +- Exchange (58) + : +- * Project (57) + : +- * Filter (56) + : +- * ColumnarToRow (55) + : +- CometScan parquet spark_catalog.default.web_returns (54) + +- * Sort (126) + +- Exchange (125) + +- * Filter (124) + +- * HashAggregate (123) + +- Exchange (122) + +- * HashAggregate (121) + +- * HashAggregate (120) + +- Exchange (119) + +- * HashAggregate (118) + +- Union (117) + :- * Project (86) + : +- * SortMergeJoin LeftOuter (85) + : :- * Sort (82) + : : +- Exchange (81) + : : +- * Project (80) + : : +- * BroadcastHashJoin Inner BuildRight (79) + : : :- * Project (77) + : : : +- * BroadcastHashJoin Inner BuildRight (76) + : : : :- * Filter (74) + : : : : +- * ColumnarToRow (73) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (72) + : : : +- ReusedExchange (75) + : : +- ReusedExchange (78) + : +- * Sort (84) + : +- ReusedExchange (83) + :- * Project (101) + : +- * SortMergeJoin LeftOuter (100) + : :- * Sort (97) + : : +- Exchange (96) + : : +- * Project (95) + : : +- * BroadcastHashJoin Inner BuildRight (94) + : : :- * Project (92) + : : : +- * BroadcastHashJoin Inner BuildRight (91) + : : : :- * Filter (89) + : : : : +- * ColumnarToRow (88) + : : : : +- CometScan parquet spark_catalog.default.store_sales (87) + : : : +- ReusedExchange (90) + : : +- ReusedExchange (93) + : +- * Sort (99) + : +- ReusedExchange (98) + +- * Project (116) + +- * SortMergeJoin LeftOuter (115) + :- * Sort (112) + : +- Exchange (111) + : +- * Project (110) + : +- * BroadcastHashJoin Inner BuildRight (109) + : :- * Project (107) + : : +- * BroadcastHashJoin Inner BuildRight (106) + : : :- * Filter (104) + : : : +- * ColumnarToRow (103) + : : : +- CometScan parquet spark_catalog.default.web_sales (102) + : : +- ReusedExchange (105) + : +- ReusedExchange (108) + +- * Sort (114) + +- ReusedExchange (113) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] + +(3) Filter [codegen id : 3] +Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] +Condition : isnotnull(cs_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Books ), IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id), IsNotNull(i_manufact_id)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] + +(6) Filter [codegen id : 1] +Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Condition : ((((((isnotnull(i_category#11) AND (i_category#11 = Books )) AND isnotnull(i_item_sk#7)) AND isnotnull(i_brand_id#8)) AND isnotnull(i_class_id#9)) AND isnotnull(i_category_id#10)) AND isnotnull(i_manufact_id#12)) + +(7) Project [codegen id : 1] +Output [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] + +(8) BroadcastExchange +Input [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#1] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Input [10]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] + +(11) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#13, d_year#14] + +(12) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#5] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 3] +Output [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Input [11]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_date_sk#13, d_year#14] + +(14) Exchange +Input [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Arguments: hashpartitioning(cs_order_number#2, cs_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) Sort [codegen id : 4] +Input [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Arguments: [cs_order_number#2 ASC NULLS FIRST, cs_item_sk#1 ASC NULLS FIRST], false, 0 + +(16) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 5] +Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] + +(18) Filter [codegen id : 5] +Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Condition : (isnotnull(cr_order_number#16) AND isnotnull(cr_item_sk#15)) + +(19) Project [codegen id : 5] +Output [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] + +(20) Exchange +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +Arguments: hashpartitioning(cr_order_number#16, cr_item_sk#15, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) Sort [codegen id : 6] +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +Arguments: [cr_order_number#16 ASC NULLS FIRST, cr_item_sk#15 ASC NULLS FIRST], false, 0 + +(22) SortMergeJoin [codegen id : 7] +Left keys [2]: [cs_order_number#2, cs_item_sk#1] +Right keys [2]: [cr_order_number#16, cr_item_sk#15] +Join type: LeftOuter +Join condition: None + +(23) Project [codegen id : 7] +Output [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, (cs_quantity#3 - coalesce(cr_return_quantity#17, 0)) AS sales_cnt#20, (cs_ext_sales_price#4 - coalesce(cr_return_amount#18, 0.00)) AS sales_amt#21] +Input [13]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14, cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] + +(24) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_sold_date_sk#26 IN dynamicpruning#27)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(25) ColumnarToRow [codegen id : 10] +Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] + +(26) Filter [codegen id : 10] +Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Condition : isnotnull(ss_item_sk#22) + +(27) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#28, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] + +(28) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_item_sk#22] +Right keys [1]: [i_item_sk#28] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 10] +Output [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] +Input [10]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_item_sk#28, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] + +(30) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#33, d_year#34] + +(31) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_sold_date_sk#26] +Right keys [1]: [d_date_sk#33] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 10] +Output [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Input [11]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_date_sk#33, d_year#34] + +(33) Exchange +Input [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Arguments: hashpartitioning(ss_ticket_number#23, ss_item_sk#22, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(34) Sort [codegen id : 11] +Input [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Arguments: [ss_ticket_number#23 ASC NULLS FIRST, ss_item_sk#22 ASC NULLS FIRST], false, 0 + +(35) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(36) ColumnarToRow [codegen id : 12] +Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] + +(37) Filter [codegen id : 12] +Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Condition : (isnotnull(sr_ticket_number#36) AND isnotnull(sr_item_sk#35)) + +(38) Project [codegen id : 12] +Output [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] + +(39) Exchange +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +Arguments: hashpartitioning(sr_ticket_number#36, sr_item_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(40) Sort [codegen id : 13] +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +Arguments: [sr_ticket_number#36 ASC NULLS FIRST, sr_item_sk#35 ASC NULLS FIRST], false, 0 + +(41) SortMergeJoin [codegen id : 14] +Left keys [2]: [ss_ticket_number#23, ss_item_sk#22] +Right keys [2]: [sr_ticket_number#36, sr_item_sk#35] +Join type: LeftOuter +Join condition: None + +(42) Project [codegen id : 14] +Output [7]: [d_year#34, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, (ss_quantity#24 - coalesce(sr_return_quantity#37, 0)) AS sales_cnt#40, (ss_ext_sales_price#25 - coalesce(sr_return_amt#38, 0.00)) AS sales_amt#41] +Input [13]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34, sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] + +(43) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#46), dynamicpruningexpression(ws_sold_date_sk#46 IN dynamicpruning#47)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(44) ColumnarToRow [codegen id : 17] +Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] + +(45) Filter [codegen id : 17] +Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] +Condition : isnotnull(ws_item_sk#42) + +(46) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#48, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] + +(47) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_item_sk#42] +Right keys [1]: [i_item_sk#48] +Join type: Inner +Join condition: None + +(48) Project [codegen id : 17] +Output [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] +Input [10]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_item_sk#48, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] + +(49) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#53, d_year#54] + +(50) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#46] +Right keys [1]: [d_date_sk#53] +Join type: Inner +Join condition: None + +(51) Project [codegen id : 17] +Output [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Input [11]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_date_sk#53, d_year#54] + +(52) Exchange +Input [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Arguments: hashpartitioning(ws_order_number#43, ws_item_sk#42, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(53) Sort [codegen id : 18] +Input [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Arguments: [ws_order_number#43 ASC NULLS FIRST, ws_item_sk#42 ASC NULLS FIRST], false, 0 + +(54) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(55) ColumnarToRow [codegen id : 19] +Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] + +(56) Filter [codegen id : 19] +Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Condition : (isnotnull(wr_order_number#56) AND isnotnull(wr_item_sk#55)) + +(57) Project [codegen id : 19] +Output [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] + +(58) Exchange +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +Arguments: hashpartitioning(wr_order_number#56, wr_item_sk#55, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(59) Sort [codegen id : 20] +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +Arguments: [wr_order_number#56 ASC NULLS FIRST, wr_item_sk#55 ASC NULLS FIRST], false, 0 + +(60) SortMergeJoin [codegen id : 21] +Left keys [2]: [ws_order_number#43, ws_item_sk#42] +Right keys [2]: [wr_order_number#56, wr_item_sk#55] +Join type: LeftOuter +Join condition: None + +(61) Project [codegen id : 21] +Output [7]: [d_year#54, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, (ws_quantity#44 - coalesce(wr_return_quantity#57, 0)) AS sales_cnt#60, (ws_ext_sales_price#45 - coalesce(wr_return_amt#58, 0.00)) AS sales_amt#61] +Input [13]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54, wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] + +(62) Union + +(63) HashAggregate [codegen id : 22] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] + +(64) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Arguments: hashpartitioning(d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(65) HashAggregate [codegen id : 23] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] + +(66) HashAggregate [codegen id : 23] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [5]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Functions [2]: [partial_sum(sales_cnt#20), partial_sum(UnscaledValue(sales_amt#21))] +Aggregate Attributes [2]: [sum#62, sum#63] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] + +(67) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] +Arguments: hashpartitioning(d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(68) HashAggregate [codegen id : 24] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] +Keys [5]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Functions [2]: [sum(sales_cnt#20), sum(UnscaledValue(sales_amt#21))] +Aggregate Attributes [2]: [sum(sales_cnt#20)#66, sum(UnscaledValue(sales_amt#21))#67] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum(sales_cnt#20)#66 AS sales_cnt#68, MakeDecimal(sum(UnscaledValue(sales_amt#21))#67,18,2) AS sales_amt#69] + +(69) Filter [codegen id : 24] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Condition : isnotnull(sales_cnt#68) + +(70) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Arguments: hashpartitioning(i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(71) Sort [codegen id : 25] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Arguments: [i_brand_id#8 ASC NULLS FIRST, i_class_id#9 ASC NULLS FIRST, i_category_id#10 ASC NULLS FIRST, i_manufact_id#12 ASC NULLS FIRST], false, 0 + +(72) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#74), dynamicpruningexpression(cs_sold_date_sk#74 IN dynamicpruning#75)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(73) ColumnarToRow [codegen id : 28] +Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] + +(74) Filter [codegen id : 28] +Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] +Condition : isnotnull(cs_item_sk#70) + +(75) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#76, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] + +(76) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [cs_item_sk#70] +Right keys [1]: [i_item_sk#76] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 28] +Output [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Input [10]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_item_sk#76, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] + +(78) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#81, d_year#82] + +(79) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [cs_sold_date_sk#74] +Right keys [1]: [d_date_sk#81] +Join type: Inner +Join condition: None + +(80) Project [codegen id : 28] +Output [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Input [11]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_date_sk#81, d_year#82] + +(81) Exchange +Input [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Arguments: hashpartitioning(cs_order_number#71, cs_item_sk#70, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(82) Sort [codegen id : 29] +Input [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Arguments: [cs_order_number#71 ASC NULLS FIRST, cs_item_sk#70 ASC NULLS FIRST], false, 0 + +(83) ReusedExchange [Reuses operator id: 20] +Output [4]: [cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] + +(84) Sort [codegen id : 31] +Input [4]: [cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] +Arguments: [cr_order_number#84 ASC NULLS FIRST, cr_item_sk#83 ASC NULLS FIRST], false, 0 + +(85) SortMergeJoin [codegen id : 32] +Left keys [2]: [cs_order_number#71, cs_item_sk#70] +Right keys [2]: [cr_order_number#84, cr_item_sk#83] +Join type: LeftOuter +Join condition: None + +(86) Project [codegen id : 32] +Output [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, (cs_quantity#72 - coalesce(cr_return_quantity#85, 0)) AS sales_cnt#87, (cs_ext_sales_price#73 - coalesce(cr_return_amount#86, 0.00)) AS sales_amt#88] +Input [13]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82, cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] + +(87) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#93), dynamicpruningexpression(ss_sold_date_sk#93 IN dynamicpruning#94)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(88) ColumnarToRow [codegen id : 35] +Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] + +(89) Filter [codegen id : 35] +Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] +Condition : isnotnull(ss_item_sk#89) + +(90) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#95, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] + +(91) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ss_item_sk#89] +Right keys [1]: [i_item_sk#95] +Join type: Inner +Join condition: None + +(92) Project [codegen id : 35] +Output [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] +Input [10]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_item_sk#95, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] + +(93) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#100, d_year#101] + +(94) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ss_sold_date_sk#93] +Right keys [1]: [d_date_sk#100] +Join type: Inner +Join condition: None + +(95) Project [codegen id : 35] +Output [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Input [11]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_date_sk#100, d_year#101] + +(96) Exchange +Input [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Arguments: hashpartitioning(ss_ticket_number#90, ss_item_sk#89, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(97) Sort [codegen id : 36] +Input [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Arguments: [ss_ticket_number#90 ASC NULLS FIRST, ss_item_sk#89 ASC NULLS FIRST], false, 0 + +(98) ReusedExchange [Reuses operator id: 39] +Output [4]: [sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] + +(99) Sort [codegen id : 38] +Input [4]: [sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] +Arguments: [sr_ticket_number#103 ASC NULLS FIRST, sr_item_sk#102 ASC NULLS FIRST], false, 0 + +(100) SortMergeJoin [codegen id : 39] +Left keys [2]: [ss_ticket_number#90, ss_item_sk#89] +Right keys [2]: [sr_ticket_number#103, sr_item_sk#102] +Join type: LeftOuter +Join condition: None + +(101) Project [codegen id : 39] +Output [7]: [d_year#101, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, (ss_quantity#91 - coalesce(sr_return_quantity#104, 0)) AS sales_cnt#106, (ss_ext_sales_price#92 - coalesce(sr_return_amt#105, 0.00)) AS sales_amt#107] +Input [13]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101, sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] + +(102) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#112), dynamicpruningexpression(ws_sold_date_sk#112 IN dynamicpruning#113)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(103) ColumnarToRow [codegen id : 42] +Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] + +(104) Filter [codegen id : 42] +Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] +Condition : isnotnull(ws_item_sk#108) + +(105) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#114, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] + +(106) BroadcastHashJoin [codegen id : 42] +Left keys [1]: [ws_item_sk#108] +Right keys [1]: [i_item_sk#114] +Join type: Inner +Join condition: None + +(107) Project [codegen id : 42] +Output [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] +Input [10]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_item_sk#114, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] + +(108) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#119, d_year#120] + +(109) BroadcastHashJoin [codegen id : 42] +Left keys [1]: [ws_sold_date_sk#112] +Right keys [1]: [d_date_sk#119] +Join type: Inner +Join condition: None + +(110) Project [codegen id : 42] +Output [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Input [11]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_date_sk#119, d_year#120] + +(111) Exchange +Input [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Arguments: hashpartitioning(ws_order_number#109, ws_item_sk#108, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(112) Sort [codegen id : 43] +Input [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Arguments: [ws_order_number#109 ASC NULLS FIRST, ws_item_sk#108 ASC NULLS FIRST], false, 0 + +(113) ReusedExchange [Reuses operator id: 58] +Output [4]: [wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] + +(114) Sort [codegen id : 45] +Input [4]: [wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] +Arguments: [wr_order_number#122 ASC NULLS FIRST, wr_item_sk#121 ASC NULLS FIRST], false, 0 + +(115) SortMergeJoin [codegen id : 46] +Left keys [2]: [ws_order_number#109, ws_item_sk#108] +Right keys [2]: [wr_order_number#122, wr_item_sk#121] +Join type: LeftOuter +Join condition: None + +(116) Project [codegen id : 46] +Output [7]: [d_year#120, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, (ws_quantity#110 - coalesce(wr_return_quantity#123, 0)) AS sales_cnt#125, (ws_ext_sales_price#111 - coalesce(wr_return_amt#124, 0.00)) AS sales_amt#126] +Input [13]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120, wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] + +(117) Union + +(118) HashAggregate [codegen id : 47] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] + +(119) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Arguments: hashpartitioning(d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(120) HashAggregate [codegen id : 48] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] + +(121) HashAggregate [codegen id : 48] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [5]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Functions [2]: [partial_sum(sales_cnt#87), partial_sum(UnscaledValue(sales_amt#88))] +Aggregate Attributes [2]: [sum#127, sum#128] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] + +(122) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] +Arguments: hashpartitioning(d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(123) HashAggregate [codegen id : 49] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] +Keys [5]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Functions [2]: [sum(sales_cnt#87), sum(UnscaledValue(sales_amt#88))] +Aggregate Attributes [2]: [sum(sales_cnt#87)#66, sum(UnscaledValue(sales_amt#88))#67] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum(sales_cnt#87)#66 AS sales_cnt#131, MakeDecimal(sum(UnscaledValue(sales_amt#88))#67,18,2) AS sales_amt#132] + +(124) Filter [codegen id : 49] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Condition : isnotnull(sales_cnt#131) + +(125) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Arguments: hashpartitioning(i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, 5), ENSURE_REQUIREMENTS, [plan_id=16] + +(126) Sort [codegen id : 50] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Arguments: [i_brand_id#77 ASC NULLS FIRST, i_class_id#78 ASC NULLS FIRST, i_category_id#79 ASC NULLS FIRST, i_manufact_id#80 ASC NULLS FIRST], false, 0 + +(127) SortMergeJoin [codegen id : 51] +Left keys [4]: [i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Right keys [4]: [i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Join type: Inner +Join condition: ((cast(sales_cnt#68 as decimal(17,2)) / cast(sales_cnt#131 as decimal(17,2))) < 0.90000000000000000000) + +(128) Project [codegen id : 51] +Output [10]: [d_year#82 AS prev_year#133, d_year#14 AS year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#131 AS prev_yr_cnt#135, sales_cnt#68 AS curr_yr_cnt#136, (sales_cnt#68 - sales_cnt#131) AS sales_cnt_diff#137, (sales_amt#69 - sales_amt#132) AS sales_amt_diff#138] +Input [14]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69, d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] + +(129) TakeOrderedAndProject +Input [10]: [prev_year#133, year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, prev_yr_cnt#135, curr_yr_cnt#136, sales_cnt_diff#137, sales_amt_diff#138] +Arguments: 100, [sales_cnt_diff#137 ASC NULLS FIRST], [prev_year#133, year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, prev_yr_cnt#135, curr_yr_cnt#136, sales_cnt_diff#137, sales_amt_diff#138] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (133) ++- * Filter (132) + +- * ColumnarToRow (131) + +- CometScan parquet spark_catalog.default.date_dim (130) + + +(130) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#13, d_year#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(131) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#13, d_year#14] + +(132) Filter [codegen id : 1] +Input [2]: [d_date_sk#13, d_year#14] +Condition : ((isnotnull(d_year#14) AND (d_year#14 = 2002)) AND isnotnull(d_date_sk#13)) + +(133) BroadcastExchange +Input [2]: [d_date_sk#13, d_year#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=17] + +Subquery:2 Hosting operator id = 24 Hosting Expression = ss_sold_date_sk#26 IN dynamicpruning#6 + +Subquery:3 Hosting operator id = 43 Hosting Expression = ws_sold_date_sk#46 IN dynamicpruning#6 + +Subquery:4 Hosting operator id = 72 Hosting Expression = cs_sold_date_sk#74 IN dynamicpruning#75 +BroadcastExchange (137) ++- * Filter (136) + +- * ColumnarToRow (135) + +- CometScan parquet spark_catalog.default.date_dim (134) + + +(134) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#81, d_year#82] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(135) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#81, d_year#82] + +(136) Filter [codegen id : 1] +Input [2]: [d_date_sk#81, d_year#82] +Condition : ((isnotnull(d_year#82) AND (d_year#82 = 2001)) AND isnotnull(d_date_sk#81)) + +(137) BroadcastExchange +Input [2]: [d_date_sk#81, d_year#82] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=18] + +Subquery:5 Hosting operator id = 87 Hosting Expression = ss_sold_date_sk#93 IN dynamicpruning#75 + +Subquery:6 Hosting operator id = 102 Hosting Expression = ws_sold_date_sk#112 IN dynamicpruning#75 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/simplified.txt new file mode 100644 index 000000000..021cddf2b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/simplified.txt @@ -0,0 +1,240 @@ +TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_category_id,i_manufact_id,prev_yr_cnt,curr_yr_cnt,sales_amt_diff] + WholeStageCodegen (51) + Project [d_year,d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_cnt,sales_amt,sales_amt] + SortMergeJoin [i_brand_id,i_class_id,i_category_id,i_manufact_id,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_cnt] + InputAdapter + WholeStageCodegen (25) + Sort [i_brand_id,i_class_id,i_category_id,i_manufact_id] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id,i_manufact_id] #1 + WholeStageCodegen (24) + Filter [sales_cnt] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sum,sum] [sum(sales_cnt),sum(UnscaledValue(sales_amt)),sales_cnt,sales_amt,sum,sum] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id] #2 + WholeStageCodegen (23) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] [sum,sum,sum,sum] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] #3 + WholeStageCodegen (22) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Union + WholeStageCodegen (7) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,cs_quantity,cr_return_quantity,cs_ext_sales_price,cr_return_amount] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (4) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #4 + WholeStageCodegen (3) + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (1) + Project [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + Filter [i_category,i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id,i_category,i_manufact_id] + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (6) + Sort [cr_order_number,cr_item_sk] + InputAdapter + Exchange [cr_order_number,cr_item_sk] #7 + WholeStageCodegen (5) + Project [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + Filter [cr_order_number,cr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] + WholeStageCodegen (14) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ss_quantity,sr_return_quantity,ss_ext_sales_price,sr_return_amt] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (11) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #8 + WholeStageCodegen (10) + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (13) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #9 + WholeStageCodegen (12) + Project [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + Filter [sr_ticket_number,sr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] + WholeStageCodegen (21) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ws_quantity,wr_return_quantity,ws_ext_sales_price,wr_return_amt] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (18) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #10 + WholeStageCodegen (17) + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (20) + Sort [wr_order_number,wr_item_sk] + InputAdapter + Exchange [wr_order_number,wr_item_sk] #11 + WholeStageCodegen (19) + Project [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + Filter [wr_order_number,wr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] + InputAdapter + WholeStageCodegen (50) + Sort [i_brand_id,i_class_id,i_category_id,i_manufact_id] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id,i_manufact_id] #12 + WholeStageCodegen (49) + Filter [sales_cnt] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sum,sum] [sum(sales_cnt),sum(UnscaledValue(sales_amt)),sales_cnt,sales_amt,sum,sum] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id] #13 + WholeStageCodegen (48) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] [sum,sum,sum,sum] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] #14 + WholeStageCodegen (47) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Union + WholeStageCodegen (32) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,cs_quantity,cr_return_quantity,cs_ext_sales_price,cr_return_amount] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (29) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #15 + WholeStageCodegen (28) + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #16 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (31) + Sort [cr_order_number,cr_item_sk] + InputAdapter + ReusedExchange [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] #7 + WholeStageCodegen (39) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ss_quantity,sr_return_quantity,ss_ext_sales_price,sr_return_amt] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (36) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #17 + WholeStageCodegen (35) + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (38) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + ReusedExchange [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] #9 + WholeStageCodegen (46) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ws_quantity,wr_return_quantity,ws_ext_sales_price,wr_return_amt] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (43) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #18 + WholeStageCodegen (42) + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (45) + Sort [wr_order_number,wr_item_sk] + InputAdapter + ReusedExchange [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] #11 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/explain.txt new file mode 100644 index 000000000..69427a8e2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/explain.txt @@ -0,0 +1,218 @@ +== Physical Plan == +TakeOrderedAndProject (38) ++- * HashAggregate (37) + +- Exchange (36) + +- * HashAggregate (35) + +- Union (34) + :- * Project (15) + : +- * BroadcastHashJoin Inner BuildRight (14) + : :- * Project (9) + : : +- * BroadcastHashJoin Inner BuildRight (8) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- BroadcastExchange (7) + : : +- * Filter (6) + : : +- * ColumnarToRow (5) + : : +- CometScan parquet spark_catalog.default.item (4) + : +- BroadcastExchange (13) + : +- * Filter (12) + : +- * ColumnarToRow (11) + : +- CometScan parquet spark_catalog.default.date_dim (10) + :- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (21) + : : +- * BroadcastHashJoin Inner BuildRight (20) + : : :- * Filter (18) + : : : +- * ColumnarToRow (17) + : : : +- CometScan parquet spark_catalog.default.web_sales (16) + : : +- ReusedExchange (19) + : +- ReusedExchange (22) + +- * Project (33) + +- * BroadcastHashJoin Inner BuildRight (32) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * Filter (27) + : : +- * ColumnarToRow (26) + : : +- CometScan parquet spark_catalog.default.catalog_sales (25) + : +- ReusedExchange (28) + +- ReusedExchange (31) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4)] +PushedFilters: [IsNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 3] +Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) + +(4) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#5, i_category#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [i_item_sk#5, i_category#6] + +(6) Filter [codegen id : 1] +Input [2]: [i_item_sk#5, i_category#6] +Condition : isnotnull(i_item_sk#5) + +(7) BroadcastExchange +Input [2]: [i_item_sk#5, i_category#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [4]: [ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, i_category#6] +Input [6]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, i_item_sk#5, i_category#6] + +(10) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#8, d_qoy#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [3]: [d_date_sk#7, d_year#8, d_qoy#9] + +(12) Filter [codegen id : 2] +Input [3]: [d_date_sk#7, d_year#8, d_qoy#9] +Condition : isnotnull(d_date_sk#7) + +(13) BroadcastExchange +Input [3]: [d_date_sk#7, d_year#8, d_qoy#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 3] +Output [6]: [store AS channel#10, ss_store_sk#2 AS col_name#11, d_year#8, d_qoy#9, i_category#6, ss_ext_sales_price#3 AS ext_sales_price#12] +Input [7]: [ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4, i_category#6, d_date_sk#7, d_year#8, d_qoy#9] + +(16) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#13, ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#16)] +PushedFilters: [IsNull(ws_ship_customer_sk), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 6] +Input [4]: [ws_item_sk#13, ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16] + +(18) Filter [codegen id : 6] +Input [4]: [ws_item_sk#13, ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16] +Condition : (isnull(ws_ship_customer_sk#14) AND isnotnull(ws_item_sk#13)) + +(19) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#17, i_category#18] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_item_sk#13] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [4]: [ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16, i_category#18] +Input [6]: [ws_item_sk#13, ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16, i_item_sk#17, i_category#18] + +(22) ReusedExchange [Reuses operator id: 13] +Output [3]: [d_date_sk#19, d_year#20, d_qoy#21] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#16] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [6]: [web AS channel#22, ws_ship_customer_sk#14 AS col_name#23, d_year#20, d_qoy#21, i_category#18, ws_ext_sales_price#15 AS ext_sales_price#24] +Input [7]: [ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16, i_category#18, d_date_sk#19, d_year#20, d_qoy#21] + +(25) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_ship_addr_sk#25, cs_item_sk#26, cs_ext_sales_price#27, cs_sold_date_sk#28] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#28)] +PushedFilters: [IsNull(cs_ship_addr_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 9] +Input [4]: [cs_ship_addr_sk#25, cs_item_sk#26, cs_ext_sales_price#27, cs_sold_date_sk#28] + +(27) Filter [codegen id : 9] +Input [4]: [cs_ship_addr_sk#25, cs_item_sk#26, cs_ext_sales_price#27, cs_sold_date_sk#28] +Condition : (isnull(cs_ship_addr_sk#25) AND isnotnull(cs_item_sk#26)) + +(28) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#29, i_category#30] + +(29) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [cs_item_sk#26] +Right keys [1]: [i_item_sk#29] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 9] +Output [4]: [cs_ship_addr_sk#25, cs_ext_sales_price#27, cs_sold_date_sk#28, i_category#30] +Input [6]: [cs_ship_addr_sk#25, cs_item_sk#26, cs_ext_sales_price#27, cs_sold_date_sk#28, i_item_sk#29, i_category#30] + +(31) ReusedExchange [Reuses operator id: 13] +Output [3]: [d_date_sk#31, d_year#32, d_qoy#33] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [cs_sold_date_sk#28] +Right keys [1]: [d_date_sk#31] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [6]: [catalog AS channel#34, cs_ship_addr_sk#25 AS col_name#35, d_year#32, d_qoy#33, i_category#30, cs_ext_sales_price#27 AS ext_sales_price#36] +Input [7]: [cs_ship_addr_sk#25, cs_ext_sales_price#27, cs_sold_date_sk#28, i_category#30, d_date_sk#31, d_year#32, d_qoy#33] + +(34) Union + +(35) HashAggregate [codegen id : 10] +Input [6]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, ext_sales_price#12] +Keys [5]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6] +Functions [2]: [partial_count(1), partial_sum(UnscaledValue(ext_sales_price#12))] +Aggregate Attributes [2]: [count#37, sum#38] +Results [7]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, count#39, sum#40] + +(36) Exchange +Input [7]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, count#39, sum#40] +Arguments: hashpartitioning(channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(37) HashAggregate [codegen id : 11] +Input [7]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, count#39, sum#40] +Keys [5]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6] +Functions [2]: [count(1), sum(UnscaledValue(ext_sales_price#12))] +Aggregate Attributes [2]: [count(1)#41, sum(UnscaledValue(ext_sales_price#12))#42] +Results [7]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, count(1)#41 AS sales_cnt#43, MakeDecimal(sum(UnscaledValue(ext_sales_price#12))#42,17,2) AS sales_amt#44] + +(38) TakeOrderedAndProject +Input [7]: [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, sales_cnt#43, sales_amt#44] +Arguments: 100, [channel#10 ASC NULLS FIRST, col_name#11 ASC NULLS FIRST, d_year#8 ASC NULLS FIRST, d_qoy#9 ASC NULLS FIRST, i_category#6 ASC NULLS FIRST], [channel#10, col_name#11, d_year#8, d_qoy#9, i_category#6, sales_cnt#43, sales_amt#44] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/simplified.txt new file mode 100644 index 000000000..074a78dd4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/simplified.txt @@ -0,0 +1,58 @@ +TakeOrderedAndProject [channel,col_name,d_year,d_qoy,i_category,sales_cnt,sales_amt] + WholeStageCodegen (11) + HashAggregate [channel,col_name,d_year,d_qoy,i_category,count,sum] [count(1),sum(UnscaledValue(ext_sales_price)),sales_cnt,sales_amt,count,sum] + InputAdapter + Exchange [channel,col_name,d_year,d_qoy,i_category] #1 + WholeStageCodegen (10) + HashAggregate [channel,col_name,d_year,d_qoy,i_category,ext_sales_price] [count,sum,count,sum] + InputAdapter + Union + WholeStageCodegen (3) + Project [ss_store_sk,d_year,d_qoy,i_category,ss_ext_sales_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_store_sk,ss_ext_sales_price,ss_sold_date_sk,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_store_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + WholeStageCodegen (6) + Project [ws_ship_customer_sk,d_year,d_qoy,i_category,ws_ext_sales_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_ship_customer_sk,ws_ext_sales_price,ws_sold_date_sk,i_category] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_ship_customer_sk,ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ship_customer_sk,ws_ext_sales_price,ws_sold_date_sk] + InputAdapter + ReusedExchange [i_item_sk,i_category] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #3 + WholeStageCodegen (9) + Project [cs_ship_addr_sk,d_year,d_qoy,i_category,cs_ext_sales_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ship_addr_sk,cs_ext_sales_price,cs_sold_date_sk,i_category] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_ship_addr_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + InputAdapter + ReusedExchange [i_item_sk,i_category] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year,d_qoy] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/explain.txt new file mode 100644 index 000000000..a228bce35 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/explain.txt @@ -0,0 +1,547 @@ +== Physical Plan == +TakeOrderedAndProject (85) ++- * HashAggregate (84) + +- Exchange (83) + +- * HashAggregate (82) + +- * Expand (81) + +- Union (80) + :- * Project (30) + : +- * BroadcastHashJoin LeftOuter BuildRight (29) + : :- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (28) + : +- * HashAggregate (27) + : +- Exchange (26) + : +- * HashAggregate (25) + : +- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (21) + : : +- * BroadcastHashJoin Inner BuildRight (20) + : : :- * Filter (18) + : : : +- * ColumnarToRow (17) + : : : +- CometScan parquet spark_catalog.default.store_returns (16) + : : +- ReusedExchange (19) + : +- ReusedExchange (22) + :- * Project (49) + : +- * BroadcastNestedLoopJoin Inner BuildLeft (48) + : :- BroadcastExchange (39) + : : +- * HashAggregate (38) + : : +- Exchange (37) + : : +- * HashAggregate (36) + : : +- * Project (35) + : : +- * BroadcastHashJoin Inner BuildRight (34) + : : :- * ColumnarToRow (32) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (31) + : : +- ReusedExchange (33) + : +- * HashAggregate (47) + : +- Exchange (46) + : +- * HashAggregate (45) + : +- * Project (44) + : +- * BroadcastHashJoin Inner BuildRight (43) + : :- * ColumnarToRow (41) + : : +- CometScan parquet spark_catalog.default.catalog_returns (40) + : +- ReusedExchange (42) + +- * Project (79) + +- * BroadcastHashJoin LeftOuter BuildRight (78) + :- * HashAggregate (64) + : +- Exchange (63) + : +- * HashAggregate (62) + : +- * Project (61) + : +- * BroadcastHashJoin Inner BuildRight (60) + : :- * Project (55) + : : +- * BroadcastHashJoin Inner BuildRight (54) + : : :- * Filter (52) + : : : +- * ColumnarToRow (51) + : : : +- CometScan parquet spark_catalog.default.web_sales (50) + : : +- ReusedExchange (53) + : +- BroadcastExchange (59) + : +- * Filter (58) + : +- * ColumnarToRow (57) + : +- CometScan parquet spark_catalog.default.web_page (56) + +- BroadcastExchange (77) + +- * HashAggregate (76) + +- Exchange (75) + +- * HashAggregate (74) + +- * Project (73) + +- * BroadcastHashJoin Inner BuildRight (72) + :- * Project (70) + : +- * BroadcastHashJoin Inner BuildRight (69) + : :- * Filter (67) + : : +- * ColumnarToRow (66) + : : +- CometScan parquet spark_catalog.default.web_returns (65) + : +- ReusedExchange (68) + +- ReusedExchange (71) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 3] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_store_sk#1) + +(4) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [3]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3] +Input [5]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#7] + +(9) Filter [codegen id : 2] +Input [1]: [s_store_sk#7] +Condition : isnotnull(s_store_sk#7) + +(10) BroadcastExchange +Input [1]: [s_store_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] + +(13) HashAggregate [codegen id : 3] +Input [3]: [ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] +Keys [1]: [s_store_sk#7] +Functions [2]: [partial_sum(UnscaledValue(ss_ext_sales_price#2)), partial_sum(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [2]: [sum#8, sum#9] +Results [3]: [s_store_sk#7, sum#10, sum#11] + +(14) Exchange +Input [3]: [s_store_sk#7, sum#10, sum#11] +Arguments: hashpartitioning(s_store_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 8] +Input [3]: [s_store_sk#7, sum#10, sum#11] +Keys [1]: [s_store_sk#7] +Functions [2]: [sum(UnscaledValue(ss_ext_sales_price#2)), sum(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_ext_sales_price#2))#12, sum(UnscaledValue(ss_net_profit#3))#13] +Results [3]: [s_store_sk#7, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#12,17,2) AS sales#14, MakeDecimal(sum(UnscaledValue(ss_net_profit#3))#13,17,2) AS profit#15] + +(16) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#19), dynamicpruningexpression(sr_returned_date_sk#19 IN dynamicpruning#20)] +PushedFilters: [IsNotNull(sr_store_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 6] +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] + +(18) Filter [codegen id : 6] +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] +Condition : isnotnull(sr_store_sk#16) + +(19) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#21] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sr_returned_date_sk#19] +Right keys [1]: [d_date_sk#21] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [3]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18] +Input [5]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19, d_date_sk#21] + +(22) ReusedExchange [Reuses operator id: 10] +Output [1]: [s_store_sk#22] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sr_store_sk#16] +Right keys [1]: [s_store_sk#22] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [3]: [sr_return_amt#17, sr_net_loss#18, s_store_sk#22] +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, s_store_sk#22] + +(25) HashAggregate [codegen id : 6] +Input [3]: [sr_return_amt#17, sr_net_loss#18, s_store_sk#22] +Keys [1]: [s_store_sk#22] +Functions [2]: [partial_sum(UnscaledValue(sr_return_amt#17)), partial_sum(UnscaledValue(sr_net_loss#18))] +Aggregate Attributes [2]: [sum#23, sum#24] +Results [3]: [s_store_sk#22, sum#25, sum#26] + +(26) Exchange +Input [3]: [s_store_sk#22, sum#25, sum#26] +Arguments: hashpartitioning(s_store_sk#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 7] +Input [3]: [s_store_sk#22, sum#25, sum#26] +Keys [1]: [s_store_sk#22] +Functions [2]: [sum(UnscaledValue(sr_return_amt#17)), sum(UnscaledValue(sr_net_loss#18))] +Aggregate Attributes [2]: [sum(UnscaledValue(sr_return_amt#17))#27, sum(UnscaledValue(sr_net_loss#18))#28] +Results [3]: [s_store_sk#22, MakeDecimal(sum(UnscaledValue(sr_return_amt#17))#27,17,2) AS returns#29, MakeDecimal(sum(UnscaledValue(sr_net_loss#18))#28,17,2) AS profit_loss#30] + +(28) BroadcastExchange +Input [3]: [s_store_sk#22, returns#29, profit_loss#30] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [s_store_sk#7] +Right keys [1]: [s_store_sk#22] +Join type: LeftOuter +Join condition: None + +(30) Project [codegen id : 8] +Output [5]: [sales#14, coalesce(returns#29, 0.00) AS returns#31, (profit#15 - coalesce(profit_loss#30, 0.00)) AS profit#32, store channel AS channel#33, s_store_sk#7 AS id#34] +Input [6]: [s_store_sk#7, sales#14, profit#15, s_store_sk#22, returns#29, profit_loss#30] + +(31) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#38), dynamicpruningexpression(cs_sold_date_sk#38 IN dynamicpruning#39)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 10] +Input [4]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38] + +(33) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#40] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#38] +Right keys [1]: [d_date_sk#40] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [3]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37] +Input [5]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38, d_date_sk#40] + +(36) HashAggregate [codegen id : 10] +Input [3]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37] +Keys [1]: [cs_call_center_sk#35] +Functions [2]: [partial_sum(UnscaledValue(cs_ext_sales_price#36)), partial_sum(UnscaledValue(cs_net_profit#37))] +Aggregate Attributes [2]: [sum#41, sum#42] +Results [3]: [cs_call_center_sk#35, sum#43, sum#44] + +(37) Exchange +Input [3]: [cs_call_center_sk#35, sum#43, sum#44] +Arguments: hashpartitioning(cs_call_center_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(38) HashAggregate [codegen id : 11] +Input [3]: [cs_call_center_sk#35, sum#43, sum#44] +Keys [1]: [cs_call_center_sk#35] +Functions [2]: [sum(UnscaledValue(cs_ext_sales_price#36)), sum(UnscaledValue(cs_net_profit#37))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_sales_price#36))#45, sum(UnscaledValue(cs_net_profit#37))#46] +Results [3]: [cs_call_center_sk#35, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#36))#45,17,2) AS sales#47, MakeDecimal(sum(UnscaledValue(cs_net_profit#37))#46,17,2) AS profit#48] + +(39) BroadcastExchange +Input [3]: [cs_call_center_sk#35, sales#47, profit#48] +Arguments: IdentityBroadcastMode, [plan_id=6] + +(40) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#51), dynamicpruningexpression(cr_returned_date_sk#51 IN dynamicpruning#52)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 13] +Input [3]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] + +(42) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#53] + +(43) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [cr_returned_date_sk#51] +Right keys [1]: [d_date_sk#53] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 13] +Output [2]: [cr_return_amount#49, cr_net_loss#50] +Input [4]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51, d_date_sk#53] + +(45) HashAggregate [codegen id : 13] +Input [2]: [cr_return_amount#49, cr_net_loss#50] +Keys: [] +Functions [2]: [partial_sum(UnscaledValue(cr_return_amount#49)), partial_sum(UnscaledValue(cr_net_loss#50))] +Aggregate Attributes [2]: [sum#54, sum#55] +Results [2]: [sum#56, sum#57] + +(46) Exchange +Input [2]: [sum#56, sum#57] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate +Input [2]: [sum#56, sum#57] +Keys: [] +Functions [2]: [sum(UnscaledValue(cr_return_amount#49)), sum(UnscaledValue(cr_net_loss#50))] +Aggregate Attributes [2]: [sum(UnscaledValue(cr_return_amount#49))#58, sum(UnscaledValue(cr_net_loss#50))#59] +Results [2]: [MakeDecimal(sum(UnscaledValue(cr_return_amount#49))#58,17,2) AS returns#60, MakeDecimal(sum(UnscaledValue(cr_net_loss#50))#59,17,2) AS profit_loss#61] + +(48) BroadcastNestedLoopJoin [codegen id : 14] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 14] +Output [5]: [sales#47, returns#60, (profit#48 - profit_loss#61) AS profit#62, catalog channel AS channel#63, cs_call_center_sk#35 AS id#64] +Input [5]: [cs_call_center_sk#35, sales#47, profit#48, returns#60, profit_loss#61] + +(50) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#68), dynamicpruningexpression(ws_sold_date_sk#68 IN dynamicpruning#69)] +PushedFilters: [IsNotNull(ws_web_page_sk)] +ReadSchema: struct + +(51) ColumnarToRow [codegen id : 17] +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] + +(52) Filter [codegen id : 17] +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] +Condition : isnotnull(ws_web_page_sk#65) + +(53) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#70] + +(54) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#68] +Right keys [1]: [d_date_sk#70] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 17] +Output [3]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67] +Input [5]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68, d_date_sk#70] + +(56) Scan parquet spark_catalog.default.web_page +Output [1]: [wp_web_page_sk#71] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_page] +PushedFilters: [IsNotNull(wp_web_page_sk)] +ReadSchema: struct + +(57) ColumnarToRow [codegen id : 16] +Input [1]: [wp_web_page_sk#71] + +(58) Filter [codegen id : 16] +Input [1]: [wp_web_page_sk#71] +Condition : isnotnull(wp_web_page_sk#71) + +(59) BroadcastExchange +Input [1]: [wp_web_page_sk#71] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(60) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_web_page_sk#65] +Right keys [1]: [wp_web_page_sk#71] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 17] +Output [3]: [ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] + +(62) HashAggregate [codegen id : 17] +Input [3]: [ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] +Keys [1]: [wp_web_page_sk#71] +Functions [2]: [partial_sum(UnscaledValue(ws_ext_sales_price#66)), partial_sum(UnscaledValue(ws_net_profit#67))] +Aggregate Attributes [2]: [sum#72, sum#73] +Results [3]: [wp_web_page_sk#71, sum#74, sum#75] + +(63) Exchange +Input [3]: [wp_web_page_sk#71, sum#74, sum#75] +Arguments: hashpartitioning(wp_web_page_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(64) HashAggregate [codegen id : 22] +Input [3]: [wp_web_page_sk#71, sum#74, sum#75] +Keys [1]: [wp_web_page_sk#71] +Functions [2]: [sum(UnscaledValue(ws_ext_sales_price#66)), sum(UnscaledValue(ws_net_profit#67))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_sales_price#66))#76, sum(UnscaledValue(ws_net_profit#67))#77] +Results [3]: [wp_web_page_sk#71, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#66))#76,17,2) AS sales#78, MakeDecimal(sum(UnscaledValue(ws_net_profit#67))#77,17,2) AS profit#79] + +(65) Scan parquet spark_catalog.default.web_returns +Output [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#83), dynamicpruningexpression(wr_returned_date_sk#83 IN dynamicpruning#84)] +PushedFilters: [IsNotNull(wr_web_page_sk)] +ReadSchema: struct + +(66) ColumnarToRow [codegen id : 20] +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] + +(67) Filter [codegen id : 20] +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] +Condition : isnotnull(wr_web_page_sk#80) + +(68) ReusedExchange [Reuses operator id: 90] +Output [1]: [d_date_sk#85] + +(69) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [wr_returned_date_sk#83] +Right keys [1]: [d_date_sk#85] +Join type: Inner +Join condition: None + +(70) Project [codegen id : 20] +Output [3]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82] +Input [5]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83, d_date_sk#85] + +(71) ReusedExchange [Reuses operator id: 59] +Output [1]: [wp_web_page_sk#86] + +(72) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [wr_web_page_sk#80] +Right keys [1]: [wp_web_page_sk#86] +Join type: Inner +Join condition: None + +(73) Project [codegen id : 20] +Output [3]: [wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] + +(74) HashAggregate [codegen id : 20] +Input [3]: [wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] +Keys [1]: [wp_web_page_sk#86] +Functions [2]: [partial_sum(UnscaledValue(wr_return_amt#81)), partial_sum(UnscaledValue(wr_net_loss#82))] +Aggregate Attributes [2]: [sum#87, sum#88] +Results [3]: [wp_web_page_sk#86, sum#89, sum#90] + +(75) Exchange +Input [3]: [wp_web_page_sk#86, sum#89, sum#90] +Arguments: hashpartitioning(wp_web_page_sk#86, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(76) HashAggregate [codegen id : 21] +Input [3]: [wp_web_page_sk#86, sum#89, sum#90] +Keys [1]: [wp_web_page_sk#86] +Functions [2]: [sum(UnscaledValue(wr_return_amt#81)), sum(UnscaledValue(wr_net_loss#82))] +Aggregate Attributes [2]: [sum(UnscaledValue(wr_return_amt#81))#91, sum(UnscaledValue(wr_net_loss#82))#92] +Results [3]: [wp_web_page_sk#86, MakeDecimal(sum(UnscaledValue(wr_return_amt#81))#91,17,2) AS returns#93, MakeDecimal(sum(UnscaledValue(wr_net_loss#82))#92,17,2) AS profit_loss#94] + +(77) BroadcastExchange +Input [3]: [wp_web_page_sk#86, returns#93, profit_loss#94] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +(78) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [wp_web_page_sk#71] +Right keys [1]: [wp_web_page_sk#86] +Join type: LeftOuter +Join condition: None + +(79) Project [codegen id : 22] +Output [5]: [sales#78, coalesce(returns#93, 0.00) AS returns#95, (profit#79 - coalesce(profit_loss#94, 0.00)) AS profit#96, web channel AS channel#97, wp_web_page_sk#71 AS id#98] +Input [6]: [wp_web_page_sk#71, sales#78, profit#79, wp_web_page_sk#86, returns#93, profit_loss#94] + +(80) Union + +(81) Expand [codegen id : 23] +Input [5]: [sales#14, returns#31, profit#32, channel#33, id#34] +Arguments: [[sales#14, returns#31, profit#32, channel#33, id#34, 0], [sales#14, returns#31, profit#32, channel#33, null, 1], [sales#14, returns#31, profit#32, null, null, 3]], [sales#14, returns#31, profit#32, channel#99, id#100, spark_grouping_id#101] + +(82) HashAggregate [codegen id : 23] +Input [6]: [sales#14, returns#31, profit#32, channel#99, id#100, spark_grouping_id#101] +Keys [3]: [channel#99, id#100, spark_grouping_id#101] +Functions [3]: [partial_sum(sales#14), partial_sum(returns#31), partial_sum(profit#32)] +Aggregate Attributes [6]: [sum#102, isEmpty#103, sum#104, isEmpty#105, sum#106, isEmpty#107] +Results [9]: [channel#99, id#100, spark_grouping_id#101, sum#108, isEmpty#109, sum#110, isEmpty#111, sum#112, isEmpty#113] + +(83) Exchange +Input [9]: [channel#99, id#100, spark_grouping_id#101, sum#108, isEmpty#109, sum#110, isEmpty#111, sum#112, isEmpty#113] +Arguments: hashpartitioning(channel#99, id#100, spark_grouping_id#101, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(84) HashAggregate [codegen id : 24] +Input [9]: [channel#99, id#100, spark_grouping_id#101, sum#108, isEmpty#109, sum#110, isEmpty#111, sum#112, isEmpty#113] +Keys [3]: [channel#99, id#100, spark_grouping_id#101] +Functions [3]: [sum(sales#14), sum(returns#31), sum(profit#32)] +Aggregate Attributes [3]: [sum(sales#14)#114, sum(returns#31)#115, sum(profit#32)#116] +Results [5]: [channel#99, id#100, sum(sales#14)#114 AS sales#117, sum(returns#31)#115 AS returns#118, sum(profit#32)#116 AS profit#119] + +(85) TakeOrderedAndProject +Input [5]: [channel#99, id#100, sales#117, returns#118, profit#119] +Arguments: 100, [channel#99 ASC NULLS FIRST, id#100 ASC NULLS FIRST], [channel#99, id#100, sales#117, returns#118, profit#119] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (90) ++- * Project (89) + +- * Filter (88) + +- * ColumnarToRow (87) + +- CometScan parquet spark_catalog.default.date_dim (86) + + +(86) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_date#120] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-08-03), LessThanOrEqual(d_date,2000-09-02), IsNotNull(d_date_sk)] +ReadSchema: struct + +(87) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#6, d_date#120] + +(88) Filter [codegen id : 1] +Input [2]: [d_date_sk#6, d_date#120] +Condition : (((isnotnull(d_date#120) AND (d_date#120 >= 2000-08-03)) AND (d_date#120 <= 2000-09-02)) AND isnotnull(d_date_sk#6)) + +(89) Project [codegen id : 1] +Output [1]: [d_date_sk#6] +Input [2]: [d_date_sk#6, d_date#120] + +(90) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:2 Hosting operator id = 16 Hosting Expression = sr_returned_date_sk#19 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 31 Hosting Expression = cs_sold_date_sk#38 IN dynamicpruning#5 + +Subquery:4 Hosting operator id = 40 Hosting Expression = cr_returned_date_sk#51 IN dynamicpruning#5 + +Subquery:5 Hosting operator id = 50 Hosting Expression = ws_sold_date_sk#68 IN dynamicpruning#5 + +Subquery:6 Hosting operator id = 65 Hosting Expression = wr_returned_date_sk#83 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/simplified.txt new file mode 100644 index 000000000..36cb2e9f5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/simplified.txt @@ -0,0 +1,143 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (24) + HashAggregate [channel,id,spark_grouping_id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id,spark_grouping_id] #1 + WholeStageCodegen (23) + HashAggregate [channel,id,spark_grouping_id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Expand [sales,returns,profit,channel,id] + InputAdapter + Union + WholeStageCodegen (8) + Project [sales,returns,profit,profit_loss,s_store_sk] + BroadcastHashJoin [s_store_sk,s_store_sk] + HashAggregate [s_store_sk,sum,sum] [sum(UnscaledValue(ss_ext_sales_price)),sum(UnscaledValue(ss_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [s_store_sk] #2 + WholeStageCodegen (3) + HashAggregate [s_store_sk,ss_ext_sales_price,ss_net_profit] [sum,sum,sum,sum] + Project [ss_ext_sales_price,ss_net_profit,s_store_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_ext_sales_price,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + HashAggregate [s_store_sk,sum,sum] [sum(UnscaledValue(sr_return_amt)),sum(UnscaledValue(sr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange [s_store_sk] #6 + WholeStageCodegen (6) + HashAggregate [s_store_sk,sr_return_amt,sr_net_loss] [sum,sum,sum,sum] + Project [sr_return_amt,sr_net_loss,s_store_sk] + BroadcastHashJoin [sr_store_sk,s_store_sk] + Project [sr_store_sk,sr_return_amt,sr_net_loss] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Filter [sr_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [s_store_sk] #4 + WholeStageCodegen (14) + Project [sales,returns,profit,profit_loss,cs_call_center_sk] + BroadcastNestedLoopJoin + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (11) + HashAggregate [cs_call_center_sk,sum,sum] [sum(UnscaledValue(cs_ext_sales_price)),sum(UnscaledValue(cs_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [cs_call_center_sk] #8 + WholeStageCodegen (10) + HashAggregate [cs_call_center_sk,cs_ext_sales_price,cs_net_profit] [sum,sum,sum,sum] + Project [cs_call_center_sk,cs_ext_sales_price,cs_net_profit] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_call_center_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + HashAggregate [sum,sum] [sum(UnscaledValue(cr_return_amount)),sum(UnscaledValue(cr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange #9 + WholeStageCodegen (13) + HashAggregate [cr_return_amount,cr_net_loss] [sum,sum,sum,sum] + Project [cr_return_amount,cr_net_loss] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_return_amount,cr_net_loss,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (22) + Project [sales,returns,profit,profit_loss,wp_web_page_sk] + BroadcastHashJoin [wp_web_page_sk,wp_web_page_sk] + HashAggregate [wp_web_page_sk,sum,sum] [sum(UnscaledValue(ws_ext_sales_price)),sum(UnscaledValue(ws_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [wp_web_page_sk] #10 + WholeStageCodegen (17) + HashAggregate [wp_web_page_sk,ws_ext_sales_price,ws_net_profit] [sum,sum,sum,sum] + Project [ws_ext_sales_price,ws_net_profit,wp_web_page_sk] + BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] + Project [ws_web_page_sk,ws_ext_sales_price,ws_net_profit] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_web_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_web_page_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (16) + Filter [wp_web_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_page [wp_web_page_sk] + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (21) + HashAggregate [wp_web_page_sk,sum,sum] [sum(UnscaledValue(wr_return_amt)),sum(UnscaledValue(wr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange [wp_web_page_sk] #13 + WholeStageCodegen (20) + HashAggregate [wp_web_page_sk,wr_return_amt,wr_net_loss] [sum,sum,sum,sum] + Project [wr_return_amt,wr_net_loss,wp_web_page_sk] + BroadcastHashJoin [wr_web_page_sk,wp_web_page_sk] + Project [wr_web_page_sk,wr_return_amt,wr_net_loss] + BroadcastHashJoin [wr_returned_date_sk,d_date_sk] + Filter [wr_web_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_web_page_sk,wr_return_amt,wr_net_loss,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + ReusedExchange [wp_web_page_sk] #11 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/explain.txt new file mode 100644 index 000000000..e2d0fc3ea --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/explain.txt @@ -0,0 +1,431 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * Project (69) + +- * SortMergeJoin Inner (68) + :- * Project (45) + : +- * SortMergeJoin Inner (44) + : :- * Sort (21) + : : +- * HashAggregate (20) + : : +- Exchange (19) + : : +- * HashAggregate (18) + : : +- * Project (17) + : : +- * BroadcastHashJoin Inner BuildRight (16) + : : :- * Project (14) + : : : +- * Filter (13) + : : : +- * SortMergeJoin LeftOuter (12) + : : : :- * Sort (5) + : : : : +- Exchange (4) + : : : : +- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- * Sort (11) + : : : +- Exchange (10) + : : : +- * Project (9) + : : : +- * Filter (8) + : : : +- * ColumnarToRow (7) + : : : +- CometScan parquet spark_catalog.default.store_returns (6) + : : +- ReusedExchange (15) + : +- * Sort (43) + : +- * Filter (42) + : +- * HashAggregate (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * Project (35) + : : +- * Filter (34) + : : +- * SortMergeJoin LeftOuter (33) + : : :- * Sort (26) + : : : +- Exchange (25) + : : : +- * Filter (24) + : : : +- * ColumnarToRow (23) + : : : +- CometScan parquet spark_catalog.default.web_sales (22) + : : +- * Sort (32) + : : +- Exchange (31) + : : +- * Project (30) + : : +- * Filter (29) + : : +- * ColumnarToRow (28) + : : +- CometScan parquet spark_catalog.default.web_returns (27) + : +- ReusedExchange (36) + +- * Sort (67) + +- * Filter (66) + +- * HashAggregate (65) + +- Exchange (64) + +- * HashAggregate (63) + +- * Project (62) + +- * BroadcastHashJoin Inner BuildRight (61) + :- * Project (59) + : +- * Filter (58) + : +- * SortMergeJoin LeftOuter (57) + : :- * Sort (50) + : : +- Exchange (49) + : : +- * Filter (48) + : : +- * ColumnarToRow (47) + : : +- CometScan parquet spark_catalog.default.catalog_sales (46) + : +- * Sort (56) + : +- Exchange (55) + : +- * Project (54) + : +- * Filter (53) + : +- * ColumnarToRow (52) + : +- CometScan parquet spark_catalog.default.catalog_returns (51) + +- ReusedExchange (60) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] + +(3) Filter [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_customer_sk#2)) + +(4) Exchange +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: hashpartitioning(ss_ticket_number#3, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: [ss_ticket_number#3 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(7) ColumnarToRow [codegen id : 3] +Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] + +(8) Filter [codegen id : 3] +Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Condition : (isnotnull(sr_ticket_number#10) AND isnotnull(sr_item_sk#9)) + +(9) Project [codegen id : 3] +Output [2]: [sr_item_sk#9, sr_ticket_number#10] +Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] + +(10) Exchange +Input [2]: [sr_item_sk#9, sr_ticket_number#10] +Arguments: hashpartitioning(sr_ticket_number#10, sr_item_sk#9, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [2]: [sr_item_sk#9, sr_ticket_number#10] +Arguments: [sr_ticket_number#10 ASC NULLS FIRST, sr_item_sk#9 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 6] +Left keys [2]: [ss_ticket_number#3, ss_item_sk#1] +Right keys [2]: [sr_ticket_number#10, sr_item_sk#9] +Join type: LeftOuter +Join condition: None + +(13) Filter [codegen id : 6] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10] +Condition : isnull(sr_ticket_number#10) + +(14) Project [codegen id : 6] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10] + +(15) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#12, d_year#13] + +(16) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 6] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, d_year#13] +Input [8]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, d_date_sk#12, d_year#13] + +(18) HashAggregate [codegen id : 6] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, d_year#13] +Keys [3]: [d_year#13, ss_item_sk#1, ss_customer_sk#2] +Functions [3]: [partial_sum(ss_quantity#4), partial_sum(UnscaledValue(ss_wholesale_cost#5)), partial_sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [3]: [sum#14, sum#15, sum#16] +Results [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] + +(19) Exchange +Input [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] +Arguments: hashpartitioning(d_year#13, ss_item_sk#1, ss_customer_sk#2, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 7] +Input [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] +Keys [3]: [d_year#13, ss_item_sk#1, ss_customer_sk#2] +Functions [3]: [sum(ss_quantity#4), sum(UnscaledValue(ss_wholesale_cost#5)), sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [3]: [sum(ss_quantity#4)#20, sum(UnscaledValue(ss_wholesale_cost#5))#21, sum(UnscaledValue(ss_sales_price#6))#22] +Results [6]: [d_year#13 AS ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, sum(ss_quantity#4)#20 AS ss_qty#24, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#5))#21,17,2) AS ss_wc#25, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#22,17,2) AS ss_sp#26] + +(21) Sort [codegen id : 7] +Input [6]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26] +Arguments: [ss_sold_year#23 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST, ss_customer_sk#2 ASC NULLS FIRST], false, 0 + +(22) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_sold_date_sk#33 IN dynamicpruning#34)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 8] +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] + +(24) Filter [codegen id : 8] +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_item_sk#27) AND isnotnull(ws_bill_customer_sk#28)) + +(25) Exchange +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Arguments: hashpartitioning(ws_order_number#29, ws_item_sk#27, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(26) Sort [codegen id : 9] +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Arguments: [ws_order_number#29 ASC NULLS FIRST, ws_item_sk#27 ASC NULLS FIRST], false, 0 + +(27) Scan parquet spark_catalog.default.web_returns +Output [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(28) ColumnarToRow [codegen id : 10] +Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] + +(29) Filter [codegen id : 10] +Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Condition : (isnotnull(wr_order_number#36) AND isnotnull(wr_item_sk#35)) + +(30) Project [codegen id : 10] +Output [2]: [wr_item_sk#35, wr_order_number#36] +Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] + +(31) Exchange +Input [2]: [wr_item_sk#35, wr_order_number#36] +Arguments: hashpartitioning(wr_order_number#36, wr_item_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 11] +Input [2]: [wr_item_sk#35, wr_order_number#36] +Arguments: [wr_order_number#36 ASC NULLS FIRST, wr_item_sk#35 ASC NULLS FIRST], false, 0 + +(33) SortMergeJoin [codegen id : 13] +Left keys [2]: [ws_order_number#29, ws_item_sk#27] +Right keys [2]: [wr_order_number#36, wr_item_sk#35] +Join type: LeftOuter +Join condition: None + +(34) Filter [codegen id : 13] +Input [9]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, wr_item_sk#35, wr_order_number#36] +Condition : isnull(wr_order_number#36) + +(35) Project [codegen id : 13] +Output [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Input [9]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, wr_item_sk#35, wr_order_number#36] + +(36) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#38, d_year#39] + +(37) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ws_sold_date_sk#33] +Right keys [1]: [d_date_sk#38] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 13] +Output [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, d_year#39] +Input [8]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, d_date_sk#38, d_year#39] + +(39) HashAggregate [codegen id : 13] +Input [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, d_year#39] +Keys [3]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28] +Functions [3]: [partial_sum(ws_quantity#30), partial_sum(UnscaledValue(ws_wholesale_cost#31)), partial_sum(UnscaledValue(ws_sales_price#32))] +Aggregate Attributes [3]: [sum#40, sum#41, sum#42] +Results [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] + +(40) Exchange +Input [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] +Arguments: hashpartitioning(d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 14] +Input [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] +Keys [3]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28] +Functions [3]: [sum(ws_quantity#30), sum(UnscaledValue(ws_wholesale_cost#31)), sum(UnscaledValue(ws_sales_price#32))] +Aggregate Attributes [3]: [sum(ws_quantity#30)#46, sum(UnscaledValue(ws_wholesale_cost#31))#47, sum(UnscaledValue(ws_sales_price#32))#48] +Results [6]: [d_year#39 AS ws_sold_year#49, ws_item_sk#27, ws_bill_customer_sk#28 AS ws_customer_sk#50, sum(ws_quantity#30)#46 AS ws_qty#51, MakeDecimal(sum(UnscaledValue(ws_wholesale_cost#31))#47,17,2) AS ws_wc#52, MakeDecimal(sum(UnscaledValue(ws_sales_price#32))#48,17,2) AS ws_sp#53] + +(42) Filter [codegen id : 14] +Input [6]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] +Condition : (coalesce(ws_qty#51, 0) > 0) + +(43) Sort [codegen id : 14] +Input [6]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] +Arguments: [ws_sold_year#49 ASC NULLS FIRST, ws_item_sk#27 ASC NULLS FIRST, ws_customer_sk#50 ASC NULLS FIRST], false, 0 + +(44) SortMergeJoin [codegen id : 15] +Left keys [3]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2] +Right keys [3]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 15] +Output [9]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, ws_wc#52, ws_sp#53] +Input [12]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] + +(46) Scan parquet spark_catalog.default.catalog_sales +Output [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#60), dynamicpruningexpression(cs_sold_date_sk#60 IN dynamicpruning#61)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 16] +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] + +(48) Filter [codegen id : 16] +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Condition : (isnotnull(cs_item_sk#55) AND isnotnull(cs_bill_customer_sk#54)) + +(49) Exchange +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Arguments: hashpartitioning(cs_order_number#56, cs_item_sk#55, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(50) Sort [codegen id : 17] +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Arguments: [cs_order_number#56 ASC NULLS FIRST, cs_item_sk#55 ASC NULLS FIRST], false, 0 + +(51) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(52) ColumnarToRow [codegen id : 18] +Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] + +(53) Filter [codegen id : 18] +Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Condition : (isnotnull(cr_order_number#63) AND isnotnull(cr_item_sk#62)) + +(54) Project [codegen id : 18] +Output [2]: [cr_item_sk#62, cr_order_number#63] +Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] + +(55) Exchange +Input [2]: [cr_item_sk#62, cr_order_number#63] +Arguments: hashpartitioning(cr_order_number#63, cr_item_sk#62, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(56) Sort [codegen id : 19] +Input [2]: [cr_item_sk#62, cr_order_number#63] +Arguments: [cr_order_number#63 ASC NULLS FIRST, cr_item_sk#62 ASC NULLS FIRST], false, 0 + +(57) SortMergeJoin [codegen id : 21] +Left keys [2]: [cs_order_number#56, cs_item_sk#55] +Right keys [2]: [cr_order_number#63, cr_item_sk#62] +Join type: LeftOuter +Join condition: None + +(58) Filter [codegen id : 21] +Input [9]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, cr_item_sk#62, cr_order_number#63] +Condition : isnull(cr_order_number#63) + +(59) Project [codegen id : 21] +Output [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Input [9]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, cr_item_sk#62, cr_order_number#63] + +(60) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#65, d_year#66] + +(61) BroadcastHashJoin [codegen id : 21] +Left keys [1]: [cs_sold_date_sk#60] +Right keys [1]: [d_date_sk#65] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 21] +Output [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, d_year#66] +Input [8]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, d_date_sk#65, d_year#66] + +(63) HashAggregate [codegen id : 21] +Input [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, d_year#66] +Keys [3]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54] +Functions [3]: [partial_sum(cs_quantity#57), partial_sum(UnscaledValue(cs_wholesale_cost#58)), partial_sum(UnscaledValue(cs_sales_price#59))] +Aggregate Attributes [3]: [sum#67, sum#68, sum#69] +Results [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] + +(64) Exchange +Input [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] +Arguments: hashpartitioning(d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 22] +Input [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] +Keys [3]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54] +Functions [3]: [sum(cs_quantity#57), sum(UnscaledValue(cs_wholesale_cost#58)), sum(UnscaledValue(cs_sales_price#59))] +Aggregate Attributes [3]: [sum(cs_quantity#57)#73, sum(UnscaledValue(cs_wholesale_cost#58))#74, sum(UnscaledValue(cs_sales_price#59))#75] +Results [6]: [d_year#66 AS cs_sold_year#76, cs_item_sk#55, cs_bill_customer_sk#54 AS cs_customer_sk#77, sum(cs_quantity#57)#73 AS cs_qty#78, MakeDecimal(sum(UnscaledValue(cs_wholesale_cost#58))#74,17,2) AS cs_wc#79, MakeDecimal(sum(UnscaledValue(cs_sales_price#59))#75,17,2) AS cs_sp#80] + +(66) Filter [codegen id : 22] +Input [6]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] +Condition : (coalesce(cs_qty#78, 0) > 0) + +(67) Sort [codegen id : 22] +Input [6]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] +Arguments: [cs_sold_year#76 ASC NULLS FIRST, cs_item_sk#55 ASC NULLS FIRST, cs_customer_sk#77 ASC NULLS FIRST], false, 0 + +(68) SortMergeJoin [codegen id : 23] +Left keys [3]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2] +Right keys [3]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77] +Join type: Inner +Join condition: None + +(69) Project [codegen id : 23] +Output [12]: [round((cast(ss_qty#24 as double) / cast(coalesce((ws_qty#51 + cs_qty#78), 1) as double)), 2) AS ratio#81, ss_qty#24 AS store_qty#82, ss_wc#25 AS store_wholesale_cost#83, ss_sp#26 AS store_sales_price#84, (coalesce(ws_qty#51, 0) + coalesce(cs_qty#78, 0)) AS other_chan_qty#85, (coalesce(ws_wc#52, 0.00) + coalesce(cs_wc#79, 0.00)) AS other_chan_wholesale_cost#86, (coalesce(ws_sp#53, 0.00) + coalesce(cs_sp#80, 0.00)) AS other_chan_sales_price#87, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, cs_qty#78] +Input [15]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, ws_wc#52, ws_sp#53, cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] + +(70) TakeOrderedAndProject +Input [12]: [ratio#81, store_qty#82, store_wholesale_cost#83, store_sales_price#84, other_chan_qty#85, other_chan_wholesale_cost#86, other_chan_sales_price#87, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, cs_qty#78] +Arguments: 100, [ratio#81 ASC NULLS FIRST, ss_qty#24 DESC NULLS LAST, ss_wc#25 DESC NULLS LAST, ss_sp#26 DESC NULLS LAST, other_chan_qty#85 ASC NULLS FIRST, other_chan_wholesale_cost#86 ASC NULLS FIRST, other_chan_sales_price#87 ASC NULLS FIRST, round((cast(ss_qty#24 as double) / cast(coalesce((ws_qty#51 + cs_qty#78), 1) as double)), 2) ASC NULLS FIRST], [ratio#81, store_qty#82, store_wholesale_cost#83, store_sales_price#84, other_chan_qty#85, other_chan_wholesale_cost#86, other_chan_sales_price#87] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (74) ++- * Filter (73) + +- * ColumnarToRow (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#12, d_year#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(72) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#12, d_year#13] + +(73) Filter [codegen id : 1] +Input [2]: [d_date_sk#12, d_year#13] +Condition : ((isnotnull(d_year#13) AND (d_year#13 = 2000)) AND isnotnull(d_date_sk#12)) + +(74) BroadcastExchange +Input [2]: [d_date_sk#12, d_year#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] + +Subquery:2 Hosting operator id = 22 Hosting Expression = ws_sold_date_sk#33 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 46 Hosting Expression = cs_sold_date_sk#60 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/simplified.txt new file mode 100644 index 000000000..bb2d54937 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/simplified.txt @@ -0,0 +1,127 @@ +TakeOrderedAndProject [ratio,ss_qty,ss_wc,ss_sp,other_chan_qty,other_chan_wholesale_cost,other_chan_sales_price,ws_qty,cs_qty,store_qty,store_wholesale_cost,store_sales_price] + WholeStageCodegen (23) + Project [ss_qty,ws_qty,cs_qty,ss_wc,ss_sp,ws_wc,cs_wc,ws_sp,cs_sp] + SortMergeJoin [ss_sold_year,ss_item_sk,ss_customer_sk,cs_sold_year,cs_item_sk,cs_customer_sk] + InputAdapter + WholeStageCodegen (15) + Project [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp,ws_qty,ws_wc,ws_sp] + SortMergeJoin [ss_sold_year,ss_item_sk,ss_customer_sk,ws_sold_year,ws_item_sk,ws_customer_sk] + InputAdapter + WholeStageCodegen (7) + Sort [ss_sold_year,ss_item_sk,ss_customer_sk] + HashAggregate [d_year,ss_item_sk,ss_customer_sk,sum,sum,sum] [sum(ss_quantity),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_sales_price)),ss_sold_year,ss_qty,ss_wc,ss_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,ss_item_sk,ss_customer_sk] #1 + WholeStageCodegen (6) + HashAggregate [d_year,ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price] [sum,sum,sum,sum,sum,sum] + Project [ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price,ss_sold_date_sk] + Filter [sr_ticket_number] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #2 + WholeStageCodegen (1) + Filter [ss_item_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_wholesale_cost,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #4 + WholeStageCodegen (3) + Project [sr_item_sk,sr_ticket_number] + Filter [sr_ticket_number,sr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + WholeStageCodegen (14) + Sort [ws_sold_year,ws_item_sk,ws_customer_sk] + Filter [ws_qty] + HashAggregate [d_year,ws_item_sk,ws_bill_customer_sk,sum,sum,sum] [sum(ws_quantity),sum(UnscaledValue(ws_wholesale_cost)),sum(UnscaledValue(ws_sales_price)),ws_sold_year,ws_customer_sk,ws_qty,ws_wc,ws_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,ws_item_sk,ws_bill_customer_sk] #5 + WholeStageCodegen (13) + HashAggregate [d_year,ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price] [sum,sum,sum,sum,sum,sum] + Project [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price,ws_sold_date_sk] + Filter [wr_order_number] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (9) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #6 + WholeStageCodegen (8) + Filter [ws_item_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_order_number,ws_quantity,ws_wholesale_cost,ws_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (11) + Sort [wr_order_number,wr_item_sk] + InputAdapter + Exchange [wr_order_number,wr_item_sk] #7 + WholeStageCodegen (10) + Project [wr_item_sk,wr_order_number] + Filter [wr_order_number,wr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + WholeStageCodegen (22) + Sort [cs_sold_year,cs_item_sk,cs_customer_sk] + Filter [cs_qty] + HashAggregate [d_year,cs_item_sk,cs_bill_customer_sk,sum,sum,sum] [sum(cs_quantity),sum(UnscaledValue(cs_wholesale_cost)),sum(UnscaledValue(cs_sales_price)),cs_sold_year,cs_customer_sk,cs_qty,cs_wc,cs_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,cs_item_sk,cs_bill_customer_sk] #8 + WholeStageCodegen (21) + HashAggregate [d_year,cs_item_sk,cs_bill_customer_sk,cs_quantity,cs_wholesale_cost,cs_sales_price] [sum,sum,sum,sum,sum,sum] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_wholesale_cost,cs_sales_price,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_wholesale_cost,cs_sales_price,cs_sold_date_sk] + Filter [cr_order_number] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (17) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #9 + WholeStageCodegen (16) + Filter [cs_item_sk,cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_order_number,cs_quantity,cs_wholesale_cost,cs_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (19) + Sort [cr_order_number,cr_item_sk] + InputAdapter + Exchange [cr_order_number,cr_item_sk] #10 + WholeStageCodegen (18) + Project [cr_item_sk,cr_order_number] + Filter [cr_order_number,cr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/explain.txt new file mode 100644 index 000000000..af1d4e56e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/explain.txt @@ -0,0 +1,208 @@ +== Physical Plan == +TakeOrderedAndProject (30) ++- * Project (29) + +- * BroadcastHashJoin Inner BuildRight (28) + :- * HashAggregate (23) + : +- Exchange (22) + : +- * HashAggregate (21) + : +- * Project (20) + : +- * BroadcastHashJoin Inner BuildRight (19) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * Project (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (18) + : +- * Project (17) + : +- * Filter (16) + : +- * ColumnarToRow (15) + : +- CometScan parquet spark_catalog.default.household_demographics (14) + +- BroadcastExchange (27) + +- * Filter (26) + +- * ColumnarToRow (25) + +- CometScan parquet spark_catalog.default.customer (24) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] + +(3) Filter [codegen id : 4] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) + +(4) ReusedExchange [Reuses operator id: 35] +Output [1]: [d_date_sk#10] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8, d_date_sk#10] + +(7) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#11, s_number_employees#12, s_city#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_number_employees), GreaterThanOrEqual(s_number_employees,200), LessThanOrEqual(s_number_employees,295), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [3]: [s_store_sk#11, s_number_employees#12, s_city#13] + +(9) Filter [codegen id : 2] +Input [3]: [s_store_sk#11, s_number_employees#12, s_city#13] +Condition : (((isnotnull(s_number_employees#12) AND (s_number_employees#12 >= 200)) AND (s_number_employees#12 <= 295)) AND isnotnull(s_store_sk#11)) + +(10) Project [codegen id : 2] +Output [2]: [s_store_sk#11, s_city#13] +Input [3]: [s_store_sk#11, s_number_employees#12, s_city#13] + +(11) BroadcastExchange +Input [2]: [s_store_sk#11, s_city#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#4] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_city#13] +Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_store_sk#11, s_city#13] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [Or(EqualTo(hd_dep_count,6),GreaterThan(hd_vehicle_count,2)), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] + +(16) Filter [codegen id : 3] +Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Condition : (((hd_dep_count#15 = 6) OR (hd_vehicle_count#16 > 2)) AND isnotnull(hd_demo_sk#14)) + +(17) Project [codegen id : 3] +Output [1]: [hd_demo_sk#14] +Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#14] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 4] +Output [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_city#13] +Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_city#13, hd_demo_sk#14] + +(21) HashAggregate [codegen id : 4] +Input [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_city#13] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13] +Functions [2]: [partial_sum(UnscaledValue(ss_coupon_amt#6)), partial_sum(UnscaledValue(ss_net_profit#7))] +Aggregate Attributes [2]: [sum#17, sum#18] +Results [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13, sum#19, sum#20] + +(22) Exchange +Input [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13, sum#19, sum#20] +Arguments: hashpartitioning(ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 6] +Input [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13, sum#19, sum#20] +Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, s_city#13] +Functions [2]: [sum(UnscaledValue(ss_coupon_amt#6)), sum(UnscaledValue(ss_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_coupon_amt#6))#21, sum(UnscaledValue(ss_net_profit#7))#22] +Results [5]: [ss_ticket_number#5, ss_customer_sk#1, s_city#13, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#6))#21,17,2) AS amt#23, MakeDecimal(sum(UnscaledValue(ss_net_profit#7))#22,17,2) AS profit#24] + +(24) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(25) ColumnarToRow [codegen id : 5] +Input [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] + +(26) Filter [codegen id : 5] +Input [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] +Condition : isnotnull(c_customer_sk#25) + +(27) BroadcastExchange +Input [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#25] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [7]: [c_last_name#27, c_first_name#26, substr(s_city#13, 1, 30) AS substr(s_city, 1, 30)#28, ss_ticket_number#5, amt#23, profit#24, s_city#13] +Input [8]: [ss_ticket_number#5, ss_customer_sk#1, s_city#13, amt#23, profit#24, c_customer_sk#25, c_first_name#26, c_last_name#27] + +(30) TakeOrderedAndProject +Input [7]: [c_last_name#27, c_first_name#26, substr(s_city, 1, 30)#28, ss_ticket_number#5, amt#23, profit#24, s_city#13] +Arguments: 100, [c_last_name#27 ASC NULLS FIRST, c_first_name#26 ASC NULLS FIRST, substr(s_city#13, 1, 30) ASC NULLS FIRST, profit#24 ASC NULLS FIRST], [c_last_name#27, c_first_name#26, substr(s_city, 1, 30)#28, ss_ticket_number#5, amt#23, profit#24] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (35) ++- * Project (34) + +- * Filter (33) + +- * ColumnarToRow (32) + +- CometScan parquet spark_catalog.default.date_dim (31) + + +(31) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#29, d_dow#30] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_dow), EqualTo(d_dow,1), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#29, d_dow#30] + +(33) Filter [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#29, d_dow#30] +Condition : (((isnotnull(d_dow#30) AND (d_dow#30 = 1)) AND d_year#29 IN (1999,2000,2001)) AND isnotnull(d_date_sk#10)) + +(34) Project [codegen id : 1] +Output [1]: [d_date_sk#10] +Input [3]: [d_date_sk#10, d_year#29, d_dow#30] + +(35) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/simplified.txt new file mode 100644 index 000000000..505434600 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/simplified.txt @@ -0,0 +1,52 @@ +TakeOrderedAndProject [c_last_name,c_first_name,s_city,profit,substr(s_city, 1, 30),ss_ticket_number,amt] + WholeStageCodegen (6) + Project [c_last_name,c_first_name,s_city,ss_ticket_number,amt,profit] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,s_city,sum,sum] [sum(UnscaledValue(ss_coupon_amt)),sum(UnscaledValue(ss_net_profit)),amt,profit,sum,sum] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk,ss_addr_sk,s_city] #1 + WholeStageCodegen (4) + HashAggregate [ss_ticket_number,ss_customer_sk,ss_addr_sk,s_city,ss_coupon_amt,ss_net_profit] [sum,sum,sum,sum] + Project [ss_customer_sk,ss_addr_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,s_city] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,s_city] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_dow,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dow] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [s_store_sk,s_city] + Filter [s_number_employees,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_number_employees,s_city] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Project [hd_demo_sk] + Filter [hd_dep_count,hd_vehicle_count,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (5) + Filter [c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/explain.txt new file mode 100644 index 000000000..0a4159cd9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/explain.txt @@ -0,0 +1,288 @@ +== Physical Plan == +TakeOrderedAndProject (43) ++- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * Filter (9) + : +- * ColumnarToRow (8) + : +- CometScan parquet spark_catalog.default.store (7) + +- BroadcastExchange (37) + +- * HashAggregate (36) + +- Exchange (35) + +- * HashAggregate (34) + +- * BroadcastHashJoin LeftSemi BuildRight (33) + :- * Project (16) + : +- * Filter (15) + : +- * ColumnarToRow (14) + : +- CometScan parquet spark_catalog.default.customer_address (13) + +- BroadcastExchange (32) + +- * Project (31) + +- * Filter (30) + +- * HashAggregate (29) + +- Exchange (28) + +- * HashAggregate (27) + +- * Project (26) + +- * BroadcastHashJoin Inner BuildRight (25) + :- * Filter (19) + : +- * ColumnarToRow (18) + : +- CometScan parquet spark_catalog.default.customer_address (17) + +- BroadcastExchange (24) + +- * Project (23) + +- * Filter (22) + +- * ColumnarToRow (21) + +- CometScan parquet spark_catalog.default.customer (20) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 8] +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] + +(3) Filter [codegen id : 8] +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) + +(4) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 8] +Output [2]: [ss_store_sk#1, ss_net_profit#2] +Input [4]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#6, s_store_name#7, s_zip#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_zip)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [3]: [s_store_sk#6, s_store_name#7, s_zip#8] + +(9) Filter [codegen id : 2] +Input [3]: [s_store_sk#6, s_store_name#7, s_zip#8] +Condition : (isnotnull(s_store_sk#6) AND isnotnull(s_zip#8)) + +(10) BroadcastExchange +Input [3]: [s_store_sk#6, s_store_name#7, s_zip#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 8] +Output [3]: [ss_net_profit#2, s_store_name#7, s_zip#8] +Input [5]: [ss_store_sk#1, ss_net_profit#2, s_store_sk#6, s_store_name#7, s_zip#8] + +(13) Scan parquet spark_catalog.default.customer_address +Output [1]: [ca_zip#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 6] +Input [1]: [ca_zip#9] + +(15) Filter [codegen id : 6] +Input [1]: [ca_zip#9] +Condition : (substr(ca_zip#9, 1, 5) INSET 10144, 10336, 10390, 10445, 10516, 10567, 11101, 11356, 11376, 11489, 11634, 11928, 12305, 13354, 13375, 13376, 13394, 13595, 13695, 13955, 14060, 14089, 14171, 14328, 14663, 14867, 14922, 15126, 15146, 15371, 15455, 15559, 15723, 15734, 15765, 15798, 15882, 16021, 16725, 16807, 17043, 17183, 17871, 17879, 17920, 18119, 18270, 18376, 18383, 18426, 18652, 18767, 18799, 18840, 18842, 18845, 18906, 19430, 19505, 19512, 19515, 19736, 19769, 19849, 20004, 20260, 20548, 21076, 21195, 21286, 21309, 21337, 21756, 22152, 22245, 22246, 22351, 22437, 22461, 22685, 22744, 22752, 22927, 23006, 23470, 23932, 23968, 24128, 24206, 24317, 24610, 24671, 24676, 24996, 25003, 25103, 25280, 25486, 25631, 25733, 25782, 25858, 25989, 26065, 26105, 26231, 26233, 26653, 26689, 26859, 27068, 27156, 27385, 27700, 28286, 28488, 28545, 28577, 28587, 28709, 28810, 28898, 28915, 29178, 29741, 29839, 30010, 30122, 30431, 30450, 30469, 30625, 30903, 31016, 31029, 31387, 31671, 31880, 32213, 32754, 33123, 33282, 33515, 33786, 34102, 34322, 34425, 35258, 35458, 35474, 35576, 35850, 35942, 36233, 36420, 36446, 36495, 36634, 37125, 37126, 37930, 38122, 38193, 38415, 38607, 38935, 39127, 39192, 39371, 39516, 39736, 39861, 39972, 40081, 40162, 40558, 40604, 41248, 41367, 41368, 41766, 41918, 42029, 42666, 42961, 43285, 43848, 43933, 44165, 44438, 45200, 45266, 45375, 45549, 45692, 45721, 45748, 46081, 46136, 46820, 47305, 47537, 47770, 48033, 48425, 48583, 49130, 49156, 49448, 50016, 50298, 50308, 50412, 51061, 51103, 51200, 51211, 51622, 51649, 51650, 51798, 51949, 52867, 53179, 53268, 53535, 53672, 54364, 54601, 54917, 55253, 55307, 55565, 56240, 56458, 56529, 56571, 56575, 56616, 56691, 56910, 57047, 57647, 57665, 57834, 57855, 58048, 58058, 58078, 58263, 58470, 58943, 59166, 59402, 60099, 60279, 60576, 61265, 61547, 61810, 61860, 62377, 62496, 62878, 62971, 63089, 63193, 63435, 63792, 63837, 63981, 64034, 64147, 64457, 64528, 64544, 65084, 65164, 66162, 66708, 66864, 67030, 67301, 67467, 67473, 67853, 67875, 67897, 68014, 68100, 68101, 68309, 68341, 68621, 68786, 68806, 68880, 68893, 68908, 69035, 69399, 69913, 69952, 70372, 70466, 70738, 71256, 71286, 71791, 71954, 72013, 72151, 72175, 72305, 72325, 72425, 72550, 72823, 73134, 73171, 73241, 73273, 73520, 73650, 74351, 75691, 76107, 76231, 76232, 76614, 76638, 76698, 77191, 77556, 77610, 77721, 78451, 78567, 78668, 78890, 79077, 79777, 79994, 81019, 81096, 81312, 81426, 82136, 82276, 82636, 83041, 83144, 83444, 83849, 83921, 83926, 83933, 84093, 84935, 85816, 86057, 86198, 86284, 86379, 87343, 87501, 87816, 88086, 88190, 88424, 88885, 89091, 89360, 90225, 90257, 90578, 91068, 91110, 91137, 91393, 92712, 94167, 94627, 94898, 94945, 94983, 96451, 96576, 96765, 96888, 96976, 97189, 97789, 98025, 98235, 98294, 98359, 98569, 99076, 99543 AND isnotnull(substr(ca_zip#9, 1, 5))) + +(16) Project [codegen id : 6] +Output [1]: [substr(ca_zip#9, 1, 5) AS ca_zip#10] +Input [1]: [ca_zip#9] + +(17) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#11, ca_zip#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 4] +Input [2]: [ca_address_sk#11, ca_zip#12] + +(19) Filter [codegen id : 4] +Input [2]: [ca_address_sk#11, ca_zip#12] +Condition : isnotnull(ca_address_sk#11) + +(20) Scan parquet spark_catalog.default.customer +Output [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_preferred_cust_flag), EqualTo(c_preferred_cust_flag,Y), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 3] +Input [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] + +(22) Filter [codegen id : 3] +Input [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] +Condition : ((isnotnull(c_preferred_cust_flag#14) AND (c_preferred_cust_flag#14 = Y)) AND isnotnull(c_current_addr_sk#13)) + +(23) Project [codegen id : 3] +Output [1]: [c_current_addr_sk#13] +Input [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] + +(24) BroadcastExchange +Input [1]: [c_current_addr_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(25) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ca_address_sk#11] +Right keys [1]: [c_current_addr_sk#13] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 4] +Output [1]: [ca_zip#12] +Input [3]: [ca_address_sk#11, ca_zip#12, c_current_addr_sk#13] + +(27) HashAggregate [codegen id : 4] +Input [1]: [ca_zip#12] +Keys [1]: [ca_zip#12] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#15] +Results [2]: [ca_zip#12, count#16] + +(28) Exchange +Input [2]: [ca_zip#12, count#16] +Arguments: hashpartitioning(ca_zip#12, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(29) HashAggregate [codegen id : 5] +Input [2]: [ca_zip#12, count#16] +Keys [1]: [ca_zip#12] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#17] +Results [2]: [substr(ca_zip#12, 1, 5) AS ca_zip#18, count(1)#17 AS cnt#19] + +(30) Filter [codegen id : 5] +Input [2]: [ca_zip#18, cnt#19] +Condition : (cnt#19 > 10) + +(31) Project [codegen id : 5] +Output [1]: [ca_zip#18] +Input [2]: [ca_zip#18, cnt#19] + +(32) BroadcastExchange +Input [1]: [ca_zip#18] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, string, true], ), isnull(input[0, string, true])),false), [plan_id=4] + +(33) BroadcastHashJoin [codegen id : 6] +Left keys [2]: [coalesce(ca_zip#10, ), isnull(ca_zip#10)] +Right keys [2]: [coalesce(ca_zip#18, ), isnull(ca_zip#18)] +Join type: LeftSemi +Join condition: None + +(34) HashAggregate [codegen id : 6] +Input [1]: [ca_zip#10] +Keys [1]: [ca_zip#10] +Functions: [] +Aggregate Attributes: [] +Results [1]: [ca_zip#10] + +(35) Exchange +Input [1]: [ca_zip#10] +Arguments: hashpartitioning(ca_zip#10, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(36) HashAggregate [codegen id : 7] +Input [1]: [ca_zip#10] +Keys [1]: [ca_zip#10] +Functions: [] +Aggregate Attributes: [] +Results [1]: [ca_zip#10] + +(37) BroadcastExchange +Input [1]: [ca_zip#10] +Arguments: HashedRelationBroadcastMode(List(substr(input[0, string, true], 1, 2)),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [substr(s_zip#8, 1, 2)] +Right keys [1]: [substr(ca_zip#10, 1, 2)] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 8] +Output [2]: [ss_net_profit#2, s_store_name#7] +Input [4]: [ss_net_profit#2, s_store_name#7, s_zip#8, ca_zip#10] + +(40) HashAggregate [codegen id : 8] +Input [2]: [ss_net_profit#2, s_store_name#7] +Keys [1]: [s_store_name#7] +Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum#20] +Results [2]: [s_store_name#7, sum#21] + +(41) Exchange +Input [2]: [s_store_name#7, sum#21] +Arguments: hashpartitioning(s_store_name#7, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(42) HashAggregate [codegen id : 9] +Input [2]: [s_store_name#7, sum#21] +Keys [1]: [s_store_name#7] +Functions [1]: [sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#2))#22] +Results [2]: [s_store_name#7, MakeDecimal(sum(UnscaledValue(ss_net_profit#2))#22,17,2) AS sum(ss_net_profit)#23] + +(43) TakeOrderedAndProject +Input [2]: [s_store_name#7, sum(ss_net_profit)#23] +Arguments: 100, [s_store_name#7 ASC NULLS FIRST], [s_store_name#7, sum(ss_net_profit)#23] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (48) ++- * Project (47) + +- * Filter (46) + +- * ColumnarToRow (45) + +- CometScan parquet spark_catalog.default.date_dim (44) + + +(44) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#5, d_year#24, d_qoy#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,1998), IsNotNull(d_date_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#5, d_year#24, d_qoy#25] + +(46) Filter [codegen id : 1] +Input [3]: [d_date_sk#5, d_year#24, d_qoy#25] +Condition : ((((isnotnull(d_qoy#25) AND isnotnull(d_year#24)) AND (d_qoy#25 = 2)) AND (d_year#24 = 1998)) AND isnotnull(d_date_sk#5)) + +(47) Project [codegen id : 1] +Output [1]: [d_date_sk#5] +Input [3]: [d_date_sk#5, d_year#24, d_qoy#25] + +(48) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/simplified.txt new file mode 100644 index 000000000..0cafe9244 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/simplified.txt @@ -0,0 +1,72 @@ +TakeOrderedAndProject [s_store_name,sum(ss_net_profit)] + WholeStageCodegen (9) + HashAggregate [s_store_name,sum] [sum(UnscaledValue(ss_net_profit)),sum(ss_net_profit),sum] + InputAdapter + Exchange [s_store_name] #1 + WholeStageCodegen (8) + HashAggregate [s_store_name,ss_net_profit] [sum,sum] + Project [ss_net_profit,s_store_name] + BroadcastHashJoin [s_zip,ca_zip] + Project [ss_net_profit,s_store_name,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_qoy,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [s_store_sk,s_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_zip] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [ca_zip] + InputAdapter + Exchange [ca_zip] #5 + WholeStageCodegen (6) + HashAggregate [ca_zip] + BroadcastHashJoin [ca_zip,ca_zip] + Project [ca_zip] + Filter [ca_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_zip] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Project [ca_zip] + Filter [cnt] + HashAggregate [ca_zip,count] [count(1),ca_zip,cnt,count] + InputAdapter + Exchange [ca_zip] #7 + WholeStageCodegen (4) + HashAggregate [ca_zip] [count,count] + Project [ca_zip] + BroadcastHashJoin [ca_address_sk,c_current_addr_sk] + Filter [ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_zip] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (3) + Project [c_current_addr_sk] + Filter [c_preferred_cust_flag,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_current_addr_sk,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/explain.txt new file mode 100644 index 000000000..6bee1df88 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/explain.txt @@ -0,0 +1,645 @@ +== Physical Plan == +TakeOrderedAndProject (107) ++- * HashAggregate (106) + +- Exchange (105) + +- * HashAggregate (104) + +- * Expand (103) + +- Union (102) + :- * HashAggregate (39) + : +- Exchange (38) + : +- * HashAggregate (37) + : +- * Project (36) + : +- * BroadcastHashJoin Inner BuildRight (35) + : :- * Project (29) + : : +- * BroadcastHashJoin Inner BuildRight (28) + : : :- * Project (22) + : : : +- * BroadcastHashJoin Inner BuildRight (21) + : : : :- * Project (16) + : : : : +- * BroadcastHashJoin Inner BuildRight (15) + : : : : :- * Project (13) + : : : : : +- * SortMergeJoin LeftOuter (12) + : : : : : :- * Sort (5) + : : : : : : +- Exchange (4) + : : : : : : +- * Filter (3) + : : : : : : +- * ColumnarToRow (2) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : +- * Sort (11) + : : : : : +- Exchange (10) + : : : : : +- * Project (9) + : : : : : +- * Filter (8) + : : : : : +- * ColumnarToRow (7) + : : : : : +- CometScan parquet spark_catalog.default.store_returns (6) + : : : : +- ReusedExchange (14) + : : : +- BroadcastExchange (20) + : : : +- * Filter (19) + : : : +- * ColumnarToRow (18) + : : : +- CometScan parquet spark_catalog.default.store (17) + : : +- BroadcastExchange (27) + : : +- * Project (26) + : : +- * Filter (25) + : : +- * ColumnarToRow (24) + : : +- CometScan parquet spark_catalog.default.item (23) + : +- BroadcastExchange (34) + : +- * Project (33) + : +- * Filter (32) + : +- * ColumnarToRow (31) + : +- CometScan parquet spark_catalog.default.promotion (30) + :- * HashAggregate (70) + : +- Exchange (69) + : +- * HashAggregate (68) + : +- * Project (67) + : +- * BroadcastHashJoin Inner BuildRight (66) + : :- * Project (64) + : : +- * BroadcastHashJoin Inner BuildRight (63) + : : :- * Project (61) + : : : +- * BroadcastHashJoin Inner BuildRight (60) + : : : :- * Project (55) + : : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : : :- * Project (52) + : : : : : +- * SortMergeJoin LeftOuter (51) + : : : : : :- * Sort (44) + : : : : : : +- Exchange (43) + : : : : : : +- * Filter (42) + : : : : : : +- * ColumnarToRow (41) + : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (40) + : : : : : +- * Sort (50) + : : : : : +- Exchange (49) + : : : : : +- * Project (48) + : : : : : +- * Filter (47) + : : : : : +- * ColumnarToRow (46) + : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (45) + : : : : +- ReusedExchange (53) + : : : +- BroadcastExchange (59) + : : : +- * Filter (58) + : : : +- * ColumnarToRow (57) + : : : +- CometScan parquet spark_catalog.default.catalog_page (56) + : : +- ReusedExchange (62) + : +- ReusedExchange (65) + +- * HashAggregate (101) + +- Exchange (100) + +- * HashAggregate (99) + +- * Project (98) + +- * BroadcastHashJoin Inner BuildRight (97) + :- * Project (95) + : +- * BroadcastHashJoin Inner BuildRight (94) + : :- * Project (92) + : : +- * BroadcastHashJoin Inner BuildRight (91) + : : :- * Project (86) + : : : +- * BroadcastHashJoin Inner BuildRight (85) + : : : :- * Project (83) + : : : : +- * SortMergeJoin LeftOuter (82) + : : : : :- * Sort (75) + : : : : : +- Exchange (74) + : : : : : +- * Filter (73) + : : : : : +- * ColumnarToRow (72) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (71) + : : : : +- * Sort (81) + : : : : +- Exchange (80) + : : : : +- * Project (79) + : : : : +- * Filter (78) + : : : : +- * ColumnarToRow (77) + : : : : +- CometScan parquet spark_catalog.default.web_returns (76) + : : : +- ReusedExchange (84) + : : +- BroadcastExchange (90) + : : +- * Filter (89) + : : +- * ColumnarToRow (88) + : : +- CometScan parquet spark_catalog.default.web_site (87) + : +- ReusedExchange (93) + +- ReusedExchange (96) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk), IsNotNull(ss_promo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] + +(3) Filter [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Condition : ((isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) + +(4) Exchange +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Arguments: hashpartitioning(ss_item_sk#1, ss_ticket_number#4, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Arguments: [ss_item_sk#1 ASC NULLS FIRST, ss_ticket_number#4 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(7) ColumnarToRow [codegen id : 3] +Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] + +(8) Filter [codegen id : 3] +Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Condition : (isnotnull(sr_item_sk#9) AND isnotnull(sr_ticket_number#10)) + +(9) Project [codegen id : 3] +Output [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] + +(10) Exchange +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +Arguments: hashpartitioning(sr_item_sk#9, sr_ticket_number#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +Arguments: [sr_item_sk#9 ASC NULLS FIRST, sr_ticket_number#10 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_item_sk#1, ss_ticket_number#4] +Right keys [2]: [sr_item_sk#9, sr_ticket_number#10] +Join type: LeftOuter +Join condition: None + +(13) Project [codegen id : 9] +Output [8]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_return_amt#11, sr_net_loss#12] +Input [11]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] + +(14) ReusedExchange [Reuses operator id: 112] +Output [1]: [d_date_sk#14] + +(15) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 9] +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_return_amt#11, sr_net_loss#12, d_date_sk#14] + +(17) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#15, s_store_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 6] +Input [2]: [s_store_sk#15, s_store_id#16] + +(19) Filter [codegen id : 6] +Input [2]: [s_store_sk#15, s_store_id#16] +Condition : isnotnull(s_store_sk#15) + +(20) BroadcastExchange +Input [2]: [s_store_sk#15, s_store_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#15] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 9] +Output [7]: [ss_item_sk#1, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_sk#15, s_store_id#16] + +(23) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#17, i_current_price#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThan(i_current_price,50.00), IsNotNull(i_item_sk)] +ReadSchema: struct + +(24) ColumnarToRow [codegen id : 7] +Input [2]: [i_item_sk#17, i_current_price#18] + +(25) Filter [codegen id : 7] +Input [2]: [i_item_sk#17, i_current_price#18] +Condition : ((isnotnull(i_current_price#18) AND (i_current_price#18 > 50.00)) AND isnotnull(i_item_sk#17)) + +(26) Project [codegen id : 7] +Output [1]: [i_item_sk#17] +Input [2]: [i_item_sk#17, i_current_price#18] + +(27) BroadcastExchange +Input [1]: [i_item_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 9] +Output [6]: [ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [8]: [ss_item_sk#1, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16, i_item_sk#17] + +(30) Scan parquet spark_catalog.default.promotion +Output [2]: [p_promo_sk#19, p_channel_tv#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_channel_tv), EqualTo(p_channel_tv,N), IsNotNull(p_promo_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 8] +Input [2]: [p_promo_sk#19, p_channel_tv#20] + +(32) Filter [codegen id : 8] +Input [2]: [p_promo_sk#19, p_channel_tv#20] +Condition : ((isnotnull(p_channel_tv#20) AND (p_channel_tv#20 = N)) AND isnotnull(p_promo_sk#19)) + +(33) Project [codegen id : 8] +Output [1]: [p_promo_sk#19] +Input [2]: [p_promo_sk#19, p_channel_tv#20] + +(34) BroadcastExchange +Input [1]: [p_promo_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(35) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_promo_sk#3] +Right keys [1]: [p_promo_sk#19] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 9] +Output [5]: [ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [7]: [ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16, p_promo_sk#19] + +(37) HashAggregate [codegen id : 9] +Input [5]: [ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Keys [1]: [s_store_id#16] +Functions [3]: [partial_sum(UnscaledValue(ss_ext_sales_price#5)), partial_sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00)), partial_sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Results [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] + +(38) Exchange +Input [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] +Arguments: hashpartitioning(s_store_id#16, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(39) HashAggregate [codegen id : 10] +Input [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] +Keys [1]: [s_store_id#16] +Functions [3]: [sum(UnscaledValue(ss_ext_sales_price#5)), sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00)), sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(ss_ext_sales_price#5))#31, sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00))#32, sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))#33] +Results [5]: [MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#31,17,2) AS sales#34, sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00))#32 AS returns#35, sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))#33 AS profit#36, store channel AS channel#37, concat(store, s_store_id#16) AS id#38] + +(40) Scan parquet spark_catalog.default.catalog_sales +Output [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_sold_date_sk#45 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cs_catalog_page_sk), IsNotNull(cs_item_sk), IsNotNull(cs_promo_sk)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 11] +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] + +(42) Filter [codegen id : 11] +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Condition : ((isnotnull(cs_catalog_page_sk#39) AND isnotnull(cs_item_sk#40)) AND isnotnull(cs_promo_sk#41)) + +(43) Exchange +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: hashpartitioning(cs_item_sk#40, cs_order_number#42, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(44) Sort [codegen id : 12] +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: [cs_item_sk#40 ASC NULLS FIRST, cs_order_number#42 ASC NULLS FIRST], false, 0 + +(45) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(46) ColumnarToRow [codegen id : 13] +Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] + +(47) Filter [codegen id : 13] +Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Condition : (isnotnull(cr_item_sk#47) AND isnotnull(cr_order_number#48)) + +(48) Project [codegen id : 13] +Output [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] + +(49) Exchange +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +Arguments: hashpartitioning(cr_item_sk#47, cr_order_number#48, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(50) Sort [codegen id : 14] +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +Arguments: [cr_item_sk#47 ASC NULLS FIRST, cr_order_number#48 ASC NULLS FIRST], false, 0 + +(51) SortMergeJoin [codegen id : 19] +Left keys [2]: [cs_item_sk#40, cs_order_number#42] +Right keys [2]: [cr_item_sk#47, cr_order_number#48] +Join type: LeftOuter +Join condition: None + +(52) Project [codegen id : 19] +Output [8]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_return_amount#49, cr_net_loss#50] +Input [11]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] + +(53) ReusedExchange [Reuses operator id: 112] +Output [1]: [d_date_sk#52] + +(54) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_sold_date_sk#45] +Right keys [1]: [d_date_sk#52] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 19] +Output [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50] +Input [9]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_return_amount#49, cr_net_loss#50, d_date_sk#52] + +(56) Scan parquet spark_catalog.default.catalog_page +Output [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_page] +PushedFilters: [IsNotNull(cp_catalog_page_sk)] +ReadSchema: struct + +(57) ColumnarToRow [codegen id : 16] +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] + +(58) Filter [codegen id : 16] +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Condition : isnotnull(cp_catalog_page_sk#53) + +(59) BroadcastExchange +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_catalog_page_sk#39] +Right keys [1]: [cp_catalog_page_sk#53] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 19] +Output [7]: [cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [9]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_sk#53, cp_catalog_page_id#54] + +(62) ReusedExchange [Reuses operator id: 27] +Output [1]: [i_item_sk#55] + +(63) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_item_sk#40] +Right keys [1]: [i_item_sk#55] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 19] +Output [6]: [cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [8]: [cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54, i_item_sk#55] + +(65) ReusedExchange [Reuses operator id: 34] +Output [1]: [p_promo_sk#56] + +(66) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_promo_sk#41] +Right keys [1]: [p_promo_sk#56] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 19] +Output [5]: [cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [7]: [cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54, p_promo_sk#56] + +(68) HashAggregate [codegen id : 19] +Input [5]: [cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Keys [1]: [cp_catalog_page_id#54] +Functions [3]: [partial_sum(UnscaledValue(cs_ext_sales_price#43)), partial_sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00)), partial_sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#57, sum#58, isEmpty#59, sum#60, isEmpty#61] +Results [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] + +(69) Exchange +Input [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] +Arguments: hashpartitioning(cp_catalog_page_id#54, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(70) HashAggregate [codegen id : 20] +Input [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] +Keys [1]: [cp_catalog_page_id#54] +Functions [3]: [sum(UnscaledValue(cs_ext_sales_price#43)), sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00)), sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(cs_ext_sales_price#43))#67, sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00))#68, sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))#69] +Results [5]: [MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#43))#67,17,2) AS sales#70, sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00))#68 AS returns#71, sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))#69 AS profit#72, catalog channel AS channel#73, concat(catalog_page, cp_catalog_page_id#54) AS id#74] + +(71) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#81), dynamicpruningexpression(ws_sold_date_sk#81 IN dynamicpruning#82)] +PushedFilters: [IsNotNull(ws_web_site_sk), IsNotNull(ws_item_sk), IsNotNull(ws_promo_sk)] +ReadSchema: struct + +(72) ColumnarToRow [codegen id : 21] +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] + +(73) Filter [codegen id : 21] +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Condition : ((isnotnull(ws_web_site_sk#76) AND isnotnull(ws_item_sk#75)) AND isnotnull(ws_promo_sk#77)) + +(74) Exchange +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Arguments: hashpartitioning(ws_item_sk#75, ws_order_number#78, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(75) Sort [codegen id : 22] +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Arguments: [ws_item_sk#75 ASC NULLS FIRST, ws_order_number#78 ASC NULLS FIRST], false, 0 + +(76) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_item_sk), IsNotNull(wr_order_number)] +ReadSchema: struct + +(77) ColumnarToRow [codegen id : 23] +Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] + +(78) Filter [codegen id : 23] +Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Condition : (isnotnull(wr_item_sk#83) AND isnotnull(wr_order_number#84)) + +(79) Project [codegen id : 23] +Output [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] + +(80) Exchange +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +Arguments: hashpartitioning(wr_item_sk#83, wr_order_number#84, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(81) Sort [codegen id : 24] +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +Arguments: [wr_item_sk#83 ASC NULLS FIRST, wr_order_number#84 ASC NULLS FIRST], false, 0 + +(82) SortMergeJoin [codegen id : 29] +Left keys [2]: [ws_item_sk#75, ws_order_number#78] +Right keys [2]: [wr_item_sk#83, wr_order_number#84] +Join type: LeftOuter +Join condition: None + +(83) Project [codegen id : 29] +Output [8]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_return_amt#85, wr_net_loss#86] +Input [11]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] + +(84) ReusedExchange [Reuses operator id: 112] +Output [1]: [d_date_sk#88] + +(85) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_sold_date_sk#81] +Right keys [1]: [d_date_sk#88] +Join type: Inner +Join condition: None + +(86) Project [codegen id : 29] +Output [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86] +Input [9]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_return_amt#85, wr_net_loss#86, d_date_sk#88] + +(87) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#89, web_site_id#90] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_site_sk)] +ReadSchema: struct + +(88) ColumnarToRow [codegen id : 26] +Input [2]: [web_site_sk#89, web_site_id#90] + +(89) Filter [codegen id : 26] +Input [2]: [web_site_sk#89, web_site_id#90] +Condition : isnotnull(web_site_sk#89) + +(90) BroadcastExchange +Input [2]: [web_site_sk#89, web_site_id#90] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +(91) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_web_site_sk#76] +Right keys [1]: [web_site_sk#89] +Join type: Inner +Join condition: None + +(92) Project [codegen id : 29] +Output [7]: [ws_item_sk#75, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [9]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_sk#89, web_site_id#90] + +(93) ReusedExchange [Reuses operator id: 27] +Output [1]: [i_item_sk#91] + +(94) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_item_sk#75] +Right keys [1]: [i_item_sk#91] +Join type: Inner +Join condition: None + +(95) Project [codegen id : 29] +Output [6]: [ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [8]: [ws_item_sk#75, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90, i_item_sk#91] + +(96) ReusedExchange [Reuses operator id: 34] +Output [1]: [p_promo_sk#92] + +(97) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_promo_sk#77] +Right keys [1]: [p_promo_sk#92] +Join type: Inner +Join condition: None + +(98) Project [codegen id : 29] +Output [5]: [ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [7]: [ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90, p_promo_sk#92] + +(99) HashAggregate [codegen id : 29] +Input [5]: [ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Keys [1]: [web_site_id#90] +Functions [3]: [partial_sum(UnscaledValue(ws_ext_sales_price#79)), partial_sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00)), partial_sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#93, sum#94, isEmpty#95, sum#96, isEmpty#97] +Results [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] + +(100) Exchange +Input [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] +Arguments: hashpartitioning(web_site_id#90, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(101) HashAggregate [codegen id : 30] +Input [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] +Keys [1]: [web_site_id#90] +Functions [3]: [sum(UnscaledValue(ws_ext_sales_price#79)), sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00)), sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_sales_price#79))#103, sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00))#104, sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))#105] +Results [5]: [MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#79))#103,17,2) AS sales#106, sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00))#104 AS returns#107, sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))#105 AS profit#108, web channel AS channel#109, concat(web_site, web_site_id#90) AS id#110] + +(102) Union + +(103) Expand [codegen id : 31] +Input [5]: [sales#34, returns#35, profit#36, channel#37, id#38] +Arguments: [[sales#34, returns#35, profit#36, channel#37, id#38, 0], [sales#34, returns#35, profit#36, channel#37, null, 1], [sales#34, returns#35, profit#36, null, null, 3]], [sales#34, returns#35, profit#36, channel#111, id#112, spark_grouping_id#113] + +(104) HashAggregate [codegen id : 31] +Input [6]: [sales#34, returns#35, profit#36, channel#111, id#112, spark_grouping_id#113] +Keys [3]: [channel#111, id#112, spark_grouping_id#113] +Functions [3]: [partial_sum(sales#34), partial_sum(returns#35), partial_sum(profit#36)] +Aggregate Attributes [6]: [sum#114, isEmpty#115, sum#116, isEmpty#117, sum#118, isEmpty#119] +Results [9]: [channel#111, id#112, spark_grouping_id#113, sum#120, isEmpty#121, sum#122, isEmpty#123, sum#124, isEmpty#125] + +(105) Exchange +Input [9]: [channel#111, id#112, spark_grouping_id#113, sum#120, isEmpty#121, sum#122, isEmpty#123, sum#124, isEmpty#125] +Arguments: hashpartitioning(channel#111, id#112, spark_grouping_id#113, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(106) HashAggregate [codegen id : 32] +Input [9]: [channel#111, id#112, spark_grouping_id#113, sum#120, isEmpty#121, sum#122, isEmpty#123, sum#124, isEmpty#125] +Keys [3]: [channel#111, id#112, spark_grouping_id#113] +Functions [3]: [sum(sales#34), sum(returns#35), sum(profit#36)] +Aggregate Attributes [3]: [sum(sales#34)#126, sum(returns#35)#127, sum(profit#36)#128] +Results [5]: [channel#111, id#112, sum(sales#34)#126 AS sales#129, sum(returns#35)#127 AS returns#130, sum(profit#36)#128 AS profit#131] + +(107) TakeOrderedAndProject +Input [5]: [channel#111, id#112, sales#129, returns#130, profit#131] +Arguments: 100, [channel#111 ASC NULLS FIRST, id#112 ASC NULLS FIRST], [channel#111, id#112, sales#129, returns#130, profit#131] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (112) ++- * Project (111) + +- * Filter (110) + +- * ColumnarToRow (109) + +- CometScan parquet spark_catalog.default.date_dim (108) + + +(108) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_date#132] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-08-23), LessThanOrEqual(d_date,2000-09-22), IsNotNull(d_date_sk)] +ReadSchema: struct + +(109) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#14, d_date#132] + +(110) Filter [codegen id : 1] +Input [2]: [d_date_sk#14, d_date#132] +Condition : (((isnotnull(d_date#132) AND (d_date#132 >= 2000-08-23)) AND (d_date#132 <= 2000-09-22)) AND isnotnull(d_date_sk#14)) + +(111) Project [codegen id : 1] +Output [1]: [d_date_sk#14] +Input [2]: [d_date_sk#14, d_date#132] + +(112) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=16] + +Subquery:2 Hosting operator id = 40 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 71 Hosting Expression = ws_sold_date_sk#81 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/simplified.txt new file mode 100644 index 000000000..9b229a658 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/simplified.txt @@ -0,0 +1,182 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (32) + HashAggregate [channel,id,spark_grouping_id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id,spark_grouping_id] #1 + WholeStageCodegen (31) + HashAggregate [channel,id,spark_grouping_id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + Expand [sales,returns,profit,channel,id] + InputAdapter + Union + WholeStageCodegen (10) + HashAggregate [s_store_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(ss_ext_sales_price)),sum(coalesce(cast(sr_return_amt as decimal(12,2)), 0.00)),sum((ss_net_profit - coalesce(cast(sr_net_loss as decimal(12,2)), 0.00))),sales,returns,profit,channel,id,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [s_store_id] #2 + WholeStageCodegen (9) + HashAggregate [s_store_id,ss_ext_sales_price,sr_return_amt,ss_net_profit,sr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk,sr_return_amt,sr_net_loss] + SortMergeJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + InputAdapter + WholeStageCodegen (2) + Sort [ss_item_sk,ss_ticket_number] + InputAdapter + Exchange [ss_item_sk,ss_ticket_number] #3 + WholeStageCodegen (1) + Filter [ss_store_sk,ss_item_sk,ss_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + WholeStageCodegen (4) + Sort [sr_item_sk,sr_ticket_number] + InputAdapter + Exchange [sr_item_sk,sr_ticket_number] #5 + WholeStageCodegen (3) + Project [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss] + Filter [sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (7) + Project [i_item_sk] + Filter [i_current_price,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (8) + Project [p_promo_sk] + Filter [p_channel_tv,p_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_tv] + WholeStageCodegen (20) + HashAggregate [cp_catalog_page_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(cs_ext_sales_price)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum((cs_net_profit - coalesce(cast(cr_net_loss as decimal(12,2)), 0.00))),sales,returns,profit,channel,id,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [cp_catalog_page_id] #9 + WholeStageCodegen (19) + HashAggregate [cp_catalog_page_id,cs_ext_sales_price,cr_return_amount,cs_net_profit,cr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_promo_sk,p_promo_sk] + Project [cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_catalog_page_sk,cp_catalog_page_sk] + Project [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk,cr_return_amount,cr_net_loss] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (12) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #10 + WholeStageCodegen (11) + Filter [cs_catalog_page_sk,cs_item_sk,cs_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (14) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #11 + WholeStageCodegen (13) + Project [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss] + Filter [cr_item_sk,cr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (16) + Filter [cp_catalog_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] + InputAdapter + ReusedExchange [i_item_sk] #7 + InputAdapter + ReusedExchange [p_promo_sk] #8 + WholeStageCodegen (30) + HashAggregate [web_site_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(ws_ext_sales_price)),sum(coalesce(cast(wr_return_amt as decimal(12,2)), 0.00)),sum((ws_net_profit - coalesce(cast(wr_net_loss as decimal(12,2)), 0.00))),sales,returns,profit,channel,id,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [web_site_id] #13 + WholeStageCodegen (29) + HashAggregate [web_site_id,ws_ext_sales_price,wr_return_amt,ws_net_profit,wr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_promo_sk,p_promo_sk] + Project [ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_web_site_sk,web_site_sk] + Project [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk,wr_return_amt,wr_net_loss] + SortMergeJoin [ws_item_sk,ws_order_number,wr_item_sk,wr_order_number] + InputAdapter + WholeStageCodegen (22) + Sort [ws_item_sk,ws_order_number] + InputAdapter + Exchange [ws_item_sk,ws_order_number] #14 + WholeStageCodegen (21) + Filter [ws_web_site_sk,ws_item_sk,ws_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_order_number,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (24) + Sort [wr_item_sk,wr_order_number] + InputAdapter + Exchange [wr_item_sk,wr_order_number] #15 + WholeStageCodegen (23) + Project [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss] + Filter [wr_item_sk,wr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #16 + WholeStageCodegen (26) + Filter [web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] + InputAdapter + ReusedExchange [i_item_sk] #7 + InputAdapter + ReusedExchange [p_promo_sk] #8 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/explain.txt new file mode 100644 index 000000000..dba7a3c3d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/explain.txt @@ -0,0 +1,319 @@ +== Physical Plan == +TakeOrderedAndProject (48) ++- * Project (47) + +- * BroadcastHashJoin Inner BuildRight (46) + :- * Project (41) + : +- * BroadcastHashJoin Inner BuildRight (40) + : :- * Project (35) + : : +- * BroadcastHashJoin Inner BuildRight (34) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (6) + : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (1) + : : : : +- ReusedExchange (4) + : : : +- BroadcastExchange (10) + : : : +- * Filter (9) + : : : +- * ColumnarToRow (8) + : : : +- CometScan parquet spark_catalog.default.customer_address (7) + : : +- BroadcastExchange (33) + : : +- * Filter (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * HashAggregate (28) + : : +- Exchange (27) + : : +- * HashAggregate (26) + : : +- * Project (25) + : : +- * BroadcastHashJoin Inner BuildRight (24) + : : :- * Project (22) + : : : +- * BroadcastHashJoin Inner BuildRight (21) + : : : :- * Filter (19) + : : : : +- * ColumnarToRow (18) + : : : : +- CometScan parquet spark_catalog.default.catalog_returns (17) + : : : +- ReusedExchange (20) + : : +- ReusedExchange (23) + : +- BroadcastExchange (39) + : +- * Filter (38) + : +- * ColumnarToRow (37) + : +- CometScan parquet spark_catalog.default.customer (36) + +- BroadcastExchange (45) + +- * Filter (44) + +- * ColumnarToRow (43) + +- CometScan parquet spark_catalog.default.customer_address (42) + + +(1) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, cr_returned_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#4), dynamicpruningexpression(cr_returned_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(cr_returning_addr_sk), IsNotNull(cr_returning_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [4]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, cr_returned_date_sk#4] + +(3) Filter [codegen id : 3] +Input [4]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, cr_returned_date_sk#4] +Condition : (isnotnull(cr_returning_addr_sk#2) AND isnotnull(cr_returning_customer_sk#1)) + +(4) ReusedExchange [Reuses operator id: 53] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cr_returned_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [3]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3] +Input [5]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, cr_returned_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_state#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_state)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_state#8] + +(9) Filter [codegen id : 2] +Input [2]: [ca_address_sk#7, ca_state#8] +Condition : (isnotnull(ca_address_sk#7) AND isnotnull(ca_state#8)) + +(10) BroadcastExchange +Input [2]: [ca_address_sk#7, ca_state#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cr_returning_addr_sk#2] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [cr_returning_customer_sk#1, cr_return_amt_inc_tax#3, ca_state#8] +Input [5]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, ca_address_sk#7, ca_state#8] + +(13) HashAggregate [codegen id : 3] +Input [3]: [cr_returning_customer_sk#1, cr_return_amt_inc_tax#3, ca_state#8] +Keys [2]: [cr_returning_customer_sk#1, ca_state#8] +Functions [1]: [partial_sum(UnscaledValue(cr_return_amt_inc_tax#3))] +Aggregate Attributes [1]: [sum#9] +Results [3]: [cr_returning_customer_sk#1, ca_state#8, sum#10] + +(14) Exchange +Input [3]: [cr_returning_customer_sk#1, ca_state#8, sum#10] +Arguments: hashpartitioning(cr_returning_customer_sk#1, ca_state#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 11] +Input [3]: [cr_returning_customer_sk#1, ca_state#8, sum#10] +Keys [2]: [cr_returning_customer_sk#1, ca_state#8] +Functions [1]: [sum(UnscaledValue(cr_return_amt_inc_tax#3))] +Aggregate Attributes [1]: [sum(UnscaledValue(cr_return_amt_inc_tax#3))#11] +Results [3]: [cr_returning_customer_sk#1 AS ctr_customer_sk#12, ca_state#8 AS ctr_state#13, MakeDecimal(sum(UnscaledValue(cr_return_amt_inc_tax#3))#11,17,2) AS ctr_total_return#14] + +(16) Filter [codegen id : 11] +Input [3]: [ctr_customer_sk#12, ctr_state#13, ctr_total_return#14] +Condition : isnotnull(ctr_total_return#14) + +(17) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, cr_returned_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#18), dynamicpruningexpression(cr_returned_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(cr_returning_addr_sk)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 6] +Input [4]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, cr_returned_date_sk#18] + +(19) Filter [codegen id : 6] +Input [4]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, cr_returned_date_sk#18] +Condition : isnotnull(cr_returning_addr_sk#16) + +(20) ReusedExchange [Reuses operator id: 53] +Output [1]: [d_date_sk#20] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cr_returned_date_sk#18] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [3]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17] +Input [5]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, cr_returned_date_sk#18, d_date_sk#20] + +(23) ReusedExchange [Reuses operator id: 10] +Output [2]: [ca_address_sk#21, ca_state#22] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cr_returning_addr_sk#16] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [3]: [cr_returning_customer_sk#15, cr_return_amt_inc_tax#17, ca_state#22] +Input [5]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, ca_address_sk#21, ca_state#22] + +(26) HashAggregate [codegen id : 6] +Input [3]: [cr_returning_customer_sk#15, cr_return_amt_inc_tax#17, ca_state#22] +Keys [2]: [cr_returning_customer_sk#15, ca_state#22] +Functions [1]: [partial_sum(UnscaledValue(cr_return_amt_inc_tax#17))] +Aggregate Attributes [1]: [sum#23] +Results [3]: [cr_returning_customer_sk#15, ca_state#22, sum#24] + +(27) Exchange +Input [3]: [cr_returning_customer_sk#15, ca_state#22, sum#24] +Arguments: hashpartitioning(cr_returning_customer_sk#15, ca_state#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(28) HashAggregate [codegen id : 7] +Input [3]: [cr_returning_customer_sk#15, ca_state#22, sum#24] +Keys [2]: [cr_returning_customer_sk#15, ca_state#22] +Functions [1]: [sum(UnscaledValue(cr_return_amt_inc_tax#17))] +Aggregate Attributes [1]: [sum(UnscaledValue(cr_return_amt_inc_tax#17))#11] +Results [2]: [ca_state#22 AS ctr_state#25, MakeDecimal(sum(UnscaledValue(cr_return_amt_inc_tax#17))#11,17,2) AS ctr_total_return#26] + +(29) HashAggregate [codegen id : 7] +Input [2]: [ctr_state#25, ctr_total_return#26] +Keys [1]: [ctr_state#25] +Functions [1]: [partial_avg(ctr_total_return#26)] +Aggregate Attributes [2]: [sum#27, count#28] +Results [3]: [ctr_state#25, sum#29, count#30] + +(30) Exchange +Input [3]: [ctr_state#25, sum#29, count#30] +Arguments: hashpartitioning(ctr_state#25, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 8] +Input [3]: [ctr_state#25, sum#29, count#30] +Keys [1]: [ctr_state#25] +Functions [1]: [avg(ctr_total_return#26)] +Aggregate Attributes [1]: [avg(ctr_total_return#26)#31] +Results [2]: [(avg(ctr_total_return#26)#31 * 1.2) AS (avg(ctr_total_return) * 1.2)#32, ctr_state#25] + +(32) Filter [codegen id : 8] +Input [2]: [(avg(ctr_total_return) * 1.2)#32, ctr_state#25] +Condition : isnotnull((avg(ctr_total_return) * 1.2)#32) + +(33) BroadcastExchange +Input [2]: [(avg(ctr_total_return) * 1.2)#32, ctr_state#25] +Arguments: HashedRelationBroadcastMode(List(input[1, string, true]),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ctr_state#13] +Right keys [1]: [ctr_state#25] +Join type: Inner +Join condition: (cast(ctr_total_return#14 as decimal(24,7)) > (avg(ctr_total_return) * 1.2)#32) + +(35) Project [codegen id : 11] +Output [2]: [ctr_customer_sk#12, ctr_total_return#14] +Input [5]: [ctr_customer_sk#12, ctr_state#13, ctr_total_return#14, (avg(ctr_total_return) * 1.2)#32, ctr_state#25] + +(36) Scan parquet spark_catalog.default.customer +Output [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(37) ColumnarToRow [codegen id : 9] +Input [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] + +(38) Filter [codegen id : 9] +Input [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] +Condition : (isnotnull(c_customer_sk#33) AND isnotnull(c_current_addr_sk#35)) + +(39) BroadcastExchange +Input [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(40) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ctr_customer_sk#12] +Right keys [1]: [c_customer_sk#33] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 11] +Output [6]: [ctr_total_return#14, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] +Input [8]: [ctr_customer_sk#12, ctr_total_return#14, c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] + +(42) Scan parquet spark_catalog.default.customer_address +Output [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,GA), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(43) ColumnarToRow [codegen id : 10] +Input [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] + +(44) Filter [codegen id : 10] +Input [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] +Condition : ((isnotnull(ca_state#46) AND (ca_state#46 = GA)) AND isnotnull(ca_address_sk#39)) + +(45) BroadcastExchange +Input [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(46) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [c_current_addr_sk#35] +Right keys [1]: [ca_address_sk#39] +Join type: Inner +Join condition: None + +(47) Project [codegen id : 11] +Output [16]: [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50, ctr_total_return#14] +Input [18]: [ctr_total_return#14, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] + +(48) TakeOrderedAndProject +Input [16]: [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50, ctr_total_return#14] +Arguments: 100, [c_customer_id#34 ASC NULLS FIRST, c_salutation#36 ASC NULLS FIRST, c_first_name#37 ASC NULLS FIRST, c_last_name#38 ASC NULLS FIRST, ca_street_number#40 ASC NULLS FIRST, ca_street_name#41 ASC NULLS FIRST, ca_street_type#42 ASC NULLS FIRST, ca_suite_number#43 ASC NULLS FIRST, ca_city#44 ASC NULLS FIRST, ca_county#45 ASC NULLS FIRST, ca_state#46 ASC NULLS FIRST, ca_zip#47 ASC NULLS FIRST, ca_country#48 ASC NULLS FIRST, ca_gmt_offset#49 ASC NULLS FIRST, ca_location_type#50 ASC NULLS FIRST, ctr_total_return#14 ASC NULLS FIRST], [c_customer_id#34, c_salutation#36, c_first_name#37, c_last_name#38, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50, ctr_total_return#14] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cr_returned_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (53) ++- * Project (52) + +- * Filter (51) + +- * ColumnarToRow (50) + +- CometScan parquet spark_catalog.default.date_dim (49) + + +(49) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_year#51] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(50) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#6, d_year#51] + +(51) Filter [codegen id : 1] +Input [2]: [d_date_sk#6, d_year#51] +Condition : ((isnotnull(d_year#51) AND (d_year#51 = 2000)) AND isnotnull(d_date_sk#6)) + +(52) Project [codegen id : 1] +Output [1]: [d_date_sk#6] +Input [2]: [d_date_sk#6, d_year#51] + +(53) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 17 Hosting Expression = cr_returned_date_sk#18 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/simplified.txt new file mode 100644 index 000000000..2b63992d3 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/simplified.txt @@ -0,0 +1,80 @@ +TakeOrderedAndProject [c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset,ca_location_type,ctr_total_return] + WholeStageCodegen (11) + Project [c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset,ca_location_type,ctr_total_return] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ctr_total_return,c_customer_id,c_current_addr_sk,c_salutation,c_first_name,c_last_name] + BroadcastHashJoin [ctr_customer_sk,c_customer_sk] + Project [ctr_customer_sk,ctr_total_return] + BroadcastHashJoin [ctr_state,ctr_state,ctr_total_return,(avg(ctr_total_return) * 1.2)] + Filter [ctr_total_return] + HashAggregate [cr_returning_customer_sk,ca_state,sum] [sum(UnscaledValue(cr_return_amt_inc_tax)),ctr_customer_sk,ctr_state,ctr_total_return,sum] + InputAdapter + Exchange [cr_returning_customer_sk,ca_state] #1 + WholeStageCodegen (3) + HashAggregate [cr_returning_customer_sk,ca_state,cr_return_amt_inc_tax] [sum,sum] + Project [cr_returning_customer_sk,cr_return_amt_inc_tax,ca_state] + BroadcastHashJoin [cr_returning_addr_sk,ca_address_sk] + Project [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + Filter [cr_returning_addr_sk,cr_returning_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax,cr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [ca_address_sk,ca_state] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (8) + Filter [(avg(ctr_total_return) * 1.2)] + HashAggregate [ctr_state,sum,count] [avg(ctr_total_return),(avg(ctr_total_return) * 1.2),sum,count] + InputAdapter + Exchange [ctr_state] #5 + WholeStageCodegen (7) + HashAggregate [ctr_state,ctr_total_return] [sum,count,sum,count] + HashAggregate [cr_returning_customer_sk,ca_state,sum] [sum(UnscaledValue(cr_return_amt_inc_tax)),ctr_state,ctr_total_return,sum] + InputAdapter + Exchange [cr_returning_customer_sk,ca_state] #6 + WholeStageCodegen (6) + HashAggregate [cr_returning_customer_sk,ca_state,cr_return_amt_inc_tax] [sum,sum] + Project [cr_returning_customer_sk,cr_return_amt_inc_tax,ca_state] + BroadcastHashJoin [cr_returning_addr_sk,ca_address_sk] + Project [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + Filter [cr_returning_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [ca_address_sk,ca_state] #3 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (9) + Filter [c_customer_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_current_addr_sk,c_salutation,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (10) + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_street_number,ca_street_name,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset,ca_location_type] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/explain.txt new file mode 100644 index 000000000..348f4d58b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/explain.txt @@ -0,0 +1,179 @@ +== Physical Plan == +TakeOrderedAndProject (25) ++- * HashAggregate (24) + +- Exchange (23) + +- * HashAggregate (22) + +- * Project (21) + +- * BroadcastHashJoin Inner BuildLeft (20) + :- BroadcastExchange (15) + : +- * Project (14) + : +- * BroadcastHashJoin Inner BuildRight (13) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildRight (10) + : : :- * Project (4) + : : : +- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.item (1) + : : +- BroadcastExchange (9) + : : +- * Project (8) + : : +- * Filter (7) + : : +- * ColumnarToRow (6) + : : +- CometScan parquet spark_catalog.default.inventory (5) + : +- ReusedExchange (12) + +- * Project (19) + +- * Filter (18) + +- * ColumnarToRow (17) + +- CometScan parquet spark_catalog.default.store_sales (16) + + +(1) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,62.00), LessThanOrEqual(i_current_price,92.00), In(i_manufact_id, [129,270,423,821]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] + +(3) Filter [codegen id : 3] +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Condition : ((((isnotnull(i_current_price#4) AND (i_current_price#4 >= 62.00)) AND (i_current_price#4 <= 92.00)) AND i_manufact_id#5 IN (129,270,821,423)) AND isnotnull(i_item_sk#1)) + +(4) Project [codegen id : 3] +Output [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] + +(5) Scan parquet spark_catalog.default.inventory +Output [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#8), dynamicpruningexpression(inv_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(inv_quantity_on_hand), GreaterThanOrEqual(inv_quantity_on_hand,100), LessThanOrEqual(inv_quantity_on_hand,500), IsNotNull(inv_item_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] + +(7) Filter [codegen id : 1] +Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Condition : (((isnotnull(inv_quantity_on_hand#7) AND (inv_quantity_on_hand#7 >= 100)) AND (inv_quantity_on_hand#7 <= 500)) AND isnotnull(inv_item_sk#6)) + +(8) Project [codegen id : 1] +Output [2]: [inv_item_sk#6, inv_date_sk#8] +Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] + +(9) BroadcastExchange +Input [2]: [inv_item_sk#6, inv_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [inv_item_sk#6] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 3] +Output [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_date_sk#8] +Input [6]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_item_sk#6, inv_date_sk#8] + +(12) ReusedExchange [Reuses operator id: 30] +Output [1]: [d_date_sk#10] + +(13) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [inv_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 3] +Output [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +Input [6]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, inv_date_sk#8, d_date_sk#10] + +(15) BroadcastExchange +Input [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#11, ss_sold_date_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow +Input [2]: [ss_item_sk#11, ss_sold_date_sk#12] + +(18) Filter +Input [2]: [ss_item_sk#11, ss_sold_date_sk#12] +Condition : isnotnull(ss_item_sk#11) + +(19) Project +Output [1]: [ss_item_sk#11] +Input [2]: [ss_item_sk#11, ss_sold_date_sk#12] + +(20) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#11] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 4] +Output [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, ss_item_sk#11] + +(22) HashAggregate [codegen id : 4] +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Keys [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Functions: [] +Aggregate Attributes: [] +Results [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] + +(23) Exchange +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: hashpartitioning(i_item_id#2, i_item_desc#3, i_current_price#4, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(24) HashAggregate [codegen id : 5] +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Keys [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Functions: [] +Aggregate Attributes: [] +Results [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] + +(25) TakeOrderedAndProject +Input [3]: [i_item_id#2, i_item_desc#3, i_current_price#4] +Arguments: 100, [i_item_id#2 ASC NULLS FIRST], [i_item_id#2, i_item_desc#3, i_current_price#4] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 5 Hosting Expression = inv_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (30) ++- * Project (29) + +- * Filter (28) + +- * ColumnarToRow (27) + +- CometScan parquet spark_catalog.default.date_dim (26) + + +(26) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#10, d_date#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-05-25), LessThanOrEqual(d_date,2000-07-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(27) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#10, d_date#13] + +(28) Filter [codegen id : 1] +Input [2]: [d_date_sk#10, d_date#13] +Condition : (((isnotnull(d_date#13) AND (d_date#13 >= 2000-05-25)) AND (d_date#13 <= 2000-07-24)) AND isnotnull(d_date_sk#10)) + +(29) Project [codegen id : 1] +Output [1]: [d_date_sk#10] +Input [2]: [d_date_sk#10, d_date#13] + +(30) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/simplified.txt new file mode 100644 index 000000000..631237f50 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/simplified.txt @@ -0,0 +1,44 @@ +TakeOrderedAndProject [i_item_id,i_item_desc,i_current_price] + WholeStageCodegen (5) + HashAggregate [i_item_id,i_item_desc,i_current_price] + InputAdapter + Exchange [i_item_id,i_item_desc,i_current_price] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_current_price] + Project [i_item_id,i_item_desc,i_current_price] + BroadcastHashJoin [i_item_sk,ss_item_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (3) + Project [i_item_sk,i_item_id,i_item_desc,i_current_price] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Project [i_item_sk,i_item_id,i_item_desc,i_current_price,inv_date_sk] + BroadcastHashJoin [i_item_sk,inv_item_sk] + Project [i_item_sk,i_item_id,i_item_desc,i_current_price] + Filter [i_current_price,i_manufact_id,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_manufact_id] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [inv_item_sk,inv_date_sk] + Filter [inv_quantity_on_hand,inv_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + ReusedExchange [d_date_sk] #4 + Project [ss_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/explain.txt new file mode 100644 index 000000000..74f90aab2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/explain.txt @@ -0,0 +1,372 @@ +== Physical Plan == +TakeOrderedAndProject (46) ++- * Project (45) + +- * BroadcastHashJoin Inner BuildRight (44) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_returns (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.item (4) + : : +- ReusedExchange (10) + : +- BroadcastExchange (28) + : +- * HashAggregate (27) + : +- Exchange (26) + : +- * HashAggregate (25) + : +- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (21) + : : +- * BroadcastHashJoin Inner BuildRight (20) + : : :- * Filter (18) + : : : +- * ColumnarToRow (17) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (16) + : : +- ReusedExchange (19) + : +- ReusedExchange (22) + +- BroadcastExchange (43) + +- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (36) + : +- * BroadcastHashJoin Inner BuildRight (35) + : :- * Filter (33) + : : +- * ColumnarToRow (32) + : : +- CometScan parquet spark_catalog.default.web_returns (31) + : +- ReusedExchange (34) + +- ReusedExchange (37) + + +(1) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#1, sr_return_quantity#2, sr_returned_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#3), dynamicpruningexpression(sr_returned_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(sr_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [3]: [sr_item_sk#1, sr_return_quantity#2, sr_returned_date_sk#3] + +(3) Filter [codegen id : 5] +Input [3]: [sr_item_sk#1, sr_return_quantity#2, sr_returned_date_sk#3] +Condition : isnotnull(sr_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#5, i_item_id#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_item_id)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [i_item_sk#5, i_item_id#6] + +(6) Filter [codegen id : 1] +Input [2]: [i_item_sk#5, i_item_id#6] +Condition : (isnotnull(i_item_sk#5) AND isnotnull(i_item_id#6)) + +(7) BroadcastExchange +Input [2]: [i_item_sk#5, i_item_id#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [sr_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [3]: [sr_return_quantity#2, sr_returned_date_sk#3, i_item_id#6] +Input [5]: [sr_item_sk#1, sr_return_quantity#2, sr_returned_date_sk#3, i_item_sk#5, i_item_id#6] + +(10) ReusedExchange [Reuses operator id: 62] +Output [1]: [d_date_sk#7] + +(11) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [sr_returned_date_sk#3] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 5] +Output [2]: [sr_return_quantity#2, i_item_id#6] +Input [4]: [sr_return_quantity#2, sr_returned_date_sk#3, i_item_id#6, d_date_sk#7] + +(13) HashAggregate [codegen id : 5] +Input [2]: [sr_return_quantity#2, i_item_id#6] +Keys [1]: [i_item_id#6] +Functions [1]: [partial_sum(sr_return_quantity#2)] +Aggregate Attributes [1]: [sum#8] +Results [2]: [i_item_id#6, sum#9] + +(14) Exchange +Input [2]: [i_item_id#6, sum#9] +Arguments: hashpartitioning(i_item_id#6, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 18] +Input [2]: [i_item_id#6, sum#9] +Keys [1]: [i_item_id#6] +Functions [1]: [sum(sr_return_quantity#2)] +Aggregate Attributes [1]: [sum(sr_return_quantity#2)#10] +Results [2]: [i_item_id#6 AS item_id#11, sum(sr_return_quantity#2)#10 AS sr_item_qty#12] + +(16) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_item_sk#13, cr_return_quantity#14, cr_returned_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#15), dynamicpruningexpression(cr_returned_date_sk#15 IN dynamicpruning#16)] +PushedFilters: [IsNotNull(cr_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 10] +Input [3]: [cr_item_sk#13, cr_return_quantity#14, cr_returned_date_sk#15] + +(18) Filter [codegen id : 10] +Input [3]: [cr_item_sk#13, cr_return_quantity#14, cr_returned_date_sk#15] +Condition : isnotnull(cr_item_sk#13) + +(19) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#17, i_item_id#18] + +(20) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cr_item_sk#13] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 10] +Output [3]: [cr_return_quantity#14, cr_returned_date_sk#15, i_item_id#18] +Input [5]: [cr_item_sk#13, cr_return_quantity#14, cr_returned_date_sk#15, i_item_sk#17, i_item_id#18] + +(22) ReusedExchange [Reuses operator id: 62] +Output [1]: [d_date_sk#19] + +(23) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cr_returned_date_sk#15] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 10] +Output [2]: [cr_return_quantity#14, i_item_id#18] +Input [4]: [cr_return_quantity#14, cr_returned_date_sk#15, i_item_id#18, d_date_sk#19] + +(25) HashAggregate [codegen id : 10] +Input [2]: [cr_return_quantity#14, i_item_id#18] +Keys [1]: [i_item_id#18] +Functions [1]: [partial_sum(cr_return_quantity#14)] +Aggregate Attributes [1]: [sum#20] +Results [2]: [i_item_id#18, sum#21] + +(26) Exchange +Input [2]: [i_item_id#18, sum#21] +Arguments: hashpartitioning(i_item_id#18, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 11] +Input [2]: [i_item_id#18, sum#21] +Keys [1]: [i_item_id#18] +Functions [1]: [sum(cr_return_quantity#14)] +Aggregate Attributes [1]: [sum(cr_return_quantity#14)#22] +Results [2]: [i_item_id#18 AS item_id#23, sum(cr_return_quantity#14)#22 AS cr_item_qty#24] + +(28) BroadcastExchange +Input [2]: [item_id#23, cr_item_qty#24] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [item_id#11] +Right keys [1]: [item_id#23] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 18] +Output [3]: [item_id#11, sr_item_qty#12, cr_item_qty#24] +Input [4]: [item_id#11, sr_item_qty#12, item_id#23, cr_item_qty#24] + +(31) Scan parquet spark_catalog.default.web_returns +Output [3]: [wr_item_sk#25, wr_return_quantity#26, wr_returned_date_sk#27] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#27), dynamicpruningexpression(wr_returned_date_sk#27 IN dynamicpruning#28)] +PushedFilters: [IsNotNull(wr_item_sk)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 16] +Input [3]: [wr_item_sk#25, wr_return_quantity#26, wr_returned_date_sk#27] + +(33) Filter [codegen id : 16] +Input [3]: [wr_item_sk#25, wr_return_quantity#26, wr_returned_date_sk#27] +Condition : isnotnull(wr_item_sk#25) + +(34) ReusedExchange [Reuses operator id: 7] +Output [2]: [i_item_sk#29, i_item_id#30] + +(35) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [wr_item_sk#25] +Right keys [1]: [i_item_sk#29] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 16] +Output [3]: [wr_return_quantity#26, wr_returned_date_sk#27, i_item_id#30] +Input [5]: [wr_item_sk#25, wr_return_quantity#26, wr_returned_date_sk#27, i_item_sk#29, i_item_id#30] + +(37) ReusedExchange [Reuses operator id: 62] +Output [1]: [d_date_sk#31] + +(38) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [wr_returned_date_sk#27] +Right keys [1]: [d_date_sk#31] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 16] +Output [2]: [wr_return_quantity#26, i_item_id#30] +Input [4]: [wr_return_quantity#26, wr_returned_date_sk#27, i_item_id#30, d_date_sk#31] + +(40) HashAggregate [codegen id : 16] +Input [2]: [wr_return_quantity#26, i_item_id#30] +Keys [1]: [i_item_id#30] +Functions [1]: [partial_sum(wr_return_quantity#26)] +Aggregate Attributes [1]: [sum#32] +Results [2]: [i_item_id#30, sum#33] + +(41) Exchange +Input [2]: [i_item_id#30, sum#33] +Arguments: hashpartitioning(i_item_id#30, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(42) HashAggregate [codegen id : 17] +Input [2]: [i_item_id#30, sum#33] +Keys [1]: [i_item_id#30] +Functions [1]: [sum(wr_return_quantity#26)] +Aggregate Attributes [1]: [sum(wr_return_quantity#26)#34] +Results [2]: [i_item_id#30 AS item_id#35, sum(wr_return_quantity#26)#34 AS wr_item_qty#36] + +(43) BroadcastExchange +Input [2]: [item_id#35, wr_item_qty#36] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=6] + +(44) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [item_id#11] +Right keys [1]: [item_id#35] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 18] +Output [8]: [item_id#11, sr_item_qty#12, (((cast(sr_item_qty#12 as double) / cast(((sr_item_qty#12 + cr_item_qty#24) + wr_item_qty#36) as double)) / 3.0) * 100.0) AS sr_dev#37, cr_item_qty#24, (((cast(cr_item_qty#24 as double) / cast(((sr_item_qty#12 + cr_item_qty#24) + wr_item_qty#36) as double)) / 3.0) * 100.0) AS cr_dev#38, wr_item_qty#36, (((cast(wr_item_qty#36 as double) / cast(((sr_item_qty#12 + cr_item_qty#24) + wr_item_qty#36) as double)) / 3.0) * 100.0) AS wr_dev#39, (cast(((sr_item_qty#12 + cr_item_qty#24) + wr_item_qty#36) as decimal(20,0)) / 3.0) AS average#40] +Input [5]: [item_id#11, sr_item_qty#12, cr_item_qty#24, item_id#35, wr_item_qty#36] + +(46) TakeOrderedAndProject +Input [8]: [item_id#11, sr_item_qty#12, sr_dev#37, cr_item_qty#24, cr_dev#38, wr_item_qty#36, wr_dev#39, average#40] +Arguments: 100, [item_id#11 ASC NULLS FIRST, sr_item_qty#12 ASC NULLS FIRST], [item_id#11, sr_item_qty#12, sr_dev#37, cr_item_qty#24, cr_dev#38, wr_item_qty#36, wr_dev#39, average#40] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = sr_returned_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (62) ++- * Project (61) + +- * BroadcastHashJoin LeftSemi BuildRight (60) + :- * Filter (49) + : +- * ColumnarToRow (48) + : +- CometScan parquet spark_catalog.default.date_dim (47) + +- BroadcastExchange (59) + +- * Project (58) + +- * BroadcastHashJoin LeftSemi BuildRight (57) + :- * ColumnarToRow (51) + : +- CometScan parquet spark_catalog.default.date_dim (50) + +- BroadcastExchange (56) + +- * Project (55) + +- * Filter (54) + +- * ColumnarToRow (53) + +- CometScan parquet spark_catalog.default.date_dim (52) + + +(47) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#7, d_date#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(48) ColumnarToRow [codegen id : 3] +Input [2]: [d_date_sk#7, d_date#41] + +(49) Filter [codegen id : 3] +Input [2]: [d_date_sk#7, d_date#41] +Condition : isnotnull(d_date_sk#7) + +(50) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date#42, d_week_seq#43] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +ReadSchema: struct + +(51) ColumnarToRow [codegen id : 2] +Input [2]: [d_date#42, d_week_seq#43] + +(52) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date#44, d_week_seq#45] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [In(d_date, [2000-06-30,2000-09-27,2000-11-17])] +ReadSchema: struct + +(53) ColumnarToRow [codegen id : 1] +Input [2]: [d_date#44, d_week_seq#45] + +(54) Filter [codegen id : 1] +Input [2]: [d_date#44, d_week_seq#45] +Condition : d_date#44 IN (2000-06-30,2000-09-27,2000-11-17) + +(55) Project [codegen id : 1] +Output [1]: [d_week_seq#45] +Input [2]: [d_date#44, d_week_seq#45] + +(56) BroadcastExchange +Input [1]: [d_week_seq#45] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(57) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [d_week_seq#43] +Right keys [1]: [d_week_seq#45] +Join type: LeftSemi +Join condition: None + +(58) Project [codegen id : 2] +Output [1]: [d_date#42] +Input [2]: [d_date#42, d_week_seq#43] + +(59) BroadcastExchange +Input [1]: [d_date#42] +Arguments: HashedRelationBroadcastMode(List(input[0, date, true]),false), [plan_id=8] + +(60) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [d_date#41] +Right keys [1]: [d_date#42] +Join type: LeftSemi +Join condition: None + +(61) Project [codegen id : 3] +Output [1]: [d_date_sk#7] +Input [2]: [d_date_sk#7, d_date#41] + +(62) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 16 Hosting Expression = cr_returned_date_sk#15 IN dynamicpruning#4 + +Subquery:3 Hosting operator id = 31 Hosting Expression = wr_returned_date_sk#27 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/simplified.txt new file mode 100644 index 000000000..52f1fe4b5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/simplified.txt @@ -0,0 +1,95 @@ +TakeOrderedAndProject [item_id,sr_item_qty,sr_dev,cr_item_qty,cr_dev,wr_item_qty,wr_dev,average] + WholeStageCodegen (18) + Project [item_id,sr_item_qty,cr_item_qty,wr_item_qty] + BroadcastHashJoin [item_id,item_id] + Project [item_id,sr_item_qty,cr_item_qty] + BroadcastHashJoin [item_id,item_id] + HashAggregate [i_item_id,sum] [sum(sr_return_quantity),item_id,sr_item_qty,sum] + InputAdapter + Exchange [i_item_id] #1 + WholeStageCodegen (5) + HashAggregate [i_item_id,sr_return_quantity] [sum,sum] + Project [sr_return_quantity,i_item_id] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Project [sr_return_quantity,sr_returned_date_sk,i_item_id] + BroadcastHashJoin [sr_item_sk,i_item_sk] + Filter [sr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_return_quantity,sr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (3) + Project [d_date_sk] + BroadcastHashJoin [d_date,d_date] + Filter [d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [d_date] + BroadcastHashJoin [d_week_seq,d_week_seq] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_week_seq] + Filter [d_date] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (1) + Filter [i_item_sk,i_item_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (11) + HashAggregate [i_item_id,sum] [sum(cr_return_quantity),item_id,cr_item_qty,sum] + InputAdapter + Exchange [i_item_id] #7 + WholeStageCodegen (10) + HashAggregate [i_item_id,cr_return_quantity] [sum,sum] + Project [cr_return_quantity,i_item_id] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + Project [cr_return_quantity,cr_returned_date_sk,i_item_id] + BroadcastHashJoin [cr_item_sk,i_item_sk] + Filter [cr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_return_quantity,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (17) + HashAggregate [i_item_id,sum] [sum(wr_return_quantity),item_id,wr_item_qty,sum] + InputAdapter + Exchange [i_item_id] #9 + WholeStageCodegen (16) + HashAggregate [i_item_id,wr_return_quantity] [sum,sum] + Project [wr_return_quantity,i_item_id] + BroadcastHashJoin [wr_returned_date_sk,d_date_sk] + Project [wr_return_quantity,wr_returned_date_sk,i_item_id] + BroadcastHashJoin [wr_item_sk,i_item_sk] + Filter [wr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_return_quantity,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/explain.txt new file mode 100644 index 000000000..c7e5238f1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/explain.txt @@ -0,0 +1,210 @@ +== Physical Plan == +TakeOrderedAndProject (37) ++- * Project (36) + +- * BroadcastHashJoin Inner BuildLeft (35) + :- BroadcastExchange (30) + : +- * Project (29) + : +- * BroadcastHashJoin Inner BuildRight (28) + : :- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * Project (16) + : : : +- * BroadcastHashJoin Inner BuildRight (15) + : : : :- * Project (10) + : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (8) + : : : : +- * Project (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.customer_address (4) + : : : +- BroadcastExchange (14) + : : : +- * Filter (13) + : : : +- * ColumnarToRow (12) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (11) + : : +- BroadcastExchange (20) + : : +- * Filter (19) + : : +- * ColumnarToRow (18) + : : +- CometScan parquet spark_catalog.default.household_demographics (17) + : +- BroadcastExchange (27) + : +- * Project (26) + : +- * Filter (25) + : +- * ColumnarToRow (24) + : +- CometScan parquet spark_catalog.default.income_band (23) + +- * Project (34) + +- * Filter (33) + +- * ColumnarToRow (32) + +- CometScan parquet spark_catalog.default.store_returns (31) + + +(1) Scan parquet spark_catalog.default.customer +Output [6]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_current_addr_sk#4, c_first_name#5, c_last_name#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [6]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_current_addr_sk#4, c_first_name#5, c_last_name#6] + +(3) Filter [codegen id : 5] +Input [6]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_current_addr_sk#4, c_first_name#5, c_last_name#6] +Condition : ((isnotnull(c_current_addr_sk#4) AND isnotnull(c_current_cdemo_sk#2)) AND isnotnull(c_current_hdemo_sk#3)) + +(4) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#7, ca_city#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_city), EqualTo(ca_city,Edgewood), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [ca_address_sk#7, ca_city#8] + +(6) Filter [codegen id : 1] +Input [2]: [ca_address_sk#7, ca_city#8] +Condition : ((isnotnull(ca_city#8) AND (ca_city#8 = Edgewood)) AND isnotnull(ca_address_sk#7)) + +(7) Project [codegen id : 1] +Output [1]: [ca_address_sk#7] +Input [2]: [ca_address_sk#7, ca_city#8] + +(8) BroadcastExchange +Input [1]: [ca_address_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [c_current_addr_sk#4] +Right keys [1]: [ca_address_sk#7] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 5] +Output [5]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_first_name#5, c_last_name#6] +Input [7]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_current_addr_sk#4, c_first_name#5, c_last_name#6, ca_address_sk#7] + +(11) Scan parquet spark_catalog.default.customer_demographics +Output [1]: [cd_demo_sk#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [1]: [cd_demo_sk#9] + +(13) Filter [codegen id : 2] +Input [1]: [cd_demo_sk#9] +Condition : isnotnull(cd_demo_sk#9) + +(14) BroadcastExchange +Input [1]: [cd_demo_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [c_current_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#9] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 5] +Output [5]: [c_customer_id#1, c_current_hdemo_sk#3, c_first_name#5, c_last_name#6, cd_demo_sk#9] +Input [6]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_first_name#5, c_last_name#6, cd_demo_sk#9] + +(17) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#10, hd_income_band_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_demo_sk), IsNotNull(hd_income_band_sk)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 3] +Input [2]: [hd_demo_sk#10, hd_income_band_sk#11] + +(19) Filter [codegen id : 3] +Input [2]: [hd_demo_sk#10, hd_income_band_sk#11] +Condition : (isnotnull(hd_demo_sk#10) AND isnotnull(hd_income_band_sk#11)) + +(20) BroadcastExchange +Input [2]: [hd_demo_sk#10, hd_income_band_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [c_current_hdemo_sk#3] +Right keys [1]: [hd_demo_sk#10] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 5] +Output [5]: [c_customer_id#1, c_first_name#5, c_last_name#6, cd_demo_sk#9, hd_income_band_sk#11] +Input [7]: [c_customer_id#1, c_current_hdemo_sk#3, c_first_name#5, c_last_name#6, cd_demo_sk#9, hd_demo_sk#10, hd_income_band_sk#11] + +(23) Scan parquet spark_catalog.default.income_band +Output [3]: [ib_income_band_sk#12, ib_lower_bound#13, ib_upper_bound#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/income_band] +PushedFilters: [IsNotNull(ib_lower_bound), IsNotNull(ib_upper_bound), GreaterThanOrEqual(ib_lower_bound,38128), LessThanOrEqual(ib_upper_bound,88128), IsNotNull(ib_income_band_sk)] +ReadSchema: struct + +(24) ColumnarToRow [codegen id : 4] +Input [3]: [ib_income_band_sk#12, ib_lower_bound#13, ib_upper_bound#14] + +(25) Filter [codegen id : 4] +Input [3]: [ib_income_band_sk#12, ib_lower_bound#13, ib_upper_bound#14] +Condition : ((((isnotnull(ib_lower_bound#13) AND isnotnull(ib_upper_bound#14)) AND (ib_lower_bound#13 >= 38128)) AND (ib_upper_bound#14 <= 88128)) AND isnotnull(ib_income_band_sk#12)) + +(26) Project [codegen id : 4] +Output [1]: [ib_income_band_sk#12] +Input [3]: [ib_income_band_sk#12, ib_lower_bound#13, ib_upper_bound#14] + +(27) BroadcastExchange +Input [1]: [ib_income_band_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [hd_income_band_sk#11] +Right keys [1]: [ib_income_band_sk#12] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 5] +Output [4]: [c_customer_id#1, c_first_name#5, c_last_name#6, cd_demo_sk#9] +Input [6]: [c_customer_id#1, c_first_name#5, c_last_name#6, cd_demo_sk#9, hd_income_band_sk#11, ib_income_band_sk#12] + +(30) BroadcastExchange +Input [4]: [c_customer_id#1, c_first_name#5, c_last_name#6, cd_demo_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[3, int, true] as bigint)),false), [plan_id=5] + +(31) Scan parquet spark_catalog.default.store_returns +Output [2]: [sr_cdemo_sk#15, sr_returned_date_sk#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_cdemo_sk)] +ReadSchema: struct + +(32) ColumnarToRow +Input [2]: [sr_cdemo_sk#15, sr_returned_date_sk#16] + +(33) Filter +Input [2]: [sr_cdemo_sk#15, sr_returned_date_sk#16] +Condition : isnotnull(sr_cdemo_sk#15) + +(34) Project +Output [1]: [sr_cdemo_sk#15] +Input [2]: [sr_cdemo_sk#15, sr_returned_date_sk#16] + +(35) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cd_demo_sk#9] +Right keys [1]: [sr_cdemo_sk#15] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 6] +Output [3]: [c_customer_id#1 AS customer_id#17, concat(c_last_name#6, , , c_first_name#5) AS customername#18, c_customer_id#1] +Input [5]: [c_customer_id#1, c_first_name#5, c_last_name#6, cd_demo_sk#9, sr_cdemo_sk#15] + +(37) TakeOrderedAndProject +Input [3]: [customer_id#17, customername#18, c_customer_id#1] +Arguments: 100, [c_customer_id#1 ASC NULLS FIRST], [customer_id#17, customername#18] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/simplified.txt new file mode 100644 index 000000000..157e471bb --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/simplified.txt @@ -0,0 +1,54 @@ +TakeOrderedAndProject [c_customer_id,customer_id,customername] + WholeStageCodegen (6) + Project [c_customer_id,c_last_name,c_first_name] + BroadcastHashJoin [cd_demo_sk,sr_cdemo_sk] + InputAdapter + BroadcastExchange #1 + WholeStageCodegen (5) + Project [c_customer_id,c_first_name,c_last_name,cd_demo_sk] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [c_customer_id,c_first_name,c_last_name,cd_demo_sk,hd_income_band_sk] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [c_customer_id,c_current_hdemo_sk,c_first_name,c_last_name,cd_demo_sk] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_customer_id,c_current_cdemo_sk,c_current_hdemo_sk,c_first_name,c_last_name] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Filter [c_current_addr_sk,c_current_cdemo_sk,c_current_hdemo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_id,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Project [ca_address_sk] + Filter [ca_city,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Filter [hd_demo_sk,hd_income_band_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_income_band_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Project [ib_income_band_sk] + Filter [ib_lower_bound,ib_upper_bound,ib_income_band_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.income_band [ib_income_band_sk,ib_lower_bound,ib_upper_bound] + Project [sr_cdemo_sk] + Filter [sr_cdemo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_cdemo_sk,sr_returned_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/explain.txt new file mode 100644 index 000000000..b6a58f11d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/explain.txt @@ -0,0 +1,310 @@ +== Physical Plan == +TakeOrderedAndProject (48) ++- * HashAggregate (47) + +- Exchange (46) + +- * HashAggregate (45) + +- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * Project (35) + : : +- * BroadcastHashJoin Inner BuildRight (34) + : : :- * Project (28) + : : : +- * BroadcastHashJoin Inner BuildRight (27) + : : : :- * Project (22) + : : : : +- * BroadcastHashJoin Inner BuildRight (21) + : : : : :- * Project (16) + : : : : : +- * BroadcastHashJoin Inner BuildRight (15) + : : : : : :- * Project (10) + : : : : : : +- * BroadcastHashJoin Inner BuildLeft (9) + : : : : : : :- BroadcastExchange (4) + : : : : : : : +- * Filter (3) + : : : : : : : +- * ColumnarToRow (2) + : : : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : : : +- * Project (8) + : : : : : : +- * Filter (7) + : : : : : : +- * ColumnarToRow (6) + : : : : : : +- CometScan parquet spark_catalog.default.web_returns (5) + : : : : : +- BroadcastExchange (14) + : : : : : +- * Filter (13) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometScan parquet spark_catalog.default.web_page (11) + : : : : +- BroadcastExchange (20) + : : : : +- * Filter (19) + : : : : +- * ColumnarToRow (18) + : : : : +- CometScan parquet spark_catalog.default.customer_demographics (17) + : : : +- BroadcastExchange (26) + : : : +- * Filter (25) + : : : +- * ColumnarToRow (24) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (23) + : : +- BroadcastExchange (33) + : : +- * Project (32) + : : +- * Filter (31) + : : +- * ColumnarToRow (30) + : : +- CometScan parquet spark_catalog.default.customer_address (29) + : +- ReusedExchange (36) + +- BroadcastExchange (42) + +- * Filter (41) + +- * ColumnarToRow (40) + +- CometScan parquet spark_catalog.default.reason (39) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#7), dynamicpruningexpression(ws_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_page_sk), Or(Or(And(GreaterThanOrEqual(ws_sales_price,100.00),LessThanOrEqual(ws_sales_price,150.00)),And(GreaterThanOrEqual(ws_sales_price,50.00),LessThanOrEqual(ws_sales_price,100.00))),And(GreaterThanOrEqual(ws_sales_price,150.00),LessThanOrEqual(ws_sales_price,200.00))), Or(Or(And(GreaterThanOrEqual(ws_net_profit,100.00),LessThanOrEqual(ws_net_profit,200.00)),And(GreaterThanOrEqual(ws_net_profit,150.00),LessThanOrEqual(ws_net_profit,300.00))),And(GreaterThanOrEqual(ws_net_profit,50.00),LessThanOrEqual(ws_net_profit,250.00)))] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] + +(3) Filter [codegen id : 1] +Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] +Condition : ((((isnotnull(ws_item_sk#1) AND isnotnull(ws_order_number#3)) AND isnotnull(ws_web_page_sk#2)) AND ((((ws_sales_price#5 >= 100.00) AND (ws_sales_price#5 <= 150.00)) OR ((ws_sales_price#5 >= 50.00) AND (ws_sales_price#5 <= 100.00))) OR ((ws_sales_price#5 >= 150.00) AND (ws_sales_price#5 <= 200.00)))) AND ((((ws_net_profit#6 >= 100.00) AND (ws_net_profit#6 <= 200.00)) OR ((ws_net_profit#6 >= 150.00) AND (ws_net_profit#6 <= 300.00))) OR ((ws_net_profit#6 >= 50.00) AND (ws_net_profit#6 <= 250.00)))) + +(4) BroadcastExchange +Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[2, int, false] as bigint) & 4294967295))),false), [plan_id=1] + +(5) Scan parquet spark_catalog.default.web_returns +Output [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_item_sk), IsNotNull(wr_order_number), IsNotNull(wr_refunded_cdemo_sk), IsNotNull(wr_returning_cdemo_sk), IsNotNull(wr_refunded_addr_sk), IsNotNull(wr_reason_sk)] +ReadSchema: struct + +(6) ColumnarToRow +Input [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] + +(7) Filter +Input [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] +Condition : (((((isnotnull(wr_item_sk#9) AND isnotnull(wr_order_number#14)) AND isnotnull(wr_refunded_cdemo_sk#10)) AND isnotnull(wr_returning_cdemo_sk#12)) AND isnotnull(wr_refunded_addr_sk#11)) AND isnotnull(wr_reason_sk#13)) + +(8) Project +Output [8]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16] +Input [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] + +(9) BroadcastHashJoin [codegen id : 8] +Left keys [2]: [ws_item_sk#1, ws_order_number#3] +Right keys [2]: [wr_item_sk#9, wr_order_number#14] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 8] +Output [11]: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] +Input [15]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16] + +(11) Scan parquet spark_catalog.default.web_page +Output [1]: [wp_web_page_sk#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_page] +PushedFilters: [IsNotNull(wp_web_page_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [1]: [wp_web_page_sk#18] + +(13) Filter [codegen id : 2] +Input [1]: [wp_web_page_sk#18] +Condition : isnotnull(wp_web_page_sk#18) + +(14) BroadcastExchange +Input [1]: [wp_web_page_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(15) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ws_web_page_sk#2] +Right keys [1]: [wp_web_page_sk#18] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 8] +Output [10]: [ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] +Input [12]: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, wp_web_page_sk#18] + +(17) Scan parquet spark_catalog.default.customer_demographics +Output [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,Advanced Degree )),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College ))),And(EqualTo(cd_marital_status,W),EqualTo(cd_education_status,2 yr Degree )))] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 3] +Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] + +(19) Filter [codegen id : 3] +Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] +Condition : (((isnotnull(cd_demo_sk#19) AND isnotnull(cd_marital_status#20)) AND isnotnull(cd_education_status#21)) AND ((((cd_marital_status#20 = M) AND (cd_education_status#21 = Advanced Degree )) OR ((cd_marital_status#20 = S) AND (cd_education_status#21 = College ))) OR ((cd_marital_status#20 = W) AND (cd_education_status#21 = 2 yr Degree )))) + +(20) BroadcastExchange +Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [wr_refunded_cdemo_sk#10] +Right keys [1]: [cd_demo_sk#19] +Join type: Inner +Join condition: ((((((cd_marital_status#20 = M) AND (cd_education_status#21 = Advanced Degree )) AND (ws_sales_price#5 >= 100.00)) AND (ws_sales_price#5 <= 150.00)) OR ((((cd_marital_status#20 = S) AND (cd_education_status#21 = College )) AND (ws_sales_price#5 >= 50.00)) AND (ws_sales_price#5 <= 100.00))) OR ((((cd_marital_status#20 = W) AND (cd_education_status#21 = 2 yr Degree )) AND (ws_sales_price#5 >= 150.00)) AND (ws_sales_price#5 <= 200.00))) + +(22) Project [codegen id : 8] +Output [10]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_marital_status#20, cd_education_status#21] +Input [13]: [ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] + +(23) Scan parquet spark_catalog.default.customer_demographics +Output [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status), IsNotNull(cd_education_status)] +ReadSchema: struct + +(24) ColumnarToRow [codegen id : 4] +Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] + +(25) Filter [codegen id : 4] +Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] +Condition : ((isnotnull(cd_demo_sk#22) AND isnotnull(cd_marital_status#23)) AND isnotnull(cd_education_status#24)) + +(26) BroadcastExchange +Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] +Arguments: HashedRelationBroadcastMode(List(input[0, int, false], input[1, string, false], input[2, string, false]),false), [plan_id=4] + +(27) BroadcastHashJoin [codegen id : 8] +Left keys [3]: [wr_returning_cdemo_sk#12, cd_marital_status#20, cd_education_status#21] +Right keys [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 8] +Output [7]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] +Input [13]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_marital_status#20, cd_education_status#21, cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] + +(29) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#25, ca_state#26, ca_country#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [IN,NJ,OH]),In(ca_state, [CT,KY,WI])),In(ca_state, [AR,IA,LA]))] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 5] +Input [3]: [ca_address_sk#25, ca_state#26, ca_country#27] + +(31) Filter [codegen id : 5] +Input [3]: [ca_address_sk#25, ca_state#26, ca_country#27] +Condition : (((isnotnull(ca_country#27) AND (ca_country#27 = United States)) AND isnotnull(ca_address_sk#25)) AND ((ca_state#26 IN (IN,OH,NJ) OR ca_state#26 IN (WI,CT,KY)) OR ca_state#26 IN (LA,IA,AR))) + +(32) Project [codegen id : 5] +Output [2]: [ca_address_sk#25, ca_state#26] +Input [3]: [ca_address_sk#25, ca_state#26, ca_country#27] + +(33) BroadcastExchange +Input [2]: [ca_address_sk#25, ca_state#26] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [wr_refunded_addr_sk#11] +Right keys [1]: [ca_address_sk#25] +Join type: Inner +Join condition: ((((ca_state#26 IN (IN,OH,NJ) AND (ws_net_profit#6 >= 100.00)) AND (ws_net_profit#6 <= 200.00)) OR ((ca_state#26 IN (WI,CT,KY) AND (ws_net_profit#6 >= 150.00)) AND (ws_net_profit#6 <= 300.00))) OR ((ca_state#26 IN (LA,IA,AR) AND (ws_net_profit#6 >= 50.00)) AND (ws_net_profit#6 <= 250.00))) + +(35) Project [codegen id : 8] +Output [5]: [ws_quantity#4, ws_sold_date_sk#7, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] +Input [9]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, ca_address_sk#25, ca_state#26] + +(36) ReusedExchange [Reuses operator id: 53] +Output [1]: [d_date_sk#28] + +(37) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ws_sold_date_sk#7] +Right keys [1]: [d_date_sk#28] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 8] +Output [4]: [ws_quantity#4, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] +Input [6]: [ws_quantity#4, ws_sold_date_sk#7, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, d_date_sk#28] + +(39) Scan parquet spark_catalog.default.reason +Output [2]: [r_reason_sk#29, r_reason_desc#30] +Batched: true +Location [not included in comparison]/{warehouse_dir}/reason] +PushedFilters: [IsNotNull(r_reason_sk)] +ReadSchema: struct + +(40) ColumnarToRow [codegen id : 7] +Input [2]: [r_reason_sk#29, r_reason_desc#30] + +(41) Filter [codegen id : 7] +Input [2]: [r_reason_sk#29, r_reason_desc#30] +Condition : isnotnull(r_reason_sk#29) + +(42) BroadcastExchange +Input [2]: [r_reason_sk#29, r_reason_desc#30] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [wr_reason_sk#13] +Right keys [1]: [r_reason_sk#29] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 8] +Output [4]: [ws_quantity#4, wr_fee#15, wr_refunded_cash#16, r_reason_desc#30] +Input [6]: [ws_quantity#4, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, r_reason_sk#29, r_reason_desc#30] + +(45) HashAggregate [codegen id : 8] +Input [4]: [ws_quantity#4, wr_fee#15, wr_refunded_cash#16, r_reason_desc#30] +Keys [1]: [r_reason_desc#30] +Functions [3]: [partial_avg(ws_quantity#4), partial_avg(UnscaledValue(wr_refunded_cash#16)), partial_avg(UnscaledValue(wr_fee#15))] +Aggregate Attributes [6]: [sum#31, count#32, sum#33, count#34, sum#35, count#36] +Results [7]: [r_reason_desc#30, sum#37, count#38, sum#39, count#40, sum#41, count#42] + +(46) Exchange +Input [7]: [r_reason_desc#30, sum#37, count#38, sum#39, count#40, sum#41, count#42] +Arguments: hashpartitioning(r_reason_desc#30, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate [codegen id : 9] +Input [7]: [r_reason_desc#30, sum#37, count#38, sum#39, count#40, sum#41, count#42] +Keys [1]: [r_reason_desc#30] +Functions [3]: [avg(ws_quantity#4), avg(UnscaledValue(wr_refunded_cash#16)), avg(UnscaledValue(wr_fee#15))] +Aggregate Attributes [3]: [avg(ws_quantity#4)#43, avg(UnscaledValue(wr_refunded_cash#16))#44, avg(UnscaledValue(wr_fee#15))#45] +Results [4]: [substr(r_reason_desc#30, 1, 20) AS substr(r_reason_desc, 1, 20)#46, avg(ws_quantity#4)#43 AS avg(ws_quantity)#47, cast((avg(UnscaledValue(wr_refunded_cash#16))#44 / 100.0) as decimal(11,6)) AS avg(wr_refunded_cash)#48, cast((avg(UnscaledValue(wr_fee#15))#45 / 100.0) as decimal(11,6)) AS avg(wr_fee)#49] + +(48) TakeOrderedAndProject +Input [4]: [substr(r_reason_desc, 1, 20)#46, avg(ws_quantity)#47, avg(wr_refunded_cash)#48, avg(wr_fee)#49] +Arguments: 100, [substr(r_reason_desc, 1, 20)#46 ASC NULLS FIRST, avg(ws_quantity)#47 ASC NULLS FIRST, avg(wr_refunded_cash)#48 ASC NULLS FIRST, avg(wr_fee)#49 ASC NULLS FIRST], [substr(r_reason_desc, 1, 20)#46, avg(ws_quantity)#47, avg(wr_refunded_cash)#48, avg(wr_fee)#49] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (53) ++- * Project (52) + +- * Filter (51) + +- * ColumnarToRow (50) + +- CometScan parquet spark_catalog.default.date_dim (49) + + +(49) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#28, d_year#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(50) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#28, d_year#50] + +(51) Filter [codegen id : 1] +Input [2]: [d_date_sk#28, d_year#50] +Condition : ((isnotnull(d_year#50) AND (d_year#50 = 2000)) AND isnotnull(d_date_sk#28)) + +(52) Project [codegen id : 1] +Output [1]: [d_date_sk#28] +Input [2]: [d_date_sk#28, d_year#50] + +(53) BroadcastExchange +Input [1]: [d_date_sk#28] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/simplified.txt new file mode 100644 index 000000000..99ca4aeaf --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/simplified.txt @@ -0,0 +1,79 @@ +TakeOrderedAndProject [substr(r_reason_desc, 1, 20),avg(ws_quantity),avg(wr_refunded_cash),avg(wr_fee)] + WholeStageCodegen (9) + HashAggregate [r_reason_desc,sum,count,sum,count,sum,count] [avg(ws_quantity),avg(UnscaledValue(wr_refunded_cash)),avg(UnscaledValue(wr_fee)),substr(r_reason_desc, 1, 20),avg(ws_quantity),avg(wr_refunded_cash),avg(wr_fee),sum,count,sum,count,sum,count] + InputAdapter + Exchange [r_reason_desc] #1 + WholeStageCodegen (8) + HashAggregate [r_reason_desc,ws_quantity,wr_refunded_cash,wr_fee] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [ws_quantity,wr_fee,wr_refunded_cash,r_reason_desc] + BroadcastHashJoin [wr_reason_sk,r_reason_sk] + Project [ws_quantity,wr_reason_sk,wr_fee,wr_refunded_cash] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_quantity,ws_sold_date_sk,wr_reason_sk,wr_fee,wr_refunded_cash] + BroadcastHashJoin [wr_refunded_addr_sk,ca_address_sk,ca_state,ws_net_profit] + Project [ws_quantity,ws_net_profit,ws_sold_date_sk,wr_refunded_addr_sk,wr_reason_sk,wr_fee,wr_refunded_cash] + BroadcastHashJoin [wr_returning_cdemo_sk,cd_marital_status,cd_education_status,cd_demo_sk,cd_marital_status,cd_education_status] + Project [ws_quantity,ws_net_profit,ws_sold_date_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_fee,wr_refunded_cash,cd_marital_status,cd_education_status] + BroadcastHashJoin [wr_refunded_cdemo_sk,cd_demo_sk,cd_marital_status,cd_education_status,ws_sales_price] + Project [ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_fee,wr_refunded_cash] + BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] + Project [ws_web_page_sk,ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_fee,wr_refunded_cash] + BroadcastHashJoin [ws_item_sk,ws_order_number,wr_item_sk,wr_order_number] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ws_item_sk,ws_order_number,ws_web_page_sk,ws_sales_price,ws_net_profit] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_page_sk,ws_order_number,ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + Project [wr_item_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_order_number,wr_fee,wr_refunded_cash] + Filter [wr_item_sk,wr_order_number,wr_refunded_cdemo_sk,wr_returning_cdemo_sk,wr_refunded_addr_sk,wr_reason_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_order_number,wr_fee,wr_refunded_cash,wr_returned_date_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [wp_web_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_page [wp_web_page_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [cd_demo_sk,cd_marital_status,cd_education_status] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + Filter [cd_demo_sk,cd_marital_status,cd_education_status] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (5) + Project [ca_address_sk,ca_state] + Filter [ca_country,ca_address_sk,ca_state] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (7) + Filter [r_reason_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.reason [r_reason_sk,r_reason_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/explain.txt new file mode 100644 index 000000000..07e05a0ae --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/explain.txt @@ -0,0 +1,155 @@ +== Physical Plan == +TakeOrderedAndProject (21) ++- * Project (20) + +- Window (19) + +- * Sort (18) + +- Exchange (17) + +- * HashAggregate (16) + +- Exchange (15) + +- * HashAggregate (14) + +- * Expand (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (6) + : +- * BroadcastHashJoin Inner BuildRight (5) + : :- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.web_sales (1) + : +- ReusedExchange (4) + +- BroadcastExchange (10) + +- * Filter (9) + +- * ColumnarToRow (8) + +- CometScan parquet spark_catalog.default.item (7) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] + +(3) Filter [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(4) ReusedExchange [Reuses operator id: 26] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [2]: [ws_item_sk#1, ws_net_paid#2] +Input [4]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#6, i_class#7, i_category#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#6, i_class#7, i_category#8] + +(9) Filter [codegen id : 2] +Input [3]: [i_item_sk#6, i_class#7, i_category#8] +Condition : isnotnull(i_item_sk#6) + +(10) BroadcastExchange +Input [3]: [i_item_sk#6, i_class#7, i_category#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_item_sk#1] +Right keys [1]: [i_item_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [ws_net_paid#2, i_category#8, i_class#7] +Input [5]: [ws_item_sk#1, ws_net_paid#2, i_item_sk#6, i_class#7, i_category#8] + +(13) Expand [codegen id : 3] +Input [3]: [ws_net_paid#2, i_category#8, i_class#7] +Arguments: [[ws_net_paid#2, i_category#8, i_class#7, 0], [ws_net_paid#2, i_category#8, null, 1], [ws_net_paid#2, null, null, 3]], [ws_net_paid#2, i_category#9, i_class#10, spark_grouping_id#11] + +(14) HashAggregate [codegen id : 3] +Input [4]: [ws_net_paid#2, i_category#9, i_class#10, spark_grouping_id#11] +Keys [3]: [i_category#9, i_class#10, spark_grouping_id#11] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#2))] +Aggregate Attributes [1]: [sum#12] +Results [4]: [i_category#9, i_class#10, spark_grouping_id#11, sum#13] + +(15) Exchange +Input [4]: [i_category#9, i_class#10, spark_grouping_id#11, sum#13] +Arguments: hashpartitioning(i_category#9, i_class#10, spark_grouping_id#11, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(16) HashAggregate [codegen id : 4] +Input [4]: [i_category#9, i_class#10, spark_grouping_id#11, sum#13] +Keys [3]: [i_category#9, i_class#10, spark_grouping_id#11] +Functions [1]: [sum(UnscaledValue(ws_net_paid#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#2))#14] +Results [7]: [MakeDecimal(sum(UnscaledValue(ws_net_paid#2))#14,17,2) AS total_sum#15, i_category#9, i_class#10, (cast((shiftright(spark_grouping_id#11, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#11, 0) & 1) as tinyint)) AS lochierarchy#16, MakeDecimal(sum(UnscaledValue(ws_net_paid#2))#14,17,2) AS _w0#17, (cast((shiftright(spark_grouping_id#11, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#11, 0) & 1) as tinyint)) AS _w1#18, CASE WHEN (cast((shiftright(spark_grouping_id#11, 0) & 1) as tinyint) = 0) THEN i_category#9 END AS _w2#19] + +(17) Exchange +Input [7]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, _w0#17, _w1#18, _w2#19] +Arguments: hashpartitioning(_w1#18, _w2#19, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(18) Sort [codegen id : 5] +Input [7]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, _w0#17, _w1#18, _w2#19] +Arguments: [_w1#18 ASC NULLS FIRST, _w2#19 ASC NULLS FIRST, _w0#17 DESC NULLS LAST], false, 0 + +(19) Window +Input [7]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, _w0#17, _w1#18, _w2#19] +Arguments: [rank(_w0#17) windowspecdefinition(_w1#18, _w2#19, _w0#17 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#20], [_w1#18, _w2#19], [_w0#17 DESC NULLS LAST] + +(20) Project [codegen id : 6] +Output [5]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, rank_within_parent#20] +Input [8]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, _w0#17, _w1#18, _w2#19, rank_within_parent#20] + +(21) TakeOrderedAndProject +Input [5]: [total_sum#15, i_category#9, i_class#10, lochierarchy#16, rank_within_parent#20] +Arguments: 100, [lochierarchy#16 DESC NULLS LAST, CASE WHEN (lochierarchy#16 = 0) THEN i_category#9 END ASC NULLS FIRST, rank_within_parent#20 ASC NULLS FIRST], [total_sum#15, i_category#9, i_class#10, lochierarchy#16, rank_within_parent#20] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (26) ++- * Project (25) + +- * Filter (24) + +- * ColumnarToRow (23) + +- CometScan parquet spark_catalog.default.date_dim (22) + + +(22) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#21] + +(24) Filter [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#21] +Condition : (((isnotnull(d_month_seq#21) AND (d_month_seq#21 >= 1200)) AND (d_month_seq#21 <= 1211)) AND isnotnull(d_date_sk#5)) + +(25) Project [codegen id : 1] +Output [1]: [d_date_sk#5] +Input [2]: [d_date_sk#5, d_month_seq#21] + +(26) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/simplified.txt new file mode 100644 index 000000000..a33617e7f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/simplified.txt @@ -0,0 +1,41 @@ +TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,total_sum,i_class] + WholeStageCodegen (6) + Project [total_sum,i_category,i_class,lochierarchy,rank_within_parent] + InputAdapter + Window [_w0,_w1,_w2] + WholeStageCodegen (5) + Sort [_w1,_w2,_w0] + InputAdapter + Exchange [_w1,_w2] #1 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,spark_grouping_id,sum] [sum(UnscaledValue(ws_net_paid)),total_sum,lochierarchy,_w0,_w1,_w2,sum] + InputAdapter + Exchange [i_category,i_class,spark_grouping_id] #2 + WholeStageCodegen (3) + HashAggregate [i_category,i_class,spark_grouping_id,ws_net_paid] [sum,sum] + Expand [ws_net_paid,i_category,i_class] + Project [ws_net_paid,i_category,i_class] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_net_paid] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_net_paid,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/explain.txt new file mode 100644 index 000000000..bce0869c5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/explain.txt @@ -0,0 +1,321 @@ +== Physical Plan == +* HashAggregate (47) ++- Exchange (46) + +- * HashAggregate (45) + +- * Project (44) + +- * BroadcastHashJoin LeftAnti BuildRight (43) + :- * BroadcastHashJoin LeftAnti BuildRight (29) + : :- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.customer (7) + : +- BroadcastExchange (28) + : +- * HashAggregate (27) + : +- Exchange (26) + : +- * HashAggregate (25) + : +- * Project (24) + : +- * BroadcastHashJoin Inner BuildRight (23) + : :- * Project (21) + : : +- * BroadcastHashJoin Inner BuildRight (20) + : : :- * Filter (18) + : : : +- * ColumnarToRow (17) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) + : : +- ReusedExchange (19) + : +- ReusedExchange (22) + +- BroadcastExchange (42) + +- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (35) + : +- * BroadcastHashJoin Inner BuildRight (34) + : :- * Filter (32) + : : +- * ColumnarToRow (31) + : : +- CometScan parquet spark_catalog.default.web_sales (30) + : +- ReusedExchange (33) + +- ReusedExchange (36) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#1, ss_sold_date_sk#2] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#2), dynamicpruningexpression(ss_sold_date_sk#2 IN dynamicpruning#3)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] + +(3) Filter [codegen id : 3] +Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] +Condition : isnotnull(ss_customer_sk#1) + +(4) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#4, d_date#5] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#2] +Right keys [1]: [d_date_sk#4] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [2]: [ss_customer_sk#1, d_date#5] +Input [4]: [ss_customer_sk#1, ss_sold_date_sk#2, d_date_sk#4, d_date#5] + +(7) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] + +(9) Filter [codegen id : 2] +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Condition : isnotnull(c_customer_sk#6) + +(10) BroadcastExchange +Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [c_last_name#8, c_first_name#7, d_date#5] +Input [5]: [ss_customer_sk#1, d_date#5, c_customer_sk#6, c_first_name#7, c_last_name#8] + +(13) HashAggregate [codegen id : 3] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Keys [3]: [c_last_name#8, c_first_name#7, d_date#5] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(14) Exchange +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Arguments: hashpartitioning(c_last_name#8, c_first_name#7, d_date#5, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 12] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] +Keys [3]: [c_last_name#8, c_first_name#7, d_date#5] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(16) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#10), dynamicpruningexpression(cs_sold_date_sk#10 IN dynamicpruning#11)] +PushedFilters: [IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 6] +Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] + +(18) Filter [codegen id : 6] +Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] +Condition : isnotnull(cs_bill_customer_sk#9) + +(19) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#12, d_date#13] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#10] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [2]: [cs_bill_customer_sk#9, d_date#13] +Input [4]: [cs_bill_customer_sk#9, cs_sold_date_sk#10, d_date_sk#12, d_date#13] + +(22) ReusedExchange [Reuses operator id: 10] +Output [3]: [c_customer_sk#14, c_first_name#15, c_last_name#16] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_bill_customer_sk#9] +Right keys [1]: [c_customer_sk#14] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [3]: [c_last_name#16, c_first_name#15, d_date#13] +Input [5]: [cs_bill_customer_sk#9, d_date#13, c_customer_sk#14, c_first_name#15, c_last_name#16] + +(25) HashAggregate [codegen id : 6] +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Keys [3]: [c_last_name#16, c_first_name#15, d_date#13] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#16, c_first_name#15, d_date#13] + +(26) Exchange +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Arguments: hashpartitioning(c_last_name#16, c_first_name#15, d_date#13, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 7] +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Keys [3]: [c_last_name#16, c_first_name#15, d_date#13] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#16, c_first_name#15, d_date#13] + +(28) BroadcastExchange +Input [3]: [c_last_name#16, c_first_name#15, d_date#13] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, string, true], ), isnull(input[0, string, true]), coalesce(input[1, string, true], ), isnull(input[1, string, true]), coalesce(input[2, date, true], 1970-01-01), isnull(input[2, date, true])),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 12] +Left keys [6]: [coalesce(c_last_name#8, ), isnull(c_last_name#8), coalesce(c_first_name#7, ), isnull(c_first_name#7), coalesce(d_date#5, 1970-01-01), isnull(d_date#5)] +Right keys [6]: [coalesce(c_last_name#16, ), isnull(c_last_name#16), coalesce(c_first_name#15, ), isnull(c_first_name#15), coalesce(d_date#13, 1970-01-01), isnull(d_date#13)] +Join type: LeftAnti +Join condition: None + +(30) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#18), dynamicpruningexpression(ws_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 10] +Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] + +(32) Filter [codegen id : 10] +Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] +Condition : isnotnull(ws_bill_customer_sk#17) + +(33) ReusedExchange [Reuses operator id: 52] +Output [2]: [d_date_sk#20, d_date#21] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#18] +Right keys [1]: [d_date_sk#20] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [2]: [ws_bill_customer_sk#17, d_date#21] +Input [4]: [ws_bill_customer_sk#17, ws_sold_date_sk#18, d_date_sk#20, d_date#21] + +(36) ReusedExchange [Reuses operator id: 10] +Output [3]: [c_customer_sk#22, c_first_name#23, c_last_name#24] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_bill_customer_sk#17] +Right keys [1]: [c_customer_sk#22] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [3]: [c_last_name#24, c_first_name#23, d_date#21] +Input [5]: [ws_bill_customer_sk#17, d_date#21, c_customer_sk#22, c_first_name#23, c_last_name#24] + +(39) HashAggregate [codegen id : 10] +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Keys [3]: [c_last_name#24, c_first_name#23, d_date#21] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#24, c_first_name#23, d_date#21] + +(40) Exchange +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Arguments: hashpartitioning(c_last_name#24, c_first_name#23, d_date#21, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(41) HashAggregate [codegen id : 11] +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Keys [3]: [c_last_name#24, c_first_name#23, d_date#21] +Functions: [] +Aggregate Attributes: [] +Results [3]: [c_last_name#24, c_first_name#23, d_date#21] + +(42) BroadcastExchange +Input [3]: [c_last_name#24, c_first_name#23, d_date#21] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, string, true], ), isnull(input[0, string, true]), coalesce(input[1, string, true], ), isnull(input[1, string, true]), coalesce(input[2, date, true], 1970-01-01), isnull(input[2, date, true])),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 12] +Left keys [6]: [coalesce(c_last_name#8, ), isnull(c_last_name#8), coalesce(c_first_name#7, ), isnull(c_first_name#7), coalesce(d_date#5, 1970-01-01), isnull(d_date#5)] +Right keys [6]: [coalesce(c_last_name#24, ), isnull(c_last_name#24), coalesce(c_first_name#23, ), isnull(c_first_name#23), coalesce(d_date#21, 1970-01-01), isnull(d_date#21)] +Join type: LeftAnti +Join condition: None + +(44) Project [codegen id : 12] +Output: [] +Input [3]: [c_last_name#8, c_first_name#7, d_date#5] + +(45) HashAggregate [codegen id : 12] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#25] +Results [1]: [count#26] + +(46) Exchange +Input [1]: [count#26] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate [codegen id : 13] +Input [1]: [count#26] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#27] +Results [1]: [count(1)#27 AS count(1)#28] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#2 IN dynamicpruning#3 +BroadcastExchange (52) ++- * Project (51) + +- * Filter (50) + +- * ColumnarToRow (49) + +- CometScan parquet spark_catalog.default.date_dim (48) + + +(48) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(49) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] + +(50) Filter [codegen id : 1] +Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Condition : (((isnotnull(d_month_seq#29) AND (d_month_seq#29 >= 1200)) AND (d_month_seq#29 <= 1211)) AND isnotnull(d_date_sk#4)) + +(51) Project [codegen id : 1] +Output [2]: [d_date_sk#4, d_date#5] +Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] + +(52) BroadcastExchange +Input [2]: [d_date_sk#4, d_date#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +Subquery:2 Hosting operator id = 16 Hosting Expression = cs_sold_date_sk#10 IN dynamicpruning#3 + +Subquery:3 Hosting operator id = 30 Hosting Expression = ws_sold_date_sk#18 IN dynamicpruning#3 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/simplified.txt new file mode 100644 index 000000000..27489c0a9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/simplified.txt @@ -0,0 +1,81 @@ +WholeStageCodegen (13) + HashAggregate [count] [count(1),count(1),count] + InputAdapter + Exchange #1 + WholeStageCodegen (12) + HashAggregate [count,count] + Project + BroadcastHashJoin [c_last_name,c_first_name,d_date,c_last_name,c_first_name,d_date] + BroadcastHashJoin [c_last_name,c_first_name,d_date,c_last_name,c_first_name,d_date] + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #2 + WholeStageCodegen (3) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk,d_date] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #6 + WholeStageCodegen (6) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,d_date] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Filter [cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name] #4 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (11) + HashAggregate [c_last_name,c_first_name,d_date] + InputAdapter + Exchange [c_last_name,c_first_name,d_date] #8 + WholeStageCodegen (10) + HashAggregate [c_last_name,c_first_name,d_date] + Project [c_last_name,c_first_name,d_date] + BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] + Project [ws_bill_customer_sk,d_date] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_first_name,c_last_name] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/explain.txt new file mode 100644 index 000000000..ecd6c5498 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/explain.txt @@ -0,0 +1,1031 @@ +== Physical Plan == +* BroadcastNestedLoopJoin Inner BuildRight (182) +:- * BroadcastNestedLoopJoin Inner BuildRight (160) +: :- * BroadcastNestedLoopJoin Inner BuildRight (138) +: : :- * BroadcastNestedLoopJoin Inner BuildRight (116) +: : : :- * BroadcastNestedLoopJoin Inner BuildRight (94) +: : : : :- * BroadcastNestedLoopJoin Inner BuildRight (72) +: : : : : :- * BroadcastNestedLoopJoin Inner BuildRight (50) +: : : : : : :- * HashAggregate (28) +: : : : : : : +- Exchange (27) +: : : : : : : +- * HashAggregate (26) +: : : : : : : +- * Project (25) +: : : : : : : +- * BroadcastHashJoin Inner BuildRight (24) +: : : : : : : :- * Project (18) +: : : : : : : : +- * BroadcastHashJoin Inner BuildRight (17) +: : : : : : : : :- * Project (11) +: : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (10) +: : : : : : : : : :- * Project (4) +: : : : : : : : : : +- * Filter (3) +: : : : : : : : : : +- * ColumnarToRow (2) +: : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) +: : : : : : : : : +- BroadcastExchange (9) +: : : : : : : : : +- * Project (8) +: : : : : : : : : +- * Filter (7) +: : : : : : : : : +- * ColumnarToRow (6) +: : : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (5) +: : : : : : : : +- BroadcastExchange (16) +: : : : : : : : +- * Project (15) +: : : : : : : : +- * Filter (14) +: : : : : : : : +- * ColumnarToRow (13) +: : : : : : : : +- CometScan parquet spark_catalog.default.time_dim (12) +: : : : : : : +- BroadcastExchange (23) +: : : : : : : +- * Project (22) +: : : : : : : +- * Filter (21) +: : : : : : : +- * ColumnarToRow (20) +: : : : : : : +- CometScan parquet spark_catalog.default.store (19) +: : : : : : +- BroadcastExchange (49) +: : : : : : +- * HashAggregate (48) +: : : : : : +- Exchange (47) +: : : : : : +- * HashAggregate (46) +: : : : : : +- * Project (45) +: : : : : : +- * BroadcastHashJoin Inner BuildRight (44) +: : : : : : :- * Project (42) +: : : : : : : +- * BroadcastHashJoin Inner BuildRight (41) +: : : : : : : :- * Project (35) +: : : : : : : : +- * BroadcastHashJoin Inner BuildRight (34) +: : : : : : : : :- * Project (32) +: : : : : : : : : +- * Filter (31) +: : : : : : : : : +- * ColumnarToRow (30) +: : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (29) +: : : : : : : : +- ReusedExchange (33) +: : : : : : : +- BroadcastExchange (40) +: : : : : : : +- * Project (39) +: : : : : : : +- * Filter (38) +: : : : : : : +- * ColumnarToRow (37) +: : : : : : : +- CometScan parquet spark_catalog.default.time_dim (36) +: : : : : : +- ReusedExchange (43) +: : : : : +- BroadcastExchange (71) +: : : : : +- * HashAggregate (70) +: : : : : +- Exchange (69) +: : : : : +- * HashAggregate (68) +: : : : : +- * Project (67) +: : : : : +- * BroadcastHashJoin Inner BuildRight (66) +: : : : : :- * Project (64) +: : : : : : +- * BroadcastHashJoin Inner BuildRight (63) +: : : : : : :- * Project (57) +: : : : : : : +- * BroadcastHashJoin Inner BuildRight (56) +: : : : : : : :- * Project (54) +: : : : : : : : +- * Filter (53) +: : : : : : : : +- * ColumnarToRow (52) +: : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (51) +: : : : : : : +- ReusedExchange (55) +: : : : : : +- BroadcastExchange (62) +: : : : : : +- * Project (61) +: : : : : : +- * Filter (60) +: : : : : : +- * ColumnarToRow (59) +: : : : : : +- CometScan parquet spark_catalog.default.time_dim (58) +: : : : : +- ReusedExchange (65) +: : : : +- BroadcastExchange (93) +: : : : +- * HashAggregate (92) +: : : : +- Exchange (91) +: : : : +- * HashAggregate (90) +: : : : +- * Project (89) +: : : : +- * BroadcastHashJoin Inner BuildRight (88) +: : : : :- * Project (86) +: : : : : +- * BroadcastHashJoin Inner BuildRight (85) +: : : : : :- * Project (79) +: : : : : : +- * BroadcastHashJoin Inner BuildRight (78) +: : : : : : :- * Project (76) +: : : : : : : +- * Filter (75) +: : : : : : : +- * ColumnarToRow (74) +: : : : : : : +- CometScan parquet spark_catalog.default.store_sales (73) +: : : : : : +- ReusedExchange (77) +: : : : : +- BroadcastExchange (84) +: : : : : +- * Project (83) +: : : : : +- * Filter (82) +: : : : : +- * ColumnarToRow (81) +: : : : : +- CometScan parquet spark_catalog.default.time_dim (80) +: : : : +- ReusedExchange (87) +: : : +- BroadcastExchange (115) +: : : +- * HashAggregate (114) +: : : +- Exchange (113) +: : : +- * HashAggregate (112) +: : : +- * Project (111) +: : : +- * BroadcastHashJoin Inner BuildRight (110) +: : : :- * Project (108) +: : : : +- * BroadcastHashJoin Inner BuildRight (107) +: : : : :- * Project (101) +: : : : : +- * BroadcastHashJoin Inner BuildRight (100) +: : : : : :- * Project (98) +: : : : : : +- * Filter (97) +: : : : : : +- * ColumnarToRow (96) +: : : : : : +- CometScan parquet spark_catalog.default.store_sales (95) +: : : : : +- ReusedExchange (99) +: : : : +- BroadcastExchange (106) +: : : : +- * Project (105) +: : : : +- * Filter (104) +: : : : +- * ColumnarToRow (103) +: : : : +- CometScan parquet spark_catalog.default.time_dim (102) +: : : +- ReusedExchange (109) +: : +- BroadcastExchange (137) +: : +- * HashAggregate (136) +: : +- Exchange (135) +: : +- * HashAggregate (134) +: : +- * Project (133) +: : +- * BroadcastHashJoin Inner BuildRight (132) +: : :- * Project (130) +: : : +- * BroadcastHashJoin Inner BuildRight (129) +: : : :- * Project (123) +: : : : +- * BroadcastHashJoin Inner BuildRight (122) +: : : : :- * Project (120) +: : : : : +- * Filter (119) +: : : : : +- * ColumnarToRow (118) +: : : : : +- CometScan parquet spark_catalog.default.store_sales (117) +: : : : +- ReusedExchange (121) +: : : +- BroadcastExchange (128) +: : : +- * Project (127) +: : : +- * Filter (126) +: : : +- * ColumnarToRow (125) +: : : +- CometScan parquet spark_catalog.default.time_dim (124) +: : +- ReusedExchange (131) +: +- BroadcastExchange (159) +: +- * HashAggregate (158) +: +- Exchange (157) +: +- * HashAggregate (156) +: +- * Project (155) +: +- * BroadcastHashJoin Inner BuildRight (154) +: :- * Project (152) +: : +- * BroadcastHashJoin Inner BuildRight (151) +: : :- * Project (145) +: : : +- * BroadcastHashJoin Inner BuildRight (144) +: : : :- * Project (142) +: : : : +- * Filter (141) +: : : : +- * ColumnarToRow (140) +: : : : +- CometScan parquet spark_catalog.default.store_sales (139) +: : : +- ReusedExchange (143) +: : +- BroadcastExchange (150) +: : +- * Project (149) +: : +- * Filter (148) +: : +- * ColumnarToRow (147) +: : +- CometScan parquet spark_catalog.default.time_dim (146) +: +- ReusedExchange (153) ++- BroadcastExchange (181) + +- * HashAggregate (180) + +- Exchange (179) + +- * HashAggregate (178) + +- * Project (177) + +- * BroadcastHashJoin Inner BuildRight (176) + :- * Project (174) + : +- * BroadcastHashJoin Inner BuildRight (173) + : :- * Project (167) + : : +- * BroadcastHashJoin Inner BuildRight (166) + : : :- * Project (164) + : : : +- * Filter (163) + : : : +- * ColumnarToRow (162) + : : : +- CometScan parquet spark_catalog.default.store_sales (161) + : : +- ReusedExchange (165) + : +- BroadcastExchange (172) + : +- * Project (171) + : +- * Filter (170) + : +- * ColumnarToRow (169) + : +- CometScan parquet spark_catalog.default.time_dim (168) + +- ReusedExchange (175) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 4] +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Condition : ((isnotnull(ss_hdemo_sk#2) AND isnotnull(ss_sold_time_sk#1)) AND isnotnull(ss_store_sk#3)) + +(4) Project [codegen id : 4] +Output [3]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] + +(5) Scan parquet spark_catalog.default.household_demographics +Output [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [Or(Or(And(EqualTo(hd_dep_count,4),LessThanOrEqual(hd_vehicle_count,6)),And(EqualTo(hd_dep_count,2),LessThanOrEqual(hd_vehicle_count,4))),And(EqualTo(hd_dep_count,0),LessThanOrEqual(hd_vehicle_count,2))), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] + +(7) Filter [codegen id : 1] +Input [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] +Condition : (((((hd_dep_count#6 = 4) AND (hd_vehicle_count#7 <= 6)) OR ((hd_dep_count#6 = 2) AND (hd_vehicle_count#7 <= 4))) OR ((hd_dep_count#6 = 0) AND (hd_vehicle_count#7 <= 2))) AND isnotnull(hd_demo_sk#5)) + +(8) Project [codegen id : 1] +Output [1]: [hd_demo_sk#5] +Input [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] + +(9) BroadcastExchange +Input [1]: [hd_demo_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#5] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 4] +Output [2]: [ss_sold_time_sk#1, ss_store_sk#3] +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, hd_demo_sk#5] + +(12) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#8, t_hour#9, t_minute#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,8), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(13) ColumnarToRow [codegen id : 2] +Input [3]: [t_time_sk#8, t_hour#9, t_minute#10] + +(14) Filter [codegen id : 2] +Input [3]: [t_time_sk#8, t_hour#9, t_minute#10] +Condition : ((((isnotnull(t_hour#9) AND isnotnull(t_minute#10)) AND (t_hour#9 = 8)) AND (t_minute#10 >= 30)) AND isnotnull(t_time_sk#8)) + +(15) Project [codegen id : 2] +Output [1]: [t_time_sk#8] +Input [3]: [t_time_sk#8, t_hour#9, t_minute#10] + +(16) BroadcastExchange +Input [1]: [t_time_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_time_sk#1] +Right keys [1]: [t_time_sk#8] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [1]: [ss_store_sk#3] +Input [3]: [ss_sold_time_sk#1, ss_store_sk#3, t_time_sk#8] + +(19) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_store_name#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_name), EqualTo(s_store_name,ese), IsNotNull(s_store_sk)] +ReadSchema: struct + +(20) ColumnarToRow [codegen id : 3] +Input [2]: [s_store_sk#11, s_store_name#12] + +(21) Filter [codegen id : 3] +Input [2]: [s_store_sk#11, s_store_name#12] +Condition : ((isnotnull(s_store_name#12) AND (s_store_name#12 = ese)) AND isnotnull(s_store_sk#11)) + +(22) Project [codegen id : 3] +Output [1]: [s_store_sk#11] +Input [2]: [s_store_sk#11, s_store_name#12] + +(23) BroadcastExchange +Input [1]: [s_store_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 4] +Output: [] +Input [2]: [ss_store_sk#3, s_store_sk#11] + +(26) HashAggregate [codegen id : 4] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#13] +Results [1]: [count#14] + +(27) Exchange +Input [1]: [count#14] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 40] +Input [1]: [count#14] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#15] +Results [1]: [count(1)#15 AS h8_30_to_9#16] + +(29) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, ss_sold_date_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 8] +Input [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, ss_sold_date_sk#20] + +(31) Filter [codegen id : 8] +Input [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, ss_sold_date_sk#20] +Condition : ((isnotnull(ss_hdemo_sk#18) AND isnotnull(ss_sold_time_sk#17)) AND isnotnull(ss_store_sk#19)) + +(32) Project [codegen id : 8] +Output [3]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19] +Input [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, ss_sold_date_sk#20] + +(33) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#21] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_hdemo_sk#18] +Right keys [1]: [hd_demo_sk#21] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [2]: [ss_sold_time_sk#17, ss_store_sk#19] +Input [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, hd_demo_sk#21] + +(36) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#22, t_hour#23, t_minute#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,9), LessThan(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(37) ColumnarToRow [codegen id : 6] +Input [3]: [t_time_sk#22, t_hour#23, t_minute#24] + +(38) Filter [codegen id : 6] +Input [3]: [t_time_sk#22, t_hour#23, t_minute#24] +Condition : ((((isnotnull(t_hour#23) AND isnotnull(t_minute#24)) AND (t_hour#23 = 9)) AND (t_minute#24 < 30)) AND isnotnull(t_time_sk#22)) + +(39) Project [codegen id : 6] +Output [1]: [t_time_sk#22] +Input [3]: [t_time_sk#22, t_hour#23, t_minute#24] + +(40) BroadcastExchange +Input [1]: [t_time_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(41) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_time_sk#17] +Right keys [1]: [t_time_sk#22] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 8] +Output [1]: [ss_store_sk#19] +Input [3]: [ss_sold_time_sk#17, ss_store_sk#19, t_time_sk#22] + +(43) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#25] + +(44) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#19] +Right keys [1]: [s_store_sk#25] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 8] +Output: [] +Input [2]: [ss_store_sk#19, s_store_sk#25] + +(46) HashAggregate [codegen id : 8] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#26] +Results [1]: [count#27] + +(47) Exchange +Input [1]: [count#27] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] + +(48) HashAggregate [codegen id : 9] +Input [1]: [count#27] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#28] +Results [1]: [count(1)#28 AS h9_to_9_30#29] + +(49) BroadcastExchange +Input [1]: [h9_to_9_30#29] +Arguments: IdentityBroadcastMode, [plan_id=7] + +(50) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(51) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, ss_sold_date_sk#33] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(52) ColumnarToRow [codegen id : 13] +Input [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, ss_sold_date_sk#33] + +(53) Filter [codegen id : 13] +Input [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, ss_sold_date_sk#33] +Condition : ((isnotnull(ss_hdemo_sk#31) AND isnotnull(ss_sold_time_sk#30)) AND isnotnull(ss_store_sk#32)) + +(54) Project [codegen id : 13] +Output [3]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32] +Input [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, ss_sold_date_sk#33] + +(55) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#34] + +(56) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_hdemo_sk#31] +Right keys [1]: [hd_demo_sk#34] +Join type: Inner +Join condition: None + +(57) Project [codegen id : 13] +Output [2]: [ss_sold_time_sk#30, ss_store_sk#32] +Input [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, hd_demo_sk#34] + +(58) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#35, t_hour#36, t_minute#37] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,9), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(59) ColumnarToRow [codegen id : 11] +Input [3]: [t_time_sk#35, t_hour#36, t_minute#37] + +(60) Filter [codegen id : 11] +Input [3]: [t_time_sk#35, t_hour#36, t_minute#37] +Condition : ((((isnotnull(t_hour#36) AND isnotnull(t_minute#37)) AND (t_hour#36 = 9)) AND (t_minute#37 >= 30)) AND isnotnull(t_time_sk#35)) + +(61) Project [codegen id : 11] +Output [1]: [t_time_sk#35] +Input [3]: [t_time_sk#35, t_hour#36, t_minute#37] + +(62) BroadcastExchange +Input [1]: [t_time_sk#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +(63) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_sold_time_sk#30] +Right keys [1]: [t_time_sk#35] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 13] +Output [1]: [ss_store_sk#32] +Input [3]: [ss_sold_time_sk#30, ss_store_sk#32, t_time_sk#35] + +(65) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#38] + +(66) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ss_store_sk#32] +Right keys [1]: [s_store_sk#38] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 13] +Output: [] +Input [2]: [ss_store_sk#32, s_store_sk#38] + +(68) HashAggregate [codegen id : 13] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#39] +Results [1]: [count#40] + +(69) Exchange +Input [1]: [count#40] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=9] + +(70) HashAggregate [codegen id : 14] +Input [1]: [count#40] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#41] +Results [1]: [count(1)#41 AS h9_30_to_10#42] + +(71) BroadcastExchange +Input [1]: [h9_30_to_10#42] +Arguments: IdentityBroadcastMode, [plan_id=10] + +(72) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(73) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, ss_sold_date_sk#46] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(74) ColumnarToRow [codegen id : 18] +Input [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, ss_sold_date_sk#46] + +(75) Filter [codegen id : 18] +Input [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, ss_sold_date_sk#46] +Condition : ((isnotnull(ss_hdemo_sk#44) AND isnotnull(ss_sold_time_sk#43)) AND isnotnull(ss_store_sk#45)) + +(76) Project [codegen id : 18] +Output [3]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45] +Input [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, ss_sold_date_sk#46] + +(77) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#47] + +(78) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ss_hdemo_sk#44] +Right keys [1]: [hd_demo_sk#47] +Join type: Inner +Join condition: None + +(79) Project [codegen id : 18] +Output [2]: [ss_sold_time_sk#43, ss_store_sk#45] +Input [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, hd_demo_sk#47] + +(80) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#48, t_hour#49, t_minute#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,10), LessThan(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(81) ColumnarToRow [codegen id : 16] +Input [3]: [t_time_sk#48, t_hour#49, t_minute#50] + +(82) Filter [codegen id : 16] +Input [3]: [t_time_sk#48, t_hour#49, t_minute#50] +Condition : ((((isnotnull(t_hour#49) AND isnotnull(t_minute#50)) AND (t_hour#49 = 10)) AND (t_minute#50 < 30)) AND isnotnull(t_time_sk#48)) + +(83) Project [codegen id : 16] +Output [1]: [t_time_sk#48] +Input [3]: [t_time_sk#48, t_hour#49, t_minute#50] + +(84) BroadcastExchange +Input [1]: [t_time_sk#48] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +(85) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ss_sold_time_sk#43] +Right keys [1]: [t_time_sk#48] +Join type: Inner +Join condition: None + +(86) Project [codegen id : 18] +Output [1]: [ss_store_sk#45] +Input [3]: [ss_sold_time_sk#43, ss_store_sk#45, t_time_sk#48] + +(87) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#51] + +(88) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [ss_store_sk#45] +Right keys [1]: [s_store_sk#51] +Join type: Inner +Join condition: None + +(89) Project [codegen id : 18] +Output: [] +Input [2]: [ss_store_sk#45, s_store_sk#51] + +(90) HashAggregate [codegen id : 18] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#52] +Results [1]: [count#53] + +(91) Exchange +Input [1]: [count#53] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=12] + +(92) HashAggregate [codegen id : 19] +Input [1]: [count#53] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#54] +Results [1]: [count(1)#54 AS h10_to_10_30#55] + +(93) BroadcastExchange +Input [1]: [h10_to_10_30#55] +Arguments: IdentityBroadcastMode, [plan_id=13] + +(94) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(95) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, ss_sold_date_sk#59] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(96) ColumnarToRow [codegen id : 23] +Input [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, ss_sold_date_sk#59] + +(97) Filter [codegen id : 23] +Input [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, ss_sold_date_sk#59] +Condition : ((isnotnull(ss_hdemo_sk#57) AND isnotnull(ss_sold_time_sk#56)) AND isnotnull(ss_store_sk#58)) + +(98) Project [codegen id : 23] +Output [3]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58] +Input [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, ss_sold_date_sk#59] + +(99) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#60] + +(100) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [ss_hdemo_sk#57] +Right keys [1]: [hd_demo_sk#60] +Join type: Inner +Join condition: None + +(101) Project [codegen id : 23] +Output [2]: [ss_sold_time_sk#56, ss_store_sk#58] +Input [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, hd_demo_sk#60] + +(102) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#61, t_hour#62, t_minute#63] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,10), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(103) ColumnarToRow [codegen id : 21] +Input [3]: [t_time_sk#61, t_hour#62, t_minute#63] + +(104) Filter [codegen id : 21] +Input [3]: [t_time_sk#61, t_hour#62, t_minute#63] +Condition : ((((isnotnull(t_hour#62) AND isnotnull(t_minute#63)) AND (t_hour#62 = 10)) AND (t_minute#63 >= 30)) AND isnotnull(t_time_sk#61)) + +(105) Project [codegen id : 21] +Output [1]: [t_time_sk#61] +Input [3]: [t_time_sk#61, t_hour#62, t_minute#63] + +(106) BroadcastExchange +Input [1]: [t_time_sk#61] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] + +(107) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [ss_sold_time_sk#56] +Right keys [1]: [t_time_sk#61] +Join type: Inner +Join condition: None + +(108) Project [codegen id : 23] +Output [1]: [ss_store_sk#58] +Input [3]: [ss_sold_time_sk#56, ss_store_sk#58, t_time_sk#61] + +(109) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#64] + +(110) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [ss_store_sk#58] +Right keys [1]: [s_store_sk#64] +Join type: Inner +Join condition: None + +(111) Project [codegen id : 23] +Output: [] +Input [2]: [ss_store_sk#58, s_store_sk#64] + +(112) HashAggregate [codegen id : 23] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#65] +Results [1]: [count#66] + +(113) Exchange +Input [1]: [count#66] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=15] + +(114) HashAggregate [codegen id : 24] +Input [1]: [count#66] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#67] +Results [1]: [count(1)#67 AS h10_30_to_11#68] + +(115) BroadcastExchange +Input [1]: [h10_30_to_11#68] +Arguments: IdentityBroadcastMode, [plan_id=16] + +(116) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(117) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, ss_sold_date_sk#72] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(118) ColumnarToRow [codegen id : 28] +Input [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, ss_sold_date_sk#72] + +(119) Filter [codegen id : 28] +Input [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, ss_sold_date_sk#72] +Condition : ((isnotnull(ss_hdemo_sk#70) AND isnotnull(ss_sold_time_sk#69)) AND isnotnull(ss_store_sk#71)) + +(120) Project [codegen id : 28] +Output [3]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71] +Input [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, ss_sold_date_sk#72] + +(121) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#73] + +(122) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [ss_hdemo_sk#70] +Right keys [1]: [hd_demo_sk#73] +Join type: Inner +Join condition: None + +(123) Project [codegen id : 28] +Output [2]: [ss_sold_time_sk#69, ss_store_sk#71] +Input [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, hd_demo_sk#73] + +(124) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#74, t_hour#75, t_minute#76] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,11), LessThan(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(125) ColumnarToRow [codegen id : 26] +Input [3]: [t_time_sk#74, t_hour#75, t_minute#76] + +(126) Filter [codegen id : 26] +Input [3]: [t_time_sk#74, t_hour#75, t_minute#76] +Condition : ((((isnotnull(t_hour#75) AND isnotnull(t_minute#76)) AND (t_hour#75 = 11)) AND (t_minute#76 < 30)) AND isnotnull(t_time_sk#74)) + +(127) Project [codegen id : 26] +Output [1]: [t_time_sk#74] +Input [3]: [t_time_sk#74, t_hour#75, t_minute#76] + +(128) BroadcastExchange +Input [1]: [t_time_sk#74] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=17] + +(129) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [ss_sold_time_sk#69] +Right keys [1]: [t_time_sk#74] +Join type: Inner +Join condition: None + +(130) Project [codegen id : 28] +Output [1]: [ss_store_sk#71] +Input [3]: [ss_sold_time_sk#69, ss_store_sk#71, t_time_sk#74] + +(131) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#77] + +(132) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [ss_store_sk#71] +Right keys [1]: [s_store_sk#77] +Join type: Inner +Join condition: None + +(133) Project [codegen id : 28] +Output: [] +Input [2]: [ss_store_sk#71, s_store_sk#77] + +(134) HashAggregate [codegen id : 28] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#78] +Results [1]: [count#79] + +(135) Exchange +Input [1]: [count#79] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=18] + +(136) HashAggregate [codegen id : 29] +Input [1]: [count#79] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#80] +Results [1]: [count(1)#80 AS h11_to_11_30#81] + +(137) BroadcastExchange +Input [1]: [h11_to_11_30#81] +Arguments: IdentityBroadcastMode, [plan_id=19] + +(138) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(139) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, ss_sold_date_sk#85] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(140) ColumnarToRow [codegen id : 33] +Input [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, ss_sold_date_sk#85] + +(141) Filter [codegen id : 33] +Input [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, ss_sold_date_sk#85] +Condition : ((isnotnull(ss_hdemo_sk#83) AND isnotnull(ss_sold_time_sk#82)) AND isnotnull(ss_store_sk#84)) + +(142) Project [codegen id : 33] +Output [3]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84] +Input [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, ss_sold_date_sk#85] + +(143) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#86] + +(144) BroadcastHashJoin [codegen id : 33] +Left keys [1]: [ss_hdemo_sk#83] +Right keys [1]: [hd_demo_sk#86] +Join type: Inner +Join condition: None + +(145) Project [codegen id : 33] +Output [2]: [ss_sold_time_sk#82, ss_store_sk#84] +Input [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, hd_demo_sk#86] + +(146) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#87, t_hour#88, t_minute#89] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,11), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(147) ColumnarToRow [codegen id : 31] +Input [3]: [t_time_sk#87, t_hour#88, t_minute#89] + +(148) Filter [codegen id : 31] +Input [3]: [t_time_sk#87, t_hour#88, t_minute#89] +Condition : ((((isnotnull(t_hour#88) AND isnotnull(t_minute#89)) AND (t_hour#88 = 11)) AND (t_minute#89 >= 30)) AND isnotnull(t_time_sk#87)) + +(149) Project [codegen id : 31] +Output [1]: [t_time_sk#87] +Input [3]: [t_time_sk#87, t_hour#88, t_minute#89] + +(150) BroadcastExchange +Input [1]: [t_time_sk#87] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=20] + +(151) BroadcastHashJoin [codegen id : 33] +Left keys [1]: [ss_sold_time_sk#82] +Right keys [1]: [t_time_sk#87] +Join type: Inner +Join condition: None + +(152) Project [codegen id : 33] +Output [1]: [ss_store_sk#84] +Input [3]: [ss_sold_time_sk#82, ss_store_sk#84, t_time_sk#87] + +(153) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#90] + +(154) BroadcastHashJoin [codegen id : 33] +Left keys [1]: [ss_store_sk#84] +Right keys [1]: [s_store_sk#90] +Join type: Inner +Join condition: None + +(155) Project [codegen id : 33] +Output: [] +Input [2]: [ss_store_sk#84, s_store_sk#90] + +(156) HashAggregate [codegen id : 33] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#91] +Results [1]: [count#92] + +(157) Exchange +Input [1]: [count#92] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=21] + +(158) HashAggregate [codegen id : 34] +Input [1]: [count#92] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#93] +Results [1]: [count(1)#93 AS h11_30_to_12#94] + +(159) BroadcastExchange +Input [1]: [h11_30_to_12#94] +Arguments: IdentityBroadcastMode, [plan_id=22] + +(160) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + +(161) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, ss_sold_date_sk#98] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(162) ColumnarToRow [codegen id : 38] +Input [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, ss_sold_date_sk#98] + +(163) Filter [codegen id : 38] +Input [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, ss_sold_date_sk#98] +Condition : ((isnotnull(ss_hdemo_sk#96) AND isnotnull(ss_sold_time_sk#95)) AND isnotnull(ss_store_sk#97)) + +(164) Project [codegen id : 38] +Output [3]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97] +Input [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, ss_sold_date_sk#98] + +(165) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#99] + +(166) BroadcastHashJoin [codegen id : 38] +Left keys [1]: [ss_hdemo_sk#96] +Right keys [1]: [hd_demo_sk#99] +Join type: Inner +Join condition: None + +(167) Project [codegen id : 38] +Output [2]: [ss_sold_time_sk#95, ss_store_sk#97] +Input [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, hd_demo_sk#99] + +(168) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#100, t_hour#101, t_minute#102] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,12), LessThan(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(169) ColumnarToRow [codegen id : 36] +Input [3]: [t_time_sk#100, t_hour#101, t_minute#102] + +(170) Filter [codegen id : 36] +Input [3]: [t_time_sk#100, t_hour#101, t_minute#102] +Condition : ((((isnotnull(t_hour#101) AND isnotnull(t_minute#102)) AND (t_hour#101 = 12)) AND (t_minute#102 < 30)) AND isnotnull(t_time_sk#100)) + +(171) Project [codegen id : 36] +Output [1]: [t_time_sk#100] +Input [3]: [t_time_sk#100, t_hour#101, t_minute#102] + +(172) BroadcastExchange +Input [1]: [t_time_sk#100] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=23] + +(173) BroadcastHashJoin [codegen id : 38] +Left keys [1]: [ss_sold_time_sk#95] +Right keys [1]: [t_time_sk#100] +Join type: Inner +Join condition: None + +(174) Project [codegen id : 38] +Output [1]: [ss_store_sk#97] +Input [3]: [ss_sold_time_sk#95, ss_store_sk#97, t_time_sk#100] + +(175) ReusedExchange [Reuses operator id: 23] +Output [1]: [s_store_sk#103] + +(176) BroadcastHashJoin [codegen id : 38] +Left keys [1]: [ss_store_sk#97] +Right keys [1]: [s_store_sk#103] +Join type: Inner +Join condition: None + +(177) Project [codegen id : 38] +Output: [] +Input [2]: [ss_store_sk#97, s_store_sk#103] + +(178) HashAggregate [codegen id : 38] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#104] +Results [1]: [count#105] + +(179) Exchange +Input [1]: [count#105] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=24] + +(180) HashAggregate [codegen id : 39] +Input [1]: [count#105] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#106] +Results [1]: [count(1)#106 AS h12_to_12_30#107] + +(181) BroadcastExchange +Input [1]: [h12_to_12_30#107] +Arguments: IdentityBroadcastMode, [plan_id=25] + +(182) BroadcastNestedLoopJoin [codegen id : 40] +Join type: Inner +Join condition: None + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/simplified.txt new file mode 100644 index 000000000..3087d3432 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/simplified.txt @@ -0,0 +1,265 @@ +WholeStageCodegen (40) + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + BroadcastNestedLoopJoin + HashAggregate [count] [count(1),h8_30_to_9,count] + InputAdapter + Exchange #1 + WholeStageCodegen (4) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Project [hd_demo_sk] + Filter [hd_dep_count,hd_vehicle_count,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [t_time_sk] + Filter [t_hour,t_minute,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Project [s_store_sk] + Filter [s_store_name,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (9) + HashAggregate [count] [count(1),h9_to_9_30,count] + InputAdapter + Exchange #6 + WholeStageCodegen (8) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + Project [t_time_sk] + Filter [t_hour,t_minute,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (14) + HashAggregate [count] [count(1),h9_30_to_10,count] + InputAdapter + Exchange #9 + WholeStageCodegen (13) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (11) + Project [t_time_sk] + Filter [t_hour,t_minute,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (19) + HashAggregate [count] [count(1),h10_to_10_30,count] + InputAdapter + Exchange #12 + WholeStageCodegen (18) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (16) + Project [t_time_sk] + Filter [t_hour,t_minute,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #14 + WholeStageCodegen (24) + HashAggregate [count] [count(1),h10_30_to_11,count] + InputAdapter + Exchange #15 + WholeStageCodegen (23) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #16 + WholeStageCodegen (21) + Project [t_time_sk] + Filter [t_hour,t_minute,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #17 + WholeStageCodegen (29) + HashAggregate [count] [count(1),h11_to_11_30,count] + InputAdapter + Exchange #18 + WholeStageCodegen (28) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #19 + WholeStageCodegen (26) + Project [t_time_sk] + Filter [t_hour,t_minute,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #20 + WholeStageCodegen (34) + HashAggregate [count] [count(1),h11_30_to_12,count] + InputAdapter + Exchange #21 + WholeStageCodegen (33) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #22 + WholeStageCodegen (31) + Project [t_time_sk] + Filter [t_hour,t_minute,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 + InputAdapter + BroadcastExchange #23 + WholeStageCodegen (39) + HashAggregate [count] [count(1),h12_to_12_30,count] + InputAdapter + Exchange #24 + WholeStageCodegen (38) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #25 + WholeStageCodegen (36) + Project [t_time_sk] + Filter [t_hour,t_minute,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + ReusedExchange [s_store_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/explain.txt new file mode 100644 index 000000000..bfa41701d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/explain.txt @@ -0,0 +1,189 @@ +== Physical Plan == +TakeOrderedAndProject (27) ++- * Project (26) + +- * Filter (25) + +- Window (24) + +- * Sort (23) + +- Exchange (22) + +- * HashAggregate (21) + +- Exchange (20) + +- * HashAggregate (19) + +- * Project (18) + +- * BroadcastHashJoin Inner BuildRight (17) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (9) + : : +- * BroadcastHashJoin Inner BuildRight (8) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.item (1) + : : +- BroadcastExchange (7) + : : +- * Filter (6) + : : +- * ColumnarToRow (5) + : : +- CometScan parquet spark_catalog.default.store_sales (4) + : +- ReusedExchange (10) + +- BroadcastExchange (16) + +- * Filter (15) + +- * ColumnarToRow (14) + +- CometScan parquet spark_catalog.default.store (13) + + +(1) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [Or(And(In(i_category, [Books ,Electronics ,Sports ]),In(i_class, [computers ,football ,stereo ])),And(In(i_category, [Jewelry ,Men ,Women ]),In(i_class, [birdal ,dresses ,shirts ]))), IsNotNull(i_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4] + +(3) Filter [codegen id : 4] +Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4] +Condition : (((i_category#4 IN (Books ,Electronics ,Sports ) AND i_class#3 IN (computers ,stereo ,football )) OR (i_category#4 IN (Men ,Jewelry ,Women ) AND i_class#3 IN (shirts ,birdal ,dresses ))) AND isnotnull(i_item_sk#1)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] + +(6) Filter [codegen id : 1] +Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] +Condition : (isnotnull(ss_item_sk#5) AND isnotnull(ss_store_sk#6)) + +(7) BroadcastExchange +Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [6]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] +Input [8]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] + +(10) ReusedExchange [Reuses operator id: 32] +Output [2]: [d_date_sk#10, d_moy#11] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, d_moy#11] +Input [8]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8, d_date_sk#10, d_moy#11] + +(13) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] + +(15) Filter [codegen id : 3] +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Condition : isnotnull(s_store_sk#12) + +(16) BroadcastExchange +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#6] +Right keys [1]: [s_store_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [7]: [i_brand#2, i_class#3, i_category#4, ss_sales_price#7, d_moy#11, s_store_name#13, s_company_name#14] +Input [9]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, d_moy#11, s_store_sk#12, s_store_name#13, s_company_name#14] + +(19) HashAggregate [codegen id : 4] +Input [7]: [i_brand#2, i_class#3, i_category#4, ss_sales_price#7, d_moy#11, s_store_name#13, s_company_name#14] +Keys [6]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#7))] +Aggregate Attributes [1]: [sum#15] +Results [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#16] + +(20) Exchange +Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#16] +Arguments: hashpartitioning(i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#16] +Keys [6]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11] +Functions [1]: [sum(UnscaledValue(ss_sales_price#7))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#7))#17] +Results [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, MakeDecimal(sum(UnscaledValue(ss_sales_price#7))#17,17,2) AS sum_sales#18, MakeDecimal(sum(UnscaledValue(ss_sales_price#7))#17,17,2) AS _w0#19] + +(22) Exchange +Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, _w0#19] +Arguments: hashpartitioning(i_category#4, i_brand#2, s_store_name#13, s_company_name#14, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) Sort [codegen id : 6] +Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, _w0#19] +Arguments: [i_category#4 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST, s_company_name#14 ASC NULLS FIRST], false, 0 + +(24) Window +Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, _w0#19] +Arguments: [avg(_w0#19) windowspecdefinition(i_category#4, i_brand#2, s_store_name#13, s_company_name#14, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#20], [i_category#4, i_brand#2, s_store_name#13, s_company_name#14] + +(25) Filter [codegen id : 7] +Input [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, _w0#19, avg_monthly_sales#20] +Condition : CASE WHEN NOT (avg_monthly_sales#20 = 0.000000) THEN ((abs((sum_sales#18 - avg_monthly_sales#20)) / avg_monthly_sales#20) > 0.1000000000000000) END + +(26) Project [codegen id : 7] +Output [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, avg_monthly_sales#20] +Input [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, _w0#19, avg_monthly_sales#20] + +(27) TakeOrderedAndProject +Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, avg_monthly_sales#20] +Arguments: 100, [(sum_sales#18 - avg_monthly_sales#20) ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST], [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#18, avg_monthly_sales#20] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (32) ++- * Project (31) + +- * Filter (30) + +- * ColumnarToRow (29) + +- CometScan parquet spark_catalog.default.date_dim (28) + + +(28) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#21, d_moy#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(29) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#21, d_moy#11] + +(30) Filter [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#21, d_moy#11] +Condition : ((isnotnull(d_year#21) AND (d_year#21 = 1999)) AND isnotnull(d_date_sk#10)) + +(31) Project [codegen id : 1] +Output [2]: [d_date_sk#10, d_moy#11] +Input [3]: [d_date_sk#10, d_year#21, d_moy#11] + +(32) BroadcastExchange +Input [2]: [d_date_sk#10, d_moy#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/simplified.txt new file mode 100644 index 000000000..d7daa4af9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/simplified.txt @@ -0,0 +1,50 @@ +TakeOrderedAndProject [sum_sales,avg_monthly_sales,s_store_name,i_category,i_class,i_brand,s_company_name,d_moy] + WholeStageCodegen (7) + Project [i_category,i_class,i_brand,s_store_name,s_company_name,d_moy,sum_sales,avg_monthly_sales] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (6) + Sort [i_category,i_brand,s_store_name,s_company_name] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_class,i_brand,s_store_name,s_company_name,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_category,i_class,i_brand,s_store_name,s_company_name,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,i_brand,s_store_name,s_company_name,d_moy,ss_sales_price] [sum,sum] + Project [i_brand,i_class,i_category,ss_sales_price,d_moy,s_store_name,s_company_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [i_brand,i_class,i_category,ss_store_sk,ss_sales_price,d_moy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [i_brand,i_class,i_category,ss_store_sk,ss_sales_price,ss_sold_date_sk] + BroadcastHashJoin [i_item_sk,ss_item_sk] + Filter [i_category,i_class,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [ss_item_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk,d_moy] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/explain.txt new file mode 100644 index 000000000..1b7aad28b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/explain.txt @@ -0,0 +1,303 @@ +== Physical Plan == +* Project (4) ++- * Filter (3) + +- * ColumnarToRow (2) + +- CometScan parquet spark_catalog.default.reason (1) + + +(1) Scan parquet spark_catalog.default.reason +Output [1]: [r_reason_sk#1] +Batched: true +Location [not included in comparison]/{warehouse_dir}/reason] +PushedFilters: [IsNotNull(r_reason_sk), EqualTo(r_reason_sk,1)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [1]: [r_reason_sk#1] + +(3) Filter [codegen id : 1] +Input [1]: [r_reason_sk#1] +Condition : (isnotnull(r_reason_sk#1) AND (r_reason_sk#1 = 1)) + +(4) Project [codegen id : 1] +Output [5]: [CASE WHEN (Subquery scalar-subquery#2, [id=#3].count(1) > 62316685) THEN ReusedSubquery Subquery scalar-subquery#2, [id=#3].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#2, [id=#3].avg(ss_net_paid) END AS bucket1#4, CASE WHEN (Subquery scalar-subquery#5, [id=#6].count(1) > 19045798) THEN ReusedSubquery Subquery scalar-subquery#5, [id=#6].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#5, [id=#6].avg(ss_net_paid) END AS bucket2#7, CASE WHEN (Subquery scalar-subquery#8, [id=#9].count(1) > 365541424) THEN ReusedSubquery Subquery scalar-subquery#8, [id=#9].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#8, [id=#9].avg(ss_net_paid) END AS bucket3#10, CASE WHEN (Subquery scalar-subquery#11, [id=#12].count(1) > 216357808) THEN ReusedSubquery Subquery scalar-subquery#11, [id=#12].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#11, [id=#12].avg(ss_net_paid) END AS bucket4#13, CASE WHEN (Subquery scalar-subquery#14, [id=#15].count(1) > 184483884) THEN ReusedSubquery Subquery scalar-subquery#14, [id=#15].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#14, [id=#15].avg(ss_net_paid) END AS bucket5#16] +Input [1]: [r_reason_sk#1] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery#2, [id=#3] +* Project (12) ++- * HashAggregate (11) + +- Exchange (10) + +- * HashAggregate (9) + +- * Project (8) + +- * Filter (7) + +- * ColumnarToRow (6) + +- CometScan parquet spark_catalog.default.store_sales (5) + + +(5) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_quantity#17, ss_ext_discount_amt#18, ss_net_paid#19, ss_sold_date_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,1), LessThanOrEqual(ss_quantity,20)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [4]: [ss_quantity#17, ss_ext_discount_amt#18, ss_net_paid#19, ss_sold_date_sk#20] + +(7) Filter [codegen id : 1] +Input [4]: [ss_quantity#17, ss_ext_discount_amt#18, ss_net_paid#19, ss_sold_date_sk#20] +Condition : ((isnotnull(ss_quantity#17) AND (ss_quantity#17 >= 1)) AND (ss_quantity#17 <= 20)) + +(8) Project [codegen id : 1] +Output [2]: [ss_ext_discount_amt#18, ss_net_paid#19] +Input [4]: [ss_quantity#17, ss_ext_discount_amt#18, ss_net_paid#19, ss_sold_date_sk#20] + +(9) HashAggregate [codegen id : 1] +Input [2]: [ss_ext_discount_amt#18, ss_net_paid#19] +Keys: [] +Functions [3]: [partial_count(1), partial_avg(UnscaledValue(ss_ext_discount_amt#18)), partial_avg(UnscaledValue(ss_net_paid#19))] +Aggregate Attributes [5]: [count#21, sum#22, count#23, sum#24, count#25] +Results [5]: [count#26, sum#27, count#28, sum#29, count#30] + +(10) Exchange +Input [5]: [count#26, sum#27, count#28, sum#29, count#30] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=1] + +(11) HashAggregate [codegen id : 2] +Input [5]: [count#26, sum#27, count#28, sum#29, count#30] +Keys: [] +Functions [3]: [count(1), avg(UnscaledValue(ss_ext_discount_amt#18)), avg(UnscaledValue(ss_net_paid#19))] +Aggregate Attributes [3]: [count(1)#31, avg(UnscaledValue(ss_ext_discount_amt#18))#32, avg(UnscaledValue(ss_net_paid#19))#33] +Results [3]: [count(1)#31 AS count(1)#34, cast((avg(UnscaledValue(ss_ext_discount_amt#18))#32 / 100.0) as decimal(11,6)) AS avg(ss_ext_discount_amt)#35, cast((avg(UnscaledValue(ss_net_paid#19))#33 / 100.0) as decimal(11,6)) AS avg(ss_net_paid)#36] + +(12) Project [codegen id : 2] +Output [1]: [named_struct(count(1), count(1)#34, avg(ss_ext_discount_amt), avg(ss_ext_discount_amt)#35, avg(ss_net_paid), avg(ss_net_paid)#36) AS mergedValue#37] +Input [3]: [count(1)#34, avg(ss_ext_discount_amt)#35, avg(ss_net_paid)#36] + +Subquery:2 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#2, [id=#3] + +Subquery:3 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#2, [id=#3] + +Subquery:4 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery#5, [id=#6] +* Project (20) ++- * HashAggregate (19) + +- Exchange (18) + +- * HashAggregate (17) + +- * Project (16) + +- * Filter (15) + +- * ColumnarToRow (14) + +- CometScan parquet spark_catalog.default.store_sales (13) + + +(13) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_quantity#38, ss_ext_discount_amt#39, ss_net_paid#40, ss_sold_date_sk#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,21), LessThanOrEqual(ss_quantity,40)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 1] +Input [4]: [ss_quantity#38, ss_ext_discount_amt#39, ss_net_paid#40, ss_sold_date_sk#41] + +(15) Filter [codegen id : 1] +Input [4]: [ss_quantity#38, ss_ext_discount_amt#39, ss_net_paid#40, ss_sold_date_sk#41] +Condition : ((isnotnull(ss_quantity#38) AND (ss_quantity#38 >= 21)) AND (ss_quantity#38 <= 40)) + +(16) Project [codegen id : 1] +Output [2]: [ss_ext_discount_amt#39, ss_net_paid#40] +Input [4]: [ss_quantity#38, ss_ext_discount_amt#39, ss_net_paid#40, ss_sold_date_sk#41] + +(17) HashAggregate [codegen id : 1] +Input [2]: [ss_ext_discount_amt#39, ss_net_paid#40] +Keys: [] +Functions [3]: [partial_count(1), partial_avg(UnscaledValue(ss_ext_discount_amt#39)), partial_avg(UnscaledValue(ss_net_paid#40))] +Aggregate Attributes [5]: [count#42, sum#43, count#44, sum#45, count#46] +Results [5]: [count#47, sum#48, count#49, sum#50, count#51] + +(18) Exchange +Input [5]: [count#47, sum#48, count#49, sum#50, count#51] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=2] + +(19) HashAggregate [codegen id : 2] +Input [5]: [count#47, sum#48, count#49, sum#50, count#51] +Keys: [] +Functions [3]: [count(1), avg(UnscaledValue(ss_ext_discount_amt#39)), avg(UnscaledValue(ss_net_paid#40))] +Aggregate Attributes [3]: [count(1)#52, avg(UnscaledValue(ss_ext_discount_amt#39))#53, avg(UnscaledValue(ss_net_paid#40))#54] +Results [3]: [count(1)#52 AS count(1)#55, cast((avg(UnscaledValue(ss_ext_discount_amt#39))#53 / 100.0) as decimal(11,6)) AS avg(ss_ext_discount_amt)#56, cast((avg(UnscaledValue(ss_net_paid#40))#54 / 100.0) as decimal(11,6)) AS avg(ss_net_paid)#57] + +(20) Project [codegen id : 2] +Output [1]: [named_struct(count(1), count(1)#55, avg(ss_ext_discount_amt), avg(ss_ext_discount_amt)#56, avg(ss_net_paid), avg(ss_net_paid)#57) AS mergedValue#58] +Input [3]: [count(1)#55, avg(ss_ext_discount_amt)#56, avg(ss_net_paid)#57] + +Subquery:5 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#5, [id=#6] + +Subquery:6 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#5, [id=#6] + +Subquery:7 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery#8, [id=#9] +* Project (28) ++- * HashAggregate (27) + +- Exchange (26) + +- * HashAggregate (25) + +- * Project (24) + +- * Filter (23) + +- * ColumnarToRow (22) + +- CometScan parquet spark_catalog.default.store_sales (21) + + +(21) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_quantity#59, ss_ext_discount_amt#60, ss_net_paid#61, ss_sold_date_sk#62] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,41), LessThanOrEqual(ss_quantity,60)] +ReadSchema: struct + +(22) ColumnarToRow [codegen id : 1] +Input [4]: [ss_quantity#59, ss_ext_discount_amt#60, ss_net_paid#61, ss_sold_date_sk#62] + +(23) Filter [codegen id : 1] +Input [4]: [ss_quantity#59, ss_ext_discount_amt#60, ss_net_paid#61, ss_sold_date_sk#62] +Condition : ((isnotnull(ss_quantity#59) AND (ss_quantity#59 >= 41)) AND (ss_quantity#59 <= 60)) + +(24) Project [codegen id : 1] +Output [2]: [ss_ext_discount_amt#60, ss_net_paid#61] +Input [4]: [ss_quantity#59, ss_ext_discount_amt#60, ss_net_paid#61, ss_sold_date_sk#62] + +(25) HashAggregate [codegen id : 1] +Input [2]: [ss_ext_discount_amt#60, ss_net_paid#61] +Keys: [] +Functions [3]: [partial_count(1), partial_avg(UnscaledValue(ss_ext_discount_amt#60)), partial_avg(UnscaledValue(ss_net_paid#61))] +Aggregate Attributes [5]: [count#63, sum#64, count#65, sum#66, count#67] +Results [5]: [count#68, sum#69, count#70, sum#71, count#72] + +(26) Exchange +Input [5]: [count#68, sum#69, count#70, sum#71, count#72] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 2] +Input [5]: [count#68, sum#69, count#70, sum#71, count#72] +Keys: [] +Functions [3]: [count(1), avg(UnscaledValue(ss_ext_discount_amt#60)), avg(UnscaledValue(ss_net_paid#61))] +Aggregate Attributes [3]: [count(1)#73, avg(UnscaledValue(ss_ext_discount_amt#60))#74, avg(UnscaledValue(ss_net_paid#61))#75] +Results [3]: [count(1)#73 AS count(1)#76, cast((avg(UnscaledValue(ss_ext_discount_amt#60))#74 / 100.0) as decimal(11,6)) AS avg(ss_ext_discount_amt)#77, cast((avg(UnscaledValue(ss_net_paid#61))#75 / 100.0) as decimal(11,6)) AS avg(ss_net_paid)#78] + +(28) Project [codegen id : 2] +Output [1]: [named_struct(count(1), count(1)#76, avg(ss_ext_discount_amt), avg(ss_ext_discount_amt)#77, avg(ss_net_paid), avg(ss_net_paid)#78) AS mergedValue#79] +Input [3]: [count(1)#76, avg(ss_ext_discount_amt)#77, avg(ss_net_paid)#78] + +Subquery:8 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#8, [id=#9] + +Subquery:9 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#8, [id=#9] + +Subquery:10 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery#11, [id=#12] +* Project (36) ++- * HashAggregate (35) + +- Exchange (34) + +- * HashAggregate (33) + +- * Project (32) + +- * Filter (31) + +- * ColumnarToRow (30) + +- CometScan parquet spark_catalog.default.store_sales (29) + + +(29) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_quantity#80, ss_ext_discount_amt#81, ss_net_paid#82, ss_sold_date_sk#83] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,61), LessThanOrEqual(ss_quantity,80)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 1] +Input [4]: [ss_quantity#80, ss_ext_discount_amt#81, ss_net_paid#82, ss_sold_date_sk#83] + +(31) Filter [codegen id : 1] +Input [4]: [ss_quantity#80, ss_ext_discount_amt#81, ss_net_paid#82, ss_sold_date_sk#83] +Condition : ((isnotnull(ss_quantity#80) AND (ss_quantity#80 >= 61)) AND (ss_quantity#80 <= 80)) + +(32) Project [codegen id : 1] +Output [2]: [ss_ext_discount_amt#81, ss_net_paid#82] +Input [4]: [ss_quantity#80, ss_ext_discount_amt#81, ss_net_paid#82, ss_sold_date_sk#83] + +(33) HashAggregate [codegen id : 1] +Input [2]: [ss_ext_discount_amt#81, ss_net_paid#82] +Keys: [] +Functions [3]: [partial_count(1), partial_avg(UnscaledValue(ss_ext_discount_amt#81)), partial_avg(UnscaledValue(ss_net_paid#82))] +Aggregate Attributes [5]: [count#84, sum#85, count#86, sum#87, count#88] +Results [5]: [count#89, sum#90, count#91, sum#92, count#93] + +(34) Exchange +Input [5]: [count#89, sum#90, count#91, sum#92, count#93] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(35) HashAggregate [codegen id : 2] +Input [5]: [count#89, sum#90, count#91, sum#92, count#93] +Keys: [] +Functions [3]: [count(1), avg(UnscaledValue(ss_ext_discount_amt#81)), avg(UnscaledValue(ss_net_paid#82))] +Aggregate Attributes [3]: [count(1)#94, avg(UnscaledValue(ss_ext_discount_amt#81))#95, avg(UnscaledValue(ss_net_paid#82))#96] +Results [3]: [count(1)#94 AS count(1)#97, cast((avg(UnscaledValue(ss_ext_discount_amt#81))#95 / 100.0) as decimal(11,6)) AS avg(ss_ext_discount_amt)#98, cast((avg(UnscaledValue(ss_net_paid#82))#96 / 100.0) as decimal(11,6)) AS avg(ss_net_paid)#99] + +(36) Project [codegen id : 2] +Output [1]: [named_struct(count(1), count(1)#97, avg(ss_ext_discount_amt), avg(ss_ext_discount_amt)#98, avg(ss_net_paid), avg(ss_net_paid)#99) AS mergedValue#100] +Input [3]: [count(1)#97, avg(ss_ext_discount_amt)#98, avg(ss_net_paid)#99] + +Subquery:11 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#11, [id=#12] + +Subquery:12 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#11, [id=#12] + +Subquery:13 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery#14, [id=#15] +* Project (44) ++- * HashAggregate (43) + +- Exchange (42) + +- * HashAggregate (41) + +- * Project (40) + +- * Filter (39) + +- * ColumnarToRow (38) + +- CometScan parquet spark_catalog.default.store_sales (37) + + +(37) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_quantity#101, ss_ext_discount_amt#102, ss_net_paid#103, ss_sold_date_sk#104] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,81), LessThanOrEqual(ss_quantity,100)] +ReadSchema: struct + +(38) ColumnarToRow [codegen id : 1] +Input [4]: [ss_quantity#101, ss_ext_discount_amt#102, ss_net_paid#103, ss_sold_date_sk#104] + +(39) Filter [codegen id : 1] +Input [4]: [ss_quantity#101, ss_ext_discount_amt#102, ss_net_paid#103, ss_sold_date_sk#104] +Condition : ((isnotnull(ss_quantity#101) AND (ss_quantity#101 >= 81)) AND (ss_quantity#101 <= 100)) + +(40) Project [codegen id : 1] +Output [2]: [ss_ext_discount_amt#102, ss_net_paid#103] +Input [4]: [ss_quantity#101, ss_ext_discount_amt#102, ss_net_paid#103, ss_sold_date_sk#104] + +(41) HashAggregate [codegen id : 1] +Input [2]: [ss_ext_discount_amt#102, ss_net_paid#103] +Keys: [] +Functions [3]: [partial_count(1), partial_avg(UnscaledValue(ss_ext_discount_amt#102)), partial_avg(UnscaledValue(ss_net_paid#103))] +Aggregate Attributes [5]: [count#105, sum#106, count#107, sum#108, count#109] +Results [5]: [count#110, sum#111, count#112, sum#113, count#114] + +(42) Exchange +Input [5]: [count#110, sum#111, count#112, sum#113, count#114] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=5] + +(43) HashAggregate [codegen id : 2] +Input [5]: [count#110, sum#111, count#112, sum#113, count#114] +Keys: [] +Functions [3]: [count(1), avg(UnscaledValue(ss_ext_discount_amt#102)), avg(UnscaledValue(ss_net_paid#103))] +Aggregate Attributes [3]: [count(1)#115, avg(UnscaledValue(ss_ext_discount_amt#102))#116, avg(UnscaledValue(ss_net_paid#103))#117] +Results [3]: [count(1)#115 AS count(1)#118, cast((avg(UnscaledValue(ss_ext_discount_amt#102))#116 / 100.0) as decimal(11,6)) AS avg(ss_ext_discount_amt)#119, cast((avg(UnscaledValue(ss_net_paid#103))#117 / 100.0) as decimal(11,6)) AS avg(ss_net_paid)#120] + +(44) Project [codegen id : 2] +Output [1]: [named_struct(count(1), count(1)#118, avg(ss_ext_discount_amt), avg(ss_ext_discount_amt)#119, avg(ss_net_paid), avg(ss_net_paid)#120) AS mergedValue#121] +Input [3]: [count(1)#118, avg(ss_ext_discount_amt)#119, avg(ss_net_paid)#120] + +Subquery:14 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#14, [id=#15] + +Subquery:15 Hosting operator id = 4 Hosting Expression = ReusedSubquery Subquery scalar-subquery#14, [id=#15] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/simplified.txt new file mode 100644 index 000000000..9e0a4a1ab --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/simplified.txt @@ -0,0 +1,81 @@ +WholeStageCodegen (1) + Project + Subquery #1 + WholeStageCodegen (2) + Project [count(1),avg(ss_ext_discount_amt),avg(ss_net_paid)] + HashAggregate [count,sum,count,sum,count] [count(1),avg(UnscaledValue(ss_ext_discount_amt)),avg(UnscaledValue(ss_net_paid)),count(1),avg(ss_ext_discount_amt),avg(ss_net_paid),count,sum,count,sum,count] + InputAdapter + Exchange #1 + WholeStageCodegen (1) + HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] + Project [ss_ext_discount_amt,ss_net_paid] + Filter [ss_quantity] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] + ReusedSubquery [mergedValue] #1 + ReusedSubquery [mergedValue] #1 + Subquery #2 + WholeStageCodegen (2) + Project [count(1),avg(ss_ext_discount_amt),avg(ss_net_paid)] + HashAggregate [count,sum,count,sum,count] [count(1),avg(UnscaledValue(ss_ext_discount_amt)),avg(UnscaledValue(ss_net_paid)),count(1),avg(ss_ext_discount_amt),avg(ss_net_paid),count,sum,count,sum,count] + InputAdapter + Exchange #2 + WholeStageCodegen (1) + HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] + Project [ss_ext_discount_amt,ss_net_paid] + Filter [ss_quantity] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] + ReusedSubquery [mergedValue] #2 + ReusedSubquery [mergedValue] #2 + Subquery #3 + WholeStageCodegen (2) + Project [count(1),avg(ss_ext_discount_amt),avg(ss_net_paid)] + HashAggregate [count,sum,count,sum,count] [count(1),avg(UnscaledValue(ss_ext_discount_amt)),avg(UnscaledValue(ss_net_paid)),count(1),avg(ss_ext_discount_amt),avg(ss_net_paid),count,sum,count,sum,count] + InputAdapter + Exchange #3 + WholeStageCodegen (1) + HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] + Project [ss_ext_discount_amt,ss_net_paid] + Filter [ss_quantity] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] + ReusedSubquery [mergedValue] #3 + ReusedSubquery [mergedValue] #3 + Subquery #4 + WholeStageCodegen (2) + Project [count(1),avg(ss_ext_discount_amt),avg(ss_net_paid)] + HashAggregate [count,sum,count,sum,count] [count(1),avg(UnscaledValue(ss_ext_discount_amt)),avg(UnscaledValue(ss_net_paid)),count(1),avg(ss_ext_discount_amt),avg(ss_net_paid),count,sum,count,sum,count] + InputAdapter + Exchange #4 + WholeStageCodegen (1) + HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] + Project [ss_ext_discount_amt,ss_net_paid] + Filter [ss_quantity] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] + ReusedSubquery [mergedValue] #4 + ReusedSubquery [mergedValue] #4 + Subquery #5 + WholeStageCodegen (2) + Project [count(1),avg(ss_ext_discount_amt),avg(ss_net_paid)] + HashAggregate [count,sum,count,sum,count] [count(1),avg(UnscaledValue(ss_ext_discount_amt)),avg(UnscaledValue(ss_net_paid)),count(1),avg(ss_ext_discount_amt),avg(ss_net_paid),count,sum,count,sum,count] + InputAdapter + Exchange #5 + WholeStageCodegen (1) + HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] + Project [ss_ext_discount_amt,ss_net_paid] + Filter [ss_quantity] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] + ReusedSubquery [mergedValue] #5 + ReusedSubquery [mergedValue] #5 + Filter [r_reason_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.reason [r_reason_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/explain.txt new file mode 100644 index 000000000..c6d4a3c0b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/explain.txt @@ -0,0 +1,292 @@ +== Physical Plan == +* Project (51) ++- * BroadcastNestedLoopJoin Inner BuildRight (50) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (11) + : : : +- * BroadcastHashJoin Inner BuildRight (10) + : : : :- * Project (4) + : : : : +- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : +- BroadcastExchange (9) + : : : +- * Project (8) + : : : +- * Filter (7) + : : : +- * ColumnarToRow (6) + : : : +- CometScan parquet spark_catalog.default.household_demographics (5) + : : +- BroadcastExchange (16) + : : +- * Project (15) + : : +- * Filter (14) + : : +- * ColumnarToRow (13) + : : +- CometScan parquet spark_catalog.default.time_dim (12) + : +- BroadcastExchange (23) + : +- * Project (22) + : +- * Filter (21) + : +- * ColumnarToRow (20) + : +- CometScan parquet spark_catalog.default.web_page (19) + +- BroadcastExchange (49) + +- * HashAggregate (48) + +- Exchange (47) + +- * HashAggregate (46) + +- * Project (45) + +- * BroadcastHashJoin Inner BuildRight (44) + :- * Project (42) + : +- * BroadcastHashJoin Inner BuildRight (41) + : :- * Project (35) + : : +- * BroadcastHashJoin Inner BuildRight (34) + : : :- * Project (32) + : : : +- * Filter (31) + : : : +- * ColumnarToRow (30) + : : : +- CometScan parquet spark_catalog.default.web_sales (29) + : : +- ReusedExchange (33) + : +- BroadcastExchange (40) + : +- * Project (39) + : +- * Filter (38) + : +- * ColumnarToRow (37) + : +- CometScan parquet spark_catalog.default.time_dim (36) + +- ReusedExchange (43) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, ws_sold_date_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_ship_hdemo_sk), IsNotNull(ws_sold_time_sk), IsNotNull(ws_web_page_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, ws_sold_date_sk#4] + +(3) Filter [codegen id : 4] +Input [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, ws_sold_date_sk#4] +Condition : ((isnotnull(ws_ship_hdemo_sk#2) AND isnotnull(ws_sold_time_sk#1)) AND isnotnull(ws_web_page_sk#3)) + +(4) Project [codegen id : 4] +Output [3]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3] +Input [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, ws_sold_date_sk#4] + +(5) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#5, hd_dep_count#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_dep_count), EqualTo(hd_dep_count,6), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [hd_demo_sk#5, hd_dep_count#6] + +(7) Filter [codegen id : 1] +Input [2]: [hd_demo_sk#5, hd_dep_count#6] +Condition : ((isnotnull(hd_dep_count#6) AND (hd_dep_count#6 = 6)) AND isnotnull(hd_demo_sk#5)) + +(8) Project [codegen id : 1] +Output [1]: [hd_demo_sk#5] +Input [2]: [hd_demo_sk#5, hd_dep_count#6] + +(9) BroadcastExchange +Input [1]: [hd_demo_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_ship_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#5] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 4] +Output [2]: [ws_sold_time_sk#1, ws_web_page_sk#3] +Input [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, hd_demo_sk#5] + +(12) Scan parquet spark_catalog.default.time_dim +Output [2]: [t_time_sk#7, t_hour#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), GreaterThanOrEqual(t_hour,8), LessThanOrEqual(t_hour,9), IsNotNull(t_time_sk)] +ReadSchema: struct + +(13) ColumnarToRow [codegen id : 2] +Input [2]: [t_time_sk#7, t_hour#8] + +(14) Filter [codegen id : 2] +Input [2]: [t_time_sk#7, t_hour#8] +Condition : (((isnotnull(t_hour#8) AND (t_hour#8 >= 8)) AND (t_hour#8 <= 9)) AND isnotnull(t_time_sk#7)) + +(15) Project [codegen id : 2] +Output [1]: [t_time_sk#7] +Input [2]: [t_time_sk#7, t_hour#8] + +(16) BroadcastExchange +Input [1]: [t_time_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_time_sk#1] +Right keys [1]: [t_time_sk#7] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [1]: [ws_web_page_sk#3] +Input [3]: [ws_sold_time_sk#1, ws_web_page_sk#3, t_time_sk#7] + +(19) Scan parquet spark_catalog.default.web_page +Output [2]: [wp_web_page_sk#9, wp_char_count#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_page] +PushedFilters: [IsNotNull(wp_char_count), GreaterThanOrEqual(wp_char_count,5000), LessThanOrEqual(wp_char_count,5200), IsNotNull(wp_web_page_sk)] +ReadSchema: struct + +(20) ColumnarToRow [codegen id : 3] +Input [2]: [wp_web_page_sk#9, wp_char_count#10] + +(21) Filter [codegen id : 3] +Input [2]: [wp_web_page_sk#9, wp_char_count#10] +Condition : (((isnotnull(wp_char_count#10) AND (wp_char_count#10 >= 5000)) AND (wp_char_count#10 <= 5200)) AND isnotnull(wp_web_page_sk#9)) + +(22) Project [codegen id : 3] +Output [1]: [wp_web_page_sk#9] +Input [2]: [wp_web_page_sk#9, wp_char_count#10] + +(23) BroadcastExchange +Input [1]: [wp_web_page_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_web_page_sk#3] +Right keys [1]: [wp_web_page_sk#9] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 4] +Output: [] +Input [2]: [ws_web_page_sk#3, wp_web_page_sk#9] + +(26) HashAggregate [codegen id : 4] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#11] +Results [1]: [count#12] + +(27) Exchange +Input [1]: [count#12] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 10] +Input [1]: [count#12] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#13] +Results [1]: [count(1)#13 AS amc#14] + +(29) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, ws_sold_date_sk#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_ship_hdemo_sk), IsNotNull(ws_sold_time_sk), IsNotNull(ws_web_page_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 8] +Input [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, ws_sold_date_sk#18] + +(31) Filter [codegen id : 8] +Input [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, ws_sold_date_sk#18] +Condition : ((isnotnull(ws_ship_hdemo_sk#16) AND isnotnull(ws_sold_time_sk#15)) AND isnotnull(ws_web_page_sk#17)) + +(32) Project [codegen id : 8] +Output [3]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17] +Input [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, ws_sold_date_sk#18] + +(33) ReusedExchange [Reuses operator id: 9] +Output [1]: [hd_demo_sk#19] + +(34) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ws_ship_hdemo_sk#16] +Right keys [1]: [hd_demo_sk#19] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 8] +Output [2]: [ws_sold_time_sk#15, ws_web_page_sk#17] +Input [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, hd_demo_sk#19] + +(36) Scan parquet spark_catalog.default.time_dim +Output [2]: [t_time_sk#20, t_hour#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), GreaterThanOrEqual(t_hour,19), LessThanOrEqual(t_hour,20), IsNotNull(t_time_sk)] +ReadSchema: struct + +(37) ColumnarToRow [codegen id : 6] +Input [2]: [t_time_sk#20, t_hour#21] + +(38) Filter [codegen id : 6] +Input [2]: [t_time_sk#20, t_hour#21] +Condition : (((isnotnull(t_hour#21) AND (t_hour#21 >= 19)) AND (t_hour#21 <= 20)) AND isnotnull(t_time_sk#20)) + +(39) Project [codegen id : 6] +Output [1]: [t_time_sk#20] +Input [2]: [t_time_sk#20, t_hour#21] + +(40) BroadcastExchange +Input [1]: [t_time_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(41) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ws_sold_time_sk#15] +Right keys [1]: [t_time_sk#20] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 8] +Output [1]: [ws_web_page_sk#17] +Input [3]: [ws_sold_time_sk#15, ws_web_page_sk#17, t_time_sk#20] + +(43) ReusedExchange [Reuses operator id: 23] +Output [1]: [wp_web_page_sk#22] + +(44) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ws_web_page_sk#17] +Right keys [1]: [wp_web_page_sk#22] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 8] +Output: [] +Input [2]: [ws_web_page_sk#17, wp_web_page_sk#22] + +(46) HashAggregate [codegen id : 8] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#23] +Results [1]: [count#24] + +(47) Exchange +Input [1]: [count#24] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] + +(48) HashAggregate [codegen id : 9] +Input [1]: [count#24] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#25] +Results [1]: [count(1)#25 AS pmc#26] + +(49) BroadcastExchange +Input [1]: [pmc#26] +Arguments: IdentityBroadcastMode, [plan_id=7] + +(50) BroadcastNestedLoopJoin [codegen id : 10] +Join type: Inner +Join condition: None + +(51) Project [codegen id : 10] +Output [1]: [(cast(amc#14 as decimal(15,4)) / cast(pmc#26 as decimal(15,4))) AS am_pm_ratio#27] +Input [2]: [amc#14, pmc#26] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/simplified.txt new file mode 100644 index 000000000..3f9582bb0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/simplified.txt @@ -0,0 +1,74 @@ +WholeStageCodegen (10) + Project [amc,pmc] + BroadcastNestedLoopJoin + HashAggregate [count] [count(1),amc,count] + InputAdapter + Exchange #1 + WholeStageCodegen (4) + HashAggregate [count,count] + Project + BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] + Project [ws_web_page_sk] + BroadcastHashJoin [ws_sold_time_sk,t_time_sk] + Project [ws_sold_time_sk,ws_web_page_sk] + BroadcastHashJoin [ws_ship_hdemo_sk,hd_demo_sk] + Project [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk] + Filter [ws_ship_hdemo_sk,ws_sold_time_sk,ws_web_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk,ws_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Project [hd_demo_sk] + Filter [hd_dep_count,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [t_time_sk] + Filter [t_hour,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Project [wp_web_page_sk] + Filter [wp_char_count,wp_web_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_page [wp_web_page_sk,wp_char_count] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (9) + HashAggregate [count] [count(1),pmc,count] + InputAdapter + Exchange #6 + WholeStageCodegen (8) + HashAggregate [count,count] + Project + BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] + Project [ws_web_page_sk] + BroadcastHashJoin [ws_sold_time_sk,t_time_sk] + Project [ws_sold_time_sk,ws_web_page_sk] + BroadcastHashJoin [ws_ship_hdemo_sk,hd_demo_sk] + Project [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk] + Filter [ws_ship_hdemo_sk,ws_sold_time_sk,ws_web_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk,ws_sold_date_sk] + InputAdapter + ReusedExchange [hd_demo_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + Project [t_time_sk] + Filter [t_hour,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour] + InputAdapter + ReusedExchange [wp_web_page_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/explain.txt new file mode 100644 index 000000000..521373bf7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/explain.txt @@ -0,0 +1,281 @@ +== Physical Plan == +* Sort (43) ++- Exchange (42) + +- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (31) + : +- * BroadcastHashJoin Inner BuildRight (30) + : :- * Project (25) + : : +- * BroadcastHashJoin Inner BuildRight (24) + : : :- * Project (18) + : : : +- * BroadcastHashJoin Inner BuildRight (17) + : : : :- * Project (12) + : : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : : :- * Project (9) + : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : :- * Filter (3) + : : : : : : +- * ColumnarToRow (2) + : : : : : : +- CometScan parquet spark_catalog.default.call_center (1) + : : : : : +- BroadcastExchange (7) + : : : : : +- * Filter (6) + : : : : : +- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (4) + : : : : +- ReusedExchange (10) + : : : +- BroadcastExchange (16) + : : : +- * Filter (15) + : : : +- * ColumnarToRow (14) + : : : +- CometScan parquet spark_catalog.default.customer (13) + : : +- BroadcastExchange (23) + : : +- * Project (22) + : : +- * Filter (21) + : : +- * ColumnarToRow (20) + : : +- CometScan parquet spark_catalog.default.customer_address (19) + : +- BroadcastExchange (29) + : +- * Filter (28) + : +- * ColumnarToRow (27) + : +- CometScan parquet spark_catalog.default.customer_demographics (26) + +- BroadcastExchange (36) + +- * Project (35) + +- * Filter (34) + +- * ColumnarToRow (33) + +- CometScan parquet spark_catalog.default.household_demographics (32) + + +(1) Scan parquet spark_catalog.default.call_center +Output [4]: [cc_call_center_sk#1, cc_call_center_id#2, cc_name#3, cc_manager#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/call_center] +PushedFilters: [IsNotNull(cc_call_center_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 7] +Input [4]: [cc_call_center_sk#1, cc_call_center_id#2, cc_name#3, cc_manager#4] + +(3) Filter [codegen id : 7] +Input [4]: [cc_call_center_sk#1, cc_call_center_id#2, cc_name#3, cc_manager#4] +Condition : isnotnull(cc_call_center_sk#1) + +(4) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#8), dynamicpruningexpression(cr_returned_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(cr_call_center_sk), IsNotNull(cr_returning_customer_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] + +(6) Filter [codegen id : 1] +Input [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] +Condition : (isnotnull(cr_call_center_sk#6) AND isnotnull(cr_returning_customer_sk#5)) + +(7) BroadcastExchange +Input [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cc_call_center_sk#1] +Right keys [1]: [cr_call_center_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 7] +Output [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_returning_customer_sk#5, cr_net_loss#7, cr_returned_date_sk#8] +Input [8]: [cc_call_center_sk#1, cc_call_center_id#2, cc_name#3, cc_manager#4, cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] + +(10) ReusedExchange [Reuses operator id: 48] +Output [1]: [d_date_sk#10] + +(11) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cr_returned_date_sk#8] +Right keys [1]: [d_date_sk#10] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 7] +Output [5]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_returning_customer_sk#5, cr_net_loss#7] +Input [7]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_returning_customer_sk#5, cr_net_loss#7, cr_returned_date_sk#8, d_date_sk#10] + +(13) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] + +(15) Filter [codegen id : 3] +Input [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] +Condition : (((isnotnull(c_customer_sk#11) AND isnotnull(c_current_addr_sk#14)) AND isnotnull(c_current_cdemo_sk#12)) AND isnotnull(c_current_hdemo_sk#13)) + +(16) BroadcastExchange +Input [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cr_returning_customer_sk#5] +Right keys [1]: [c_customer_sk#11] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 7] +Output [7]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] +Input [9]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_returning_customer_sk#5, cr_net_loss#7, c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] + +(19) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#15, ca_gmt_offset#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-7.00), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(20) ColumnarToRow [codegen id : 4] +Input [2]: [ca_address_sk#15, ca_gmt_offset#16] + +(21) Filter [codegen id : 4] +Input [2]: [ca_address_sk#15, ca_gmt_offset#16] +Condition : ((isnotnull(ca_gmt_offset#16) AND (ca_gmt_offset#16 = -7.00)) AND isnotnull(ca_address_sk#15)) + +(22) Project [codegen id : 4] +Output [1]: [ca_address_sk#15] +Input [2]: [ca_address_sk#15, ca_gmt_offset#16] + +(23) BroadcastExchange +Input [1]: [ca_address_sk#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_addr_sk#14] +Right keys [1]: [ca_address_sk#15] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 7] +Output [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_cdemo_sk#12, c_current_hdemo_sk#13] +Input [8]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14, ca_address_sk#15] + +(26) Scan parquet spark_catalog.default.customer_demographics +Output [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,Unknown )),And(EqualTo(cd_marital_status,W),EqualTo(cd_education_status,Advanced Degree ))), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(27) ColumnarToRow [codegen id : 5] +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] + +(28) Filter [codegen id : 5] +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Condition : ((((cd_marital_status#18 = M) AND (cd_education_status#19 = Unknown )) OR ((cd_marital_status#18 = W) AND (cd_education_status#19 = Advanced Degree ))) AND isnotnull(cd_demo_sk#17)) + +(29) BroadcastExchange +Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_cdemo_sk#12] +Right keys [1]: [cd_demo_sk#17] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 7] +Output [7]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_hdemo_sk#13, cd_marital_status#18, cd_education_status#19] +Input [9]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_cdemo_sk#12, c_current_hdemo_sk#13, cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] + +(32) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#20, hd_buy_potential#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_buy_potential), StringStartsWith(hd_buy_potential,Unknown), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(33) ColumnarToRow [codegen id : 6] +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] + +(34) Filter [codegen id : 6] +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Condition : ((isnotnull(hd_buy_potential#21) AND StartsWith(hd_buy_potential#21, Unknown)) AND isnotnull(hd_demo_sk#20)) + +(35) Project [codegen id : 6] +Output [1]: [hd_demo_sk#20] +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] + +(36) BroadcastExchange +Input [1]: [hd_demo_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_hdemo_sk#13] +Right keys [1]: [hd_demo_sk#20] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 7] +Output [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, cd_marital_status#18, cd_education_status#19] +Input [8]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, c_current_hdemo_sk#13, cd_marital_status#18, cd_education_status#19, hd_demo_sk#20] + +(39) HashAggregate [codegen id : 7] +Input [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cr_net_loss#7, cd_marital_status#18, cd_education_status#19] +Keys [5]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19] +Functions [1]: [partial_sum(UnscaledValue(cr_net_loss#7))] +Aggregate Attributes [1]: [sum#22] +Results [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19, sum#23] + +(40) Exchange +Input [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19, sum#23] +Arguments: hashpartitioning(cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 8] +Input [6]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19, sum#23] +Keys [5]: [cc_call_center_id#2, cc_name#3, cc_manager#4, cd_marital_status#18, cd_education_status#19] +Functions [1]: [sum(UnscaledValue(cr_net_loss#7))] +Aggregate Attributes [1]: [sum(UnscaledValue(cr_net_loss#7))#24] +Results [4]: [cc_call_center_id#2 AS Call_Center#25, cc_name#3 AS Call_Center_Name#26, cc_manager#4 AS Manager#27, MakeDecimal(sum(UnscaledValue(cr_net_loss#7))#24,17,2) AS Returns_Loss#28] + +(42) Exchange +Input [4]: [Call_Center#25, Call_Center_Name#26, Manager#27, Returns_Loss#28] +Arguments: rangepartitioning(Returns_Loss#28 DESC NULLS LAST, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(43) Sort [codegen id : 9] +Input [4]: [Call_Center#25, Call_Center_Name#26, Manager#27, Returns_Loss#28] +Arguments: [Returns_Loss#28 DESC NULLS LAST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = cr_returned_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (48) ++- * Project (47) + +- * Filter (46) + +- * ColumnarToRow (45) + +- CometScan parquet spark_catalog.default.date_dim (44) + + +(44) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#10, d_year#29, d_moy#30] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,11), IsNotNull(d_date_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#29, d_moy#30] + +(46) Filter [codegen id : 1] +Input [3]: [d_date_sk#10, d_year#29, d_moy#30] +Condition : ((((isnotnull(d_year#29) AND isnotnull(d_moy#30)) AND (d_year#29 = 1998)) AND (d_moy#30 = 11)) AND isnotnull(d_date_sk#10)) + +(47) Project [codegen id : 1] +Output [1]: [d_date_sk#10] +Input [3]: [d_date_sk#10, d_year#29, d_moy#30] + +(48) BroadcastExchange +Input [1]: [d_date_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/simplified.txt new file mode 100644 index 000000000..d40b04b59 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/simplified.txt @@ -0,0 +1,73 @@ +WholeStageCodegen (9) + Sort [Returns_Loss] + InputAdapter + Exchange [Returns_Loss] #1 + WholeStageCodegen (8) + HashAggregate [cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status,sum] [sum(UnscaledValue(cr_net_loss)),Call_Center,Call_Center_Name,Manager,Returns_Loss,sum] + InputAdapter + Exchange [cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status] #2 + WholeStageCodegen (7) + HashAggregate [cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status,cr_net_loss] [sum,sum] + Project [cc_call_center_id,cc_name,cc_manager,cr_net_loss,cd_marital_status,cd_education_status] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [cc_call_center_id,cc_name,cc_manager,cr_net_loss,c_current_hdemo_sk,cd_marital_status,cd_education_status] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cc_call_center_id,cc_name,cc_manager,cr_net_loss,c_current_cdemo_sk,c_current_hdemo_sk] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cc_call_center_id,cc_name,cc_manager,cr_net_loss,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] + BroadcastHashJoin [cr_returning_customer_sk,c_customer_sk] + Project [cc_call_center_id,cc_name,cc_manager,cr_returning_customer_sk,cr_net_loss] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + Project [cc_call_center_id,cc_name,cc_manager,cr_returning_customer_sk,cr_net_loss,cr_returned_date_sk] + BroadcastHashJoin [cc_call_center_sk,cr_call_center_sk] + Filter [cc_call_center_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_call_center_id,cc_name,cc_manager] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [cr_call_center_sk,cr_returning_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_returning_customer_sk,cr_call_center_sk,cr_net_loss,cr_returned_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [c_customer_sk,c_current_addr_sk,c_current_cdemo_sk,c_current_hdemo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + Project [ca_address_sk] + Filter [ca_gmt_offset,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (5) + Filter [cd_marital_status,cd_education_status,cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (6) + Project [hd_demo_sk] + Filter [hd_buy_potential,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/explain.txt new file mode 100644 index 000000000..204b23130 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/explain.txt @@ -0,0 +1,209 @@ +== Physical Plan == +* HashAggregate (29) ++- Exchange (28) + +- * HashAggregate (27) + +- * Project (26) + +- * BroadcastHashJoin Inner BuildRight (25) + :- * Project (23) + : +- * BroadcastHashJoin Inner BuildRight (22) + : :- * Project (10) + : : +- * BroadcastHashJoin Inner BuildRight (9) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : +- BroadcastExchange (8) + : : +- * Project (7) + : : +- * Filter (6) + : : +- * ColumnarToRow (5) + : : +- CometScan parquet spark_catalog.default.item (4) + : +- BroadcastExchange (21) + : +- * Filter (20) + : +- * HashAggregate (19) + : +- Exchange (18) + : +- * HashAggregate (17) + : +- * Project (16) + : +- * BroadcastHashJoin Inner BuildRight (15) + : :- * Filter (13) + : : +- * ColumnarToRow (12) + : : +- CometScan parquet spark_catalog.default.web_sales (11) + : +- ReusedExchange (14) + +- ReusedExchange (24) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_ext_discount_amt#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_ext_discount_amt)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 6] +Input [3]: [ws_item_sk#1, ws_ext_discount_amt#2, ws_sold_date_sk#3] + +(3) Filter [codegen id : 6] +Input [3]: [ws_item_sk#1, ws_ext_discount_amt#2, ws_sold_date_sk#3] +Condition : (isnotnull(ws_item_sk#1) AND isnotnull(ws_ext_discount_amt#2)) + +(4) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#5, i_manufact_id#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_manufact_id), EqualTo(i_manufact_id,350), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [i_item_sk#5, i_manufact_id#6] + +(6) Filter [codegen id : 1] +Input [2]: [i_item_sk#5, i_manufact_id#6] +Condition : ((isnotnull(i_manufact_id#6) AND (i_manufact_id#6 = 350)) AND isnotnull(i_item_sk#5)) + +(7) Project [codegen id : 1] +Output [1]: [i_item_sk#5] +Input [2]: [i_item_sk#5, i_manufact_id#6] + +(8) BroadcastExchange +Input [1]: [i_item_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 6] +Output [3]: [ws_ext_discount_amt#2, ws_sold_date_sk#3, i_item_sk#5] +Input [4]: [ws_item_sk#1, ws_ext_discount_amt#2, ws_sold_date_sk#3, i_item_sk#5] + +(11) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#7, ws_ext_discount_amt#8, ws_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#9), dynamicpruningexpression(ws_sold_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 3] +Input [3]: [ws_item_sk#7, ws_ext_discount_amt#8, ws_sold_date_sk#9] + +(13) Filter [codegen id : 3] +Input [3]: [ws_item_sk#7, ws_ext_discount_amt#8, ws_sold_date_sk#9] +Condition : isnotnull(ws_item_sk#7) + +(14) ReusedExchange [Reuses operator id: 34] +Output [1]: [d_date_sk#11] + +(15) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 3] +Output [2]: [ws_item_sk#7, ws_ext_discount_amt#8] +Input [4]: [ws_item_sk#7, ws_ext_discount_amt#8, ws_sold_date_sk#9, d_date_sk#11] + +(17) HashAggregate [codegen id : 3] +Input [2]: [ws_item_sk#7, ws_ext_discount_amt#8] +Keys [1]: [ws_item_sk#7] +Functions [1]: [partial_avg(UnscaledValue(ws_ext_discount_amt#8))] +Aggregate Attributes [2]: [sum#12, count#13] +Results [3]: [ws_item_sk#7, sum#14, count#15] + +(18) Exchange +Input [3]: [ws_item_sk#7, sum#14, count#15] +Arguments: hashpartitioning(ws_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(19) HashAggregate [codegen id : 4] +Input [3]: [ws_item_sk#7, sum#14, count#15] +Keys [1]: [ws_item_sk#7] +Functions [1]: [avg(UnscaledValue(ws_ext_discount_amt#8))] +Aggregate Attributes [1]: [avg(UnscaledValue(ws_ext_discount_amt#8))#16] +Results [2]: [(1.3 * cast((avg(UnscaledValue(ws_ext_discount_amt#8))#16 / 100.0) as decimal(11,6))) AS (1.3 * avg(ws_ext_discount_amt))#17, ws_item_sk#7] + +(20) Filter [codegen id : 4] +Input [2]: [(1.3 * avg(ws_ext_discount_amt))#17, ws_item_sk#7] +Condition : isnotnull((1.3 * avg(ws_ext_discount_amt))#17) + +(21) BroadcastExchange +Input [2]: [(1.3 * avg(ws_ext_discount_amt))#17, ws_item_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, true] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [i_item_sk#5] +Right keys [1]: [ws_item_sk#7] +Join type: Inner +Join condition: (cast(ws_ext_discount_amt#2 as decimal(14,7)) > (1.3 * avg(ws_ext_discount_amt))#17) + +(23) Project [codegen id : 6] +Output [2]: [ws_ext_discount_amt#2, ws_sold_date_sk#3] +Input [5]: [ws_ext_discount_amt#2, ws_sold_date_sk#3, i_item_sk#5, (1.3 * avg(ws_ext_discount_amt))#17, ws_item_sk#7] + +(24) ReusedExchange [Reuses operator id: 34] +Output [1]: [d_date_sk#18] + +(25) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#18] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 6] +Output [1]: [ws_ext_discount_amt#2] +Input [3]: [ws_ext_discount_amt#2, ws_sold_date_sk#3, d_date_sk#18] + +(27) HashAggregate [codegen id : 6] +Input [1]: [ws_ext_discount_amt#2] +Keys: [] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_discount_amt#2))] +Aggregate Attributes [1]: [sum#19] +Results [1]: [sum#20] + +(28) Exchange +Input [1]: [sum#20] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(29) HashAggregate [codegen id : 7] +Input [1]: [sum#20] +Keys: [] +Functions [1]: [sum(UnscaledValue(ws_ext_discount_amt#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_discount_amt#2))#21] +Results [1]: [MakeDecimal(sum(UnscaledValue(ws_ext_discount_amt#2))#21,17,2) AS Excess Discount Amount #22] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (34) ++- * Project (33) + +- * Filter (32) + +- * ColumnarToRow (31) + +- CometScan parquet spark_catalog.default.date_dim (30) + + +(30) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#18, d_date#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-01-27), LessThanOrEqual(d_date,2000-04-26), IsNotNull(d_date_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#18, d_date#23] + +(32) Filter [codegen id : 1] +Input [2]: [d_date_sk#18, d_date#23] +Condition : (((isnotnull(d_date#23) AND (d_date#23 >= 2000-01-27)) AND (d_date#23 <= 2000-04-26)) AND isnotnull(d_date_sk#18)) + +(33) Project [codegen id : 1] +Output [1]: [d_date_sk#18] +Input [2]: [d_date_sk#18, d_date#23] + +(34) BroadcastExchange +Input [1]: [d_date_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#9 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/simplified.txt new file mode 100644 index 000000000..33d262f07 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/simplified.txt @@ -0,0 +1,52 @@ +WholeStageCodegen (7) + HashAggregate [sum] [sum(UnscaledValue(ws_ext_discount_amt)),Excess Discount Amount ,sum] + InputAdapter + Exchange #1 + WholeStageCodegen (6) + HashAggregate [ws_ext_discount_amt] [sum,sum] + Project [ws_ext_discount_amt] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_ext_discount_amt,ws_sold_date_sk] + BroadcastHashJoin [i_item_sk,ws_item_sk,ws_ext_discount_amt,(1.3 * avg(ws_ext_discount_amt))] + Project [ws_ext_discount_amt,ws_sold_date_sk,i_item_sk] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk,ws_ext_discount_amt] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_discount_amt,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [i_item_sk] + Filter [i_manufact_id,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_manufact_id] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Filter [(1.3 * avg(ws_ext_discount_amt))] + HashAggregate [ws_item_sk,sum,count] [avg(UnscaledValue(ws_ext_discount_amt)),(1.3 * avg(ws_ext_discount_amt)),sum,count] + InputAdapter + Exchange [ws_item_sk] #5 + WholeStageCodegen (3) + HashAggregate [ws_item_sk,ws_ext_discount_amt] [sum,count,sum,count] + Project [ws_item_sk,ws_ext_discount_amt] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_discount_amt,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/explain.txt new file mode 100644 index 000000000..121f25701 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/explain.txt @@ -0,0 +1,138 @@ +== Physical Plan == +TakeOrderedAndProject (24) ++- * HashAggregate (23) + +- Exchange (22) + +- * HashAggregate (21) + +- * Project (20) + +- * BroadcastHashJoin Inner BuildRight (19) + :- * Project (13) + : +- * SortMergeJoin Inner (12) + : :- * Sort (5) + : : +- Exchange (4) + : : +- * Project (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.store_sales (1) + : +- * Sort (11) + : +- Exchange (10) + : +- * Project (9) + : +- * Filter (8) + : +- * ColumnarToRow (7) + : +- CometScan parquet spark_catalog.default.store_returns (6) + +- BroadcastExchange (18) + +- * Project (17) + +- * Filter (16) + +- * ColumnarToRow (15) + +- CometScan parquet spark_catalog.default.reason (14) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5, ss_sold_date_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5, ss_sold_date_sk#6] + +(3) Project [codegen id : 1] +Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5, ss_sold_date_sk#6] + +(4) Exchange +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] +Arguments: hashpartitioning(ss_item_sk#1, ss_ticket_number#3, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] +Arguments: [ss_item_sk#1 ASC NULLS FIRST, ss_ticket_number#3 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number), IsNotNull(sr_reason_sk)] +ReadSchema: struct + +(7) ColumnarToRow [codegen id : 3] +Input [5]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11] + +(8) Filter [codegen id : 3] +Input [5]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11] +Condition : ((isnotnull(sr_item_sk#7) AND isnotnull(sr_ticket_number#9)) AND isnotnull(sr_reason_sk#8)) + +(9) Project [codegen id : 3] +Output [4]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] +Input [5]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11] + +(10) Exchange +Input [4]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] +Arguments: hashpartitioning(sr_item_sk#7, sr_ticket_number#9, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [4]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] +Arguments: [sr_item_sk#7 ASC NULLS FIRST, sr_ticket_number#9 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 6] +Left keys [2]: [ss_item_sk#1, ss_ticket_number#3] +Right keys [2]: [sr_item_sk#7, sr_ticket_number#9] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 6] +Output [5]: [ss_customer_sk#2, ss_quantity#4, ss_sales_price#5, sr_reason_sk#8, sr_return_quantity#10] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5, sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] + +(14) Scan parquet spark_catalog.default.reason +Output [2]: [r_reason_sk#12, r_reason_desc#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/reason] +PushedFilters: [IsNotNull(r_reason_desc), EqualTo(r_reason_desc,reason 28 ), IsNotNull(r_reason_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 5] +Input [2]: [r_reason_sk#12, r_reason_desc#13] + +(16) Filter [codegen id : 5] +Input [2]: [r_reason_sk#12, r_reason_desc#13] +Condition : ((isnotnull(r_reason_desc#13) AND (r_reason_desc#13 = reason 28 )) AND isnotnull(r_reason_sk#12)) + +(17) Project [codegen id : 5] +Output [1]: [r_reason_sk#12] +Input [2]: [r_reason_sk#12, r_reason_desc#13] + +(18) BroadcastExchange +Input [1]: [r_reason_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(19) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sr_reason_sk#8] +Right keys [1]: [r_reason_sk#12] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 6] +Output [2]: [ss_customer_sk#2, CASE WHEN isnotnull(sr_return_quantity#10) THEN (cast((ss_quantity#4 - sr_return_quantity#10) as decimal(10,0)) * ss_sales_price#5) ELSE (cast(ss_quantity#4 as decimal(10,0)) * ss_sales_price#5) END AS act_sales#14] +Input [6]: [ss_customer_sk#2, ss_quantity#4, ss_sales_price#5, sr_reason_sk#8, sr_return_quantity#10, r_reason_sk#12] + +(21) HashAggregate [codegen id : 6] +Input [2]: [ss_customer_sk#2, act_sales#14] +Keys [1]: [ss_customer_sk#2] +Functions [1]: [partial_sum(act_sales#14)] +Aggregate Attributes [2]: [sum#15, isEmpty#16] +Results [3]: [ss_customer_sk#2, sum#17, isEmpty#18] + +(22) Exchange +Input [3]: [ss_customer_sk#2, sum#17, isEmpty#18] +Arguments: hashpartitioning(ss_customer_sk#2, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) HashAggregate [codegen id : 7] +Input [3]: [ss_customer_sk#2, sum#17, isEmpty#18] +Keys [1]: [ss_customer_sk#2] +Functions [1]: [sum(act_sales#14)] +Aggregate Attributes [1]: [sum(act_sales#14)#19] +Results [2]: [ss_customer_sk#2, sum(act_sales#14)#19 AS sumsales#20] + +(24) TakeOrderedAndProject +Input [2]: [ss_customer_sk#2, sumsales#20] +Arguments: 100, [sumsales#20 ASC NULLS FIRST, ss_customer_sk#2 ASC NULLS FIRST], [ss_customer_sk#2, sumsales#20] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/simplified.txt new file mode 100644 index 000000000..775e14725 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/simplified.txt @@ -0,0 +1,40 @@ +TakeOrderedAndProject [sumsales,ss_customer_sk] + WholeStageCodegen (7) + HashAggregate [ss_customer_sk,sum,isEmpty] [sum(act_sales),sumsales,sum,isEmpty] + InputAdapter + Exchange [ss_customer_sk] #1 + WholeStageCodegen (6) + HashAggregate [ss_customer_sk,act_sales] [sum,isEmpty,sum,isEmpty] + Project [ss_customer_sk,sr_return_quantity,ss_quantity,ss_sales_price] + BroadcastHashJoin [sr_reason_sk,r_reason_sk] + Project [ss_customer_sk,ss_quantity,ss_sales_price,sr_reason_sk,sr_return_quantity] + SortMergeJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + InputAdapter + WholeStageCodegen (2) + Sort [ss_item_sk,ss_ticket_number] + InputAdapter + Exchange [ss_item_sk,ss_ticket_number] #2 + WholeStageCodegen (1) + Project [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_sales_price] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_sales_price,ss_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [sr_item_sk,sr_ticket_number] + InputAdapter + Exchange [sr_item_sk,sr_ticket_number] #3 + WholeStageCodegen (3) + Project [sr_item_sk,sr_reason_sk,sr_ticket_number,sr_return_quantity] + Filter [sr_item_sk,sr_ticket_number,sr_reason_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_reason_sk,sr_ticket_number,sr_return_quantity,sr_returned_date_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (5) + Project [r_reason_sk] + Filter [r_reason_desc,r_reason_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.reason [r_reason_sk,r_reason_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/explain.txt new file mode 100644 index 000000000..180e7e033 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/explain.txt @@ -0,0 +1,260 @@ +== Physical Plan == +* HashAggregate (45) ++- Exchange (44) + +- * HashAggregate (43) + +- * HashAggregate (42) + +- * HashAggregate (41) + +- * Project (40) + +- * BroadcastHashJoin Inner BuildRight (39) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (26) + : : +- * BroadcastHashJoin Inner BuildRight (25) + : : :- * SortMergeJoin LeftAnti (19) + : : : :- * Project (13) + : : : : +- * SortMergeJoin LeftSemi (12) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * Project (4) + : : : : : +- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : +- * Sort (11) + : : : : +- Exchange (10) + : : : : +- * Project (9) + : : : : +- * ColumnarToRow (8) + : : : : +- CometScan parquet spark_catalog.default.web_sales (7) + : : : +- * Sort (18) + : : : +- Exchange (17) + : : : +- * Project (16) + : : : +- * ColumnarToRow (15) + : : : +- CometScan parquet spark_catalog.default.web_returns (14) + : : +- BroadcastExchange (24) + : : +- * Project (23) + : : +- * Filter (22) + : : +- * ColumnarToRow (21) + : : +- CometScan parquet spark_catalog.default.date_dim (20) + : +- BroadcastExchange (31) + : +- * Project (30) + : +- * Filter (29) + : +- * ColumnarToRow (28) + : +- CometScan parquet spark_catalog.default.customer_address (27) + +- BroadcastExchange (38) + +- * Project (37) + +- * Filter (36) + +- * ColumnarToRow (35) + +- CometScan parquet spark_catalog.default.web_site (34) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [8]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ws_sold_date_sk#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_ship_date_sk), IsNotNull(ws_ship_addr_sk), IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [8]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ws_sold_date_sk#8] + +(3) Filter [codegen id : 1] +Input [8]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ws_sold_date_sk#8] +Condition : ((isnotnull(ws_ship_date_sk#1) AND isnotnull(ws_ship_addr_sk#2)) AND isnotnull(ws_web_site_sk#3)) + +(4) Project [codegen id : 1] +Output [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Input [8]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ws_sold_date_sk#8] + +(5) Exchange +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Arguments: hashpartitioning(ws_order_number#5, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Arguments: [ws_order_number#5 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_warehouse_sk#9, ws_order_number#10, ws_sold_date_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 3] +Input [3]: [ws_warehouse_sk#9, ws_order_number#10, ws_sold_date_sk#11] + +(9) Project [codegen id : 3] +Output [2]: [ws_warehouse_sk#9, ws_order_number#10] +Input [3]: [ws_warehouse_sk#9, ws_order_number#10, ws_sold_date_sk#11] + +(10) Exchange +Input [2]: [ws_warehouse_sk#9, ws_order_number#10] +Arguments: hashpartitioning(ws_order_number#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [2]: [ws_warehouse_sk#9, ws_order_number#10] +Arguments: [ws_order_number#10 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 5] +Left keys [1]: [ws_order_number#5] +Right keys [1]: [ws_order_number#10] +Join type: LeftSemi +Join condition: NOT (ws_warehouse_sk#4 = ws_warehouse_sk#9) + +(13) Project [codegen id : 5] +Output [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] + +(14) Scan parquet spark_catalog.default.web_returns +Output [2]: [wr_order_number#12, wr_returned_date_sk#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 6] +Input [2]: [wr_order_number#12, wr_returned_date_sk#13] + +(16) Project [codegen id : 6] +Output [1]: [wr_order_number#12] +Input [2]: [wr_order_number#12, wr_returned_date_sk#13] + +(17) Exchange +Input [1]: [wr_order_number#12] +Arguments: hashpartitioning(wr_order_number#12, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(18) Sort [codegen id : 7] +Input [1]: [wr_order_number#12] +Arguments: [wr_order_number#12 ASC NULLS FIRST], false, 0 + +(19) SortMergeJoin [codegen id : 11] +Left keys [1]: [ws_order_number#5] +Right keys [1]: [wr_order_number#12] +Join type: LeftAnti +Join condition: None + +(20) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_date#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-01), LessThanOrEqual(d_date,1999-04-02), IsNotNull(d_date_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 8] +Input [2]: [d_date_sk#14, d_date#15] + +(22) Filter [codegen id : 8] +Input [2]: [d_date_sk#14, d_date#15] +Condition : (((isnotnull(d_date#15) AND (d_date#15 >= 1999-02-01)) AND (d_date#15 <= 1999-04-02)) AND isnotnull(d_date_sk#14)) + +(23) Project [codegen id : 8] +Output [1]: [d_date_sk#14] +Input [2]: [d_date_sk#14, d_date#15] + +(24) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(25) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ws_ship_date_sk#1] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 11] +Output [5]: [ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, d_date_sk#14] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#16, ca_state#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,IL), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) ColumnarToRow [codegen id : 9] +Input [2]: [ca_address_sk#16, ca_state#17] + +(29) Filter [codegen id : 9] +Input [2]: [ca_address_sk#16, ca_state#17] +Condition : ((isnotnull(ca_state#17) AND (ca_state#17 = IL)) AND isnotnull(ca_address_sk#16)) + +(30) Project [codegen id : 9] +Output [1]: [ca_address_sk#16] +Input [2]: [ca_address_sk#16, ca_state#17] + +(31) BroadcastExchange +Input [1]: [ca_address_sk#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ws_ship_addr_sk#2] +Right keys [1]: [ca_address_sk#16] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 11] +Output [4]: [ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Input [6]: [ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ca_address_sk#16] + +(34) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#18, web_company_name#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_company_name), EqualTo(web_company_name,pri ), IsNotNull(web_site_sk)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 10] +Input [2]: [web_site_sk#18, web_company_name#19] + +(36) Filter [codegen id : 10] +Input [2]: [web_site_sk#18, web_company_name#19] +Condition : ((isnotnull(web_company_name#19) AND (web_company_name#19 = pri )) AND isnotnull(web_site_sk#18)) + +(37) Project [codegen id : 10] +Output [1]: [web_site_sk#18] +Input [2]: [web_site_sk#18, web_company_name#19] + +(38) BroadcastExchange +Input [1]: [web_site_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +(39) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ws_web_site_sk#3] +Right keys [1]: [web_site_sk#18] +Join type: Inner +Join condition: None + +(40) Project [codegen id : 11] +Output [3]: [ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Input [5]: [ws_web_site_sk#3, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, web_site_sk#18] + +(41) HashAggregate [codegen id : 11] +Input [3]: [ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +Keys [1]: [ws_order_number#5] +Functions [2]: [partial_sum(UnscaledValue(ws_ext_ship_cost#6)), partial_sum(UnscaledValue(ws_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_ship_cost#6))#20, sum(UnscaledValue(ws_net_profit#7))#21] +Results [3]: [ws_order_number#5, sum#22, sum#23] + +(42) HashAggregate [codegen id : 11] +Input [3]: [ws_order_number#5, sum#22, sum#23] +Keys [1]: [ws_order_number#5] +Functions [2]: [merge_sum(UnscaledValue(ws_ext_ship_cost#6)), merge_sum(UnscaledValue(ws_net_profit#7))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_ship_cost#6))#20, sum(UnscaledValue(ws_net_profit#7))#21] +Results [3]: [ws_order_number#5, sum#22, sum#23] + +(43) HashAggregate [codegen id : 11] +Input [3]: [ws_order_number#5, sum#22, sum#23] +Keys: [] +Functions [3]: [merge_sum(UnscaledValue(ws_ext_ship_cost#6)), merge_sum(UnscaledValue(ws_net_profit#7)), partial_count(distinct ws_order_number#5)] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_ship_cost#6))#20, sum(UnscaledValue(ws_net_profit#7))#21, count(ws_order_number#5)#24] +Results [3]: [sum#22, sum#23, count#25] + +(44) Exchange +Input [3]: [sum#22, sum#23, count#25] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(45) HashAggregate [codegen id : 12] +Input [3]: [sum#22, sum#23, count#25] +Keys: [] +Functions [3]: [sum(UnscaledValue(ws_ext_ship_cost#6)), sum(UnscaledValue(ws_net_profit#7)), count(distinct ws_order_number#5)] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_ship_cost#6))#20, sum(UnscaledValue(ws_net_profit#7))#21, count(ws_order_number#5)#24] +Results [3]: [count(ws_order_number#5)#24 AS order count #26, MakeDecimal(sum(UnscaledValue(ws_ext_ship_cost#6))#20,17,2) AS total shipping cost #27, MakeDecimal(sum(UnscaledValue(ws_net_profit#7))#21,17,2) AS total net profit #28] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/simplified.txt new file mode 100644 index 000000000..1aa3b4dc1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/simplified.txt @@ -0,0 +1,74 @@ +WholeStageCodegen (12) + HashAggregate [sum,sum,count] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),count(ws_order_number),order count ,total shipping cost ,total net profit ,sum,sum,count] + InputAdapter + Exchange #1 + WholeStageCodegen (11) + HashAggregate [ws_order_number] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),count(ws_order_number),sum,sum,count,sum,sum,count] + HashAggregate [ws_order_number] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),sum,sum,sum,sum] + HashAggregate [ws_order_number,ws_ext_ship_cost,ws_net_profit] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),sum,sum,sum,sum] + Project [ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_web_site_sk,web_site_sk] + Project [ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_ship_addr_sk,ca_address_sk] + Project [ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_ship_date_sk,d_date_sk] + SortMergeJoin [ws_order_number,wr_order_number] + InputAdapter + WholeStageCodegen (5) + Project [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + SortMergeJoin [ws_order_number,ws_order_number,ws_warehouse_sk,ws_warehouse_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ws_order_number] + InputAdapter + Exchange [ws_order_number] #2 + WholeStageCodegen (1) + Project [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_warehouse_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + Filter [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_warehouse_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit,ws_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [ws_order_number] + InputAdapter + Exchange [ws_order_number] #3 + WholeStageCodegen (3) + Project [ws_warehouse_sk,ws_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_warehouse_sk,ws_order_number,ws_sold_date_sk] + InputAdapter + WholeStageCodegen (7) + Sort [wr_order_number] + InputAdapter + Exchange [wr_order_number] #4 + WholeStageCodegen (6) + Project [wr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_order_number,wr_returned_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (8) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (9) + Project [ca_address_sk] + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (10) + Project [web_site_sk] + Filter [web_company_name,web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_company_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/explain.txt new file mode 100644 index 000000000..f8ee8ccb8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/explain.txt @@ -0,0 +1,330 @@ +== Physical Plan == +* HashAggregate (58) ++- Exchange (57) + +- * HashAggregate (56) + +- * HashAggregate (55) + +- * HashAggregate (54) + +- * Project (53) + +- * BroadcastHashJoin Inner BuildRight (52) + :- * Project (46) + : +- * BroadcastHashJoin Inner BuildRight (45) + : :- * Project (39) + : : +- * BroadcastHashJoin Inner BuildRight (38) + : : :- * SortMergeJoin LeftSemi (32) + : : : :- * SortMergeJoin LeftSemi (17) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * Project (4) + : : : : : +- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : +- * Project (16) + : : : : +- * SortMergeJoin Inner (15) + : : : : :- * Sort (12) + : : : : : +- Exchange (11) + : : : : : +- * Project (10) + : : : : : +- * Filter (9) + : : : : : +- * ColumnarToRow (8) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (7) + : : : : +- * Sort (14) + : : : : +- ReusedExchange (13) + : : : +- * Project (31) + : : : +- * SortMergeJoin Inner (30) + : : : :- * Sort (23) + : : : : +- Exchange (22) + : : : : +- * Project (21) + : : : : +- * Filter (20) + : : : : +- * ColumnarToRow (19) + : : : : +- CometScan parquet spark_catalog.default.web_returns (18) + : : : +- * Project (29) + : : : +- * SortMergeJoin Inner (28) + : : : :- * Sort (25) + : : : : +- ReusedExchange (24) + : : : +- * Sort (27) + : : : +- ReusedExchange (26) + : : +- BroadcastExchange (37) + : : +- * Project (36) + : : +- * Filter (35) + : : +- * ColumnarToRow (34) + : : +- CometScan parquet spark_catalog.default.date_dim (33) + : +- BroadcastExchange (44) + : +- * Project (43) + : +- * Filter (42) + : +- * ColumnarToRow (41) + : +- CometScan parquet spark_catalog.default.customer_address (40) + +- BroadcastExchange (51) + +- * Project (50) + +- * Filter (49) + +- * ColumnarToRow (48) + +- CometScan parquet spark_catalog.default.web_site (47) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ws_sold_date_sk#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_ship_date_sk), IsNotNull(ws_ship_addr_sk), IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ws_sold_date_sk#7] + +(3) Filter [codegen id : 1] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ws_sold_date_sk#7] +Condition : ((isnotnull(ws_ship_date_sk#1) AND isnotnull(ws_ship_addr_sk#2)) AND isnotnull(ws_web_site_sk#3)) + +(4) Project [codegen id : 1] +Output [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ws_sold_date_sk#7] + +(5) Exchange +Input [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Arguments: hashpartitioning(ws_order_number#4, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Arguments: [ws_order_number#4 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_warehouse_sk#8, ws_order_number#9, ws_sold_date_sk#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_order_number), IsNotNull(ws_warehouse_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 3] +Input [3]: [ws_warehouse_sk#8, ws_order_number#9, ws_sold_date_sk#10] + +(9) Filter [codegen id : 3] +Input [3]: [ws_warehouse_sk#8, ws_order_number#9, ws_sold_date_sk#10] +Condition : (isnotnull(ws_order_number#9) AND isnotnull(ws_warehouse_sk#8)) + +(10) Project [codegen id : 3] +Output [2]: [ws_warehouse_sk#8, ws_order_number#9] +Input [3]: [ws_warehouse_sk#8, ws_order_number#9, ws_sold_date_sk#10] + +(11) Exchange +Input [2]: [ws_warehouse_sk#8, ws_order_number#9] +Arguments: hashpartitioning(ws_order_number#9, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 4] +Input [2]: [ws_warehouse_sk#8, ws_order_number#9] +Arguments: [ws_order_number#9 ASC NULLS FIRST], false, 0 + +(13) ReusedExchange [Reuses operator id: 11] +Output [2]: [ws_warehouse_sk#11, ws_order_number#12] + +(14) Sort [codegen id : 6] +Input [2]: [ws_warehouse_sk#11, ws_order_number#12] +Arguments: [ws_order_number#12 ASC NULLS FIRST], false, 0 + +(15) SortMergeJoin [codegen id : 7] +Left keys [1]: [ws_order_number#9] +Right keys [1]: [ws_order_number#12] +Join type: Inner +Join condition: NOT (ws_warehouse_sk#8 = ws_warehouse_sk#11) + +(16) Project [codegen id : 7] +Output [1]: [ws_order_number#9] +Input [4]: [ws_warehouse_sk#8, ws_order_number#9, ws_warehouse_sk#11, ws_order_number#12] + +(17) SortMergeJoin [codegen id : 8] +Left keys [1]: [ws_order_number#4] +Right keys [1]: [ws_order_number#9] +Join type: LeftSemi +Join condition: None + +(18) Scan parquet spark_catalog.default.web_returns +Output [2]: [wr_order_number#13, wr_returned_date_sk#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_order_number)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 9] +Input [2]: [wr_order_number#13, wr_returned_date_sk#14] + +(20) Filter [codegen id : 9] +Input [2]: [wr_order_number#13, wr_returned_date_sk#14] +Condition : isnotnull(wr_order_number#13) + +(21) Project [codegen id : 9] +Output [1]: [wr_order_number#13] +Input [2]: [wr_order_number#13, wr_returned_date_sk#14] + +(22) Exchange +Input [1]: [wr_order_number#13] +Arguments: hashpartitioning(wr_order_number#13, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) Sort [codegen id : 10] +Input [1]: [wr_order_number#13] +Arguments: [wr_order_number#13 ASC NULLS FIRST], false, 0 + +(24) ReusedExchange [Reuses operator id: 11] +Output [2]: [ws_warehouse_sk#15, ws_order_number#16] + +(25) Sort [codegen id : 12] +Input [2]: [ws_warehouse_sk#15, ws_order_number#16] +Arguments: [ws_order_number#16 ASC NULLS FIRST], false, 0 + +(26) ReusedExchange [Reuses operator id: 11] +Output [2]: [ws_warehouse_sk#17, ws_order_number#18] + +(27) Sort [codegen id : 14] +Input [2]: [ws_warehouse_sk#17, ws_order_number#18] +Arguments: [ws_order_number#18 ASC NULLS FIRST], false, 0 + +(28) SortMergeJoin [codegen id : 15] +Left keys [1]: [ws_order_number#16] +Right keys [1]: [ws_order_number#18] +Join type: Inner +Join condition: NOT (ws_warehouse_sk#15 = ws_warehouse_sk#17) + +(29) Project [codegen id : 15] +Output [1]: [ws_order_number#16] +Input [4]: [ws_warehouse_sk#15, ws_order_number#16, ws_warehouse_sk#17, ws_order_number#18] + +(30) SortMergeJoin [codegen id : 16] +Left keys [1]: [wr_order_number#13] +Right keys [1]: [ws_order_number#16] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 16] +Output [1]: [wr_order_number#13] +Input [2]: [wr_order_number#13, ws_order_number#16] + +(32) SortMergeJoin [codegen id : 20] +Left keys [1]: [ws_order_number#4] +Right keys [1]: [wr_order_number#13] +Join type: LeftSemi +Join condition: None + +(33) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#19, d_date#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-01), LessThanOrEqual(d_date,1999-04-02), IsNotNull(d_date_sk)] +ReadSchema: struct + +(34) ColumnarToRow [codegen id : 17] +Input [2]: [d_date_sk#19, d_date#20] + +(35) Filter [codegen id : 17] +Input [2]: [d_date_sk#19, d_date#20] +Condition : (((isnotnull(d_date#20) AND (d_date#20 >= 1999-02-01)) AND (d_date#20 <= 1999-04-02)) AND isnotnull(d_date_sk#19)) + +(36) Project [codegen id : 17] +Output [1]: [d_date_sk#19] +Input [2]: [d_date_sk#19, d_date#20] + +(37) BroadcastExchange +Input [1]: [d_date_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(38) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [ws_ship_date_sk#1] +Right keys [1]: [d_date_sk#19] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 20] +Output [5]: [ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, d_date_sk#19] + +(40) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#21, ca_state#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,IL), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 18] +Input [2]: [ca_address_sk#21, ca_state#22] + +(42) Filter [codegen id : 18] +Input [2]: [ca_address_sk#21, ca_state#22] +Condition : ((isnotnull(ca_state#22) AND (ca_state#22 = IL)) AND isnotnull(ca_address_sk#21)) + +(43) Project [codegen id : 18] +Output [1]: [ca_address_sk#21] +Input [2]: [ca_address_sk#21, ca_state#22] + +(44) BroadcastExchange +Input [1]: [ca_address_sk#21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(45) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [ws_ship_addr_sk#2] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(46) Project [codegen id : 20] +Output [4]: [ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Input [6]: [ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ca_address_sk#21] + +(47) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#23, web_company_name#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_company_name), EqualTo(web_company_name,pri ), IsNotNull(web_site_sk)] +ReadSchema: struct + +(48) ColumnarToRow [codegen id : 19] +Input [2]: [web_site_sk#23, web_company_name#24] + +(49) Filter [codegen id : 19] +Input [2]: [web_site_sk#23, web_company_name#24] +Condition : ((isnotnull(web_company_name#24) AND (web_company_name#24 = pri )) AND isnotnull(web_site_sk#23)) + +(50) Project [codegen id : 19] +Output [1]: [web_site_sk#23] +Input [2]: [web_site_sk#23, web_company_name#24] + +(51) BroadcastExchange +Input [1]: [web_site_sk#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +(52) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [ws_web_site_sk#3] +Right keys [1]: [web_site_sk#23] +Join type: Inner +Join condition: None + +(53) Project [codegen id : 20] +Output [3]: [ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Input [5]: [ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, web_site_sk#23] + +(54) HashAggregate [codegen id : 20] +Input [3]: [ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +Keys [1]: [ws_order_number#4] +Functions [2]: [partial_sum(UnscaledValue(ws_ext_ship_cost#5)), partial_sum(UnscaledValue(ws_net_profit#6))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_ship_cost#5))#25, sum(UnscaledValue(ws_net_profit#6))#26] +Results [3]: [ws_order_number#4, sum#27, sum#28] + +(55) HashAggregate [codegen id : 20] +Input [3]: [ws_order_number#4, sum#27, sum#28] +Keys [1]: [ws_order_number#4] +Functions [2]: [merge_sum(UnscaledValue(ws_ext_ship_cost#5)), merge_sum(UnscaledValue(ws_net_profit#6))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_ship_cost#5))#25, sum(UnscaledValue(ws_net_profit#6))#26] +Results [3]: [ws_order_number#4, sum#27, sum#28] + +(56) HashAggregate [codegen id : 20] +Input [3]: [ws_order_number#4, sum#27, sum#28] +Keys: [] +Functions [3]: [merge_sum(UnscaledValue(ws_ext_ship_cost#5)), merge_sum(UnscaledValue(ws_net_profit#6)), partial_count(distinct ws_order_number#4)] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_ship_cost#5))#25, sum(UnscaledValue(ws_net_profit#6))#26, count(ws_order_number#4)#29] +Results [3]: [sum#27, sum#28, count#30] + +(57) Exchange +Input [3]: [sum#27, sum#28, count#30] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(58) HashAggregate [codegen id : 21] +Input [3]: [sum#27, sum#28, count#30] +Keys: [] +Functions [3]: [sum(UnscaledValue(ws_ext_ship_cost#5)), sum(UnscaledValue(ws_net_profit#6)), count(distinct ws_order_number#4)] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_ship_cost#5))#25, sum(UnscaledValue(ws_net_profit#6))#26, count(ws_order_number#4)#29] +Results [3]: [count(ws_order_number#4)#29 AS order count #31, MakeDecimal(sum(UnscaledValue(ws_ext_ship_cost#5))#25,17,2) AS total shipping cost #32, MakeDecimal(sum(UnscaledValue(ws_net_profit#6))#26,17,2) AS total net profit #33] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/simplified.txt new file mode 100644 index 000000000..389d74d39 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/simplified.txt @@ -0,0 +1,102 @@ +WholeStageCodegen (21) + HashAggregate [sum,sum,count] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),count(ws_order_number),order count ,total shipping cost ,total net profit ,sum,sum,count] + InputAdapter + Exchange #1 + WholeStageCodegen (20) + HashAggregate [ws_order_number] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),count(ws_order_number),sum,sum,count,sum,sum,count] + HashAggregate [ws_order_number] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),sum,sum,sum,sum] + HashAggregate [ws_order_number,ws_ext_ship_cost,ws_net_profit] [sum(UnscaledValue(ws_ext_ship_cost)),sum(UnscaledValue(ws_net_profit)),sum,sum,sum,sum] + Project [ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_web_site_sk,web_site_sk] + Project [ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_ship_addr_sk,ca_address_sk] + Project [ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + BroadcastHashJoin [ws_ship_date_sk,d_date_sk] + SortMergeJoin [ws_order_number,wr_order_number] + InputAdapter + WholeStageCodegen (8) + SortMergeJoin [ws_order_number,ws_order_number] + InputAdapter + WholeStageCodegen (2) + Sort [ws_order_number] + InputAdapter + Exchange [ws_order_number] #2 + WholeStageCodegen (1) + Project [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + Filter [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit,ws_sold_date_sk] + InputAdapter + WholeStageCodegen (7) + Project [ws_order_number] + SortMergeJoin [ws_order_number,ws_order_number,ws_warehouse_sk,ws_warehouse_sk] + InputAdapter + WholeStageCodegen (4) + Sort [ws_order_number] + InputAdapter + Exchange [ws_order_number] #3 + WholeStageCodegen (3) + Project [ws_warehouse_sk,ws_order_number] + Filter [ws_order_number,ws_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_warehouse_sk,ws_order_number,ws_sold_date_sk] + InputAdapter + WholeStageCodegen (6) + Sort [ws_order_number] + InputAdapter + ReusedExchange [ws_warehouse_sk,ws_order_number] #3 + InputAdapter + WholeStageCodegen (16) + Project [wr_order_number] + SortMergeJoin [wr_order_number,ws_order_number] + InputAdapter + WholeStageCodegen (10) + Sort [wr_order_number] + InputAdapter + Exchange [wr_order_number] #4 + WholeStageCodegen (9) + Project [wr_order_number] + Filter [wr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_order_number,wr_returned_date_sk] + InputAdapter + WholeStageCodegen (15) + Project [ws_order_number] + SortMergeJoin [ws_order_number,ws_order_number,ws_warehouse_sk,ws_warehouse_sk] + InputAdapter + WholeStageCodegen (12) + Sort [ws_order_number] + InputAdapter + ReusedExchange [ws_warehouse_sk,ws_order_number] #3 + InputAdapter + WholeStageCodegen (14) + Sort [ws_order_number] + InputAdapter + ReusedExchange [ws_warehouse_sk,ws_order_number] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (17) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (18) + Project [ca_address_sk] + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (19) + Project [web_site_sk] + Filter [web_company_name,web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_company_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/explain.txt new file mode 100644 index 000000000..e0ce29b43 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/explain.txt @@ -0,0 +1,163 @@ +== Physical Plan == +* HashAggregate (28) ++- Exchange (27) + +- * HashAggregate (26) + +- * Project (25) + +- * BroadcastHashJoin Inner BuildRight (24) + :- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildRight (10) + : : :- * Project (4) + : : : +- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- BroadcastExchange (9) + : : +- * Project (8) + : : +- * Filter (7) + : : +- * ColumnarToRow (6) + : : +- CometScan parquet spark_catalog.default.household_demographics (5) + : +- BroadcastExchange (16) + : +- * Project (15) + : +- * Filter (14) + : +- * ColumnarToRow (13) + : +- CometScan parquet spark_catalog.default.time_dim (12) + +- BroadcastExchange (23) + +- * Project (22) + +- * Filter (21) + +- * ColumnarToRow (20) + +- CometScan parquet spark_catalog.default.store (19) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 4] +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Condition : ((isnotnull(ss_hdemo_sk#2) AND isnotnull(ss_sold_time_sk#1)) AND isnotnull(ss_store_sk#3)) + +(4) Project [codegen id : 4] +Output [3]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] + +(5) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#5, hd_dep_count#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_dep_count), EqualTo(hd_dep_count,7), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 1] +Input [2]: [hd_demo_sk#5, hd_dep_count#6] + +(7) Filter [codegen id : 1] +Input [2]: [hd_demo_sk#5, hd_dep_count#6] +Condition : ((isnotnull(hd_dep_count#6) AND (hd_dep_count#6 = 7)) AND isnotnull(hd_demo_sk#5)) + +(8) Project [codegen id : 1] +Output [1]: [hd_demo_sk#5] +Input [2]: [hd_demo_sk#5, hd_dep_count#6] + +(9) BroadcastExchange +Input [1]: [hd_demo_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#5] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 4] +Output [2]: [ss_sold_time_sk#1, ss_store_sk#3] +Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, hd_demo_sk#5] + +(12) Scan parquet spark_catalog.default.time_dim +Output [3]: [t_time_sk#7, t_hour#8, t_minute#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/time_dim] +PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,20), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] +ReadSchema: struct + +(13) ColumnarToRow [codegen id : 2] +Input [3]: [t_time_sk#7, t_hour#8, t_minute#9] + +(14) Filter [codegen id : 2] +Input [3]: [t_time_sk#7, t_hour#8, t_minute#9] +Condition : ((((isnotnull(t_hour#8) AND isnotnull(t_minute#9)) AND (t_hour#8 = 20)) AND (t_minute#9 >= 30)) AND isnotnull(t_time_sk#7)) + +(15) Project [codegen id : 2] +Output [1]: [t_time_sk#7] +Input [3]: [t_time_sk#7, t_hour#8, t_minute#9] + +(16) BroadcastExchange +Input [1]: [t_time_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_time_sk#1] +Right keys [1]: [t_time_sk#7] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [1]: [ss_store_sk#3] +Input [3]: [ss_sold_time_sk#1, ss_store_sk#3, t_time_sk#7] + +(19) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#10, s_store_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_name), EqualTo(s_store_name,ese), IsNotNull(s_store_sk)] +ReadSchema: struct + +(20) ColumnarToRow [codegen id : 3] +Input [2]: [s_store_sk#10, s_store_name#11] + +(21) Filter [codegen id : 3] +Input [2]: [s_store_sk#10, s_store_name#11] +Condition : ((isnotnull(s_store_name#11) AND (s_store_name#11 = ese)) AND isnotnull(s_store_sk#10)) + +(22) Project [codegen id : 3] +Output [1]: [s_store_sk#10] +Input [2]: [s_store_sk#10, s_store_name#11] + +(23) BroadcastExchange +Input [1]: [s_store_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#10] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 4] +Output: [] +Input [2]: [ss_store_sk#3, s_store_sk#10] + +(26) HashAggregate [codegen id : 4] +Input: [] +Keys: [] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#12] +Results [1]: [count#13] + +(27) Exchange +Input [1]: [count#13] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 5] +Input [1]: [count#13] +Keys: [] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#14] +Results [1]: [count(1)#14 AS count(1)#15] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/simplified.txt new file mode 100644 index 000000000..fe9cd8bc8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/simplified.txt @@ -0,0 +1,41 @@ +WholeStageCodegen (5) + HashAggregate [count] [count(1),count(1),count] + InputAdapter + Exchange #1 + WholeStageCodegen (4) + HashAggregate [count,count] + Project + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk] + BroadcastHashJoin [ss_sold_time_sk,t_time_sk] + Project [ss_sold_time_sk,ss_store_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Project [hd_demo_sk] + Filter [hd_dep_count,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Project [t_time_sk] + Filter [t_hour,t_minute,t_time_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Project [s_store_sk] + Filter [s_store_name,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/explain.txt new file mode 100644 index 000000000..6d54b23d8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/explain.txt @@ -0,0 +1,179 @@ +== Physical Plan == +* HashAggregate (23) ++- Exchange (22) + +- * HashAggregate (21) + +- * Project (20) + +- * SortMergeJoin FullOuter (19) + :- * Sort (9) + : +- * HashAggregate (8) + : +- Exchange (7) + : +- * HashAggregate (6) + : +- * Project (5) + : +- * BroadcastHashJoin Inner BuildRight (4) + : :- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.store_sales (1) + : +- ReusedExchange (3) + +- * Sort (18) + +- * HashAggregate (17) + +- Exchange (16) + +- * HashAggregate (15) + +- * Project (14) + +- * BroadcastHashJoin Inner BuildRight (13) + :- * ColumnarToRow (11) + : +- CometScan parquet spark_catalog.default.catalog_sales (10) + +- ReusedExchange (12) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#1, ss_customer_sk#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 2] +Input [3]: [ss_item_sk#1, ss_customer_sk#2, ss_sold_date_sk#3] + +(3) ReusedExchange [Reuses operator id: 28] +Output [1]: [d_date_sk#5] + +(4) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(5) Project [codegen id : 2] +Output [2]: [ss_item_sk#1, ss_customer_sk#2] +Input [4]: [ss_item_sk#1, ss_customer_sk#2, ss_sold_date_sk#3, d_date_sk#5] + +(6) HashAggregate [codegen id : 2] +Input [2]: [ss_item_sk#1, ss_customer_sk#2] +Keys [2]: [ss_customer_sk#2, ss_item_sk#1] +Functions: [] +Aggregate Attributes: [] +Results [2]: [ss_customer_sk#2, ss_item_sk#1] + +(7) Exchange +Input [2]: [ss_customer_sk#2, ss_item_sk#1] +Arguments: hashpartitioning(ss_customer_sk#2, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(8) HashAggregate [codegen id : 3] +Input [2]: [ss_customer_sk#2, ss_item_sk#1] +Keys [2]: [ss_customer_sk#2, ss_item_sk#1] +Functions: [] +Aggregate Attributes: [] +Results [2]: [ss_customer_sk#2 AS customer_sk#6, ss_item_sk#1 AS item_sk#7] + +(9) Sort [codegen id : 3] +Input [2]: [customer_sk#6, item_sk#7] +Arguments: [customer_sk#6 ASC NULLS FIRST, item_sk#7 ASC NULLS FIRST], false, 0 + +(10) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_bill_customer_sk#8, cs_item_sk#9, cs_sold_date_sk#10] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#10), dynamicpruningexpression(cs_sold_date_sk#10 IN dynamicpruning#11)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 5] +Input [3]: [cs_bill_customer_sk#8, cs_item_sk#9, cs_sold_date_sk#10] + +(12) ReusedExchange [Reuses operator id: 28] +Output [1]: [d_date_sk#12] + +(13) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_sold_date_sk#10] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 5] +Output [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Input [4]: [cs_bill_customer_sk#8, cs_item_sk#9, cs_sold_date_sk#10, d_date_sk#12] + +(15) HashAggregate [codegen id : 5] +Input [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Keys [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Functions: [] +Aggregate Attributes: [] +Results [2]: [cs_bill_customer_sk#8, cs_item_sk#9] + +(16) Exchange +Input [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Arguments: hashpartitioning(cs_bill_customer_sk#8, cs_item_sk#9, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(17) HashAggregate [codegen id : 6] +Input [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Keys [2]: [cs_bill_customer_sk#8, cs_item_sk#9] +Functions: [] +Aggregate Attributes: [] +Results [2]: [cs_bill_customer_sk#8 AS customer_sk#13, cs_item_sk#9 AS item_sk#14] + +(18) Sort [codegen id : 6] +Input [2]: [customer_sk#13, item_sk#14] +Arguments: [customer_sk#13 ASC NULLS FIRST, item_sk#14 ASC NULLS FIRST], false, 0 + +(19) SortMergeJoin [codegen id : 7] +Left keys [2]: [customer_sk#6, item_sk#7] +Right keys [2]: [customer_sk#13, item_sk#14] +Join type: FullOuter +Join condition: None + +(20) Project [codegen id : 7] +Output [2]: [customer_sk#6, customer_sk#13] +Input [4]: [customer_sk#6, item_sk#7, customer_sk#13, item_sk#14] + +(21) HashAggregate [codegen id : 7] +Input [2]: [customer_sk#6, customer_sk#13] +Keys: [] +Functions [3]: [partial_sum(CASE WHEN (isnotnull(customer_sk#6) AND isnull(customer_sk#13)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (isnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (isnotnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)] +Aggregate Attributes [3]: [sum#15, sum#16, sum#17] +Results [3]: [sum#18, sum#19, sum#20] + +(22) Exchange +Input [3]: [sum#18, sum#19, sum#20] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 8] +Input [3]: [sum#18, sum#19, sum#20] +Keys: [] +Functions [3]: [sum(CASE WHEN (isnotnull(customer_sk#6) AND isnull(customer_sk#13)) THEN 1 ELSE 0 END), sum(CASE WHEN (isnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END), sum(CASE WHEN (isnotnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)] +Aggregate Attributes [3]: [sum(CASE WHEN (isnotnull(customer_sk#6) AND isnull(customer_sk#13)) THEN 1 ELSE 0 END)#21, sum(CASE WHEN (isnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)#22, sum(CASE WHEN (isnotnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)#23] +Results [3]: [sum(CASE WHEN (isnotnull(customer_sk#6) AND isnull(customer_sk#13)) THEN 1 ELSE 0 END)#21 AS store_only#24, sum(CASE WHEN (isnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)#22 AS catalog_only#25, sum(CASE WHEN (isnotnull(customer_sk#6) AND isnotnull(customer_sk#13)) THEN 1 ELSE 0 END)#23 AS store_and_catalog#26] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (28) ++- * Project (27) + +- * Filter (26) + +- * ColumnarToRow (25) + +- CometScan parquet spark_catalog.default.date_dim (24) + + +(24) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(25) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#27] + +(26) Filter [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#27] +Condition : (((isnotnull(d_month_seq#27) AND (d_month_seq#27 >= 1200)) AND (d_month_seq#27 <= 1211)) AND isnotnull(d_date_sk#5)) + +(27) Project [codegen id : 1] +Output [1]: [d_date_sk#5] +Input [2]: [d_date_sk#5, d_month_seq#27] + +(28) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +Subquery:2 Hosting operator id = 10 Hosting Expression = cs_sold_date_sk#10 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/simplified.txt new file mode 100644 index 000000000..ba918e146 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/simplified.txt @@ -0,0 +1,47 @@ +WholeStageCodegen (8) + HashAggregate [sum,sum,sum] [sum(CASE WHEN (isnotnull(customer_sk) AND isnull(customer_sk)) THEN 1 ELSE 0 END),sum(CASE WHEN (isnull(customer_sk) AND isnotnull(customer_sk)) THEN 1 ELSE 0 END),sum(CASE WHEN (isnotnull(customer_sk) AND isnotnull(customer_sk)) THEN 1 ELSE 0 END),store_only,catalog_only,store_and_catalog,sum,sum,sum] + InputAdapter + Exchange #1 + WholeStageCodegen (7) + HashAggregate [customer_sk,customer_sk] [sum,sum,sum,sum,sum,sum] + Project [customer_sk,customer_sk] + SortMergeJoin [customer_sk,item_sk,customer_sk,item_sk] + InputAdapter + WholeStageCodegen (3) + Sort [customer_sk,item_sk] + HashAggregate [ss_customer_sk,ss_item_sk] [customer_sk,item_sk] + InputAdapter + Exchange [ss_customer_sk,ss_item_sk] #2 + WholeStageCodegen (2) + HashAggregate [ss_customer_sk,ss_item_sk] + Project [ss_item_sk,ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + WholeStageCodegen (6) + Sort [customer_sk,item_sk] + HashAggregate [cs_bill_customer_sk,cs_item_sk] [customer_sk,item_sk] + InputAdapter + Exchange [cs_bill_customer_sk,cs_item_sk] #4 + WholeStageCodegen (5) + HashAggregate [cs_bill_customer_sk,cs_item_sk] + Project [cs_bill_customer_sk,cs_item_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/explain.txt new file mode 100644 index 000000000..d4202b01d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/explain.txt @@ -0,0 +1,160 @@ +== Physical Plan == +* Project (22) ++- * Sort (21) + +- Exchange (20) + +- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.store_sales (1) + : +- BroadcastExchange (7) + : +- * Filter (6) + : +- * ColumnarToRow (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] + +(3) Filter [codegen id : 3] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(6) Filter [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 27] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [ss_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [ss_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#2))#14] +Results [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#14,17,2) AS _w0#16, i_item_id#6] + +(16) Exchange +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18, i_item_id#6] +Input [8]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, i_item_id#6, _we0#17] + +(20) Exchange +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18, i_item_id#6] +Arguments: rangepartitioning(i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(21) Sort [codegen id : 7] +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18, i_item_id#6] +Arguments: [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], true, 0 + +(22) Project [codegen id : 7] +Output [6]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] +Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18, i_item_id#6] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (27) ++- * Project (26) + +- * Filter (25) + +- * ColumnarToRow (24) + +- CometScan parquet spark_catalog.default.date_dim (23) + + +(23) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(24) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] + +(25) Filter [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(26) Project [codegen id : 1] +Output [1]: [d_date_sk#11] +Input [2]: [d_date_sk#11, d_date#19] + +(27) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/simplified.txt new file mode 100644 index 000000000..d3b1f3fe6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/simplified.txt @@ -0,0 +1,44 @@ +WholeStageCodegen (7) + Project [i_item_desc,i_category,i_class,i_current_price,itemrevenue,revenueratio] + Sort [i_category,i_class,i_item_id,i_item_desc,revenueratio] + InputAdapter + Exchange [i_category,i_class,i_item_id,i_item_desc,revenueratio] #1 + WholeStageCodegen (6) + Project [i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0,i_item_id] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #2 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(ss_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #3 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_ext_sales_price,ss_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (1) + Filter [i_category,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/explain.txt new file mode 100644 index 000000000..f8cf6b243 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/explain.txt @@ -0,0 +1,187 @@ +== Physical Plan == +TakeOrderedAndProject (32) ++- * HashAggregate (31) + +- Exchange (30) + +- * HashAggregate (29) + +- * Project (28) + +- * BroadcastHashJoin Inner BuildRight (27) + :- * Project (21) + : +- * BroadcastHashJoin Inner BuildRight (20) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.warehouse (4) + : : +- BroadcastExchange (13) + : : +- * Filter (12) + : : +- * ColumnarToRow (11) + : : +- CometScan parquet spark_catalog.default.ship_mode (10) + : +- BroadcastExchange (19) + : +- * Filter (18) + : +- * ColumnarToRow (17) + : +- CometScan parquet spark_catalog.default.call_center (16) + +- BroadcastExchange (26) + +- * Project (25) + +- * Filter (24) + +- * ColumnarToRow (23) + +- CometScan parquet spark_catalog.default.date_dim (22) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_warehouse_sk#4, cs_sold_date_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +PushedFilters: [IsNotNull(cs_warehouse_sk), IsNotNull(cs_ship_mode_sk), IsNotNull(cs_call_center_sk), IsNotNull(cs_ship_date_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_warehouse_sk#4, cs_sold_date_sk#5] + +(3) Filter [codegen id : 5] +Input [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_warehouse_sk#4, cs_sold_date_sk#5] +Condition : (((isnotnull(cs_warehouse_sk#4) AND isnotnull(cs_ship_mode_sk#3)) AND isnotnull(cs_call_center_sk#2)) AND isnotnull(cs_ship_date_sk#1)) + +(4) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] + +(6) Filter [codegen id : 1] +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Condition : isnotnull(w_warehouse_sk#6) + +(7) BroadcastExchange +Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_warehouse_sk#4] +Right keys [1]: [w_warehouse_sk#6] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 5] +Output [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_sold_date_sk#5, w_warehouse_name#7] +Input [7]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_warehouse_sk#4, cs_sold_date_sk#5, w_warehouse_sk#6, w_warehouse_name#7] + +(10) Scan parquet spark_catalog.default.ship_mode +Output [2]: [sm_ship_mode_sk#8, sm_type#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/ship_mode] +PushedFilters: [IsNotNull(sm_ship_mode_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [2]: [sm_ship_mode_sk#8, sm_type#9] + +(12) Filter [codegen id : 2] +Input [2]: [sm_ship_mode_sk#8, sm_type#9] +Condition : isnotnull(sm_ship_mode_sk#8) + +(13) BroadcastExchange +Input [2]: [sm_ship_mode_sk#8, sm_type#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_ship_mode_sk#3] +Right keys [1]: [sm_ship_mode_sk#8] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 5] +Output [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_sold_date_sk#5, w_warehouse_name#7, sm_type#9] +Input [7]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_sold_date_sk#5, w_warehouse_name#7, sm_ship_mode_sk#8, sm_type#9] + +(16) Scan parquet spark_catalog.default.call_center +Output [2]: [cc_call_center_sk#10, cc_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/call_center] +PushedFilters: [IsNotNull(cc_call_center_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 3] +Input [2]: [cc_call_center_sk#10, cc_name#11] + +(18) Filter [codegen id : 3] +Input [2]: [cc_call_center_sk#10, cc_name#11] +Condition : isnotnull(cc_call_center_sk#10) + +(19) BroadcastExchange +Input [2]: [cc_call_center_sk#10, cc_name#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_call_center_sk#2] +Right keys [1]: [cc_call_center_sk#10] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 5] +Output [5]: [cs_ship_date_sk#1, cs_sold_date_sk#5, w_warehouse_name#7, sm_type#9, cc_name#11] +Input [7]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_sold_date_sk#5, w_warehouse_name#7, sm_type#9, cc_call_center_sk#10, cc_name#11] + +(22) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#12, d_month_seq#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 4] +Input [2]: [d_date_sk#12, d_month_seq#13] + +(24) Filter [codegen id : 4] +Input [2]: [d_date_sk#12, d_month_seq#13] +Condition : (((isnotnull(d_month_seq#13) AND (d_month_seq#13 >= 1200)) AND (d_month_seq#13 <= 1211)) AND isnotnull(d_date_sk#12)) + +(25) Project [codegen id : 4] +Output [1]: [d_date_sk#12] +Input [2]: [d_date_sk#12, d_month_seq#13] + +(26) BroadcastExchange +Input [1]: [d_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(27) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [cs_ship_date_sk#1] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 5] +Output [5]: [cs_ship_date_sk#1, cs_sold_date_sk#5, sm_type#9, cc_name#11, substr(w_warehouse_name#7, 1, 20) AS _groupingexpression#14] +Input [6]: [cs_ship_date_sk#1, cs_sold_date_sk#5, w_warehouse_name#7, sm_type#9, cc_name#11, d_date_sk#12] + +(29) HashAggregate [codegen id : 5] +Input [5]: [cs_ship_date_sk#1, cs_sold_date_sk#5, sm_type#9, cc_name#11, _groupingexpression#14] +Keys [3]: [_groupingexpression#14, sm_type#9, cc_name#11] +Functions [5]: [partial_sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 30) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 60) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 90) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum#15, sum#16, sum#17, sum#18, sum#19] +Results [8]: [_groupingexpression#14, sm_type#9, cc_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] + +(30) Exchange +Input [8]: [_groupingexpression#14, sm_type#9, cc_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] +Arguments: hashpartitioning(_groupingexpression#14, sm_type#9, cc_name#11, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(31) HashAggregate [codegen id : 6] +Input [8]: [_groupingexpression#14, sm_type#9, cc_name#11, sum#20, sum#21, sum#22, sum#23, sum#24] +Keys [3]: [_groupingexpression#14, sm_type#9, cc_name#11] +Functions [5]: [sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 30) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 60) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 90) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)] +Aggregate Attributes [5]: [sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#25, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 30) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#26, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 60) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#27, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 90) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#28, sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#29] +Results [8]: [_groupingexpression#14 AS substr(w_warehouse_name, 1, 20)#30, sm_type#9, cc_name#11, sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#25 AS 30 days #31, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 30) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#26 AS 31 - 60 days #32, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 60) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#27 AS 61 - 90 days #33, sum(CASE WHEN (((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 90) AND ((cs_ship_date_sk#1 - cs_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#28 AS 91 - 120 days #34, sum(CASE WHEN ((cs_ship_date_sk#1 - cs_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#29 AS >120 days #35] + +(32) TakeOrderedAndProject +Input [8]: [substr(w_warehouse_name, 1, 20)#30, sm_type#9, cc_name#11, 30 days #31, 31 - 60 days #32, 61 - 90 days #33, 91 - 120 days #34, >120 days #35] +Arguments: 100, [substr(w_warehouse_name, 1, 20)#30 ASC NULLS FIRST, sm_type#9 ASC NULLS FIRST, cc_name#11 ASC NULLS FIRST], [substr(w_warehouse_name, 1, 20)#30, sm_type#9, cc_name#11, 30 days #31, 31 - 60 days #32, 61 - 90 days #33, 91 - 120 days #34, >120 days #35] + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/simplified.txt new file mode 100644 index 000000000..c165c1fc1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/simplified.txt @@ -0,0 +1,48 @@ +TakeOrderedAndProject [substr(w_warehouse_name, 1, 20),sm_type,cc_name,30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ] + WholeStageCodegen (6) + HashAggregate [_groupingexpression,sm_type,cc_name,sum,sum,sum,sum,sum] [sum(CASE WHEN ((cs_ship_date_sk - cs_sold_date_sk) <= 30) THEN 1 ELSE 0 END),sum(CASE WHEN (((cs_ship_date_sk - cs_sold_date_sk) > 30) AND ((cs_ship_date_sk - cs_sold_date_sk) <= 60)) THEN 1 ELSE 0 END),sum(CASE WHEN (((cs_ship_date_sk - cs_sold_date_sk) > 60) AND ((cs_ship_date_sk - cs_sold_date_sk) <= 90)) THEN 1 ELSE 0 END),sum(CASE WHEN (((cs_ship_date_sk - cs_sold_date_sk) > 90) AND ((cs_ship_date_sk - cs_sold_date_sk) <= 120)) THEN 1 ELSE 0 END),sum(CASE WHEN ((cs_ship_date_sk - cs_sold_date_sk) > 120) THEN 1 ELSE 0 END),substr(w_warehouse_name, 1, 20),30 days ,31 - 60 days ,61 - 90 days ,91 - 120 days ,>120 days ,sum,sum,sum,sum,sum] + InputAdapter + Exchange [_groupingexpression,sm_type,cc_name] #1 + WholeStageCodegen (5) + HashAggregate [_groupingexpression,sm_type,cc_name,cs_ship_date_sk,cs_sold_date_sk] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] + Project [cs_ship_date_sk,cs_sold_date_sk,sm_type,cc_name,w_warehouse_name] + BroadcastHashJoin [cs_ship_date_sk,d_date_sk] + Project [cs_ship_date_sk,cs_sold_date_sk,w_warehouse_name,sm_type,cc_name] + BroadcastHashJoin [cs_call_center_sk,cc_call_center_sk] + Project [cs_ship_date_sk,cs_call_center_sk,cs_sold_date_sk,w_warehouse_name,sm_type] + BroadcastHashJoin [cs_ship_mode_sk,sm_ship_mode_sk] + Project [cs_ship_date_sk,cs_call_center_sk,cs_ship_mode_sk,cs_sold_date_sk,w_warehouse_name] + BroadcastHashJoin [cs_warehouse_sk,w_warehouse_sk] + Filter [cs_warehouse_sk,cs_ship_mode_sk,cs_call_center_sk,cs_ship_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_call_center_sk,cs_ship_mode_sk,cs_warehouse_sk,cs_sold_date_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [sm_ship_mode_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.ship_mode [sm_ship_mode_sk,sm_type] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Filter [cc_call_center_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_name] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/explain.txt new file mode 100644 index 000000000..a0259dcc2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/explain.txt @@ -0,0 +1,272 @@ +== Physical Plan == +TakeOrderedAndProject (41) ++- * HashAggregate (40) + +- Exchange (39) + +- * HashAggregate (38) + +- * Project (37) + +- * BroadcastHashJoin Inner BuildRight (36) + :- * Project (31) + : +- * BroadcastHashJoin Inner BuildRight (30) + : :- * Project (24) + : : +- * BroadcastHashJoin LeftSemi BuildRight (23) + : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : +- BroadcastExchange (9) + : : : +- * Project (8) + : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : :- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (6) + : : +- BroadcastExchange (22) + : : +- Union (21) + : : :- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- * Project (20) + : : +- * BroadcastHashJoin Inner BuildRight (19) + : : :- * ColumnarToRow (17) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) + : : +- ReusedExchange (18) + : +- BroadcastExchange (29) + : +- * Project (28) + : +- * Filter (27) + : +- * ColumnarToRow (26) + : +- CometScan parquet spark_catalog.default.customer_address (25) + +- BroadcastExchange (35) + +- * Filter (34) + +- * ColumnarToRow (33) + +- CometScan parquet spark_catalog.default.customer_demographics (32) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(3) Filter [codegen id : 9] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#4, ss_sold_date_sk#5] + +(6) ReusedExchange [Reuses operator id: 46] +Output [1]: [d_date_sk#7] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#4] +Input [3]: [ss_customer_sk#4, ss_sold_date_sk#5, d_date_sk#7] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#4] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#9), dynamicpruningexpression(ws_sold_date_sk#9 IN dynamicpruning#10)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] + +(13) ReusedExchange [Reuses operator id: 46] +Output [1]: [d_date_sk#11] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#8 AS customer_sk#12] +Input [3]: [ws_bill_customer_sk#8, ws_sold_date_sk#9, d_date_sk#11] + +(16) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#13, cs_sold_date_sk#14] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#14), dynamicpruningexpression(cs_sold_date_sk#14 IN dynamicpruning#15)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#13, cs_sold_date_sk#14] + +(18) ReusedExchange [Reuses operator id: 46] +Output [1]: [d_date_sk#16] + +(19) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#14] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#13 AS customer_sk#17] +Input [3]: [cs_ship_customer_sk#13, cs_sold_date_sk#14, d_date_sk#16] + +(21) Union + +(22) BroadcastExchange +Input [1]: [customer_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(23) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [customer_sk#12] +Join type: LeftSemi +Join condition: None + +(24) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#2, c_current_addr_sk#3] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(25) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#18, ca_county#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_county, [Dona Ana County,Douglas County,Gaines County,Richland County,Walker County]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_county#19] + +(27) Filter [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_county#19] +Condition : (ca_county#19 IN (Walker County,Richland County,Gaines County,Douglas County,Dona Ana County) AND isnotnull(ca_address_sk#18)) + +(28) Project [codegen id : 7] +Output [1]: [ca_address_sk#18] +Input [2]: [ca_address_sk#18, ca_county#19] + +(29) BroadcastExchange +Input [1]: [ca_address_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(30) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#3] +Right keys [1]: [ca_address_sk#18] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 9] +Output [1]: [c_current_cdemo_sk#2] +Input [3]: [c_current_cdemo_sk#2, c_current_addr_sk#3, ca_address_sk#18] + +(32) Scan parquet spark_catalog.default.customer_demographics +Output [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(33) ColumnarToRow [codegen id : 8] +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] + +(34) Filter [codegen id : 8] +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Condition : isnotnull(cd_demo_sk#20) + +(35) BroadcastExchange +Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(36) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 9] +Output [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Input [10]: [c_current_cdemo_sk#2, cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] + +(38) HashAggregate [codegen id : 9] +Input [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Keys [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#29] +Results [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] + +(39) Exchange +Input [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] +Arguments: hashpartitioning(cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(40) HashAggregate [codegen id : 10] +Input [9]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28, count#30] +Keys [8]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#31] +Results [14]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, count(1)#31 AS cnt1#32, cd_purchase_estimate#24, count(1)#31 AS cnt2#33, cd_credit_rating#25, count(1)#31 AS cnt3#34, cd_dep_count#26, count(1)#31 AS cnt4#35, cd_dep_employed_count#27, count(1)#31 AS cnt5#36, cd_dep_college_count#28, count(1)#31 AS cnt6#37] + +(41) TakeOrderedAndProject +Input [14]: [cd_gender#21, cd_marital_status#22, cd_education_status#23, cnt1#32, cd_purchase_estimate#24, cnt2#33, cd_credit_rating#25, cnt3#34, cd_dep_count#26, cnt4#35, cd_dep_employed_count#27, cnt5#36, cd_dep_college_count#28, cnt6#37] +Arguments: 100, [cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FIRST, cd_education_status#23 ASC NULLS FIRST, cd_purchase_estimate#24 ASC NULLS FIRST, cd_credit_rating#25 ASC NULLS FIRST, cd_dep_count#26 ASC NULLS FIRST, cd_dep_employed_count#27 ASC NULLS FIRST, cd_dep_college_count#28 ASC NULLS FIRST], [cd_gender#21, cd_marital_status#22, cd_education_status#23, cnt1#32, cd_purchase_estimate#24, cnt2#33, cd_credit_rating#25, cnt3#34, cd_dep_count#26, cnt4#35, cd_dep_employed_count#27, cnt5#36, cd_dep_college_count#28, cnt6#37] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (46) ++- * Project (45) + +- * Filter (44) + +- * ColumnarToRow (43) + +- CometScan parquet spark_catalog.default.date_dim (42) + + +(42) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#38, d_moy#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2002), GreaterThanOrEqual(d_moy,4), LessThanOrEqual(d_moy,7), IsNotNull(d_date_sk)] +ReadSchema: struct + +(43) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#38, d_moy#39] + +(44) Filter [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#38, d_moy#39] +Condition : (((((isnotnull(d_year#38) AND isnotnull(d_moy#39)) AND (d_year#38 = 2002)) AND (d_moy#39 >= 4)) AND (d_moy#39 <= 7)) AND isnotnull(d_date_sk#7)) + +(45) Project [codegen id : 1] +Output [1]: [d_date_sk#7] +Input [3]: [d_date_sk#7, d_year#38, d_moy#39] + +(46) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#9 IN dynamicpruning#6 + +Subquery:3 Hosting operator id = 16 Hosting Expression = cs_sold_date_sk#14 IN dynamicpruning#6 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/simplified.txt new file mode 100644 index 000000000..668cec531 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/simplified.txt @@ -0,0 +1,72 @@ +TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,cnt1,cnt2,cnt3,cnt4,cnt5,cnt6] + WholeStageCodegen (10) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,count] [count(1),cnt1,cnt2,cnt3,cnt4,cnt5,cnt6,count] + InputAdapter + Exchange [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] #1 + WholeStageCodegen (9) + HashAggregate [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] [count,count] + Project [cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + BroadcastHashJoin [c_customer_sk,customer_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_current_addr_sk,c_current_cdemo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + Union + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + Project [ca_address_sk] + Filter [ca_county,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (8) + Filter [cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/explain.txt new file mode 100644 index 000000000..2c9f35aea --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/explain.txt @@ -0,0 +1,477 @@ +== Physical Plan == +TakeOrderedAndProject (71) ++- * Project (70) + +- * BroadcastHashJoin Inner BuildRight (69) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * Project (28) + : : +- * BroadcastHashJoin Inner BuildRight (27) + : : :- * Project (25) + : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : :- * Filter (19) + : : : : +- * ColumnarToRow (18) + : : : : +- CometScan parquet spark_catalog.default.customer (17) + : : : +- BroadcastExchange (23) + : : : +- * Filter (22) + : : : +- * ColumnarToRow (21) + : : : +- CometScan parquet spark_catalog.default.store_sales (20) + : : +- ReusedExchange (26) + : +- BroadcastExchange (50) + : +- * Filter (49) + : +- * HashAggregate (48) + : +- Exchange (47) + : +- * HashAggregate (46) + : +- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (42) + : : +- * BroadcastHashJoin Inner BuildRight (41) + : : :- * Filter (36) + : : : +- * ColumnarToRow (35) + : : : +- CometScan parquet spark_catalog.default.customer (34) + : : +- BroadcastExchange (40) + : : +- * Filter (39) + : : +- * ColumnarToRow (38) + : : +- CometScan parquet spark_catalog.default.web_sales (37) + : +- ReusedExchange (43) + +- BroadcastExchange (68) + +- * HashAggregate (67) + +- Exchange (66) + +- * HashAggregate (65) + +- * Project (64) + +- * BroadcastHashJoin Inner BuildRight (63) + :- * Project (61) + : +- * BroadcastHashJoin Inner BuildRight (60) + : :- * Filter (55) + : : +- * ColumnarToRow (54) + : : +- CometScan parquet spark_catalog.default.customer (53) + : +- BroadcastExchange (59) + : +- * Filter (58) + : +- * ColumnarToRow (57) + : +- CometScan parquet spark_catalog.default.web_sales (56) + +- ReusedExchange (62) + + +(1) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] + +(3) Filter [codegen id : 3] +Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_sold_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] + +(6) Filter [codegen id : 1] +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Condition : isnotnull(ss_customer_sk#9) + +(7) BroadcastExchange +Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#9] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Input [12]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] + +(10) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#14, d_year#15] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#12] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, d_year#15] +Input [12]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12, d_date_sk#14, d_year#15] + +(13) HashAggregate [codegen id : 3] +Input [10]: [c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, ss_ext_discount_amt#10, ss_ext_list_price#11, d_year#15] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Functions [1]: [partial_sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))] +Aggregate Attributes [1]: [sum#16] +Results [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] + +(14) Exchange +Input [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] +Arguments: hashpartitioning(c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 16] +Input [9]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8, sum#17] +Keys [8]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#15, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Functions [1]: [sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))#18] +Results [2]: [c_customer_id#2 AS customer_id#19, MakeDecimal(sum(UnscaledValue((ss_ext_list_price#11 - ss_ext_discount_amt#10)))#18,18,2) AS year_total#20] + +(16) Filter [codegen id : 16] +Input [2]: [customer_id#19, year_total#20] +Condition : (isnotnull(year_total#20) AND (year_total#20 > 0.00)) + +(17) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 6] +Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] + +(19) Filter [codegen id : 6] +Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_customer_id#22)) + +(20) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#32), dynamicpruningexpression(ss_sold_date_sk#32 IN dynamicpruning#33)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] + +(22) Filter [codegen id : 4] +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Condition : isnotnull(ss_customer_sk#29) + +(23) BroadcastExchange +Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_customer_sk#21] +Right keys [1]: [ss_customer_sk#29] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Input [12]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] + +(26) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#34, d_year#35] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#32] +Right keys [1]: [d_date_sk#34] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, d_year#35] +Input [12]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32, d_date_sk#34, d_year#35] + +(29) HashAggregate [codegen id : 6] +Input [10]: [c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, ss_ext_discount_amt#30, ss_ext_list_price#31, d_year#35] +Keys [8]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Functions [1]: [partial_sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))] +Aggregate Attributes [1]: [sum#36] +Results [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] + +(30) Exchange +Input [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] +Arguments: hashpartitioning(c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [9]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28, sum#37] +Keys [8]: [c_customer_id#22, c_first_name#23, c_last_name#24, d_year#35, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Functions [1]: [sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))#18] +Results [5]: [c_customer_id#22 AS customer_id#38, c_first_name#23 AS customer_first_name#39, c_last_name#24 AS customer_last_name#40, c_email_address#28 AS customer_email_address#41, MakeDecimal(sum(UnscaledValue((ss_ext_list_price#31 - ss_ext_discount_amt#30)))#18,18,2) AS year_total#42] + +(32) BroadcastExchange +Input [5]: [customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41, year_total#42] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#38] +Join type: Inner +Join condition: None + +(34) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#43, c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 10] +Input [8]: [c_customer_sk#43, c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50] + +(36) Filter [codegen id : 10] +Input [8]: [c_customer_sk#43, c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50] +Condition : (isnotnull(c_customer_sk#43) AND isnotnull(c_customer_id#44)) + +(37) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#54), dynamicpruningexpression(ws_sold_date_sk#54 IN dynamicpruning#55)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(38) ColumnarToRow [codegen id : 8] +Input [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] + +(39) Filter [codegen id : 8] +Input [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] +Condition : isnotnull(ws_bill_customer_sk#51) + +(40) BroadcastExchange +Input [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(41) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [c_customer_sk#43] +Right keys [1]: [ws_bill_customer_sk#51] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 10] +Output [10]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] +Input [12]: [c_customer_sk#43, c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] + +(43) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#56, d_year#57] + +(44) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#54] +Right keys [1]: [d_date_sk#56] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 10] +Output [10]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, ws_ext_discount_amt#52, ws_ext_list_price#53, d_year#57] +Input [12]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54, d_date_sk#56, d_year#57] + +(46) HashAggregate [codegen id : 10] +Input [10]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, ws_ext_discount_amt#52, ws_ext_list_price#53, d_year#57] +Keys [8]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57] +Functions [1]: [partial_sum(UnscaledValue((ws_ext_list_price#53 - ws_ext_discount_amt#52)))] +Aggregate Attributes [1]: [sum#58] +Results [9]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57, sum#59] + +(47) Exchange +Input [9]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57, sum#59] +Arguments: hashpartitioning(c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(48) HashAggregate [codegen id : 11] +Input [9]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57, sum#59] +Keys [8]: [c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50, d_year#57] +Functions [1]: [sum(UnscaledValue((ws_ext_list_price#53 - ws_ext_discount_amt#52)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ws_ext_list_price#53 - ws_ext_discount_amt#52)))#60] +Results [2]: [c_customer_id#44 AS customer_id#61, MakeDecimal(sum(UnscaledValue((ws_ext_list_price#53 - ws_ext_discount_amt#52)))#60,18,2) AS year_total#62] + +(49) Filter [codegen id : 11] +Input [2]: [customer_id#61, year_total#62] +Condition : (isnotnull(year_total#62) AND (year_total#62 > 0.00)) + +(50) BroadcastExchange +Input [2]: [customer_id#61, year_total#62] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(51) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#61] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 16] +Output [8]: [customer_id#19, year_total#20, customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41, year_total#42, year_total#62] +Input [9]: [customer_id#19, year_total#20, customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41, year_total#42, customer_id#61, year_total#62] + +(53) Scan parquet spark_catalog.default.customer +Output [8]: [c_customer_sk#63, c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(54) ColumnarToRow [codegen id : 14] +Input [8]: [c_customer_sk#63, c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70] + +(55) Filter [codegen id : 14] +Input [8]: [c_customer_sk#63, c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70] +Condition : (isnotnull(c_customer_sk#63) AND isnotnull(c_customer_id#64)) + +(56) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#74), dynamicpruningexpression(ws_sold_date_sk#74 IN dynamicpruning#75)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(57) ColumnarToRow [codegen id : 12] +Input [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] + +(58) Filter [codegen id : 12] +Input [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] +Condition : isnotnull(ws_bill_customer_sk#71) + +(59) BroadcastExchange +Input [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [c_customer_sk#63] +Right keys [1]: [ws_bill_customer_sk#71] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 14] +Output [10]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] +Input [12]: [c_customer_sk#63, c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] + +(62) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#76, d_year#77] + +(63) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_sold_date_sk#74] +Right keys [1]: [d_date_sk#76] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 14] +Output [10]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, ws_ext_discount_amt#72, ws_ext_list_price#73, d_year#77] +Input [12]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74, d_date_sk#76, d_year#77] + +(65) HashAggregate [codegen id : 14] +Input [10]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, ws_ext_discount_amt#72, ws_ext_list_price#73, d_year#77] +Keys [8]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77] +Functions [1]: [partial_sum(UnscaledValue((ws_ext_list_price#73 - ws_ext_discount_amt#72)))] +Aggregate Attributes [1]: [sum#78] +Results [9]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77, sum#79] + +(66) Exchange +Input [9]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77, sum#79] +Arguments: hashpartitioning(c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(67) HashAggregate [codegen id : 15] +Input [9]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77, sum#79] +Keys [8]: [c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70, d_year#77] +Functions [1]: [sum(UnscaledValue((ws_ext_list_price#73 - ws_ext_discount_amt#72)))] +Aggregate Attributes [1]: [sum(UnscaledValue((ws_ext_list_price#73 - ws_ext_discount_amt#72)))#60] +Results [2]: [c_customer_id#64 AS customer_id#80, MakeDecimal(sum(UnscaledValue((ws_ext_list_price#73 - ws_ext_discount_amt#72)))#60,18,2) AS year_total#81] + +(68) BroadcastExchange +Input [2]: [customer_id#80, year_total#81] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=11] + +(69) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#19] +Right keys [1]: [customer_id#80] +Join type: Inner +Join condition: (CASE WHEN (year_total#62 > 0.00) THEN (year_total#81 / year_total#62) ELSE 0E-20 END > CASE WHEN (year_total#20 > 0.00) THEN (year_total#42 / year_total#20) ELSE 0E-20 END) + +(70) Project [codegen id : 16] +Output [4]: [customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41] +Input [10]: [customer_id#19, year_total#20, customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41, year_total#42, year_total#62, customer_id#80, year_total#81] + +(71) TakeOrderedAndProject +Input [4]: [customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41] +Arguments: 100, [customer_id#38 ASC NULLS FIRST, customer_first_name#39 ASC NULLS FIRST, customer_last_name#40 ASC NULLS FIRST, customer_email_address#41 ASC NULLS FIRST], [customer_id#38, customer_first_name#39, customer_last_name#40, customer_email_address#41] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (75) ++- * Filter (74) + +- * ColumnarToRow (73) + +- CometScan parquet spark_catalog.default.date_dim (72) + + +(72) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(73) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#15] + +(74) Filter [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#15] +Condition : ((isnotnull(d_year#15) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#14)) + +(75) BroadcastExchange +Input [2]: [d_date_sk#14, d_year#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#32 IN dynamicpruning#33 +BroadcastExchange (79) ++- * Filter (78) + +- * ColumnarToRow (77) + +- CometScan parquet spark_catalog.default.date_dim (76) + + +(76) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#34, d_year#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(77) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#34, d_year#35] + +(78) Filter [codegen id : 1] +Input [2]: [d_date_sk#34, d_year#35] +Condition : ((isnotnull(d_year#35) AND (d_year#35 = 2002)) AND isnotnull(d_date_sk#34)) + +(79) BroadcastExchange +Input [2]: [d_date_sk#34, d_year#35] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +Subquery:3 Hosting operator id = 37 Hosting Expression = ws_sold_date_sk#54 IN dynamicpruning#13 + +Subquery:4 Hosting operator id = 56 Hosting Expression = ws_sold_date_sk#74 IN dynamicpruning#33 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/simplified.txt new file mode 100644 index 000000000..172da54ae --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/simplified.txt @@ -0,0 +1,122 @@ +TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,customer_email_address] + WholeStageCodegen (16) + Project [customer_id,customer_first_name,customer_last_name,customer_email_address] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,year_total,customer_id,customer_first_name,customer_last_name,customer_email_address,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + BroadcastHashJoin [customer_id,customer_id] + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,sum] [sum(UnscaledValue((ss_ext_list_price - ss_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] #1 + WholeStageCodegen (3) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_list_price,ss_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,sum] [sum(UnscaledValue((ss_ext_list_price - ss_ext_discount_amt))),customer_id,customer_first_name,customer_last_name,customer_email_address,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] #5 + WholeStageCodegen (6) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_list_price,ss_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum] [sum(UnscaledValue((ws_ext_list_price - ws_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #9 + WholeStageCodegen (10) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,sum] [sum(UnscaledValue((ws_ext_list_price - ws_ext_discount_amt))),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year] #12 + WholeStageCodegen (14) + HashAggregate [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,d_year,ws_ext_list_price,ws_ext_discount_amt] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (12) + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/explain.txt new file mode 100644 index 000000000..233ef7cb0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/explain.txt @@ -0,0 +1,150 @@ +== Physical Plan == +TakeOrderedAndProject (20) ++- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.web_sales (1) + : +- BroadcastExchange (7) + : +- * Filter (6) + : +- * ColumnarToRow (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] + +(3) Filter [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(6) Filter [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 25] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [ws_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [ws_ext_sales_price#2, ws_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [ws_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#2))#14] +Results [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#2))#14,17,2) AS _w0#16] + +(16) Exchange +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18] +Input [8]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, _we0#17] + +(20) TakeOrderedAndProject +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] +Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (25) ++- * Project (24) + +- * Filter (23) + +- * ColumnarToRow (22) + +- CometScan parquet spark_catalog.default.date_dim (21) + + +(21) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(22) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] + +(23) Filter [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(24) Project [codegen id : 1] +Output [1]: [d_date_sk#11] +Input [2]: [d_date_sk#11, d_date#19] + +(25) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/simplified.txt new file mode 100644 index 000000000..689e8ae67 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/simplified.txt @@ -0,0 +1,40 @@ +TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_current_price,itemrevenue] + WholeStageCodegen (6) + Project [i_item_id,i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(ws_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #2 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,ws_ext_sales_price] [sum,sum] + Project [ws_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_ext_sales_price,ws_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [i_category,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/explain.txt new file mode 100644 index 000000000..04118281e --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/explain.txt @@ -0,0 +1,759 @@ +== Physical Plan == +TakeOrderedAndProject (84) ++- * BroadcastHashJoin Inner BuildRight (83) + :- * Filter (66) + : +- * HashAggregate (65) + : +- Exchange (64) + : +- * HashAggregate (63) + : +- * Project (62) + : +- * BroadcastHashJoin Inner BuildRight (61) + : :- * Project (59) + : : +- * BroadcastHashJoin Inner BuildRight (58) + : : :- * BroadcastHashJoin LeftSemi BuildRight (51) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- BroadcastExchange (50) + : : : +- * Project (49) + : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : :- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : +- BroadcastExchange (47) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) + : : : :- * HashAggregate (35) + : : : : +- Exchange (34) + : : : : +- * HashAggregate (33) + : : : : +- * Project (32) + : : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : : :- * Project (29) + : : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : : :- * Filter (9) + : : : : : : +- * ColumnarToRow (8) + : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) + : : : : : +- BroadcastExchange (27) + : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) + : : : : : :- * Filter (12) + : : : : : : +- * ColumnarToRow (11) + : : : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : : : +- BroadcastExchange (25) + : : : : : +- * Project (24) + : : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : : :- * Project (21) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : :- * Filter (15) + : : : : : : : +- * ColumnarToRow (14) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) + : : : : : : +- BroadcastExchange (19) + : : : : : : +- * Filter (18) + : : : : : : +- * ColumnarToRow (17) + : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : +- ReusedExchange (22) + : : : : +- ReusedExchange (30) + : : : +- BroadcastExchange (45) + : : : +- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * Project (41) + : : : : +- * BroadcastHashJoin Inner BuildRight (40) + : : : : :- * Filter (38) + : : : : : +- * ColumnarToRow (37) + : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) + : : : : +- ReusedExchange (39) + : : : +- ReusedExchange (42) + : : +- BroadcastExchange (57) + : : +- * BroadcastHashJoin LeftSemi BuildRight (56) + : : :- * Filter (54) + : : : +- * ColumnarToRow (53) + : : : +- CometScan parquet spark_catalog.default.item (52) + : : +- ReusedExchange (55) + : +- ReusedExchange (60) + +- BroadcastExchange (82) + +- * Filter (81) + +- * HashAggregate (80) + +- Exchange (79) + +- * HashAggregate (78) + +- * Project (77) + +- * BroadcastHashJoin Inner BuildRight (76) + :- * Project (74) + : +- * BroadcastHashJoin Inner BuildRight (73) + : :- * BroadcastHashJoin LeftSemi BuildRight (71) + : : :- * Filter (69) + : : : +- * ColumnarToRow (68) + : : : +- CometScan parquet spark_catalog.default.store_sales (67) + : : +- ReusedExchange (70) + : +- ReusedExchange (72) + +- ReusedExchange (75) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] + +(6) Filter [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) + +(7) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] + +(9) Filter [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) + +(10) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(12) Filter [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) + +(13) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] + +(15) Filter [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) + +(16) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(18) Filter [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) + +(19) BroadcastExchange +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(20) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#17] +Right keys [1]: [i_item_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 3] +Output [4]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23] +Input [6]: [cs_item_sk#17, cs_sold_date_sk#18, i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(22) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#24] + +(23) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#18] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 3] +Output [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Input [5]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23, d_date_sk#24] + +(25) BroadcastExchange +Input [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=2] + +(26) BroadcastHashJoin [codegen id : 4] +Left keys [6]: [coalesce(i_brand_id#14, 0), isnull(i_brand_id#14), coalesce(i_class_id#15, 0), isnull(i_class_id#15), coalesce(i_category_id#16, 0), isnull(i_category_id#16)] +Right keys [6]: [coalesce(i_brand_id#21, 0), isnull(i_brand_id#21), coalesce(i_class_id#22, 0), isnull(i_class_id#22), coalesce(i_category_id#23, 0), isnull(i_category_id#23)] +Join type: LeftSemi +Join condition: None + +(27) BroadcastExchange +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_item_sk#10] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [4]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16] +Input [6]: [ss_item_sk#10, ss_sold_date_sk#11, i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(30) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 6] +Output [3]: [i_brand_id#14 AS brand_id#26, i_class_id#15 AS class_id#27, i_category_id#16 AS category_id#28] +Input [5]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16, d_date_sk#25] + +(33) HashAggregate [codegen id : 6] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(34) Exchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: hashpartitioning(brand_id#26, class_id#27, category_id#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(35) HashAggregate [codegen id : 10] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(36) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_sold_date_sk#30 IN dynamicpruning#31)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(37) ColumnarToRow [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] + +(38) Filter [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) + +(39) ReusedExchange [Reuses operator id: 19] +Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(40) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_item_sk#29] +Right keys [1]: [i_item_sk#32] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 9] +Output [4]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35] +Input [6]: [ws_item_sk#29, ws_sold_date_sk#30, i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(42) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#36] + +(43) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_sold_date_sk#30] +Right keys [1]: [d_date_sk#36] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 9] +Output [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Input [5]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35, d_date_sk#36] + +(45) BroadcastExchange +Input [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=5] + +(46) BroadcastHashJoin [codegen id : 10] +Left keys [6]: [coalesce(brand_id#26, 0), isnull(brand_id#26), coalesce(class_id#27, 0), isnull(class_id#27), coalesce(category_id#28, 0), isnull(category_id#28)] +Right keys [6]: [coalesce(i_brand_id#33, 0), isnull(i_brand_id#33), coalesce(i_class_id#34, 0), isnull(i_class_id#34), coalesce(i_category_id#35, 0), isnull(i_category_id#35)] +Join type: LeftSemi +Join condition: None + +(47) BroadcastExchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: HashedRelationBroadcastMode(List(input[0, int, true], input[1, int, true], input[2, int, true]),false), [plan_id=6] + +(48) BroadcastHashJoin [codegen id : 11] +Left keys [3]: [i_brand_id#7, i_class_id#8, i_category_id#9] +Right keys [3]: [brand_id#26, class_id#27, category_id#28] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 11] +Output [1]: [i_item_sk#6 AS ss_item_sk#37] +Input [7]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9, brand_id#26, class_id#27, category_id#28] + +(50) BroadcastExchange +Input [1]: [ss_item_sk#37] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(51) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(52) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(53) ColumnarToRow [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(54) Filter [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : (((isnotnull(i_item_sk#38) AND isnotnull(i_brand_id#39)) AND isnotnull(i_class_id#40)) AND isnotnull(i_category_id#41)) + +(55) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#37] + +(56) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [i_item_sk#38] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(57) BroadcastExchange +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(58) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#38] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 25] +Output [6]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [8]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(60) ReusedExchange [Reuses operator id: 108] +Output [1]: [d_date_sk#42] + +(61) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#42] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 25] +Output [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [7]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41, d_date_sk#42] + +(63) HashAggregate [codegen id : 25] +Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [partial_sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), partial_count(1)] +Aggregate Attributes [3]: [sum#43, isEmpty#44, count#45] +Results [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] + +(64) Exchange +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Arguments: hashpartitioning(i_brand_id#39, i_class_id#40, i_category_id#41, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 52] +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49, count(1)#50] +Results [6]: [store AS channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49 AS sales#52, count(1)#50 AS number_sales#53] + +(66) Filter [codegen id : 52] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53] +Condition : (isnotnull(sales#52) AND (cast(sales#52 as decimal(32,6)) > cast(Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(67) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#59), dynamicpruningexpression(ss_sold_date_sk#59 IN dynamicpruning#60)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(68) ColumnarToRow [codegen id : 50] +Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] + +(69) Filter [codegen id : 50] +Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] +Condition : isnotnull(ss_item_sk#56) + +(70) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#61] + +(71) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_item_sk#56] +Right keys [1]: [ss_item_sk#61] +Join type: LeftSemi +Join condition: None + +(72) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(73) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_item_sk#56] +Right keys [1]: [i_item_sk#62] +Join type: Inner +Join condition: None + +(74) Project [codegen id : 50] +Output [6]: [ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [8]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(75) ReusedExchange [Reuses operator id: 122] +Output [1]: [d_date_sk#66] + +(76) BroadcastHashJoin [codegen id : 50] +Left keys [1]: [ss_sold_date_sk#59] +Right keys [1]: [d_date_sk#66] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 50] +Output [5]: [ss_quantity#57, ss_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [7]: [ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65, d_date_sk#66] + +(78) HashAggregate [codegen id : 50] +Input [5]: [ss_quantity#57, ss_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [partial_sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58)), partial_count(1)] +Aggregate Attributes [3]: [sum#67, isEmpty#68, count#69] +Results [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] + +(79) Exchange +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Arguments: hashpartitioning(i_brand_id#63, i_class_id#64, i_category_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(80) HashAggregate [codegen id : 51] +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58))#73, count(1)#74] +Results [6]: [store AS channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sum((cast(ss_quantity#57 as decimal(10,0)) * ss_list_price#58))#73 AS sales#76, count(1)#74 AS number_sales#77] + +(81) Filter [codegen id : 51] +Input [6]: [channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Condition : (isnotnull(sales#76) AND (cast(sales#76 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(82) BroadcastExchange +Input [6]: [channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Arguments: HashedRelationBroadcastMode(List(input[1, int, true], input[2, int, true], input[3, int, true]),false), [plan_id=11] + +(83) BroadcastHashJoin [codegen id : 52] +Left keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Right keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Join type: Inner +Join condition: None + +(84) TakeOrderedAndProject +Input [12]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53, channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Arguments: 100, [i_brand_id#39 ASC NULLS FIRST, i_class_id#40 ASC NULLS FIRST, i_category_id#41 ASC NULLS FIRST], [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53, channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 66 Hosting Expression = Subquery scalar-subquery#54, [id=#55] +* HashAggregate (103) ++- Exchange (102) + +- * HashAggregate (101) + +- Union (100) + :- * Project (89) + : +- * BroadcastHashJoin Inner BuildRight (88) + : :- * ColumnarToRow (86) + : : +- CometScan parquet spark_catalog.default.store_sales (85) + : +- ReusedExchange (87) + :- * Project (94) + : +- * BroadcastHashJoin Inner BuildRight (93) + : :- * ColumnarToRow (91) + : : +- CometScan parquet spark_catalog.default.catalog_sales (90) + : +- ReusedExchange (92) + +- * Project (99) + +- * BroadcastHashJoin Inner BuildRight (98) + :- * ColumnarToRow (96) + : +- CometScan parquet spark_catalog.default.web_sales (95) + +- ReusedExchange (97) + + +(85) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#80), dynamicpruningexpression(ss_sold_date_sk#80 IN dynamicpruning#81)] +ReadSchema: struct + +(86) ColumnarToRow [codegen id : 2] +Input [3]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80] + +(87) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#82] + +(88) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#80] +Right keys [1]: [d_date_sk#82] +Join type: Inner +Join condition: None + +(89) Project [codegen id : 2] +Output [2]: [ss_quantity#78 AS quantity#83, ss_list_price#79 AS list_price#84] +Input [4]: [ss_quantity#78, ss_list_price#79, ss_sold_date_sk#80, d_date_sk#82] + +(90) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#87), dynamicpruningexpression(cs_sold_date_sk#87 IN dynamicpruning#88)] +ReadSchema: struct + +(91) ColumnarToRow [codegen id : 4] +Input [3]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87] + +(92) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#89] + +(93) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#87] +Right keys [1]: [d_date_sk#89] +Join type: Inner +Join condition: None + +(94) Project [codegen id : 4] +Output [2]: [cs_quantity#85 AS quantity#90, cs_list_price#86 AS list_price#91] +Input [4]: [cs_quantity#85, cs_list_price#86, cs_sold_date_sk#87, d_date_sk#89] + +(95) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#94), dynamicpruningexpression(ws_sold_date_sk#94 IN dynamicpruning#95)] +ReadSchema: struct + +(96) ColumnarToRow [codegen id : 6] +Input [3]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94] + +(97) ReusedExchange [Reuses operator id: 117] +Output [1]: [d_date_sk#96] + +(98) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#94] +Right keys [1]: [d_date_sk#96] +Join type: Inner +Join condition: None + +(99) Project [codegen id : 6] +Output [2]: [ws_quantity#92 AS quantity#97, ws_list_price#93 AS list_price#98] +Input [4]: [ws_quantity#92, ws_list_price#93, ws_sold_date_sk#94, d_date_sk#96] + +(100) Union + +(101) HashAggregate [codegen id : 7] +Input [2]: [quantity#83, list_price#84] +Keys: [] +Functions [1]: [partial_avg((cast(quantity#83 as decimal(10,0)) * list_price#84))] +Aggregate Attributes [2]: [sum#99, count#100] +Results [2]: [sum#101, count#102] + +(102) Exchange +Input [2]: [sum#101, count#102] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=12] + +(103) HashAggregate [codegen id : 8] +Input [2]: [sum#101, count#102] +Keys: [] +Functions [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))] +Aggregate Attributes [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))#103] +Results [1]: [avg((cast(quantity#83 as decimal(10,0)) * list_price#84))#103 AS average_sales#104] + +Subquery:2 Hosting operator id = 85 Hosting Expression = ss_sold_date_sk#80 IN dynamicpruning#12 + +Subquery:3 Hosting operator id = 90 Hosting Expression = cs_sold_date_sk#87 IN dynamicpruning#12 + +Subquery:4 Hosting operator id = 95 Hosting Expression = ws_sold_date_sk#94 IN dynamicpruning#12 + +Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (108) ++- * Project (107) + +- * Filter (106) + +- * ColumnarToRow (105) + +- CometScan parquet spark_catalog.default.date_dim (104) + + +(104) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#42, d_week_seq#105] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#106), IsNotNull(d_date_sk)] +ReadSchema: struct + +(105) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#42, d_week_seq#105] + +(106) Filter [codegen id : 1] +Input [2]: [d_date_sk#42, d_week_seq#105] +Condition : ((isnotnull(d_week_seq#105) AND (d_week_seq#105 = ReusedSubquery Subquery scalar-subquery#106, [id=#107])) AND isnotnull(d_date_sk#42)) + +(107) Project [codegen id : 1] +Output [1]: [d_date_sk#42] +Input [2]: [d_date_sk#42, d_week_seq#105] + +(108) BroadcastExchange +Input [1]: [d_date_sk#42] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:6 Hosting operator id = 106 Hosting Expression = ReusedSubquery Subquery scalar-subquery#106, [id=#107] + +Subquery:7 Hosting operator id = 104 Hosting Expression = Subquery scalar-subquery#106, [id=#107] +* Project (112) ++- * Filter (111) + +- * ColumnarToRow (110) + +- CometScan parquet spark_catalog.default.date_dim (109) + + +(109) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1999), EqualTo(d_moy,12), EqualTo(d_dom,16)] +ReadSchema: struct + +(110) ColumnarToRow [codegen id : 1] +Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] + +(111) Filter [codegen id : 1] +Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Condition : (((((isnotnull(d_year#109) AND isnotnull(d_moy#110)) AND isnotnull(d_dom#111)) AND (d_year#109 = 1999)) AND (d_moy#110 = 12)) AND (d_dom#111 = 16)) + +(112) Project [codegen id : 1] +Output [1]: [d_week_seq#108] +Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] + +Subquery:8 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 +BroadcastExchange (117) ++- * Project (116) + +- * Filter (115) + +- * ColumnarToRow (114) + +- CometScan parquet spark_catalog.default.date_dim (113) + + +(113) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#112] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1998), LessThanOrEqual(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(114) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#112] + +(115) Filter [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#112] +Condition : (((isnotnull(d_year#112) AND (d_year#112 >= 1998)) AND (d_year#112 <= 2000)) AND isnotnull(d_date_sk#25)) + +(116) Project [codegen id : 1] +Output [1]: [d_date_sk#25] +Input [2]: [d_date_sk#25, d_year#112] + +(117) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] + +Subquery:9 Hosting operator id = 13 Hosting Expression = cs_sold_date_sk#18 IN dynamicpruning#12 + +Subquery:10 Hosting operator id = 36 Hosting Expression = ws_sold_date_sk#30 IN dynamicpruning#12 + +Subquery:11 Hosting operator id = 81 Hosting Expression = ReusedSubquery Subquery scalar-subquery#54, [id=#55] + +Subquery:12 Hosting operator id = 67 Hosting Expression = ss_sold_date_sk#59 IN dynamicpruning#60 +BroadcastExchange (122) ++- * Project (121) + +- * Filter (120) + +- * ColumnarToRow (119) + +- CometScan parquet spark_catalog.default.date_dim (118) + + +(118) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#66, d_week_seq#113] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#114), IsNotNull(d_date_sk)] +ReadSchema: struct + +(119) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#66, d_week_seq#113] + +(120) Filter [codegen id : 1] +Input [2]: [d_date_sk#66, d_week_seq#113] +Condition : ((isnotnull(d_week_seq#113) AND (d_week_seq#113 = ReusedSubquery Subquery scalar-subquery#114, [id=#115])) AND isnotnull(d_date_sk#66)) + +(121) Project [codegen id : 1] +Output [1]: [d_date_sk#66] +Input [2]: [d_date_sk#66, d_week_seq#113] + +(122) BroadcastExchange +Input [1]: [d_date_sk#66] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15] + +Subquery:13 Hosting operator id = 120 Hosting Expression = ReusedSubquery Subquery scalar-subquery#114, [id=#115] + +Subquery:14 Hosting operator id = 118 Hosting Expression = Subquery scalar-subquery#114, [id=#115] +* Project (126) ++- * Filter (125) + +- * ColumnarToRow (124) + +- CometScan parquet spark_catalog.default.date_dim (123) + + +(123) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1998), EqualTo(d_moy,12), EqualTo(d_dom,16)] +ReadSchema: struct + +(124) ColumnarToRow [codegen id : 1] +Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] + +(125) Filter [codegen id : 1] +Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Condition : (((((isnotnull(d_year#117) AND isnotnull(d_moy#118)) AND isnotnull(d_dom#119)) AND (d_year#117 = 1998)) AND (d_moy#118 = 12)) AND (d_dom#119 = 16)) + +(126) Project [codegen id : 1] +Output [1]: [d_week_seq#116] +Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/simplified.txt new file mode 100644 index 000000000..64646b717 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/simplified.txt @@ -0,0 +1,204 @@ +TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_sales,channel,i_brand_id,i_class_id,i_category_id,sales,number_sales] + WholeStageCodegen (52) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + Filter [sales] + Subquery #4 + WholeStageCodegen (8) + HashAggregate [sum,count] [avg((cast(quantity as decimal(10,0)) * list_price)),average_sales,sum,count] + InputAdapter + Exchange #12 + WholeStageCodegen (7) + HashAggregate [quantity,list_price] [sum,count,sum,count] + InputAdapter + Union + WholeStageCodegen (2) + Project [ss_quantity,ss_list_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_list_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + WholeStageCodegen (4) + Project [cs_quantity,cs_list_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_quantity,cs_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + WholeStageCodegen (6) + Project [ws_quantity,ws_list_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #6 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #1 + WholeStageCodegen (25) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #2 + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + Subquery #2 + WholeStageCodegen (1) + Project [d_week_seq] + Filter [d_year,d_moy,d_dom] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (11) + Project [i_item_sk] + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] + Filter [i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (10) + BroadcastHashJoin [brand_id,class_id,category_id,i_brand_id,i_class_id,i_category_id] + HashAggregate [brand_id,class_id,category_id] + InputAdapter + Exchange [brand_id,class_id,category_id] #5 + WholeStageCodegen (6) + HashAggregate [brand_id,class_id,category_id] + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #3 + BroadcastExchange #6 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (4) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (3) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (1) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (9) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #3 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #9 + InputAdapter + ReusedExchange [d_date_sk] #6 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (23) + BroadcastHashJoin [i_item_sk,ss_item_sk] + Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [ss_item_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (51) + Filter [sales] + ReusedSubquery [average_sales] #4 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #14 + WholeStageCodegen (50) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #5 + BroadcastExchange #15 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #6 + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + Subquery #6 + WholeStageCodegen (1) + Project [d_week_seq] + Filter [d_year,d_moy,d_dom] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] + InputAdapter + ReusedExchange [ss_item_sk] #3 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #11 + InputAdapter + ReusedExchange [d_date_sk] #15 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/explain.txt new file mode 100644 index 000000000..4dd70ec51 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/explain.txt @@ -0,0 +1,964 @@ +== Physical Plan == +TakeOrderedAndProject (125) ++- * HashAggregate (124) + +- Exchange (123) + +- * HashAggregate (122) + +- Union (121) + :- * HashAggregate (100) + : +- Exchange (99) + : +- * HashAggregate (98) + : +- Union (97) + : :- * Filter (66) + : : +- * HashAggregate (65) + : : +- Exchange (64) + : : +- * HashAggregate (63) + : : +- * Project (62) + : : +- * BroadcastHashJoin Inner BuildRight (61) + : : :- * Project (59) + : : : +- * BroadcastHashJoin Inner BuildRight (58) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (51) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- BroadcastExchange (50) + : : : : +- * Project (49) + : : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : : :- * Filter (6) + : : : : : +- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : : +- BroadcastExchange (47) + : : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) + : : : : :- * HashAggregate (35) + : : : : : +- Exchange (34) + : : : : : +- * HashAggregate (33) + : : : : : +- * Project (32) + : : : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : : : :- * Project (29) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : : : :- * Filter (9) + : : : : : : : +- * ColumnarToRow (8) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) + : : : : : : +- BroadcastExchange (27) + : : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) + : : : : : : :- * Filter (12) + : : : : : : : +- * ColumnarToRow (11) + : : : : : : : +- CometScan parquet spark_catalog.default.item (10) + : : : : : : +- BroadcastExchange (25) + : : : : : : +- * Project (24) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : : : :- * Project (21) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : : :- * Filter (15) + : : : : : : : : +- * ColumnarToRow (14) + : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) + : : : : : : : +- BroadcastExchange (19) + : : : : : : : +- * Filter (18) + : : : : : : : +- * ColumnarToRow (17) + : : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : : +- ReusedExchange (22) + : : : : : +- ReusedExchange (30) + : : : : +- BroadcastExchange (45) + : : : : +- * Project (44) + : : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : : :- * Project (41) + : : : : : +- * BroadcastHashJoin Inner BuildRight (40) + : : : : : :- * Filter (38) + : : : : : : +- * ColumnarToRow (37) + : : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) + : : : : : +- ReusedExchange (39) + : : : : +- ReusedExchange (42) + : : : +- BroadcastExchange (57) + : : : +- * BroadcastHashJoin LeftSemi BuildRight (56) + : : : :- * Filter (54) + : : : : +- * ColumnarToRow (53) + : : : : +- CometScan parquet spark_catalog.default.item (52) + : : : +- ReusedExchange (55) + : : +- ReusedExchange (60) + : :- * Filter (81) + : : +- * HashAggregate (80) + : : +- Exchange (79) + : : +- * HashAggregate (78) + : : +- * Project (77) + : : +- * BroadcastHashJoin Inner BuildRight (76) + : : :- * Project (74) + : : : +- * BroadcastHashJoin Inner BuildRight (73) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (71) + : : : : :- * Filter (69) + : : : : : +- * ColumnarToRow (68) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (67) + : : : : +- ReusedExchange (70) + : : : +- ReusedExchange (72) + : : +- ReusedExchange (75) + : +- * Filter (96) + : +- * HashAggregate (95) + : +- Exchange (94) + : +- * HashAggregate (93) + : +- * Project (92) + : +- * BroadcastHashJoin Inner BuildRight (91) + : :- * Project (89) + : : +- * BroadcastHashJoin Inner BuildRight (88) + : : :- * BroadcastHashJoin LeftSemi BuildRight (86) + : : : :- * Filter (84) + : : : : +- * ColumnarToRow (83) + : : : : +- CometScan parquet spark_catalog.default.web_sales (82) + : : : +- ReusedExchange (85) + : : +- ReusedExchange (87) + : +- ReusedExchange (90) + :- * HashAggregate (105) + : +- Exchange (104) + : +- * HashAggregate (103) + : +- * HashAggregate (102) + : +- ReusedExchange (101) + :- * HashAggregate (110) + : +- Exchange (109) + : +- * HashAggregate (108) + : +- * HashAggregate (107) + : +- ReusedExchange (106) + :- * HashAggregate (115) + : +- Exchange (114) + : +- * HashAggregate (113) + : +- * HashAggregate (112) + : +- ReusedExchange (111) + +- * HashAggregate (120) + +- Exchange (119) + +- * HashAggregate (118) + +- * HashAggregate (117) + +- ReusedExchange (116) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 25] +Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] + +(6) Filter [codegen id : 11] +Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) + +(7) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] + +(9) Filter [codegen id : 6] +Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) + +(10) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(12) Filter [codegen id : 4] +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) + +(13) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_sold_date_sk#18 IN dynamicpruning#19)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] + +(15) Filter [codegen id : 3] +Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) + +(16) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(18) Filter [codegen id : 1] +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) + +(19) BroadcastExchange +Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(20) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#17] +Right keys [1]: [i_item_sk#20] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 3] +Output [4]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23] +Input [6]: [cs_item_sk#17, cs_sold_date_sk#18, i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] + +(22) ReusedExchange [Reuses operator id: 159] +Output [1]: [d_date_sk#24] + +(23) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#18] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 3] +Output [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Input [5]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23, d_date_sk#24] + +(25) BroadcastExchange +Input [3]: [i_brand_id#21, i_class_id#22, i_category_id#23] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=2] + +(26) BroadcastHashJoin [codegen id : 4] +Left keys [6]: [coalesce(i_brand_id#14, 0), isnull(i_brand_id#14), coalesce(i_class_id#15, 0), isnull(i_class_id#15), coalesce(i_category_id#16, 0), isnull(i_category_id#16)] +Right keys [6]: [coalesce(i_brand_id#21, 0), isnull(i_brand_id#21), coalesce(i_class_id#22, 0), isnull(i_class_id#22), coalesce(i_category_id#23, 0), isnull(i_category_id#23)] +Join type: LeftSemi +Join condition: None + +(27) BroadcastExchange +Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(28) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_item_sk#10] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 6] +Output [4]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16] +Input [6]: [ss_item_sk#10, ss_sold_date_sk#11, i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] + +(30) ReusedExchange [Reuses operator id: 159] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 6] +Output [3]: [i_brand_id#14 AS brand_id#26, i_class_id#15 AS class_id#27, i_category_id#16 AS category_id#28] +Input [5]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16, d_date_sk#25] + +(33) HashAggregate [codegen id : 6] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(34) Exchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: hashpartitioning(brand_id#26, class_id#27, category_id#28, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(35) HashAggregate [codegen id : 10] +Input [3]: [brand_id#26, class_id#27, category_id#28] +Keys [3]: [brand_id#26, class_id#27, category_id#28] +Functions: [] +Aggregate Attributes: [] +Results [3]: [brand_id#26, class_id#27, category_id#28] + +(36) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_sold_date_sk#30 IN dynamicpruning#31)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(37) ColumnarToRow [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] + +(38) Filter [codegen id : 9] +Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) + +(39) ReusedExchange [Reuses operator id: 19] +Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(40) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_item_sk#29] +Right keys [1]: [i_item_sk#32] +Join type: Inner +Join condition: None + +(41) Project [codegen id : 9] +Output [4]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35] +Input [6]: [ws_item_sk#29, ws_sold_date_sk#30, i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] + +(42) ReusedExchange [Reuses operator id: 159] +Output [1]: [d_date_sk#36] + +(43) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ws_sold_date_sk#30] +Right keys [1]: [d_date_sk#36] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 9] +Output [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Input [5]: [ws_sold_date_sk#30, i_brand_id#33, i_class_id#34, i_category_id#35, d_date_sk#36] + +(45) BroadcastExchange +Input [3]: [i_brand_id#33, i_class_id#34, i_category_id#35] +Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=5] + +(46) BroadcastHashJoin [codegen id : 10] +Left keys [6]: [coalesce(brand_id#26, 0), isnull(brand_id#26), coalesce(class_id#27, 0), isnull(class_id#27), coalesce(category_id#28, 0), isnull(category_id#28)] +Right keys [6]: [coalesce(i_brand_id#33, 0), isnull(i_brand_id#33), coalesce(i_class_id#34, 0), isnull(i_class_id#34), coalesce(i_category_id#35, 0), isnull(i_category_id#35)] +Join type: LeftSemi +Join condition: None + +(47) BroadcastExchange +Input [3]: [brand_id#26, class_id#27, category_id#28] +Arguments: HashedRelationBroadcastMode(List(input[0, int, true], input[1, int, true], input[2, int, true]),false), [plan_id=6] + +(48) BroadcastHashJoin [codegen id : 11] +Left keys [3]: [i_brand_id#7, i_class_id#8, i_category_id#9] +Right keys [3]: [brand_id#26, class_id#27, category_id#28] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 11] +Output [1]: [i_item_sk#6 AS ss_item_sk#37] +Input [7]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9, brand_id#26, class_id#27, category_id#28] + +(50) BroadcastExchange +Input [1]: [ss_item_sk#37] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +(51) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(52) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(53) ColumnarToRow [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(54) Filter [codegen id : 23] +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : isnotnull(i_item_sk#38) + +(55) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#37] + +(56) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [i_item_sk#38] +Right keys [1]: [ss_item_sk#37] +Join type: LeftSemi +Join condition: None + +(57) BroadcastExchange +Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(58) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#38] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 25] +Output [6]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [8]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] + +(60) ReusedExchange [Reuses operator id: 154] +Output [1]: [d_date_sk#42] + +(61) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#42] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 25] +Output [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Input [7]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#39, i_class_id#40, i_category_id#41, d_date_sk#42] + +(63) HashAggregate [codegen id : 25] +Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#39, i_class_id#40, i_category_id#41] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [partial_sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), partial_count(1)] +Aggregate Attributes [3]: [sum#43, isEmpty#44, count#45] +Results [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] + +(64) Exchange +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Arguments: hashpartitioning(i_brand_id#39, i_class_id#40, i_category_id#41, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 26] +Input [6]: [i_brand_id#39, i_class_id#40, i_category_id#41, sum#46, isEmpty#47, count#48] +Keys [3]: [i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), count(1)] +Aggregate Attributes [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49, count(1)#50] +Results [6]: [store AS channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#49 AS sales#52, count(1)#50 AS number_sales#53] + +(66) Filter [codegen id : 26] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53] +Condition : (isnotnull(sales#52) AND (cast(sales#52 as decimal(32,6)) > cast(Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(67) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_item_sk#56, cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#59), dynamicpruningexpression(cs_sold_date_sk#59 IN dynamicpruning#60)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(68) ColumnarToRow [codegen id : 51] +Input [4]: [cs_item_sk#56, cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59] + +(69) Filter [codegen id : 51] +Input [4]: [cs_item_sk#56, cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59] +Condition : isnotnull(cs_item_sk#56) + +(70) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#61] + +(71) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_item_sk#56] +Right keys [1]: [ss_item_sk#61] +Join type: LeftSemi +Join condition: None + +(72) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(73) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_item_sk#56] +Right keys [1]: [i_item_sk#62] +Join type: Inner +Join condition: None + +(74) Project [codegen id : 51] +Output [6]: [cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [8]: [cs_item_sk#56, cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59, i_item_sk#62, i_brand_id#63, i_class_id#64, i_category_id#65] + +(75) ReusedExchange [Reuses operator id: 154] +Output [1]: [d_date_sk#66] + +(76) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [cs_sold_date_sk#59] +Right keys [1]: [d_date_sk#66] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 51] +Output [5]: [cs_quantity#57, cs_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Input [7]: [cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59, i_brand_id#63, i_class_id#64, i_category_id#65, d_date_sk#66] + +(78) HashAggregate [codegen id : 51] +Input [5]: [cs_quantity#57, cs_list_price#58, i_brand_id#63, i_class_id#64, i_category_id#65] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [partial_sum((cast(cs_quantity#57 as decimal(10,0)) * cs_list_price#58)), partial_count(1)] +Aggregate Attributes [3]: [sum#67, isEmpty#68, count#69] +Results [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] + +(79) Exchange +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Arguments: hashpartitioning(i_brand_id#63, i_class_id#64, i_category_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(80) HashAggregate [codegen id : 52] +Input [6]: [i_brand_id#63, i_class_id#64, i_category_id#65, sum#70, isEmpty#71, count#72] +Keys [3]: [i_brand_id#63, i_class_id#64, i_category_id#65] +Functions [2]: [sum((cast(cs_quantity#57 as decimal(10,0)) * cs_list_price#58)), count(1)] +Aggregate Attributes [2]: [sum((cast(cs_quantity#57 as decimal(10,0)) * cs_list_price#58))#73, count(1)#74] +Results [6]: [catalog AS channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sum((cast(cs_quantity#57 as decimal(10,0)) * cs_list_price#58))#73 AS sales#76, count(1)#74 AS number_sales#77] + +(81) Filter [codegen id : 52] +Input [6]: [channel#75, i_brand_id#63, i_class_id#64, i_category_id#65, sales#76, number_sales#77] +Condition : (isnotnull(sales#76) AND (cast(sales#76 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(82) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#78, ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#81), dynamicpruningexpression(ws_sold_date_sk#81 IN dynamicpruning#82)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(83) ColumnarToRow [codegen id : 77] +Input [4]: [ws_item_sk#78, ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81] + +(84) Filter [codegen id : 77] +Input [4]: [ws_item_sk#78, ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81] +Condition : isnotnull(ws_item_sk#78) + +(85) ReusedExchange [Reuses operator id: 50] +Output [1]: [ss_item_sk#83] + +(86) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_item_sk#78] +Right keys [1]: [ss_item_sk#83] +Join type: LeftSemi +Join condition: None + +(87) ReusedExchange [Reuses operator id: 57] +Output [4]: [i_item_sk#84, i_brand_id#85, i_class_id#86, i_category_id#87] + +(88) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_item_sk#78] +Right keys [1]: [i_item_sk#84] +Join type: Inner +Join condition: None + +(89) Project [codegen id : 77] +Output [6]: [ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81, i_brand_id#85, i_class_id#86, i_category_id#87] +Input [8]: [ws_item_sk#78, ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81, i_item_sk#84, i_brand_id#85, i_class_id#86, i_category_id#87] + +(90) ReusedExchange [Reuses operator id: 154] +Output [1]: [d_date_sk#88] + +(91) BroadcastHashJoin [codegen id : 77] +Left keys [1]: [ws_sold_date_sk#81] +Right keys [1]: [d_date_sk#88] +Join type: Inner +Join condition: None + +(92) Project [codegen id : 77] +Output [5]: [ws_quantity#79, ws_list_price#80, i_brand_id#85, i_class_id#86, i_category_id#87] +Input [7]: [ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81, i_brand_id#85, i_class_id#86, i_category_id#87, d_date_sk#88] + +(93) HashAggregate [codegen id : 77] +Input [5]: [ws_quantity#79, ws_list_price#80, i_brand_id#85, i_class_id#86, i_category_id#87] +Keys [3]: [i_brand_id#85, i_class_id#86, i_category_id#87] +Functions [2]: [partial_sum((cast(ws_quantity#79 as decimal(10,0)) * ws_list_price#80)), partial_count(1)] +Aggregate Attributes [3]: [sum#89, isEmpty#90, count#91] +Results [6]: [i_brand_id#85, i_class_id#86, i_category_id#87, sum#92, isEmpty#93, count#94] + +(94) Exchange +Input [6]: [i_brand_id#85, i_class_id#86, i_category_id#87, sum#92, isEmpty#93, count#94] +Arguments: hashpartitioning(i_brand_id#85, i_class_id#86, i_category_id#87, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(95) HashAggregate [codegen id : 78] +Input [6]: [i_brand_id#85, i_class_id#86, i_category_id#87, sum#92, isEmpty#93, count#94] +Keys [3]: [i_brand_id#85, i_class_id#86, i_category_id#87] +Functions [2]: [sum((cast(ws_quantity#79 as decimal(10,0)) * ws_list_price#80)), count(1)] +Aggregate Attributes [2]: [sum((cast(ws_quantity#79 as decimal(10,0)) * ws_list_price#80))#95, count(1)#96] +Results [6]: [web AS channel#97, i_brand_id#85, i_class_id#86, i_category_id#87, sum((cast(ws_quantity#79 as decimal(10,0)) * ws_list_price#80))#95 AS sales#98, count(1)#96 AS number_sales#99] + +(96) Filter [codegen id : 78] +Input [6]: [channel#97, i_brand_id#85, i_class_id#86, i_category_id#87, sales#98, number_sales#99] +Condition : (isnotnull(sales#98) AND (cast(sales#98 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#54, [id=#55] as decimal(32,6)))) + +(97) Union + +(98) HashAggregate [codegen id : 79] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sales#52, number_sales#53] +Keys [4]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [partial_sum(sales#52), partial_sum(number_sales#53)] +Aggregate Attributes [3]: [sum#100, isEmpty#101, sum#102] +Results [7]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum#103, isEmpty#104, sum#105] + +(99) Exchange +Input [7]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum#103, isEmpty#104, sum#105] +Arguments: hashpartitioning(channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(100) HashAggregate [codegen id : 80] +Input [7]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum#103, isEmpty#104, sum#105] +Keys [4]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41] +Functions [2]: [sum(sales#52), sum(number_sales#53)] +Aggregate Attributes [2]: [sum(sales#52)#106, sum(number_sales#53)#107] +Results [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum(sales#52)#106 AS sum_sales#108, sum(number_sales#53)#107 AS number_sales#109] + +(101) ReusedExchange [Reuses operator id: 99] +Output [7]: [channel#110, i_brand_id#111, i_class_id#112, i_category_id#113, sum#114, isEmpty#115, sum#116] + +(102) HashAggregate [codegen id : 160] +Input [7]: [channel#110, i_brand_id#111, i_class_id#112, i_category_id#113, sum#114, isEmpty#115, sum#116] +Keys [4]: [channel#110, i_brand_id#111, i_class_id#112, i_category_id#113] +Functions [2]: [sum(sales#117), sum(number_sales#118)] +Aggregate Attributes [2]: [sum(sales#117)#106, sum(number_sales#118)#107] +Results [5]: [channel#110, i_brand_id#111, i_class_id#112, sum(sales#117)#106 AS sum_sales#119, sum(number_sales#118)#107 AS number_sales#120] + +(103) HashAggregate [codegen id : 160] +Input [5]: [channel#110, i_brand_id#111, i_class_id#112, sum_sales#119, number_sales#120] +Keys [3]: [channel#110, i_brand_id#111, i_class_id#112] +Functions [2]: [partial_sum(sum_sales#119), partial_sum(number_sales#120)] +Aggregate Attributes [3]: [sum#121, isEmpty#122, sum#123] +Results [6]: [channel#110, i_brand_id#111, i_class_id#112, sum#124, isEmpty#125, sum#126] + +(104) Exchange +Input [6]: [channel#110, i_brand_id#111, i_class_id#112, sum#124, isEmpty#125, sum#126] +Arguments: hashpartitioning(channel#110, i_brand_id#111, i_class_id#112, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(105) HashAggregate [codegen id : 161] +Input [6]: [channel#110, i_brand_id#111, i_class_id#112, sum#124, isEmpty#125, sum#126] +Keys [3]: [channel#110, i_brand_id#111, i_class_id#112] +Functions [2]: [sum(sum_sales#119), sum(number_sales#120)] +Aggregate Attributes [2]: [sum(sum_sales#119)#127, sum(number_sales#120)#128] +Results [6]: [channel#110, i_brand_id#111, i_class_id#112, null AS i_category_id#129, sum(sum_sales#119)#127 AS sum(sum_sales)#130, sum(number_sales#120)#128 AS sum(number_sales)#131] + +(106) ReusedExchange [Reuses operator id: 99] +Output [7]: [channel#132, i_brand_id#133, i_class_id#134, i_category_id#135, sum#136, isEmpty#137, sum#138] + +(107) HashAggregate [codegen id : 241] +Input [7]: [channel#132, i_brand_id#133, i_class_id#134, i_category_id#135, sum#136, isEmpty#137, sum#138] +Keys [4]: [channel#132, i_brand_id#133, i_class_id#134, i_category_id#135] +Functions [2]: [sum(sales#139), sum(number_sales#140)] +Aggregate Attributes [2]: [sum(sales#139)#106, sum(number_sales#140)#107] +Results [4]: [channel#132, i_brand_id#133, sum(sales#139)#106 AS sum_sales#141, sum(number_sales#140)#107 AS number_sales#142] + +(108) HashAggregate [codegen id : 241] +Input [4]: [channel#132, i_brand_id#133, sum_sales#141, number_sales#142] +Keys [2]: [channel#132, i_brand_id#133] +Functions [2]: [partial_sum(sum_sales#141), partial_sum(number_sales#142)] +Aggregate Attributes [3]: [sum#143, isEmpty#144, sum#145] +Results [5]: [channel#132, i_brand_id#133, sum#146, isEmpty#147, sum#148] + +(109) Exchange +Input [5]: [channel#132, i_brand_id#133, sum#146, isEmpty#147, sum#148] +Arguments: hashpartitioning(channel#132, i_brand_id#133, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(110) HashAggregate [codegen id : 242] +Input [5]: [channel#132, i_brand_id#133, sum#146, isEmpty#147, sum#148] +Keys [2]: [channel#132, i_brand_id#133] +Functions [2]: [sum(sum_sales#141), sum(number_sales#142)] +Aggregate Attributes [2]: [sum(sum_sales#141)#149, sum(number_sales#142)#150] +Results [6]: [channel#132, i_brand_id#133, null AS i_class_id#151, null AS i_category_id#152, sum(sum_sales#141)#149 AS sum(sum_sales)#153, sum(number_sales#142)#150 AS sum(number_sales)#154] + +(111) ReusedExchange [Reuses operator id: 99] +Output [7]: [channel#155, i_brand_id#156, i_class_id#157, i_category_id#158, sum#159, isEmpty#160, sum#161] + +(112) HashAggregate [codegen id : 322] +Input [7]: [channel#155, i_brand_id#156, i_class_id#157, i_category_id#158, sum#159, isEmpty#160, sum#161] +Keys [4]: [channel#155, i_brand_id#156, i_class_id#157, i_category_id#158] +Functions [2]: [sum(sales#162), sum(number_sales#163)] +Aggregate Attributes [2]: [sum(sales#162)#106, sum(number_sales#163)#107] +Results [3]: [channel#155, sum(sales#162)#106 AS sum_sales#164, sum(number_sales#163)#107 AS number_sales#165] + +(113) HashAggregate [codegen id : 322] +Input [3]: [channel#155, sum_sales#164, number_sales#165] +Keys [1]: [channel#155] +Functions [2]: [partial_sum(sum_sales#164), partial_sum(number_sales#165)] +Aggregate Attributes [3]: [sum#166, isEmpty#167, sum#168] +Results [4]: [channel#155, sum#169, isEmpty#170, sum#171] + +(114) Exchange +Input [4]: [channel#155, sum#169, isEmpty#170, sum#171] +Arguments: hashpartitioning(channel#155, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(115) HashAggregate [codegen id : 323] +Input [4]: [channel#155, sum#169, isEmpty#170, sum#171] +Keys [1]: [channel#155] +Functions [2]: [sum(sum_sales#164), sum(number_sales#165)] +Aggregate Attributes [2]: [sum(sum_sales#164)#172, sum(number_sales#165)#173] +Results [6]: [channel#155, null AS i_brand_id#174, null AS i_class_id#175, null AS i_category_id#176, sum(sum_sales#164)#172 AS sum(sum_sales)#177, sum(number_sales#165)#173 AS sum(number_sales)#178] + +(116) ReusedExchange [Reuses operator id: 99] +Output [7]: [channel#179, i_brand_id#180, i_class_id#181, i_category_id#182, sum#183, isEmpty#184, sum#185] + +(117) HashAggregate [codegen id : 403] +Input [7]: [channel#179, i_brand_id#180, i_class_id#181, i_category_id#182, sum#183, isEmpty#184, sum#185] +Keys [4]: [channel#179, i_brand_id#180, i_class_id#181, i_category_id#182] +Functions [2]: [sum(sales#186), sum(number_sales#187)] +Aggregate Attributes [2]: [sum(sales#186)#106, sum(number_sales#187)#107] +Results [2]: [sum(sales#186)#106 AS sum_sales#188, sum(number_sales#187)#107 AS number_sales#189] + +(118) HashAggregate [codegen id : 403] +Input [2]: [sum_sales#188, number_sales#189] +Keys: [] +Functions [2]: [partial_sum(sum_sales#188), partial_sum(number_sales#189)] +Aggregate Attributes [3]: [sum#190, isEmpty#191, sum#192] +Results [3]: [sum#193, isEmpty#194, sum#195] + +(119) Exchange +Input [3]: [sum#193, isEmpty#194, sum#195] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=16] + +(120) HashAggregate [codegen id : 404] +Input [3]: [sum#193, isEmpty#194, sum#195] +Keys: [] +Functions [2]: [sum(sum_sales#188), sum(number_sales#189)] +Aggregate Attributes [2]: [sum(sum_sales#188)#196, sum(number_sales#189)#197] +Results [6]: [null AS channel#198, null AS i_brand_id#199, null AS i_class_id#200, null AS i_category_id#201, sum(sum_sales#188)#196 AS sum(sum_sales)#202, sum(number_sales#189)#197 AS sum(number_sales)#203] + +(121) Union + +(122) HashAggregate [codegen id : 405] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Keys [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Functions: [] +Aggregate Attributes: [] +Results [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] + +(123) Exchange +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Arguments: hashpartitioning(channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109, 5), ENSURE_REQUIREMENTS, [plan_id=17] + +(124) HashAggregate [codegen id : 406] +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Keys [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Functions: [] +Aggregate Attributes: [] +Results [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] + +(125) TakeOrderedAndProject +Input [6]: [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] +Arguments: 100, [channel#51 ASC NULLS FIRST, i_brand_id#39 ASC NULLS FIRST, i_class_id#40 ASC NULLS FIRST, i_category_id#41 ASC NULLS FIRST], [channel#51, i_brand_id#39, i_class_id#40, i_category_id#41, sum_sales#108, number_sales#109] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 66 Hosting Expression = Subquery scalar-subquery#54, [id=#55] +* HashAggregate (144) ++- Exchange (143) + +- * HashAggregate (142) + +- Union (141) + :- * Project (130) + : +- * BroadcastHashJoin Inner BuildRight (129) + : :- * ColumnarToRow (127) + : : +- CometScan parquet spark_catalog.default.store_sales (126) + : +- ReusedExchange (128) + :- * Project (135) + : +- * BroadcastHashJoin Inner BuildRight (134) + : :- * ColumnarToRow (132) + : : +- CometScan parquet spark_catalog.default.catalog_sales (131) + : +- ReusedExchange (133) + +- * Project (140) + +- * BroadcastHashJoin Inner BuildRight (139) + :- * ColumnarToRow (137) + : +- CometScan parquet spark_catalog.default.web_sales (136) + +- ReusedExchange (138) + + +(126) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_quantity#204, ss_list_price#205, ss_sold_date_sk#206] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#206), dynamicpruningexpression(ss_sold_date_sk#206 IN dynamicpruning#207)] +ReadSchema: struct + +(127) ColumnarToRow [codegen id : 2] +Input [3]: [ss_quantity#204, ss_list_price#205, ss_sold_date_sk#206] + +(128) ReusedExchange [Reuses operator id: 159] +Output [1]: [d_date_sk#208] + +(129) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#206] +Right keys [1]: [d_date_sk#208] +Join type: Inner +Join condition: None + +(130) Project [codegen id : 2] +Output [2]: [ss_quantity#204 AS quantity#209, ss_list_price#205 AS list_price#210] +Input [4]: [ss_quantity#204, ss_list_price#205, ss_sold_date_sk#206, d_date_sk#208] + +(131) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_quantity#211, cs_list_price#212, cs_sold_date_sk#213] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#213), dynamicpruningexpression(cs_sold_date_sk#213 IN dynamicpruning#214)] +ReadSchema: struct + +(132) ColumnarToRow [codegen id : 4] +Input [3]: [cs_quantity#211, cs_list_price#212, cs_sold_date_sk#213] + +(133) ReusedExchange [Reuses operator id: 149] +Output [1]: [d_date_sk#215] + +(134) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#213] +Right keys [1]: [d_date_sk#215] +Join type: Inner +Join condition: None + +(135) Project [codegen id : 4] +Output [2]: [cs_quantity#211 AS quantity#216, cs_list_price#212 AS list_price#217] +Input [4]: [cs_quantity#211, cs_list_price#212, cs_sold_date_sk#213, d_date_sk#215] + +(136) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_quantity#218, ws_list_price#219, ws_sold_date_sk#220] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#220), dynamicpruningexpression(ws_sold_date_sk#220 IN dynamicpruning#221)] +ReadSchema: struct + +(137) ColumnarToRow [codegen id : 6] +Input [3]: [ws_quantity#218, ws_list_price#219, ws_sold_date_sk#220] + +(138) ReusedExchange [Reuses operator id: 149] +Output [1]: [d_date_sk#222] + +(139) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ws_sold_date_sk#220] +Right keys [1]: [d_date_sk#222] +Join type: Inner +Join condition: None + +(140) Project [codegen id : 6] +Output [2]: [ws_quantity#218 AS quantity#223, ws_list_price#219 AS list_price#224] +Input [4]: [ws_quantity#218, ws_list_price#219, ws_sold_date_sk#220, d_date_sk#222] + +(141) Union + +(142) HashAggregate [codegen id : 7] +Input [2]: [quantity#209, list_price#210] +Keys: [] +Functions [1]: [partial_avg((cast(quantity#209 as decimal(10,0)) * list_price#210))] +Aggregate Attributes [2]: [sum#225, count#226] +Results [2]: [sum#227, count#228] + +(143) Exchange +Input [2]: [sum#227, count#228] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=18] + +(144) HashAggregate [codegen id : 8] +Input [2]: [sum#227, count#228] +Keys: [] +Functions [1]: [avg((cast(quantity#209 as decimal(10,0)) * list_price#210))] +Aggregate Attributes [1]: [avg((cast(quantity#209 as decimal(10,0)) * list_price#210))#229] +Results [1]: [avg((cast(quantity#209 as decimal(10,0)) * list_price#210))#229 AS average_sales#230] + +Subquery:2 Hosting operator id = 126 Hosting Expression = ss_sold_date_sk#206 IN dynamicpruning#12 + +Subquery:3 Hosting operator id = 131 Hosting Expression = cs_sold_date_sk#213 IN dynamicpruning#214 +BroadcastExchange (149) ++- * Project (148) + +- * Filter (147) + +- * ColumnarToRow (146) + +- CometScan parquet spark_catalog.default.date_dim (145) + + +(145) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#215, d_year#231] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1998), LessThanOrEqual(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(146) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#215, d_year#231] + +(147) Filter [codegen id : 1] +Input [2]: [d_date_sk#215, d_year#231] +Condition : (((isnotnull(d_year#231) AND (d_year#231 >= 1998)) AND (d_year#231 <= 2000)) AND isnotnull(d_date_sk#215)) + +(148) Project [codegen id : 1] +Output [1]: [d_date_sk#215] +Input [2]: [d_date_sk#215, d_year#231] + +(149) BroadcastExchange +Input [1]: [d_date_sk#215] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=19] + +Subquery:4 Hosting operator id = 136 Hosting Expression = ws_sold_date_sk#220 IN dynamicpruning#214 + +Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (154) ++- * Project (153) + +- * Filter (152) + +- * ColumnarToRow (151) + +- CometScan parquet spark_catalog.default.date_dim (150) + + +(150) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#42, d_year#232, d_moy#233] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,11), IsNotNull(d_date_sk)] +ReadSchema: struct + +(151) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#42, d_year#232, d_moy#233] + +(152) Filter [codegen id : 1] +Input [3]: [d_date_sk#42, d_year#232, d_moy#233] +Condition : ((((isnotnull(d_year#232) AND isnotnull(d_moy#233)) AND (d_year#232 = 2000)) AND (d_moy#233 = 11)) AND isnotnull(d_date_sk#42)) + +(153) Project [codegen id : 1] +Output [1]: [d_date_sk#42] +Input [3]: [d_date_sk#42, d_year#232, d_moy#233] + +(154) BroadcastExchange +Input [1]: [d_date_sk#42] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=20] + +Subquery:6 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 +BroadcastExchange (159) ++- * Project (158) + +- * Filter (157) + +- * ColumnarToRow (156) + +- CometScan parquet spark_catalog.default.date_dim (155) + + +(155) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#234] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(156) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#234] + +(157) Filter [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#234] +Condition : (((isnotnull(d_year#234) AND (d_year#234 >= 1999)) AND (d_year#234 <= 2001)) AND isnotnull(d_date_sk#25)) + +(158) Project [codegen id : 1] +Output [1]: [d_date_sk#25] +Input [2]: [d_date_sk#25, d_year#234] + +(159) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=21] + +Subquery:7 Hosting operator id = 13 Hosting Expression = cs_sold_date_sk#18 IN dynamicpruning#12 + +Subquery:8 Hosting operator id = 36 Hosting Expression = ws_sold_date_sk#30 IN dynamicpruning#12 + +Subquery:9 Hosting operator id = 81 Hosting Expression = ReusedSubquery Subquery scalar-subquery#54, [id=#55] + +Subquery:10 Hosting operator id = 67 Hosting Expression = cs_sold_date_sk#59 IN dynamicpruning#5 + +Subquery:11 Hosting operator id = 96 Hosting Expression = ReusedSubquery Subquery scalar-subquery#54, [id=#55] + +Subquery:12 Hosting operator id = 82 Hosting Expression = ws_sold_date_sk#81 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/simplified.txt new file mode 100644 index 000000000..7284dab53 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/simplified.txt @@ -0,0 +1,261 @@ +TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum_sales,number_sales] + WholeStageCodegen (406) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum_sales,number_sales] + InputAdapter + Exchange [channel,i_brand_id,i_class_id,i_category_id,sum_sales,number_sales] #1 + WholeStageCodegen (405) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum_sales,number_sales] + InputAdapter + Union + WholeStageCodegen (80) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum_sales,number_sales,sum,isEmpty,sum] + InputAdapter + Exchange [channel,i_brand_id,i_class_id,i_category_id] #2 + WholeStageCodegen (79) + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + InputAdapter + Union + WholeStageCodegen (26) + Filter [sales] + Subquery #3 + WholeStageCodegen (8) + HashAggregate [sum,count] [avg((cast(quantity as decimal(10,0)) * list_price)),average_sales,sum,count] + InputAdapter + Exchange #14 + WholeStageCodegen (7) + HashAggregate [quantity,list_price] [sum,count,sum,count] + InputAdapter + Union + WholeStageCodegen (2) + Project [ss_quantity,ss_list_price] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_list_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk] #8 + WholeStageCodegen (4) + Project [cs_quantity,cs_list_price] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_quantity,cs_list_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #4 + BroadcastExchange #15 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #15 + WholeStageCodegen (6) + Project [ws_quantity,ws_list_price] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #4 + InputAdapter + ReusedExchange [d_date_sk] #15 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ss_quantity as decimal(10,0)) * ss_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #3 + WholeStageCodegen (25) + HashAggregate [i_brand_id,i_class_id,i_category_id,ss_quantity,ss_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ss_quantity,ss_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + BroadcastHashJoin [ss_item_sk,ss_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (11) + Project [i_item_sk] + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] + Filter [i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (10) + BroadcastHashJoin [brand_id,class_id,category_id,i_brand_id,i_class_id,i_category_id] + HashAggregate [brand_id,class_id,category_id] + InputAdapter + Exchange [brand_id,class_id,category_id] #7 + WholeStageCodegen (6) + HashAggregate [brand_id,class_id,category_id] + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #8 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (4) + BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] + Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (3) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (1) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [d_date_sk] #8 + InputAdapter + ReusedExchange [d_date_sk] #8 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (9) + Project [i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #11 + InputAdapter + ReusedExchange [d_date_sk] #8 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (23) + BroadcastHashJoin [i_item_sk,ss_item_sk] + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] + InputAdapter + ReusedExchange [ss_item_sk] #5 + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (52) + Filter [sales] + ReusedSubquery [average_sales] #3 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(cs_quantity as decimal(10,0)) * cs_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #16 + WholeStageCodegen (51) + HashAggregate [i_brand_id,i_class_id,i_category_id,cs_quantity,cs_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [cs_quantity,cs_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_quantity,cs_list_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + BroadcastHashJoin [cs_item_sk,ss_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [ss_item_sk] #5 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #13 + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (78) + Filter [sales] + ReusedSubquery [average_sales] #3 + HashAggregate [i_brand_id,i_class_id,i_category_id,sum,isEmpty,count] [sum((cast(ws_quantity as decimal(10,0)) * ws_list_price)),count(1),channel,sales,number_sales,sum,isEmpty,count] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id] #17 + WholeStageCodegen (77) + HashAggregate [i_brand_id,i_class_id,i_category_id,ws_quantity,ws_list_price] [sum,isEmpty,count,sum,isEmpty,count] + Project [ws_quantity,ws_list_price,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_quantity,ws_list_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + BroadcastHashJoin [ws_item_sk,ss_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_quantity,ws_list_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [ss_item_sk] #5 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id] #13 + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (161) + HashAggregate [channel,i_brand_id,i_class_id,sum,isEmpty,sum] [sum(sum_sales),sum(number_salesL),i_category_id,sum(sum_sales),sum(number_sales),sum,isEmpty,sum] + InputAdapter + Exchange [channel,i_brand_id,i_class_id] #18 + WholeStageCodegen (160) + HashAggregate [channel,i_brand_id,i_class_id,sum_sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum_sales,number_sales,sum,isEmpty,sum] + InputAdapter + ReusedExchange [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] #2 + WholeStageCodegen (242) + HashAggregate [channel,i_brand_id,sum,isEmpty,sum] [sum(sum_sales),sum(number_salesL),i_class_id,i_category_id,sum(sum_sales),sum(number_sales),sum,isEmpty,sum] + InputAdapter + Exchange [channel,i_brand_id] #19 + WholeStageCodegen (241) + HashAggregate [channel,i_brand_id,sum_sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum_sales,number_sales,sum,isEmpty,sum] + InputAdapter + ReusedExchange [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] #2 + WholeStageCodegen (323) + HashAggregate [channel,sum,isEmpty,sum] [sum(sum_sales),sum(number_salesL),i_brand_id,i_class_id,i_category_id,sum(sum_sales),sum(number_sales),sum,isEmpty,sum] + InputAdapter + Exchange [channel] #20 + WholeStageCodegen (322) + HashAggregate [channel,sum_sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum_sales,number_sales,sum,isEmpty,sum] + InputAdapter + ReusedExchange [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] #2 + WholeStageCodegen (404) + HashAggregate [sum,isEmpty,sum] [sum(sum_sales),sum(number_salesL),channel,i_brand_id,i_class_id,i_category_id,sum(sum_sales),sum(number_sales),sum,isEmpty,sum] + InputAdapter + Exchange #21 + WholeStageCodegen (403) + HashAggregate [sum_sales,number_sales] [sum,isEmpty,sum,sum,isEmpty,sum] + HashAggregate [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] [sum(sales),sum(number_salesL),sum_sales,number_sales,sum,isEmpty,sum] + InputAdapter + ReusedExchange [channel,i_brand_id,i_class_id,i_category_id,sum,isEmpty,sum] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/explain.txt new file mode 100644 index 000000000..908089cc5 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/explain.txt @@ -0,0 +1,909 @@ +== Physical Plan == +TakeOrderedAndProject (153) ++- Union (152) + :- * HashAggregate (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * Project (32) + : : +- * BroadcastHashJoin Inner BuildRight (31) + : : :- * Project (29) + : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : :- * Project (23) + : : : : +- * BroadcastHashJoin Inner BuildRight (22) + : : : : :- * Project (17) + : : : : : +- * BroadcastHashJoin Inner BuildRight (16) + : : : : : :- * Project (10) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : : : :- * Filter (3) + : : : : : : : +- * ColumnarToRow (2) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : : +- BroadcastExchange (8) + : : : : : : +- * Project (7) + : : : : : : +- * Filter (6) + : : : : : : +- * ColumnarToRow (5) + : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : : : : +- BroadcastExchange (15) + : : : : : +- * Project (14) + : : : : : +- * Filter (13) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometScan parquet spark_catalog.default.customer (11) + : : : : +- BroadcastExchange (21) + : : : : +- * Filter (20) + : : : : +- * ColumnarToRow (19) + : : : : +- CometScan parquet spark_catalog.default.customer_demographics (18) + : : : +- BroadcastExchange (27) + : : : +- * Filter (26) + : : : +- * ColumnarToRow (25) + : : : +- CometScan parquet spark_catalog.default.customer_address (24) + : : +- ReusedExchange (30) + : +- BroadcastExchange (36) + : +- * Filter (35) + : +- * ColumnarToRow (34) + : +- CometScan parquet spark_catalog.default.item (33) + :- * HashAggregate (68) + : +- Exchange (67) + : +- * HashAggregate (66) + : +- * Project (65) + : +- * BroadcastHashJoin Inner BuildRight (64) + : :- * Project (62) + : : +- * BroadcastHashJoin Inner BuildRight (61) + : : :- * Project (59) + : : : +- * BroadcastHashJoin Inner BuildRight (58) + : : : :- * Project (53) + : : : : +- * BroadcastHashJoin Inner BuildRight (52) + : : : : :- * Project (50) + : : : : : +- * BroadcastHashJoin Inner BuildRight (49) + : : : : : :- * Project (47) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (46) + : : : : : : :- * Filter (44) + : : : : : : : +- * ColumnarToRow (43) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (42) + : : : : : : +- ReusedExchange (45) + : : : : : +- ReusedExchange (48) + : : : : +- ReusedExchange (51) + : : : +- BroadcastExchange (57) + : : : +- * Filter (56) + : : : +- * ColumnarToRow (55) + : : : +- CometScan parquet spark_catalog.default.customer_address (54) + : : +- ReusedExchange (60) + : +- ReusedExchange (63) + :- * HashAggregate (96) + : +- Exchange (95) + : +- * HashAggregate (94) + : +- * Project (93) + : +- * BroadcastHashJoin Inner BuildRight (92) + : :- * Project (90) + : : +- * BroadcastHashJoin Inner BuildRight (89) + : : :- * Project (87) + : : : +- * BroadcastHashJoin Inner BuildRight (86) + : : : :- * Project (80) + : : : : +- * BroadcastHashJoin Inner BuildRight (79) + : : : : :- * Project (77) + : : : : : +- * BroadcastHashJoin Inner BuildRight (76) + : : : : : :- * Project (74) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (73) + : : : : : : :- * Filter (71) + : : : : : : : +- * ColumnarToRow (70) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (69) + : : : : : : +- ReusedExchange (72) + : : : : : +- ReusedExchange (75) + : : : : +- ReusedExchange (78) + : : : +- BroadcastExchange (85) + : : : +- * Project (84) + : : : +- * Filter (83) + : : : +- * ColumnarToRow (82) + : : : +- CometScan parquet spark_catalog.default.customer_address (81) + : : +- ReusedExchange (88) + : +- ReusedExchange (91) + :- * HashAggregate (124) + : +- Exchange (123) + : +- * HashAggregate (122) + : +- * Project (121) + : +- * BroadcastHashJoin Inner BuildRight (120) + : :- * Project (118) + : : +- * BroadcastHashJoin Inner BuildRight (117) + : : :- * Project (115) + : : : +- * BroadcastHashJoin Inner BuildRight (114) + : : : :- * Project (108) + : : : : +- * BroadcastHashJoin Inner BuildRight (107) + : : : : :- * Project (105) + : : : : : +- * BroadcastHashJoin Inner BuildRight (104) + : : : : : :- * Project (102) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (101) + : : : : : : :- * Filter (99) + : : : : : : : +- * ColumnarToRow (98) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (97) + : : : : : : +- ReusedExchange (100) + : : : : : +- ReusedExchange (103) + : : : : +- ReusedExchange (106) + : : : +- BroadcastExchange (113) + : : : +- * Project (112) + : : : +- * Filter (111) + : : : +- * ColumnarToRow (110) + : : : +- CometScan parquet spark_catalog.default.customer_address (109) + : : +- ReusedExchange (116) + : +- ReusedExchange (119) + +- * HashAggregate (151) + +- Exchange (150) + +- * HashAggregate (149) + +- * Project (148) + +- * BroadcastHashJoin Inner BuildRight (147) + :- * Project (142) + : +- * BroadcastHashJoin Inner BuildRight (141) + : :- * Project (139) + : : +- * BroadcastHashJoin Inner BuildRight (138) + : : :- * Project (136) + : : : +- * BroadcastHashJoin Inner BuildRight (135) + : : : :- * Project (133) + : : : : +- * BroadcastHashJoin Inner BuildRight (132) + : : : : :- * Project (130) + : : : : : +- * BroadcastHashJoin Inner BuildRight (129) + : : : : : :- * Filter (127) + : : : : : : +- * ColumnarToRow (126) + : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (125) + : : : : : +- ReusedExchange (128) + : : : : +- ReusedExchange (131) + : : : +- ReusedExchange (134) + : : +- ReusedExchange (137) + : +- ReusedExchange (140) + +- BroadcastExchange (146) + +- * Filter (145) + +- * ColumnarToRow (144) + +- CometScan parquet spark_catalog.default.item (143) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#9), dynamicpruningexpression(cs_sold_date_sk#9 IN dynamicpruning#10)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 7] +Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] + +(3) Filter [codegen id : 7] +Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] +Condition : ((isnotnull(cs_bill_cdemo_sk#2) AND isnotnull(cs_bill_customer_sk#1)) AND isnotnull(cs_item_sk#3)) + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] + +(6) Filter [codegen id : 1] +Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Condition : ((((isnotnull(cd_gender#12) AND isnotnull(cd_education_status#13)) AND (cd_gender#12 = M)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#11)) + +(7) Project [codegen id : 1] +Output [2]: [cd_demo_sk#11, cd_dep_count#14] +Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] + +(8) BroadcastExchange +Input [2]: [cd_demo_sk#11, cd_dep_count#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_bill_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#11] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 7] +Output [9]: [cs_bill_customer_sk#1, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14] +Input [11]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_demo_sk#11, cd_dep_count#14] + +(11) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [In(c_birth_month, [1,10,12,4,5,9]), IsNotNull(c_customer_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 2] +Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] + +(13) Filter [codegen id : 2] +Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Condition : (((c_birth_month#18 IN (9,5,12,4,1,10) AND isnotnull(c_customer_sk#15)) AND isnotnull(c_current_cdemo_sk#16)) AND isnotnull(c_current_addr_sk#17)) + +(14) Project [codegen id : 2] +Output [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] + +(15) BroadcastExchange +Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(16) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_bill_customer_sk#1] +Right keys [1]: [c_customer_sk#15] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 7] +Output [11]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +Input [13]: [cs_bill_customer_sk#1, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] + +(18) Scan parquet spark_catalog.default.customer_demographics +Output [1]: [cd_demo_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 3] +Input [1]: [cd_demo_sk#20] + +(20) Filter [codegen id : 3] +Input [1]: [cd_demo_sk#20] +Condition : isnotnull(cd_demo_sk#20) + +(21) BroadcastExchange +Input [1]: [cd_demo_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(22) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_cdemo_sk#16] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(23) Project [codegen id : 7] +Output [10]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_addr_sk#17, c_birth_year#19] +Input [12]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19, cd_demo_sk#20] + +(24) Scan parquet spark_catalog.default.customer_address +Output [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(25) ColumnarToRow [codegen id : 4] +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] + +(26) Filter [codegen id : 4] +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Condition : (ca_state#23 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#21)) + +(27) BroadcastExchange +Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_current_addr_sk#17] +Right keys [1]: [ca_address_sk#21] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 7] +Output [12]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24] +Input [14]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_addr_sk#17, c_birth_year#19, ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] + +(30) ReusedExchange [Reuses operator id: 158] +Output [1]: [d_date_sk#25] + +(31) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_sold_date_sk#9] +Right keys [1]: [d_date_sk#25] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 7] +Output [11]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24] +Input [13]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24, d_date_sk#25] + +(33) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#26, i_item_id#27] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(34) ColumnarToRow [codegen id : 6] +Input [2]: [i_item_sk#26, i_item_id#27] + +(35) Filter [codegen id : 6] +Input [2]: [i_item_sk#26, i_item_id#27] +Condition : isnotnull(i_item_sk#26) + +(36) BroadcastExchange +Input [2]: [i_item_sk#26, i_item_id#27] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [cs_item_sk#3] +Right keys [1]: [i_item_sk#26] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 7] +Output [11]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, cast(cs_quantity#4 as decimal(12,2)) AS agg1#28, cast(cs_list_price#5 as decimal(12,2)) AS agg2#29, cast(cs_coupon_amt#7 as decimal(12,2)) AS agg3#30, cast(cs_sales_price#6 as decimal(12,2)) AS agg4#31, cast(cs_net_profit#8 as decimal(12,2)) AS agg5#32, cast(c_birth_year#19 as decimal(12,2)) AS agg6#33, cast(cd_dep_count#14 as decimal(12,2)) AS agg7#34] +Input [13]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24, i_item_sk#26, i_item_id#27] + +(39) HashAggregate [codegen id : 7] +Input [11]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, agg1#28, agg2#29, agg3#30, agg4#31, agg5#32, agg6#33, agg7#34] +Keys [4]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22] +Functions [7]: [partial_avg(agg1#28), partial_avg(agg2#29), partial_avg(agg3#30), partial_avg(agg4#31), partial_avg(agg5#32), partial_avg(agg6#33), partial_avg(agg7#34)] +Aggregate Attributes [14]: [sum#35, count#36, sum#37, count#38, sum#39, count#40, sum#41, count#42, sum#43, count#44, sum#45, count#46, sum#47, count#48] +Results [18]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60, sum#61, count#62] + +(40) Exchange +Input [18]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60, sum#61, count#62] +Arguments: hashpartitioning(i_item_id#27, ca_country#24, ca_state#23, ca_county#22, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 8] +Input [18]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, sum#49, count#50, sum#51, count#52, sum#53, count#54, sum#55, count#56, sum#57, count#58, sum#59, count#60, sum#61, count#62] +Keys [4]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22] +Functions [7]: [avg(agg1#28), avg(agg2#29), avg(agg3#30), avg(agg4#31), avg(agg5#32), avg(agg6#33), avg(agg7#34)] +Aggregate Attributes [7]: [avg(agg1#28)#63, avg(agg2#29)#64, avg(agg3#30)#65, avg(agg4#31)#66, avg(agg5#32)#67, avg(agg6#33)#68, avg(agg7#34)#69] +Results [11]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, avg(agg1#28)#63 AS agg1#70, avg(agg2#29)#64 AS agg2#71, avg(agg3#30)#65 AS agg3#72, avg(agg4#31)#66 AS agg4#73, avg(agg5#32)#67 AS agg5#74, avg(agg6#33)#68 AS agg6#75, avg(agg7#34)#69 AS agg7#76] + +(42) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#77, cs_bill_cdemo_sk#78, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#85), dynamicpruningexpression(cs_sold_date_sk#85 IN dynamicpruning#86)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(43) ColumnarToRow [codegen id : 15] +Input [9]: [cs_bill_customer_sk#77, cs_bill_cdemo_sk#78, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85] + +(44) Filter [codegen id : 15] +Input [9]: [cs_bill_customer_sk#77, cs_bill_cdemo_sk#78, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85] +Condition : ((isnotnull(cs_bill_cdemo_sk#78) AND isnotnull(cs_bill_customer_sk#77)) AND isnotnull(cs_item_sk#79)) + +(45) ReusedExchange [Reuses operator id: 8] +Output [2]: [cd_demo_sk#87, cd_dep_count#88] + +(46) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [cs_bill_cdemo_sk#78] +Right keys [1]: [cd_demo_sk#87] +Join type: Inner +Join condition: None + +(47) Project [codegen id : 15] +Output [9]: [cs_bill_customer_sk#77, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88] +Input [11]: [cs_bill_customer_sk#77, cs_bill_cdemo_sk#78, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_demo_sk#87, cd_dep_count#88] + +(48) ReusedExchange [Reuses operator id: 15] +Output [4]: [c_customer_sk#89, c_current_cdemo_sk#90, c_current_addr_sk#91, c_birth_year#92] + +(49) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [cs_bill_customer_sk#77] +Right keys [1]: [c_customer_sk#89] +Join type: Inner +Join condition: None + +(50) Project [codegen id : 15] +Output [11]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_current_cdemo_sk#90, c_current_addr_sk#91, c_birth_year#92] +Input [13]: [cs_bill_customer_sk#77, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_customer_sk#89, c_current_cdemo_sk#90, c_current_addr_sk#91, c_birth_year#92] + +(51) ReusedExchange [Reuses operator id: 21] +Output [1]: [cd_demo_sk#93] + +(52) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [c_current_cdemo_sk#90] +Right keys [1]: [cd_demo_sk#93] +Join type: Inner +Join condition: None + +(53) Project [codegen id : 15] +Output [10]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_current_addr_sk#91, c_birth_year#92] +Input [12]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_current_cdemo_sk#90, c_current_addr_sk#91, c_birth_year#92, cd_demo_sk#93] + +(54) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#94, ca_state#95, ca_country#96] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(55) ColumnarToRow [codegen id : 12] +Input [3]: [ca_address_sk#94, ca_state#95, ca_country#96] + +(56) Filter [codegen id : 12] +Input [3]: [ca_address_sk#94, ca_state#95, ca_country#96] +Condition : (ca_state#95 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#94)) + +(57) BroadcastExchange +Input [3]: [ca_address_sk#94, ca_state#95, ca_country#96] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(58) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [c_current_addr_sk#91] +Right keys [1]: [ca_address_sk#94] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 15] +Output [11]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_birth_year#92, ca_state#95, ca_country#96] +Input [13]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_current_addr_sk#91, c_birth_year#92, ca_address_sk#94, ca_state#95, ca_country#96] + +(60) ReusedExchange [Reuses operator id: 158] +Output [1]: [d_date_sk#97] + +(61) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [cs_sold_date_sk#85] +Right keys [1]: [d_date_sk#97] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 15] +Output [10]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cd_dep_count#88, c_birth_year#92, ca_state#95, ca_country#96] +Input [12]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85, cd_dep_count#88, c_birth_year#92, ca_state#95, ca_country#96, d_date_sk#97] + +(63) ReusedExchange [Reuses operator id: 36] +Output [2]: [i_item_sk#98, i_item_id#99] + +(64) BroadcastHashJoin [codegen id : 15] +Left keys [1]: [cs_item_sk#79] +Right keys [1]: [i_item_sk#98] +Join type: Inner +Join condition: None + +(65) Project [codegen id : 15] +Output [10]: [i_item_id#99, ca_country#96, ca_state#95, cast(cs_quantity#80 as decimal(12,2)) AS agg1#100, cast(cs_list_price#81 as decimal(12,2)) AS agg2#101, cast(cs_coupon_amt#83 as decimal(12,2)) AS agg3#102, cast(cs_sales_price#82 as decimal(12,2)) AS agg4#103, cast(cs_net_profit#84 as decimal(12,2)) AS agg5#104, cast(c_birth_year#92 as decimal(12,2)) AS agg6#105, cast(cd_dep_count#88 as decimal(12,2)) AS agg7#106] +Input [12]: [cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cd_dep_count#88, c_birth_year#92, ca_state#95, ca_country#96, i_item_sk#98, i_item_id#99] + +(66) HashAggregate [codegen id : 15] +Input [10]: [i_item_id#99, ca_country#96, ca_state#95, agg1#100, agg2#101, agg3#102, agg4#103, agg5#104, agg6#105, agg7#106] +Keys [3]: [i_item_id#99, ca_country#96, ca_state#95] +Functions [7]: [partial_avg(agg1#100), partial_avg(agg2#101), partial_avg(agg3#102), partial_avg(agg4#103), partial_avg(agg5#104), partial_avg(agg6#105), partial_avg(agg7#106)] +Aggregate Attributes [14]: [sum#107, count#108, sum#109, count#110, sum#111, count#112, sum#113, count#114, sum#115, count#116, sum#117, count#118, sum#119, count#120] +Results [17]: [i_item_id#99, ca_country#96, ca_state#95, sum#121, count#122, sum#123, count#124, sum#125, count#126, sum#127, count#128, sum#129, count#130, sum#131, count#132, sum#133, count#134] + +(67) Exchange +Input [17]: [i_item_id#99, ca_country#96, ca_state#95, sum#121, count#122, sum#123, count#124, sum#125, count#126, sum#127, count#128, sum#129, count#130, sum#131, count#132, sum#133, count#134] +Arguments: hashpartitioning(i_item_id#99, ca_country#96, ca_state#95, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(68) HashAggregate [codegen id : 16] +Input [17]: [i_item_id#99, ca_country#96, ca_state#95, sum#121, count#122, sum#123, count#124, sum#125, count#126, sum#127, count#128, sum#129, count#130, sum#131, count#132, sum#133, count#134] +Keys [3]: [i_item_id#99, ca_country#96, ca_state#95] +Functions [7]: [avg(agg1#100), avg(agg2#101), avg(agg3#102), avg(agg4#103), avg(agg5#104), avg(agg6#105), avg(agg7#106)] +Aggregate Attributes [7]: [avg(agg1#100)#135, avg(agg2#101)#136, avg(agg3#102)#137, avg(agg4#103)#138, avg(agg5#104)#139, avg(agg6#105)#140, avg(agg7#106)#141] +Results [11]: [i_item_id#99, ca_country#96, ca_state#95, null AS county#142, avg(agg1#100)#135 AS agg1#143, avg(agg2#101)#136 AS agg2#144, avg(agg3#102)#137 AS agg3#145, avg(agg4#103)#138 AS agg4#146, avg(agg5#104)#139 AS agg5#147, avg(agg6#105)#140 AS agg6#148, avg(agg7#106)#141 AS agg7#149] + +(69) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#150, cs_bill_cdemo_sk#151, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#158), dynamicpruningexpression(cs_sold_date_sk#158 IN dynamicpruning#159)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(70) ColumnarToRow [codegen id : 23] +Input [9]: [cs_bill_customer_sk#150, cs_bill_cdemo_sk#151, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158] + +(71) Filter [codegen id : 23] +Input [9]: [cs_bill_customer_sk#150, cs_bill_cdemo_sk#151, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158] +Condition : ((isnotnull(cs_bill_cdemo_sk#151) AND isnotnull(cs_bill_customer_sk#150)) AND isnotnull(cs_item_sk#152)) + +(72) ReusedExchange [Reuses operator id: 8] +Output [2]: [cd_demo_sk#160, cd_dep_count#161] + +(73) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [cs_bill_cdemo_sk#151] +Right keys [1]: [cd_demo_sk#160] +Join type: Inner +Join condition: None + +(74) Project [codegen id : 23] +Output [9]: [cs_bill_customer_sk#150, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161] +Input [11]: [cs_bill_customer_sk#150, cs_bill_cdemo_sk#151, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_demo_sk#160, cd_dep_count#161] + +(75) ReusedExchange [Reuses operator id: 15] +Output [4]: [c_customer_sk#162, c_current_cdemo_sk#163, c_current_addr_sk#164, c_birth_year#165] + +(76) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [cs_bill_customer_sk#150] +Right keys [1]: [c_customer_sk#162] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 23] +Output [11]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_current_cdemo_sk#163, c_current_addr_sk#164, c_birth_year#165] +Input [13]: [cs_bill_customer_sk#150, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_customer_sk#162, c_current_cdemo_sk#163, c_current_addr_sk#164, c_birth_year#165] + +(78) ReusedExchange [Reuses operator id: 21] +Output [1]: [cd_demo_sk#166] + +(79) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [c_current_cdemo_sk#163] +Right keys [1]: [cd_demo_sk#166] +Join type: Inner +Join condition: None + +(80) Project [codegen id : 23] +Output [10]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_current_addr_sk#164, c_birth_year#165] +Input [12]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_current_cdemo_sk#163, c_current_addr_sk#164, c_birth_year#165, cd_demo_sk#166] + +(81) Scan parquet spark_catalog.default.customer_address +Output [3]: [ca_address_sk#167, ca_state#168, ca_country#169] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(82) ColumnarToRow [codegen id : 20] +Input [3]: [ca_address_sk#167, ca_state#168, ca_country#169] + +(83) Filter [codegen id : 20] +Input [3]: [ca_address_sk#167, ca_state#168, ca_country#169] +Condition : (ca_state#168 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#167)) + +(84) Project [codegen id : 20] +Output [2]: [ca_address_sk#167, ca_country#169] +Input [3]: [ca_address_sk#167, ca_state#168, ca_country#169] + +(85) BroadcastExchange +Input [2]: [ca_address_sk#167, ca_country#169] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +(86) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [c_current_addr_sk#164] +Right keys [1]: [ca_address_sk#167] +Join type: Inner +Join condition: None + +(87) Project [codegen id : 23] +Output [10]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_birth_year#165, ca_country#169] +Input [12]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_current_addr_sk#164, c_birth_year#165, ca_address_sk#167, ca_country#169] + +(88) ReusedExchange [Reuses operator id: 158] +Output [1]: [d_date_sk#170] + +(89) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [cs_sold_date_sk#158] +Right keys [1]: [d_date_sk#170] +Join type: Inner +Join condition: None + +(90) Project [codegen id : 23] +Output [9]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cd_dep_count#161, c_birth_year#165, ca_country#169] +Input [11]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158, cd_dep_count#161, c_birth_year#165, ca_country#169, d_date_sk#170] + +(91) ReusedExchange [Reuses operator id: 36] +Output [2]: [i_item_sk#171, i_item_id#172] + +(92) BroadcastHashJoin [codegen id : 23] +Left keys [1]: [cs_item_sk#152] +Right keys [1]: [i_item_sk#171] +Join type: Inner +Join condition: None + +(93) Project [codegen id : 23] +Output [9]: [i_item_id#172, ca_country#169, cast(cs_quantity#153 as decimal(12,2)) AS agg1#173, cast(cs_list_price#154 as decimal(12,2)) AS agg2#174, cast(cs_coupon_amt#156 as decimal(12,2)) AS agg3#175, cast(cs_sales_price#155 as decimal(12,2)) AS agg4#176, cast(cs_net_profit#157 as decimal(12,2)) AS agg5#177, cast(c_birth_year#165 as decimal(12,2)) AS agg6#178, cast(cd_dep_count#161 as decimal(12,2)) AS agg7#179] +Input [11]: [cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cd_dep_count#161, c_birth_year#165, ca_country#169, i_item_sk#171, i_item_id#172] + +(94) HashAggregate [codegen id : 23] +Input [9]: [i_item_id#172, ca_country#169, agg1#173, agg2#174, agg3#175, agg4#176, agg5#177, agg6#178, agg7#179] +Keys [2]: [i_item_id#172, ca_country#169] +Functions [7]: [partial_avg(agg1#173), partial_avg(agg2#174), partial_avg(agg3#175), partial_avg(agg4#176), partial_avg(agg5#177), partial_avg(agg6#178), partial_avg(agg7#179)] +Aggregate Attributes [14]: [sum#180, count#181, sum#182, count#183, sum#184, count#185, sum#186, count#187, sum#188, count#189, sum#190, count#191, sum#192, count#193] +Results [16]: [i_item_id#172, ca_country#169, sum#194, count#195, sum#196, count#197, sum#198, count#199, sum#200, count#201, sum#202, count#203, sum#204, count#205, sum#206, count#207] + +(95) Exchange +Input [16]: [i_item_id#172, ca_country#169, sum#194, count#195, sum#196, count#197, sum#198, count#199, sum#200, count#201, sum#202, count#203, sum#204, count#205, sum#206, count#207] +Arguments: hashpartitioning(i_item_id#172, ca_country#169, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(96) HashAggregate [codegen id : 24] +Input [16]: [i_item_id#172, ca_country#169, sum#194, count#195, sum#196, count#197, sum#198, count#199, sum#200, count#201, sum#202, count#203, sum#204, count#205, sum#206, count#207] +Keys [2]: [i_item_id#172, ca_country#169] +Functions [7]: [avg(agg1#173), avg(agg2#174), avg(agg3#175), avg(agg4#176), avg(agg5#177), avg(agg6#178), avg(agg7#179)] +Aggregate Attributes [7]: [avg(agg1#173)#208, avg(agg2#174)#209, avg(agg3#175)#210, avg(agg4#176)#211, avg(agg5#177)#212, avg(agg6#178)#213, avg(agg7#179)#214] +Results [11]: [i_item_id#172, ca_country#169, null AS ca_state#215, null AS county#216, avg(agg1#173)#208 AS agg1#217, avg(agg2#174)#209 AS agg2#218, avg(agg3#175)#210 AS agg3#219, avg(agg4#176)#211 AS agg4#220, avg(agg5#177)#212 AS agg5#221, avg(agg6#178)#213 AS agg6#222, avg(agg7#179)#214 AS agg7#223] + +(97) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#224, cs_bill_cdemo_sk#225, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#232), dynamicpruningexpression(cs_sold_date_sk#232 IN dynamicpruning#233)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(98) ColumnarToRow [codegen id : 31] +Input [9]: [cs_bill_customer_sk#224, cs_bill_cdemo_sk#225, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232] + +(99) Filter [codegen id : 31] +Input [9]: [cs_bill_customer_sk#224, cs_bill_cdemo_sk#225, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232] +Condition : ((isnotnull(cs_bill_cdemo_sk#225) AND isnotnull(cs_bill_customer_sk#224)) AND isnotnull(cs_item_sk#226)) + +(100) ReusedExchange [Reuses operator id: 8] +Output [2]: [cd_demo_sk#234, cd_dep_count#235] + +(101) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [cs_bill_cdemo_sk#225] +Right keys [1]: [cd_demo_sk#234] +Join type: Inner +Join condition: None + +(102) Project [codegen id : 31] +Output [9]: [cs_bill_customer_sk#224, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235] +Input [11]: [cs_bill_customer_sk#224, cs_bill_cdemo_sk#225, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_demo_sk#234, cd_dep_count#235] + +(103) ReusedExchange [Reuses operator id: 15] +Output [4]: [c_customer_sk#236, c_current_cdemo_sk#237, c_current_addr_sk#238, c_birth_year#239] + +(104) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [cs_bill_customer_sk#224] +Right keys [1]: [c_customer_sk#236] +Join type: Inner +Join condition: None + +(105) Project [codegen id : 31] +Output [11]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_current_cdemo_sk#237, c_current_addr_sk#238, c_birth_year#239] +Input [13]: [cs_bill_customer_sk#224, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_customer_sk#236, c_current_cdemo_sk#237, c_current_addr_sk#238, c_birth_year#239] + +(106) ReusedExchange [Reuses operator id: 21] +Output [1]: [cd_demo_sk#240] + +(107) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [c_current_cdemo_sk#237] +Right keys [1]: [cd_demo_sk#240] +Join type: Inner +Join condition: None + +(108) Project [codegen id : 31] +Output [10]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_current_addr_sk#238, c_birth_year#239] +Input [12]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_current_cdemo_sk#237, c_current_addr_sk#238, c_birth_year#239, cd_demo_sk#240] + +(109) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#241, ca_state#242] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] +ReadSchema: struct + +(110) ColumnarToRow [codegen id : 28] +Input [2]: [ca_address_sk#241, ca_state#242] + +(111) Filter [codegen id : 28] +Input [2]: [ca_address_sk#241, ca_state#242] +Condition : (ca_state#242 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#241)) + +(112) Project [codegen id : 28] +Output [1]: [ca_address_sk#241] +Input [2]: [ca_address_sk#241, ca_state#242] + +(113) BroadcastExchange +Input [1]: [ca_address_sk#241] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +(114) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [c_current_addr_sk#238] +Right keys [1]: [ca_address_sk#241] +Join type: Inner +Join condition: None + +(115) Project [codegen id : 31] +Output [9]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_birth_year#239] +Input [11]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_current_addr_sk#238, c_birth_year#239, ca_address_sk#241] + +(116) ReusedExchange [Reuses operator id: 158] +Output [1]: [d_date_sk#243] + +(117) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [cs_sold_date_sk#232] +Right keys [1]: [d_date_sk#243] +Join type: Inner +Join condition: None + +(118) Project [codegen id : 31] +Output [8]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cd_dep_count#235, c_birth_year#239] +Input [10]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232, cd_dep_count#235, c_birth_year#239, d_date_sk#243] + +(119) ReusedExchange [Reuses operator id: 36] +Output [2]: [i_item_sk#244, i_item_id#245] + +(120) BroadcastHashJoin [codegen id : 31] +Left keys [1]: [cs_item_sk#226] +Right keys [1]: [i_item_sk#244] +Join type: Inner +Join condition: None + +(121) Project [codegen id : 31] +Output [8]: [i_item_id#245, cast(cs_quantity#227 as decimal(12,2)) AS agg1#246, cast(cs_list_price#228 as decimal(12,2)) AS agg2#247, cast(cs_coupon_amt#230 as decimal(12,2)) AS agg3#248, cast(cs_sales_price#229 as decimal(12,2)) AS agg4#249, cast(cs_net_profit#231 as decimal(12,2)) AS agg5#250, cast(c_birth_year#239 as decimal(12,2)) AS agg6#251, cast(cd_dep_count#235 as decimal(12,2)) AS agg7#252] +Input [10]: [cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cd_dep_count#235, c_birth_year#239, i_item_sk#244, i_item_id#245] + +(122) HashAggregate [codegen id : 31] +Input [8]: [i_item_id#245, agg1#246, agg2#247, agg3#248, agg4#249, agg5#250, agg6#251, agg7#252] +Keys [1]: [i_item_id#245] +Functions [7]: [partial_avg(agg1#246), partial_avg(agg2#247), partial_avg(agg3#248), partial_avg(agg4#249), partial_avg(agg5#250), partial_avg(agg6#251), partial_avg(agg7#252)] +Aggregate Attributes [14]: [sum#253, count#254, sum#255, count#256, sum#257, count#258, sum#259, count#260, sum#261, count#262, sum#263, count#264, sum#265, count#266] +Results [15]: [i_item_id#245, sum#267, count#268, sum#269, count#270, sum#271, count#272, sum#273, count#274, sum#275, count#276, sum#277, count#278, sum#279, count#280] + +(123) Exchange +Input [15]: [i_item_id#245, sum#267, count#268, sum#269, count#270, sum#271, count#272, sum#273, count#274, sum#275, count#276, sum#277, count#278, sum#279, count#280] +Arguments: hashpartitioning(i_item_id#245, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(124) HashAggregate [codegen id : 32] +Input [15]: [i_item_id#245, sum#267, count#268, sum#269, count#270, sum#271, count#272, sum#273, count#274, sum#275, count#276, sum#277, count#278, sum#279, count#280] +Keys [1]: [i_item_id#245] +Functions [7]: [avg(agg1#246), avg(agg2#247), avg(agg3#248), avg(agg4#249), avg(agg5#250), avg(agg6#251), avg(agg7#252)] +Aggregate Attributes [7]: [avg(agg1#246)#281, avg(agg2#247)#282, avg(agg3#248)#283, avg(agg4#249)#284, avg(agg5#250)#285, avg(agg6#251)#286, avg(agg7#252)#287] +Results [11]: [i_item_id#245, null AS ca_country#288, null AS ca_state#289, null AS county#290, avg(agg1#246)#281 AS agg1#291, avg(agg2#247)#282 AS agg2#292, avg(agg3#248)#283 AS agg3#293, avg(agg4#249)#284 AS agg4#294, avg(agg5#250)#285 AS agg5#295, avg(agg6#251)#286 AS agg6#296, avg(agg7#252)#287 AS agg7#297] + +(125) Scan parquet spark_catalog.default.catalog_sales +Output [9]: [cs_bill_customer_sk#298, cs_bill_cdemo_sk#299, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#306), dynamicpruningexpression(cs_sold_date_sk#306 IN dynamicpruning#307)] +PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(126) ColumnarToRow [codegen id : 39] +Input [9]: [cs_bill_customer_sk#298, cs_bill_cdemo_sk#299, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306] + +(127) Filter [codegen id : 39] +Input [9]: [cs_bill_customer_sk#298, cs_bill_cdemo_sk#299, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306] +Condition : ((isnotnull(cs_bill_cdemo_sk#299) AND isnotnull(cs_bill_customer_sk#298)) AND isnotnull(cs_item_sk#300)) + +(128) ReusedExchange [Reuses operator id: 8] +Output [2]: [cd_demo_sk#308, cd_dep_count#309] + +(129) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [cs_bill_cdemo_sk#299] +Right keys [1]: [cd_demo_sk#308] +Join type: Inner +Join condition: None + +(130) Project [codegen id : 39] +Output [9]: [cs_bill_customer_sk#298, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309] +Input [11]: [cs_bill_customer_sk#298, cs_bill_cdemo_sk#299, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_demo_sk#308, cd_dep_count#309] + +(131) ReusedExchange [Reuses operator id: 15] +Output [4]: [c_customer_sk#310, c_current_cdemo_sk#311, c_current_addr_sk#312, c_birth_year#313] + +(132) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [cs_bill_customer_sk#298] +Right keys [1]: [c_customer_sk#310] +Join type: Inner +Join condition: None + +(133) Project [codegen id : 39] +Output [11]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_current_cdemo_sk#311, c_current_addr_sk#312, c_birth_year#313] +Input [13]: [cs_bill_customer_sk#298, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_customer_sk#310, c_current_cdemo_sk#311, c_current_addr_sk#312, c_birth_year#313] + +(134) ReusedExchange [Reuses operator id: 21] +Output [1]: [cd_demo_sk#314] + +(135) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [c_current_cdemo_sk#311] +Right keys [1]: [cd_demo_sk#314] +Join type: Inner +Join condition: None + +(136) Project [codegen id : 39] +Output [10]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_current_addr_sk#312, c_birth_year#313] +Input [12]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_current_cdemo_sk#311, c_current_addr_sk#312, c_birth_year#313, cd_demo_sk#314] + +(137) ReusedExchange [Reuses operator id: 113] +Output [1]: [ca_address_sk#315] + +(138) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [c_current_addr_sk#312] +Right keys [1]: [ca_address_sk#315] +Join type: Inner +Join condition: None + +(139) Project [codegen id : 39] +Output [9]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_birth_year#313] +Input [11]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_current_addr_sk#312, c_birth_year#313, ca_address_sk#315] + +(140) ReusedExchange [Reuses operator id: 158] +Output [1]: [d_date_sk#316] + +(141) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [cs_sold_date_sk#306] +Right keys [1]: [d_date_sk#316] +Join type: Inner +Join condition: None + +(142) Project [codegen id : 39] +Output [8]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cd_dep_count#309, c_birth_year#313] +Input [10]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306, cd_dep_count#309, c_birth_year#313, d_date_sk#316] + +(143) Scan parquet spark_catalog.default.item +Output [1]: [i_item_sk#317] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(144) ColumnarToRow [codegen id : 38] +Input [1]: [i_item_sk#317] + +(145) Filter [codegen id : 38] +Input [1]: [i_item_sk#317] +Condition : isnotnull(i_item_sk#317) + +(146) BroadcastExchange +Input [1]: [i_item_sk#317] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +(147) BroadcastHashJoin [codegen id : 39] +Left keys [1]: [cs_item_sk#300] +Right keys [1]: [i_item_sk#317] +Join type: Inner +Join condition: None + +(148) Project [codegen id : 39] +Output [7]: [cast(cs_quantity#301 as decimal(12,2)) AS agg1#318, cast(cs_list_price#302 as decimal(12,2)) AS agg2#319, cast(cs_coupon_amt#304 as decimal(12,2)) AS agg3#320, cast(cs_sales_price#303 as decimal(12,2)) AS agg4#321, cast(cs_net_profit#305 as decimal(12,2)) AS agg5#322, cast(c_birth_year#313 as decimal(12,2)) AS agg6#323, cast(cd_dep_count#309 as decimal(12,2)) AS agg7#324] +Input [9]: [cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cd_dep_count#309, c_birth_year#313, i_item_sk#317] + +(149) HashAggregate [codegen id : 39] +Input [7]: [agg1#318, agg2#319, agg3#320, agg4#321, agg5#322, agg6#323, agg7#324] +Keys: [] +Functions [7]: [partial_avg(agg1#318), partial_avg(agg2#319), partial_avg(agg3#320), partial_avg(agg4#321), partial_avg(agg5#322), partial_avg(agg6#323), partial_avg(agg7#324)] +Aggregate Attributes [14]: [sum#325, count#326, sum#327, count#328, sum#329, count#330, sum#331, count#332, sum#333, count#334, sum#335, count#336, sum#337, count#338] +Results [14]: [sum#339, count#340, sum#341, count#342, sum#343, count#344, sum#345, count#346, sum#347, count#348, sum#349, count#350, sum#351, count#352] + +(150) Exchange +Input [14]: [sum#339, count#340, sum#341, count#342, sum#343, count#344, sum#345, count#346, sum#347, count#348, sum#349, count#350, sum#351, count#352] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=14] + +(151) HashAggregate [codegen id : 40] +Input [14]: [sum#339, count#340, sum#341, count#342, sum#343, count#344, sum#345, count#346, sum#347, count#348, sum#349, count#350, sum#351, count#352] +Keys: [] +Functions [7]: [avg(agg1#318), avg(agg2#319), avg(agg3#320), avg(agg4#321), avg(agg5#322), avg(agg6#323), avg(agg7#324)] +Aggregate Attributes [7]: [avg(agg1#318)#353, avg(agg2#319)#354, avg(agg3#320)#355, avg(agg4#321)#356, avg(agg5#322)#357, avg(agg6#323)#358, avg(agg7#324)#359] +Results [11]: [null AS i_item_id#360, null AS ca_country#361, null AS ca_state#362, null AS county#363, avg(agg1#318)#353 AS agg1#364, avg(agg2#319)#354 AS agg2#365, avg(agg3#320)#355 AS agg3#366, avg(agg4#321)#356 AS agg4#367, avg(agg5#322)#357 AS agg5#368, avg(agg6#323)#358 AS agg6#369, avg(agg7#324)#359 AS agg7#370] + +(152) Union + +(153) TakeOrderedAndProject +Input [11]: [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, agg1#70, agg2#71, agg3#72, agg4#73, agg5#74, agg6#75, agg7#76] +Arguments: 100, [ca_country#24 ASC NULLS FIRST, ca_state#23 ASC NULLS FIRST, ca_county#22 ASC NULLS FIRST, i_item_id#27 ASC NULLS FIRST], [i_item_id#27, ca_country#24, ca_state#23, ca_county#22, agg1#70, agg2#71, agg3#72, agg4#73, agg5#74, agg6#75, agg7#76] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#9 IN dynamicpruning#10 +BroadcastExchange (158) ++- * Project (157) + +- * Filter (156) + +- * ColumnarToRow (155) + +- CometScan parquet spark_catalog.default.date_dim (154) + + +(154) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_year#371] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(155) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#371] + +(156) Filter [codegen id : 1] +Input [2]: [d_date_sk#25, d_year#371] +Condition : ((isnotnull(d_year#371) AND (d_year#371 = 2001)) AND isnotnull(d_date_sk#25)) + +(157) Project [codegen id : 1] +Output [1]: [d_date_sk#25] +Input [2]: [d_date_sk#25, d_year#371] + +(158) BroadcastExchange +Input [1]: [d_date_sk#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15] + +Subquery:2 Hosting operator id = 42 Hosting Expression = cs_sold_date_sk#85 IN dynamicpruning#10 + +Subquery:3 Hosting operator id = 69 Hosting Expression = cs_sold_date_sk#158 IN dynamicpruning#10 + +Subquery:4 Hosting operator id = 97 Hosting Expression = cs_sold_date_sk#232 IN dynamicpruning#10 + +Subquery:5 Hosting operator id = 125 Hosting Expression = cs_sold_date_sk#306 IN dynamicpruning#10 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/simplified.txt new file mode 100644 index 000000000..369a6d222 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/simplified.txt @@ -0,0 +1,233 @@ +TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,agg4,agg5,agg6,agg7] + Union + WholeStageCodegen (8) + HashAggregate [i_item_id,ca_country,ca_state,ca_county,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,ca_country,ca_state,ca_county] #1 + WholeStageCodegen (7) + HashAggregate [i_item_id,ca_country,ca_state,ca_county,agg1,agg2,agg3,agg4,agg5,agg6,agg7] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,ca_country,ca_state,ca_county,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,ca_county,ca_state,ca_country] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year,ca_county,ca_state,ca_country] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [cd_demo_sk,cd_dep_count] + Filter [cd_gender,cd_education_status,cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_education_status,cd_dep_count] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + Filter [c_birth_month,c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_month,c_birth_year] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + WholeStageCodegen (16) + HashAggregate [i_item_id,ca_country,ca_state,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),county,agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,ca_country,ca_state] #8 + WholeStageCodegen (15) + HashAggregate [i_item_id,ca_country,ca_state,agg1,agg2,agg3,agg4,agg5,agg6,agg7] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,ca_country,ca_state,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,ca_state,ca_country] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year,ca_state,ca_country] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk,cd_dep_count] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] #4 + InputAdapter + ReusedExchange [cd_demo_sk] #5 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (12) + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #7 + WholeStageCodegen (24) + HashAggregate [i_item_id,ca_country,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),ca_state,county,agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,ca_country] #10 + WholeStageCodegen (23) + HashAggregate [i_item_id,ca_country,agg1,agg2,agg3,agg4,agg5,agg6,agg7] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,ca_country,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year,ca_country] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year,ca_country] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk,cd_dep_count] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] #4 + InputAdapter + ReusedExchange [cd_demo_sk] #5 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (20) + Project [ca_address_sk,ca_country] + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #7 + WholeStageCodegen (32) + HashAggregate [i_item_id,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),ca_country,ca_state,county,agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id] #12 + WholeStageCodegen (31) + HashAggregate [i_item_id,agg1,agg2,agg3,agg4,agg5,agg6,agg7] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk,cd_dep_count] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] #4 + InputAdapter + ReusedExchange [cd_demo_sk] #5 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (28) + Project [ca_address_sk] + Filter [ca_state,ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #7 + WholeStageCodegen (40) + HashAggregate [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),i_item_id,ca_country,ca_state,county,agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange #14 + WholeStageCodegen (39) + HashAggregate [agg1,agg2,agg3,agg4,agg5,agg6,agg7] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [cs_quantity,cs_list_price,cs_coupon_amt,cs_sales_price,cs_net_profit,c_birth_year,cd_dep_count] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cd_dep_count,c_birth_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_birth_year] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk,cd_dep_count] #3 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] #4 + InputAdapter + ReusedExchange [cd_demo_sk] #5 + InputAdapter + ReusedExchange [ca_address_sk] #13 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #15 + WholeStageCodegen (38) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/explain.txt new file mode 100644 index 000000000..5c6c60771 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/explain.txt @@ -0,0 +1,150 @@ +== Physical Plan == +TakeOrderedAndProject (20) ++- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : +- BroadcastExchange (7) + : +- * Filter (6) + : +- * ColumnarToRow (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] + +(3) Filter [codegen id : 3] +Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] +Condition : isnotnull(cs_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(6) Filter [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 25] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [cs_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [cs_ext_sales_price#2, cs_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [cs_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#2))#14] +Results [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#2))#14,17,2) AS _w0#16] + +(16) Exchange +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18] +Input [8]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, _we0#17] + +(20) TakeOrderedAndProject +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] +Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (25) ++- * Project (24) + +- * Filter (23) + +- * ColumnarToRow (22) + +- CometScan parquet spark_catalog.default.date_dim (21) + + +(21) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(22) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] + +(23) Filter [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(24) Project [codegen id : 1] +Output [1]: [d_date_sk#11] +Input [2]: [d_date_sk#11, d_date#19] + +(25) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/simplified.txt new file mode 100644 index 000000000..b5d7b5cc8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/simplified.txt @@ -0,0 +1,40 @@ +TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_current_price,itemrevenue] + WholeStageCodegen (6) + Project [i_item_id,i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #1 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(cs_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #2 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,cs_ext_sales_price] [sum,sum] + Project [cs_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ext_sales_price,cs_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [i_category,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/explain.txt new file mode 100644 index 000000000..5085b8ed3 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/explain.txt @@ -0,0 +1,161 @@ +== Physical Plan == +TakeOrderedAndProject (22) ++- * HashAggregate (21) + +- Exchange (20) + +- * HashAggregate (19) + +- * Expand (18) + +- * Project (17) + +- * BroadcastNestedLoopJoin Inner BuildRight (16) + :- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * Filter (9) + : +- * ColumnarToRow (8) + : +- CometScan parquet spark_catalog.default.item (7) + +- BroadcastExchange (15) + +- * ColumnarToRow (14) + +- CometScan parquet spark_catalog.default.warehouse (13) + + +(1) Scan parquet spark_catalog.default.inventory +Output [3]: [inv_item_sk#1, inv_quantity_on_hand#2, inv_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#3), dynamicpruningexpression(inv_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(inv_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [3]: [inv_item_sk#1, inv_quantity_on_hand#2, inv_date_sk#3] + +(3) Filter [codegen id : 4] +Input [3]: [inv_item_sk#1, inv_quantity_on_hand#2, inv_date_sk#3] +Condition : isnotnull(inv_item_sk#1) + +(4) ReusedExchange [Reuses operator id: 27] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [2]: [inv_item_sk#1, inv_quantity_on_hand#2] +Input [4]: [inv_item_sk#1, inv_quantity_on_hand#2, inv_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] + +(9) Filter [codegen id : 2] +Input [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] +Condition : isnotnull(i_item_sk#6) + +(10) BroadcastExchange +Input [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#2, i_brand#7, i_class#8, i_category#9, i_product_name#10] +Input [7]: [inv_item_sk#1, inv_quantity_on_hand#2, i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] + +(13) Scan parquet spark_catalog.default.warehouse +Output: [] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +ReadSchema: struct<> + +(14) ColumnarToRow [codegen id : 3] +Input: [] + +(15) BroadcastExchange +Input: [] +Arguments: IdentityBroadcastMode, [plan_id=2] + +(16) BroadcastNestedLoopJoin [codegen id : 4] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#2, i_product_name#10, i_brand#7, i_class#8, i_category#9] +Input [5]: [inv_quantity_on_hand#2, i_brand#7, i_class#8, i_category#9, i_product_name#10] + +(18) Expand [codegen id : 4] +Input [5]: [inv_quantity_on_hand#2, i_product_name#10, i_brand#7, i_class#8, i_category#9] +Arguments: [[inv_quantity_on_hand#2, i_product_name#10, i_brand#7, i_class#8, i_category#9, 0], [inv_quantity_on_hand#2, i_product_name#10, i_brand#7, i_class#8, null, 1], [inv_quantity_on_hand#2, i_product_name#10, i_brand#7, null, null, 3], [inv_quantity_on_hand#2, i_product_name#10, null, null, null, 7], [inv_quantity_on_hand#2, null, null, null, null, 15]], [inv_quantity_on_hand#2, i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15] + +(19) HashAggregate [codegen id : 4] +Input [6]: [inv_quantity_on_hand#2, i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15] +Keys [5]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15] +Functions [1]: [partial_avg(inv_quantity_on_hand#2)] +Aggregate Attributes [2]: [sum#16, count#17] +Results [7]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15, sum#18, count#19] + +(20) Exchange +Input [7]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15, sum#18, count#19] +Arguments: hashpartitioning(i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [7]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15, sum#18, count#19] +Keys [5]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, spark_grouping_id#15] +Functions [1]: [avg(inv_quantity_on_hand#2)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#2)#20] +Results [5]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, avg(inv_quantity_on_hand#2)#20 AS qoh#21] + +(22) TakeOrderedAndProject +Input [5]: [i_product_name#11, i_brand#12, i_class#13, i_category#14, qoh#21] +Arguments: 100, [qoh#21 ASC NULLS FIRST, i_product_name#11 ASC NULLS FIRST, i_brand#12 ASC NULLS FIRST, i_class#13 ASC NULLS FIRST, i_category#14 ASC NULLS FIRST], [i_product_name#11, i_brand#12, i_class#13, i_category#14, qoh#21] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (27) ++- * Project (26) + +- * Filter (25) + +- * ColumnarToRow (24) + +- CometScan parquet spark_catalog.default.date_dim (23) + + +(23) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] +ReadSchema: struct + +(24) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#22] + +(25) Filter [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#22] +Condition : (((isnotnull(d_month_seq#22) AND (d_month_seq#22 >= 1200)) AND (d_month_seq#22 <= 1211)) AND isnotnull(d_date_sk#5)) + +(26) Project [codegen id : 1] +Output [1]: [d_date_sk#5] +Input [2]: [d_date_sk#5, d_month_seq#22] + +(27) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/simplified.txt new file mode 100644 index 000000000..853aad173 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/simplified.txt @@ -0,0 +1,41 @@ +TakeOrderedAndProject [qoh,i_product_name,i_brand,i_class,i_category] + WholeStageCodegen (5) + HashAggregate [i_product_name,i_brand,i_class,i_category,spark_grouping_id,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + Exchange [i_product_name,i_brand,i_class,i_category,spark_grouping_id] #1 + WholeStageCodegen (4) + HashAggregate [i_product_name,i_brand,i_class,i_category,spark_grouping_id,inv_quantity_on_hand] [sum,count,sum,count] + Expand [inv_quantity_on_hand,i_product_name,i_brand,i_class,i_category] + Project [inv_quantity_on_hand,i_product_name,i_brand,i_class,i_category] + BroadcastNestedLoopJoin + Project [inv_quantity_on_hand,i_brand,i_class,i_category,i_product_name] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Project [inv_item_sk,inv_quantity_on_hand] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Filter [inv_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/explain.txt new file mode 100644 index 000000000..4f067d199 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/explain.txt @@ -0,0 +1,315 @@ +== Physical Plan == +TakeOrderedAndProject (45) ++- Union (44) + :- * HashAggregate (23) + : +- * HashAggregate (22) + : +- * HashAggregate (21) + : +- Exchange (20) + : +- * HashAggregate (19) + : +- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.inventory (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.item (7) + : +- BroadcastExchange (16) + : +- * Filter (15) + : +- * ColumnarToRow (14) + : +- CometScan parquet spark_catalog.default.warehouse (13) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * HashAggregate (25) + : +- ReusedExchange (24) + :- * HashAggregate (33) + : +- Exchange (32) + : +- * HashAggregate (31) + : +- * HashAggregate (30) + : +- ReusedExchange (29) + :- * HashAggregate (38) + : +- Exchange (37) + : +- * HashAggregate (36) + : +- * HashAggregate (35) + : +- ReusedExchange (34) + +- * HashAggregate (43) + +- Exchange (42) + +- * HashAggregate (41) + +- * HashAggregate (40) + +- ReusedExchange (39) + + +(1) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] + +(3) Filter [codegen id : 4] +Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) + +(4) ReusedExchange [Reuses operator id: 50] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [3]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3] +Input [5]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] + +(9) Filter [codegen id : 2] +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Condition : isnotnull(i_item_sk#7) + +(10) BroadcastExchange +Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_item_sk#1] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Input [8]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] + +(13) Scan parquet spark_catalog.default.warehouse +Output [1]: [w_warehouse_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [1]: [w_warehouse_sk#12] + +(15) Filter [codegen id : 3] +Input [1]: [w_warehouse_sk#12] +Condition : isnotnull(w_warehouse_sk#12) + +(16) BroadcastExchange +Input [1]: [w_warehouse_sk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [inv_warehouse_sk#2] +Right keys [1]: [w_warehouse_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [5]: [inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Input [7]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11, w_warehouse_sk#12] + +(19) HashAggregate [codegen id : 4] +Input [5]: [inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Keys [4]: [i_product_name#11, i_brand#8, i_class#9, i_category#10] +Functions [1]: [partial_avg(inv_quantity_on_hand#3)] +Aggregate Attributes [2]: [sum#13, count#14] +Results [6]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, sum#15, count#16] + +(20) Exchange +Input [6]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, sum#15, count#16] +Arguments: hashpartitioning(i_product_name#11, i_brand#8, i_class#9, i_category#10, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [6]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, sum#15, count#16] +Keys [4]: [i_product_name#11, i_brand#8, i_class#9, i_category#10] +Functions [1]: [avg(inv_quantity_on_hand#3)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#3)#17] +Results [5]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, avg(inv_quantity_on_hand#3)#17 AS qoh#18] + +(22) HashAggregate [codegen id : 5] +Input [5]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, qoh#18] +Keys [4]: [i_product_name#11, i_brand#8, i_class#9, i_category#10] +Functions [1]: [partial_avg(qoh#18)] +Aggregate Attributes [2]: [sum#19, count#20] +Results [6]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, sum#21, count#22] + +(23) HashAggregate [codegen id : 5] +Input [6]: [i_product_name#11, i_brand#8, i_class#9, i_category#10, sum#21, count#22] +Keys [4]: [i_product_name#11, i_brand#8, i_class#9, i_category#10] +Functions [1]: [avg(qoh#18)] +Aggregate Attributes [1]: [avg(qoh#18)#23] +Results [5]: [i_product_name#11 AS i_product_name#24, i_brand#8 AS i_brand#25, i_class#9 AS i_class#26, i_category#10 AS i_category#27, avg(qoh#18)#23 AS qoh#28] + +(24) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_product_name#29, i_brand#30, i_class#31, i_category#32, sum#33, count#34] + +(25) HashAggregate [codegen id : 10] +Input [6]: [i_product_name#29, i_brand#30, i_class#31, i_category#32, sum#33, count#34] +Keys [4]: [i_product_name#29, i_brand#30, i_class#31, i_category#32] +Functions [1]: [avg(inv_quantity_on_hand#35)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#35)#17] +Results [4]: [i_product_name#29, i_brand#30, i_class#31, avg(inv_quantity_on_hand#35)#17 AS qoh#36] + +(26) HashAggregate [codegen id : 10] +Input [4]: [i_product_name#29, i_brand#30, i_class#31, qoh#36] +Keys [3]: [i_product_name#29, i_brand#30, i_class#31] +Functions [1]: [partial_avg(qoh#36)] +Aggregate Attributes [2]: [sum#37, count#38] +Results [5]: [i_product_name#29, i_brand#30, i_class#31, sum#39, count#40] + +(27) Exchange +Input [5]: [i_product_name#29, i_brand#30, i_class#31, sum#39, count#40] +Arguments: hashpartitioning(i_product_name#29, i_brand#30, i_class#31, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 11] +Input [5]: [i_product_name#29, i_brand#30, i_class#31, sum#39, count#40] +Keys [3]: [i_product_name#29, i_brand#30, i_class#31] +Functions [1]: [avg(qoh#36)] +Aggregate Attributes [1]: [avg(qoh#36)#41] +Results [5]: [i_product_name#29, i_brand#30, i_class#31, null AS i_category#42, avg(qoh#36)#41 AS qoh#43] + +(29) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_product_name#44, i_brand#45, i_class#46, i_category#47, sum#48, count#49] + +(30) HashAggregate [codegen id : 16] +Input [6]: [i_product_name#44, i_brand#45, i_class#46, i_category#47, sum#48, count#49] +Keys [4]: [i_product_name#44, i_brand#45, i_class#46, i_category#47] +Functions [1]: [avg(inv_quantity_on_hand#50)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#50)#17] +Results [3]: [i_product_name#44, i_brand#45, avg(inv_quantity_on_hand#50)#17 AS qoh#51] + +(31) HashAggregate [codegen id : 16] +Input [3]: [i_product_name#44, i_brand#45, qoh#51] +Keys [2]: [i_product_name#44, i_brand#45] +Functions [1]: [partial_avg(qoh#51)] +Aggregate Attributes [2]: [sum#52, count#53] +Results [4]: [i_product_name#44, i_brand#45, sum#54, count#55] + +(32) Exchange +Input [4]: [i_product_name#44, i_brand#45, sum#54, count#55] +Arguments: hashpartitioning(i_product_name#44, i_brand#45, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(33) HashAggregate [codegen id : 17] +Input [4]: [i_product_name#44, i_brand#45, sum#54, count#55] +Keys [2]: [i_product_name#44, i_brand#45] +Functions [1]: [avg(qoh#51)] +Aggregate Attributes [1]: [avg(qoh#51)#56] +Results [5]: [i_product_name#44, i_brand#45, null AS i_class#57, null AS i_category#58, avg(qoh#51)#56 AS qoh#59] + +(34) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_product_name#60, i_brand#61, i_class#62, i_category#63, sum#64, count#65] + +(35) HashAggregate [codegen id : 22] +Input [6]: [i_product_name#60, i_brand#61, i_class#62, i_category#63, sum#64, count#65] +Keys [4]: [i_product_name#60, i_brand#61, i_class#62, i_category#63] +Functions [1]: [avg(inv_quantity_on_hand#66)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#66)#17] +Results [2]: [i_product_name#60, avg(inv_quantity_on_hand#66)#17 AS qoh#67] + +(36) HashAggregate [codegen id : 22] +Input [2]: [i_product_name#60, qoh#67] +Keys [1]: [i_product_name#60] +Functions [1]: [partial_avg(qoh#67)] +Aggregate Attributes [2]: [sum#68, count#69] +Results [3]: [i_product_name#60, sum#70, count#71] + +(37) Exchange +Input [3]: [i_product_name#60, sum#70, count#71] +Arguments: hashpartitioning(i_product_name#60, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(38) HashAggregate [codegen id : 23] +Input [3]: [i_product_name#60, sum#70, count#71] +Keys [1]: [i_product_name#60] +Functions [1]: [avg(qoh#67)] +Aggregate Attributes [1]: [avg(qoh#67)#72] +Results [5]: [i_product_name#60, null AS i_brand#73, null AS i_class#74, null AS i_category#75, avg(qoh#67)#72 AS qoh#76] + +(39) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_product_name#77, i_brand#78, i_class#79, i_category#80, sum#81, count#82] + +(40) HashAggregate [codegen id : 28] +Input [6]: [i_product_name#77, i_brand#78, i_class#79, i_category#80, sum#81, count#82] +Keys [4]: [i_product_name#77, i_brand#78, i_class#79, i_category#80] +Functions [1]: [avg(inv_quantity_on_hand#83)] +Aggregate Attributes [1]: [avg(inv_quantity_on_hand#83)#17] +Results [1]: [avg(inv_quantity_on_hand#83)#17 AS qoh#84] + +(41) HashAggregate [codegen id : 28] +Input [1]: [qoh#84] +Keys: [] +Functions [1]: [partial_avg(qoh#84)] +Aggregate Attributes [2]: [sum#85, count#86] +Results [2]: [sum#87, count#88] + +(42) Exchange +Input [2]: [sum#87, count#88] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(43) HashAggregate [codegen id : 29] +Input [2]: [sum#87, count#88] +Keys: [] +Functions [1]: [avg(qoh#84)] +Aggregate Attributes [1]: [avg(qoh#84)#89] +Results [5]: [null AS i_product_name#90, null AS i_brand#91, null AS i_class#92, null AS i_category#93, avg(qoh#84)#89 AS qoh#94] + +(44) Union + +(45) TakeOrderedAndProject +Input [5]: [i_product_name#24, i_brand#25, i_class#26, i_category#27, qoh#28] +Arguments: 100, [qoh#28 ASC NULLS FIRST, i_product_name#24 ASC NULLS FIRST, i_brand#25 ASC NULLS FIRST, i_class#26 ASC NULLS FIRST, i_category#27 ASC NULLS FIRST], [i_product_name#24, i_brand#25, i_class#26, i_category#27, qoh#28] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (50) ++- * Project (49) + +- * Filter (48) + +- * ColumnarToRow (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_month_seq#95] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#6, d_month_seq#95] + +(48) Filter [codegen id : 1] +Input [2]: [d_date_sk#6, d_month_seq#95] +Condition : (((isnotnull(d_month_seq#95) AND (d_month_seq#95 >= 1212)) AND (d_month_seq#95 <= 1223)) AND isnotnull(d_date_sk#6)) + +(49) Project [codegen id : 1] +Output [1]: [d_date_sk#6] +Input [2]: [d_date_sk#6, d_month_seq#95] + +(50) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/simplified.txt new file mode 100644 index 000000000..0819dc055 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/simplified.txt @@ -0,0 +1,80 @@ +TakeOrderedAndProject [qoh,i_product_name,i_brand,i_class,i_category] + Union + WholeStageCodegen (5) + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(qoh),i_product_name,i_brand,i_class,i_category,qoh,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,qoh] [sum,count,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + Exchange [i_product_name,i_brand,i_class,i_category] #1 + WholeStageCodegen (4) + HashAggregate [i_product_name,i_brand,i_class,i_category,inv_quantity_on_hand] [sum,count,sum,count] + Project [inv_quantity_on_hand,i_brand,i_class,i_category,i_product_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [inv_warehouse_sk,inv_quantity_on_hand,i_brand,i_class,i_category,i_product_name] + BroadcastHashJoin [inv_item_sk,i_item_sk] + Project [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand] + BroadcastHashJoin [inv_date_sk,d_date_sk] + Filter [inv_item_sk,inv_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk] + WholeStageCodegen (11) + HashAggregate [i_product_name,i_brand,i_class,sum,count] [avg(qoh),i_category,qoh,sum,count] + InputAdapter + Exchange [i_product_name,i_brand,i_class] #5 + WholeStageCodegen (10) + HashAggregate [i_product_name,i_brand,i_class,qoh] [sum,count,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + ReusedExchange [i_product_name,i_brand,i_class,i_category,sum,count] #1 + WholeStageCodegen (17) + HashAggregate [i_product_name,i_brand,sum,count] [avg(qoh),i_class,i_category,qoh,sum,count] + InputAdapter + Exchange [i_product_name,i_brand] #6 + WholeStageCodegen (16) + HashAggregate [i_product_name,i_brand,qoh] [sum,count,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + ReusedExchange [i_product_name,i_brand,i_class,i_category,sum,count] #1 + WholeStageCodegen (23) + HashAggregate [i_product_name,sum,count] [avg(qoh),i_brand,i_class,i_category,qoh,sum,count] + InputAdapter + Exchange [i_product_name] #7 + WholeStageCodegen (22) + HashAggregate [i_product_name,qoh] [sum,count,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + ReusedExchange [i_product_name,i_brand,i_class,i_category,sum,count] #1 + WholeStageCodegen (29) + HashAggregate [sum,count] [avg(qoh),i_product_name,i_brand,i_class,i_category,qoh,sum,count] + InputAdapter + Exchange #8 + WholeStageCodegen (28) + HashAggregate [qoh] [sum,count,sum,count] + HashAggregate [i_product_name,i_brand,i_class,i_category,sum,count] [avg(inv_quantity_on_hand),qoh,sum,count] + InputAdapter + ReusedExchange [i_product_name,i_brand,i_class,i_category,sum,count] #1 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/explain.txt new file mode 100644 index 000000000..f2d354a2d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/explain.txt @@ -0,0 +1,437 @@ +== Physical Plan == +* Sort (48) ++- Exchange (47) + +- * Filter (46) + +- * HashAggregate (45) + +- Exchange (44) + +- * HashAggregate (43) + +- * HashAggregate (42) + +- Exchange (41) + +- * HashAggregate (40) + +- * Project (39) + +- * BroadcastHashJoin Inner BuildRight (38) + :- * Project (33) + : +- * BroadcastHashJoin Inner BuildRight (32) + : :- * Project (27) + : : +- * BroadcastHashJoin Inner BuildRight (26) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Project (14) + : : : : +- * SortMergeJoin Inner (13) + : : : : :- * Sort (6) + : : : : : +- Exchange (5) + : : : : : +- * Project (4) + : : : : : +- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- * Sort (12) + : : : : +- Exchange (11) + : : : : +- * Project (10) + : : : : +- * Filter (9) + : : : : +- * ColumnarToRow (8) + : : : : +- CometScan parquet spark_catalog.default.store_returns (7) + : : : +- BroadcastExchange (19) + : : : +- * Project (18) + : : : +- * Filter (17) + : : : +- * ColumnarToRow (16) + : : : +- CometScan parquet spark_catalog.default.store (15) + : : +- BroadcastExchange (25) + : : +- * Filter (24) + : : +- * ColumnarToRow (23) + : : +- CometScan parquet spark_catalog.default.item (22) + : +- BroadcastExchange (31) + : +- * Filter (30) + : +- * ColumnarToRow (29) + : +- CometScan parquet spark_catalog.default.customer (28) + +- BroadcastExchange (37) + +- * Filter (36) + +- * ColumnarToRow (35) + +- CometScan parquet spark_catalog.default.customer_address (34) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_sales] +PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] + +(3) Filter [codegen id : 1] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_customer_sk#2)) + +(4) Project [codegen id : 1] +Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] + +(5) Exchange +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: hashpartitioning(ss_ticket_number#4, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(6) Sort [codegen id : 2] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +Arguments: [ss_ticket_number#4 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(7) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 3] +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] + +(9) Filter [codegen id : 3] +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Condition : (isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#7)) + +(10) Project [codegen id : 3] +Output [2]: [sr_item_sk#7, sr_ticket_number#8] +Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] + +(11) Exchange +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: hashpartitioning(sr_ticket_number#8, sr_item_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 4] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] +Arguments: [sr_ticket_number#8 ASC NULLS FIRST, sr_item_sk#7 ASC NULLS FIRST], false, 0 + +(13) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#4, ss_item_sk#1] +Right keys [2]: [sr_ticket_number#8, sr_item_sk#7] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 9] +Output [4]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, sr_item_sk#7, sr_ticket_number#8] + +(15) Scan parquet spark_catalog.default.store +Output [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_market_id), EqualTo(s_market_id,8), IsNotNull(s_store_sk), IsNotNull(s_zip)] +ReadSchema: struct + +(16) ColumnarToRow [codegen id : 5] +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] + +(17) Filter [codegen id : 5] +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Condition : (((isnotnull(s_market_id#12) AND (s_market_id#12 = 8)) AND isnotnull(s_store_sk#10)) AND isnotnull(s_zip#14)) + +(18) Project [codegen id : 5] +Output [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] + +(19) BroadcastExchange +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#10] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 9] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14] +Input [8]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_net_paid#5, s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(22) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_color), EqualTo(i_color,pale ), IsNotNull(i_item_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(24) Filter [codegen id : 6] +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Condition : ((isnotnull(i_color#18) AND (i_color#18 = pale )) AND isnotnull(i_item_sk#15)) + +(25) BroadcastExchange +Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(26) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#15] +Join type: Inner +Join condition: None + +(27) Project [codegen id : 9] +Output [10]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] + +(28) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk), IsNotNull(c_birth_country)] +ReadSchema: struct + +(29) ColumnarToRow [codegen id : 7] +Input [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] + +(30) Filter [codegen id : 7] +Input [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] +Condition : ((isnotnull(c_customer_sk#21) AND isnotnull(c_current_addr_sk#22)) AND isnotnull(c_birth_country#25)) + +(31) BroadcastExchange +Input [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(32) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#21] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 9] +Output [13]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] +Input [15]: [ss_customer_sk#2, ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] + +(34) Scan parquet spark_catalog.default.customer_address +Output [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_country), IsNotNull(ca_zip)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 8] +Input [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] + +(36) Filter [codegen id : 8] +Input [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] +Condition : ((isnotnull(ca_address_sk#26) AND isnotnull(ca_country#29)) AND isnotnull(ca_zip#28)) + +(37) BroadcastExchange +Input [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] +Arguments: HashedRelationBroadcastMode(List(input[0, int, false], upper(input[3, string, false]), input[2, string, false]),false), [plan_id=6] + +(38) BroadcastHashJoin [codegen id : 9] +Left keys [3]: [c_current_addr_sk#22, c_birth_country#25, s_zip#14] +Right keys [3]: [ca_address_sk#26, upper(ca_country#29), ca_zip#28] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 9] +Output [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#23, c_last_name#24, ca_state#27] +Input [17]: [ss_net_paid#5, s_store_name#11, s_state#13, s_zip#14, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25, ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] + +(40) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#5, s_store_name#11, s_state#13, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20, c_first_name#23, c_last_name#24, ca_state#27] +Keys [10]: [c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum#30] +Results [11]: [c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#31] + +(41) Exchange +Input [11]: [c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#31] +Arguments: hashpartitioning(c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(42) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17, sum#31] +Keys [10]: [c_last_name#24, c_first_name#23, s_store_name#11, ca_state#27, s_state#13, i_color#18, i_current_price#16, i_manager_id#20, i_units#19, i_size#17] +Functions [1]: [sum(UnscaledValue(ss_net_paid#5))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#5))#32] +Results [4]: [c_last_name#24, c_first_name#23, s_store_name#11, MakeDecimal(sum(UnscaledValue(ss_net_paid#5))#32,17,2) AS netpaid#33] + +(43) HashAggregate [codegen id : 10] +Input [4]: [c_last_name#24, c_first_name#23, s_store_name#11, netpaid#33] +Keys [3]: [c_last_name#24, c_first_name#23, s_store_name#11] +Functions [1]: [partial_sum(netpaid#33)] +Aggregate Attributes [2]: [sum#34, isEmpty#35] +Results [5]: [c_last_name#24, c_first_name#23, s_store_name#11, sum#36, isEmpty#37] + +(44) Exchange +Input [5]: [c_last_name#24, c_first_name#23, s_store_name#11, sum#36, isEmpty#37] +Arguments: hashpartitioning(c_last_name#24, c_first_name#23, s_store_name#11, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(45) HashAggregate [codegen id : 11] +Input [5]: [c_last_name#24, c_first_name#23, s_store_name#11, sum#36, isEmpty#37] +Keys [3]: [c_last_name#24, c_first_name#23, s_store_name#11] +Functions [1]: [sum(netpaid#33)] +Aggregate Attributes [1]: [sum(netpaid#33)#38] +Results [4]: [c_last_name#24, c_first_name#23, s_store_name#11, sum(netpaid#33)#38 AS paid#39] + +(46) Filter [codegen id : 11] +Input [4]: [c_last_name#24, c_first_name#23, s_store_name#11, paid#39] +Condition : (isnotnull(paid#39) AND (cast(paid#39 as decimal(33,8)) > cast(Subquery scalar-subquery#40, [id=#41] as decimal(33,8)))) + +(47) Exchange +Input [4]: [c_last_name#24, c_first_name#23, s_store_name#11, paid#39] +Arguments: rangepartitioning(c_last_name#24 ASC NULLS FIRST, c_first_name#23 ASC NULLS FIRST, s_store_name#11 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(48) Sort [codegen id : 12] +Input [4]: [c_last_name#24, c_first_name#23, s_store_name#11, paid#39] +Arguments: [c_last_name#24 ASC NULLS FIRST, c_first_name#23 ASC NULLS FIRST, s_store_name#11 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 46 Hosting Expression = Subquery scalar-subquery#40, [id=#41] +* HashAggregate (75) ++- Exchange (74) + +- * HashAggregate (73) + +- * HashAggregate (72) + +- Exchange (71) + +- * HashAggregate (70) + +- * Project (69) + +- * BroadcastHashJoin Inner BuildRight (68) + :- * Project (66) + : +- * BroadcastHashJoin Inner BuildRight (65) + : :- * Project (63) + : : +- * BroadcastHashJoin Inner BuildRight (62) + : : :- * Project (57) + : : : +- * BroadcastHashJoin Inner BuildRight (56) + : : : :- * Project (54) + : : : : +- * SortMergeJoin Inner (53) + : : : : :- * Sort (50) + : : : : : +- ReusedExchange (49) + : : : : +- * Sort (52) + : : : : +- ReusedExchange (51) + : : : +- ReusedExchange (55) + : : +- BroadcastExchange (61) + : : +- * Filter (60) + : : +- * ColumnarToRow (59) + : : +- CometScan parquet spark_catalog.default.item (58) + : +- ReusedExchange (64) + +- ReusedExchange (67) + + +(49) ReusedExchange [Reuses operator id: 5] +Output [5]: [ss_item_sk#42, ss_customer_sk#43, ss_store_sk#44, ss_ticket_number#45, ss_net_paid#46] + +(50) Sort [codegen id : 2] +Input [5]: [ss_item_sk#42, ss_customer_sk#43, ss_store_sk#44, ss_ticket_number#45, ss_net_paid#46] +Arguments: [ss_ticket_number#45 ASC NULLS FIRST, ss_item_sk#42 ASC NULLS FIRST], false, 0 + +(51) ReusedExchange [Reuses operator id: 11] +Output [2]: [sr_item_sk#47, sr_ticket_number#48] + +(52) Sort [codegen id : 4] +Input [2]: [sr_item_sk#47, sr_ticket_number#48] +Arguments: [sr_ticket_number#48 ASC NULLS FIRST, sr_item_sk#47 ASC NULLS FIRST], false, 0 + +(53) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_ticket_number#45, ss_item_sk#42] +Right keys [2]: [sr_ticket_number#48, sr_item_sk#47] +Join type: Inner +Join condition: None + +(54) Project [codegen id : 9] +Output [4]: [ss_item_sk#42, ss_customer_sk#43, ss_store_sk#44, ss_net_paid#46] +Input [7]: [ss_item_sk#42, ss_customer_sk#43, ss_store_sk#44, ss_ticket_number#45, ss_net_paid#46, sr_item_sk#47, sr_ticket_number#48] + +(55) ReusedExchange [Reuses operator id: 19] +Output [4]: [s_store_sk#49, s_store_name#50, s_state#51, s_zip#52] + +(56) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#44] +Right keys [1]: [s_store_sk#49] +Join type: Inner +Join condition: None + +(57) Project [codegen id : 9] +Output [6]: [ss_item_sk#42, ss_customer_sk#43, ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52] +Input [8]: [ss_item_sk#42, ss_customer_sk#43, ss_store_sk#44, ss_net_paid#46, s_store_sk#49, s_store_name#50, s_state#51, s_zip#52] + +(58) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(59) ColumnarToRow [codegen id : 6] +Input [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] + +(60) Filter [codegen id : 6] +Input [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] +Condition : isnotnull(i_item_sk#53) + +(61) BroadcastExchange +Input [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] + +(62) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#42] +Right keys [1]: [i_item_sk#53] +Join type: Inner +Join condition: None + +(63) Project [codegen id : 9] +Output [10]: [ss_customer_sk#43, ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] +Input [12]: [ss_item_sk#42, ss_customer_sk#43, ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52, i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] + +(64) ReusedExchange [Reuses operator id: 31] +Output [5]: [c_customer_sk#59, c_current_addr_sk#60, c_first_name#61, c_last_name#62, c_birth_country#63] + +(65) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_customer_sk#43] +Right keys [1]: [c_customer_sk#59] +Join type: Inner +Join condition: None + +(66) Project [codegen id : 9] +Output [13]: [ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58, c_current_addr_sk#60, c_first_name#61, c_last_name#62, c_birth_country#63] +Input [15]: [ss_customer_sk#43, ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58, c_customer_sk#59, c_current_addr_sk#60, c_first_name#61, c_last_name#62, c_birth_country#63] + +(67) ReusedExchange [Reuses operator id: 37] +Output [4]: [ca_address_sk#64, ca_state#65, ca_zip#66, ca_country#67] + +(68) BroadcastHashJoin [codegen id : 9] +Left keys [3]: [c_current_addr_sk#60, c_birth_country#63, s_zip#52] +Right keys [3]: [ca_address_sk#64, upper(ca_country#67), ca_zip#66] +Join type: Inner +Join condition: None + +(69) Project [codegen id : 9] +Output [11]: [ss_net_paid#46, s_store_name#50, s_state#51, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58, c_first_name#61, c_last_name#62, ca_state#65] +Input [17]: [ss_net_paid#46, s_store_name#50, s_state#51, s_zip#52, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58, c_current_addr_sk#60, c_first_name#61, c_last_name#62, c_birth_country#63, ca_address_sk#64, ca_state#65, ca_zip#66, ca_country#67] + +(70) HashAggregate [codegen id : 9] +Input [11]: [ss_net_paid#46, s_store_name#50, s_state#51, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58, c_first_name#61, c_last_name#62, ca_state#65] +Keys [10]: [c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#46))] +Aggregate Attributes [1]: [sum#68] +Results [11]: [c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55, sum#69] + +(71) Exchange +Input [11]: [c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55, sum#69] +Arguments: hashpartitioning(c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(72) HashAggregate [codegen id : 10] +Input [11]: [c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55, sum#69] +Keys [10]: [c_last_name#62, c_first_name#61, s_store_name#50, ca_state#65, s_state#51, i_color#56, i_current_price#54, i_manager_id#58, i_units#57, i_size#55] +Functions [1]: [sum(UnscaledValue(ss_net_paid#46))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#46))#32] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_net_paid#46))#32,17,2) AS netpaid#70] + +(73) HashAggregate [codegen id : 10] +Input [1]: [netpaid#70] +Keys: [] +Functions [1]: [partial_avg(netpaid#70)] +Aggregate Attributes [2]: [sum#71, count#72] +Results [2]: [sum#73, count#74] + +(74) Exchange +Input [2]: [sum#73, count#74] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=12] + +(75) HashAggregate [codegen id : 11] +Input [2]: [sum#73, count#74] +Keys: [] +Functions [1]: [avg(netpaid#70)] +Aggregate Attributes [1]: [avg(netpaid#70)#75] +Results [1]: [(0.05 * avg(netpaid#70)#75) AS (0.05 * avg(netpaid))#76] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/simplified.txt new file mode 100644 index 000000000..02c50e74d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/simplified.txt @@ -0,0 +1,122 @@ +WholeStageCodegen (12) + Sort [c_last_name,c_first_name,s_store_name] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name] #1 + WholeStageCodegen (11) + Filter [paid] + Subquery #1 + WholeStageCodegen (11) + HashAggregate [sum,count] [avg(netpaid),(0.05 * avg(netpaid)),sum,count] + InputAdapter + Exchange #10 + WholeStageCodegen (10) + HashAggregate [netpaid] [sum,count,sum,count] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #11 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_current_addr_sk,c_birth_country,s_zip,ca_address_sk,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_current_addr_sk,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + ReusedExchange [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] #4 + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + ReusedExchange [sr_item_sk,sr_ticket_number] #5 + InputAdapter + ReusedExchange [s_store_sk,s_store_name,s_state,s_zip] #6 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (6) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + ReusedExchange [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name,c_birth_country] #8 + InputAdapter + ReusedExchange [ca_address_sk,ca_state,ca_zip,ca_country] #9 + HashAggregate [c_last_name,c_first_name,s_store_name,sum,isEmpty] [sum(netpaid),paid,sum,isEmpty] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name] #2 + WholeStageCodegen (10) + HashAggregate [c_last_name,c_first_name,s_store_name,netpaid] [sum,isEmpty,sum,isEmpty] + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,sum] [sum(UnscaledValue(ss_net_paid)),netpaid,sum] + InputAdapter + Exchange [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size] #3 + WholeStageCodegen (9) + HashAggregate [c_last_name,c_first_name,s_store_name,ca_state,s_state,i_color,i_current_price,i_manager_id,i_units,i_size,ss_net_paid] [sum,sum] + Project [ss_net_paid,s_store_name,s_state,i_current_price,i_size,i_color,i_units,i_manager_id,c_first_name,c_last_name,ca_state] + BroadcastHashJoin [c_current_addr_sk,c_birth_country,s_zip,ca_address_sk,ca_country,ca_zip] + Project [ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id,c_current_addr_sk,c_first_name,c_last_name,c_birth_country] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip,i_current_price,i_size,i_color,i_units,i_manager_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_customer_sk,ss_net_paid,s_store_name,s_state,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_net_paid] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #4 + WholeStageCodegen (1) + Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] + Filter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid,ss_sold_date_sk] + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #5 + WholeStageCodegen (3) + Project [sr_item_sk,sr_ticket_number] + Filter [sr_ticket_number,sr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Project [s_store_sk,s_store_name,s_state,s_zip] + Filter [s_market_id,s_store_sk,s_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_market_id,s_state,s_zip] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + Filter [i_color,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (7) + Filter [c_customer_sk,c_current_addr_sk,c_birth_country] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name,c_birth_country] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (8) + Filter [ca_address_sk,ca_country,ca_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_zip,ca_country] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/explain.txt new file mode 100644 index 000000000..803b7f919 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/explain.txt @@ -0,0 +1,457 @@ +== Physical Plan == +TakeOrderedAndProject (73) ++- Union (72) + :- * HashAggregate (28) + : +- Exchange (27) + : +- * HashAggregate (26) + : +- * Project (25) + : +- * BroadcastHashJoin Inner BuildRight (24) + : :- * Project (19) + : : +- * BroadcastHashJoin Inner BuildRight (18) + : : :- * Project (13) + : : : +- * BroadcastHashJoin Inner BuildRight (12) + : : : :- * Project (10) + : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- BroadcastExchange (8) + : : : : +- * Project (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) + : : : +- ReusedExchange (11) + : : +- BroadcastExchange (17) + : : +- * Filter (16) + : : +- * ColumnarToRow (15) + : : +- CometScan parquet spark_catalog.default.store (14) + : +- BroadcastExchange (23) + : +- * Filter (22) + : +- * ColumnarToRow (21) + : +- CometScan parquet spark_catalog.default.item (20) + :- * HashAggregate (50) + : +- Exchange (49) + : +- * HashAggregate (48) + : +- * Project (47) + : +- * BroadcastHashJoin Inner BuildRight (46) + : :- * Project (44) + : : +- * BroadcastHashJoin Inner BuildRight (43) + : : :- * Project (37) + : : : +- * BroadcastHashJoin Inner BuildRight (36) + : : : :- * Project (34) + : : : : +- * BroadcastHashJoin Inner BuildRight (33) + : : : : :- * Filter (31) + : : : : : +- * ColumnarToRow (30) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (29) + : : : : +- ReusedExchange (32) + : : : +- ReusedExchange (35) + : : +- BroadcastExchange (42) + : : +- * Project (41) + : : +- * Filter (40) + : : +- * ColumnarToRow (39) + : : +- CometScan parquet spark_catalog.default.store (38) + : +- ReusedExchange (45) + +- * HashAggregate (71) + +- Exchange (70) + +- * HashAggregate (69) + +- * Project (68) + +- * BroadcastHashJoin Inner BuildRight (67) + :- * Project (62) + : +- * BroadcastHashJoin Inner BuildRight (61) + : :- * Project (59) + : : +- * BroadcastHashJoin Inner BuildRight (58) + : : :- * Project (56) + : : : +- * BroadcastHashJoin Inner BuildRight (55) + : : : :- * Filter (53) + : : : : +- * ColumnarToRow (52) + : : : : +- CometScan parquet spark_catalog.default.store_sales (51) + : : : +- ReusedExchange (54) + : : +- ReusedExchange (57) + : +- ReusedExchange (60) + +- BroadcastExchange (66) + +- * Filter (65) + +- * ColumnarToRow (64) + +- CometScan parquet spark_catalog.default.item (63) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 5] +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] + +(3) Filter [codegen id : 5] +Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_item_sk#1)) + +(4) Scan parquet spark_catalog.default.customer_demographics +Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,F), EqualTo(cd_marital_status,W), EqualTo(cd_education_status,Primary ), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] + +(6) Filter [codegen id : 1] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = F)) AND (cd_marital_status#12 = W)) AND (cd_education_status#13 = Primary )) AND isnotnull(cd_demo_sk#10)) + +(7) Project [codegen id : 1] +Output [1]: [cd_demo_sk#10] +Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] + +(8) BroadcastExchange +Input [1]: [cd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#10] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 5] +Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Input [9]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, cd_demo_sk#10] + +(11) ReusedExchange [Reuses operator id: 78] +Output [1]: [d_date_sk#14] + +(12) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_sold_date_sk#8] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 5] +Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, d_date_sk#14] + +(14) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#15, s_state#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [2]: [s_store_sk#15, s_state#16] + +(16) Filter [codegen id : 3] +Input [2]: [s_store_sk#15, s_state#16] +Condition : ((isnotnull(s_state#16) AND (s_state#16 = TN)) AND isnotnull(s_store_sk#15)) + +(17) BroadcastExchange +Input [2]: [s_store_sk#15, s_state#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#15] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 5] +Output [6]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#16] +Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_store_sk#15, s_state#16] + +(20) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#17, i_item_id#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#17, i_item_id#18] + +(22) Filter [codegen id : 4] +Input [2]: [i_item_sk#17, i_item_id#18] +Condition : isnotnull(i_item_sk#17) + +(23) BroadcastExchange +Input [2]: [i_item_sk#17, i_item_id#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 5] +Output [6]: [i_item_id#18, s_state#16, ss_quantity#4 AS agg1#19, ss_list_price#5 AS agg2#20, ss_coupon_amt#7 AS agg3#21, ss_sales_price#6 AS agg4#22] +Input [8]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#16, i_item_sk#17, i_item_id#18] + +(26) HashAggregate [codegen id : 5] +Input [6]: [i_item_id#18, s_state#16, agg1#19, agg2#20, agg3#21, agg4#22] +Keys [2]: [i_item_id#18, s_state#16] +Functions [4]: [partial_avg(agg1#19), partial_avg(UnscaledValue(agg2#20)), partial_avg(UnscaledValue(agg3#21)), partial_avg(UnscaledValue(agg4#22))] +Aggregate Attributes [8]: [sum#23, count#24, sum#25, count#26, sum#27, count#28, sum#29, count#30] +Results [10]: [i_item_id#18, s_state#16, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38] + +(27) Exchange +Input [10]: [i_item_id#18, s_state#16, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38] +Arguments: hashpartitioning(i_item_id#18, s_state#16, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(28) HashAggregate [codegen id : 6] +Input [10]: [i_item_id#18, s_state#16, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38] +Keys [2]: [i_item_id#18, s_state#16] +Functions [4]: [avg(agg1#19), avg(UnscaledValue(agg2#20)), avg(UnscaledValue(agg3#21)), avg(UnscaledValue(agg4#22))] +Aggregate Attributes [4]: [avg(agg1#19)#39, avg(UnscaledValue(agg2#20))#40, avg(UnscaledValue(agg3#21))#41, avg(UnscaledValue(agg4#22))#42] +Results [7]: [i_item_id#18, s_state#16, 0 AS g_state#43, avg(agg1#19)#39 AS agg1#44, cast((avg(UnscaledValue(agg2#20))#40 / 100.0) as decimal(11,6)) AS agg2#45, cast((avg(UnscaledValue(agg3#21))#41 / 100.0) as decimal(11,6)) AS agg3#46, cast((avg(UnscaledValue(agg4#22))#42 / 100.0) as decimal(11,6)) AS agg4#47] + +(29) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_item_sk#48, ss_cdemo_sk#49, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#55), dynamicpruningexpression(ss_sold_date_sk#55 IN dynamicpruning#56)] +PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 11] +Input [8]: [ss_item_sk#48, ss_cdemo_sk#49, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55] + +(31) Filter [codegen id : 11] +Input [8]: [ss_item_sk#48, ss_cdemo_sk#49, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55] +Condition : ((isnotnull(ss_cdemo_sk#49) AND isnotnull(ss_store_sk#50)) AND isnotnull(ss_item_sk#48)) + +(32) ReusedExchange [Reuses operator id: 8] +Output [1]: [cd_demo_sk#57] + +(33) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ss_cdemo_sk#49] +Right keys [1]: [cd_demo_sk#57] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 11] +Output [7]: [ss_item_sk#48, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55] +Input [9]: [ss_item_sk#48, ss_cdemo_sk#49, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55, cd_demo_sk#57] + +(35) ReusedExchange [Reuses operator id: 78] +Output [1]: [d_date_sk#58] + +(36) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ss_sold_date_sk#55] +Right keys [1]: [d_date_sk#58] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 11] +Output [6]: [ss_item_sk#48, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54] +Input [8]: [ss_item_sk#48, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55, d_date_sk#58] + +(38) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#59, s_state#60] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(39) ColumnarToRow [codegen id : 9] +Input [2]: [s_store_sk#59, s_state#60] + +(40) Filter [codegen id : 9] +Input [2]: [s_store_sk#59, s_state#60] +Condition : ((isnotnull(s_state#60) AND (s_state#60 = TN)) AND isnotnull(s_store_sk#59)) + +(41) Project [codegen id : 9] +Output [1]: [s_store_sk#59] +Input [2]: [s_store_sk#59, s_state#60] + +(42) BroadcastExchange +Input [1]: [s_store_sk#59] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(43) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ss_store_sk#50] +Right keys [1]: [s_store_sk#59] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 11] +Output [5]: [ss_item_sk#48, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54] +Input [7]: [ss_item_sk#48, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, s_store_sk#59] + +(45) ReusedExchange [Reuses operator id: 23] +Output [2]: [i_item_sk#61, i_item_id#62] + +(46) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [ss_item_sk#48] +Right keys [1]: [i_item_sk#61] +Join type: Inner +Join condition: None + +(47) Project [codegen id : 11] +Output [5]: [i_item_id#62, ss_quantity#51 AS agg1#63, ss_list_price#52 AS agg2#64, ss_coupon_amt#54 AS agg3#65, ss_sales_price#53 AS agg4#66] +Input [7]: [ss_item_sk#48, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, i_item_sk#61, i_item_id#62] + +(48) HashAggregate [codegen id : 11] +Input [5]: [i_item_id#62, agg1#63, agg2#64, agg3#65, agg4#66] +Keys [1]: [i_item_id#62] +Functions [4]: [partial_avg(agg1#63), partial_avg(UnscaledValue(agg2#64)), partial_avg(UnscaledValue(agg3#65)), partial_avg(UnscaledValue(agg4#66))] +Aggregate Attributes [8]: [sum#67, count#68, sum#69, count#70, sum#71, count#72, sum#73, count#74] +Results [9]: [i_item_id#62, sum#75, count#76, sum#77, count#78, sum#79, count#80, sum#81, count#82] + +(49) Exchange +Input [9]: [i_item_id#62, sum#75, count#76, sum#77, count#78, sum#79, count#80, sum#81, count#82] +Arguments: hashpartitioning(i_item_id#62, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(50) HashAggregate [codegen id : 12] +Input [9]: [i_item_id#62, sum#75, count#76, sum#77, count#78, sum#79, count#80, sum#81, count#82] +Keys [1]: [i_item_id#62] +Functions [4]: [avg(agg1#63), avg(UnscaledValue(agg2#64)), avg(UnscaledValue(agg3#65)), avg(UnscaledValue(agg4#66))] +Aggregate Attributes [4]: [avg(agg1#63)#83, avg(UnscaledValue(agg2#64))#84, avg(UnscaledValue(agg3#65))#85, avg(UnscaledValue(agg4#66))#86] +Results [7]: [i_item_id#62, null AS s_state#87, 1 AS g_state#88, avg(agg1#63)#83 AS agg1#89, cast((avg(UnscaledValue(agg2#64))#84 / 100.0) as decimal(11,6)) AS agg2#90, cast((avg(UnscaledValue(agg3#65))#85 / 100.0) as decimal(11,6)) AS agg3#91, cast((avg(UnscaledValue(agg4#66))#86 / 100.0) as decimal(11,6)) AS agg4#92] + +(51) Scan parquet spark_catalog.default.store_sales +Output [8]: [ss_item_sk#93, ss_cdemo_sk#94, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#100), dynamicpruningexpression(ss_sold_date_sk#100 IN dynamicpruning#101)] +PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(52) ColumnarToRow [codegen id : 17] +Input [8]: [ss_item_sk#93, ss_cdemo_sk#94, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100] + +(53) Filter [codegen id : 17] +Input [8]: [ss_item_sk#93, ss_cdemo_sk#94, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100] +Condition : ((isnotnull(ss_cdemo_sk#94) AND isnotnull(ss_store_sk#95)) AND isnotnull(ss_item_sk#93)) + +(54) ReusedExchange [Reuses operator id: 8] +Output [1]: [cd_demo_sk#102] + +(55) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ss_cdemo_sk#94] +Right keys [1]: [cd_demo_sk#102] +Join type: Inner +Join condition: None + +(56) Project [codegen id : 17] +Output [7]: [ss_item_sk#93, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100] +Input [9]: [ss_item_sk#93, ss_cdemo_sk#94, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100, cd_demo_sk#102] + +(57) ReusedExchange [Reuses operator id: 78] +Output [1]: [d_date_sk#103] + +(58) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ss_sold_date_sk#100] +Right keys [1]: [d_date_sk#103] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 17] +Output [6]: [ss_item_sk#93, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99] +Input [8]: [ss_item_sk#93, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100, d_date_sk#103] + +(60) ReusedExchange [Reuses operator id: 42] +Output [1]: [s_store_sk#104] + +(61) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ss_store_sk#95] +Right keys [1]: [s_store_sk#104] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 17] +Output [5]: [ss_item_sk#93, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99] +Input [7]: [ss_item_sk#93, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, s_store_sk#104] + +(63) Scan parquet spark_catalog.default.item +Output [1]: [i_item_sk#105] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(64) ColumnarToRow [codegen id : 16] +Input [1]: [i_item_sk#105] + +(65) Filter [codegen id : 16] +Input [1]: [i_item_sk#105] +Condition : isnotnull(i_item_sk#105) + +(66) BroadcastExchange +Input [1]: [i_item_sk#105] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(67) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ss_item_sk#93] +Right keys [1]: [i_item_sk#105] +Join type: Inner +Join condition: None + +(68) Project [codegen id : 17] +Output [4]: [ss_quantity#96 AS agg1#106, ss_list_price#97 AS agg2#107, ss_coupon_amt#99 AS agg3#108, ss_sales_price#98 AS agg4#109] +Input [6]: [ss_item_sk#93, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, i_item_sk#105] + +(69) HashAggregate [codegen id : 17] +Input [4]: [agg1#106, agg2#107, agg3#108, agg4#109] +Keys: [] +Functions [4]: [partial_avg(agg1#106), partial_avg(UnscaledValue(agg2#107)), partial_avg(UnscaledValue(agg3#108)), partial_avg(UnscaledValue(agg4#109))] +Aggregate Attributes [8]: [sum#110, count#111, sum#112, count#113, sum#114, count#115, sum#116, count#117] +Results [8]: [sum#118, count#119, sum#120, count#121, sum#122, count#123, sum#124, count#125] + +(70) Exchange +Input [8]: [sum#118, count#119, sum#120, count#121, sum#122, count#123, sum#124, count#125] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=8] + +(71) HashAggregate [codegen id : 18] +Input [8]: [sum#118, count#119, sum#120, count#121, sum#122, count#123, sum#124, count#125] +Keys: [] +Functions [4]: [avg(agg1#106), avg(UnscaledValue(agg2#107)), avg(UnscaledValue(agg3#108)), avg(UnscaledValue(agg4#109))] +Aggregate Attributes [4]: [avg(agg1#106)#126, avg(UnscaledValue(agg2#107))#127, avg(UnscaledValue(agg3#108))#128, avg(UnscaledValue(agg4#109))#129] +Results [7]: [null AS i_item_id#130, null AS s_state#131, 1 AS g_state#132, avg(agg1#106)#126 AS agg1#133, cast((avg(UnscaledValue(agg2#107))#127 / 100.0) as decimal(11,6)) AS agg2#134, cast((avg(UnscaledValue(agg3#108))#128 / 100.0) as decimal(11,6)) AS agg3#135, cast((avg(UnscaledValue(agg4#109))#129 / 100.0) as decimal(11,6)) AS agg4#136] + +(72) Union + +(73) TakeOrderedAndProject +Input [7]: [i_item_id#18, s_state#16, g_state#43, agg1#44, agg2#45, agg3#46, agg4#47] +Arguments: 100, [i_item_id#18 ASC NULLS FIRST, s_state#16 ASC NULLS FIRST], [i_item_id#18, s_state#16, g_state#43, agg1#44, agg2#45, agg3#46, agg4#47] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (78) ++- * Project (77) + +- * Filter (76) + +- * ColumnarToRow (75) + +- CometScan parquet spark_catalog.default.date_dim (74) + + +(74) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_year#137] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1998), IsNotNull(d_date_sk)] +ReadSchema: struct + +(75) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#137] + +(76) Filter [codegen id : 1] +Input [2]: [d_date_sk#14, d_year#137] +Condition : ((isnotnull(d_year#137) AND (d_year#137 = 1998)) AND isnotnull(d_date_sk#14)) + +(77) Project [codegen id : 1] +Output [1]: [d_date_sk#14] +Input [2]: [d_date_sk#14, d_year#137] + +(78) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] + +Subquery:2 Hosting operator id = 29 Hosting Expression = ss_sold_date_sk#55 IN dynamicpruning#9 + +Subquery:3 Hosting operator id = 51 Hosting Expression = ss_sold_date_sk#100 IN dynamicpruning#9 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/simplified.txt new file mode 100644 index 000000000..a05c3e288 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/simplified.txt @@ -0,0 +1,117 @@ +TakeOrderedAndProject [i_item_id,s_state,g_state,agg1,agg2,agg3,agg4] + Union + WholeStageCodegen (6) + HashAggregate [i_item_id,s_state,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(UnscaledValue(agg2)),avg(UnscaledValue(agg3)),avg(UnscaledValue(agg4)),g_state,agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id,s_state] #1 + WholeStageCodegen (5) + HashAggregate [i_item_id,s_state,agg1,agg2,agg3,agg4] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,s_state,ss_quantity,ss_list_price,ss_coupon_amt,ss_sales_price] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Filter [ss_cdemo_sk,ss_store_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #2 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Project [cd_demo_sk] + Filter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (3) + Filter [s_state,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] + WholeStageCodegen (12) + HashAggregate [i_item_id,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(UnscaledValue(agg2)),avg(UnscaledValue(agg3)),avg(UnscaledValue(agg4)),s_state,g_state,agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange [i_item_id] #6 + WholeStageCodegen (11) + HashAggregate [i_item_id,agg1,agg2,agg3,agg4] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [i_item_id,ss_quantity,ss_list_price,ss_coupon_amt,ss_sales_price] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Filter [ss_cdemo_sk,ss_store_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (9) + Project [s_store_sk] + Filter [s_state,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + ReusedExchange [i_item_sk,i_item_id] #5 + WholeStageCodegen (18) + HashAggregate [sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(UnscaledValue(agg2)),avg(UnscaledValue(agg3)),avg(UnscaledValue(agg4)),i_item_id,s_state,g_state,agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] + InputAdapter + Exchange #8 + WholeStageCodegen (17) + HashAggregate [agg1,agg2,agg3,agg4] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] + Project [ss_quantity,ss_list_price,ss_coupon_amt,ss_sales_price] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Filter [ss_cdemo_sk,ss_store_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [cd_demo_sk] #3 + InputAdapter + ReusedExchange [d_date_sk] #2 + InputAdapter + ReusedExchange [s_store_sk] #7 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (16) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/explain.txt new file mode 100644 index 000000000..a42f101d7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/explain.txt @@ -0,0 +1,218 @@ +== Physical Plan == +* Sort (32) ++- Exchange (31) + +- * Project (30) + +- * BroadcastHashJoin Inner BuildRight (29) + :- * Filter (24) + : +- * HashAggregate (23) + : +- Exchange (22) + : +- * HashAggregate (21) + : +- * Project (20) + : +- * BroadcastHashJoin Inner BuildRight (19) + : :- * Project (13) + : : +- * BroadcastHashJoin Inner BuildRight (12) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (11) + : : +- * Project (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (18) + : +- * Project (17) + : +- * Filter (16) + : +- * ColumnarToRow (15) + : +- CometScan parquet spark_catalog.default.household_demographics (14) + +- BroadcastExchange (28) + +- * Filter (27) + +- * ColumnarToRow (26) + +- CometScan parquet spark_catalog.default.customer (25) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] + +(3) Filter [codegen id : 4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) + +(4) ReusedExchange [Reuses operator id: 37] +Output [1]: [d_date_sk#7] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4] +Input [6]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5, d_date_sk#7] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#8, s_county#9] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_county), EqualTo(s_county,Williamson County), IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#8, s_county#9] + +(9) Filter [codegen id : 2] +Input [2]: [s_store_sk#8, s_county#9] +Condition : ((isnotnull(s_county#9) AND (s_county#9 = Williamson County)) AND isnotnull(s_store_sk#8)) + +(10) Project [codegen id : 2] +Output [1]: [s_store_sk#8] +Input [2]: [s_store_sk#8, s_county#9] + +(11) BroadcastExchange +Input [1]: [s_store_sk#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(12) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#3] +Right keys [1]: [s_store_sk#8] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 4] +Output [3]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4] +Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, s_store_sk#8] + +(14) Scan parquet spark_catalog.default.household_demographics +Output [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_vehicle_count), Or(EqualTo(hd_buy_potential,>10000 ),EqualTo(hd_buy_potential,unknown )), GreaterThan(hd_vehicle_count,0), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(15) ColumnarToRow [codegen id : 3] +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] + +(16) Filter [codegen id : 3] +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Condition : ((((isnotnull(hd_vehicle_count#13) AND ((hd_buy_potential#11 = >10000 ) OR (hd_buy_potential#11 = unknown ))) AND (hd_vehicle_count#13 > 0)) AND CASE WHEN (hd_vehicle_count#13 > 0) THEN ((cast(hd_dep_count#12 as double) / cast(hd_vehicle_count#13 as double)) > 1.2) END) AND isnotnull(hd_demo_sk#10)) + +(17) Project [codegen id : 3] +Output [1]: [hd_demo_sk#10] +Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] + +(18) BroadcastExchange +Input [1]: [hd_demo_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(19) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_hdemo_sk#2] +Right keys [1]: [hd_demo_sk#10] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 4] +Output [2]: [ss_customer_sk#1, ss_ticket_number#4] +Input [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4, hd_demo_sk#10] + +(21) HashAggregate [codegen id : 4] +Input [2]: [ss_customer_sk#1, ss_ticket_number#4] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#14] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] + +(22) Exchange +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Arguments: hashpartitioning(ss_ticket_number#4, ss_customer_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(23) HashAggregate [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15] +Keys [2]: [ss_ticket_number#4, ss_customer_sk#1] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#16] +Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count(1)#16 AS cnt#17] + +(24) Filter [codegen id : 6] +Input [3]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17] +Condition : ((cnt#17 >= 15) AND (cnt#17 <= 20)) + +(25) Scan parquet spark_catalog.default.customer +Output [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 5] +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(27) Filter [codegen id : 5] +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Condition : isnotnull(c_customer_sk#18) + +(28) BroadcastExchange +Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_customer_sk#1] +Right keys [1]: [c_customer_sk#18] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 6] +Output [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Input [8]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17, c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] + +(31) Exchange +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: rangepartitioning(c_last_name#21 ASC NULLS FIRST, c_first_name#20 ASC NULLS FIRST, c_salutation#19 ASC NULLS FIRST, c_preferred_cust_flag#22 DESC NULLS LAST, ss_ticket_number#4 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 7] +Input [6]: [c_last_name#21, c_first_name#20, c_salutation#19, c_preferred_cust_flag#22, ss_ticket_number#4, cnt#17] +Arguments: [c_last_name#21 ASC NULLS FIRST, c_first_name#20 ASC NULLS FIRST, c_salutation#19 ASC NULLS FIRST, c_preferred_cust_flag#22 DESC NULLS LAST, ss_ticket_number#4 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (37) ++- * Project (36) + +- * Filter (35) + +- * ColumnarToRow (34) + +- CometScan parquet spark_catalog.default.date_dim (33) + + +(33) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#23, d_dom#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(And(GreaterThanOrEqual(d_dom,1),LessThanOrEqual(d_dom,3)),And(GreaterThanOrEqual(d_dom,25),LessThanOrEqual(d_dom,28))), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(34) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] + +(35) Filter [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Condition : (((((d_dom#24 >= 1) AND (d_dom#24 <= 3)) OR ((d_dom#24 >= 25) AND (d_dom#24 <= 28))) AND d_year#23 IN (1999,2000,2001)) AND isnotnull(d_date_sk#7)) + +(36) Project [codegen id : 1] +Output [1]: [d_date_sk#7] +Input [3]: [d_date_sk#7, d_year#23, d_dom#24] + +(37) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/simplified.txt new file mode 100644 index 000000000..cb7ac8dc8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/simplified.txt @@ -0,0 +1,56 @@ +WholeStageCodegen (7) + Sort [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag,ss_ticket_number] + InputAdapter + Exchange [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag,ss_ticket_number] #1 + WholeStageCodegen (6) + Project [c_last_name,c_first_name,c_salutation,c_preferred_cust_flag,ss_ticket_number,cnt] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Filter [cnt] + HashAggregate [ss_ticket_number,ss_customer_sk,count] [count(1),cnt,count] + InputAdapter + Exchange [ss_ticket_number,ss_customer_sk] #2 + WholeStageCodegen (4) + HashAggregate [ss_ticket_number,ss_customer_sk] [count,count] + Project [ss_customer_sk,ss_ticket_number] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_ticket_number] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_dom,d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Project [s_store_sk] + Filter [s_county,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_county] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Project [hd_demo_sk] + Filter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential,hd_dep_count,hd_vehicle_count] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (5) + Filter [c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/explain.txt new file mode 100644 index 000000000..03d608ad6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/explain.txt @@ -0,0 +1,281 @@ +== Physical Plan == +TakeOrderedAndProject (42) ++- * HashAggregate (41) + +- Exchange (40) + +- * HashAggregate (39) + +- * Project (38) + +- * BroadcastHashJoin Inner BuildRight (37) + :- * Project (32) + : +- * BroadcastHashJoin Inner BuildRight (31) + : :- * Project (26) + : : +- * Filter (25) + : : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (24) + : : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (17) + : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (9) + : : : : +- * Project (8) + : : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : : :- * ColumnarToRow (5) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : : +- ReusedExchange (6) + : : : +- BroadcastExchange (16) + : : : +- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- BroadcastExchange (23) + : : +- * Project (22) + : : +- * BroadcastHashJoin Inner BuildRight (21) + : : :- * ColumnarToRow (19) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) + : : +- ReusedExchange (20) + : +- BroadcastExchange (30) + : +- * Filter (29) + : +- * ColumnarToRow (28) + : +- CometScan parquet spark_catalog.default.customer_address (27) + +- BroadcastExchange (36) + +- * Filter (35) + +- * ColumnarToRow (34) + +- CometScan parquet spark_catalog.default.customer_demographics (33) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] + +(3) Filter [codegen id : 9] +Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#6, ss_sold_date_sk#7] + +(6) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#9] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#6] +Input [3]: [ss_customer_sk#6, ss_sold_date_sk#7, d_date_sk#9] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ss_customer_sk#6] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#11), dynamicpruningexpression(ws_sold_date_sk#11 IN dynamicpruning#12)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11] + +(13) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#13] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#11] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#10] +Input [3]: [ws_bill_customer_sk#10, ws_sold_date_sk#11, d_date_sk#13] + +(16) BroadcastExchange +Input [1]: [ws_bill_customer_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ws_bill_customer_sk#10] +Join type: ExistenceJoin(exists#2) +Join condition: None + +(18) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#15), dynamicpruningexpression(cs_sold_date_sk#15 IN dynamicpruning#16)] +ReadSchema: struct + +(19) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#14, cs_sold_date_sk#15] + +(20) ReusedExchange [Reuses operator id: 47] +Output [1]: [d_date_sk#17] + +(21) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#15] +Right keys [1]: [d_date_sk#17] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#14] +Input [3]: [cs_ship_customer_sk#14, cs_sold_date_sk#15, d_date_sk#17] + +(23) BroadcastExchange +Input [1]: [cs_ship_customer_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [cs_ship_customer_sk#14] +Join type: ExistenceJoin(exists#1) +Join condition: None + +(25) Filter [codegen id : 9] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] +Condition : (exists#2 OR exists#1) + +(26) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#4, c_current_addr_sk#5] +Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1] + +(27) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#18, ca_state#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(28) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_state#19] + +(29) Filter [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_state#19] +Condition : isnotnull(ca_address_sk#18) + +(30) BroadcastExchange +Input [2]: [ca_address_sk#18, ca_state#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(31) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#5] +Right keys [1]: [ca_address_sk#18] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#4, ca_state#19] +Input [4]: [c_current_cdemo_sk#4, c_current_addr_sk#5, ca_address_sk#18, ca_state#19] + +(33) Scan parquet spark_catalog.default.customer_demographics +Output [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(34) ColumnarToRow [codegen id : 8] +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(35) Filter [codegen id : 8] +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Condition : isnotnull(cd_demo_sk#20) + +(36) BroadcastExchange +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] + +(37) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#4] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 9] +Output [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Input [8]: [c_current_cdemo_sk#4, ca_state#19, cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(39) HashAggregate [codegen id : 9] +Input [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [partial_count(1), partial_avg(cd_dep_count#23), partial_max(cd_dep_count#23), partial_sum(cd_dep_count#23), partial_avg(cd_dep_employed_count#24), partial_max(cd_dep_employed_count#24), partial_sum(cd_dep_employed_count#24), partial_avg(cd_dep_college_count#25), partial_max(cd_dep_college_count#25), partial_sum(cd_dep_college_count#25)] +Aggregate Attributes [13]: [count#26, sum#27, count#28, max#29, sum#30, sum#31, count#32, max#33, sum#34, sum#35, count#36, max#37, sum#38] +Results [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] + +(40) Exchange +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] +Arguments: hashpartitioning(ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 10] +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [count(1), avg(cd_dep_count#23), max(cd_dep_count#23), sum(cd_dep_count#23), avg(cd_dep_employed_count#24), max(cd_dep_employed_count#24), sum(cd_dep_employed_count#24), avg(cd_dep_college_count#25), max(cd_dep_college_count#25), sum(cd_dep_college_count#25)] +Aggregate Attributes [10]: [count(1)#52, avg(cd_dep_count#23)#53, max(cd_dep_count#23)#54, sum(cd_dep_count#23)#55, avg(cd_dep_employed_count#24)#56, max(cd_dep_employed_count#24)#57, sum(cd_dep_employed_count#24)#58, avg(cd_dep_college_count#25)#59, max(cd_dep_college_count#25)#60, sum(cd_dep_college_count#25)#61] +Results [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, count(1)#52 AS cnt1#62, avg(cd_dep_count#23)#53 AS avg(cd_dep_count)#63, max(cd_dep_count#23)#54 AS max(cd_dep_count)#64, sum(cd_dep_count#23)#55 AS sum(cd_dep_count)#65, cd_dep_employed_count#24, count(1)#52 AS cnt2#66, avg(cd_dep_employed_count#24)#56 AS avg(cd_dep_employed_count)#67, max(cd_dep_employed_count#24)#57 AS max(cd_dep_employed_count)#68, sum(cd_dep_employed_count#24)#58 AS sum(cd_dep_employed_count)#69, cd_dep_college_count#25, count(1)#52 AS cnt3#70, avg(cd_dep_college_count#25)#59 AS avg(cd_dep_college_count)#71, max(cd_dep_college_count#25)#60 AS max(cd_dep_college_count)#72, sum(cd_dep_college_count#25)#61 AS sum(cd_dep_college_count)#73] + +(42) TakeOrderedAndProject +Input [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cnt1#62, avg(cd_dep_count)#63, max(cd_dep_count)#64, sum(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, avg(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, sum(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, avg(cd_dep_college_count)#71, max(cd_dep_college_count)#72, sum(cd_dep_college_count)#73] +Arguments: 100, [ca_state#19 ASC NULLS FIRST, cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FIRST, cd_dep_count#23 ASC NULLS FIRST, cd_dep_employed_count#24 ASC NULLS FIRST, cd_dep_college_count#25 ASC NULLS FIRST], [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cnt1#62, avg(cd_dep_count)#63, max(cd_dep_count)#64, sum(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, avg(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, sum(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, avg(cd_dep_college_count)#71, max(cd_dep_college_count)#72, sum(cd_dep_college_count)#73] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (47) ++- * Project (46) + +- * Filter (45) + +- * ColumnarToRow (44) + +- CometScan parquet spark_catalog.default.date_dim (43) + + +(43) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,2002), LessThan(d_qoy,4), IsNotNull(d_date_sk)] +ReadSchema: struct + +(44) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] + +(45) Filter [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Condition : ((((isnotnull(d_year#74) AND isnotnull(d_qoy#75)) AND (d_year#74 = 2002)) AND (d_qoy#75 < 4)) AND isnotnull(d_date_sk#9)) + +(46) Project [codegen id : 1] +Output [1]: [d_date_sk#9] +Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] + +(47) BroadcastExchange +Input [1]: [d_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#11 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 18 Hosting Expression = cs_sold_date_sk#15 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/simplified.txt new file mode 100644 index 000000000..6b81822e4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/simplified.txt @@ -0,0 +1,74 @@ +TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,cnt1,avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),cnt2,avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),cnt3,avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count)] + WholeStageCodegen (10) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] [count(1),avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count),cnt1,avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),cnt2,avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),cnt3,avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count),count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] + InputAdapter + Exchange [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] #1 + WholeStageCodegen (9) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] [count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum,count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] + Project [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk,ca_state] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + Filter [exists,exists] + BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_current_addr_sk,c_current_cdemo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_qoy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + Filter [ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (8) + Filter [cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/explain.txt new file mode 100644 index 000000000..11ca8c0c8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/explain.txt @@ -0,0 +1,267 @@ +== Physical Plan == +TakeOrderedAndProject (40) ++- * HashAggregate (39) + +- Exchange (38) + +- * HashAggregate (37) + +- * Project (36) + +- * BroadcastHashJoin Inner BuildRight (35) + :- * Project (30) + : +- * BroadcastHashJoin Inner BuildRight (29) + : :- * Project (24) + : : +- * BroadcastHashJoin LeftSemi BuildRight (23) + : : :- * BroadcastHashJoin LeftSemi BuildRight (10) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : +- BroadcastExchange (9) + : : : +- * Project (8) + : : : +- * BroadcastHashJoin Inner BuildRight (7) + : : : :- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (6) + : : +- BroadcastExchange (22) + : : +- Union (21) + : : :- * Project (15) + : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : :- * ColumnarToRow (12) + : : : : +- CometScan parquet spark_catalog.default.web_sales (11) + : : : +- ReusedExchange (13) + : : +- * Project (20) + : : +- * BroadcastHashJoin Inner BuildRight (19) + : : :- * ColumnarToRow (17) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) + : : +- ReusedExchange (18) + : +- BroadcastExchange (28) + : +- * Filter (27) + : +- * ColumnarToRow (26) + : +- CometScan parquet spark_catalog.default.customer_address (25) + +- BroadcastExchange (34) + +- * Filter (33) + +- * ColumnarToRow (32) + +- CometScan parquet spark_catalog.default.customer_demographics (31) + + +(1) Scan parquet spark_catalog.default.customer +Output [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 9] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(3) Filter [codegen id : 9] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [2]: [ss_customer_sk#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 2] +Input [2]: [ss_customer_sk#4, ss_sold_date_sk#5] + +(6) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#7] + +(7) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(8) Project [codegen id : 2] +Output [1]: [ss_customer_sk#4] +Input [3]: [ss_customer_sk#4, ss_sold_date_sk#5, d_date_sk#7] + +(9) BroadcastExchange +Input [1]: [ss_customer_sk#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(10) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#4] +Join type: LeftSemi +Join condition: None + +(11) Scan parquet spark_catalog.default.web_sales +Output [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#9), dynamicpruningexpression(ws_sold_date_sk#9 IN dynamicpruning#10)] +ReadSchema: struct + +(12) ColumnarToRow [codegen id : 4] +Input [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9] + +(13) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#11] + +(14) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ws_sold_date_sk#9] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 4] +Output [1]: [ws_bill_customer_sk#8 AS customsk#12] +Input [3]: [ws_bill_customer_sk#8, ws_sold_date_sk#9, d_date_sk#11] + +(16) Scan parquet spark_catalog.default.catalog_sales +Output [2]: [cs_ship_customer_sk#13, cs_sold_date_sk#14] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#14), dynamicpruningexpression(cs_sold_date_sk#14 IN dynamicpruning#15)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 6] +Input [2]: [cs_ship_customer_sk#13, cs_sold_date_sk#14] + +(18) ReusedExchange [Reuses operator id: 45] +Output [1]: [d_date_sk#16] + +(19) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [cs_sold_date_sk#14] +Right keys [1]: [d_date_sk#16] +Join type: Inner +Join condition: None + +(20) Project [codegen id : 6] +Output [1]: [cs_ship_customer_sk#13 AS customsk#17] +Input [3]: [cs_ship_customer_sk#13, cs_sold_date_sk#14, d_date_sk#16] + +(21) Union + +(22) BroadcastExchange +Input [1]: [customsk#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(23) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [customsk#12] +Join type: LeftSemi +Join condition: None + +(24) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#2, c_current_addr_sk#3] +Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] + +(25) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#18, ca_state#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_state#19] + +(27) Filter [codegen id : 7] +Input [2]: [ca_address_sk#18, ca_state#19] +Condition : isnotnull(ca_address_sk#18) + +(28) BroadcastExchange +Input [2]: [ca_address_sk#18, ca_state#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(29) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_addr_sk#3] +Right keys [1]: [ca_address_sk#18] +Join type: Inner +Join condition: None + +(30) Project [codegen id : 9] +Output [2]: [c_current_cdemo_sk#2, ca_state#19] +Input [4]: [c_current_cdemo_sk#2, c_current_addr_sk#3, ca_address_sk#18, ca_state#19] + +(31) Scan parquet spark_catalog.default.customer_demographics +Output [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 8] +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(33) Filter [codegen id : 8] +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Condition : isnotnull(cd_demo_sk#20) + +(34) BroadcastExchange +Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(35) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [c_current_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#20] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 9] +Output [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Input [8]: [c_current_cdemo_sk#2, ca_state#19, cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] + +(37) HashAggregate [codegen id : 9] +Input [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [partial_count(1), partial_avg(cd_dep_count#23), partial_max(cd_dep_count#23), partial_sum(cd_dep_count#23), partial_avg(cd_dep_employed_count#24), partial_max(cd_dep_employed_count#24), partial_sum(cd_dep_employed_count#24), partial_avg(cd_dep_college_count#25), partial_max(cd_dep_college_count#25), partial_sum(cd_dep_college_count#25)] +Aggregate Attributes [13]: [count#26, sum#27, count#28, max#29, sum#30, sum#31, count#32, max#33, sum#34, sum#35, count#36, max#37, sum#38] +Results [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] + +(38) Exchange +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] +Arguments: hashpartitioning(ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(39) HashAggregate [codegen id : 10] +Input [19]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25, count#39, sum#40, count#41, max#42, sum#43, sum#44, count#45, max#46, sum#47, sum#48, count#49, max#50, sum#51] +Keys [6]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Functions [10]: [count(1), avg(cd_dep_count#23), max(cd_dep_count#23), sum(cd_dep_count#23), avg(cd_dep_employed_count#24), max(cd_dep_employed_count#24), sum(cd_dep_employed_count#24), avg(cd_dep_college_count#25), max(cd_dep_college_count#25), sum(cd_dep_college_count#25)] +Aggregate Attributes [10]: [count(1)#52, avg(cd_dep_count#23)#53, max(cd_dep_count#23)#54, sum(cd_dep_count#23)#55, avg(cd_dep_employed_count#24)#56, max(cd_dep_employed_count#24)#57, sum(cd_dep_employed_count#24)#58, avg(cd_dep_college_count#25)#59, max(cd_dep_college_count#25)#60, sum(cd_dep_college_count#25)#61] +Results [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, count(1)#52 AS cnt1#62, avg(cd_dep_count#23)#53 AS avg(cd_dep_count)#63, max(cd_dep_count#23)#54 AS max(cd_dep_count)#64, sum(cd_dep_count#23)#55 AS sum(cd_dep_count)#65, cd_dep_employed_count#24, count(1)#52 AS cnt2#66, avg(cd_dep_employed_count#24)#56 AS avg(cd_dep_employed_count)#67, max(cd_dep_employed_count#24)#57 AS max(cd_dep_employed_count)#68, sum(cd_dep_employed_count#24)#58 AS sum(cd_dep_employed_count)#69, cd_dep_college_count#25, count(1)#52 AS cnt3#70, avg(cd_dep_college_count#25)#59 AS avg(cd_dep_college_count)#71, max(cd_dep_college_count#25)#60 AS max(cd_dep_college_count)#72, sum(cd_dep_college_count#25)#61 AS sum(cd_dep_college_count)#73] + +(40) TakeOrderedAndProject +Input [18]: [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cnt1#62, avg(cd_dep_count)#63, max(cd_dep_count)#64, sum(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, avg(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, sum(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, avg(cd_dep_college_count)#71, max(cd_dep_college_count)#72, sum(cd_dep_college_count)#73] +Arguments: 100, [ca_state#19 ASC NULLS FIRST, cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FIRST, cd_dep_count#23 ASC NULLS FIRST, cd_dep_employed_count#24 ASC NULLS FIRST, cd_dep_college_count#25 ASC NULLS FIRST], [ca_state#19, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cnt1#62, avg(cd_dep_count)#63, max(cd_dep_count)#64, sum(cd_dep_count)#65, cd_dep_employed_count#24, cnt2#66, avg(cd_dep_employed_count)#67, max(cd_dep_employed_count)#68, sum(cd_dep_employed_count)#69, cd_dep_college_count#25, cnt3#70, avg(cd_dep_college_count)#71, max(cd_dep_college_count)#72, sum(cd_dep_college_count)#73] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (45) ++- * Project (44) + +- * Filter (43) + +- * ColumnarToRow (42) + +- CometScan parquet spark_catalog.default.date_dim (41) + + +(41) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#7, d_year#74, d_qoy#75] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,1999), LessThan(d_qoy,4), IsNotNull(d_date_sk)] +ReadSchema: struct + +(42) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#74, d_qoy#75] + +(43) Filter [codegen id : 1] +Input [3]: [d_date_sk#7, d_year#74, d_qoy#75] +Condition : ((((isnotnull(d_year#74) AND isnotnull(d_qoy#75)) AND (d_year#74 = 1999)) AND (d_qoy#75 < 4)) AND isnotnull(d_date_sk#7)) + +(44) Project [codegen id : 1] +Output [1]: [d_date_sk#7] +Input [3]: [d_date_sk#7, d_year#74, d_qoy#75] + +(45) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6] + +Subquery:2 Hosting operator id = 11 Hosting Expression = ws_sold_date_sk#9 IN dynamicpruning#6 + +Subquery:3 Hosting operator id = 16 Hosting Expression = cs_sold_date_sk#14 IN dynamicpruning#6 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/simplified.txt new file mode 100644 index 000000000..2cf44995a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/simplified.txt @@ -0,0 +1,71 @@ +TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,cnt1,avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),cnt2,avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),cnt3,avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count)] + WholeStageCodegen (10) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count,count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] [count(1),avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count),cnt1,avg(cd_dep_count),max(cd_dep_count),sum(cd_dep_count),cnt2,avg(cd_dep_employed_count),max(cd_dep_employed_count),sum(cd_dep_employed_count),cnt3,avg(cd_dep_college_count),max(cd_dep_college_count),sum(cd_dep_college_count),count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] + InputAdapter + Exchange [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] #1 + WholeStageCodegen (9) + HashAggregate [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] [count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum,count,sum,count,max,sum,sum,count,max,sum,sum,count,max,sum] + Project [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] + Project [c_current_cdemo_sk,ca_state] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [c_current_cdemo_sk,c_current_addr_sk] + BroadcastHashJoin [c_customer_sk,customsk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_current_addr_sk,c_current_cdemo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (2) + Project [ss_customer_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_qoy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #4 + Union + WholeStageCodegen (4) + Project [ws_bill_customer_sk] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + WholeStageCodegen (6) + Project [cs_ship_customer_sk] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_customer_sk,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #3 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + Filter [ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (8) + Filter [cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/explain.txt new file mode 100644 index 000000000..5a7efec07 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/explain.txt @@ -0,0 +1,279 @@ +== Physical Plan == +TakeOrderedAndProject (41) ++- * Project (40) + +- Window (39) + +- * Sort (38) + +- Exchange (37) + +- * HashAggregate (36) + +- Exchange (35) + +- * HashAggregate (34) + +- Union (33) + :- * HashAggregate (22) + : +- Exchange (21) + : +- * HashAggregate (20) + : +- * Project (19) + : +- * BroadcastHashJoin Inner BuildRight (18) + : :- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.item (7) + : +- BroadcastExchange (17) + : +- * Project (16) + : +- * Filter (15) + : +- * ColumnarToRow (14) + : +- CometScan parquet spark_catalog.default.store (13) + :- * HashAggregate (27) + : +- Exchange (26) + : +- * HashAggregate (25) + : +- * HashAggregate (24) + : +- ReusedExchange (23) + +- * HashAggregate (32) + +- Exchange (31) + +- * HashAggregate (30) + +- * HashAggregate (29) + +- ReusedExchange (28) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] + +(3) Filter [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_store_sk#2)) + +(4) ReusedExchange [Reuses operator id: 46] +Output [1]: [d_date_sk#7] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4] +Input [6]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5, d_date_sk#7] + +(7) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#8, i_class#9, i_category#10] + +(9) Filter [codegen id : 2] +Input [3]: [i_item_sk#8, i_class#9, i_category#10] +Condition : isnotnull(i_item_sk#8) + +(10) BroadcastExchange +Input [3]: [i_item_sk#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#8] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [5]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_item_sk#8, i_class#9, i_category#10] + +(13) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_state#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [2]: [s_store_sk#11, s_state#12] + +(15) Filter [codegen id : 3] +Input [2]: [s_store_sk#11, s_state#12] +Condition : ((isnotnull(s_state#12) AND (s_state#12 = TN)) AND isnotnull(s_store_sk#11)) + +(16) Project [codegen id : 3] +Output [1]: [s_store_sk#11] +Input [2]: [s_store_sk#11, s_state#12] + +(17) BroadcastExchange +Input [1]: [s_store_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2] + +(18) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(19) Project [codegen id : 4] +Output [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10] +Input [6]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10, s_store_sk#11] + +(20) HashAggregate [codegen id : 4] +Input [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10] +Keys [2]: [i_category#10, i_class#9] +Functions [2]: [partial_sum(UnscaledValue(ss_net_profit#4)), partial_sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [2]: [sum#13, sum#14] +Results [4]: [i_category#10, i_class#9, sum#15, sum#16] + +(21) Exchange +Input [4]: [i_category#10, i_class#9, sum#15, sum#16] +Arguments: hashpartitioning(i_category#10, i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(22) HashAggregate [codegen id : 5] +Input [4]: [i_category#10, i_class#9, sum#15, sum#16] +Keys [2]: [i_category#10, i_class#9] +Functions [2]: [sum(UnscaledValue(ss_net_profit#4)), sum(UnscaledValue(ss_ext_sales_price#3))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#4))#17, sum(UnscaledValue(ss_ext_sales_price#3))#18] +Results [6]: [cast((MakeDecimal(sum(UnscaledValue(ss_net_profit#4))#17,17,2) / MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#18,17,2)) as decimal(38,11)) AS gross_margin#19, i_category#10, i_class#9, 0 AS t_category#20, 0 AS t_class#21, 0 AS lochierarchy#22] + +(23) ReusedExchange [Reuses operator id: 21] +Output [4]: [i_category#23, i_class#24, sum#25, sum#26] + +(24) HashAggregate [codegen id : 10] +Input [4]: [i_category#23, i_class#24, sum#25, sum#26] +Keys [2]: [i_category#23, i_class#24] +Functions [2]: [sum(UnscaledValue(ss_net_profit#27)), sum(UnscaledValue(ss_ext_sales_price#28))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#27))#29, sum(UnscaledValue(ss_ext_sales_price#28))#30] +Results [3]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#27))#29,17,2) AS ss_net_profit#31, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#28))#30,17,2) AS ss_ext_sales_price#32, i_category#23] + +(25) HashAggregate [codegen id : 10] +Input [3]: [ss_net_profit#31, ss_ext_sales_price#32, i_category#23] +Keys [1]: [i_category#23] +Functions [2]: [partial_sum(ss_net_profit#31), partial_sum(ss_ext_sales_price#32)] +Aggregate Attributes [4]: [sum#33, isEmpty#34, sum#35, isEmpty#36] +Results [5]: [i_category#23, sum#37, isEmpty#38, sum#39, isEmpty#40] + +(26) Exchange +Input [5]: [i_category#23, sum#37, isEmpty#38, sum#39, isEmpty#40] +Arguments: hashpartitioning(i_category#23, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(27) HashAggregate [codegen id : 11] +Input [5]: [i_category#23, sum#37, isEmpty#38, sum#39, isEmpty#40] +Keys [1]: [i_category#23] +Functions [2]: [sum(ss_net_profit#31), sum(ss_ext_sales_price#32)] +Aggregate Attributes [2]: [sum(ss_net_profit#31)#41, sum(ss_ext_sales_price#32)#42] +Results [6]: [(sum(ss_net_profit#31)#41 / sum(ss_ext_sales_price#32)#42) AS gross_margin#43, i_category#23, null AS i_class#44, 0 AS t_category#45, 1 AS t_class#46, 1 AS lochierarchy#47] + +(28) ReusedExchange [Reuses operator id: 21] +Output [4]: [i_category#48, i_class#49, sum#50, sum#51] + +(29) HashAggregate [codegen id : 16] +Input [4]: [i_category#48, i_class#49, sum#50, sum#51] +Keys [2]: [i_category#48, i_class#49] +Functions [2]: [sum(UnscaledValue(ss_net_profit#52)), sum(UnscaledValue(ss_ext_sales_price#53))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#52))#29, sum(UnscaledValue(ss_ext_sales_price#53))#30] +Results [2]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#52))#29,17,2) AS ss_net_profit#54, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#53))#30,17,2) AS ss_ext_sales_price#55] + +(30) HashAggregate [codegen id : 16] +Input [2]: [ss_net_profit#54, ss_ext_sales_price#55] +Keys: [] +Functions [2]: [partial_sum(ss_net_profit#54), partial_sum(ss_ext_sales_price#55)] +Aggregate Attributes [4]: [sum#56, isEmpty#57, sum#58, isEmpty#59] +Results [4]: [sum#60, isEmpty#61, sum#62, isEmpty#63] + +(31) Exchange +Input [4]: [sum#60, isEmpty#61, sum#62, isEmpty#63] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=5] + +(32) HashAggregate [codegen id : 17] +Input [4]: [sum#60, isEmpty#61, sum#62, isEmpty#63] +Keys: [] +Functions [2]: [sum(ss_net_profit#54), sum(ss_ext_sales_price#55)] +Aggregate Attributes [2]: [sum(ss_net_profit#54)#64, sum(ss_ext_sales_price#55)#65] +Results [6]: [(sum(ss_net_profit#54)#64 / sum(ss_ext_sales_price#55)#65) AS gross_margin#66, null AS i_category#67, null AS i_class#68, 1 AS t_category#69, 1 AS t_class#70, 2 AS lochierarchy#71] + +(33) Union + +(34) HashAggregate [codegen id : 18] +Input [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] +Keys [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] +Functions: [] +Aggregate Attributes: [] +Results [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] + +(35) Exchange +Input [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] +Arguments: hashpartitioning(gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(36) HashAggregate [codegen id : 19] +Input [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] +Keys [6]: [gross_margin#19, i_category#10, i_class#9, t_category#20, t_class#21, lochierarchy#22] +Functions: [] +Aggregate Attributes: [] +Results [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, CASE WHEN (t_class#21 = 0) THEN i_category#10 END AS _w0#72] + +(37) Exchange +Input [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, _w0#72] +Arguments: hashpartitioning(lochierarchy#22, _w0#72, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(38) Sort [codegen id : 20] +Input [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, _w0#72] +Arguments: [lochierarchy#22 ASC NULLS FIRST, _w0#72 ASC NULLS FIRST, gross_margin#19 ASC NULLS FIRST], false, 0 + +(39) Window +Input [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, _w0#72] +Arguments: [rank(gross_margin#19) windowspecdefinition(lochierarchy#22, _w0#72, gross_margin#19 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#73], [lochierarchy#22, _w0#72], [gross_margin#19 ASC NULLS FIRST] + +(40) Project [codegen id : 21] +Output [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, rank_within_parent#73] +Input [6]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, _w0#72, rank_within_parent#73] + +(41) TakeOrderedAndProject +Input [5]: [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, rank_within_parent#73] +Arguments: 100, [lochierarchy#22 DESC NULLS LAST, CASE WHEN (lochierarchy#22 = 0) THEN i_category#10 END ASC NULLS FIRST, rank_within_parent#73 ASC NULLS FIRST], [gross_margin#19, i_category#10, i_class#9, lochierarchy#22, rank_within_parent#73] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (46) ++- * Project (45) + +- * Filter (44) + +- * ColumnarToRow (43) + +- CometScan parquet spark_catalog.default.date_dim (42) + + +(42) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#7, d_year#74] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(43) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#7, d_year#74] + +(44) Filter [codegen id : 1] +Input [2]: [d_date_sk#7, d_year#74] +Condition : ((isnotnull(d_year#74) AND (d_year#74 = 2001)) AND isnotnull(d_date_sk#7)) + +(45) Project [codegen id : 1] +Output [1]: [d_date_sk#7] +Input [2]: [d_date_sk#7, d_year#74] + +(46) BroadcastExchange +Input [1]: [d_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/simplified.txt new file mode 100644 index 000000000..9d07011c7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/simplified.txt @@ -0,0 +1,76 @@ +TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,gross_margin,i_class] + WholeStageCodegen (21) + Project [gross_margin,i_category,i_class,lochierarchy,rank_within_parent] + InputAdapter + Window [gross_margin,lochierarchy,_w0] + WholeStageCodegen (20) + Sort [lochierarchy,_w0,gross_margin] + InputAdapter + Exchange [lochierarchy,_w0] #1 + WholeStageCodegen (19) + HashAggregate [gross_margin,i_category,i_class,t_category,t_class,lochierarchy] [_w0] + InputAdapter + Exchange [gross_margin,i_category,i_class,t_category,t_class,lochierarchy] #2 + WholeStageCodegen (18) + HashAggregate [gross_margin,i_category,i_class,t_category,t_class,lochierarchy] + InputAdapter + Union + WholeStageCodegen (5) + HashAggregate [i_category,i_class,sum,sum] [sum(UnscaledValue(ss_net_profit)),sum(UnscaledValue(ss_ext_sales_price)),gross_margin,t_category,t_class,lochierarchy,sum,sum] + InputAdapter + Exchange [i_category,i_class] #3 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,ss_net_profit,ss_ext_sales_price] [sum,sum,sum,sum] + Project [ss_ext_sales_price,ss_net_profit,i_class,i_category] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_ext_sales_price,ss_net_profit,i_class,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_item_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + Project [s_store_sk] + Filter [s_state,s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + WholeStageCodegen (11) + HashAggregate [i_category,sum,isEmpty,sum,isEmpty] [sum(ss_net_profit),sum(ss_ext_sales_price),gross_margin,i_class,t_category,t_class,lochierarchy,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [i_category] #7 + WholeStageCodegen (10) + HashAggregate [i_category,ss_net_profit,ss_ext_sales_price] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,sum,sum] [sum(UnscaledValue(ss_net_profit)),sum(UnscaledValue(ss_ext_sales_price)),ss_net_profit,ss_ext_sales_price,sum,sum] + InputAdapter + ReusedExchange [i_category,i_class,sum,sum] #3 + WholeStageCodegen (17) + HashAggregate [sum,isEmpty,sum,isEmpty] [sum(ss_net_profit),sum(ss_ext_sales_price),gross_margin,i_category,i_class,t_category,t_class,lochierarchy,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange #8 + WholeStageCodegen (16) + HashAggregate [ss_net_profit,ss_ext_sales_price] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,sum,sum] [sum(UnscaledValue(ss_net_profit)),sum(UnscaledValue(ss_ext_sales_price)),ss_net_profit,ss_ext_sales_price,sum,sum] + InputAdapter + ReusedExchange [i_category,i_class,sum,sum] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/explain.txt new file mode 100644 index 000000000..95dc7f0cd --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/explain.txt @@ -0,0 +1,279 @@ +== Physical Plan == +TakeOrderedAndProject (45) ++- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (28) + : : +- * Filter (27) + : : +- Window (26) + : : +- * Filter (25) + : : +- Window (24) + : : +- * Sort (23) + : : +- Exchange (22) + : : +- * HashAggregate (21) + : : +- Exchange (20) + : : +- * HashAggregate (19) + : : +- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.item (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (16) + : : +- * Filter (15) + : : +- * ColumnarToRow (14) + : : +- CometScan parquet spark_catalog.default.store (13) + : +- BroadcastExchange (35) + : +- * Project (34) + : +- Window (33) + : +- * Sort (32) + : +- Exchange (31) + : +- * HashAggregate (30) + : +- ReusedExchange (29) + +- BroadcastExchange (42) + +- * Project (41) + +- Window (40) + +- * Sort (39) + +- ReusedExchange (38) + + +(1) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#1, i_brand#2, i_category#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] + +(3) Filter [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] + +(6) Filter [codegen id : 1] +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#4) AND isnotnull(ss_store_sk#5)) + +(7) BroadcastExchange +Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [ss_item_sk#4] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [5]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Input [7]: [i_item_sk#1, i_brand#2, i_category#3, ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 49] +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, d_year#10, d_moy#11] +Input [8]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7, d_date_sk#9, d_year#10, d_moy#11] + +(13) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_company_name)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] + +(15) Filter [codegen id : 3] +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Condition : ((isnotnull(s_store_sk#12) AND isnotnull(s_store_name#13)) AND isnotnull(s_company_name#14)) + +(16) BroadcastExchange +Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#5] +Right keys [1]: [s_store_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [7]: [i_brand#2, i_category#3, ss_sales_price#6, d_year#10, d_moy#11, s_store_name#13, s_company_name#14] +Input [9]: [i_brand#2, i_category#3, ss_store_sk#5, ss_sales_price#6, d_year#10, d_moy#11, s_store_sk#12, s_store_name#13, s_company_name#14] + +(19) HashAggregate [codegen id : 4] +Input [7]: [i_brand#2, i_category#3, ss_sales_price#6, d_year#10, d_moy#11, s_store_name#13, s_company_name#14] +Keys [6]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [1]: [sum#15] +Results [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] + +(20) Exchange +Input [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] +Arguments: hashpartitioning(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [7]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum#16] +Keys [6]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11] +Functions [1]: [sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#6))#17] +Results [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#17,17,2) AS sum_sales#18, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#17,17,2) AS _w0#19] + +(22) Exchange +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: hashpartitioning(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) Sort [codegen id : 6] +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: [i_category#3 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST, s_company_name#14 ASC NULLS FIRST, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST], false, 0 + +(24) Window +Input [8]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19] +Arguments: [rank(d_year#10, d_moy#11) windowspecdefinition(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#20], [i_category#3, i_brand#2, s_store_name#13, s_company_name#14], [d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST] + +(25) Filter [codegen id : 7] +Input [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20] +Condition : (isnotnull(d_year#10) AND (d_year#10 = 1999)) + +(26) Window +Input [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20] +Arguments: [avg(_w0#19) windowspecdefinition(i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#21], [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10] + +(27) Filter [codegen id : 22] +Input [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20, avg_monthly_sales#21] +Condition : ((isnotnull(avg_monthly_sales#21) AND (avg_monthly_sales#21 > 0.000000)) AND CASE WHEN (avg_monthly_sales#21 > 0.000000) THEN ((abs((sum_sales#18 - avg_monthly_sales#21)) / avg_monthly_sales#21) > 0.1000000000000000) END) + +(28) Project [codegen id : 22] +Output [9]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20] +Input [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, _w0#19, rn#20, avg_monthly_sales#21] + +(29) ReusedExchange [Reuses operator id: 20] +Output [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum#28] + +(30) HashAggregate [codegen id : 12] +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum#28] +Keys [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27] +Functions [1]: [sum(UnscaledValue(ss_sales_price#29))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#29))#17] +Results [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, MakeDecimal(sum(UnscaledValue(ss_sales_price#29))#17,17,2) AS sum_sales#30] + +(31) Exchange +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: hashpartitioning(i_category#22, i_brand#23, s_store_name#24, s_company_name#25, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 13] +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: [i_category#22 ASC NULLS FIRST, i_brand#23 ASC NULLS FIRST, s_store_name#24 ASC NULLS FIRST, s_company_name#25 ASC NULLS FIRST, d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST], false, 0 + +(33) Window +Input [7]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30] +Arguments: [rank(d_year#26, d_moy#27) windowspecdefinition(i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#31], [i_category#22, i_brand#23, s_store_name#24, s_company_name#25], [d_year#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST] + +(34) Project [codegen id : 14] +Output [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] +Input [8]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, d_year#26, d_moy#27, sum_sales#30, rn#31] + +(35) BroadcastExchange +Input [6]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], input[3, string, true], (input[5, int, false] + 1)),false), [plan_id=6] + +(36) BroadcastHashJoin [codegen id : 22] +Left keys [5]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, rn#20] +Right keys [5]: [i_category#22, i_brand#23, s_store_name#24, s_company_name#25, (rn#31 + 1)] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 22] +Output [10]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, sum_sales#30] +Input [15]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, i_category#22, i_brand#23, s_store_name#24, s_company_name#25, sum_sales#30, rn#31] + +(38) ReusedExchange [Reuses operator id: 31] +Output [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] + +(39) Sort [codegen id : 20] +Input [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] +Arguments: [i_category#32 ASC NULLS FIRST, i_brand#33 ASC NULLS FIRST, s_store_name#34 ASC NULLS FIRST, s_company_name#35 ASC NULLS FIRST, d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST], false, 0 + +(40) Window +Input [7]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38] +Arguments: [rank(d_year#36, d_moy#37) windowspecdefinition(i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#39], [i_category#32, i_brand#33, s_store_name#34, s_company_name#35], [d_year#36 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST] + +(41) Project [codegen id : 21] +Output [6]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] +Input [8]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, d_year#36, d_moy#37, sum_sales#38, rn#39] + +(42) BroadcastExchange +Input [6]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], input[3, string, true], (input[5, int, false] - 1)),false), [plan_id=7] + +(43) BroadcastHashJoin [codegen id : 22] +Left keys [5]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, rn#20] +Right keys [5]: [i_category#32, i_brand#33, s_store_name#34, s_company_name#35, (rn#39 - 1)] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 22] +Output [7]: [i_category#3, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, sum_sales#30 AS psum#40, sum_sales#38 AS nsum#41] +Input [16]: [i_category#3, i_brand#2, s_store_name#13, s_company_name#14, d_year#10, d_moy#11, sum_sales#18, avg_monthly_sales#21, rn#20, sum_sales#30, i_category#32, i_brand#33, s_store_name#34, s_company_name#35, sum_sales#38, rn#39] + +(45) TakeOrderedAndProject +Input [7]: [i_category#3, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, psum#40, nsum#41] +Arguments: 100, [(sum_sales#18 - avg_monthly_sales#21) ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST], [i_category#3, d_year#10, d_moy#11, avg_monthly_sales#21, sum_sales#18, psum#40, nsum#41] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (49) ++- * Filter (48) + +- * ColumnarToRow (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(48) Filter [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) + +(49) BroadcastExchange +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/simplified.txt new file mode 100644 index 000000000..1a45368ff --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [sum_sales,avg_monthly_sales,d_moy,i_category,d_year,psum,nsum] + WholeStageCodegen (22) + Project [i_category,d_year,d_moy,avg_monthly_sales,sum_sales,sum_sales,sum_sales] + BroadcastHashJoin [i_category,i_brand,s_store_name,s_company_name,rn,i_category,i_brand,s_store_name,s_company_name,rn] + Project [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn,sum_sales] + BroadcastHashJoin [i_category,i_brand,s_store_name,s_company_name,rn,i_category,i_brand,s_store_name,s_company_name,rn] + Project [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_category,i_brand,s_store_name,s_company_name,d_year] + WholeStageCodegen (7) + Filter [d_year] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (6) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,ss_sales_price] [sum,sum] + Project [i_brand,i_category,ss_sales_price,d_year,d_moy,s_store_name,s_company_name] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [i_brand,i_category,ss_store_sk,ss_sales_price,d_year,d_moy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [i_brand,i_category,ss_store_sk,ss_sales_price,ss_sold_date_sk] + BroadcastHashJoin [i_item_sk,ss_item_sk] + Filter [i_item_sk,i_category,i_brand] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [ss_item_sk,ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [s_store_sk,s_store_name,s_company_name] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (14) + Project [i_category,i_brand,s_store_name,s_company_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (13) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,s_store_name,s_company_name] #7 + WholeStageCodegen (12) + HashAggregate [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] [sum(UnscaledValue(ss_sales_price)),sum_sales,sum] + InputAdapter + ReusedExchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum] #2 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (21) + Project [i_category,i_brand,s_store_name,s_company_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,s_store_name,s_company_name] + WholeStageCodegen (20) + Sort [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy] + InputAdapter + ReusedExchange [i_category,i_brand,s_store_name,s_company_name,d_year,d_moy,sum_sales] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/explain.txt new file mode 100644 index 000000000..2a8889da9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/explain.txt @@ -0,0 +1,471 @@ +== Physical Plan == +TakeOrderedAndProject (77) ++- * HashAggregate (76) + +- Exchange (75) + +- * HashAggregate (74) + +- Union (73) + :- * Project (24) + : +- * Filter (23) + : +- Window (22) + : +- * Sort (21) + : +- Window (20) + : +- * Sort (19) + : +- Exchange (18) + : +- * HashAggregate (17) + : +- Exchange (16) + : +- * HashAggregate (15) + : +- * Project (14) + : +- * BroadcastHashJoin Inner BuildRight (13) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildLeft (10) + : : :- BroadcastExchange (5) + : : : +- * Project (4) + : : : +- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : +- * Project (9) + : : +- * Filter (8) + : : +- * ColumnarToRow (7) + : : +- CometScan parquet spark_catalog.default.web_returns (6) + : +- ReusedExchange (12) + :- * Project (48) + : +- * Filter (47) + : +- Window (46) + : +- * Sort (45) + : +- Window (44) + : +- * Sort (43) + : +- Exchange (42) + : +- * HashAggregate (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * Project (35) + : : +- * BroadcastHashJoin Inner BuildLeft (34) + : : :- BroadcastExchange (29) + : : : +- * Project (28) + : : : +- * Filter (27) + : : : +- * ColumnarToRow (26) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (25) + : : +- * Project (33) + : : +- * Filter (32) + : : +- * ColumnarToRow (31) + : : +- CometScan parquet spark_catalog.default.catalog_returns (30) + : +- ReusedExchange (36) + +- * Project (72) + +- * Filter (71) + +- Window (70) + +- * Sort (69) + +- Window (68) + +- * Sort (67) + +- Exchange (66) + +- * HashAggregate (65) + +- Exchange (64) + +- * HashAggregate (63) + +- * Project (62) + +- * BroadcastHashJoin Inner BuildRight (61) + :- * Project (59) + : +- * BroadcastHashJoin Inner BuildLeft (58) + : :- BroadcastExchange (53) + : : +- * Project (52) + : : +- * Filter (51) + : : +- * ColumnarToRow (50) + : : +- CometScan parquet spark_catalog.default.store_sales (49) + : +- * Project (57) + : +- * Filter (56) + : +- * ColumnarToRow (55) + : +- CometScan parquet spark_catalog.default.store_returns (54) + +- ReusedExchange (60) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#6), dynamicpruningexpression(ws_sold_date_sk#6 IN dynamicpruning#7)] +PushedFilters: [IsNotNull(ws_net_profit), IsNotNull(ws_net_paid), IsNotNull(ws_quantity), GreaterThan(ws_net_profit,1.00), GreaterThan(ws_net_paid,0.00), GreaterThan(ws_quantity,0), IsNotNull(ws_order_number), IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] + +(3) Filter [codegen id : 1] +Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Condition : (((((((isnotnull(ws_net_profit#5) AND isnotnull(ws_net_paid#4)) AND isnotnull(ws_quantity#3)) AND (ws_net_profit#5 > 1.00)) AND (ws_net_paid#4 > 0.00)) AND (ws_quantity#3 > 0)) AND isnotnull(ws_order_number#2)) AND isnotnull(ws_item_sk#1)) + +(4) Project [codegen id : 1] +Output [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] + +(5) BroadcastExchange +Input [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=1] + +(6) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_return_amt), GreaterThan(wr_return_amt,10000.00), IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(7) ColumnarToRow +Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] + +(8) Filter +Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Condition : (((isnotnull(wr_return_amt#11) AND (wr_return_amt#11 > 10000.00)) AND isnotnull(wr_order_number#9)) AND isnotnull(wr_item_sk#8)) + +(9) Project +Output [4]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] + +(10) BroadcastHashJoin [codegen id : 3] +Left keys [2]: [ws_order_number#2, ws_item_sk#1] +Right keys [2]: [wr_order_number#9, wr_item_sk#8] +Join type: Inner +Join condition: None + +(11) Project [codegen id : 3] +Output [6]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] +Input [9]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] + +(12) ReusedExchange [Reuses operator id: 82] +Output [1]: [d_date_sk#13] + +(13) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#6] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(14) Project [codegen id : 3] +Output [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] +Input [7]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11, d_date_sk#13] + +(15) HashAggregate [codegen id : 3] +Input [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] +Keys [1]: [ws_item_sk#1] +Functions [4]: [partial_sum(coalesce(wr_return_quantity#10, 0)), partial_sum(coalesce(ws_quantity#3, 0)), partial_sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#14, sum#15, sum#16, isEmpty#17, sum#18, isEmpty#19] +Results [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] + +(16) Exchange +Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(17) HashAggregate [codegen id : 4] +Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Keys [1]: [ws_item_sk#1] +Functions [4]: [sum(coalesce(wr_return_quantity#10, 0)), sum(coalesce(ws_quantity#3, 0)), sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(wr_return_quantity#10, 0))#26, sum(coalesce(ws_quantity#3, 0))#27, sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28, sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29] +Results [3]: [ws_item_sk#1 AS item#30, (cast(sum(coalesce(wr_return_quantity#10, 0))#26 as decimal(15,4)) / cast(sum(coalesce(ws_quantity#3, 0))#27 as decimal(15,4))) AS return_ratio#31, (cast(sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28 as decimal(15,4)) / cast(sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29 as decimal(15,4))) AS currency_ratio#32] + +(18) Exchange +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=3] + +(19) Sort [codegen id : 5] +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: [return_ratio#31 ASC NULLS FIRST], false, 0 + +(20) Window +Input [3]: [item#30, return_ratio#31, currency_ratio#32] +Arguments: [rank(return_ratio#31) windowspecdefinition(return_ratio#31 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#33], [return_ratio#31 ASC NULLS FIRST] + +(21) Sort [codegen id : 6] +Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] +Arguments: [currency_ratio#32 ASC NULLS FIRST], false, 0 + +(22) Window +Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] +Arguments: [rank(currency_ratio#32) windowspecdefinition(currency_ratio#32 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#34], [currency_ratio#32 ASC NULLS FIRST] + +(23) Filter [codegen id : 7] +Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] +Condition : ((return_rank#33 <= 10) OR (currency_rank#34 <= 10)) + +(24) Project [codegen id : 7] +Output [5]: [web AS channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] + +(25) Scan parquet spark_catalog.default.catalog_sales +Output [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#41), dynamicpruningexpression(cs_sold_date_sk#41 IN dynamicpruning#42)] +PushedFilters: [IsNotNull(cs_net_profit), IsNotNull(cs_net_paid), IsNotNull(cs_quantity), GreaterThan(cs_net_profit,1.00), GreaterThan(cs_net_paid,0.00), GreaterThan(cs_quantity,0), IsNotNull(cs_order_number), IsNotNull(cs_item_sk)] +ReadSchema: struct + +(26) ColumnarToRow [codegen id : 8] +Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] + +(27) Filter [codegen id : 8] +Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Condition : (((((((isnotnull(cs_net_profit#40) AND isnotnull(cs_net_paid#39)) AND isnotnull(cs_quantity#38)) AND (cs_net_profit#40 > 1.00)) AND (cs_net_paid#39 > 0.00)) AND (cs_quantity#38 > 0)) AND isnotnull(cs_order_number#37)) AND isnotnull(cs_item_sk#36)) + +(28) Project [codegen id : 8] +Output [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] + +(29) BroadcastExchange +Input [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=4] + +(30) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_return_amount), GreaterThan(cr_return_amount,10000.00), IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(31) ColumnarToRow +Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] + +(32) Filter +Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Condition : (((isnotnull(cr_return_amount#46) AND (cr_return_amount#46 > 10000.00)) AND isnotnull(cr_order_number#44)) AND isnotnull(cr_item_sk#43)) + +(33) Project +Output [4]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [cs_order_number#37, cs_item_sk#36] +Right keys [2]: [cr_order_number#44, cr_item_sk#43] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [6]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] +Input [9]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] + +(36) ReusedExchange [Reuses operator id: 82] +Output [1]: [d_date_sk#48] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#41] +Right keys [1]: [d_date_sk#48] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] +Input [7]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46, d_date_sk#48] + +(39) HashAggregate [codegen id : 10] +Input [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] +Keys [1]: [cs_item_sk#36] +Functions [4]: [partial_sum(coalesce(cr_return_quantity#45, 0)), partial_sum(coalesce(cs_quantity#38, 0)), partial_sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#49, sum#50, sum#51, isEmpty#52, sum#53, isEmpty#54] +Results [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] + +(40) Exchange +Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] +Arguments: hashpartitioning(cs_item_sk#36, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(41) HashAggregate [codegen id : 11] +Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] +Keys [1]: [cs_item_sk#36] +Functions [4]: [sum(coalesce(cr_return_quantity#45, 0)), sum(coalesce(cs_quantity#38, 0)), sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(cr_return_quantity#45, 0))#61, sum(coalesce(cs_quantity#38, 0))#62, sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63, sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64] +Results [3]: [cs_item_sk#36 AS item#65, (cast(sum(coalesce(cr_return_quantity#45, 0))#61 as decimal(15,4)) / cast(sum(coalesce(cs_quantity#38, 0))#62 as decimal(15,4))) AS return_ratio#66, (cast(sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63 as decimal(15,4)) / cast(sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64 as decimal(15,4))) AS currency_ratio#67] + +(42) Exchange +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] + +(43) Sort [codegen id : 12] +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: [return_ratio#66 ASC NULLS FIRST], false, 0 + +(44) Window +Input [3]: [item#65, return_ratio#66, currency_ratio#67] +Arguments: [rank(return_ratio#66) windowspecdefinition(return_ratio#66 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#68], [return_ratio#66 ASC NULLS FIRST] + +(45) Sort [codegen id : 13] +Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] +Arguments: [currency_ratio#67 ASC NULLS FIRST], false, 0 + +(46) Window +Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] +Arguments: [rank(currency_ratio#67) windowspecdefinition(currency_ratio#67 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#69], [currency_ratio#67 ASC NULLS FIRST] + +(47) Filter [codegen id : 14] +Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] +Condition : ((return_rank#68 <= 10) OR (currency_rank#69 <= 10)) + +(48) Project [codegen id : 14] +Output [5]: [catalog AS channel#70, item#65, return_ratio#66, return_rank#68, currency_rank#69] +Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] + +(49) Scan parquet spark_catalog.default.store_sales +Output [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#76), dynamicpruningexpression(ss_sold_date_sk#76 IN dynamicpruning#77)] +PushedFilters: [IsNotNull(ss_net_profit), IsNotNull(ss_net_paid), IsNotNull(ss_quantity), GreaterThan(ss_net_profit,1.00), GreaterThan(ss_net_paid,0.00), GreaterThan(ss_quantity,0), IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(50) ColumnarToRow [codegen id : 15] +Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] + +(51) Filter [codegen id : 15] +Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Condition : (((((((isnotnull(ss_net_profit#75) AND isnotnull(ss_net_paid#74)) AND isnotnull(ss_quantity#73)) AND (ss_net_profit#75 > 1.00)) AND (ss_net_paid#74 > 0.00)) AND (ss_quantity#73 > 0)) AND isnotnull(ss_ticket_number#72)) AND isnotnull(ss_item_sk#71)) + +(52) Project [codegen id : 15] +Output [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] + +(53) BroadcastExchange +Input [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=7] + +(54) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_return_amt), GreaterThan(sr_return_amt,10000.00), IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(55) ColumnarToRow +Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] + +(56) Filter +Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Condition : (((isnotnull(sr_return_amt#81) AND (sr_return_amt#81 > 10000.00)) AND isnotnull(sr_ticket_number#79)) AND isnotnull(sr_item_sk#78)) + +(57) Project +Output [4]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] + +(58) BroadcastHashJoin [codegen id : 17] +Left keys [2]: [ss_ticket_number#72, ss_item_sk#71] +Right keys [2]: [sr_ticket_number#79, sr_item_sk#78] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 17] +Output [6]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] +Input [9]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] + +(60) ReusedExchange [Reuses operator id: 82] +Output [1]: [d_date_sk#83] + +(61) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ss_sold_date_sk#76] +Right keys [1]: [d_date_sk#83] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 17] +Output [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] +Input [7]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81, d_date_sk#83] + +(63) HashAggregate [codegen id : 17] +Input [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] +Keys [1]: [ss_item_sk#71] +Functions [4]: [partial_sum(coalesce(sr_return_quantity#80, 0)), partial_sum(coalesce(ss_quantity#73, 0)), partial_sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] +Aggregate Attributes [6]: [sum#84, sum#85, sum#86, isEmpty#87, sum#88, isEmpty#89] +Results [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] + +(64) Exchange +Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] +Arguments: hashpartitioning(ss_item_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(65) HashAggregate [codegen id : 18] +Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] +Keys [1]: [ss_item_sk#71] +Functions [4]: [sum(coalesce(sr_return_quantity#80, 0)), sum(coalesce(ss_quantity#73, 0)), sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] +Aggregate Attributes [4]: [sum(coalesce(sr_return_quantity#80, 0))#96, sum(coalesce(ss_quantity#73, 0))#97, sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98, sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99] +Results [3]: [ss_item_sk#71 AS item#100, (cast(sum(coalesce(sr_return_quantity#80, 0))#96 as decimal(15,4)) / cast(sum(coalesce(ss_quantity#73, 0))#97 as decimal(15,4))) AS return_ratio#101, (cast(sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98 as decimal(15,4)) / cast(sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99 as decimal(15,4))) AS currency_ratio#102] + +(66) Exchange +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=9] + +(67) Sort [codegen id : 19] +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: [return_ratio#101 ASC NULLS FIRST], false, 0 + +(68) Window +Input [3]: [item#100, return_ratio#101, currency_ratio#102] +Arguments: [rank(return_ratio#101) windowspecdefinition(return_ratio#101 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#103], [return_ratio#101 ASC NULLS FIRST] + +(69) Sort [codegen id : 20] +Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] +Arguments: [currency_ratio#102 ASC NULLS FIRST], false, 0 + +(70) Window +Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] +Arguments: [rank(currency_ratio#102) windowspecdefinition(currency_ratio#102 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#104], [currency_ratio#102 ASC NULLS FIRST] + +(71) Filter [codegen id : 21] +Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] +Condition : ((return_rank#103 <= 10) OR (currency_rank#104 <= 10)) + +(72) Project [codegen id : 21] +Output [5]: [store AS channel#105, item#100, return_ratio#101, return_rank#103, currency_rank#104] +Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] + +(73) Union + +(74) HashAggregate [codegen id : 22] +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +(75) Exchange +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Arguments: hashpartitioning(channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(76) HashAggregate [codegen id : 23] +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +(77) TakeOrderedAndProject +Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] +Arguments: 100, [channel#35 ASC NULLS FIRST, return_rank#33 ASC NULLS FIRST, currency_rank#34 ASC NULLS FIRST, item#30 ASC NULLS FIRST], [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#6 IN dynamicpruning#7 +BroadcastExchange (82) ++- * Project (81) + +- * Filter (80) + +- * ColumnarToRow (79) + +- CometScan parquet spark_catalog.default.date_dim (78) + + +(78) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#13, d_year#106, d_moy#107] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,12), IsNotNull(d_date_sk)] +ReadSchema: struct + +(79) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#13, d_year#106, d_moy#107] + +(80) Filter [codegen id : 1] +Input [3]: [d_date_sk#13, d_year#106, d_moy#107] +Condition : ((((isnotnull(d_year#106) AND isnotnull(d_moy#107)) AND (d_year#106 = 2001)) AND (d_moy#107 = 12)) AND isnotnull(d_date_sk#13)) + +(81) Project [codegen id : 1] +Output [1]: [d_date_sk#13] +Input [3]: [d_date_sk#13, d_year#106, d_moy#107] + +(82) BroadcastExchange +Input [1]: [d_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +Subquery:2 Hosting operator id = 25 Hosting Expression = cs_sold_date_sk#41 IN dynamicpruning#7 + +Subquery:3 Hosting operator id = 49 Hosting Expression = ss_sold_date_sk#76 IN dynamicpruning#7 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/simplified.txt new file mode 100644 index 000000000..b707750da --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/simplified.txt @@ -0,0 +1,133 @@ +TakeOrderedAndProject [channel,return_rank,currency_rank,item,return_ratio] + WholeStageCodegen (23) + HashAggregate [channel,item,return_ratio,return_rank,currency_rank] + InputAdapter + Exchange [channel,item,return_ratio,return_rank,currency_rank] #1 + WholeStageCodegen (22) + HashAggregate [channel,item,return_ratio,return_rank,currency_rank] + InputAdapter + Union + WholeStageCodegen (7) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (6) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (5) + Sort [return_ratio] + InputAdapter + Exchange #2 + WholeStageCodegen (4) + HashAggregate [ws_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(wr_return_quantity, 0)),sum(coalesce(ws_quantity, 0)),sum(coalesce(cast(wr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ws_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [ws_item_sk] #3 + WholeStageCodegen (3) + HashAggregate [ws_item_sk,wr_return_quantity,ws_quantity,wr_return_amt,ws_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [ws_item_sk,ws_quantity,ws_net_paid,wr_return_quantity,wr_return_amt] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_quantity,ws_net_paid,ws_sold_date_sk,wr_return_quantity,wr_return_amt] + BroadcastHashJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Project [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_sold_date_sk] + Filter [ws_net_profit,ws_net_paid,ws_quantity,ws_order_number,ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_net_profit,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + Project [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + Filter [wr_return_amt,wr_order_number,wr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + WholeStageCodegen (14) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (13) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (12) + Sort [return_ratio] + InputAdapter + Exchange #6 + WholeStageCodegen (11) + HashAggregate [cs_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(cr_return_quantity, 0)),sum(coalesce(cs_quantity, 0)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum(coalesce(cast(cs_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [cs_item_sk] #7 + WholeStageCodegen (10) + HashAggregate [cs_item_sk,cr_return_quantity,cs_quantity,cr_return_amount,cs_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [cs_item_sk,cs_quantity,cs_net_paid,cr_return_quantity,cr_return_amount] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_quantity,cs_net_paid,cs_sold_date_sk,cr_return_quantity,cr_return_amount] + BroadcastHashJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (8) + Project [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_sold_date_sk] + Filter [cs_net_profit,cs_net_paid,cs_quantity,cs_order_number,cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + Project [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + Filter [cr_return_amount,cr_order_number,cr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + WholeStageCodegen (21) + Project [item,return_ratio,return_rank,currency_rank] + Filter [return_rank,currency_rank] + InputAdapter + Window [currency_ratio] + WholeStageCodegen (20) + Sort [currency_ratio] + InputAdapter + Window [return_ratio] + WholeStageCodegen (19) + Sort [return_ratio] + InputAdapter + Exchange #9 + WholeStageCodegen (18) + HashAggregate [ss_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(sr_return_quantity, 0)),sum(coalesce(ss_quantity, 0)),sum(coalesce(cast(sr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ss_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [ss_item_sk] #10 + WholeStageCodegen (17) + HashAggregate [ss_item_sk,sr_return_quantity,ss_quantity,sr_return_amt,ss_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] + Project [ss_item_sk,ss_quantity,ss_net_paid,sr_return_quantity,sr_return_amt] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_quantity,ss_net_paid,ss_sold_date_sk,sr_return_quantity,sr_return_amt] + BroadcastHashJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_sold_date_sk] + Filter [ss_net_profit,ss_net_paid,ss_quantity,ss_ticket_number,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_net_profit,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + Project [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + Filter [sr_return_amt,sr_ticket_number,sr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/explain.txt new file mode 100644 index 000000000..cb9e772c9 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/explain.txt @@ -0,0 +1,416 @@ +== Physical Plan == +TakeOrderedAndProject (67) ++- * Filter (66) + +- * HashAggregate (65) + +- * HashAggregate (64) + +- * Project (63) + +- * BroadcastHashJoin Inner BuildRight (62) + :- Window (56) + : +- * Sort (55) + : +- Exchange (54) + : +- * Project (53) + : +- * Filter (52) + : +- * SortMergeJoin FullOuter (51) + : :- * Sort (25) + : : +- Exchange (24) + : : +- * HashAggregate (23) + : : +- Exchange (22) + : : +- * HashAggregate (21) + : : +- * Project (20) + : : +- * BroadcastHashJoin Inner BuildRight (19) + : : :- * Project (13) + : : : +- Window (12) + : : : +- * Sort (11) + : : : +- Exchange (10) + : : : +- * HashAggregate (9) + : : : +- Exchange (8) + : : : +- * HashAggregate (7) + : : : +- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (18) + : : +- * Project (17) + : : +- Window (16) + : : +- * Sort (15) + : : +- ReusedExchange (14) + : +- * Sort (50) + : +- Exchange (49) + : +- * HashAggregate (48) + : +- Exchange (47) + : +- * HashAggregate (46) + : +- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (38) + : : +- Window (37) + : : +- * Sort (36) + : : +- Exchange (35) + : : +- * HashAggregate (34) + : : +- Exchange (33) + : : +- * HashAggregate (32) + : : +- * Project (31) + : : +- * BroadcastHashJoin Inner BuildRight (30) + : : :- * Filter (28) + : : : +- * ColumnarToRow (27) + : : : +- CometScan parquet spark_catalog.default.store_sales (26) + : : +- ReusedExchange (29) + : +- BroadcastExchange (43) + : +- * Project (42) + : +- Window (41) + : +- * Sort (40) + : +- ReusedExchange (39) + +- BroadcastExchange (61) + +- * Project (60) + +- Window (59) + +- * Sort (58) + +- ReusedExchange (57) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 2] +Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] + +(3) Filter [codegen id : 2] +Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(4) ReusedExchange [Reuses operator id: 72] +Output [2]: [d_date_sk#5, d_date#6] + +(5) BroadcastHashJoin [codegen id : 2] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 2] +Output [3]: [ws_item_sk#1, ws_sales_price#2, d_date#6] +Input [5]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3, d_date_sk#5, d_date#6] + +(7) HashAggregate [codegen id : 2] +Input [3]: [ws_item_sk#1, ws_sales_price#2, d_date#6] +Keys [2]: [ws_item_sk#1, d_date#6] +Functions [1]: [partial_sum(UnscaledValue(ws_sales_price#2))] +Aggregate Attributes [1]: [sum#7] +Results [3]: [ws_item_sk#1, d_date#6, sum#8] + +(8) Exchange +Input [3]: [ws_item_sk#1, d_date#6, sum#8] +Arguments: hashpartitioning(ws_item_sk#1, d_date#6, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(9) HashAggregate [codegen id : 3] +Input [3]: [ws_item_sk#1, d_date#6, sum#8] +Keys [2]: [ws_item_sk#1, d_date#6] +Functions [1]: [sum(UnscaledValue(ws_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_sales_price#2))#9] +Results [4]: [ws_item_sk#1 AS item_sk#10, d_date#6, MakeDecimal(sum(UnscaledValue(ws_sales_price#2))#9,17,2) AS sumws#11, ws_item_sk#1] + +(10) Exchange +Input [4]: [item_sk#10, d_date#6, sumws#11, ws_item_sk#1] +Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [4]: [item_sk#10, d_date#6, sumws#11, ws_item_sk#1] +Arguments: [ws_item_sk#1 ASC NULLS FIRST, d_date#6 ASC NULLS FIRST], false, 0 + +(12) Window +Input [4]: [item_sk#10, d_date#6, sumws#11, ws_item_sk#1] +Arguments: [row_number() windowspecdefinition(ws_item_sk#1, d_date#6 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#12], [ws_item_sk#1], [d_date#6 ASC NULLS FIRST] + +(13) Project [codegen id : 10] +Output [4]: [item_sk#10, d_date#6, sumws#11, rk#12] +Input [5]: [item_sk#10, d_date#6, sumws#11, ws_item_sk#1, rk#12] + +(14) ReusedExchange [Reuses operator id: 10] +Output [4]: [item_sk#13, d_date#14, sumws#15, ws_item_sk#16] + +(15) Sort [codegen id : 8] +Input [4]: [item_sk#13, d_date#14, sumws#15, ws_item_sk#16] +Arguments: [ws_item_sk#16 ASC NULLS FIRST, d_date#14 ASC NULLS FIRST], false, 0 + +(16) Window +Input [4]: [item_sk#13, d_date#14, sumws#15, ws_item_sk#16] +Arguments: [row_number() windowspecdefinition(ws_item_sk#16, d_date#14 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#17], [ws_item_sk#16], [d_date#14 ASC NULLS FIRST] + +(17) Project [codegen id : 9] +Output [3]: [item_sk#13, sumws#15, rk#17] +Input [5]: [item_sk#13, d_date#14, sumws#15, ws_item_sk#16, rk#17] + +(18) BroadcastExchange +Input [3]: [item_sk#13, sumws#15, rk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] + +(19) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [item_sk#10] +Right keys [1]: [item_sk#13] +Join type: Inner +Join condition: (rk#12 >= rk#17) + +(20) Project [codegen id : 10] +Output [4]: [item_sk#10, d_date#6, sumws#11, sumws#15] +Input [7]: [item_sk#10, d_date#6, sumws#11, rk#12, item_sk#13, sumws#15, rk#17] + +(21) HashAggregate [codegen id : 10] +Input [4]: [item_sk#10, d_date#6, sumws#11, sumws#15] +Keys [3]: [item_sk#10, d_date#6, sumws#11] +Functions [1]: [partial_sum(sumws#15)] +Aggregate Attributes [2]: [sum#18, isEmpty#19] +Results [5]: [item_sk#10, d_date#6, sumws#11, sum#20, isEmpty#21] + +(22) Exchange +Input [5]: [item_sk#10, d_date#6, sumws#11, sum#20, isEmpty#21] +Arguments: hashpartitioning(item_sk#10, d_date#6, sumws#11, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) HashAggregate [codegen id : 11] +Input [5]: [item_sk#10, d_date#6, sumws#11, sum#20, isEmpty#21] +Keys [3]: [item_sk#10, d_date#6, sumws#11] +Functions [1]: [sum(sumws#15)] +Aggregate Attributes [1]: [sum(sumws#15)#22] +Results [3]: [item_sk#10, d_date#6, sum(sumws#15)#22 AS cume_sales#23] + +(24) Exchange +Input [3]: [item_sk#10, d_date#6, cume_sales#23] +Arguments: hashpartitioning(item_sk#10, d_date#6, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(25) Sort [codegen id : 12] +Input [3]: [item_sk#10, d_date#6, cume_sales#23] +Arguments: [item_sk#10 ASC NULLS FIRST, d_date#6 ASC NULLS FIRST], false, 0 + +(26) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#24, ss_sales_price#25, ss_sold_date_sk#26] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_sold_date_sk#26 IN dynamicpruning#27)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(27) ColumnarToRow [codegen id : 14] +Input [3]: [ss_item_sk#24, ss_sales_price#25, ss_sold_date_sk#26] + +(28) Filter [codegen id : 14] +Input [3]: [ss_item_sk#24, ss_sales_price#25, ss_sold_date_sk#26] +Condition : isnotnull(ss_item_sk#24) + +(29) ReusedExchange [Reuses operator id: 72] +Output [2]: [d_date_sk#28, d_date#29] + +(30) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ss_sold_date_sk#26] +Right keys [1]: [d_date_sk#28] +Join type: Inner +Join condition: None + +(31) Project [codegen id : 14] +Output [3]: [ss_item_sk#24, ss_sales_price#25, d_date#29] +Input [5]: [ss_item_sk#24, ss_sales_price#25, ss_sold_date_sk#26, d_date_sk#28, d_date#29] + +(32) HashAggregate [codegen id : 14] +Input [3]: [ss_item_sk#24, ss_sales_price#25, d_date#29] +Keys [2]: [ss_item_sk#24, d_date#29] +Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#25))] +Aggregate Attributes [1]: [sum#30] +Results [3]: [ss_item_sk#24, d_date#29, sum#31] + +(33) Exchange +Input [3]: [ss_item_sk#24, d_date#29, sum#31] +Arguments: hashpartitioning(ss_item_sk#24, d_date#29, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(34) HashAggregate [codegen id : 15] +Input [3]: [ss_item_sk#24, d_date#29, sum#31] +Keys [2]: [ss_item_sk#24, d_date#29] +Functions [1]: [sum(UnscaledValue(ss_sales_price#25))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#25))#32] +Results [4]: [ss_item_sk#24 AS item_sk#33, d_date#29, MakeDecimal(sum(UnscaledValue(ss_sales_price#25))#32,17,2) AS sumss#34, ss_item_sk#24] + +(35) Exchange +Input [4]: [item_sk#33, d_date#29, sumss#34, ss_item_sk#24] +Arguments: hashpartitioning(ss_item_sk#24, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(36) Sort [codegen id : 16] +Input [4]: [item_sk#33, d_date#29, sumss#34, ss_item_sk#24] +Arguments: [ss_item_sk#24 ASC NULLS FIRST, d_date#29 ASC NULLS FIRST], false, 0 + +(37) Window +Input [4]: [item_sk#33, d_date#29, sumss#34, ss_item_sk#24] +Arguments: [row_number() windowspecdefinition(ss_item_sk#24, d_date#29 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#35], [ss_item_sk#24], [d_date#29 ASC NULLS FIRST] + +(38) Project [codegen id : 22] +Output [4]: [item_sk#33, d_date#29, sumss#34, rk#35] +Input [5]: [item_sk#33, d_date#29, sumss#34, ss_item_sk#24, rk#35] + +(39) ReusedExchange [Reuses operator id: 35] +Output [4]: [item_sk#36, d_date#37, sumss#38, ss_item_sk#39] + +(40) Sort [codegen id : 20] +Input [4]: [item_sk#36, d_date#37, sumss#38, ss_item_sk#39] +Arguments: [ss_item_sk#39 ASC NULLS FIRST, d_date#37 ASC NULLS FIRST], false, 0 + +(41) Window +Input [4]: [item_sk#36, d_date#37, sumss#38, ss_item_sk#39] +Arguments: [row_number() windowspecdefinition(ss_item_sk#39, d_date#37 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#40], [ss_item_sk#39], [d_date#37 ASC NULLS FIRST] + +(42) Project [codegen id : 21] +Output [3]: [item_sk#36, sumss#38, rk#40] +Input [5]: [item_sk#36, d_date#37, sumss#38, ss_item_sk#39, rk#40] + +(43) BroadcastExchange +Input [3]: [item_sk#36, sumss#38, rk#40] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] + +(44) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [item_sk#33] +Right keys [1]: [item_sk#36] +Join type: Inner +Join condition: (rk#35 >= rk#40) + +(45) Project [codegen id : 22] +Output [4]: [item_sk#33, d_date#29, sumss#34, sumss#38] +Input [7]: [item_sk#33, d_date#29, sumss#34, rk#35, item_sk#36, sumss#38, rk#40] + +(46) HashAggregate [codegen id : 22] +Input [4]: [item_sk#33, d_date#29, sumss#34, sumss#38] +Keys [3]: [item_sk#33, d_date#29, sumss#34] +Functions [1]: [partial_sum(sumss#38)] +Aggregate Attributes [2]: [sum#41, isEmpty#42] +Results [5]: [item_sk#33, d_date#29, sumss#34, sum#43, isEmpty#44] + +(47) Exchange +Input [5]: [item_sk#33, d_date#29, sumss#34, sum#43, isEmpty#44] +Arguments: hashpartitioning(item_sk#33, d_date#29, sumss#34, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(48) HashAggregate [codegen id : 23] +Input [5]: [item_sk#33, d_date#29, sumss#34, sum#43, isEmpty#44] +Keys [3]: [item_sk#33, d_date#29, sumss#34] +Functions [1]: [sum(sumss#38)] +Aggregate Attributes [1]: [sum(sumss#38)#45] +Results [3]: [item_sk#33, d_date#29, sum(sumss#38)#45 AS cume_sales#46] + +(49) Exchange +Input [3]: [item_sk#33, d_date#29, cume_sales#46] +Arguments: hashpartitioning(item_sk#33, d_date#29, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(50) Sort [codegen id : 24] +Input [3]: [item_sk#33, d_date#29, cume_sales#46] +Arguments: [item_sk#33 ASC NULLS FIRST, d_date#29 ASC NULLS FIRST], false, 0 + +(51) SortMergeJoin [codegen id : 25] +Left keys [2]: [item_sk#10, d_date#6] +Right keys [2]: [item_sk#33, d_date#29] +Join type: FullOuter +Join condition: None + +(52) Filter [codegen id : 25] +Input [6]: [item_sk#10, d_date#6, cume_sales#23, item_sk#33, d_date#29, cume_sales#46] +Condition : isnotnull(CASE WHEN isnotnull(item_sk#10) THEN item_sk#10 ELSE item_sk#33 END) + +(53) Project [codegen id : 25] +Output [4]: [CASE WHEN isnotnull(item_sk#10) THEN item_sk#10 ELSE item_sk#33 END AS item_sk#47, CASE WHEN isnotnull(d_date#6) THEN d_date#6 ELSE d_date#29 END AS d_date#48, cume_sales#23 AS web_sales#49, cume_sales#46 AS store_sales#50] +Input [6]: [item_sk#10, d_date#6, cume_sales#23, item_sk#33, d_date#29, cume_sales#46] + +(54) Exchange +Input [4]: [item_sk#47, d_date#48, web_sales#49, store_sales#50] +Arguments: hashpartitioning(item_sk#47, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(55) Sort [codegen id : 26] +Input [4]: [item_sk#47, d_date#48, web_sales#49, store_sales#50] +Arguments: [item_sk#47 ASC NULLS FIRST, d_date#48 ASC NULLS FIRST], false, 0 + +(56) Window +Input [4]: [item_sk#47, d_date#48, web_sales#49, store_sales#50] +Arguments: [row_number() windowspecdefinition(item_sk#47, d_date#48 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#51], [item_sk#47], [d_date#48 ASC NULLS FIRST] + +(57) ReusedExchange [Reuses operator id: 54] +Output [4]: [item_sk#52, d_date#53, web_sales#54, store_sales#55] + +(58) Sort [codegen id : 52] +Input [4]: [item_sk#52, d_date#53, web_sales#54, store_sales#55] +Arguments: [item_sk#52 ASC NULLS FIRST, d_date#53 ASC NULLS FIRST], false, 0 + +(59) Window +Input [4]: [item_sk#52, d_date#53, web_sales#54, store_sales#55] +Arguments: [row_number() windowspecdefinition(item_sk#52, d_date#53 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#56], [item_sk#52], [d_date#53 ASC NULLS FIRST] + +(60) Project [codegen id : 53] +Output [4]: [item_sk#52, web_sales#54, store_sales#55, rk#56] +Input [5]: [item_sk#52, d_date#53, web_sales#54, store_sales#55, rk#56] + +(61) BroadcastExchange +Input [4]: [item_sk#52, web_sales#54, store_sales#55, rk#56] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12] + +(62) BroadcastHashJoin [codegen id : 54] +Left keys [1]: [item_sk#47] +Right keys [1]: [item_sk#52] +Join type: Inner +Join condition: (rk#51 >= rk#56) + +(63) Project [codegen id : 54] +Output [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, web_sales#54, store_sales#55] +Input [9]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, rk#51, item_sk#52, web_sales#54, store_sales#55, rk#56] + +(64) HashAggregate [codegen id : 54] +Input [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, web_sales#54, store_sales#55] +Keys [4]: [item_sk#47, d_date#48, web_sales#49, store_sales#50] +Functions [2]: [partial_max(web_sales#54), partial_max(store_sales#55)] +Aggregate Attributes [2]: [max#57, max#58] +Results [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, max#59, max#60] + +(65) HashAggregate [codegen id : 54] +Input [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, max#59, max#60] +Keys [4]: [item_sk#47, d_date#48, web_sales#49, store_sales#50] +Functions [2]: [max(web_sales#54), max(store_sales#55)] +Aggregate Attributes [2]: [max(web_sales#54)#61, max(store_sales#55)#62] +Results [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, max(web_sales#54)#61 AS web_cumulative#63, max(store_sales#55)#62 AS store_cumulative#64] + +(66) Filter [codegen id : 54] +Input [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, web_cumulative#63, store_cumulative#64] +Condition : ((isnotnull(web_cumulative#63) AND isnotnull(store_cumulative#64)) AND (web_cumulative#63 > store_cumulative#64)) + +(67) TakeOrderedAndProject +Input [6]: [item_sk#47, d_date#48, web_sales#49, store_sales#50, web_cumulative#63, store_cumulative#64] +Arguments: 100, [item_sk#47 ASC NULLS FIRST, d_date#48 ASC NULLS FIRST], [item_sk#47, d_date#48, web_sales#49, store_sales#50, web_cumulative#63, store_cumulative#64] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (72) ++- * Project (71) + +- * Filter (70) + +- * ColumnarToRow (69) + +- CometScan parquet spark_catalog.default.date_dim (68) + + +(68) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#5, d_date#6, d_month_seq#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] +ReadSchema: struct + +(69) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#5, d_date#6, d_month_seq#65] + +(70) Filter [codegen id : 1] +Input [3]: [d_date_sk#5, d_date#6, d_month_seq#65] +Condition : (((isnotnull(d_month_seq#65) AND (d_month_seq#65 >= 1212)) AND (d_month_seq#65 <= 1223)) AND isnotnull(d_date_sk#5)) + +(71) Project [codegen id : 1] +Output [2]: [d_date_sk#5, d_date#6] +Input [3]: [d_date_sk#5, d_date#6, d_month_seq#65] + +(72) BroadcastExchange +Input [2]: [d_date_sk#5, d_date#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + +Subquery:2 Hosting operator id = 26 Hosting Expression = ss_sold_date_sk#26 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/simplified.txt new file mode 100644 index 000000000..252bc7f69 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/simplified.txt @@ -0,0 +1,124 @@ +TakeOrderedAndProject [item_sk,d_date,web_sales,store_sales,web_cumulative,store_cumulative] + WholeStageCodegen (54) + Filter [web_cumulative,store_cumulative] + HashAggregate [item_sk,d_date,web_sales,store_sales,max,max] [max(web_sales),max(store_sales),web_cumulative,store_cumulative,max,max] + HashAggregate [item_sk,d_date,web_sales,store_sales,web_sales,store_sales] [max,max,max,max] + Project [item_sk,d_date,web_sales,store_sales,web_sales,store_sales] + BroadcastHashJoin [item_sk,item_sk,rk,rk] + InputAdapter + Window [item_sk,d_date] + WholeStageCodegen (26) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk] #1 + WholeStageCodegen (25) + Project [item_sk,item_sk,d_date,d_date,cume_sales,cume_sales] + Filter [item_sk,item_sk] + SortMergeJoin [item_sk,d_date,item_sk,d_date] + InputAdapter + WholeStageCodegen (12) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk,d_date] #2 + WholeStageCodegen (11) + HashAggregate [item_sk,d_date,sumws,sum,isEmpty] [sum(sumws),cume_sales,sum,isEmpty] + InputAdapter + Exchange [item_sk,d_date,sumws] #3 + WholeStageCodegen (10) + HashAggregate [item_sk,d_date,sumws,sumws] [sum,isEmpty,sum,isEmpty] + Project [item_sk,d_date,sumws,sumws] + BroadcastHashJoin [item_sk,item_sk,rk,rk] + Project [item_sk,d_date,sumws,rk] + InputAdapter + Window [ws_item_sk,d_date] + WholeStageCodegen (4) + Sort [ws_item_sk,d_date] + InputAdapter + Exchange [ws_item_sk] #4 + WholeStageCodegen (3) + HashAggregate [ws_item_sk,d_date,sum] [sum(UnscaledValue(ws_sales_price)),item_sk,sumws,sum] + InputAdapter + Exchange [ws_item_sk,d_date] #5 + WholeStageCodegen (2) + HashAggregate [ws_item_sk,d_date,ws_sales_price] [sum,sum] + Project [ws_item_sk,ws_sales_price,d_date] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sales_price,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #6 + WholeStageCodegen (1) + Project [d_date_sk,d_date] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk,d_date] #6 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (9) + Project [item_sk,sumws,rk] + InputAdapter + Window [ws_item_sk,d_date] + WholeStageCodegen (8) + Sort [ws_item_sk,d_date] + InputAdapter + ReusedExchange [item_sk,d_date,sumws,ws_item_sk] #4 + InputAdapter + WholeStageCodegen (24) + Sort [item_sk,d_date] + InputAdapter + Exchange [item_sk,d_date] #8 + WholeStageCodegen (23) + HashAggregate [item_sk,d_date,sumss,sum,isEmpty] [sum(sumss),cume_sales,sum,isEmpty] + InputAdapter + Exchange [item_sk,d_date,sumss] #9 + WholeStageCodegen (22) + HashAggregate [item_sk,d_date,sumss,sumss] [sum,isEmpty,sum,isEmpty] + Project [item_sk,d_date,sumss,sumss] + BroadcastHashJoin [item_sk,item_sk,rk,rk] + Project [item_sk,d_date,sumss,rk] + InputAdapter + Window [ss_item_sk,d_date] + WholeStageCodegen (16) + Sort [ss_item_sk,d_date] + InputAdapter + Exchange [ss_item_sk] #10 + WholeStageCodegen (15) + HashAggregate [ss_item_sk,d_date,sum] [sum(UnscaledValue(ss_sales_price)),item_sk,sumss,sum] + InputAdapter + Exchange [ss_item_sk,d_date] #11 + WholeStageCodegen (14) + HashAggregate [ss_item_sk,d_date,ss_sales_price] [sum,sum] + Project [ss_item_sk,ss_sales_price,d_date] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_date] #6 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (21) + Project [item_sk,sumss,rk] + InputAdapter + Window [ss_item_sk,d_date] + WholeStageCodegen (20) + Sort [ss_item_sk,d_date] + InputAdapter + ReusedExchange [item_sk,d_date,sumss,ss_item_sk] #10 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (53) + Project [item_sk,web_sales,store_sales,rk] + InputAdapter + Window [item_sk,d_date] + WholeStageCodegen (52) + Sort [item_sk,d_date] + InputAdapter + ReusedExchange [item_sk,d_date,web_sales,store_sales] #1 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/explain.txt new file mode 100644 index 000000000..ef343f0e7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/explain.txt @@ -0,0 +1,279 @@ +== Physical Plan == +TakeOrderedAndProject (45) ++- * Project (44) + +- * BroadcastHashJoin Inner BuildRight (43) + :- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (28) + : : +- * Filter (27) + : : +- Window (26) + : : +- * Filter (25) + : : +- Window (24) + : : +- * Sort (23) + : : +- Exchange (22) + : : +- * HashAggregate (21) + : : +- Exchange (20) + : : +- * HashAggregate (19) + : : +- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.item (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (16) + : : +- * Filter (15) + : : +- * ColumnarToRow (14) + : : +- CometScan parquet spark_catalog.default.call_center (13) + : +- BroadcastExchange (35) + : +- * Project (34) + : +- Window (33) + : +- * Sort (32) + : +- Exchange (31) + : +- * HashAggregate (30) + : +- ReusedExchange (29) + +- BroadcastExchange (42) + +- * Project (41) + +- Window (40) + +- * Sort (39) + +- ReusedExchange (38) + + +(1) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#1, i_brand#2, i_category#3] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] + +(3) Filter [codegen id : 4] +Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) + +(4) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#7), dynamicpruningexpression(cs_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_call_center_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] + +(6) Filter [codegen id : 1] +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Condition : (isnotnull(cs_item_sk#5) AND isnotnull(cs_call_center_sk#4)) + +(7) BroadcastExchange +Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [i_item_sk#1] +Right keys [1]: [cs_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 4] +Output [5]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, cs_sold_date_sk#7] +Input [7]: [i_item_sk#1, i_brand#2, i_category#3, cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 49] +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, d_year#10, d_moy#11] +Input [8]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, cs_sold_date_sk#7, d_date_sk#9, d_year#10, d_moy#11] + +(13) Scan parquet spark_catalog.default.call_center +Output [2]: [cc_call_center_sk#12, cc_name#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/call_center] +PushedFilters: [IsNotNull(cc_call_center_sk), IsNotNull(cc_name)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [2]: [cc_call_center_sk#12, cc_name#13] + +(15) Filter [codegen id : 3] +Input [2]: [cc_call_center_sk#12, cc_name#13] +Condition : (isnotnull(cc_call_center_sk#12) AND isnotnull(cc_name#13)) + +(16) BroadcastExchange +Input [2]: [cc_call_center_sk#12, cc_name#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [cs_call_center_sk#4] +Right keys [1]: [cc_call_center_sk#12] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [6]: [i_brand#2, i_category#3, cs_sales_price#6, d_year#10, d_moy#11, cc_name#13] +Input [8]: [i_brand#2, i_category#3, cs_call_center_sk#4, cs_sales_price#6, d_year#10, d_moy#11, cc_call_center_sk#12, cc_name#13] + +(19) HashAggregate [codegen id : 4] +Input [6]: [i_brand#2, i_category#3, cs_sales_price#6, d_year#10, d_moy#11, cc_name#13] +Keys [5]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11] +Functions [1]: [partial_sum(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [1]: [sum#14] +Results [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] + +(20) Exchange +Input [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] +Arguments: hashpartitioning(i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [6]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum#15] +Keys [5]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11] +Functions [1]: [sum(UnscaledValue(cs_sales_price#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_sales_price#6))#16] +Results [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, MakeDecimal(sum(UnscaledValue(cs_sales_price#6))#16,17,2) AS sum_sales#17, MakeDecimal(sum(UnscaledValue(cs_sales_price#6))#16,17,2) AS _w0#18] + +(22) Exchange +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: hashpartitioning(i_category#3, i_brand#2, cc_name#13, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(23) Sort [codegen id : 6] +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: [i_category#3 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, cc_name#13 ASC NULLS FIRST, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST], false, 0 + +(24) Window +Input [7]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18] +Arguments: [rank(d_year#10, d_moy#11) windowspecdefinition(i_category#3, i_brand#2, cc_name#13, d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#19], [i_category#3, i_brand#2, cc_name#13], [d_year#10 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST] + +(25) Filter [codegen id : 7] +Input [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19] +Condition : (isnotnull(d_year#10) AND (d_year#10 = 1999)) + +(26) Window +Input [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19] +Arguments: [avg(_w0#18) windowspecdefinition(i_category#3, i_brand#2, cc_name#13, d_year#10, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#20], [i_category#3, i_brand#2, cc_name#13, d_year#10] + +(27) Filter [codegen id : 22] +Input [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19, avg_monthly_sales#20] +Condition : ((isnotnull(avg_monthly_sales#20) AND (avg_monthly_sales#20 > 0.000000)) AND CASE WHEN (avg_monthly_sales#20 > 0.000000) THEN ((abs((sum_sales#17 - avg_monthly_sales#20)) / avg_monthly_sales#20) > 0.1000000000000000) END) + +(28) Project [codegen id : 22] +Output [8]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19] +Input [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, _w0#18, rn#19, avg_monthly_sales#20] + +(29) ReusedExchange [Reuses operator id: 20] +Output [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum#26] + +(30) HashAggregate [codegen id : 12] +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum#26] +Keys [5]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25] +Functions [1]: [sum(UnscaledValue(cs_sales_price#27))] +Aggregate Attributes [1]: [sum(UnscaledValue(cs_sales_price#27))#16] +Results [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, MakeDecimal(sum(UnscaledValue(cs_sales_price#27))#16,17,2) AS sum_sales#28] + +(31) Exchange +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: hashpartitioning(i_category#21, i_brand#22, cc_name#23, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 13] +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: [i_category#21 ASC NULLS FIRST, i_brand#22 ASC NULLS FIRST, cc_name#23 ASC NULLS FIRST, d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST], false, 0 + +(33) Window +Input [6]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28] +Arguments: [rank(d_year#24, d_moy#25) windowspecdefinition(i_category#21, i_brand#22, cc_name#23, d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#29], [i_category#21, i_brand#22, cc_name#23], [d_year#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST] + +(34) Project [codegen id : 14] +Output [5]: [i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] +Input [7]: [i_category#21, i_brand#22, cc_name#23, d_year#24, d_moy#25, sum_sales#28, rn#29] + +(35) BroadcastExchange +Input [5]: [i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], (input[4, int, false] + 1)),false), [plan_id=6] + +(36) BroadcastHashJoin [codegen id : 22] +Left keys [4]: [i_category#3, i_brand#2, cc_name#13, rn#19] +Right keys [4]: [i_category#21, i_brand#22, cc_name#23, (rn#29 + 1)] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 22] +Output [9]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, sum_sales#28] +Input [13]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, i_category#21, i_brand#22, cc_name#23, sum_sales#28, rn#29] + +(38) ReusedExchange [Reuses operator id: 31] +Output [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] + +(39) Sort [codegen id : 20] +Input [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] +Arguments: [i_category#30 ASC NULLS FIRST, i_brand#31 ASC NULLS FIRST, cc_name#32 ASC NULLS FIRST, d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST], false, 0 + +(40) Window +Input [6]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35] +Arguments: [rank(d_year#33, d_moy#34) windowspecdefinition(i_category#30, i_brand#31, cc_name#32, d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rn#36], [i_category#30, i_brand#31, cc_name#32], [d_year#33 ASC NULLS FIRST, d_moy#34 ASC NULLS FIRST] + +(41) Project [codegen id : 21] +Output [5]: [i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] +Input [7]: [i_category#30, i_brand#31, cc_name#32, d_year#33, d_moy#34, sum_sales#35, rn#36] + +(42) BroadcastExchange +Input [5]: [i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true], input[1, string, true], input[2, string, true], (input[4, int, false] - 1)),false), [plan_id=7] + +(43) BroadcastHashJoin [codegen id : 22] +Left keys [4]: [i_category#3, i_brand#2, cc_name#13, rn#19] +Right keys [4]: [i_category#30, i_brand#31, cc_name#32, (rn#36 - 1)] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 22] +Output [8]: [i_category#3, i_brand#2, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, sum_sales#28 AS psum#37, sum_sales#35 AS nsum#38] +Input [14]: [i_category#3, i_brand#2, cc_name#13, d_year#10, d_moy#11, sum_sales#17, avg_monthly_sales#20, rn#19, sum_sales#28, i_category#30, i_brand#31, cc_name#32, sum_sales#35, rn#36] + +(45) TakeOrderedAndProject +Input [8]: [i_category#3, i_brand#2, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, psum#37, nsum#38] +Arguments: 100, [(sum_sales#17 - avg_monthly_sales#20) ASC NULLS FIRST, d_year#10 ASC NULLS FIRST], [i_category#3, i_brand#2, d_year#10, d_moy#11, avg_monthly_sales#20, sum_sales#17, psum#37, nsum#38] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = cs_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (49) ++- * Filter (48) + +- * ColumnarToRow (47) + +- CometScan parquet spark_catalog.default.date_dim (46) + + +(46) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_date_sk#9, d_year#10, d_moy#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] + +(48) Filter [codegen id : 1] +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) + +(49) BroadcastExchange +Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/simplified.txt new file mode 100644 index 000000000..8e259bf7f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/simplified.txt @@ -0,0 +1,81 @@ +TakeOrderedAndProject [sum_sales,avg_monthly_sales,d_year,i_category,i_brand,d_moy,psum,nsum] + WholeStageCodegen (22) + Project [i_category,i_brand,d_year,d_moy,avg_monthly_sales,sum_sales,sum_sales,sum_sales] + BroadcastHashJoin [i_category,i_brand,cc_name,rn,i_category,i_brand,cc_name,rn] + Project [i_category,i_brand,cc_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn,sum_sales] + BroadcastHashJoin [i_category,i_brand,cc_name,rn,i_category,i_brand,cc_name,rn] + Project [i_category,i_brand,cc_name,d_year,d_moy,sum_sales,avg_monthly_sales,rn] + Filter [avg_monthly_sales,sum_sales] + InputAdapter + Window [_w0,i_category,i_brand,cc_name,d_year] + WholeStageCodegen (7) + Filter [d_year] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (6) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,cc_name] #1 + WholeStageCodegen (5) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,sum] [sum(UnscaledValue(cs_sales_price)),sum_sales,_w0,sum] + InputAdapter + Exchange [i_category,i_brand,cc_name,d_year,d_moy] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,cs_sales_price] [sum,sum] + Project [i_brand,i_category,cs_sales_price,d_year,d_moy,cc_name] + BroadcastHashJoin [cs_call_center_sk,cc_call_center_sk] + Project [i_brand,i_category,cs_call_center_sk,cs_sales_price,d_year,d_moy] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [i_brand,i_category,cs_call_center_sk,cs_sales_price,cs_sold_date_sk] + BroadcastHashJoin [i_item_sk,cs_item_sk] + Filter [i_item_sk,i_category,i_brand] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [cs_item_sk,cs_call_center_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_call_center_sk,cs_item_sk,cs_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [d_year,d_moy,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [cc_call_center_sk,cc_name] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (14) + Project [i_category,i_brand,cc_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (13) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + Exchange [i_category,i_brand,cc_name] #7 + WholeStageCodegen (12) + HashAggregate [i_category,i_brand,cc_name,d_year,d_moy,sum] [sum(UnscaledValue(cs_sales_price)),sum_sales,sum] + InputAdapter + ReusedExchange [i_category,i_brand,cc_name,d_year,d_moy,sum] #2 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (21) + Project [i_category,i_brand,cc_name,sum_sales,rn] + InputAdapter + Window [d_year,d_moy,i_category,i_brand,cc_name] + WholeStageCodegen (20) + Sort [i_category,i_brand,cc_name,d_year,d_moy] + InputAdapter + ReusedExchange [i_category,i_brand,cc_name,d_year,d_moy,sum_sales] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/explain.txt new file mode 100644 index 000000000..8489cf66d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/explain.txt @@ -0,0 +1,553 @@ +== Physical Plan == +TakeOrderedAndProject (87) ++- * HashAggregate (86) + +- Exchange (85) + +- * HashAggregate (84) + +- Union (83) + :- * HashAggregate (72) + : +- Exchange (71) + : +- * HashAggregate (70) + : +- Union (69) + : :- * HashAggregate (21) + : : +- Exchange (20) + : : +- * HashAggregate (19) + : : +- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- Union (9) + : : : : :- * Project (4) + : : : : : +- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- * Project (8) + : : : : +- * Filter (7) + : : : : +- * ColumnarToRow (6) + : : : : +- CometScan parquet spark_catalog.default.store_returns (5) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (16) + : : +- * Filter (15) + : : +- * ColumnarToRow (14) + : : +- CometScan parquet spark_catalog.default.store (13) + : :- * HashAggregate (42) + : : +- Exchange (41) + : : +- * HashAggregate (40) + : : +- * Project (39) + : : +- * BroadcastHashJoin Inner BuildRight (38) + : : :- * Project (33) + : : : +- * BroadcastHashJoin Inner BuildRight (32) + : : : :- Union (30) + : : : : :- * Project (25) + : : : : : +- * Filter (24) + : : : : : +- * ColumnarToRow (23) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (22) + : : : : +- * Project (29) + : : : : +- * Filter (28) + : : : : +- * ColumnarToRow (27) + : : : : +- CometScan parquet spark_catalog.default.catalog_returns (26) + : : : +- ReusedExchange (31) + : : +- BroadcastExchange (37) + : : +- * Filter (36) + : : +- * ColumnarToRow (35) + : : +- CometScan parquet spark_catalog.default.catalog_page (34) + : +- * HashAggregate (68) + : +- Exchange (67) + : +- * HashAggregate (66) + : +- * Project (65) + : +- * BroadcastHashJoin Inner BuildRight (64) + : :- * Project (59) + : : +- * BroadcastHashJoin Inner BuildRight (58) + : : :- Union (56) + : : : :- * Project (46) + : : : : +- * Filter (45) + : : : : +- * ColumnarToRow (44) + : : : : +- CometScan parquet spark_catalog.default.web_sales (43) + : : : +- * Project (55) + : : : +- * BroadcastHashJoin Inner BuildLeft (54) + : : : :- BroadcastExchange (49) + : : : : +- * ColumnarToRow (48) + : : : : +- CometScan parquet spark_catalog.default.web_returns (47) + : : : +- * Project (53) + : : : +- * Filter (52) + : : : +- * ColumnarToRow (51) + : : : +- CometScan parquet spark_catalog.default.web_sales (50) + : : +- ReusedExchange (57) + : +- BroadcastExchange (63) + : +- * Filter (62) + : +- * ColumnarToRow (61) + : +- CometScan parquet spark_catalog.default.web_site (60) + :- * HashAggregate (77) + : +- Exchange (76) + : +- * HashAggregate (75) + : +- * HashAggregate (74) + : +- ReusedExchange (73) + +- * HashAggregate (82) + +- Exchange (81) + +- * HashAggregate (80) + +- * HashAggregate (79) + +- ReusedExchange (78) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 1] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_store_sk#1) + +(4) Project [codegen id : 1] +Output [6]: [ss_store_sk#1 AS store_sk#6, ss_sold_date_sk#4 AS date_sk#7, ss_ext_sales_price#2 AS sales_price#8, ss_net_profit#3 AS profit#9, 0.00 AS return_amt#10, 0.00 AS net_loss#11] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] + +(5) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#15), dynamicpruningexpression(sr_returned_date_sk#15 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(sr_store_sk)] +ReadSchema: struct + +(6) ColumnarToRow [codegen id : 2] +Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] + +(7) Filter [codegen id : 2] +Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Condition : isnotnull(sr_store_sk#12) + +(8) Project [codegen id : 2] +Output [6]: [sr_store_sk#12 AS store_sk#16, sr_returned_date_sk#15 AS date_sk#17, 0.00 AS sales_price#18, 0.00 AS profit#19, sr_return_amt#13 AS return_amt#20, sr_net_loss#14 AS net_loss#21] +Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] + +(9) Union + +(10) ReusedExchange [Reuses operator id: 92] +Output [1]: [d_date_sk#22] + +(11) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [date_sk#7] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 5] +Output [5]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11] +Input [7]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11, d_date_sk#22] + +(13) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#23, s_store_id#24] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 4] +Input [2]: [s_store_sk#23, s_store_id#24] + +(15) Filter [codegen id : 4] +Input [2]: [s_store_sk#23, s_store_id#24] +Condition : isnotnull(s_store_sk#23) + +(16) BroadcastExchange +Input [2]: [s_store_sk#23, s_store_id#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(17) BroadcastHashJoin [codegen id : 5] +Left keys [1]: [store_sk#6] +Right keys [1]: [s_store_sk#23] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 5] +Output [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] +Input [7]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_sk#23, s_store_id#24] + +(19) HashAggregate [codegen id : 5] +Input [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] +Keys [1]: [s_store_id#24] +Functions [4]: [partial_sum(UnscaledValue(sales_price#8)), partial_sum(UnscaledValue(return_amt#10)), partial_sum(UnscaledValue(profit#9)), partial_sum(UnscaledValue(net_loss#11))] +Aggregate Attributes [4]: [sum#25, sum#26, sum#27, sum#28] +Results [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] + +(20) Exchange +Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] +Arguments: hashpartitioning(s_store_id#24, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(21) HashAggregate [codegen id : 6] +Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] +Keys [1]: [s_store_id#24] +Functions [4]: [sum(UnscaledValue(sales_price#8)), sum(UnscaledValue(return_amt#10)), sum(UnscaledValue(profit#9)), sum(UnscaledValue(net_loss#11))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#8))#33, sum(UnscaledValue(return_amt#10))#34, sum(UnscaledValue(profit#9))#35, sum(UnscaledValue(net_loss#11))#36] +Results [5]: [store channel AS channel#37, concat(store, s_store_id#24) AS id#38, MakeDecimal(sum(UnscaledValue(sales_price#8))#33,17,2) AS sales#39, MakeDecimal(sum(UnscaledValue(return_amt#10))#34,17,2) AS returns#40, (MakeDecimal(sum(UnscaledValue(profit#9))#35,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#11))#36,17,2)) AS profit#41] + +(22) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_sold_date_sk#45 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cs_catalog_page_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 7] +Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] + +(24) Filter [codegen id : 7] +Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Condition : isnotnull(cs_catalog_page_sk#42) + +(25) Project [codegen id : 7] +Output [6]: [cs_catalog_page_sk#42 AS page_sk#47, cs_sold_date_sk#45 AS date_sk#48, cs_ext_sales_price#43 AS sales_price#49, cs_net_profit#44 AS profit#50, 0.00 AS return_amt#51, 0.00 AS net_loss#52] +Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] + +(26) Scan parquet spark_catalog.default.catalog_returns +Output [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#56), dynamicpruningexpression(cr_returned_date_sk#56 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cr_catalog_page_sk)] +ReadSchema: struct + +(27) ColumnarToRow [codegen id : 8] +Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] + +(28) Filter [codegen id : 8] +Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Condition : isnotnull(cr_catalog_page_sk#53) + +(29) Project [codegen id : 8] +Output [6]: [cr_catalog_page_sk#53 AS page_sk#57, cr_returned_date_sk#56 AS date_sk#58, 0.00 AS sales_price#59, 0.00 AS profit#60, cr_return_amount#54 AS return_amt#61, cr_net_loss#55 AS net_loss#62] +Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] + +(30) Union + +(31) ReusedExchange [Reuses operator id: 92] +Output [1]: [d_date_sk#63] + +(32) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [date_sk#48] +Right keys [1]: [d_date_sk#63] +Join type: Inner +Join condition: None + +(33) Project [codegen id : 11] +Output [5]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52] +Input [7]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52, d_date_sk#63] + +(34) Scan parquet spark_catalog.default.catalog_page +Output [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_page] +PushedFilters: [IsNotNull(cp_catalog_page_sk)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 10] +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] + +(36) Filter [codegen id : 10] +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Condition : isnotnull(cp_catalog_page_sk#64) + +(37) BroadcastExchange +Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(38) BroadcastHashJoin [codegen id : 11] +Left keys [1]: [page_sk#47] +Right keys [1]: [cp_catalog_page_sk#64] +Join type: Inner +Join condition: None + +(39) Project [codegen id : 11] +Output [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] +Input [7]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_sk#64, cp_catalog_page_id#65] + +(40) HashAggregate [codegen id : 11] +Input [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] +Keys [1]: [cp_catalog_page_id#65] +Functions [4]: [partial_sum(UnscaledValue(sales_price#49)), partial_sum(UnscaledValue(return_amt#51)), partial_sum(UnscaledValue(profit#50)), partial_sum(UnscaledValue(net_loss#52))] +Aggregate Attributes [4]: [sum#66, sum#67, sum#68, sum#69] +Results [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] + +(41) Exchange +Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] +Arguments: hashpartitioning(cp_catalog_page_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(42) HashAggregate [codegen id : 12] +Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] +Keys [1]: [cp_catalog_page_id#65] +Functions [4]: [sum(UnscaledValue(sales_price#49)), sum(UnscaledValue(return_amt#51)), sum(UnscaledValue(profit#50)), sum(UnscaledValue(net_loss#52))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#49))#74, sum(UnscaledValue(return_amt#51))#75, sum(UnscaledValue(profit#50))#76, sum(UnscaledValue(net_loss#52))#77] +Results [5]: [catalog channel AS channel#78, concat(catalog_page, cp_catalog_page_id#65) AS id#79, MakeDecimal(sum(UnscaledValue(sales_price#49))#74,17,2) AS sales#80, MakeDecimal(sum(UnscaledValue(return_amt#51))#75,17,2) AS returns#81, (MakeDecimal(sum(UnscaledValue(profit#50))#76,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#52))#77,17,2)) AS profit#82] + +(43) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#86), dynamicpruningexpression(ws_sold_date_sk#86 IN dynamicpruning#87)] +PushedFilters: [IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(44) ColumnarToRow [codegen id : 13] +Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] + +(45) Filter [codegen id : 13] +Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Condition : isnotnull(ws_web_site_sk#83) + +(46) Project [codegen id : 13] +Output [6]: [ws_web_site_sk#83 AS wsr_web_site_sk#88, ws_sold_date_sk#86 AS date_sk#89, ws_ext_sales_price#84 AS sales_price#90, ws_net_profit#85 AS profit#91, 0.00 AS return_amt#92, 0.00 AS net_loss#93] +Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] + +(47) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#98), dynamicpruningexpression(wr_returned_date_sk#98 IN dynamicpruning#87)] +ReadSchema: struct + +(48) ColumnarToRow [codegen id : 14] +Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] + +(49) BroadcastExchange +Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, true] as bigint), 32) | (cast(input[1, int, true] as bigint) & 4294967295))),false), [plan_id=5] + +(50) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_sales] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_site_sk)] +ReadSchema: struct + +(51) ColumnarToRow +Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] + +(52) Filter +Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Condition : ((isnotnull(ws_item_sk#99) AND isnotnull(ws_order_number#101)) AND isnotnull(ws_web_site_sk#100)) + +(53) Project +Output [3]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] + +(54) BroadcastHashJoin [codegen id : 15] +Left keys [2]: [wr_item_sk#94, wr_order_number#95] +Right keys [2]: [ws_item_sk#99, ws_order_number#101] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 15] +Output [6]: [ws_web_site_sk#100 AS wsr_web_site_sk#103, wr_returned_date_sk#98 AS date_sk#104, 0.00 AS sales_price#105, 0.00 AS profit#106, wr_return_amt#96 AS return_amt#107, wr_net_loss#97 AS net_loss#108] +Input [8]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98, ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] + +(56) Union + +(57) ReusedExchange [Reuses operator id: 92] +Output [1]: [d_date_sk#109] + +(58) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [date_sk#89] +Right keys [1]: [d_date_sk#109] +Join type: Inner +Join condition: None + +(59) Project [codegen id : 18] +Output [5]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93] +Input [7]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93, d_date_sk#109] + +(60) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#110, web_site_id#111] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_site_sk)] +ReadSchema: struct + +(61) ColumnarToRow [codegen id : 17] +Input [2]: [web_site_sk#110, web_site_id#111] + +(62) Filter [codegen id : 17] +Input [2]: [web_site_sk#110, web_site_id#111] +Condition : isnotnull(web_site_sk#110) + +(63) BroadcastExchange +Input [2]: [web_site_sk#110, web_site_id#111] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(64) BroadcastHashJoin [codegen id : 18] +Left keys [1]: [wsr_web_site_sk#88] +Right keys [1]: [web_site_sk#110] +Join type: Inner +Join condition: None + +(65) Project [codegen id : 18] +Output [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] +Input [7]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_sk#110, web_site_id#111] + +(66) HashAggregate [codegen id : 18] +Input [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] +Keys [1]: [web_site_id#111] +Functions [4]: [partial_sum(UnscaledValue(sales_price#90)), partial_sum(UnscaledValue(return_amt#92)), partial_sum(UnscaledValue(profit#91)), partial_sum(UnscaledValue(net_loss#93))] +Aggregate Attributes [4]: [sum#112, sum#113, sum#114, sum#115] +Results [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] + +(67) Exchange +Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] +Arguments: hashpartitioning(web_site_id#111, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(68) HashAggregate [codegen id : 19] +Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] +Keys [1]: [web_site_id#111] +Functions [4]: [sum(UnscaledValue(sales_price#90)), sum(UnscaledValue(return_amt#92)), sum(UnscaledValue(profit#91)), sum(UnscaledValue(net_loss#93))] +Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#90))#120, sum(UnscaledValue(return_amt#92))#121, sum(UnscaledValue(profit#91))#122, sum(UnscaledValue(net_loss#93))#123] +Results [5]: [web channel AS channel#124, concat(web_site, web_site_id#111) AS id#125, MakeDecimal(sum(UnscaledValue(sales_price#90))#120,17,2) AS sales#126, MakeDecimal(sum(UnscaledValue(return_amt#92))#121,17,2) AS returns#127, (MakeDecimal(sum(UnscaledValue(profit#91))#122,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#93))#123,17,2)) AS profit#128] + +(69) Union + +(70) HashAggregate [codegen id : 20] +Input [5]: [channel#37, id#38, sales#39, returns#40, profit#41] +Keys [2]: [channel#37, id#38] +Functions [3]: [partial_sum(sales#39), partial_sum(returns#40), partial_sum(profit#41)] +Aggregate Attributes [6]: [sum#129, isEmpty#130, sum#131, isEmpty#132, sum#133, isEmpty#134] +Results [8]: [channel#37, id#38, sum#135, isEmpty#136, sum#137, isEmpty#138, sum#139, isEmpty#140] + +(71) Exchange +Input [8]: [channel#37, id#38, sum#135, isEmpty#136, sum#137, isEmpty#138, sum#139, isEmpty#140] +Arguments: hashpartitioning(channel#37, id#38, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(72) HashAggregate [codegen id : 21] +Input [8]: [channel#37, id#38, sum#135, isEmpty#136, sum#137, isEmpty#138, sum#139, isEmpty#140] +Keys [2]: [channel#37, id#38] +Functions [3]: [sum(sales#39), sum(returns#40), sum(profit#41)] +Aggregate Attributes [3]: [sum(sales#39)#141, sum(returns#40)#142, sum(profit#41)#143] +Results [5]: [channel#37, id#38, cast(sum(sales#39)#141 as decimal(37,2)) AS sales#144, cast(sum(returns#40)#142 as decimal(37,2)) AS returns#145, cast(sum(profit#41)#143 as decimal(38,2)) AS profit#146] + +(73) ReusedExchange [Reuses operator id: 71] +Output [8]: [channel#147, id#148, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] + +(74) HashAggregate [codegen id : 42] +Input [8]: [channel#147, id#148, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] +Keys [2]: [channel#147, id#148] +Functions [3]: [sum(sales#155), sum(returns#156), sum(profit#157)] +Aggregate Attributes [3]: [sum(sales#155)#141, sum(returns#156)#142, sum(profit#157)#143] +Results [4]: [channel#147, sum(sales#155)#141 AS sales#158, sum(returns#156)#142 AS returns#159, sum(profit#157)#143 AS profit#160] + +(75) HashAggregate [codegen id : 42] +Input [4]: [channel#147, sales#158, returns#159, profit#160] +Keys [1]: [channel#147] +Functions [3]: [partial_sum(sales#158), partial_sum(returns#159), partial_sum(profit#160)] +Aggregate Attributes [6]: [sum#161, isEmpty#162, sum#163, isEmpty#164, sum#165, isEmpty#166] +Results [7]: [channel#147, sum#167, isEmpty#168, sum#169, isEmpty#170, sum#171, isEmpty#172] + +(76) Exchange +Input [7]: [channel#147, sum#167, isEmpty#168, sum#169, isEmpty#170, sum#171, isEmpty#172] +Arguments: hashpartitioning(channel#147, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(77) HashAggregate [codegen id : 43] +Input [7]: [channel#147, sum#167, isEmpty#168, sum#169, isEmpty#170, sum#171, isEmpty#172] +Keys [1]: [channel#147] +Functions [3]: [sum(sales#158), sum(returns#159), sum(profit#160)] +Aggregate Attributes [3]: [sum(sales#158)#173, sum(returns#159)#174, sum(profit#160)#175] +Results [5]: [channel#147, null AS id#176, sum(sales#158)#173 AS sum(sales)#177, sum(returns#159)#174 AS sum(returns)#178, sum(profit#160)#175 AS sum(profit)#179] + +(78) ReusedExchange [Reuses operator id: 71] +Output [8]: [channel#180, id#181, sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] + +(79) HashAggregate [codegen id : 64] +Input [8]: [channel#180, id#181, sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] +Keys [2]: [channel#180, id#181] +Functions [3]: [sum(sales#188), sum(returns#189), sum(profit#190)] +Aggregate Attributes [3]: [sum(sales#188)#141, sum(returns#189)#142, sum(profit#190)#143] +Results [3]: [sum(sales#188)#141 AS sales#191, sum(returns#189)#142 AS returns#192, sum(profit#190)#143 AS profit#193] + +(80) HashAggregate [codegen id : 64] +Input [3]: [sales#191, returns#192, profit#193] +Keys: [] +Functions [3]: [partial_sum(sales#191), partial_sum(returns#192), partial_sum(profit#193)] +Aggregate Attributes [6]: [sum#194, isEmpty#195, sum#196, isEmpty#197, sum#198, isEmpty#199] +Results [6]: [sum#200, isEmpty#201, sum#202, isEmpty#203, sum#204, isEmpty#205] + +(81) Exchange +Input [6]: [sum#200, isEmpty#201, sum#202, isEmpty#203, sum#204, isEmpty#205] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=10] + +(82) HashAggregate [codegen id : 65] +Input [6]: [sum#200, isEmpty#201, sum#202, isEmpty#203, sum#204, isEmpty#205] +Keys: [] +Functions [3]: [sum(sales#191), sum(returns#192), sum(profit#193)] +Aggregate Attributes [3]: [sum(sales#191)#206, sum(returns#192)#207, sum(profit#193)#208] +Results [5]: [null AS channel#209, null AS id#210, sum(sales#191)#206 AS sum(sales)#211, sum(returns#192)#207 AS sum(returns)#212, sum(profit#193)#208 AS sum(profit)#213] + +(83) Union + +(84) HashAggregate [codegen id : 66] +Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Keys [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#37, id#38, sales#144, returns#145, profit#146] + +(85) Exchange +Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Arguments: hashpartitioning(channel#37, id#38, sales#144, returns#145, profit#146, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(86) HashAggregate [codegen id : 67] +Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Keys [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#37, id#38, sales#144, returns#145, profit#146] + +(87) TakeOrderedAndProject +Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] +Arguments: 100, [channel#37 ASC NULLS FIRST, id#38 ASC NULLS FIRST], [channel#37, id#38, sales#144, returns#145, profit#146] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (92) ++- * Project (91) + +- * Filter (90) + +- * ColumnarToRow (89) + +- CometScan parquet spark_catalog.default.date_dim (88) + + +(88) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#22, d_date#214] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1998-08-04), LessThanOrEqual(d_date,1998-08-18), IsNotNull(d_date_sk)] +ReadSchema: struct + +(89) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#22, d_date#214] + +(90) Filter [codegen id : 1] +Input [2]: [d_date_sk#22, d_date#214] +Condition : (((isnotnull(d_date#214) AND (d_date#214 >= 1998-08-04)) AND (d_date#214 <= 1998-08-18)) AND isnotnull(d_date_sk#22)) + +(91) Project [codegen id : 1] +Output [1]: [d_date_sk#22] +Input [2]: [d_date_sk#22, d_date#214] + +(92) BroadcastExchange +Input [1]: [d_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 5 Hosting Expression = sr_returned_date_sk#15 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 22 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#5 + +Subquery:4 Hosting operator id = 26 Hosting Expression = cr_returned_date_sk#56 IN dynamicpruning#5 + +Subquery:5 Hosting operator id = 43 Hosting Expression = ws_sold_date_sk#86 IN dynamicpruning#5 + +Subquery:6 Hosting operator id = 47 Hosting Expression = wr_returned_date_sk#98 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/simplified.txt new file mode 100644 index 000000000..f132fec3b --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/simplified.txt @@ -0,0 +1,155 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (67) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Exchange [channel,id,sales,returns,profit] #1 + WholeStageCodegen (66) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Union + WholeStageCodegen (21) + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id] #2 + WholeStageCodegen (20) + HashAggregate [channel,id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (6) + HashAggregate [s_store_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),channel,id,sales,returns,profit,sum,sum,sum,sum] + InputAdapter + Exchange [s_store_id] #3 + WholeStageCodegen (5) + HashAggregate [s_store_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,s_store_id] + BroadcastHashJoin [store_sk,s_store_sk] + Project [store_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + InputAdapter + Union + WholeStageCodegen (1) + Project [ss_store_sk,ss_sold_date_sk,ss_ext_sales_price,ss_net_profit] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + WholeStageCodegen (2) + Project [sr_store_sk,sr_returned_date_sk,sr_return_amt,sr_net_loss] + Filter [sr_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (4) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + WholeStageCodegen (12) + HashAggregate [cp_catalog_page_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),channel,id,sales,returns,profit,sum,sum,sum,sum] + InputAdapter + Exchange [cp_catalog_page_id] #6 + WholeStageCodegen (11) + HashAggregate [cp_catalog_page_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,cp_catalog_page_id] + BroadcastHashJoin [page_sk,cp_catalog_page_sk] + Project [page_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + InputAdapter + Union + WholeStageCodegen (7) + Project [cs_catalog_page_sk,cs_sold_date_sk,cs_ext_sales_price,cs_net_profit] + Filter [cs_catalog_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + WholeStageCodegen (8) + Project [cr_catalog_page_sk,cr_returned_date_sk,cr_return_amount,cr_net_loss] + Filter [cr_catalog_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_catalog_page_sk,cr_return_amount,cr_net_loss,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (10) + Filter [cp_catalog_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] + WholeStageCodegen (19) + HashAggregate [web_site_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),channel,id,sales,returns,profit,sum,sum,sum,sum] + InputAdapter + Exchange [web_site_id] #8 + WholeStageCodegen (18) + HashAggregate [web_site_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] + Project [sales_price,profit,return_amt,net_loss,web_site_id] + BroadcastHashJoin [wsr_web_site_sk,web_site_sk] + Project [wsr_web_site_sk,sales_price,profit,return_amt,net_loss] + BroadcastHashJoin [date_sk,d_date_sk] + InputAdapter + Union + WholeStageCodegen (13) + Project [ws_web_site_sk,ws_sold_date_sk,ws_ext_sales_price,ws_net_profit] + Filter [ws_web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_web_site_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + WholeStageCodegen (15) + Project [ws_web_site_sk,wr_returned_date_sk,wr_return_amt,wr_net_loss] + BroadcastHashJoin [wr_item_sk,wr_order_number,ws_item_sk,ws_order_number] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (14) + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + Project [ws_item_sk,ws_web_site_sk,ws_order_number] + Filter [ws_item_sk,ws_order_number,ws_web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_order_number,ws_sold_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (17) + Filter [web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] + WholeStageCodegen (43) + HashAggregate [channel,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),id,sum(sales),sum(returns),sum(profit),sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel] #11 + WholeStageCodegen (42) + HashAggregate [channel,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 + WholeStageCodegen (65) + HashAggregate [sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),channel,id,sum(sales),sum(returns),sum(profit),sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange #12 + WholeStageCodegen (64) + HashAggregate [sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/explain.txt new file mode 100644 index 000000000..7e0bfdaf7 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/explain.txt @@ -0,0 +1,311 @@ +== Physical Plan == +TakeOrderedAndProject (39) ++- * Filter (38) + +- * HashAggregate (37) + +- Exchange (36) + +- * HashAggregate (35) + +- * Project (34) + +- * BroadcastHashJoin Inner BuildRight (33) + :- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (15) + : : +- * BroadcastHashJoin Inner BuildRight (14) + : : :- * Project (9) + : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.customer_address (1) + : : : +- BroadcastExchange (7) + : : : +- * Filter (6) + : : : +- * ColumnarToRow (5) + : : : +- CometScan parquet spark_catalog.default.customer (4) + : : +- BroadcastExchange (13) + : : +- * Filter (12) + : : +- * ColumnarToRow (11) + : : +- CometScan parquet spark_catalog.default.store_sales (10) + : +- ReusedExchange (16) + +- BroadcastExchange (32) + +- * Project (31) + +- * BroadcastHashJoin Inner BuildRight (30) + :- * Filter (21) + : +- * ColumnarToRow (20) + : +- CometScan parquet spark_catalog.default.item (19) + +- BroadcastExchange (29) + +- * Filter (28) + +- * HashAggregate (27) + +- Exchange (26) + +- * HashAggregate (25) + +- * Filter (24) + +- * ColumnarToRow (23) + +- CometScan parquet spark_catalog.default.item (22) + + +(1) Scan parquet spark_catalog.default.customer_address +Output [2]: [ca_address_sk#1, ca_state#2] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 7] +Input [2]: [ca_address_sk#1, ca_state#2] + +(3) Filter [codegen id : 7] +Input [2]: [ca_address_sk#1, ca_state#2] +Condition : isnotnull(ca_address_sk#1) + +(4) Scan parquet spark_catalog.default.customer +Output [2]: [c_customer_sk#3, c_current_addr_sk#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_customer_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] + +(6) Filter [codegen id : 1] +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] +Condition : (isnotnull(c_current_addr_sk#4) AND isnotnull(c_customer_sk#3)) + +(7) BroadcastExchange +Input [2]: [c_customer_sk#3, c_current_addr_sk#4] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ca_address_sk#1] +Right keys [1]: [c_current_addr_sk#4] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 7] +Output [2]: [ca_state#2, c_customer_sk#3] +Input [4]: [ca_address_sk#1, ca_state#2, c_customer_sk#3, c_current_addr_sk#4] + +(10) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] + +(12) Filter [codegen id : 2] +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_customer_sk#6) AND isnotnull(ss_item_sk#5)) + +(13) BroadcastExchange +Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [c_customer_sk#3] +Right keys [1]: [ss_customer_sk#6] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 7] +Output [3]: [ca_state#2, ss_item_sk#5, ss_sold_date_sk#7] +Input [5]: [ca_state#2, c_customer_sk#3, ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] + +(16) ReusedExchange [Reuses operator id: 44] +Output [1]: [d_date_sk#9] + +(17) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 7] +Output [2]: [ca_state#2, ss_item_sk#5] +Input [4]: [ca_state#2, ss_item_sk#5, ss_sold_date_sk#7, d_date_sk#9] + +(19) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#10, i_current_price#11, i_category#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), IsNotNull(i_category), IsNotNull(i_item_sk)] +ReadSchema: struct + +(20) ColumnarToRow [codegen id : 6] +Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] + +(21) Filter [codegen id : 6] +Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] +Condition : ((isnotnull(i_current_price#11) AND isnotnull(i_category#12)) AND isnotnull(i_item_sk#10)) + +(22) Scan parquet spark_catalog.default.item +Output [2]: [i_current_price#13, i_category#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 4] +Input [2]: [i_current_price#13, i_category#14] + +(24) Filter [codegen id : 4] +Input [2]: [i_current_price#13, i_category#14] +Condition : isnotnull(i_category#14) + +(25) HashAggregate [codegen id : 4] +Input [2]: [i_current_price#13, i_category#14] +Keys [1]: [i_category#14] +Functions [1]: [partial_avg(UnscaledValue(i_current_price#13))] +Aggregate Attributes [2]: [sum#15, count#16] +Results [3]: [i_category#14, sum#17, count#18] + +(26) Exchange +Input [3]: [i_category#14, sum#17, count#18] +Arguments: hashpartitioning(i_category#14, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 5] +Input [3]: [i_category#14, sum#17, count#18] +Keys [1]: [i_category#14] +Functions [1]: [avg(UnscaledValue(i_current_price#13))] +Aggregate Attributes [1]: [avg(UnscaledValue(i_current_price#13))#19] +Results [2]: [cast((avg(UnscaledValue(i_current_price#13))#19 / 100.0) as decimal(11,6)) AS avg(i_current_price)#20, i_category#14] + +(28) Filter [codegen id : 5] +Input [2]: [avg(i_current_price)#20, i_category#14] +Condition : isnotnull(avg(i_current_price)#20) + +(29) BroadcastExchange +Input [2]: [avg(i_current_price)#20, i_category#14] +Arguments: HashedRelationBroadcastMode(List(input[1, string, true]),false), [plan_id=4] + +(30) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [i_category#12] +Right keys [1]: [i_category#14] +Join type: Inner +Join condition: (cast(i_current_price#11 as decimal(14,7)) > (1.2 * avg(i_current_price)#20)) + +(31) Project [codegen id : 6] +Output [1]: [i_item_sk#10] +Input [5]: [i_item_sk#10, i_current_price#11, i_category#12, avg(i_current_price)#20, i_category#14] + +(32) BroadcastExchange +Input [1]: [i_item_sk#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [ss_item_sk#5] +Right keys [1]: [i_item_sk#10] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 7] +Output [1]: [ca_state#2] +Input [3]: [ca_state#2, ss_item_sk#5, i_item_sk#10] + +(35) HashAggregate [codegen id : 7] +Input [1]: [ca_state#2] +Keys [1]: [ca_state#2] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#21] +Results [2]: [ca_state#2, count#22] + +(36) Exchange +Input [2]: [ca_state#2, count#22] +Arguments: hashpartitioning(ca_state#2, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(37) HashAggregate [codegen id : 8] +Input [2]: [ca_state#2, count#22] +Keys [1]: [ca_state#2] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#23] +Results [2]: [ca_state#2 AS state#24, count(1)#23 AS cnt#25] + +(38) Filter [codegen id : 8] +Input [2]: [state#24, cnt#25] +Condition : (cnt#25 >= 10) + +(39) TakeOrderedAndProject +Input [2]: [state#24, cnt#25] +Arguments: 100, [cnt#25 ASC NULLS FIRST, state#24 ASC NULLS FIRST], [state#24, cnt#25] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (44) ++- * Project (43) + +- * Filter (42) + +- * ColumnarToRow (41) + +- CometScan parquet spark_catalog.default.date_dim (40) + + +(40) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#9, d_month_seq#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), EqualTo(d_month_seq,ScalarSubquery#27), IsNotNull(d_date_sk)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#9, d_month_seq#26] + +(42) Filter [codegen id : 1] +Input [2]: [d_date_sk#9, d_month_seq#26] +Condition : ((isnotnull(d_month_seq#26) AND (d_month_seq#26 = ReusedSubquery Subquery scalar-subquery#27, [id=#28])) AND isnotnull(d_date_sk#9)) + +(43) Project [codegen id : 1] +Output [1]: [d_date_sk#9] +Input [2]: [d_date_sk#9, d_month_seq#26] + +(44) BroadcastExchange +Input [1]: [d_date_sk#9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + +Subquery:2 Hosting operator id = 42 Hosting Expression = ReusedSubquery Subquery scalar-subquery#27, [id=#28] + +Subquery:3 Hosting operator id = 40 Hosting Expression = Subquery scalar-subquery#27, [id=#28] +* HashAggregate (51) ++- Exchange (50) + +- * HashAggregate (49) + +- * Project (48) + +- * Filter (47) + +- * ColumnarToRow (46) + +- CometScan parquet spark_catalog.default.date_dim (45) + + +(45) Scan parquet spark_catalog.default.date_dim +Output [3]: [d_month_seq#29, d_year#30, d_moy#31] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,1)] +ReadSchema: struct + +(46) ColumnarToRow [codegen id : 1] +Input [3]: [d_month_seq#29, d_year#30, d_moy#31] + +(47) Filter [codegen id : 1] +Input [3]: [d_month_seq#29, d_year#30, d_moy#31] +Condition : (((isnotnull(d_year#30) AND isnotnull(d_moy#31)) AND (d_year#30 = 2000)) AND (d_moy#31 = 1)) + +(48) Project [codegen id : 1] +Output [1]: [d_month_seq#29] +Input [3]: [d_month_seq#29, d_year#30, d_moy#31] + +(49) HashAggregate [codegen id : 1] +Input [1]: [d_month_seq#29] +Keys [1]: [d_month_seq#29] +Functions: [] +Aggregate Attributes: [] +Results [1]: [d_month_seq#29] + +(50) Exchange +Input [1]: [d_month_seq#29] +Arguments: hashpartitioning(d_month_seq#29, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(51) HashAggregate [codegen id : 2] +Input [1]: [d_month_seq#29] +Keys [1]: [d_month_seq#29] +Functions: [] +Aggregate Attributes: [] +Results [1]: [d_month_seq#29] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/simplified.txt new file mode 100644 index 000000000..7078a77e4 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/simplified.txt @@ -0,0 +1,79 @@ +TakeOrderedAndProject [cnt,state] + WholeStageCodegen (8) + Filter [cnt] + HashAggregate [ca_state,count] [count(1),state,cnt,count] + InputAdapter + Exchange [ca_state] #1 + WholeStageCodegen (7) + HashAggregate [ca_state] [count,count] + Project [ca_state] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ca_state,ss_item_sk] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ca_state,ss_item_sk,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Project [ca_state,c_customer_sk] + BroadcastHashJoin [ca_address_sk,c_current_addr_sk] + Filter [ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [c_current_addr_sk,c_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] + InputAdapter + BroadcastExchange #3 + WholeStageCodegen (2) + Filter [ss_customer_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ReusedSubquery [d_month_seq] #2 + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + Subquery #2 + WholeStageCodegen (2) + HashAggregate [d_month_seq] + InputAdapter + Exchange [d_month_seq] #5 + WholeStageCodegen (1) + HashAggregate [d_month_seq] + Project [d_month_seq] + Filter [d_year,d_moy] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Project [i_item_sk] + BroadcastHashJoin [i_category,i_category,i_current_price,avg(i_current_price)] + Filter [i_current_price,i_category,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_category] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (5) + Filter [avg(i_current_price)] + HashAggregate [i_category,sum,count] [avg(UnscaledValue(i_current_price)),avg(i_current_price),sum,count] + InputAdapter + Exchange [i_category] #8 + WholeStageCodegen (4) + HashAggregate [i_category,i_current_price] [sum,count,sum,count] + Filter [i_category] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_current_price,i_category] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/explain.txt new file mode 100644 index 000000000..d2d493a6d --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/explain.txt @@ -0,0 +1,1074 @@ +== Physical Plan == +* Sort (183) ++- Exchange (182) + +- * Project (181) + +- * SortMergeJoin Inner (180) + :- * Sort (111) + : +- Exchange (110) + : +- * HashAggregate (109) + : +- * HashAggregate (108) + : +- * Project (107) + : +- * BroadcastHashJoin Inner BuildRight (106) + : :- * Project (100) + : : +- * BroadcastHashJoin Inner BuildRight (99) + : : :- * Project (97) + : : : +- * BroadcastHashJoin Inner BuildRight (96) + : : : :- * Project (91) + : : : : +- * BroadcastHashJoin Inner BuildRight (90) + : : : : :- * Project (88) + : : : : : +- * BroadcastHashJoin Inner BuildRight (87) + : : : : : :- * Project (82) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (81) + : : : : : : :- * Project (79) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (78) + : : : : : : : :- * Project (73) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (72) + : : : : : : : : :- * Project (67) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (66) + : : : : : : : : : :- * Project (64) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (63) + : : : : : : : : : : :- * Project (58) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (57) + : : : : : : : : : : : :- * Project (55) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : : : : : : : : : : :- * Project (49) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (48) + : : : : : : : : : : : : : :- * Project (43) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (42) + : : : : : : : : : : : : : : :- * Project (37) + : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (36) + : : : : : : : : : : : : : : : :- * Project (34) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (33) + : : : : : : : : : : : : : : : : :- * Sort (12) + : : : : : : : : : : : : : : : : : +- Exchange (11) + : : : : : : : : : : : : : : : : : +- * Project (10) + : : : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildLeft (9) + : : : : : : : : : : : : : : : : : :- BroadcastExchange (4) + : : : : : : : : : : : : : : : : : : +- * Filter (3) + : : : : : : : : : : : : : : : : : : +- * ColumnarToRow (2) + : : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : : : : : : : : : : : : +- * Project (8) + : : : : : : : : : : : : : : : : : +- * Filter (7) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (6) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (5) + : : : : : : : : : : : : : : : : +- * Sort (32) + : : : : : : : : : : : : : : : : +- * Project (31) + : : : : : : : : : : : : : : : : +- * Filter (30) + : : : : : : : : : : : : : : : : +- * HashAggregate (29) + : : : : : : : : : : : : : : : : +- Exchange (28) + : : : : : : : : : : : : : : : : +- * HashAggregate (27) + : : : : : : : : : : : : : : : : +- * Project (26) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (25) + : : : : : : : : : : : : : : : : :- * Sort (18) + : : : : : : : : : : : : : : : : : +- Exchange (17) + : : : : : : : : : : : : : : : : : +- * Project (16) + : : : : : : : : : : : : : : : : : +- * Filter (15) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (14) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) + : : : : : : : : : : : : : : : : +- * Sort (24) + : : : : : : : : : : : : : : : : +- Exchange (23) + : : : : : : : : : : : : : : : : +- * Project (22) + : : : : : : : : : : : : : : : : +- * Filter (21) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (20) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (19) + : : : : : : : : : : : : : : : +- ReusedExchange (35) + : : : : : : : : : : : : : : +- BroadcastExchange (41) + : : : : : : : : : : : : : : +- * Filter (40) + : : : : : : : : : : : : : : +- * ColumnarToRow (39) + : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store (38) + : : : : : : : : : : : : : +- BroadcastExchange (47) + : : : : : : : : : : : : : +- * Filter (46) + : : : : : : : : : : : : : +- * ColumnarToRow (45) + : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer (44) + : : : : : : : : : : : : +- BroadcastExchange (53) + : : : : : : : : : : : : +- * Filter (52) + : : : : : : : : : : : : +- * ColumnarToRow (51) + : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.date_dim (50) + : : : : : : : : : : : +- ReusedExchange (56) + : : : : : : : : : : +- BroadcastExchange (62) + : : : : : : : : : : +- * Filter (61) + : : : : : : : : : : +- * ColumnarToRow (60) + : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (59) + : : : : : : : : : +- ReusedExchange (65) + : : : : : : : : +- BroadcastExchange (71) + : : : : : : : : +- * Filter (70) + : : : : : : : : +- * ColumnarToRow (69) + : : : : : : : : +- CometScan parquet spark_catalog.default.promotion (68) + : : : : : : : +- BroadcastExchange (77) + : : : : : : : +- * Filter (76) + : : : : : : : +- * ColumnarToRow (75) + : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (74) + : : : : : : +- ReusedExchange (80) + : : : : : +- BroadcastExchange (86) + : : : : : +- * Filter (85) + : : : : : +- * ColumnarToRow (84) + : : : : : +- CometScan parquet spark_catalog.default.customer_address (83) + : : : : +- ReusedExchange (89) + : : : +- BroadcastExchange (95) + : : : +- * Filter (94) + : : : +- * ColumnarToRow (93) + : : : +- CometScan parquet spark_catalog.default.income_band (92) + : : +- ReusedExchange (98) + : +- BroadcastExchange (105) + : +- * Project (104) + : +- * Filter (103) + : +- * ColumnarToRow (102) + : +- CometScan parquet spark_catalog.default.item (101) + +- * Sort (179) + +- Exchange (178) + +- * HashAggregate (177) + +- * HashAggregate (176) + +- * Project (175) + +- * BroadcastHashJoin Inner BuildRight (174) + :- * Project (172) + : +- * BroadcastHashJoin Inner BuildRight (171) + : :- * Project (169) + : : +- * BroadcastHashJoin Inner BuildRight (168) + : : :- * Project (166) + : : : +- * BroadcastHashJoin Inner BuildRight (165) + : : : :- * Project (163) + : : : : +- * BroadcastHashJoin Inner BuildRight (162) + : : : : :- * Project (160) + : : : : : +- * BroadcastHashJoin Inner BuildRight (159) + : : : : : :- * Project (157) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (156) + : : : : : : :- * Project (154) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (153) + : : : : : : : :- * Project (151) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (150) + : : : : : : : : :- * Project (148) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (147) + : : : : : : : : : :- * Project (145) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (144) + : : : : : : : : : : :- * Project (142) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (141) + : : : : : : : : : : : :- * Project (139) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (138) + : : : : : : : : : : : : :- * Project (136) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (135) + : : : : : : : : : : : : : :- * Project (133) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (132) + : : : : : : : : : : : : : : :- * Project (130) + : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (129) + : : : : : : : : : : : : : : : :- * Sort (123) + : : : : : : : : : : : : : : : : +- Exchange (122) + : : : : : : : : : : : : : : : : +- * Project (121) + : : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildLeft (120) + : : : : : : : : : : : : : : : : :- BroadcastExchange (115) + : : : : : : : : : : : : : : : : : +- * Filter (114) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (113) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (112) + : : : : : : : : : : : : : : : : +- * Project (119) + : : : : : : : : : : : : : : : : +- * Filter (118) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (117) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (116) + : : : : : : : : : : : : : : : +- * Sort (128) + : : : : : : : : : : : : : : : +- * Project (127) + : : : : : : : : : : : : : : : +- * Filter (126) + : : : : : : : : : : : : : : : +- * HashAggregate (125) + : : : : : : : : : : : : : : : +- ReusedExchange (124) + : : : : : : : : : : : : : : +- ReusedExchange (131) + : : : : : : : : : : : : : +- ReusedExchange (134) + : : : : : : : : : : : : +- ReusedExchange (137) + : : : : : : : : : : : +- ReusedExchange (140) + : : : : : : : : : : +- ReusedExchange (143) + : : : : : : : : : +- ReusedExchange (146) + : : : : : : : : +- ReusedExchange (149) + : : : : : : : +- ReusedExchange (152) + : : : : : : +- ReusedExchange (155) + : : : : : +- ReusedExchange (158) + : : : : +- ReusedExchange (161) + : : : +- ReusedExchange (164) + : : +- ReusedExchange (167) + : +- ReusedExchange (170) + +- ReusedExchange (173) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_sold_date_sk#12 IN dynamicpruning#13)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] + +(3) Filter [codegen id : 1] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Condition : (((((((isnotnull(ss_item_sk#1) AND isnotnull(ss_ticket_number#8)) AND isnotnull(ss_store_sk#6)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_cdemo_sk#3)) AND isnotnull(ss_promo_sk#7)) AND isnotnull(ss_hdemo_sk#4)) AND isnotnull(ss_addr_sk#5)) + +(4) BroadcastExchange +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[7, int, false] as bigint) & 4294967295))),false), [plan_id=1] + +(5) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(6) ColumnarToRow +Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] + +(7) Filter +Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Condition : (isnotnull(sr_item_sk#14) AND isnotnull(sr_ticket_number#15)) + +(8) Project +Output [2]: [sr_item_sk#14, sr_ticket_number#15] +Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] + +(9) BroadcastHashJoin [codegen id : 2] +Left keys [2]: [ss_item_sk#1, ss_ticket_number#8] +Right keys [2]: [sr_item_sk#14, sr_ticket_number#15] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 2] +Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, sr_item_sk#14, sr_ticket_number#15] + +(11) Exchange +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(12) Sort [codegen id : 3] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Arguments: [ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(13) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_sales] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_order_number)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 4] +Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] + +(15) Filter [codegen id : 4] +Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_item_sk#17) AND isnotnull(cs_order_number#18)) + +(16) Project [codegen id : 4] +Output [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] + +(17) Exchange +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +Arguments: hashpartitioning(cs_item_sk#17, cs_order_number#18, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(18) Sort [codegen id : 5] +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +Arguments: [cs_item_sk#17 ASC NULLS FIRST, cs_order_number#18 ASC NULLS FIRST], false, 0 + +(19) Scan parquet spark_catalog.default.catalog_returns +Output [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(20) ColumnarToRow [codegen id : 6] +Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] + +(21) Filter [codegen id : 6] +Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Condition : (isnotnull(cr_item_sk#21) AND isnotnull(cr_order_number#22)) + +(22) Project [codegen id : 6] +Output [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] + +(23) Exchange +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Arguments: hashpartitioning(cr_item_sk#21, cr_order_number#22, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(24) Sort [codegen id : 7] +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Arguments: [cr_item_sk#21 ASC NULLS FIRST, cr_order_number#22 ASC NULLS FIRST], false, 0 + +(25) SortMergeJoin [codegen id : 8] +Left keys [2]: [cs_item_sk#17, cs_order_number#18] +Right keys [2]: [cr_item_sk#21, cr_order_number#22] +Join type: Inner +Join condition: None + +(26) Project [codegen id : 8] +Output [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Input [8]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] + +(27) HashAggregate [codegen id : 8] +Input [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +Keys [1]: [cs_item_sk#17] +Functions [2]: [partial_sum(UnscaledValue(cs_ext_list_price#19)), partial_sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] +Aggregate Attributes [3]: [sum#27, sum#28, isEmpty#29] +Results [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] + +(28) Exchange +Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] +Arguments: hashpartitioning(cs_item_sk#17, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(29) HashAggregate [codegen id : 9] +Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] +Keys [1]: [cs_item_sk#17] +Functions [2]: [sum(UnscaledValue(cs_ext_list_price#19)), sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#19))#33, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34] +Results [3]: [cs_item_sk#17, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#19))#33,17,2) AS sale#35, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34 AS refund#36] + +(30) Filter [codegen id : 9] +Input [3]: [cs_item_sk#17, sale#35, refund#36] +Condition : ((isnotnull(sale#35) AND isnotnull(refund#36)) AND (cast(sale#35 as decimal(21,2)) > (2 * refund#36))) + +(31) Project [codegen id : 9] +Output [1]: [cs_item_sk#17] +Input [3]: [cs_item_sk#17, sale#35, refund#36] + +(32) Sort [codegen id : 9] +Input [1]: [cs_item_sk#17] +Arguments: [cs_item_sk#17 ASC NULLS FIRST], false, 0 + +(33) SortMergeJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [cs_item_sk#17] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 25] +Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, cs_item_sk#17] + +(35) ReusedExchange [Reuses operator id: 187] +Output [2]: [d_date_sk#37, d_year#38] + +(36) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_sold_date_sk#12] +Right keys [1]: [d_date_sk#37] +Join type: Inner +Join condition: None + +(37) Project [codegen id : 25] +Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38] +Input [13]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, d_date_sk#37, d_year#38] + +(38) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_zip)] +ReadSchema: struct + +(39) ColumnarToRow [codegen id : 11] +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] + +(40) Filter [codegen id : 11] +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Condition : ((isnotnull(s_store_sk#39) AND isnotnull(s_store_name#40)) AND isnotnull(s_zip#41)) + +(41) BroadcastExchange +Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(42) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_store_sk#6] +Right keys [1]: [s_store_sk#39] +Join type: Inner +Join condition: None + +(43) Project [codegen id : 25] +Output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41] +Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_sk#39, s_store_name#40, s_zip#41] + +(44) Scan parquet spark_catalog.default.customer +Output [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_first_sales_date_sk), IsNotNull(c_first_shipto_date_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk), IsNotNull(c_current_addr_sk)] +ReadSchema: struct + +(45) ColumnarToRow [codegen id : 12] +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] + +(46) Filter [codegen id : 12] +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Condition : (((((isnotnull(c_customer_sk#42) AND isnotnull(c_first_sales_date_sk#47)) AND isnotnull(c_first_shipto_date_sk#46)) AND isnotnull(c_current_cdemo_sk#43)) AND isnotnull(c_current_hdemo_sk#44)) AND isnotnull(c_current_addr_sk#45)) + +(47) BroadcastExchange +Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(48) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_customer_sk#2] +Right keys [1]: [c_customer_sk#42] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 25] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Input [18]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] + +(50) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#48, d_year#49] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date_sk)] +ReadSchema: struct + +(51) ColumnarToRow [codegen id : 13] +Input [2]: [d_date_sk#48, d_year#49] + +(52) Filter [codegen id : 13] +Input [2]: [d_date_sk#48, d_year#49] +Condition : isnotnull(d_date_sk#48) + +(53) BroadcastExchange +Input [2]: [d_date_sk#48, d_year#49] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(54) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [c_first_sales_date_sk#47] +Right keys [1]: [d_date_sk#48] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 25] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47, d_date_sk#48, d_year#49] + +(56) ReusedExchange [Reuses operator id: 53] +Output [2]: [d_date_sk#50, d_year#51] + +(57) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [c_first_shipto_date_sk#46] +Right keys [1]: [d_date_sk#50] +Join type: Inner +Join condition: None + +(58) Project [codegen id : 25] +Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49, d_date_sk#50, d_year#51] + +(59) Scan parquet spark_catalog.default.customer_demographics +Output [2]: [cd_demo_sk#52, cd_marital_status#53] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status)] +ReadSchema: struct + +(60) ColumnarToRow [codegen id : 15] +Input [2]: [cd_demo_sk#52, cd_marital_status#53] + +(61) Filter [codegen id : 15] +Input [2]: [cd_demo_sk#52, cd_marital_status#53] +Condition : (isnotnull(cd_demo_sk#52) AND isnotnull(cd_marital_status#53)) + +(62) BroadcastExchange +Input [2]: [cd_demo_sk#52, cd_marital_status#53] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(63) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_cdemo_sk#3] +Right keys [1]: [cd_demo_sk#52] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 25] +Output [16]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53] +Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_demo_sk#52, cd_marital_status#53] + +(65) ReusedExchange [Reuses operator id: 62] +Output [2]: [cd_demo_sk#54, cd_marital_status#55] + +(66) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [c_current_cdemo_sk#43] +Right keys [1]: [cd_demo_sk#54] +Join type: Inner +Join condition: NOT (cd_marital_status#53 = cd_marital_status#55) + +(67) Project [codegen id : 25] +Output [14]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [18]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53, cd_demo_sk#54, cd_marital_status#55] + +(68) Scan parquet spark_catalog.default.promotion +Output [1]: [p_promo_sk#56] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_promo_sk)] +ReadSchema: struct + +(69) ColumnarToRow [codegen id : 17] +Input [1]: [p_promo_sk#56] + +(70) Filter [codegen id : 17] +Input [1]: [p_promo_sk#56] +Condition : isnotnull(p_promo_sk#56) + +(71) BroadcastExchange +Input [1]: [p_promo_sk#56] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] + +(72) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_promo_sk#7] +Right keys [1]: [p_promo_sk#56] +Join type: Inner +Join condition: None + +(73) Project [codegen id : 25] +Output [13]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] +Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, p_promo_sk#56] + +(74) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_demo_sk), IsNotNull(hd_income_band_sk)] +ReadSchema: struct + +(75) ColumnarToRow [codegen id : 18] +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] + +(76) Filter [codegen id : 18] +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Condition : (isnotnull(hd_demo_sk#57) AND isnotnull(hd_income_band_sk#58)) + +(77) BroadcastExchange +Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=11] + +(78) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_hdemo_sk#4] +Right keys [1]: [hd_demo_sk#57] +Join type: Inner +Join condition: None + +(79) Project [codegen id : 25] +Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58] +Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_demo_sk#57, hd_income_band_sk#58] + +(80) ReusedExchange [Reuses operator id: 77] +Output [2]: [hd_demo_sk#59, hd_income_band_sk#60] + +(81) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [c_current_hdemo_sk#44] +Right keys [1]: [hd_demo_sk#59] +Join type: Inner +Join condition: None + +(82) Project [codegen id : 25] +Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60] +Input [15]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_demo_sk#59, hd_income_band_sk#60] + +(83) Scan parquet spark_catalog.default.customer_address +Output [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_address] +PushedFilters: [IsNotNull(ca_address_sk)] +ReadSchema: struct + +(84) ColumnarToRow [codegen id : 20] +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] + +(85) Filter [codegen id : 20] +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Condition : isnotnull(ca_address_sk#61) + +(86) BroadcastExchange +Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +(87) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_addr_sk#5] +Right keys [1]: [ca_address_sk#61] +Join type: Inner +Join condition: None + +(88) Project [codegen id : 25] +Output [16]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Input [18]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] + +(89) ReusedExchange [Reuses operator id: 86] +Output [5]: [ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] + +(90) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [c_current_addr_sk#45] +Right keys [1]: [ca_address_sk#66] +Join type: Inner +Join condition: None + +(91) Project [codegen id : 25] +Output [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [21]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] + +(92) Scan parquet spark_catalog.default.income_band +Output [1]: [ib_income_band_sk#71] +Batched: true +Location [not included in comparison]/{warehouse_dir}/income_band] +PushedFilters: [IsNotNull(ib_income_band_sk)] +ReadSchema: struct + +(93) ColumnarToRow [codegen id : 22] +Input [1]: [ib_income_band_sk#71] + +(94) Filter [codegen id : 22] +Input [1]: [ib_income_band_sk#71] +Condition : isnotnull(ib_income_band_sk#71) + +(95) BroadcastExchange +Input [1]: [ib_income_band_sk#71] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +(96) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [hd_income_band_sk#58] +Right keys [1]: [ib_income_band_sk#71] +Join type: Inner +Join condition: None + +(97) Project [codegen id : 25] +Output [18]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [20]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#71] + +(98) ReusedExchange [Reuses operator id: 95] +Output [1]: [ib_income_band_sk#72] + +(99) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [hd_income_band_sk#60] +Right keys [1]: [ib_income_band_sk#72] +Join type: Inner +Join condition: None + +(100) Project [codegen id : 25] +Output [17]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] +Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#72] + +(101) Scan parquet spark_catalog.default.item +Output [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), In(i_color, [burlywood ,floral ,indian ,medium ,purple ,spring ]), GreaterThanOrEqual(i_current_price,64.00), LessThanOrEqual(i_current_price,74.00), GreaterThanOrEqual(i_current_price,65.00), LessThanOrEqual(i_current_price,79.00), IsNotNull(i_item_sk)] +ReadSchema: struct + +(102) ColumnarToRow [codegen id : 24] +Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] + +(103) Filter [codegen id : 24] +Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Condition : ((((((isnotnull(i_current_price#74) AND i_color#75 IN (purple ,burlywood ,indian ,spring ,floral ,medium )) AND (i_current_price#74 >= 64.00)) AND (i_current_price#74 <= 74.00)) AND (i_current_price#74 >= 65.00)) AND (i_current_price#74 <= 79.00)) AND isnotnull(i_item_sk#73)) + +(104) Project [codegen id : 24] +Output [2]: [i_item_sk#73, i_product_name#76] +Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] + +(105) BroadcastExchange +Input [2]: [i_item_sk#73, i_product_name#76] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] + +(106) BroadcastHashJoin [codegen id : 25] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#73] +Join type: Inner +Join condition: None + +(107) Project [codegen id : 25] +Output [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] +Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] + +(108) HashAggregate [codegen id : 25] +Input [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] +Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] +Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#9)), partial_sum(UnscaledValue(ss_list_price#10)), partial_sum(UnscaledValue(ss_coupon_amt#11))] +Aggregate Attributes [4]: [count#77, sum#78, sum#79, sum#80] +Results [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] + +(109) HashAggregate [codegen id : 25] +Input [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] +Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] +Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#9)), sum(UnscaledValue(ss_list_price#10)), sum(UnscaledValue(ss_coupon_amt#11))] +Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#9))#86, sum(UnscaledValue(ss_list_price#10))#87, sum(UnscaledValue(ss_coupon_amt#11))#88] +Results [17]: [i_product_name#76 AS product_name#89, i_item_sk#73 AS item_sk#90, s_store_name#40 AS store_name#91, s_zip#41 AS store_zip#92, ca_street_number#62 AS b_street_number#93, ca_street_name#63 AS b_streen_name#94, ca_city#64 AS b_city#95, ca_zip#65 AS b_zip#96, ca_street_number#67 AS c_street_number#97, ca_street_name#68 AS c_street_name#98, ca_city#69 AS c_city#99, ca_zip#70 AS c_zip#100, d_year#38 AS syear#101, count(1)#85 AS cnt#102, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#9))#86,17,2) AS s1#103, MakeDecimal(sum(UnscaledValue(ss_list_price#10))#87,17,2) AS s2#104, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#11))#88,17,2) AS s3#105] + +(110) Exchange +Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] +Arguments: hashpartitioning(item_sk#90, store_name#91, store_zip#92, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(111) Sort [codegen id : 26] +Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] +Arguments: [item_sk#90 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, store_zip#92 ASC NULLS FIRST], false, 0 + +(112) Scan parquet spark_catalog.default.store_sales +Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#117), dynamicpruningexpression(ss_sold_date_sk#117 IN dynamicpruning#118)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] +ReadSchema: struct + +(113) ColumnarToRow [codegen id : 27] +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] + +(114) Filter [codegen id : 27] +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Condition : (((((((isnotnull(ss_item_sk#106) AND isnotnull(ss_ticket_number#113)) AND isnotnull(ss_store_sk#111)) AND isnotnull(ss_customer_sk#107)) AND isnotnull(ss_cdemo_sk#108)) AND isnotnull(ss_promo_sk#112)) AND isnotnull(ss_hdemo_sk#109)) AND isnotnull(ss_addr_sk#110)) + +(115) BroadcastExchange +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[7, int, false] as bigint) & 4294967295))),false), [plan_id=16] + +(116) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(117) ColumnarToRow +Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] + +(118) Filter +Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Condition : (isnotnull(sr_item_sk#119) AND isnotnull(sr_ticket_number#120)) + +(119) Project +Output [2]: [sr_item_sk#119, sr_ticket_number#120] +Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] + +(120) BroadcastHashJoin [codegen id : 28] +Left keys [2]: [ss_item_sk#106, ss_ticket_number#113] +Right keys [2]: [sr_item_sk#119, sr_ticket_number#120] +Join type: Inner +Join condition: None + +(121) Project [codegen id : 28] +Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, sr_item_sk#119, sr_ticket_number#120] + +(122) Exchange +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: hashpartitioning(ss_item_sk#106, 5), ENSURE_REQUIREMENTS, [plan_id=17] + +(123) Sort [codegen id : 29] +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Arguments: [ss_item_sk#106 ASC NULLS FIRST], false, 0 + +(124) ReusedExchange [Reuses operator id: 28] +Output [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] + +(125) HashAggregate [codegen id : 35] +Input [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] +Keys [1]: [cs_item_sk#122] +Functions [2]: [sum(UnscaledValue(cs_ext_list_price#126)), sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#126))#33, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34] +Results [3]: [cs_item_sk#122, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#126))#33,17,2) AS sale#130, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34 AS refund#131] + +(126) Filter [codegen id : 35] +Input [3]: [cs_item_sk#122, sale#130, refund#131] +Condition : ((isnotnull(sale#130) AND isnotnull(refund#131)) AND (cast(sale#130 as decimal(21,2)) > (2 * refund#131))) + +(127) Project [codegen id : 35] +Output [1]: [cs_item_sk#122] +Input [3]: [cs_item_sk#122, sale#130, refund#131] + +(128) Sort [codegen id : 35] +Input [1]: [cs_item_sk#122] +Arguments: [cs_item_sk#122 ASC NULLS FIRST], false, 0 + +(129) SortMergeJoin [codegen id : 51] +Left keys [1]: [ss_item_sk#106] +Right keys [1]: [cs_item_sk#122] +Join type: Inner +Join condition: None + +(130) Project [codegen id : 51] +Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, cs_item_sk#122] + +(131) ReusedExchange [Reuses operator id: 191] +Output [2]: [d_date_sk#132, d_year#133] + +(132) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_sold_date_sk#117] +Right keys [1]: [d_date_sk#132] +Join type: Inner +Join condition: None + +(133) Project [codegen id : 51] +Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133] +Input [13]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, d_date_sk#132, d_year#133] + +(134) ReusedExchange [Reuses operator id: 41] +Output [3]: [s_store_sk#134, s_store_name#135, s_zip#136] + +(135) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_store_sk#111] +Right keys [1]: [s_store_sk#134] +Join type: Inner +Join condition: None + +(136) Project [codegen id : 51] +Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136] +Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_sk#134, s_store_name#135, s_zip#136] + +(137) ReusedExchange [Reuses operator id: 47] +Output [6]: [c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] + +(138) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_customer_sk#107] +Right keys [1]: [c_customer_sk#137] +Join type: Inner +Join condition: None + +(139) Project [codegen id : 51] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] +Input [18]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] + +(140) ReusedExchange [Reuses operator id: 53] +Output [2]: [d_date_sk#143, d_year#144] + +(141) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [c_first_sales_date_sk#142] +Right keys [1]: [d_date_sk#143] +Join type: Inner +Join condition: None + +(142) Project [codegen id : 51] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142, d_date_sk#143, d_year#144] + +(143) ReusedExchange [Reuses operator id: 53] +Output [2]: [d_date_sk#145, d_year#146] + +(144) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [c_first_shipto_date_sk#141] +Right keys [1]: [d_date_sk#145] +Join type: Inner +Join condition: None + +(145) Project [codegen id : 51] +Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144, d_date_sk#145, d_year#146] + +(146) ReusedExchange [Reuses operator id: 62] +Output [2]: [cd_demo_sk#147, cd_marital_status#148] + +(147) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_cdemo_sk#108] +Right keys [1]: [cd_demo_sk#147] +Join type: Inner +Join condition: None + +(148) Project [codegen id : 51] +Output [16]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148] +Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_demo_sk#147, cd_marital_status#148] + +(149) ReusedExchange [Reuses operator id: 62] +Output [2]: [cd_demo_sk#149, cd_marital_status#150] + +(150) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [c_current_cdemo_sk#138] +Right keys [1]: [cd_demo_sk#149] +Join type: Inner +Join condition: NOT (cd_marital_status#148 = cd_marital_status#150) + +(151) Project [codegen id : 51] +Output [14]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [18]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148, cd_demo_sk#149, cd_marital_status#150] + +(152) ReusedExchange [Reuses operator id: 71] +Output [1]: [p_promo_sk#151] + +(153) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_promo_sk#112] +Right keys [1]: [p_promo_sk#151] +Join type: Inner +Join condition: None + +(154) Project [codegen id : 51] +Output [13]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] +Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, p_promo_sk#151] + +(155) ReusedExchange [Reuses operator id: 77] +Output [2]: [hd_demo_sk#152, hd_income_band_sk#153] + +(156) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_hdemo_sk#109] +Right keys [1]: [hd_demo_sk#152] +Join type: Inner +Join condition: None + +(157) Project [codegen id : 51] +Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153] +Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_demo_sk#152, hd_income_band_sk#153] + +(158) ReusedExchange [Reuses operator id: 77] +Output [2]: [hd_demo_sk#154, hd_income_band_sk#155] + +(159) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [c_current_hdemo_sk#139] +Right keys [1]: [hd_demo_sk#154] +Join type: Inner +Join condition: None + +(160) Project [codegen id : 51] +Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155] +Input [15]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_demo_sk#154, hd_income_band_sk#155] + +(161) ReusedExchange [Reuses operator id: 86] +Output [5]: [ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] + +(162) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_addr_sk#110] +Right keys [1]: [ca_address_sk#156] +Join type: Inner +Join condition: None + +(163) Project [codegen id : 51] +Output [16]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] +Input [18]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] + +(164) ReusedExchange [Reuses operator id: 86] +Output [5]: [ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] + +(165) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [c_current_addr_sk#140] +Right keys [1]: [ca_address_sk#161] +Join type: Inner +Join condition: None + +(166) Project [codegen id : 51] +Output [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [21]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] + +(167) ReusedExchange [Reuses operator id: 95] +Output [1]: [ib_income_band_sk#166] + +(168) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [hd_income_band_sk#153] +Right keys [1]: [ib_income_band_sk#166] +Join type: Inner +Join condition: None + +(169) Project [codegen id : 51] +Output [18]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [20]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#166] + +(170) ReusedExchange [Reuses operator id: 95] +Output [1]: [ib_income_band_sk#167] + +(171) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [hd_income_band_sk#155] +Right keys [1]: [ib_income_band_sk#167] +Join type: Inner +Join condition: None + +(172) Project [codegen id : 51] +Output [17]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] +Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#167] + +(173) ReusedExchange [Reuses operator id: 105] +Output [2]: [i_item_sk#168, i_product_name#169] + +(174) BroadcastHashJoin [codegen id : 51] +Left keys [1]: [ss_item_sk#106] +Right keys [1]: [i_item_sk#168] +Join type: Inner +Join condition: None + +(175) Project [codegen id : 51] +Output [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] +Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] + +(176) HashAggregate [codegen id : 51] +Input [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] +Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] +Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#114)), partial_sum(UnscaledValue(ss_list_price#115)), partial_sum(UnscaledValue(ss_coupon_amt#116))] +Aggregate Attributes [4]: [count#77, sum#170, sum#171, sum#172] +Results [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] + +(177) HashAggregate [codegen id : 51] +Input [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] +Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] +Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#114)), sum(UnscaledValue(ss_list_price#115)), sum(UnscaledValue(ss_coupon_amt#116))] +Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#114))#86, sum(UnscaledValue(ss_list_price#115))#87, sum(UnscaledValue(ss_coupon_amt#116))#88] +Results [8]: [i_item_sk#168 AS item_sk#176, s_store_name#135 AS store_name#177, s_zip#136 AS store_zip#178, d_year#133 AS syear#179, count(1)#85 AS cnt#180, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#114))#86,17,2) AS s1#181, MakeDecimal(sum(UnscaledValue(ss_list_price#115))#87,17,2) AS s2#182, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#116))#88,17,2) AS s3#183] + +(178) Exchange +Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] +Arguments: hashpartitioning(item_sk#176, store_name#177, store_zip#178, 5), ENSURE_REQUIREMENTS, [plan_id=18] + +(179) Sort [codegen id : 52] +Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] +Arguments: [item_sk#176 ASC NULLS FIRST, store_name#177 ASC NULLS FIRST, store_zip#178 ASC NULLS FIRST], false, 0 + +(180) SortMergeJoin [codegen id : 53] +Left keys [3]: [item_sk#90, store_name#91, store_zip#92] +Right keys [3]: [item_sk#176, store_name#177, store_zip#178] +Join type: Inner +Join condition: (cnt#180 <= cnt#102) + +(181) Project [codegen id : 53] +Output [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Input [25]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] + +(182) Exchange +Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Arguments: rangepartitioning(product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, s1#103 ASC NULLS FIRST, s1#181 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=19] + +(183) Sort [codegen id : 54] +Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] +Arguments: [product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, s1#103 ASC NULLS FIRST, s1#181 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 +BroadcastExchange (187) ++- * Filter (186) + +- * ColumnarToRow (185) + +- CometScan parquet spark_catalog.default.date_dim (184) + + +(184) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#37, d_year#38] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk)] +ReadSchema: struct + +(185) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#37, d_year#38] + +(186) Filter [codegen id : 1] +Input [2]: [d_date_sk#37, d_year#38] +Condition : ((isnotnull(d_year#38) AND (d_year#38 = 1999)) AND isnotnull(d_date_sk#37)) + +(187) BroadcastExchange +Input [2]: [d_date_sk#37, d_year#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=20] + +Subquery:2 Hosting operator id = 112 Hosting Expression = ss_sold_date_sk#117 IN dynamicpruning#118 +BroadcastExchange (191) ++- * Filter (190) + +- * ColumnarToRow (189) + +- CometScan parquet spark_catalog.default.date_dim (188) + + +(188) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#132, d_year#133] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(189) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#132, d_year#133] + +(190) Filter [codegen id : 1] +Input [2]: [d_date_sk#132, d_year#133] +Condition : ((isnotnull(d_year#133) AND (d_year#133 = 2000)) AND isnotnull(d_date_sk#132)) + +(191) BroadcastExchange +Input [2]: [d_date_sk#132, d_year#133] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=21] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/simplified.txt new file mode 100644 index 000000000..410352945 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/simplified.txt @@ -0,0 +1,289 @@ +WholeStageCodegen (54) + Sort [product_name,store_name,cnt,s1,s1] + InputAdapter + Exchange [product_name,store_name,cnt,s1,s1] #1 + WholeStageCodegen (53) + Project [product_name,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,s1,s2,s3,syear,cnt] + SortMergeJoin [item_sk,store_name,store_zip,item_sk,store_name,store_zip,cnt,cnt] + InputAdapter + WholeStageCodegen (26) + Sort [item_sk,store_name,store_zip] + InputAdapter + Exchange [item_sk,store_name,store_zip] #2 + WholeStageCodegen (25) + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),product_name,item_sk,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] + Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,hd_income_band_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk,cd_marital_status,cd_marital_status] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,cd_marital_status] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_first_shipto_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,d_year] + BroadcastHashJoin [c_first_sales_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SortMergeJoin [ss_item_sk,cs_item_sk] + InputAdapter + WholeStageCodegen (3) + Sort [ss_item_sk] + InputAdapter + Exchange [ss_item_sk] #3 + WholeStageCodegen (2) + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + Project [sr_item_sk,sr_ticket_number] + Filter [sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + WholeStageCodegen (9) + Sort [cs_item_sk] + Project [cs_item_sk] + Filter [sale,refund] + HashAggregate [cs_item_sk,sum,sum,isEmpty] [sum(UnscaledValue(cs_ext_list_price)),sum(((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)),sale,refund,sum,sum,isEmpty] + InputAdapter + Exchange [cs_item_sk] #6 + WholeStageCodegen (8) + HashAggregate [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] [sum,sum,isEmpty,sum,sum,isEmpty] + Project [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (5) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #7 + WholeStageCodegen (4) + Project [cs_item_sk,cs_order_number,cs_ext_list_price] + Filter [cs_item_sk,cs_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_ext_list_price,cs_sold_date_sk] + InputAdapter + WholeStageCodegen (7) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #8 + WholeStageCodegen (6) + Project [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit] + Filter [cr_item_sk,cr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (11) + Filter [s_store_sk,s_store_name,s_zip] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_zip] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (12) + Filter [c_customer_sk,c_first_sales_date_sk,c_first_shipto_date_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (13) + Filter [d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (15) + Filter [cd_demo_sk,cd_marital_status] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (17) + Filter [p_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.promotion [p_promo_sk] + InputAdapter + BroadcastExchange #14 + WholeStageCodegen (18) + Filter [hd_demo_sk,hd_income_band_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_income_band_sk] + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + BroadcastExchange #15 + WholeStageCodegen (20) + Filter [ca_address_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + BroadcastExchange #16 + WholeStageCodegen (22) + Filter [ib_income_band_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.income_band [ib_income_band_sk] + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + BroadcastExchange #17 + WholeStageCodegen (24) + Project [i_item_sk,i_product_name] + Filter [i_current_price,i_color,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_color,i_product_name] + InputAdapter + WholeStageCodegen (52) + Sort [item_sk,store_name,store_zip] + InputAdapter + Exchange [item_sk,store_name,store_zip] #18 + WholeStageCodegen (51) + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),item_sk,store_name,store_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] + HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] + Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [hd_income_band_sk,ib_income_band_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [c_current_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk,ca_street_number,ca_street_name,ca_city,ca_zip] + BroadcastHashJoin [ss_addr_sk,ca_address_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_addr_sk,d_year,d_year,hd_income_band_sk,hd_income_band_sk] + BroadcastHashJoin [c_current_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,hd_income_band_sk] + BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk,cd_marital_status,cd_marital_status] + Project [ss_item_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year,cd_marital_status] + BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,d_year,d_year] + BroadcastHashJoin [c_first_shipto_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,d_year] + BroadcastHashJoin [c_first_sales_date_sk,d_date_sk] + Project [ss_item_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] + BroadcastHashJoin [ss_customer_sk,c_customer_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,s_store_name,s_zip] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SortMergeJoin [ss_item_sk,cs_item_sk] + InputAdapter + WholeStageCodegen (29) + Sort [ss_item_sk] + InputAdapter + Exchange [ss_item_sk] #19 + WholeStageCodegen (28) + Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + BroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + InputAdapter + BroadcastExchange #20 + WholeStageCodegen (27) + Filter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #21 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + Project [sr_item_sk,sr_ticket_number] + Filter [sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + WholeStageCodegen (35) + Sort [cs_item_sk] + Project [cs_item_sk] + Filter [sale,refund] + HashAggregate [cs_item_sk,sum,sum,isEmpty] [sum(UnscaledValue(cs_ext_list_price)),sum(((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)),sale,refund,sum,sum,isEmpty] + InputAdapter + ReusedExchange [cs_item_sk,sum,sum,isEmpty] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #21 + InputAdapter + ReusedExchange [s_store_sk,s_store_name,s_zip] #9 + InputAdapter + ReusedExchange [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] #10 + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + ReusedExchange [d_date_sk,d_year] #11 + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + ReusedExchange [cd_demo_sk,cd_marital_status] #12 + InputAdapter + ReusedExchange [p_promo_sk] #13 + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + ReusedExchange [ib_income_band_sk] #16 + InputAdapter + ReusedExchange [i_item_sk,i_product_name] #17 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/explain.txt new file mode 100644 index 000000000..5c6c416ce --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/explain.txt @@ -0,0 +1,466 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * Filter (69) + +- Window (68) + +- WindowGroupLimit (67) + +- * Sort (66) + +- Exchange (65) + +- WindowGroupLimit (64) + +- * Sort (63) + +- Union (62) + :- * HashAggregate (21) + : +- Exchange (20) + : +- * HashAggregate (19) + : +- * Project (18) + : +- * BroadcastHashJoin Inner BuildRight (17) + : :- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * Project (6) + : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : :- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- ReusedExchange (4) + : : +- BroadcastExchange (10) + : : +- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (16) + : +- * Filter (15) + : +- * ColumnarToRow (14) + : +- CometScan parquet spark_catalog.default.item (13) + :- * HashAggregate (26) + : +- Exchange (25) + : +- * HashAggregate (24) + : +- * HashAggregate (23) + : +- ReusedExchange (22) + :- * HashAggregate (31) + : +- Exchange (30) + : +- * HashAggregate (29) + : +- * HashAggregate (28) + : +- ReusedExchange (27) + :- * HashAggregate (36) + : +- Exchange (35) + : +- * HashAggregate (34) + : +- * HashAggregate (33) + : +- ReusedExchange (32) + :- * HashAggregate (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- * HashAggregate (38) + : +- ReusedExchange (37) + :- * HashAggregate (46) + : +- Exchange (45) + : +- * HashAggregate (44) + : +- * HashAggregate (43) + : +- ReusedExchange (42) + :- * HashAggregate (51) + : +- Exchange (50) + : +- * HashAggregate (49) + : +- * HashAggregate (48) + : +- ReusedExchange (47) + :- * HashAggregate (56) + : +- Exchange (55) + : +- * HashAggregate (54) + : +- * HashAggregate (53) + : +- ReusedExchange (52) + +- * HashAggregate (61) + +- Exchange (60) + +- * HashAggregate (59) + +- * HashAggregate (58) + +- ReusedExchange (57) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] + +(3) Filter [codegen id : 4] +Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) + +(4) ReusedExchange [Reuses operator id: 75] +Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(5) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#5] +Right keys [1]: [d_date_sk#7] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 4] +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5, d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(7) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#11, s_store_id#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#11, s_store_id#12] + +(9) Filter [codegen id : 2] +Input [2]: [s_store_sk#11, s_store_id#12] +Condition : isnotnull(s_store_sk#11) + +(10) BroadcastExchange +Input [2]: [s_store_sk#11, s_store_id#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 4] +Output [7]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_sk#11, s_store_id#12] + +(13) Scan parquet spark_catalog.default.item +Output [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 3] +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] + +(15) Filter [codegen id : 3] +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Condition : isnotnull(i_item_sk#13) + +(16) BroadcastExchange +Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#13] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [10]: [ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Input [12]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12, i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] + +(19) HashAggregate [codegen id : 4] +Input [10]: [ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Keys [8]: [i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12] +Functions [1]: [partial_sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))] +Aggregate Attributes [2]: [sum#18, isEmpty#19] +Results [10]: [i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, sum#20, isEmpty#21] + +(20) Exchange +Input [10]: [i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, sum#20, isEmpty#21] +Arguments: hashpartitioning(i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) HashAggregate [codegen id : 5] +Input [10]: [i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, sum#20, isEmpty#21] +Keys [8]: [i_category#16, i_class#15, i_brand#14, i_product_name#17, d_year#8, d_qoy#10, d_moy#9, s_store_id#12] +Functions [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))#22] +Results [9]: [i_category#16 AS i_category#23, i_class#15 AS i_class#24, i_brand#14 AS i_brand#25, i_product_name#17 AS i_product_name#26, d_year#8 AS d_year#27, d_qoy#10 AS d_qoy#28, d_moy#9 AS d_moy#29, s_store_id#12 AS s_store_id#30, cast(sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))#22 as decimal(38,2)) AS sumsales#31] + +(22) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, s_store_id#39, sum#40, isEmpty#41] + +(23) HashAggregate [codegen id : 10] +Input [10]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, s_store_id#39, sum#40, isEmpty#41] +Keys [8]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, s_store_id#39] +Functions [1]: [sum(coalesce((ss_sales_price#42 * cast(ss_quantity#43 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#42 * cast(ss_quantity#43 as decimal(10,0))), 0.00))#22] +Results [8]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, sum(coalesce((ss_sales_price#42 * cast(ss_quantity#43 as decimal(10,0))), 0.00))#22 AS sumsales#44] + +(24) HashAggregate [codegen id : 10] +Input [8]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, sumsales#44] +Keys [7]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38] +Functions [1]: [partial_sum(sumsales#44)] +Aggregate Attributes [2]: [sum#45, isEmpty#46] +Results [9]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, sum#47, isEmpty#48] + +(25) Exchange +Input [9]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, sum#47, isEmpty#48] +Arguments: hashpartitioning(i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(26) HashAggregate [codegen id : 11] +Input [9]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, sum#47, isEmpty#48] +Keys [7]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38] +Functions [1]: [sum(sumsales#44)] +Aggregate Attributes [1]: [sum(sumsales#44)#49] +Results [9]: [i_category#32, i_class#33, i_brand#34, i_product_name#35, d_year#36, d_qoy#37, d_moy#38, null AS s_store_id#50, sum(sumsales#44)#49 AS sumsales#51] + +(27) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, d_moy#58, s_store_id#59, sum#60, isEmpty#61] + +(28) HashAggregate [codegen id : 16] +Input [10]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, d_moy#58, s_store_id#59, sum#60, isEmpty#61] +Keys [8]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, d_moy#58, s_store_id#59] +Functions [1]: [sum(coalesce((ss_sales_price#62 * cast(ss_quantity#63 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#62 * cast(ss_quantity#63 as decimal(10,0))), 0.00))#22] +Results [7]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, sum(coalesce((ss_sales_price#62 * cast(ss_quantity#63 as decimal(10,0))), 0.00))#22 AS sumsales#64] + +(29) HashAggregate [codegen id : 16] +Input [7]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, sumsales#64] +Keys [6]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57] +Functions [1]: [partial_sum(sumsales#64)] +Aggregate Attributes [2]: [sum#65, isEmpty#66] +Results [8]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, sum#67, isEmpty#68] + +(30) Exchange +Input [8]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, sum#67, isEmpty#68] +Arguments: hashpartitioning(i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(31) HashAggregate [codegen id : 17] +Input [8]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, sum#67, isEmpty#68] +Keys [6]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57] +Functions [1]: [sum(sumsales#64)] +Aggregate Attributes [1]: [sum(sumsales#64)#69] +Results [9]: [i_category#52, i_class#53, i_brand#54, i_product_name#55, d_year#56, d_qoy#57, null AS d_moy#70, null AS s_store_id#71, sum(sumsales#64)#69 AS sumsales#72] + +(32) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, d_qoy#78, d_moy#79, s_store_id#80, sum#81, isEmpty#82] + +(33) HashAggregate [codegen id : 22] +Input [10]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, d_qoy#78, d_moy#79, s_store_id#80, sum#81, isEmpty#82] +Keys [8]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, d_qoy#78, d_moy#79, s_store_id#80] +Functions [1]: [sum(coalesce((ss_sales_price#83 * cast(ss_quantity#84 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#83 * cast(ss_quantity#84 as decimal(10,0))), 0.00))#22] +Results [6]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, sum(coalesce((ss_sales_price#83 * cast(ss_quantity#84 as decimal(10,0))), 0.00))#22 AS sumsales#85] + +(34) HashAggregate [codegen id : 22] +Input [6]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, sumsales#85] +Keys [5]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77] +Functions [1]: [partial_sum(sumsales#85)] +Aggregate Attributes [2]: [sum#86, isEmpty#87] +Results [7]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, sum#88, isEmpty#89] + +(35) Exchange +Input [7]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, sum#88, isEmpty#89] +Arguments: hashpartitioning(i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(36) HashAggregate [codegen id : 23] +Input [7]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, sum#88, isEmpty#89] +Keys [5]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77] +Functions [1]: [sum(sumsales#85)] +Aggregate Attributes [1]: [sum(sumsales#85)#90] +Results [9]: [i_category#73, i_class#74, i_brand#75, i_product_name#76, d_year#77, null AS d_qoy#91, null AS d_moy#92, null AS s_store_id#93, sum(sumsales#85)#90 AS sumsales#94] + +(37) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, d_year#99, d_qoy#100, d_moy#101, s_store_id#102, sum#103, isEmpty#104] + +(38) HashAggregate [codegen id : 28] +Input [10]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, d_year#99, d_qoy#100, d_moy#101, s_store_id#102, sum#103, isEmpty#104] +Keys [8]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, d_year#99, d_qoy#100, d_moy#101, s_store_id#102] +Functions [1]: [sum(coalesce((ss_sales_price#105 * cast(ss_quantity#106 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#105 * cast(ss_quantity#106 as decimal(10,0))), 0.00))#22] +Results [5]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, sum(coalesce((ss_sales_price#105 * cast(ss_quantity#106 as decimal(10,0))), 0.00))#22 AS sumsales#107] + +(39) HashAggregate [codegen id : 28] +Input [5]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, sumsales#107] +Keys [4]: [i_category#95, i_class#96, i_brand#97, i_product_name#98] +Functions [1]: [partial_sum(sumsales#107)] +Aggregate Attributes [2]: [sum#108, isEmpty#109] +Results [6]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, sum#110, isEmpty#111] + +(40) Exchange +Input [6]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, sum#110, isEmpty#111] +Arguments: hashpartitioning(i_category#95, i_class#96, i_brand#97, i_product_name#98, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(41) HashAggregate [codegen id : 29] +Input [6]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, sum#110, isEmpty#111] +Keys [4]: [i_category#95, i_class#96, i_brand#97, i_product_name#98] +Functions [1]: [sum(sumsales#107)] +Aggregate Attributes [1]: [sum(sumsales#107)#112] +Results [9]: [i_category#95, i_class#96, i_brand#97, i_product_name#98, null AS d_year#113, null AS d_qoy#114, null AS d_moy#115, null AS s_store_id#116, sum(sumsales#107)#112 AS sumsales#117] + +(42) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#118, i_class#119, i_brand#120, i_product_name#121, d_year#122, d_qoy#123, d_moy#124, s_store_id#125, sum#126, isEmpty#127] + +(43) HashAggregate [codegen id : 34] +Input [10]: [i_category#118, i_class#119, i_brand#120, i_product_name#121, d_year#122, d_qoy#123, d_moy#124, s_store_id#125, sum#126, isEmpty#127] +Keys [8]: [i_category#118, i_class#119, i_brand#120, i_product_name#121, d_year#122, d_qoy#123, d_moy#124, s_store_id#125] +Functions [1]: [sum(coalesce((ss_sales_price#128 * cast(ss_quantity#129 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#128 * cast(ss_quantity#129 as decimal(10,0))), 0.00))#22] +Results [4]: [i_category#118, i_class#119, i_brand#120, sum(coalesce((ss_sales_price#128 * cast(ss_quantity#129 as decimal(10,0))), 0.00))#22 AS sumsales#130] + +(44) HashAggregate [codegen id : 34] +Input [4]: [i_category#118, i_class#119, i_brand#120, sumsales#130] +Keys [3]: [i_category#118, i_class#119, i_brand#120] +Functions [1]: [partial_sum(sumsales#130)] +Aggregate Attributes [2]: [sum#131, isEmpty#132] +Results [5]: [i_category#118, i_class#119, i_brand#120, sum#133, isEmpty#134] + +(45) Exchange +Input [5]: [i_category#118, i_class#119, i_brand#120, sum#133, isEmpty#134] +Arguments: hashpartitioning(i_category#118, i_class#119, i_brand#120, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(46) HashAggregate [codegen id : 35] +Input [5]: [i_category#118, i_class#119, i_brand#120, sum#133, isEmpty#134] +Keys [3]: [i_category#118, i_class#119, i_brand#120] +Functions [1]: [sum(sumsales#130)] +Aggregate Attributes [1]: [sum(sumsales#130)#135] +Results [9]: [i_category#118, i_class#119, i_brand#120, null AS i_product_name#136, null AS d_year#137, null AS d_qoy#138, null AS d_moy#139, null AS s_store_id#140, sum(sumsales#130)#135 AS sumsales#141] + +(47) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#142, i_class#143, i_brand#144, i_product_name#145, d_year#146, d_qoy#147, d_moy#148, s_store_id#149, sum#150, isEmpty#151] + +(48) HashAggregate [codegen id : 40] +Input [10]: [i_category#142, i_class#143, i_brand#144, i_product_name#145, d_year#146, d_qoy#147, d_moy#148, s_store_id#149, sum#150, isEmpty#151] +Keys [8]: [i_category#142, i_class#143, i_brand#144, i_product_name#145, d_year#146, d_qoy#147, d_moy#148, s_store_id#149] +Functions [1]: [sum(coalesce((ss_sales_price#152 * cast(ss_quantity#153 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#152 * cast(ss_quantity#153 as decimal(10,0))), 0.00))#22] +Results [3]: [i_category#142, i_class#143, sum(coalesce((ss_sales_price#152 * cast(ss_quantity#153 as decimal(10,0))), 0.00))#22 AS sumsales#154] + +(49) HashAggregate [codegen id : 40] +Input [3]: [i_category#142, i_class#143, sumsales#154] +Keys [2]: [i_category#142, i_class#143] +Functions [1]: [partial_sum(sumsales#154)] +Aggregate Attributes [2]: [sum#155, isEmpty#156] +Results [4]: [i_category#142, i_class#143, sum#157, isEmpty#158] + +(50) Exchange +Input [4]: [i_category#142, i_class#143, sum#157, isEmpty#158] +Arguments: hashpartitioning(i_category#142, i_class#143, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(51) HashAggregate [codegen id : 41] +Input [4]: [i_category#142, i_class#143, sum#157, isEmpty#158] +Keys [2]: [i_category#142, i_class#143] +Functions [1]: [sum(sumsales#154)] +Aggregate Attributes [1]: [sum(sumsales#154)#159] +Results [9]: [i_category#142, i_class#143, null AS i_brand#160, null AS i_product_name#161, null AS d_year#162, null AS d_qoy#163, null AS d_moy#164, null AS s_store_id#165, sum(sumsales#154)#159 AS sumsales#166] + +(52) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#167, i_class#168, i_brand#169, i_product_name#170, d_year#171, d_qoy#172, d_moy#173, s_store_id#174, sum#175, isEmpty#176] + +(53) HashAggregate [codegen id : 46] +Input [10]: [i_category#167, i_class#168, i_brand#169, i_product_name#170, d_year#171, d_qoy#172, d_moy#173, s_store_id#174, sum#175, isEmpty#176] +Keys [8]: [i_category#167, i_class#168, i_brand#169, i_product_name#170, d_year#171, d_qoy#172, d_moy#173, s_store_id#174] +Functions [1]: [sum(coalesce((ss_sales_price#177 * cast(ss_quantity#178 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#177 * cast(ss_quantity#178 as decimal(10,0))), 0.00))#22] +Results [2]: [i_category#167, sum(coalesce((ss_sales_price#177 * cast(ss_quantity#178 as decimal(10,0))), 0.00))#22 AS sumsales#179] + +(54) HashAggregate [codegen id : 46] +Input [2]: [i_category#167, sumsales#179] +Keys [1]: [i_category#167] +Functions [1]: [partial_sum(sumsales#179)] +Aggregate Attributes [2]: [sum#180, isEmpty#181] +Results [3]: [i_category#167, sum#182, isEmpty#183] + +(55) Exchange +Input [3]: [i_category#167, sum#182, isEmpty#183] +Arguments: hashpartitioning(i_category#167, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(56) HashAggregate [codegen id : 47] +Input [3]: [i_category#167, sum#182, isEmpty#183] +Keys [1]: [i_category#167] +Functions [1]: [sum(sumsales#179)] +Aggregate Attributes [1]: [sum(sumsales#179)#184] +Results [9]: [i_category#167, null AS i_class#185, null AS i_brand#186, null AS i_product_name#187, null AS d_year#188, null AS d_qoy#189, null AS d_moy#190, null AS s_store_id#191, sum(sumsales#179)#184 AS sumsales#192] + +(57) ReusedExchange [Reuses operator id: 20] +Output [10]: [i_category#193, i_class#194, i_brand#195, i_product_name#196, d_year#197, d_qoy#198, d_moy#199, s_store_id#200, sum#201, isEmpty#202] + +(58) HashAggregate [codegen id : 52] +Input [10]: [i_category#193, i_class#194, i_brand#195, i_product_name#196, d_year#197, d_qoy#198, d_moy#199, s_store_id#200, sum#201, isEmpty#202] +Keys [8]: [i_category#193, i_class#194, i_brand#195, i_product_name#196, d_year#197, d_qoy#198, d_moy#199, s_store_id#200] +Functions [1]: [sum(coalesce((ss_sales_price#203 * cast(ss_quantity#204 as decimal(10,0))), 0.00))] +Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#203 * cast(ss_quantity#204 as decimal(10,0))), 0.00))#22] +Results [1]: [sum(coalesce((ss_sales_price#203 * cast(ss_quantity#204 as decimal(10,0))), 0.00))#22 AS sumsales#205] + +(59) HashAggregate [codegen id : 52] +Input [1]: [sumsales#205] +Keys: [] +Functions [1]: [partial_sum(sumsales#205)] +Aggregate Attributes [2]: [sum#206, isEmpty#207] +Results [2]: [sum#208, isEmpty#209] + +(60) Exchange +Input [2]: [sum#208, isEmpty#209] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=11] + +(61) HashAggregate [codegen id : 53] +Input [2]: [sum#208, isEmpty#209] +Keys: [] +Functions [1]: [sum(sumsales#205)] +Aggregate Attributes [1]: [sum(sumsales#205)#210] +Results [9]: [null AS i_category#211, null AS i_class#212, null AS i_brand#213, null AS i_product_name#214, null AS d_year#215, null AS d_qoy#216, null AS d_moy#217, null AS s_store_id#218, sum(sumsales#205)#210 AS sumsales#219] + +(62) Union + +(63) Sort [codegen id : 54] +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: [i_category#23 ASC NULLS FIRST, sumsales#31 DESC NULLS LAST], false, 0 + +(64) WindowGroupLimit +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: [i_category#23], [sumsales#31 DESC NULLS LAST], rank(sumsales#31), 100, Partial + +(65) Exchange +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: hashpartitioning(i_category#23, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(66) Sort [codegen id : 55] +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: [i_category#23 ASC NULLS FIRST, sumsales#31 DESC NULLS LAST], false, 0 + +(67) WindowGroupLimit +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: [i_category#23], [sumsales#31 DESC NULLS LAST], rank(sumsales#31), 100, Final + +(68) Window +Input [9]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31] +Arguments: [rank(sumsales#31) windowspecdefinition(i_category#23, sumsales#31 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#220], [i_category#23], [sumsales#31 DESC NULLS LAST] + +(69) Filter [codegen id : 56] +Input [10]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31, rk#220] +Condition : (rk#220 <= 100) + +(70) TakeOrderedAndProject +Input [10]: [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31, rk#220] +Arguments: 100, [i_category#23 ASC NULLS FIRST, i_class#24 ASC NULLS FIRST, i_brand#25 ASC NULLS FIRST, i_product_name#26 ASC NULLS FIRST, d_year#27 ASC NULLS FIRST, d_qoy#28 ASC NULLS FIRST, d_moy#29 ASC NULLS FIRST, s_store_id#30 ASC NULLS FIRST, sumsales#31 ASC NULLS FIRST, rk#220 ASC NULLS FIRST], [i_category#23, i_class#24, i_brand#25, i_product_name#26, d_year#27, d_qoy#28, d_moy#29, s_store_id#30, sumsales#31, rk#220] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (75) ++- * Project (74) + +- * Filter (73) + +- * ColumnarToRow (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [5]: [d_date_sk#7, d_month_seq#221, d_year#8, d_moy#9, d_qoy#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] +ReadSchema: struct + +(72) ColumnarToRow [codegen id : 1] +Input [5]: [d_date_sk#7, d_month_seq#221, d_year#8, d_moy#9, d_qoy#10] + +(73) Filter [codegen id : 1] +Input [5]: [d_date_sk#7, d_month_seq#221, d_year#8, d_moy#9, d_qoy#10] +Condition : (((isnotnull(d_month_seq#221) AND (d_month_seq#221 >= 1212)) AND (d_month_seq#221 <= 1223)) AND isnotnull(d_date_sk#7)) + +(74) Project [codegen id : 1] +Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] +Input [5]: [d_date_sk#7, d_month_seq#221, d_year#8, d_moy#9, d_qoy#10] + +(75) BroadcastExchange +Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/simplified.txt new file mode 100644 index 000000000..aed12f8ec --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/simplified.txt @@ -0,0 +1,127 @@ +TakeOrderedAndProject [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,rk] + WholeStageCodegen (56) + Filter [rk] + InputAdapter + Window [sumsales,i_category] + WindowGroupLimit [i_category,sumsales] + WholeStageCodegen (55) + Sort [i_category,sumsales] + InputAdapter + Exchange [i_category] #1 + WindowGroupLimit [i_category,sumsales] + WholeStageCodegen (54) + Sort [i_category,sumsales] + InputAdapter + Union + WholeStageCodegen (5) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id] #2 + WholeStageCodegen (4) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,ss_sales_price,ss_quantity] [sum,isEmpty,sum,isEmpty] + Project [ss_quantity,ss_sales_price,d_year,d_moy,d_qoy,s_store_id,i_brand,i_class,i_category,i_product_name] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_quantity,ss_sales_price,d_year,d_moy,d_qoy,s_store_id] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,d_year,d_moy,d_qoy] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk,ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk,d_year,d_moy,d_qoy] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_year,d_moy,d_qoy] + InputAdapter + ReusedExchange [d_date_sk,d_year,d_moy,d_qoy] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (2) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (3) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] + WholeStageCodegen (11) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,sum,isEmpty] [sum(sumsales),s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy] #6 + WholeStageCodegen (10) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (17) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,sum,isEmpty] [sum(sumsales),d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy] #7 + WholeStageCodegen (16) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (23) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,sum,isEmpty] [sum(sumsales),d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name,d_year] #8 + WholeStageCodegen (22) + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (29) + HashAggregate [i_category,i_class,i_brand,i_product_name,sum,isEmpty] [sum(sumsales),d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand,i_product_name] #9 + WholeStageCodegen (28) + HashAggregate [i_category,i_class,i_brand,i_product_name,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (35) + HashAggregate [i_category,i_class,i_brand,sum,isEmpty] [sum(sumsales),i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class,i_brand] #10 + WholeStageCodegen (34) + HashAggregate [i_category,i_class,i_brand,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (41) + HashAggregate [i_category,i_class,sum,isEmpty] [sum(sumsales),i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category,i_class] #11 + WholeStageCodegen (40) + HashAggregate [i_category,i_class,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (47) + HashAggregate [i_category,sum,isEmpty] [sum(sumsales),i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange [i_category] #12 + WholeStageCodegen (46) + HashAggregate [i_category,sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 + WholeStageCodegen (53) + HashAggregate [sum,isEmpty] [sum(sumsales),i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sumsales,sum,isEmpty] + InputAdapter + Exchange #13 + WholeStageCodegen (52) + HashAggregate [sumsales] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] [sum(coalesce((ss_sales_price * cast(ss_quantity as decimal(10,0))), 0.00)),sumsales,sum,isEmpty] + InputAdapter + ReusedExchange [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,s_store_id,sum,isEmpty] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/explain.txt new file mode 100644 index 000000000..189cbfd42 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/explain.txt @@ -0,0 +1,368 @@ +== Physical Plan == +TakeOrderedAndProject (56) ++- * Project (55) + +- Window (54) + +- * Sort (53) + +- Exchange (52) + +- * HashAggregate (51) + +- Exchange (50) + +- * HashAggregate (49) + +- Union (48) + :- * HashAggregate (37) + : +- Exchange (36) + : +- * HashAggregate (35) + : +- * Project (34) + : +- * BroadcastHashJoin Inner BuildRight (33) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (32) + : +- * BroadcastHashJoin LeftSemi BuildRight (31) + : :- * Filter (9) + : : +- * ColumnarToRow (8) + : : +- CometScan parquet spark_catalog.default.store (7) + : +- BroadcastExchange (30) + : +- * Project (29) + : +- * Filter (28) + : +- Window (27) + : +- WindowGroupLimit (26) + : +- * Sort (25) + : +- * HashAggregate (24) + : +- Exchange (23) + : +- * HashAggregate (22) + : +- * Project (21) + : +- * BroadcastHashJoin Inner BuildRight (20) + : :- * Project (18) + : : +- * BroadcastHashJoin Inner BuildRight (17) + : : :- * Filter (12) + : : : +- * ColumnarToRow (11) + : : : +- CometScan parquet spark_catalog.default.store_sales (10) + : : +- BroadcastExchange (16) + : : +- * Filter (15) + : : +- * ColumnarToRow (14) + : : +- CometScan parquet spark_catalog.default.store (13) + : +- ReusedExchange (19) + :- * HashAggregate (42) + : +- Exchange (41) + : +- * HashAggregate (40) + : +- * HashAggregate (39) + : +- ReusedExchange (38) + +- * HashAggregate (47) + +- Exchange (46) + +- * HashAggregate (45) + +- * HashAggregate (44) + +- ReusedExchange (43) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 8] +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] + +(3) Filter [codegen id : 8] +Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) + +(4) ReusedExchange [Reuses operator id: 61] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 8] +Output [2]: [ss_store_sk#1, ss_net_profit#2] +Input [4]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.store +Output [3]: [s_store_sk#6, s_county#7, s_state#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 7] +Input [3]: [s_store_sk#6, s_county#7, s_state#8] + +(9) Filter [codegen id : 7] +Input [3]: [s_store_sk#6, s_county#7, s_state#8] +Condition : isnotnull(s_store_sk#6) + +(10) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 4] +Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] + +(12) Filter [codegen id : 4] +Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_store_sk#9) + +(13) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#13, s_state#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(14) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#13, s_state#14] + +(15) Filter [codegen id : 2] +Input [2]: [s_store_sk#13, s_state#14] +Condition : isnotnull(s_store_sk#13) + +(16) BroadcastExchange +Input [2]: [s_store_sk#13, s_state#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(17) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_store_sk#9] +Right keys [1]: [s_store_sk#13] +Join type: Inner +Join condition: None + +(18) Project [codegen id : 4] +Output [3]: [ss_net_profit#10, ss_sold_date_sk#11, s_state#14] +Input [5]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11, s_store_sk#13, s_state#14] + +(19) ReusedExchange [Reuses operator id: 61] +Output [1]: [d_date_sk#15] + +(20) BroadcastHashJoin [codegen id : 4] +Left keys [1]: [ss_sold_date_sk#11] +Right keys [1]: [d_date_sk#15] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 4] +Output [2]: [ss_net_profit#10, s_state#14] +Input [4]: [ss_net_profit#10, ss_sold_date_sk#11, s_state#14, d_date_sk#15] + +(22) HashAggregate [codegen id : 4] +Input [2]: [ss_net_profit#10, s_state#14] +Keys [1]: [s_state#14] +Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#10))] +Aggregate Attributes [1]: [sum#16] +Results [2]: [s_state#14, sum#17] + +(23) Exchange +Input [2]: [s_state#14, sum#17] +Arguments: hashpartitioning(s_state#14, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(24) HashAggregate [codegen id : 5] +Input [2]: [s_state#14, sum#17] +Keys [1]: [s_state#14] +Functions [1]: [sum(UnscaledValue(ss_net_profit#10))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#10))#18] +Results [3]: [s_state#14, MakeDecimal(sum(UnscaledValue(ss_net_profit#10))#18,17,2) AS _w0#19, s_state#14] + +(25) Sort [codegen id : 5] +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [s_state#14 ASC NULLS FIRST, _w0#19 DESC NULLS LAST], false, 0 + +(26) WindowGroupLimit +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [s_state#14], [_w0#19 DESC NULLS LAST], rank(_w0#19), 5, Final + +(27) Window +Input [3]: [s_state#14, _w0#19, s_state#14] +Arguments: [rank(_w0#19) windowspecdefinition(s_state#14, _w0#19 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS ranking#20], [s_state#14], [_w0#19 DESC NULLS LAST] + +(28) Filter [codegen id : 6] +Input [4]: [s_state#14, _w0#19, s_state#14, ranking#20] +Condition : (ranking#20 <= 5) + +(29) Project [codegen id : 6] +Output [1]: [s_state#14] +Input [4]: [s_state#14, _w0#19, s_state#14, ranking#20] + +(30) BroadcastExchange +Input [1]: [s_state#14] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=3] + +(31) BroadcastHashJoin [codegen id : 7] +Left keys [1]: [s_state#8] +Right keys [1]: [s_state#14] +Join type: LeftSemi +Join condition: None + +(32) BroadcastExchange +Input [3]: [s_store_sk#6, s_county#7, s_state#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] + +(33) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#6] +Join type: Inner +Join condition: None + +(34) Project [codegen id : 8] +Output [3]: [ss_net_profit#2, s_county#7, s_state#8] +Input [5]: [ss_store_sk#1, ss_net_profit#2, s_store_sk#6, s_county#7, s_state#8] + +(35) HashAggregate [codegen id : 8] +Input [3]: [ss_net_profit#2, s_county#7, s_state#8] +Keys [2]: [s_state#8, s_county#7] +Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum#21] +Results [3]: [s_state#8, s_county#7, sum#22] + +(36) Exchange +Input [3]: [s_state#8, s_county#7, sum#22] +Arguments: hashpartitioning(s_state#8, s_county#7, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(37) HashAggregate [codegen id : 9] +Input [3]: [s_state#8, s_county#7, sum#22] +Keys [2]: [s_state#8, s_county#7] +Functions [1]: [sum(UnscaledValue(ss_net_profit#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#2))#23] +Results [6]: [cast(MakeDecimal(sum(UnscaledValue(ss_net_profit#2))#23,17,2) as decimal(27,2)) AS total_sum#24, s_state#8, s_county#7, 0 AS g_state#25, 0 AS g_county#26, 0 AS lochierarchy#27] + +(38) ReusedExchange [Reuses operator id: 36] +Output [3]: [s_state#28, s_county#29, sum#30] + +(39) HashAggregate [codegen id : 18] +Input [3]: [s_state#28, s_county#29, sum#30] +Keys [2]: [s_state#28, s_county#29] +Functions [1]: [sum(UnscaledValue(ss_net_profit#31))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#31))#23] +Results [2]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#31))#23,17,2) AS total_sum#32, s_state#28] + +(40) HashAggregate [codegen id : 18] +Input [2]: [total_sum#32, s_state#28] +Keys [1]: [s_state#28] +Functions [1]: [partial_sum(total_sum#32)] +Aggregate Attributes [2]: [sum#33, isEmpty#34] +Results [3]: [s_state#28, sum#35, isEmpty#36] + +(41) Exchange +Input [3]: [s_state#28, sum#35, isEmpty#36] +Arguments: hashpartitioning(s_state#28, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(42) HashAggregate [codegen id : 19] +Input [3]: [s_state#28, sum#35, isEmpty#36] +Keys [1]: [s_state#28] +Functions [1]: [sum(total_sum#32)] +Aggregate Attributes [1]: [sum(total_sum#32)#37] +Results [6]: [sum(total_sum#32)#37 AS total_sum#38, s_state#28, null AS s_county#39, 0 AS g_state#40, 1 AS g_county#41, 1 AS lochierarchy#42] + +(43) ReusedExchange [Reuses operator id: 36] +Output [3]: [s_state#43, s_county#44, sum#45] + +(44) HashAggregate [codegen id : 28] +Input [3]: [s_state#43, s_county#44, sum#45] +Keys [2]: [s_state#43, s_county#44] +Functions [1]: [sum(UnscaledValue(ss_net_profit#46))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#46))#23] +Results [1]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#46))#23,17,2) AS total_sum#47] + +(45) HashAggregate [codegen id : 28] +Input [1]: [total_sum#47] +Keys: [] +Functions [1]: [partial_sum(total_sum#47)] +Aggregate Attributes [2]: [sum#48, isEmpty#49] +Results [2]: [sum#50, isEmpty#51] + +(46) Exchange +Input [2]: [sum#50, isEmpty#51] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate [codegen id : 29] +Input [2]: [sum#50, isEmpty#51] +Keys: [] +Functions [1]: [sum(total_sum#47)] +Aggregate Attributes [1]: [sum(total_sum#47)#52] +Results [6]: [sum(total_sum#47)#52 AS total_sum#53, null AS s_state#54, null AS s_county#55, 1 AS g_state#56, 1 AS g_county#57, 2 AS lochierarchy#58] + +(48) Union + +(49) HashAggregate [codegen id : 30] +Input [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] +Keys [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] +Functions: [] +Aggregate Attributes: [] +Results [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] + +(50) Exchange +Input [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] +Arguments: hashpartitioning(total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(51) HashAggregate [codegen id : 31] +Input [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] +Keys [6]: [total_sum#24, s_state#8, s_county#7, g_state#25, g_county#26, lochierarchy#27] +Functions: [] +Aggregate Attributes: [] +Results [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, CASE WHEN (g_county#26 = 0) THEN s_state#8 END AS _w0#59] + +(52) Exchange +Input [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, _w0#59] +Arguments: hashpartitioning(lochierarchy#27, _w0#59, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(53) Sort [codegen id : 32] +Input [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, _w0#59] +Arguments: [lochierarchy#27 ASC NULLS FIRST, _w0#59 ASC NULLS FIRST, total_sum#24 DESC NULLS LAST], false, 0 + +(54) Window +Input [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, _w0#59] +Arguments: [rank(total_sum#24) windowspecdefinition(lochierarchy#27, _w0#59, total_sum#24 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#60], [lochierarchy#27, _w0#59], [total_sum#24 DESC NULLS LAST] + +(55) Project [codegen id : 33] +Output [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, rank_within_parent#60] +Input [6]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, _w0#59, rank_within_parent#60] + +(56) TakeOrderedAndProject +Input [5]: [total_sum#24, s_state#8, s_county#7, lochierarchy#27, rank_within_parent#60] +Arguments: 100, [lochierarchy#27 DESC NULLS LAST, CASE WHEN (lochierarchy#27 = 0) THEN s_state#8 END ASC NULLS FIRST, rank_within_parent#60 ASC NULLS FIRST], [total_sum#24, s_state#8, s_county#7, lochierarchy#27, rank_within_parent#60] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (61) ++- * Project (60) + +- * Filter (59) + +- * ColumnarToRow (58) + +- CometScan parquet spark_catalog.default.date_dim (57) + + +(57) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#61] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] +ReadSchema: struct + +(58) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#61] + +(59) Filter [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#61] +Condition : (((isnotnull(d_month_seq#61) AND (d_month_seq#61 >= 1212)) AND (d_month_seq#61 <= 1223)) AND isnotnull(d_date_sk#5)) + +(60) Project [codegen id : 1] +Output [1]: [d_date_sk#5] +Input [2]: [d_date_sk#5, d_month_seq#61] + +(61) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=10] + +Subquery:2 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#4 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/simplified.txt new file mode 100644 index 000000000..4155cfa24 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/simplified.txt @@ -0,0 +1,100 @@ +TakeOrderedAndProject [lochierarchy,s_state,rank_within_parent,total_sum,s_county] + WholeStageCodegen (33) + Project [total_sum,s_state,s_county,lochierarchy,rank_within_parent] + InputAdapter + Window [total_sum,lochierarchy,_w0] + WholeStageCodegen (32) + Sort [lochierarchy,_w0,total_sum] + InputAdapter + Exchange [lochierarchy,_w0] #1 + WholeStageCodegen (31) + HashAggregate [total_sum,s_state,s_county,g_state,g_county,lochierarchy] [_w0] + InputAdapter + Exchange [total_sum,s_state,s_county,g_state,g_county,lochierarchy] #2 + WholeStageCodegen (30) + HashAggregate [total_sum,s_state,s_county,g_state,g_county,lochierarchy] + InputAdapter + Union + WholeStageCodegen (9) + HashAggregate [s_state,s_county,sum] [sum(UnscaledValue(ss_net_profit)),total_sum,g_state,g_county,lochierarchy,sum] + InputAdapter + Exchange [s_state,s_county] #3 + WholeStageCodegen (8) + HashAggregate [s_state,s_county,ss_net_profit] [sum,sum] + Project [ss_net_profit,s_county,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (7) + BroadcastHashJoin [s_state,s_state] + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_county,s_state] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (6) + Project [s_state] + Filter [ranking] + InputAdapter + Window [_w0,s_state] + WindowGroupLimit [s_state,_w0] + WholeStageCodegen (5) + Sort [s_state,_w0] + HashAggregate [sum] [sum(UnscaledValue(ss_net_profit)),_w0,s_state,sum] + InputAdapter + Exchange [s_state] #7 + WholeStageCodegen (4) + HashAggregate [s_state,ss_net_profit] [sum,sum] + Project [ss_net_profit,s_state] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_net_profit,ss_sold_date_sk,s_state] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (2) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_state] + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (19) + HashAggregate [s_state,sum,isEmpty] [sum(total_sum),total_sum,s_county,g_state,g_county,lochierarchy,sum,isEmpty] + InputAdapter + Exchange [s_state] #9 + WholeStageCodegen (18) + HashAggregate [s_state,total_sum] [sum,isEmpty,sum,isEmpty] + HashAggregate [s_state,s_county,sum] [sum(UnscaledValue(ss_net_profit)),total_sum,sum] + InputAdapter + ReusedExchange [s_state,s_county,sum] #3 + WholeStageCodegen (29) + HashAggregate [sum,isEmpty] [sum(total_sum),total_sum,s_state,s_county,g_state,g_county,lochierarchy,sum,isEmpty] + InputAdapter + Exchange #10 + WholeStageCodegen (28) + HashAggregate [total_sum] [sum,isEmpty,sum,isEmpty] + HashAggregate [s_state,s_county,sum] [sum(UnscaledValue(ss_net_profit)),total_sum,sum] + InputAdapter + ReusedExchange [s_state,s_county,sum] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/explain.txt new file mode 100644 index 000000000..68229396a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/explain.txt @@ -0,0 +1,433 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * HashAggregate (69) + +- Exchange (68) + +- * HashAggregate (67) + +- * Project (66) + +- * SortMergeJoin LeftOuter (65) + :- * Sort (58) + : +- Exchange (57) + : +- * Project (56) + : +- * BroadcastHashJoin LeftOuter BuildRight (55) + : :- * Project (50) + : : +- * BroadcastHashJoin Inner BuildRight (49) + : : :- * Project (44) + : : : +- * BroadcastHashJoin Inner BuildRight (43) + : : : :- * Project (38) + : : : : +- * BroadcastHashJoin Inner BuildRight (37) + : : : : :- * Project (35) + : : : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : : : :- * Project (28) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (27) + : : : : : : :- * Project (21) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : : : : :- * Project (15) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : : : : :- * Project (9) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : : : : : : :- * Filter (3) + : : : : : : : : : : +- * ColumnarToRow (2) + : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : : : : : +- BroadcastExchange (7) + : : : : : : : : : +- * Filter (6) + : : : : : : : : : +- * ColumnarToRow (5) + : : : : : : : : : +- CometScan parquet spark_catalog.default.inventory (4) + : : : : : : : : +- BroadcastExchange (13) + : : : : : : : : +- * Filter (12) + : : : : : : : : +- * ColumnarToRow (11) + : : : : : : : : +- CometScan parquet spark_catalog.default.warehouse (10) + : : : : : : : +- BroadcastExchange (19) + : : : : : : : +- * Filter (18) + : : : : : : : +- * ColumnarToRow (17) + : : : : : : : +- CometScan parquet spark_catalog.default.item (16) + : : : : : : +- BroadcastExchange (26) + : : : : : : +- * Project (25) + : : : : : : +- * Filter (24) + : : : : : : +- * ColumnarToRow (23) + : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (22) + : : : : : +- BroadcastExchange (33) + : : : : : +- * Project (32) + : : : : : +- * Filter (31) + : : : : : +- * ColumnarToRow (30) + : : : : : +- CometScan parquet spark_catalog.default.household_demographics (29) + : : : : +- ReusedExchange (36) + : : : +- BroadcastExchange (42) + : : : +- * Filter (41) + : : : +- * ColumnarToRow (40) + : : : +- CometScan parquet spark_catalog.default.date_dim (39) + : : +- BroadcastExchange (48) + : : +- * Filter (47) + : : +- * ColumnarToRow (46) + : : +- CometScan parquet spark_catalog.default.date_dim (45) + : +- BroadcastExchange (54) + : +- * Filter (53) + : +- * ColumnarToRow (52) + : +- CometScan parquet spark_catalog.default.promotion (51) + +- * Sort (64) + +- Exchange (63) + +- * Project (62) + +- * Filter (61) + +- * ColumnarToRow (60) + +- CometScan parquet spark_catalog.default.catalog_returns (59) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#8), dynamicpruningexpression(cs_sold_date_sk#8 IN dynamicpruning#9)] +PushedFilters: [IsNotNull(cs_quantity), IsNotNull(cs_item_sk), IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_hdemo_sk), IsNotNull(cs_ship_date_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 10] +Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] + +(3) Filter [codegen id : 10] +Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] +Condition : ((((isnotnull(cs_quantity#7) AND isnotnull(cs_item_sk#4)) AND isnotnull(cs_bill_cdemo_sk#2)) AND isnotnull(cs_bill_hdemo_sk#3)) AND isnotnull(cs_ship_date_sk#1)) + +(4) Scan parquet spark_catalog.default.inventory +Output [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(inv_date_sk#13)] +PushedFilters: [IsNotNull(inv_quantity_on_hand), IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] + +(6) Filter [codegen id : 1] +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Condition : ((isnotnull(inv_quantity_on_hand#12) AND isnotnull(inv_item_sk#10)) AND isnotnull(inv_warehouse_sk#11)) + +(7) BroadcastExchange +Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_item_sk#4] +Right keys [1]: [inv_item_sk#10] +Join type: Inner +Join condition: (inv_quantity_on_hand#12 < cs_quantity#7) + +(9) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_warehouse_sk#11, inv_date_sk#13] +Input [12]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8, inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] + +(10) Scan parquet spark_catalog.default.warehouse +Output [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Batched: true +Location [not included in comparison]/{warehouse_dir}/warehouse] +PushedFilters: [IsNotNull(w_warehouse_sk)] +ReadSchema: struct + +(11) ColumnarToRow [codegen id : 2] +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] + +(12) Filter [codegen id : 2] +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Condition : isnotnull(w_warehouse_sk#14) + +(13) BroadcastExchange +Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] + +(14) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [inv_warehouse_sk#11] +Right keys [1]: [w_warehouse_sk#14] +Join type: Inner +Join condition: None + +(15) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_warehouse_sk#11, inv_date_sk#13, w_warehouse_sk#14, w_warehouse_name#15] + +(16) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#16, i_item_desc#17] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 3] +Input [2]: [i_item_sk#16, i_item_desc#17] + +(18) Filter [codegen id : 3] +Input [2]: [i_item_sk#16, i_item_desc#17] +Condition : isnotnull(i_item_sk#16) + +(19) BroadcastExchange +Input [2]: [i_item_sk#16, i_item_desc#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(20) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_item_sk#4] +Right keys [1]: [i_item_sk#16] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 10] +Output [10]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_sk#16, i_item_desc#17] + +(22) Scan parquet spark_catalog.default.customer_demographics +Output [2]: [cd_demo_sk#18, cd_marital_status#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer_demographics] +PushedFilters: [IsNotNull(cd_marital_status), EqualTo(cd_marital_status,M), IsNotNull(cd_demo_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 4] +Input [2]: [cd_demo_sk#18, cd_marital_status#19] + +(24) Filter [codegen id : 4] +Input [2]: [cd_demo_sk#18, cd_marital_status#19] +Condition : ((isnotnull(cd_marital_status#19) AND (cd_marital_status#19 = M)) AND isnotnull(cd_demo_sk#18)) + +(25) Project [codegen id : 4] +Output [1]: [cd_demo_sk#18] +Input [2]: [cd_demo_sk#18, cd_marital_status#19] + +(26) BroadcastExchange +Input [1]: [cd_demo_sk#18] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(27) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_bill_cdemo_sk#2] +Right keys [1]: [cd_demo_sk#18] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, cd_demo_sk#18] + +(29) Scan parquet spark_catalog.default.household_demographics +Output [2]: [hd_demo_sk#20, hd_buy_potential#21] +Batched: true +Location [not included in comparison]/{warehouse_dir}/household_demographics] +PushedFilters: [IsNotNull(hd_buy_potential), EqualTo(hd_buy_potential,1001-5000 ), IsNotNull(hd_demo_sk)] +ReadSchema: struct + +(30) ColumnarToRow [codegen id : 5] +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] + +(31) Filter [codegen id : 5] +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Condition : ((isnotnull(hd_buy_potential#21) AND (hd_buy_potential#21 = 1001-5000 )) AND isnotnull(hd_demo_sk#20)) + +(32) Project [codegen id : 5] +Output [1]: [hd_demo_sk#20] +Input [2]: [hd_demo_sk#20, hd_buy_potential#21] + +(33) BroadcastExchange +Input [1]: [hd_demo_sk#20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_bill_hdemo_sk#3] +Right keys [1]: [hd_demo_sk#20] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [8]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17] +Input [10]: [cs_ship_date_sk#1, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, hd_demo_sk#20] + +(36) ReusedExchange [Reuses operator id: 75] +Output [3]: [d_date_sk#22, d_date#23, d_week_seq#24] + +(37) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#8] +Right keys [1]: [d_date_sk#22] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 10] +Output [9]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24] +Input [11]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date_sk#22, d_date#23, d_week_seq#24] + +(39) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#25, d_week_seq#26] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_week_seq), IsNotNull(d_date_sk)] +ReadSchema: struct + +(40) ColumnarToRow [codegen id : 7] +Input [2]: [d_date_sk#25, d_week_seq#26] + +(41) Filter [codegen id : 7] +Input [2]: [d_date_sk#25, d_week_seq#26] +Condition : (isnotnull(d_week_seq#26) AND isnotnull(d_date_sk#25)) + +(42) BroadcastExchange +Input [2]: [d_date_sk#25, d_week_seq#26] +Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, false] as bigint), 32) | (cast(input[0, int, false] as bigint) & 4294967295))),false), [plan_id=6] + +(43) BroadcastHashJoin [codegen id : 10] +Left keys [2]: [d_week_seq#24, inv_date_sk#13] +Right keys [2]: [d_week_seq#26, d_date_sk#25] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 10] +Output [8]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24] +Input [11]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24, d_date_sk#25, d_week_seq#26] + +(45) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#27, d_date#28] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), IsNotNull(d_date_sk)] +ReadSchema: struct + +(46) ColumnarToRow [codegen id : 8] +Input [2]: [d_date_sk#27, d_date#28] + +(47) Filter [codegen id : 8] +Input [2]: [d_date_sk#27, d_date#28] +Condition : (isnotnull(d_date#28) AND isnotnull(d_date_sk#27)) + +(48) BroadcastExchange +Input [2]: [d_date_sk#27, d_date#28] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] + +(49) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_ship_date_sk#1] +Right keys [1]: [d_date_sk#27] +Join type: Inner +Join condition: (d_date#28 > date_add(d_date#23, 5)) + +(50) Project [codegen id : 10] +Output [6]: [cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [10]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24, d_date_sk#27, d_date#28] + +(51) Scan parquet spark_catalog.default.promotion +Output [1]: [p_promo_sk#29] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_promo_sk)] +ReadSchema: struct + +(52) ColumnarToRow [codegen id : 9] +Input [1]: [p_promo_sk#29] + +(53) Filter [codegen id : 9] +Input [1]: [p_promo_sk#29] +Condition : isnotnull(p_promo_sk#29) + +(54) BroadcastExchange +Input [1]: [p_promo_sk#29] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(55) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_promo_sk#5] +Right keys [1]: [p_promo_sk#29] +Join type: LeftOuter +Join condition: None + +(56) Project [codegen id : 10] +Output [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [7]: [cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24, p_promo_sk#29] + +(57) Exchange +Input [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Arguments: hashpartitioning(cs_item_sk#4, cs_order_number#6, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(58) Sort [codegen id : 11] +Input [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Arguments: [cs_item_sk#4 ASC NULLS FIRST, cs_order_number#6 ASC NULLS FIRST], false, 0 + +(59) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(60) ColumnarToRow [codegen id : 12] +Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] + +(61) Filter [codegen id : 12] +Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Condition : (isnotnull(cr_item_sk#30) AND isnotnull(cr_order_number#31)) + +(62) Project [codegen id : 12] +Output [2]: [cr_item_sk#30, cr_order_number#31] +Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] + +(63) Exchange +Input [2]: [cr_item_sk#30, cr_order_number#31] +Arguments: hashpartitioning(cr_item_sk#30, cr_order_number#31, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(64) Sort [codegen id : 13] +Input [2]: [cr_item_sk#30, cr_order_number#31] +Arguments: [cr_item_sk#30 ASC NULLS FIRST, cr_order_number#31 ASC NULLS FIRST], false, 0 + +(65) SortMergeJoin [codegen id : 14] +Left keys [2]: [cs_item_sk#4, cs_order_number#6] +Right keys [2]: [cr_item_sk#30, cr_order_number#31] +Join type: LeftOuter +Join condition: None + +(66) Project [codegen id : 14] +Output [3]: [w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Input [7]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24, cr_item_sk#30, cr_order_number#31] + +(67) HashAggregate [codegen id : 14] +Input [3]: [w_warehouse_name#15, i_item_desc#17, d_week_seq#24] +Keys [3]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24] +Functions [1]: [partial_count(1)] +Aggregate Attributes [1]: [count#33] +Results [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] + +(68) Exchange +Input [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] +Arguments: hashpartitioning(i_item_desc#17, w_warehouse_name#15, d_week_seq#24, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(69) HashAggregate [codegen id : 15] +Input [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34] +Keys [3]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24] +Functions [1]: [count(1)] +Aggregate Attributes [1]: [count(1)#35] +Results [6]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count(1)#35 AS no_promo#36, count(1)#35 AS promo#37, count(1)#35 AS total_cnt#38] + +(70) TakeOrderedAndProject +Input [6]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, no_promo#36, promo#37, total_cnt#38] +Arguments: 100, [total_cnt#38 DESC NULLS LAST, i_item_desc#17 ASC NULLS FIRST, w_warehouse_name#15 ASC NULLS FIRST, d_week_seq#24 ASC NULLS FIRST], [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, no_promo#36, promo#37, total_cnt#38] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9 +BroadcastExchange (75) ++- * Project (74) + +- * Filter (73) + +- * ColumnarToRow (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk), IsNotNull(d_week_seq), IsNotNull(d_date)] +ReadSchema: struct + +(72) ColumnarToRow [codegen id : 1] +Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] + +(73) Filter [codegen id : 1] +Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Condition : ((((isnotnull(d_year#39) AND (d_year#39 = 2001)) AND isnotnull(d_date_sk#22)) AND isnotnull(d_week_seq#24)) AND isnotnull(d_date#23)) + +(74) Project [codegen id : 1] +Output [3]: [d_date_sk#22, d_date#23, d_week_seq#24] +Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] + +(75) BroadcastExchange +Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt new file mode 100644 index 000000000..59e1279ae --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt @@ -0,0 +1,116 @@ +TakeOrderedAndProject [total_cnt,i_item_desc,w_warehouse_name,d_week_seq,no_promo,promo] + WholeStageCodegen (15) + HashAggregate [i_item_desc,w_warehouse_name,d_week_seq,count] [count(1),no_promo,promo,total_cnt,count] + InputAdapter + Exchange [i_item_desc,w_warehouse_name,d_week_seq] #1 + WholeStageCodegen (14) + HashAggregate [i_item_desc,w_warehouse_name,d_week_seq] [count,count] + Project [w_warehouse_name,i_item_desc,d_week_seq] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (11) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #2 + WholeStageCodegen (10) + Project [cs_item_sk,cs_order_number,w_warehouse_name,i_item_desc,d_week_seq] + BroadcastHashJoin [cs_promo_sk,p_promo_sk] + Project [cs_item_sk,cs_promo_sk,cs_order_number,w_warehouse_name,i_item_desc,d_week_seq] + BroadcastHashJoin [cs_ship_date_sk,d_date_sk,d_date,d_date] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,w_warehouse_name,i_item_desc,d_date,d_week_seq] + BroadcastHashJoin [d_week_seq,inv_date_sk,d_week_seq,d_date_sk] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,inv_date_sk,w_warehouse_name,i_item_desc,d_date,d_week_seq] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_ship_date_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_bill_hdemo_sk,hd_demo_sk] + Project [cs_ship_date_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name,i_item_desc] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_date_sk,w_warehouse_name] + BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] + Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_warehouse_sk,inv_date_sk] + BroadcastHashJoin [cs_item_sk,inv_item_sk,inv_quantity_on_hand,cs_quantity] + Filter [cs_quantity,cs_item_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_ship_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_quantity,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Project [d_date_sk,d_date,d_week_seq] + Filter [d_year,d_date_sk,d_week_seq,d_date] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_week_seq,d_year] + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (1) + Filter [inv_quantity_on_hand,inv_item_sk,inv_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + Filter [w_warehouse_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (3) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (4) + Project [cd_demo_sk] + Filter [cd_marital_status,cd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (5) + Project [hd_demo_sk] + Filter [hd_buy_potential,hd_demo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential] + InputAdapter + ReusedExchange [d_date_sk,d_date,d_week_seq] #3 + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (7) + Filter [d_week_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (9) + Filter [p_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.promotion [p_promo_sk] + InputAdapter + WholeStageCodegen (13) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #12 + WholeStageCodegen (12) + Project [cr_item_sk,cr_order_number] + Filter [cr_item_sk,cr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt new file mode 100644 index 000000000..a2f00f500 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt @@ -0,0 +1,477 @@ +== Physical Plan == +TakeOrderedAndProject (71) ++- * Project (70) + +- * BroadcastHashJoin Inner BuildRight (69) + :- * Project (52) + : +- * BroadcastHashJoin Inner BuildRight (51) + : :- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Filter (16) + : : : +- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (9) + : : : : +- * BroadcastHashJoin Inner BuildRight (8) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.customer (1) + : : : : +- BroadcastExchange (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.store_sales (4) + : : : +- ReusedExchange (10) + : : +- BroadcastExchange (32) + : : +- * HashAggregate (31) + : : +- Exchange (30) + : : +- * HashAggregate (29) + : : +- * Project (28) + : : +- * BroadcastHashJoin Inner BuildRight (27) + : : :- * Project (25) + : : : +- * BroadcastHashJoin Inner BuildRight (24) + : : : :- * Filter (19) + : : : : +- * ColumnarToRow (18) + : : : : +- CometScan parquet spark_catalog.default.customer (17) + : : : +- BroadcastExchange (23) + : : : +- * Filter (22) + : : : +- * ColumnarToRow (21) + : : : +- CometScan parquet spark_catalog.default.store_sales (20) + : : +- ReusedExchange (26) + : +- BroadcastExchange (50) + : +- * Filter (49) + : +- * HashAggregate (48) + : +- Exchange (47) + : +- * HashAggregate (46) + : +- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (42) + : : +- * BroadcastHashJoin Inner BuildRight (41) + : : :- * Filter (36) + : : : +- * ColumnarToRow (35) + : : : +- CometScan parquet spark_catalog.default.customer (34) + : : +- BroadcastExchange (40) + : : +- * Filter (39) + : : +- * ColumnarToRow (38) + : : +- CometScan parquet spark_catalog.default.web_sales (37) + : +- ReusedExchange (43) + +- BroadcastExchange (68) + +- * HashAggregate (67) + +- Exchange (66) + +- * HashAggregate (65) + +- * Project (64) + +- * BroadcastHashJoin Inner BuildRight (63) + :- * Project (61) + : +- * BroadcastHashJoin Inner BuildRight (60) + : :- * Filter (55) + : : +- * ColumnarToRow (54) + : : +- CometScan parquet spark_catalog.default.customer (53) + : +- BroadcastExchange (59) + : +- * Filter (58) + : +- * ColumnarToRow (57) + : +- CometScan parquet spark_catalog.default.web_sales (56) + +- ReusedExchange (62) + + +(1) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] + +(3) Filter [codegen id : 3] +Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) + +(4) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] + +(6) Filter [codegen id : 1] +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Condition : isnotnull(ss_customer_sk#5) + +(7) BroadcastExchange +Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [c_customer_sk#1] +Right keys [1]: [ss_customer_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, ss_sold_date_sk#7] +Input [7]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] + +(10) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#9, d_year#10] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#9] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, d_year#10] +Input [7]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, ss_sold_date_sk#7, d_date_sk#9, d_year#10] + +(13) HashAggregate [codegen id : 3] +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, ss_net_paid#6, d_year#10] +Keys [4]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#6))] +Aggregate Attributes [1]: [sum#11] +Results [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] + +(14) Exchange +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] +Arguments: hashpartitioning(c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 16] +Input [5]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10, sum#12] +Keys [4]: [c_customer_id#2, c_first_name#3, c_last_name#4, d_year#10] +Functions [1]: [sum(UnscaledValue(ss_net_paid#6))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#6))#13] +Results [2]: [c_customer_id#2 AS customer_id#14, MakeDecimal(sum(UnscaledValue(ss_net_paid#6))#13,17,2) AS year_total#15] + +(16) Filter [codegen id : 16] +Input [2]: [customer_id#14, year_total#15] +Condition : (isnotnull(year_total#15) AND (year_total#15 > 0.00)) + +(17) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 6] +Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] + +(19) Filter [codegen id : 6] +Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] +Condition : (isnotnull(c_customer_sk#16) AND isnotnull(c_customer_id#17)) + +(20) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#22), dynamicpruningexpression(ss_sold_date_sk#22 IN dynamicpruning#23)] +PushedFilters: [IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(21) ColumnarToRow [codegen id : 4] +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] + +(22) Filter [codegen id : 4] +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Condition : isnotnull(ss_customer_sk#20) + +(23) BroadcastExchange +Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(24) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [c_customer_sk#16] +Right keys [1]: [ss_customer_sk#20] +Join type: Inner +Join condition: None + +(25) Project [codegen id : 6] +Output [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, ss_sold_date_sk#22] +Input [7]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19, ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] + +(26) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#24, d_year#25] + +(27) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#22] +Right keys [1]: [d_date_sk#24] +Join type: Inner +Join condition: None + +(28) Project [codegen id : 6] +Output [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, d_year#25] +Input [7]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, ss_sold_date_sk#22, d_date_sk#24, d_year#25] + +(29) HashAggregate [codegen id : 6] +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, ss_net_paid#21, d_year#25] +Keys [4]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25] +Functions [1]: [partial_sum(UnscaledValue(ss_net_paid#21))] +Aggregate Attributes [1]: [sum#26] +Results [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] + +(30) Exchange +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] +Arguments: hashpartitioning(c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(31) HashAggregate [codegen id : 7] +Input [5]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25, sum#27] +Keys [4]: [c_customer_id#17, c_first_name#18, c_last_name#19, d_year#25] +Functions [1]: [sum(UnscaledValue(ss_net_paid#21))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_paid#21))#13] +Results [4]: [c_customer_id#17 AS customer_id#28, c_first_name#18 AS customer_first_name#29, c_last_name#19 AS customer_last_name#30, MakeDecimal(sum(UnscaledValue(ss_net_paid#21))#13,17,2) AS year_total#31] + +(32) BroadcastExchange +Input [4]: [customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=5] + +(33) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#28] +Join type: Inner +Join condition: None + +(34) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(35) ColumnarToRow [codegen id : 10] +Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] + +(36) Filter [codegen id : 10] +Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] +Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_customer_id#33)) + +(37) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#38), dynamicpruningexpression(ws_sold_date_sk#38 IN dynamicpruning#39)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(38) ColumnarToRow [codegen id : 8] +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] + +(39) Filter [codegen id : 8] +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Condition : isnotnull(ws_bill_customer_sk#36) + +(40) BroadcastExchange +Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] + +(41) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [c_customer_sk#32] +Right keys [1]: [ws_bill_customer_sk#36] +Join type: Inner +Join condition: None + +(42) Project [codegen id : 10] +Output [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, ws_sold_date_sk#38] +Input [7]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35, ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] + +(43) ReusedExchange [Reuses operator id: 75] +Output [2]: [d_date_sk#40, d_year#41] + +(44) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ws_sold_date_sk#38] +Right keys [1]: [d_date_sk#40] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 10] +Output [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, d_year#41] +Input [7]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, ws_sold_date_sk#38, d_date_sk#40, d_year#41] + +(46) HashAggregate [codegen id : 10] +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, ws_net_paid#37, d_year#41] +Keys [4]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#37))] +Aggregate Attributes [1]: [sum#42] +Results [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] + +(47) Exchange +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] +Arguments: hashpartitioning(c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(48) HashAggregate [codegen id : 11] +Input [5]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41, sum#43] +Keys [4]: [c_customer_id#33, c_first_name#34, c_last_name#35, d_year#41] +Functions [1]: [sum(UnscaledValue(ws_net_paid#37))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#37))#44] +Results [2]: [c_customer_id#33 AS customer_id#45, MakeDecimal(sum(UnscaledValue(ws_net_paid#37))#44,17,2) AS year_total#46] + +(49) Filter [codegen id : 11] +Input [2]: [customer_id#45, year_total#46] +Condition : (isnotnull(year_total#46) AND (year_total#46 > 0.00)) + +(50) BroadcastExchange +Input [2]: [customer_id#45, year_total#46] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=8] + +(51) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#45] +Join type: Inner +Join condition: None + +(52) Project [codegen id : 16] +Output [7]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, year_total#46] +Input [8]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, customer_id#45, year_total#46] + +(53) Scan parquet spark_catalog.default.customer +Output [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] +Batched: true +Location [not included in comparison]/{warehouse_dir}/customer] +PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] +ReadSchema: struct + +(54) ColumnarToRow [codegen id : 14] +Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] + +(55) Filter [codegen id : 14] +Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] +Condition : (isnotnull(c_customer_sk#47) AND isnotnull(c_customer_id#48)) + +(56) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#53), dynamicpruningexpression(ws_sold_date_sk#53 IN dynamicpruning#54)] +PushedFilters: [IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(57) ColumnarToRow [codegen id : 12] +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] + +(58) Filter [codegen id : 12] +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Condition : isnotnull(ws_bill_customer_sk#51) + +(59) BroadcastExchange +Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [c_customer_sk#47] +Right keys [1]: [ws_bill_customer_sk#51] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 14] +Output [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, ws_sold_date_sk#53] +Input [7]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50, ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] + +(62) ReusedExchange [Reuses operator id: 79] +Output [2]: [d_date_sk#55, d_year#56] + +(63) BroadcastHashJoin [codegen id : 14] +Left keys [1]: [ws_sold_date_sk#53] +Right keys [1]: [d_date_sk#55] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 14] +Output [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, d_year#56] +Input [7]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, ws_sold_date_sk#53, d_date_sk#55, d_year#56] + +(65) HashAggregate [codegen id : 14] +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, ws_net_paid#52, d_year#56] +Keys [4]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#52))] +Aggregate Attributes [1]: [sum#57] +Results [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] + +(66) Exchange +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] +Arguments: hashpartitioning(c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(67) HashAggregate [codegen id : 15] +Input [5]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56, sum#58] +Keys [4]: [c_customer_id#48, c_first_name#49, c_last_name#50, d_year#56] +Functions [1]: [sum(UnscaledValue(ws_net_paid#52))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#52))#44] +Results [2]: [c_customer_id#48 AS customer_id#59, MakeDecimal(sum(UnscaledValue(ws_net_paid#52))#44,17,2) AS year_total#60] + +(68) BroadcastExchange +Input [2]: [customer_id#59, year_total#60] +Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=11] + +(69) BroadcastHashJoin [codegen id : 16] +Left keys [1]: [customer_id#14] +Right keys [1]: [customer_id#59] +Join type: Inner +Join condition: (CASE WHEN (year_total#46 > 0.00) THEN (year_total#60 / year_total#46) END > CASE WHEN (year_total#15 > 0.00) THEN (year_total#31 / year_total#15) END) + +(70) Project [codegen id : 16] +Output [3]: [customer_id#28, customer_first_name#29, customer_last_name#30] +Input [9]: [customer_id#14, year_total#15, customer_id#28, customer_first_name#29, customer_last_name#30, year_total#31, year_total#46, customer_id#59, year_total#60] + +(71) TakeOrderedAndProject +Input [3]: [customer_id#28, customer_first_name#29, customer_last_name#30] +Arguments: 100, [customer_first_name#29 ASC NULLS FIRST, customer_id#28 ASC NULLS FIRST, customer_last_name#30 ASC NULLS FIRST], [customer_id#28, customer_first_name#29, customer_last_name#30] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (75) ++- * Filter (74) + +- * ColumnarToRow (73) + +- CometScan parquet spark_catalog.default.date_dim (72) + + +(72) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#9, d_year#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(73) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#9, d_year#10] + +(74) Filter [codegen id : 1] +Input [2]: [d_date_sk#9, d_year#10] +Condition : (((isnotnull(d_year#10) AND (d_year#10 = 2001)) AND d_year#10 IN (2001,2002)) AND isnotnull(d_date_sk#9)) + +(75) BroadcastExchange +Input [2]: [d_date_sk#9, d_year#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] + +Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#22 IN dynamicpruning#23 +BroadcastExchange (79) ++- * Filter (78) + +- * ColumnarToRow (77) + +- CometScan parquet spark_catalog.default.date_dim (76) + + +(76) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#24, d_year#25] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] +ReadSchema: struct + +(77) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#24, d_year#25] + +(78) Filter [codegen id : 1] +Input [2]: [d_date_sk#24, d_year#25] +Condition : (((isnotnull(d_year#25) AND (d_year#25 = 2002)) AND d_year#25 IN (2001,2002)) AND isnotnull(d_date_sk#24)) + +(79) BroadcastExchange +Input [2]: [d_date_sk#24, d_year#25] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +Subquery:3 Hosting operator id = 37 Hosting Expression = ws_sold_date_sk#38 IN dynamicpruning#8 + +Subquery:4 Hosting operator id = 56 Hosting Expression = ws_sold_date_sk#53 IN dynamicpruning#23 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt new file mode 100644 index 000000000..9d6161f56 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt @@ -0,0 +1,122 @@ +TakeOrderedAndProject [customer_first_name,customer_id,customer_last_name] + WholeStageCodegen (16) + Project [customer_id,customer_first_name,customer_last_name] + BroadcastHashJoin [customer_id,customer_id,year_total,year_total,year_total,year_total] + Project [customer_id,year_total,customer_id,customer_first_name,customer_last_name,year_total,year_total] + BroadcastHashJoin [customer_id,customer_id] + BroadcastHashJoin [customer_id,customer_id] + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ss_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #1 + WholeStageCodegen (3) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ss_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #2 + WholeStageCodegen (1) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #4 + WholeStageCodegen (7) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ss_net_paid)),customer_id,customer_first_name,customer_last_name,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #5 + WholeStageCodegen (6) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ss_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ss_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (4) + Filter [ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #7 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + Filter [year_total] + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ws_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #9 + WholeStageCodegen (10) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ws_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #10 + WholeStageCodegen (8) + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + BroadcastExchange #11 + WholeStageCodegen (15) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,sum] [sum(UnscaledValue(ws_net_paid)),customer_id,year_total,sum] + InputAdapter + Exchange [c_customer_id,c_first_name,c_last_name,d_year] #12 + WholeStageCodegen (14) + HashAggregate [c_customer_id,c_first_name,c_last_name,d_year,ws_net_paid] [sum,sum] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] + BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] + Filter [c_customer_sk,c_customer_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (12) + Filter [ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [d_date_sk,d_year] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt new file mode 100644 index 000000000..e52462afa --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt @@ -0,0 +1,779 @@ +== Physical Plan == +TakeOrderedAndProject (129) ++- * Project (128) + +- * SortMergeJoin Inner (127) + :- * Sort (71) + : +- Exchange (70) + : +- * Filter (69) + : +- * HashAggregate (68) + : +- Exchange (67) + : +- * HashAggregate (66) + : +- * HashAggregate (65) + : +- Exchange (64) + : +- * HashAggregate (63) + : +- Union (62) + : :- * Project (23) + : : +- * SortMergeJoin LeftOuter (22) + : : :- * Sort (15) + : : : +- Exchange (14) + : : : +- * Project (13) + : : : +- * BroadcastHashJoin Inner BuildRight (12) + : : : :- * Project (10) + : : : : +- * BroadcastHashJoin Inner BuildRight (9) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : +- BroadcastExchange (8) + : : : : +- * Project (7) + : : : : +- * Filter (6) + : : : : +- * ColumnarToRow (5) + : : : : +- CometScan parquet spark_catalog.default.item (4) + : : : +- ReusedExchange (11) + : : +- * Sort (21) + : : +- Exchange (20) + : : +- * Project (19) + : : +- * Filter (18) + : : +- * ColumnarToRow (17) + : : +- CometScan parquet spark_catalog.default.catalog_returns (16) + : :- * Project (42) + : : +- * SortMergeJoin LeftOuter (41) + : : :- * Sort (34) + : : : +- Exchange (33) + : : : +- * Project (32) + : : : +- * BroadcastHashJoin Inner BuildRight (31) + : : : :- * Project (29) + : : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : : :- * Filter (26) + : : : : : +- * ColumnarToRow (25) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (24) + : : : : +- ReusedExchange (27) + : : : +- ReusedExchange (30) + : : +- * Sort (40) + : : +- Exchange (39) + : : +- * Project (38) + : : +- * Filter (37) + : : +- * ColumnarToRow (36) + : : +- CometScan parquet spark_catalog.default.store_returns (35) + : +- * Project (61) + : +- * SortMergeJoin LeftOuter (60) + : :- * Sort (53) + : : +- Exchange (52) + : : +- * Project (51) + : : +- * BroadcastHashJoin Inner BuildRight (50) + : : :- * Project (48) + : : : +- * BroadcastHashJoin Inner BuildRight (47) + : : : :- * Filter (45) + : : : : +- * ColumnarToRow (44) + : : : : +- CometScan parquet spark_catalog.default.web_sales (43) + : : : +- ReusedExchange (46) + : : +- ReusedExchange (49) + : +- * Sort (59) + : +- Exchange (58) + : +- * Project (57) + : +- * Filter (56) + : +- * ColumnarToRow (55) + : +- CometScan parquet spark_catalog.default.web_returns (54) + +- * Sort (126) + +- Exchange (125) + +- * Filter (124) + +- * HashAggregate (123) + +- Exchange (122) + +- * HashAggregate (121) + +- * HashAggregate (120) + +- Exchange (119) + +- * HashAggregate (118) + +- Union (117) + :- * Project (86) + : +- * SortMergeJoin LeftOuter (85) + : :- * Sort (82) + : : +- Exchange (81) + : : +- * Project (80) + : : +- * BroadcastHashJoin Inner BuildRight (79) + : : :- * Project (77) + : : : +- * BroadcastHashJoin Inner BuildRight (76) + : : : :- * Filter (74) + : : : : +- * ColumnarToRow (73) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (72) + : : : +- ReusedExchange (75) + : : +- ReusedExchange (78) + : +- * Sort (84) + : +- ReusedExchange (83) + :- * Project (101) + : +- * SortMergeJoin LeftOuter (100) + : :- * Sort (97) + : : +- Exchange (96) + : : +- * Project (95) + : : +- * BroadcastHashJoin Inner BuildRight (94) + : : :- * Project (92) + : : : +- * BroadcastHashJoin Inner BuildRight (91) + : : : :- * Filter (89) + : : : : +- * ColumnarToRow (88) + : : : : +- CometScan parquet spark_catalog.default.store_sales (87) + : : : +- ReusedExchange (90) + : : +- ReusedExchange (93) + : +- * Sort (99) + : +- ReusedExchange (98) + +- * Project (116) + +- * SortMergeJoin LeftOuter (115) + :- * Sort (112) + : +- Exchange (111) + : +- * Project (110) + : +- * BroadcastHashJoin Inner BuildRight (109) + : :- * Project (107) + : : +- * BroadcastHashJoin Inner BuildRight (106) + : : :- * Filter (104) + : : : +- * ColumnarToRow (103) + : : : +- CometScan parquet spark_catalog.default.web_sales (102) + : : +- ReusedExchange (105) + : +- ReusedExchange (108) + +- * Sort (114) + +- ReusedExchange (113) + + +(1) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sold_date_sk#5 IN dynamicpruning#6)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] + +(3) Filter [codegen id : 3] +Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] +Condition : isnotnull(cs_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Books ), IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id), IsNotNull(i_manufact_id)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] + +(6) Filter [codegen id : 1] +Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Condition : ((((((isnotnull(i_category#11) AND (i_category#11 = Books )) AND isnotnull(i_item_sk#7)) AND isnotnull(i_brand_id#8)) AND isnotnull(i_class_id#9)) AND isnotnull(i_category_id#10)) AND isnotnull(i_manufact_id#12)) + +(7) Project [codegen id : 1] +Output [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] + +(8) BroadcastExchange +Input [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] + +(9) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_item_sk#1] +Right keys [1]: [i_item_sk#7] +Join type: Inner +Join condition: None + +(10) Project [codegen id : 3] +Output [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Input [10]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] + +(11) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#13, d_year#14] + +(12) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [cs_sold_date_sk#5] +Right keys [1]: [d_date_sk#13] +Join type: Inner +Join condition: None + +(13) Project [codegen id : 3] +Output [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Input [11]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_date_sk#13, d_year#14] + +(14) Exchange +Input [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Arguments: hashpartitioning(cs_order_number#2, cs_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) Sort [codegen id : 4] +Input [9]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14] +Arguments: [cs_order_number#2 ASC NULLS FIRST, cs_item_sk#1 ASC NULLS FIRST], false, 0 + +(16) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 5] +Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] + +(18) Filter [codegen id : 5] +Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Condition : (isnotnull(cr_order_number#16) AND isnotnull(cr_item_sk#15)) + +(19) Project [codegen id : 5] +Output [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] + +(20) Exchange +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +Arguments: hashpartitioning(cr_order_number#16, cr_item_sk#15, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(21) Sort [codegen id : 6] +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +Arguments: [cr_order_number#16 ASC NULLS FIRST, cr_item_sk#15 ASC NULLS FIRST], false, 0 + +(22) SortMergeJoin [codegen id : 7] +Left keys [2]: [cs_order_number#2, cs_item_sk#1] +Right keys [2]: [cr_order_number#16, cr_item_sk#15] +Join type: LeftOuter +Join condition: None + +(23) Project [codegen id : 7] +Output [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, (cs_quantity#3 - coalesce(cr_return_quantity#17, 0)) AS sales_cnt#20, (cs_ext_sales_price#4 - coalesce(cr_return_amount#18, 0.00)) AS sales_amt#21] +Input [13]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, d_year#14, cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] + +(24) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_sold_date_sk#26 IN dynamicpruning#27)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(25) ColumnarToRow [codegen id : 10] +Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] + +(26) Filter [codegen id : 10] +Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Condition : isnotnull(ss_item_sk#22) + +(27) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#28, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] + +(28) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_item_sk#22] +Right keys [1]: [i_item_sk#28] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 10] +Output [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] +Input [10]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_item_sk#28, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] + +(30) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#33, d_year#34] + +(31) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [ss_sold_date_sk#26] +Right keys [1]: [d_date_sk#33] +Join type: Inner +Join condition: None + +(32) Project [codegen id : 10] +Output [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Input [11]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_date_sk#33, d_year#34] + +(33) Exchange +Input [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Arguments: hashpartitioning(ss_ticket_number#23, ss_item_sk#22, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(34) Sort [codegen id : 11] +Input [9]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34] +Arguments: [ss_ticket_number#23 ASC NULLS FIRST, ss_item_sk#22 ASC NULLS FIRST], false, 0 + +(35) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(36) ColumnarToRow [codegen id : 12] +Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] + +(37) Filter [codegen id : 12] +Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Condition : (isnotnull(sr_ticket_number#36) AND isnotnull(sr_item_sk#35)) + +(38) Project [codegen id : 12] +Output [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] + +(39) Exchange +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +Arguments: hashpartitioning(sr_ticket_number#36, sr_item_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(40) Sort [codegen id : 13] +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +Arguments: [sr_ticket_number#36 ASC NULLS FIRST, sr_item_sk#35 ASC NULLS FIRST], false, 0 + +(41) SortMergeJoin [codegen id : 14] +Left keys [2]: [ss_ticket_number#23, ss_item_sk#22] +Right keys [2]: [sr_ticket_number#36, sr_item_sk#35] +Join type: LeftOuter +Join condition: None + +(42) Project [codegen id : 14] +Output [7]: [d_year#34, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, (ss_quantity#24 - coalesce(sr_return_quantity#37, 0)) AS sales_cnt#40, (ss_ext_sales_price#25 - coalesce(sr_return_amt#38, 0.00)) AS sales_amt#41] +Input [13]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32, d_year#34, sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] + +(43) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#46), dynamicpruningexpression(ws_sold_date_sk#46 IN dynamicpruning#47)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(44) ColumnarToRow [codegen id : 17] +Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] + +(45) Filter [codegen id : 17] +Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] +Condition : isnotnull(ws_item_sk#42) + +(46) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#48, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] + +(47) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_item_sk#42] +Right keys [1]: [i_item_sk#48] +Join type: Inner +Join condition: None + +(48) Project [codegen id : 17] +Output [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] +Input [10]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_item_sk#48, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] + +(49) ReusedExchange [Reuses operator id: 133] +Output [2]: [d_date_sk#53, d_year#54] + +(50) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#46] +Right keys [1]: [d_date_sk#53] +Join type: Inner +Join condition: None + +(51) Project [codegen id : 17] +Output [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Input [11]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_date_sk#53, d_year#54] + +(52) Exchange +Input [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Arguments: hashpartitioning(ws_order_number#43, ws_item_sk#42, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(53) Sort [codegen id : 18] +Input [9]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54] +Arguments: [ws_order_number#43 ASC NULLS FIRST, ws_item_sk#42 ASC NULLS FIRST], false, 0 + +(54) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(55) ColumnarToRow [codegen id : 19] +Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] + +(56) Filter [codegen id : 19] +Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Condition : (isnotnull(wr_order_number#56) AND isnotnull(wr_item_sk#55)) + +(57) Project [codegen id : 19] +Output [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] + +(58) Exchange +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +Arguments: hashpartitioning(wr_order_number#56, wr_item_sk#55, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(59) Sort [codegen id : 20] +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +Arguments: [wr_order_number#56 ASC NULLS FIRST, wr_item_sk#55 ASC NULLS FIRST], false, 0 + +(60) SortMergeJoin [codegen id : 21] +Left keys [2]: [ws_order_number#43, ws_item_sk#42] +Right keys [2]: [wr_order_number#56, wr_item_sk#55] +Join type: LeftOuter +Join condition: None + +(61) Project [codegen id : 21] +Output [7]: [d_year#54, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, (ws_quantity#44 - coalesce(wr_return_quantity#57, 0)) AS sales_cnt#60, (ws_ext_sales_price#45 - coalesce(wr_return_amt#58, 0.00)) AS sales_amt#61] +Input [13]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52, d_year#54, wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] + +(62) Union + +(63) HashAggregate [codegen id : 22] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] + +(64) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Arguments: hashpartitioning(d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(65) HashAggregate [codegen id : 23] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] + +(66) HashAggregate [codegen id : 23] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#20, sales_amt#21] +Keys [5]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Functions [2]: [partial_sum(sales_cnt#20), partial_sum(UnscaledValue(sales_amt#21))] +Aggregate Attributes [2]: [sum#62, sum#63] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] + +(67) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] +Arguments: hashpartitioning(d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(68) HashAggregate [codegen id : 24] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum#64, sum#65] +Keys [5]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Functions [2]: [sum(sales_cnt#20), sum(UnscaledValue(sales_amt#21))] +Aggregate Attributes [2]: [sum(sales_cnt#20)#66, sum(UnscaledValue(sales_amt#21))#67] +Results [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sum(sales_cnt#20)#66 AS sales_cnt#68, MakeDecimal(sum(UnscaledValue(sales_amt#21))#67,18,2) AS sales_amt#69] + +(69) Filter [codegen id : 24] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Condition : isnotnull(sales_cnt#68) + +(70) Exchange +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Arguments: hashpartitioning(i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(71) Sort [codegen id : 25] +Input [7]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69] +Arguments: [i_brand_id#8 ASC NULLS FIRST, i_class_id#9 ASC NULLS FIRST, i_category_id#10 ASC NULLS FIRST, i_manufact_id#12 ASC NULLS FIRST], false, 0 + +(72) Scan parquet spark_catalog.default.catalog_sales +Output [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#74), dynamicpruningexpression(cs_sold_date_sk#74 IN dynamicpruning#75)] +PushedFilters: [IsNotNull(cs_item_sk)] +ReadSchema: struct + +(73) ColumnarToRow [codegen id : 28] +Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] + +(74) Filter [codegen id : 28] +Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] +Condition : isnotnull(cs_item_sk#70) + +(75) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#76, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] + +(76) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [cs_item_sk#70] +Right keys [1]: [i_item_sk#76] +Join type: Inner +Join condition: None + +(77) Project [codegen id : 28] +Output [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Input [10]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_item_sk#76, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] + +(78) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#81, d_year#82] + +(79) BroadcastHashJoin [codegen id : 28] +Left keys [1]: [cs_sold_date_sk#74] +Right keys [1]: [d_date_sk#81] +Join type: Inner +Join condition: None + +(80) Project [codegen id : 28] +Output [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Input [11]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_date_sk#81, d_year#82] + +(81) Exchange +Input [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Arguments: hashpartitioning(cs_order_number#71, cs_item_sk#70, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(82) Sort [codegen id : 29] +Input [9]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82] +Arguments: [cs_order_number#71 ASC NULLS FIRST, cs_item_sk#70 ASC NULLS FIRST], false, 0 + +(83) ReusedExchange [Reuses operator id: 20] +Output [4]: [cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] + +(84) Sort [codegen id : 31] +Input [4]: [cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] +Arguments: [cr_order_number#84 ASC NULLS FIRST, cr_item_sk#83 ASC NULLS FIRST], false, 0 + +(85) SortMergeJoin [codegen id : 32] +Left keys [2]: [cs_order_number#71, cs_item_sk#70] +Right keys [2]: [cr_order_number#84, cr_item_sk#83] +Join type: LeftOuter +Join condition: None + +(86) Project [codegen id : 32] +Output [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, (cs_quantity#72 - coalesce(cr_return_quantity#85, 0)) AS sales_cnt#87, (cs_ext_sales_price#73 - coalesce(cr_return_amount#86, 0.00)) AS sales_amt#88] +Input [13]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, d_year#82, cr_item_sk#83, cr_order_number#84, cr_return_quantity#85, cr_return_amount#86] + +(87) Scan parquet spark_catalog.default.store_sales +Output [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#93), dynamicpruningexpression(ss_sold_date_sk#93 IN dynamicpruning#94)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(88) ColumnarToRow [codegen id : 35] +Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] + +(89) Filter [codegen id : 35] +Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] +Condition : isnotnull(ss_item_sk#89) + +(90) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#95, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] + +(91) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ss_item_sk#89] +Right keys [1]: [i_item_sk#95] +Join type: Inner +Join condition: None + +(92) Project [codegen id : 35] +Output [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] +Input [10]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_item_sk#95, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] + +(93) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#100, d_year#101] + +(94) BroadcastHashJoin [codegen id : 35] +Left keys [1]: [ss_sold_date_sk#93] +Right keys [1]: [d_date_sk#100] +Join type: Inner +Join condition: None + +(95) Project [codegen id : 35] +Output [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Input [11]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_date_sk#100, d_year#101] + +(96) Exchange +Input [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Arguments: hashpartitioning(ss_ticket_number#90, ss_item_sk#89, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(97) Sort [codegen id : 36] +Input [9]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101] +Arguments: [ss_ticket_number#90 ASC NULLS FIRST, ss_item_sk#89 ASC NULLS FIRST], false, 0 + +(98) ReusedExchange [Reuses operator id: 39] +Output [4]: [sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] + +(99) Sort [codegen id : 38] +Input [4]: [sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] +Arguments: [sr_ticket_number#103 ASC NULLS FIRST, sr_item_sk#102 ASC NULLS FIRST], false, 0 + +(100) SortMergeJoin [codegen id : 39] +Left keys [2]: [ss_ticket_number#90, ss_item_sk#89] +Right keys [2]: [sr_ticket_number#103, sr_item_sk#102] +Join type: LeftOuter +Join condition: None + +(101) Project [codegen id : 39] +Output [7]: [d_year#101, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, (ss_quantity#91 - coalesce(sr_return_quantity#104, 0)) AS sales_cnt#106, (ss_ext_sales_price#92 - coalesce(sr_return_amt#105, 0.00)) AS sales_amt#107] +Input [13]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99, d_year#101, sr_item_sk#102, sr_ticket_number#103, sr_return_quantity#104, sr_return_amt#105] + +(102) Scan parquet spark_catalog.default.web_sales +Output [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#112), dynamicpruningexpression(ws_sold_date_sk#112 IN dynamicpruning#113)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(103) ColumnarToRow [codegen id : 42] +Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] + +(104) Filter [codegen id : 42] +Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] +Condition : isnotnull(ws_item_sk#108) + +(105) ReusedExchange [Reuses operator id: 8] +Output [5]: [i_item_sk#114, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] + +(106) BroadcastHashJoin [codegen id : 42] +Left keys [1]: [ws_item_sk#108] +Right keys [1]: [i_item_sk#114] +Join type: Inner +Join condition: None + +(107) Project [codegen id : 42] +Output [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] +Input [10]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_item_sk#114, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] + +(108) ReusedExchange [Reuses operator id: 137] +Output [2]: [d_date_sk#119, d_year#120] + +(109) BroadcastHashJoin [codegen id : 42] +Left keys [1]: [ws_sold_date_sk#112] +Right keys [1]: [d_date_sk#119] +Join type: Inner +Join condition: None + +(110) Project [codegen id : 42] +Output [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Input [11]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_date_sk#119, d_year#120] + +(111) Exchange +Input [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Arguments: hashpartitioning(ws_order_number#109, ws_item_sk#108, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(112) Sort [codegen id : 43] +Input [9]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120] +Arguments: [ws_order_number#109 ASC NULLS FIRST, ws_item_sk#108 ASC NULLS FIRST], false, 0 + +(113) ReusedExchange [Reuses operator id: 58] +Output [4]: [wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] + +(114) Sort [codegen id : 45] +Input [4]: [wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] +Arguments: [wr_order_number#122 ASC NULLS FIRST, wr_item_sk#121 ASC NULLS FIRST], false, 0 + +(115) SortMergeJoin [codegen id : 46] +Left keys [2]: [ws_order_number#109, ws_item_sk#108] +Right keys [2]: [wr_order_number#122, wr_item_sk#121] +Join type: LeftOuter +Join condition: None + +(116) Project [codegen id : 46] +Output [7]: [d_year#120, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, (ws_quantity#110 - coalesce(wr_return_quantity#123, 0)) AS sales_cnt#125, (ws_ext_sales_price#111 - coalesce(wr_return_amt#124, 0.00)) AS sales_amt#126] +Input [13]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118, d_year#120, wr_item_sk#121, wr_order_number#122, wr_return_quantity#123, wr_return_amt#124] + +(117) Union + +(118) HashAggregate [codegen id : 47] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] + +(119) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Arguments: hashpartitioning(d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(120) HashAggregate [codegen id : 48] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Functions: [] +Aggregate Attributes: [] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] + +(121) HashAggregate [codegen id : 48] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#87, sales_amt#88] +Keys [5]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Functions [2]: [partial_sum(sales_cnt#87), partial_sum(UnscaledValue(sales_amt#88))] +Aggregate Attributes [2]: [sum#127, sum#128] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] + +(122) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] +Arguments: hashpartitioning(d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(123) HashAggregate [codegen id : 49] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum#129, sum#130] +Keys [5]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Functions [2]: [sum(sales_cnt#87), sum(UnscaledValue(sales_amt#88))] +Aggregate Attributes [2]: [sum(sales_cnt#87)#66, sum(UnscaledValue(sales_amt#88))#67] +Results [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sum(sales_cnt#87)#66 AS sales_cnt#131, MakeDecimal(sum(UnscaledValue(sales_amt#88))#67,18,2) AS sales_amt#132] + +(124) Filter [codegen id : 49] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Condition : isnotnull(sales_cnt#131) + +(125) Exchange +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Arguments: hashpartitioning(i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, 5), ENSURE_REQUIREMENTS, [plan_id=16] + +(126) Sort [codegen id : 50] +Input [7]: [d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] +Arguments: [i_brand_id#77 ASC NULLS FIRST, i_class_id#78 ASC NULLS FIRST, i_category_id#79 ASC NULLS FIRST, i_manufact_id#80 ASC NULLS FIRST], false, 0 + +(127) SortMergeJoin [codegen id : 51] +Left keys [4]: [i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +Right keys [4]: [i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] +Join type: Inner +Join condition: ((cast(sales_cnt#68 as decimal(17,2)) / cast(sales_cnt#131 as decimal(17,2))) < 0.90000000000000000000) + +(128) Project [codegen id : 51] +Output [10]: [d_year#82 AS prev_year#133, d_year#14 AS year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#131 AS prev_yr_cnt#135, sales_cnt#68 AS curr_yr_cnt#136, (sales_cnt#68 - sales_cnt#131) AS sales_cnt_diff#137, (sales_amt#69 - sales_amt#132) AS sales_amt_diff#138] +Input [14]: [d_year#14, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, sales_cnt#68, sales_amt#69, d_year#82, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80, sales_cnt#131, sales_amt#132] + +(129) TakeOrderedAndProject +Input [10]: [prev_year#133, year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, prev_yr_cnt#135, curr_yr_cnt#136, sales_cnt_diff#137, sales_amt_diff#138] +Arguments: 100, [sales_cnt_diff#137 ASC NULLS FIRST, sales_amt_diff#138 ASC NULLS FIRST], [prev_year#133, year#134, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12, prev_yr_cnt#135, curr_yr_cnt#136, sales_cnt_diff#137, sales_amt_diff#138] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 +BroadcastExchange (133) ++- * Filter (132) + +- * ColumnarToRow (131) + +- CometScan parquet spark_catalog.default.date_dim (130) + + +(130) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#13, d_year#14] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] +ReadSchema: struct + +(131) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#13, d_year#14] + +(132) Filter [codegen id : 1] +Input [2]: [d_date_sk#13, d_year#14] +Condition : ((isnotnull(d_year#14) AND (d_year#14 = 2002)) AND isnotnull(d_date_sk#13)) + +(133) BroadcastExchange +Input [2]: [d_date_sk#13, d_year#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=17] + +Subquery:2 Hosting operator id = 24 Hosting Expression = ss_sold_date_sk#26 IN dynamicpruning#6 + +Subquery:3 Hosting operator id = 43 Hosting Expression = ws_sold_date_sk#46 IN dynamicpruning#6 + +Subquery:4 Hosting operator id = 72 Hosting Expression = cs_sold_date_sk#74 IN dynamicpruning#75 +BroadcastExchange (137) ++- * Filter (136) + +- * ColumnarToRow (135) + +- CometScan parquet spark_catalog.default.date_dim (134) + + +(134) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#81, d_year#82] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] +ReadSchema: struct + +(135) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#81, d_year#82] + +(136) Filter [codegen id : 1] +Input [2]: [d_date_sk#81, d_year#82] +Condition : ((isnotnull(d_year#82) AND (d_year#82 = 2001)) AND isnotnull(d_date_sk#81)) + +(137) BroadcastExchange +Input [2]: [d_date_sk#81, d_year#82] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=18] + +Subquery:5 Hosting operator id = 87 Hosting Expression = ss_sold_date_sk#93 IN dynamicpruning#75 + +Subquery:6 Hosting operator id = 102 Hosting Expression = ws_sold_date_sk#112 IN dynamicpruning#75 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt new file mode 100644 index 000000000..3a7ec65a0 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt @@ -0,0 +1,240 @@ +TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i_class_id,i_category_id,i_manufact_id,prev_yr_cnt,curr_yr_cnt] + WholeStageCodegen (51) + Project [d_year,d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_cnt,sales_amt,sales_amt] + SortMergeJoin [i_brand_id,i_class_id,i_category_id,i_manufact_id,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_cnt] + InputAdapter + WholeStageCodegen (25) + Sort [i_brand_id,i_class_id,i_category_id,i_manufact_id] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id,i_manufact_id] #1 + WholeStageCodegen (24) + Filter [sales_cnt] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sum,sum] [sum(sales_cnt),sum(UnscaledValue(sales_amt)),sales_cnt,sales_amt,sum,sum] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id] #2 + WholeStageCodegen (23) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] [sum,sum,sum,sum] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] #3 + WholeStageCodegen (22) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Union + WholeStageCodegen (7) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,cs_quantity,cr_return_quantity,cs_ext_sales_price,cr_return_amount] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (4) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #4 + WholeStageCodegen (3) + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (1) + Project [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + Filter [i_category,i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id,i_category,i_manufact_id] + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (6) + Sort [cr_order_number,cr_item_sk] + InputAdapter + Exchange [cr_order_number,cr_item_sk] #7 + WholeStageCodegen (5) + Project [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + Filter [cr_order_number,cr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] + WholeStageCodegen (14) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ss_quantity,sr_return_quantity,ss_ext_sales_price,sr_return_amt] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (11) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #8 + WholeStageCodegen (10) + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (13) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #9 + WholeStageCodegen (12) + Project [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + Filter [sr_ticket_number,sr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] + WholeStageCodegen (21) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ws_quantity,wr_return_quantity,ws_ext_sales_price,wr_return_amt] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (18) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #10 + WholeStageCodegen (17) + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #5 + InputAdapter + WholeStageCodegen (20) + Sort [wr_order_number,wr_item_sk] + InputAdapter + Exchange [wr_order_number,wr_item_sk] #11 + WholeStageCodegen (19) + Project [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + Filter [wr_order_number,wr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] + InputAdapter + WholeStageCodegen (50) + Sort [i_brand_id,i_class_id,i_category_id,i_manufact_id] + InputAdapter + Exchange [i_brand_id,i_class_id,i_category_id,i_manufact_id] #12 + WholeStageCodegen (49) + Filter [sales_cnt] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sum,sum] [sum(sales_cnt),sum(UnscaledValue(sales_amt)),sales_cnt,sales_amt,sum,sum] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id] #13 + WholeStageCodegen (48) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] [sum,sum,sum,sum] + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Exchange [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] #14 + WholeStageCodegen (47) + HashAggregate [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,sales_cnt,sales_amt] + InputAdapter + Union + WholeStageCodegen (32) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,cs_quantity,cr_return_quantity,cs_ext_sales_price,cr_return_amount] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (29) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #15 + WholeStageCodegen (28) + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Filter [cs_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #16 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (31) + Sort [cr_order_number,cr_item_sk] + InputAdapter + ReusedExchange [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] #7 + WholeStageCodegen (39) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ss_quantity,sr_return_quantity,ss_ext_sales_price,sr_return_amt] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (36) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #17 + WholeStageCodegen (35) + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (38) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + ReusedExchange [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] #9 + WholeStageCodegen (46) + Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ws_quantity,wr_return_quantity,ws_ext_sales_price,wr_return_amt] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (43) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #18 + WholeStageCodegen (42) + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,i_brand_id,i_class_id,i_category_id,i_manufact_id,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #2 + InputAdapter + ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 + InputAdapter + ReusedExchange [d_date_sk,d_year] #16 + InputAdapter + WholeStageCodegen (45) + Sort [wr_order_number,wr_item_sk] + InputAdapter + ReusedExchange [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] #11 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt new file mode 100644 index 000000000..ec9c0ac47 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt @@ -0,0 +1,632 @@ +== Physical Plan == +TakeOrderedAndProject (98) ++- * HashAggregate (97) + +- Exchange (96) + +- * HashAggregate (95) + +- Union (94) + :- * HashAggregate (83) + : +- Exchange (82) + : +- * HashAggregate (81) + : +- Union (80) + : :- * Project (30) + : : +- * BroadcastHashJoin LeftOuter BuildRight (29) + : : :- * HashAggregate (15) + : : : +- Exchange (14) + : : : +- * HashAggregate (13) + : : : +- * Project (12) + : : : +- * BroadcastHashJoin Inner BuildRight (11) + : : : :- * Project (6) + : : : : +- * BroadcastHashJoin Inner BuildRight (5) + : : : : :- * Filter (3) + : : : : : +- * ColumnarToRow (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- ReusedExchange (4) + : : : +- BroadcastExchange (10) + : : : +- * Filter (9) + : : : +- * ColumnarToRow (8) + : : : +- CometScan parquet spark_catalog.default.store (7) + : : +- BroadcastExchange (28) + : : +- * HashAggregate (27) + : : +- Exchange (26) + : : +- * HashAggregate (25) + : : +- * Project (24) + : : +- * BroadcastHashJoin Inner BuildRight (23) + : : :- * Project (21) + : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : :- * Filter (18) + : : : : +- * ColumnarToRow (17) + : : : : +- CometScan parquet spark_catalog.default.store_returns (16) + : : : +- ReusedExchange (19) + : : +- ReusedExchange (22) + : :- * Project (49) + : : +- * BroadcastNestedLoopJoin Inner BuildLeft (48) + : : :- BroadcastExchange (39) + : : : +- * HashAggregate (38) + : : : +- Exchange (37) + : : : +- * HashAggregate (36) + : : : +- * Project (35) + : : : +- * BroadcastHashJoin Inner BuildRight (34) + : : : :- * ColumnarToRow (32) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (31) + : : : +- ReusedExchange (33) + : : +- * HashAggregate (47) + : : +- Exchange (46) + : : +- * HashAggregate (45) + : : +- * Project (44) + : : +- * BroadcastHashJoin Inner BuildRight (43) + : : :- * ColumnarToRow (41) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (40) + : : +- ReusedExchange (42) + : +- * Project (79) + : +- * BroadcastHashJoin LeftOuter BuildRight (78) + : :- * HashAggregate (64) + : : +- Exchange (63) + : : +- * HashAggregate (62) + : : +- * Project (61) + : : +- * BroadcastHashJoin Inner BuildRight (60) + : : :- * Project (55) + : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : :- * Filter (52) + : : : : +- * ColumnarToRow (51) + : : : : +- CometScan parquet spark_catalog.default.web_sales (50) + : : : +- ReusedExchange (53) + : : +- BroadcastExchange (59) + : : +- * Filter (58) + : : +- * ColumnarToRow (57) + : : +- CometScan parquet spark_catalog.default.web_page (56) + : +- BroadcastExchange (77) + : +- * HashAggregate (76) + : +- Exchange (75) + : +- * HashAggregate (74) + : +- * Project (73) + : +- * BroadcastHashJoin Inner BuildRight (72) + : :- * Project (70) + : : +- * BroadcastHashJoin Inner BuildRight (69) + : : :- * Filter (67) + : : : +- * ColumnarToRow (66) + : : : +- CometScan parquet spark_catalog.default.web_returns (65) + : : +- ReusedExchange (68) + : +- ReusedExchange (71) + :- * HashAggregate (88) + : +- Exchange (87) + : +- * HashAggregate (86) + : +- * HashAggregate (85) + : +- ReusedExchange (84) + +- * HashAggregate (93) + +- Exchange (92) + +- * HashAggregate (91) + +- * HashAggregate (90) + +- ReusedExchange (89) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)] +PushedFilters: [IsNotNull(ss_store_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] + +(3) Filter [codegen id : 3] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_store_sk#1) + +(4) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#6] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#4] +Right keys [1]: [d_date_sk#6] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [3]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3] +Input [5]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4, d_date_sk#6] + +(7) Scan parquet spark_catalog.default.store +Output [1]: [s_store_sk#7] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#7] + +(9) Filter [codegen id : 2] +Input [1]: [s_store_sk#7] +Condition : isnotnull(s_store_sk#7) + +(10) BroadcastExchange +Input [1]: [s_store_sk#7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_store_sk#1] +Right keys [1]: [s_store_sk#7] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] +Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] + +(13) HashAggregate [codegen id : 3] +Input [3]: [ss_ext_sales_price#2, ss_net_profit#3, s_store_sk#7] +Keys [1]: [s_store_sk#7] +Functions [2]: [partial_sum(UnscaledValue(ss_ext_sales_price#2)), partial_sum(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [2]: [sum#8, sum#9] +Results [3]: [s_store_sk#7, sum#10, sum#11] + +(14) Exchange +Input [3]: [s_store_sk#7, sum#10, sum#11] +Arguments: hashpartitioning(s_store_sk#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 8] +Input [3]: [s_store_sk#7, sum#10, sum#11] +Keys [1]: [s_store_sk#7] +Functions [2]: [sum(UnscaledValue(ss_ext_sales_price#2)), sum(UnscaledValue(ss_net_profit#3))] +Aggregate Attributes [2]: [sum(UnscaledValue(ss_ext_sales_price#2))#12, sum(UnscaledValue(ss_net_profit#3))#13] +Results [3]: [s_store_sk#7, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#12,17,2) AS sales#14, MakeDecimal(sum(UnscaledValue(ss_net_profit#3))#13,17,2) AS profit#15] + +(16) Scan parquet spark_catalog.default.store_returns +Output [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(sr_returned_date_sk#19), dynamicpruningexpression(sr_returned_date_sk#19 IN dynamicpruning#20)] +PushedFilters: [IsNotNull(sr_store_sk)] +ReadSchema: struct + +(17) ColumnarToRow [codegen id : 6] +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] + +(18) Filter [codegen id : 6] +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] +Condition : isnotnull(sr_store_sk#16) + +(19) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#21] + +(20) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sr_returned_date_sk#19] +Right keys [1]: [d_date_sk#21] +Join type: Inner +Join condition: None + +(21) Project [codegen id : 6] +Output [3]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18] +Input [5]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19, d_date_sk#21] + +(22) ReusedExchange [Reuses operator id: 10] +Output [1]: [s_store_sk#22] + +(23) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [sr_store_sk#16] +Right keys [1]: [s_store_sk#22] +Join type: Inner +Join condition: None + +(24) Project [codegen id : 6] +Output [3]: [sr_return_amt#17, sr_net_loss#18, s_store_sk#22] +Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, s_store_sk#22] + +(25) HashAggregate [codegen id : 6] +Input [3]: [sr_return_amt#17, sr_net_loss#18, s_store_sk#22] +Keys [1]: [s_store_sk#22] +Functions [2]: [partial_sum(UnscaledValue(sr_return_amt#17)), partial_sum(UnscaledValue(sr_net_loss#18))] +Aggregate Attributes [2]: [sum#23, sum#24] +Results [3]: [s_store_sk#22, sum#25, sum#26] + +(26) Exchange +Input [3]: [s_store_sk#22, sum#25, sum#26] +Arguments: hashpartitioning(s_store_sk#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(27) HashAggregate [codegen id : 7] +Input [3]: [s_store_sk#22, sum#25, sum#26] +Keys [1]: [s_store_sk#22] +Functions [2]: [sum(UnscaledValue(sr_return_amt#17)), sum(UnscaledValue(sr_net_loss#18))] +Aggregate Attributes [2]: [sum(UnscaledValue(sr_return_amt#17))#27, sum(UnscaledValue(sr_net_loss#18))#28] +Results [3]: [s_store_sk#22, MakeDecimal(sum(UnscaledValue(sr_return_amt#17))#27,17,2) AS returns#29, MakeDecimal(sum(UnscaledValue(sr_net_loss#18))#28,17,2) AS profit_loss#30] + +(28) BroadcastExchange +Input [3]: [s_store_sk#22, returns#29, profit_loss#30] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(29) BroadcastHashJoin [codegen id : 8] +Left keys [1]: [s_store_sk#7] +Right keys [1]: [s_store_sk#22] +Join type: LeftOuter +Join condition: None + +(30) Project [codegen id : 8] +Output [5]: [store channel AS channel#31, s_store_sk#7 AS id#32, sales#14, coalesce(returns#29, 0.00) AS returns#33, (profit#15 - coalesce(profit_loss#30, 0.00)) AS profit#34] +Input [6]: [s_store_sk#7, sales#14, profit#15, s_store_sk#22, returns#29, profit_loss#30] + +(31) Scan parquet spark_catalog.default.catalog_sales +Output [4]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#38), dynamicpruningexpression(cs_sold_date_sk#38 IN dynamicpruning#39)] +ReadSchema: struct + +(32) ColumnarToRow [codegen id : 10] +Input [4]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38] + +(33) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#40] + +(34) BroadcastHashJoin [codegen id : 10] +Left keys [1]: [cs_sold_date_sk#38] +Right keys [1]: [d_date_sk#40] +Join type: Inner +Join condition: None + +(35) Project [codegen id : 10] +Output [3]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37] +Input [5]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37, cs_sold_date_sk#38, d_date_sk#40] + +(36) HashAggregate [codegen id : 10] +Input [3]: [cs_call_center_sk#35, cs_ext_sales_price#36, cs_net_profit#37] +Keys [1]: [cs_call_center_sk#35] +Functions [2]: [partial_sum(UnscaledValue(cs_ext_sales_price#36)), partial_sum(UnscaledValue(cs_net_profit#37))] +Aggregate Attributes [2]: [sum#41, sum#42] +Results [3]: [cs_call_center_sk#35, sum#43, sum#44] + +(37) Exchange +Input [3]: [cs_call_center_sk#35, sum#43, sum#44] +Arguments: hashpartitioning(cs_call_center_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(38) HashAggregate [codegen id : 11] +Input [3]: [cs_call_center_sk#35, sum#43, sum#44] +Keys [1]: [cs_call_center_sk#35] +Functions [2]: [sum(UnscaledValue(cs_ext_sales_price#36)), sum(UnscaledValue(cs_net_profit#37))] +Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_sales_price#36))#45, sum(UnscaledValue(cs_net_profit#37))#46] +Results [3]: [cs_call_center_sk#35, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#36))#45,17,2) AS sales#47, MakeDecimal(sum(UnscaledValue(cs_net_profit#37))#46,17,2) AS profit#48] + +(39) BroadcastExchange +Input [3]: [cs_call_center_sk#35, sales#47, profit#48] +Arguments: IdentityBroadcastMode, [plan_id=6] + +(40) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cr_returned_date_sk#51), dynamicpruningexpression(cr_returned_date_sk#51 IN dynamicpruning#52)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 13] +Input [3]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] + +(42) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#53] + +(43) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [cr_returned_date_sk#51] +Right keys [1]: [d_date_sk#53] +Join type: Inner +Join condition: None + +(44) Project [codegen id : 13] +Output [2]: [cr_return_amount#49, cr_net_loss#50] +Input [4]: [cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51, d_date_sk#53] + +(45) HashAggregate [codegen id : 13] +Input [2]: [cr_return_amount#49, cr_net_loss#50] +Keys: [] +Functions [2]: [partial_sum(UnscaledValue(cr_return_amount#49)), partial_sum(UnscaledValue(cr_net_loss#50))] +Aggregate Attributes [2]: [sum#54, sum#55] +Results [2]: [sum#56, sum#57] + +(46) Exchange +Input [2]: [sum#56, sum#57] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=7] + +(47) HashAggregate +Input [2]: [sum#56, sum#57] +Keys: [] +Functions [2]: [sum(UnscaledValue(cr_return_amount#49)), sum(UnscaledValue(cr_net_loss#50))] +Aggregate Attributes [2]: [sum(UnscaledValue(cr_return_amount#49))#58, sum(UnscaledValue(cr_net_loss#50))#59] +Results [2]: [MakeDecimal(sum(UnscaledValue(cr_return_amount#49))#58,17,2) AS returns#60, MakeDecimal(sum(UnscaledValue(cr_net_loss#50))#59,17,2) AS profit_loss#61] + +(48) BroadcastNestedLoopJoin [codegen id : 14] +Join type: Inner +Join condition: None + +(49) Project [codegen id : 14] +Output [5]: [catalog channel AS channel#62, cs_call_center_sk#35 AS id#63, sales#47, returns#60, (profit#48 - profit_loss#61) AS profit#64] +Input [5]: [cs_call_center_sk#35, sales#47, profit#48, returns#60, profit_loss#61] + +(50) Scan parquet spark_catalog.default.web_sales +Output [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#68), dynamicpruningexpression(ws_sold_date_sk#68 IN dynamicpruning#69)] +PushedFilters: [IsNotNull(ws_web_page_sk)] +ReadSchema: struct + +(51) ColumnarToRow [codegen id : 17] +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] + +(52) Filter [codegen id : 17] +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] +Condition : isnotnull(ws_web_page_sk#65) + +(53) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#70] + +(54) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_sold_date_sk#68] +Right keys [1]: [d_date_sk#70] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 17] +Output [3]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67] +Input [5]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68, d_date_sk#70] + +(56) Scan parquet spark_catalog.default.web_page +Output [1]: [wp_web_page_sk#71] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_page] +PushedFilters: [IsNotNull(wp_web_page_sk)] +ReadSchema: struct + +(57) ColumnarToRow [codegen id : 16] +Input [1]: [wp_web_page_sk#71] + +(58) Filter [codegen id : 16] +Input [1]: [wp_web_page_sk#71] +Condition : isnotnull(wp_web_page_sk#71) + +(59) BroadcastExchange +Input [1]: [wp_web_page_sk#71] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] + +(60) BroadcastHashJoin [codegen id : 17] +Left keys [1]: [ws_web_page_sk#65] +Right keys [1]: [wp_web_page_sk#71] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 17] +Output [3]: [ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] +Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] + +(62) HashAggregate [codegen id : 17] +Input [3]: [ws_ext_sales_price#66, ws_net_profit#67, wp_web_page_sk#71] +Keys [1]: [wp_web_page_sk#71] +Functions [2]: [partial_sum(UnscaledValue(ws_ext_sales_price#66)), partial_sum(UnscaledValue(ws_net_profit#67))] +Aggregate Attributes [2]: [sum#72, sum#73] +Results [3]: [wp_web_page_sk#71, sum#74, sum#75] + +(63) Exchange +Input [3]: [wp_web_page_sk#71, sum#74, sum#75] +Arguments: hashpartitioning(wp_web_page_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(64) HashAggregate [codegen id : 22] +Input [3]: [wp_web_page_sk#71, sum#74, sum#75] +Keys [1]: [wp_web_page_sk#71] +Functions [2]: [sum(UnscaledValue(ws_ext_sales_price#66)), sum(UnscaledValue(ws_net_profit#67))] +Aggregate Attributes [2]: [sum(UnscaledValue(ws_ext_sales_price#66))#76, sum(UnscaledValue(ws_net_profit#67))#77] +Results [3]: [wp_web_page_sk#71, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#66))#76,17,2) AS sales#78, MakeDecimal(sum(UnscaledValue(ws_net_profit#67))#77,17,2) AS profit#79] + +(65) Scan parquet spark_catalog.default.web_returns +Output [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(wr_returned_date_sk#83), dynamicpruningexpression(wr_returned_date_sk#83 IN dynamicpruning#84)] +PushedFilters: [IsNotNull(wr_web_page_sk)] +ReadSchema: struct + +(66) ColumnarToRow [codegen id : 20] +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] + +(67) Filter [codegen id : 20] +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] +Condition : isnotnull(wr_web_page_sk#80) + +(68) ReusedExchange [Reuses operator id: 103] +Output [1]: [d_date_sk#85] + +(69) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [wr_returned_date_sk#83] +Right keys [1]: [d_date_sk#85] +Join type: Inner +Join condition: None + +(70) Project [codegen id : 20] +Output [3]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82] +Input [5]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83, d_date_sk#85] + +(71) ReusedExchange [Reuses operator id: 59] +Output [1]: [wp_web_page_sk#86] + +(72) BroadcastHashJoin [codegen id : 20] +Left keys [1]: [wr_web_page_sk#80] +Right keys [1]: [wp_web_page_sk#86] +Join type: Inner +Join condition: None + +(73) Project [codegen id : 20] +Output [3]: [wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] +Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] + +(74) HashAggregate [codegen id : 20] +Input [3]: [wr_return_amt#81, wr_net_loss#82, wp_web_page_sk#86] +Keys [1]: [wp_web_page_sk#86] +Functions [2]: [partial_sum(UnscaledValue(wr_return_amt#81)), partial_sum(UnscaledValue(wr_net_loss#82))] +Aggregate Attributes [2]: [sum#87, sum#88] +Results [3]: [wp_web_page_sk#86, sum#89, sum#90] + +(75) Exchange +Input [3]: [wp_web_page_sk#86, sum#89, sum#90] +Arguments: hashpartitioning(wp_web_page_sk#86, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(76) HashAggregate [codegen id : 21] +Input [3]: [wp_web_page_sk#86, sum#89, sum#90] +Keys [1]: [wp_web_page_sk#86] +Functions [2]: [sum(UnscaledValue(wr_return_amt#81)), sum(UnscaledValue(wr_net_loss#82))] +Aggregate Attributes [2]: [sum(UnscaledValue(wr_return_amt#81))#91, sum(UnscaledValue(wr_net_loss#82))#92] +Results [3]: [wp_web_page_sk#86, MakeDecimal(sum(UnscaledValue(wr_return_amt#81))#91,17,2) AS returns#93, MakeDecimal(sum(UnscaledValue(wr_net_loss#82))#92,17,2) AS profit_loss#94] + +(77) BroadcastExchange +Input [3]: [wp_web_page_sk#86, returns#93, profit_loss#94] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] + +(78) BroadcastHashJoin [codegen id : 22] +Left keys [1]: [wp_web_page_sk#71] +Right keys [1]: [wp_web_page_sk#86] +Join type: LeftOuter +Join condition: None + +(79) Project [codegen id : 22] +Output [5]: [web channel AS channel#95, wp_web_page_sk#71 AS id#96, sales#78, coalesce(returns#93, 0.00) AS returns#97, (profit#79 - coalesce(profit_loss#94, 0.00)) AS profit#98] +Input [6]: [wp_web_page_sk#71, sales#78, profit#79, wp_web_page_sk#86, returns#93, profit_loss#94] + +(80) Union + +(81) HashAggregate [codegen id : 23] +Input [5]: [channel#31, id#32, sales#14, returns#33, profit#34] +Keys [2]: [channel#31, id#32] +Functions [3]: [partial_sum(sales#14), partial_sum(returns#33), partial_sum(profit#34)] +Aggregate Attributes [6]: [sum#99, isEmpty#100, sum#101, isEmpty#102, sum#103, isEmpty#104] +Results [8]: [channel#31, id#32, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110] + +(82) Exchange +Input [8]: [channel#31, id#32, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110] +Arguments: hashpartitioning(channel#31, id#32, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(83) HashAggregate [codegen id : 24] +Input [8]: [channel#31, id#32, sum#105, isEmpty#106, sum#107, isEmpty#108, sum#109, isEmpty#110] +Keys [2]: [channel#31, id#32] +Functions [3]: [sum(sales#14), sum(returns#33), sum(profit#34)] +Aggregate Attributes [3]: [sum(sales#14)#111, sum(returns#33)#112, sum(profit#34)#113] +Results [5]: [channel#31, id#32, cast(sum(sales#14)#111 as decimal(37,2)) AS sales#114, cast(sum(returns#33)#112 as decimal(37,2)) AS returns#115, cast(sum(profit#34)#113 as decimal(38,2)) AS profit#116] + +(84) ReusedExchange [Reuses operator id: 82] +Output [8]: [channel#117, id#118, sum#119, isEmpty#120, sum#121, isEmpty#122, sum#123, isEmpty#124] + +(85) HashAggregate [codegen id : 48] +Input [8]: [channel#117, id#118, sum#119, isEmpty#120, sum#121, isEmpty#122, sum#123, isEmpty#124] +Keys [2]: [channel#117, id#118] +Functions [3]: [sum(sales#125), sum(returns#126), sum(profit#127)] +Aggregate Attributes [3]: [sum(sales#125)#111, sum(returns#126)#112, sum(profit#127)#113] +Results [4]: [channel#117, sum(sales#125)#111 AS sales#128, sum(returns#126)#112 AS returns#129, sum(profit#127)#113 AS profit#130] + +(86) HashAggregate [codegen id : 48] +Input [4]: [channel#117, sales#128, returns#129, profit#130] +Keys [1]: [channel#117] +Functions [3]: [partial_sum(sales#128), partial_sum(returns#129), partial_sum(profit#130)] +Aggregate Attributes [6]: [sum#131, isEmpty#132, sum#133, isEmpty#134, sum#135, isEmpty#136] +Results [7]: [channel#117, sum#137, isEmpty#138, sum#139, isEmpty#140, sum#141, isEmpty#142] + +(87) Exchange +Input [7]: [channel#117, sum#137, isEmpty#138, sum#139, isEmpty#140, sum#141, isEmpty#142] +Arguments: hashpartitioning(channel#117, 5), ENSURE_REQUIREMENTS, [plan_id=13] + +(88) HashAggregate [codegen id : 49] +Input [7]: [channel#117, sum#137, isEmpty#138, sum#139, isEmpty#140, sum#141, isEmpty#142] +Keys [1]: [channel#117] +Functions [3]: [sum(sales#128), sum(returns#129), sum(profit#130)] +Aggregate Attributes [3]: [sum(sales#128)#143, sum(returns#129)#144, sum(profit#130)#145] +Results [5]: [channel#117, null AS id#146, sum(sales#128)#143 AS sales#147, sum(returns#129)#144 AS returns#148, sum(profit#130)#145 AS profit#149] + +(89) ReusedExchange [Reuses operator id: 82] +Output [8]: [channel#150, id#151, sum#152, isEmpty#153, sum#154, isEmpty#155, sum#156, isEmpty#157] + +(90) HashAggregate [codegen id : 73] +Input [8]: [channel#150, id#151, sum#152, isEmpty#153, sum#154, isEmpty#155, sum#156, isEmpty#157] +Keys [2]: [channel#150, id#151] +Functions [3]: [sum(sales#158), sum(returns#159), sum(profit#160)] +Aggregate Attributes [3]: [sum(sales#158)#111, sum(returns#159)#112, sum(profit#160)#113] +Results [3]: [sum(sales#158)#111 AS sales#161, sum(returns#159)#112 AS returns#162, sum(profit#160)#113 AS profit#163] + +(91) HashAggregate [codegen id : 73] +Input [3]: [sales#161, returns#162, profit#163] +Keys: [] +Functions [3]: [partial_sum(sales#161), partial_sum(returns#162), partial_sum(profit#163)] +Aggregate Attributes [6]: [sum#164, isEmpty#165, sum#166, isEmpty#167, sum#168, isEmpty#169] +Results [6]: [sum#170, isEmpty#171, sum#172, isEmpty#173, sum#174, isEmpty#175] + +(92) Exchange +Input [6]: [sum#170, isEmpty#171, sum#172, isEmpty#173, sum#174, isEmpty#175] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=14] + +(93) HashAggregate [codegen id : 74] +Input [6]: [sum#170, isEmpty#171, sum#172, isEmpty#173, sum#174, isEmpty#175] +Keys: [] +Functions [3]: [sum(sales#161), sum(returns#162), sum(profit#163)] +Aggregate Attributes [3]: [sum(sales#161)#176, sum(returns#162)#177, sum(profit#163)#178] +Results [5]: [null AS channel#179, null AS id#180, sum(sales#161)#176 AS sales#181, sum(returns#162)#177 AS returns#182, sum(profit#163)#178 AS profit#183] + +(94) Union + +(95) HashAggregate [codegen id : 75] +Input [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Keys [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#31, id#32, sales#114, returns#115, profit#116] + +(96) Exchange +Input [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Arguments: hashpartitioning(channel#31, id#32, sales#114, returns#115, profit#116, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(97) HashAggregate [codegen id : 76] +Input [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Keys [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#31, id#32, sales#114, returns#115, profit#116] + +(98) TakeOrderedAndProject +Input [5]: [channel#31, id#32, sales#114, returns#115, profit#116] +Arguments: 100, [channel#31 ASC NULLS FIRST, id#32 ASC NULLS FIRST], [channel#31, id#32, sales#114, returns#115, profit#116] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 +BroadcastExchange (103) ++- * Project (102) + +- * Filter (101) + +- * ColumnarToRow (100) + +- CometScan parquet spark_catalog.default.date_dim (99) + + +(99) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#6, d_date#184] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1998-08-04), LessThanOrEqual(d_date,1998-09-03), IsNotNull(d_date_sk)] +ReadSchema: struct + +(100) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#6, d_date#184] + +(101) Filter [codegen id : 1] +Input [2]: [d_date_sk#6, d_date#184] +Condition : (((isnotnull(d_date#184) AND (d_date#184 >= 1998-08-04)) AND (d_date#184 <= 1998-09-03)) AND isnotnull(d_date_sk#6)) + +(102) Project [codegen id : 1] +Output [1]: [d_date_sk#6] +Input [2]: [d_date_sk#6, d_date#184] + +(103) BroadcastExchange +Input [1]: [d_date_sk#6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=16] + +Subquery:2 Hosting operator id = 16 Hosting Expression = sr_returned_date_sk#19 IN dynamicpruning#5 + +Subquery:3 Hosting operator id = 31 Hosting Expression = cs_sold_date_sk#38 IN dynamicpruning#5 + +Subquery:4 Hosting operator id = 40 Hosting Expression = cr_returned_date_sk#51 IN dynamicpruning#5 + +Subquery:5 Hosting operator id = 50 Hosting Expression = ws_sold_date_sk#68 IN dynamicpruning#5 + +Subquery:6 Hosting operator id = 65 Hosting Expression = wr_returned_date_sk#83 IN dynamicpruning#5 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt new file mode 100644 index 000000000..9b7a2b9ef --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt @@ -0,0 +1,168 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (76) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Exchange [channel,id,sales,returns,profit] #1 + WholeStageCodegen (75) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Union + WholeStageCodegen (24) + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id] #2 + WholeStageCodegen (23) + HashAggregate [channel,id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (8) + Project [s_store_sk,sales,returns,profit,profit_loss] + BroadcastHashJoin [s_store_sk,s_store_sk] + HashAggregate [s_store_sk,sum,sum] [sum(UnscaledValue(ss_ext_sales_price)),sum(UnscaledValue(ss_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [s_store_sk] #3 + WholeStageCodegen (3) + HashAggregate [s_store_sk,ss_ext_sales_price,ss_net_profit] [sum,sum,sum,sum] + Project [ss_ext_sales_price,ss_net_profit,s_store_sk] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_store_sk,ss_ext_sales_price,ss_net_profit] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Filter [ss_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk] + InputAdapter + BroadcastExchange #6 + WholeStageCodegen (7) + HashAggregate [s_store_sk,sum,sum] [sum(UnscaledValue(sr_return_amt)),sum(UnscaledValue(sr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange [s_store_sk] #7 + WholeStageCodegen (6) + HashAggregate [s_store_sk,sr_return_amt,sr_net_loss] [sum,sum,sum,sum] + Project [sr_return_amt,sr_net_loss,s_store_sk] + BroadcastHashJoin [sr_store_sk,s_store_sk] + Project [sr_store_sk,sr_return_amt,sr_net_loss] + BroadcastHashJoin [sr_returned_date_sk,d_date_sk] + Filter [sr_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + ReusedExchange [s_store_sk] #5 + WholeStageCodegen (14) + Project [cs_call_center_sk,sales,returns,profit,profit_loss] + BroadcastNestedLoopJoin + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (11) + HashAggregate [cs_call_center_sk,sum,sum] [sum(UnscaledValue(cs_ext_sales_price)),sum(UnscaledValue(cs_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [cs_call_center_sk] #9 + WholeStageCodegen (10) + HashAggregate [cs_call_center_sk,cs_ext_sales_price,cs_net_profit] [sum,sum,sum,sum] + Project [cs_call_center_sk,cs_ext_sales_price,cs_net_profit] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_call_center_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + HashAggregate [sum,sum] [sum(UnscaledValue(cr_return_amount)),sum(UnscaledValue(cr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange #10 + WholeStageCodegen (13) + HashAggregate [cr_return_amount,cr_net_loss] [sum,sum,sum,sum] + Project [cr_return_amount,cr_net_loss] + BroadcastHashJoin [cr_returned_date_sk,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_return_amount,cr_net_loss,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + WholeStageCodegen (22) + Project [wp_web_page_sk,sales,returns,profit,profit_loss] + BroadcastHashJoin [wp_web_page_sk,wp_web_page_sk] + HashAggregate [wp_web_page_sk,sum,sum] [sum(UnscaledValue(ws_ext_sales_price)),sum(UnscaledValue(ws_net_profit)),sales,profit,sum,sum] + InputAdapter + Exchange [wp_web_page_sk] #11 + WholeStageCodegen (17) + HashAggregate [wp_web_page_sk,ws_ext_sales_price,ws_net_profit] [sum,sum,sum,sum] + Project [ws_ext_sales_price,ws_net_profit,wp_web_page_sk] + BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] + Project [ws_web_page_sk,ws_ext_sales_price,ws_net_profit] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_web_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_web_page_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #12 + WholeStageCodegen (16) + Filter [wp_web_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_page [wp_web_page_sk] + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (21) + HashAggregate [wp_web_page_sk,sum,sum] [sum(UnscaledValue(wr_return_amt)),sum(UnscaledValue(wr_net_loss)),returns,profit_loss,sum,sum] + InputAdapter + Exchange [wp_web_page_sk] #14 + WholeStageCodegen (20) + HashAggregate [wp_web_page_sk,wr_return_amt,wr_net_loss] [sum,sum,sum,sum] + Project [wr_return_amt,wr_net_loss,wp_web_page_sk] + BroadcastHashJoin [wr_web_page_sk,wp_web_page_sk] + Project [wr_web_page_sk,wr_return_amt,wr_net_loss] + BroadcastHashJoin [wr_returned_date_sk,d_date_sk] + Filter [wr_web_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_web_page_sk,wr_return_amt,wr_net_loss,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + ReusedExchange [wp_web_page_sk] #12 + WholeStageCodegen (49) + HashAggregate [channel,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),id,sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel] #15 + WholeStageCodegen (48) + HashAggregate [channel,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 + WholeStageCodegen (74) + HashAggregate [sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),channel,id,sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange #16 + WholeStageCodegen (73) + HashAggregate [sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt new file mode 100644 index 000000000..76c968e91 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt @@ -0,0 +1,431 @@ +== Physical Plan == +TakeOrderedAndProject (70) ++- * Project (69) + +- * SortMergeJoin Inner (68) + :- * Project (45) + : +- * SortMergeJoin Inner (44) + : :- * Sort (21) + : : +- * HashAggregate (20) + : : +- Exchange (19) + : : +- * HashAggregate (18) + : : +- * Project (17) + : : +- * BroadcastHashJoin Inner BuildRight (16) + : : :- * Project (14) + : : : +- * Filter (13) + : : : +- * SortMergeJoin LeftOuter (12) + : : : :- * Sort (5) + : : : : +- Exchange (4) + : : : : +- * Filter (3) + : : : : +- * ColumnarToRow (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- * Sort (11) + : : : +- Exchange (10) + : : : +- * Project (9) + : : : +- * Filter (8) + : : : +- * ColumnarToRow (7) + : : : +- CometScan parquet spark_catalog.default.store_returns (6) + : : +- ReusedExchange (15) + : +- * Sort (43) + : +- * Filter (42) + : +- * HashAggregate (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- * Project (38) + : +- * BroadcastHashJoin Inner BuildRight (37) + : :- * Project (35) + : : +- * Filter (34) + : : +- * SortMergeJoin LeftOuter (33) + : : :- * Sort (26) + : : : +- Exchange (25) + : : : +- * Filter (24) + : : : +- * ColumnarToRow (23) + : : : +- CometScan parquet spark_catalog.default.web_sales (22) + : : +- * Sort (32) + : : +- Exchange (31) + : : +- * Project (30) + : : +- * Filter (29) + : : +- * ColumnarToRow (28) + : : +- CometScan parquet spark_catalog.default.web_returns (27) + : +- ReusedExchange (36) + +- * Sort (67) + +- * Filter (66) + +- * HashAggregate (65) + +- Exchange (64) + +- * HashAggregate (63) + +- * Project (62) + +- * BroadcastHashJoin Inner BuildRight (61) + :- * Project (59) + : +- * Filter (58) + : +- * SortMergeJoin LeftOuter (57) + : :- * Sort (50) + : : +- Exchange (49) + : : +- * Filter (48) + : : +- * ColumnarToRow (47) + : : +- CometScan parquet spark_catalog.default.catalog_sales (46) + : +- * Sort (56) + : +- Exchange (55) + : +- * Project (54) + : +- * Filter (53) + : +- * ColumnarToRow (52) + : +- CometScan parquet spark_catalog.default.catalog_returns (51) + +- ReusedExchange (60) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] + +(3) Filter [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_customer_sk#2)) + +(4) Exchange +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: hashpartitioning(ss_ticket_number#3, ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Arguments: [ss_ticket_number#3 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.store_returns +Output [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] +ReadSchema: struct + +(7) ColumnarToRow [codegen id : 3] +Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] + +(8) Filter [codegen id : 3] +Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Condition : (isnotnull(sr_ticket_number#10) AND isnotnull(sr_item_sk#9)) + +(9) Project [codegen id : 3] +Output [2]: [sr_item_sk#9, sr_ticket_number#10] +Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] + +(10) Exchange +Input [2]: [sr_item_sk#9, sr_ticket_number#10] +Arguments: hashpartitioning(sr_ticket_number#10, sr_item_sk#9, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [2]: [sr_item_sk#9, sr_ticket_number#10] +Arguments: [sr_ticket_number#10 ASC NULLS FIRST, sr_item_sk#9 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 6] +Left keys [2]: [ss_ticket_number#3, ss_item_sk#1] +Right keys [2]: [sr_ticket_number#10, sr_item_sk#9] +Join type: LeftOuter +Join condition: None + +(13) Filter [codegen id : 6] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10] +Condition : isnull(sr_ticket_number#10) + +(14) Project [codegen id : 6] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10] + +(15) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#12, d_year#13] + +(16) BroadcastHashJoin [codegen id : 6] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#12] +Join type: Inner +Join condition: None + +(17) Project [codegen id : 6] +Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, d_year#13] +Input [8]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7, d_date_sk#12, d_year#13] + +(18) HashAggregate [codegen id : 6] +Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, d_year#13] +Keys [3]: [d_year#13, ss_item_sk#1, ss_customer_sk#2] +Functions [3]: [partial_sum(ss_quantity#4), partial_sum(UnscaledValue(ss_wholesale_cost#5)), partial_sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [3]: [sum#14, sum#15, sum#16] +Results [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] + +(19) Exchange +Input [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] +Arguments: hashpartitioning(d_year#13, ss_item_sk#1, ss_customer_sk#2, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 7] +Input [6]: [d_year#13, ss_item_sk#1, ss_customer_sk#2, sum#17, sum#18, sum#19] +Keys [3]: [d_year#13, ss_item_sk#1, ss_customer_sk#2] +Functions [3]: [sum(ss_quantity#4), sum(UnscaledValue(ss_wholesale_cost#5)), sum(UnscaledValue(ss_sales_price#6))] +Aggregate Attributes [3]: [sum(ss_quantity#4)#20, sum(UnscaledValue(ss_wholesale_cost#5))#21, sum(UnscaledValue(ss_sales_price#6))#22] +Results [6]: [d_year#13 AS ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, sum(ss_quantity#4)#20 AS ss_qty#24, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#5))#21,17,2) AS ss_wc#25, MakeDecimal(sum(UnscaledValue(ss_sales_price#6))#22,17,2) AS ss_sp#26] + +(21) Sort [codegen id : 7] +Input [6]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26] +Arguments: [ss_sold_year#23 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST, ss_customer_sk#2 ASC NULLS FIRST], false, 0 + +(22) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_sold_date_sk#33 IN dynamicpruning#34)] +PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_bill_customer_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 8] +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] + +(24) Filter [codegen id : 8] +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_item_sk#27) AND isnotnull(ws_bill_customer_sk#28)) + +(25) Exchange +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Arguments: hashpartitioning(ws_order_number#29, ws_item_sk#27, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(26) Sort [codegen id : 9] +Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Arguments: [ws_order_number#29 ASC NULLS FIRST, ws_item_sk#27 ASC NULLS FIRST], false, 0 + +(27) Scan parquet spark_catalog.default.web_returns +Output [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] +ReadSchema: struct + +(28) ColumnarToRow [codegen id : 10] +Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] + +(29) Filter [codegen id : 10] +Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Condition : (isnotnull(wr_order_number#36) AND isnotnull(wr_item_sk#35)) + +(30) Project [codegen id : 10] +Output [2]: [wr_item_sk#35, wr_order_number#36] +Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] + +(31) Exchange +Input [2]: [wr_item_sk#35, wr_order_number#36] +Arguments: hashpartitioning(wr_order_number#36, wr_item_sk#35, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(32) Sort [codegen id : 11] +Input [2]: [wr_item_sk#35, wr_order_number#36] +Arguments: [wr_order_number#36 ASC NULLS FIRST, wr_item_sk#35 ASC NULLS FIRST], false, 0 + +(33) SortMergeJoin [codegen id : 13] +Left keys [2]: [ws_order_number#29, ws_item_sk#27] +Right keys [2]: [wr_order_number#36, wr_item_sk#35] +Join type: LeftOuter +Join condition: None + +(34) Filter [codegen id : 13] +Input [9]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, wr_item_sk#35, wr_order_number#36] +Condition : isnull(wr_order_number#36) + +(35) Project [codegen id : 13] +Output [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Input [9]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, wr_item_sk#35, wr_order_number#36] + +(36) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#38, d_year#39] + +(37) BroadcastHashJoin [codegen id : 13] +Left keys [1]: [ws_sold_date_sk#33] +Right keys [1]: [d_date_sk#38] +Join type: Inner +Join condition: None + +(38) Project [codegen id : 13] +Output [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, d_year#39] +Input [8]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33, d_date_sk#38, d_year#39] + +(39) HashAggregate [codegen id : 13] +Input [6]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, d_year#39] +Keys [3]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28] +Functions [3]: [partial_sum(ws_quantity#30), partial_sum(UnscaledValue(ws_wholesale_cost#31)), partial_sum(UnscaledValue(ws_sales_price#32))] +Aggregate Attributes [3]: [sum#40, sum#41, sum#42] +Results [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] + +(40) Exchange +Input [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] +Arguments: hashpartitioning(d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(41) HashAggregate [codegen id : 14] +Input [6]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28, sum#43, sum#44, sum#45] +Keys [3]: [d_year#39, ws_item_sk#27, ws_bill_customer_sk#28] +Functions [3]: [sum(ws_quantity#30), sum(UnscaledValue(ws_wholesale_cost#31)), sum(UnscaledValue(ws_sales_price#32))] +Aggregate Attributes [3]: [sum(ws_quantity#30)#46, sum(UnscaledValue(ws_wholesale_cost#31))#47, sum(UnscaledValue(ws_sales_price#32))#48] +Results [6]: [d_year#39 AS ws_sold_year#49, ws_item_sk#27, ws_bill_customer_sk#28 AS ws_customer_sk#50, sum(ws_quantity#30)#46 AS ws_qty#51, MakeDecimal(sum(UnscaledValue(ws_wholesale_cost#31))#47,17,2) AS ws_wc#52, MakeDecimal(sum(UnscaledValue(ws_sales_price#32))#48,17,2) AS ws_sp#53] + +(42) Filter [codegen id : 14] +Input [6]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] +Condition : (coalesce(ws_qty#51, 0) > 0) + +(43) Sort [codegen id : 14] +Input [6]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] +Arguments: [ws_sold_year#49 ASC NULLS FIRST, ws_item_sk#27 ASC NULLS FIRST, ws_customer_sk#50 ASC NULLS FIRST], false, 0 + +(44) SortMergeJoin [codegen id : 15] +Left keys [3]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2] +Right keys [3]: [ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50] +Join type: Inner +Join condition: None + +(45) Project [codegen id : 15] +Output [9]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, ws_wc#52, ws_sp#53] +Input [12]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_sold_year#49, ws_item_sk#27, ws_customer_sk#50, ws_qty#51, ws_wc#52, ws_sp#53] + +(46) Scan parquet spark_catalog.default.catalog_sales +Output [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#60), dynamicpruningexpression(cs_sold_date_sk#60 IN dynamicpruning#61)] +PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_bill_customer_sk)] +ReadSchema: struct + +(47) ColumnarToRow [codegen id : 16] +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] + +(48) Filter [codegen id : 16] +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Condition : (isnotnull(cs_item_sk#55) AND isnotnull(cs_bill_customer_sk#54)) + +(49) Exchange +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Arguments: hashpartitioning(cs_order_number#56, cs_item_sk#55, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(50) Sort [codegen id : 17] +Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Arguments: [cs_order_number#56 ASC NULLS FIRST, cs_item_sk#55 ASC NULLS FIRST], false, 0 + +(51) Scan parquet spark_catalog.default.catalog_returns +Output [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] +ReadSchema: struct + +(52) ColumnarToRow [codegen id : 18] +Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] + +(53) Filter [codegen id : 18] +Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Condition : (isnotnull(cr_order_number#63) AND isnotnull(cr_item_sk#62)) + +(54) Project [codegen id : 18] +Output [2]: [cr_item_sk#62, cr_order_number#63] +Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] + +(55) Exchange +Input [2]: [cr_item_sk#62, cr_order_number#63] +Arguments: hashpartitioning(cr_order_number#63, cr_item_sk#62, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(56) Sort [codegen id : 19] +Input [2]: [cr_item_sk#62, cr_order_number#63] +Arguments: [cr_order_number#63 ASC NULLS FIRST, cr_item_sk#62 ASC NULLS FIRST], false, 0 + +(57) SortMergeJoin [codegen id : 21] +Left keys [2]: [cs_order_number#56, cs_item_sk#55] +Right keys [2]: [cr_order_number#63, cr_item_sk#62] +Join type: LeftOuter +Join condition: None + +(58) Filter [codegen id : 21] +Input [9]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, cr_item_sk#62, cr_order_number#63] +Condition : isnull(cr_order_number#63) + +(59) Project [codegen id : 21] +Output [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Input [9]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, cr_item_sk#62, cr_order_number#63] + +(60) ReusedExchange [Reuses operator id: 74] +Output [2]: [d_date_sk#65, d_year#66] + +(61) BroadcastHashJoin [codegen id : 21] +Left keys [1]: [cs_sold_date_sk#60] +Right keys [1]: [d_date_sk#65] +Join type: Inner +Join condition: None + +(62) Project [codegen id : 21] +Output [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, d_year#66] +Input [8]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60, d_date_sk#65, d_year#66] + +(63) HashAggregate [codegen id : 21] +Input [6]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, d_year#66] +Keys [3]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54] +Functions [3]: [partial_sum(cs_quantity#57), partial_sum(UnscaledValue(cs_wholesale_cost#58)), partial_sum(UnscaledValue(cs_sales_price#59))] +Aggregate Attributes [3]: [sum#67, sum#68, sum#69] +Results [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] + +(64) Exchange +Input [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] +Arguments: hashpartitioning(d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, 5), ENSURE_REQUIREMENTS, [plan_id=9] + +(65) HashAggregate [codegen id : 22] +Input [6]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54, sum#70, sum#71, sum#72] +Keys [3]: [d_year#66, cs_item_sk#55, cs_bill_customer_sk#54] +Functions [3]: [sum(cs_quantity#57), sum(UnscaledValue(cs_wholesale_cost#58)), sum(UnscaledValue(cs_sales_price#59))] +Aggregate Attributes [3]: [sum(cs_quantity#57)#73, sum(UnscaledValue(cs_wholesale_cost#58))#74, sum(UnscaledValue(cs_sales_price#59))#75] +Results [6]: [d_year#66 AS cs_sold_year#76, cs_item_sk#55, cs_bill_customer_sk#54 AS cs_customer_sk#77, sum(cs_quantity#57)#73 AS cs_qty#78, MakeDecimal(sum(UnscaledValue(cs_wholesale_cost#58))#74,17,2) AS cs_wc#79, MakeDecimal(sum(UnscaledValue(cs_sales_price#59))#75,17,2) AS cs_sp#80] + +(66) Filter [codegen id : 22] +Input [6]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] +Condition : (coalesce(cs_qty#78, 0) > 0) + +(67) Sort [codegen id : 22] +Input [6]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] +Arguments: [cs_sold_year#76 ASC NULLS FIRST, cs_item_sk#55 ASC NULLS FIRST, cs_customer_sk#77 ASC NULLS FIRST], false, 0 + +(68) SortMergeJoin [codegen id : 23] +Left keys [3]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2] +Right keys [3]: [cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77] +Join type: Inner +Join condition: None + +(69) Project [codegen id : 23] +Output [13]: [round((cast(ss_qty#24 as double) / cast(coalesce((ws_qty#51 + cs_qty#78), 1) as double)), 2) AS ratio#81, ss_qty#24 AS store_qty#82, ss_wc#25 AS store_wholesale_cost#83, ss_sp#26 AS store_sales_price#84, (coalesce(ws_qty#51, 0) + coalesce(cs_qty#78, 0)) AS other_chan_qty#85, (coalesce(ws_wc#52, 0.00) + coalesce(cs_wc#79, 0.00)) AS other_chan_wholesale_cost#86, (coalesce(ws_sp#53, 0.00) + coalesce(cs_sp#80, 0.00)) AS other_chan_sales_price#87, ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26] +Input [15]: [ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26, ws_qty#51, ws_wc#52, ws_sp#53, cs_sold_year#76, cs_item_sk#55, cs_customer_sk#77, cs_qty#78, cs_wc#79, cs_sp#80] + +(70) TakeOrderedAndProject +Input [13]: [ratio#81, store_qty#82, store_wholesale_cost#83, store_sales_price#84, other_chan_qty#85, other_chan_wholesale_cost#86, other_chan_sales_price#87, ss_sold_year#23, ss_item_sk#1, ss_customer_sk#2, ss_qty#24, ss_wc#25, ss_sp#26] +Arguments: 100, [ss_sold_year#23 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST, ss_customer_sk#2 ASC NULLS FIRST, ss_qty#24 DESC NULLS LAST, ss_wc#25 DESC NULLS LAST, ss_sp#26 DESC NULLS LAST, other_chan_qty#85 ASC NULLS FIRST, other_chan_wholesale_cost#86 ASC NULLS FIRST, other_chan_sales_price#87 ASC NULLS FIRST, ratio#81 ASC NULLS FIRST], [ratio#81, store_qty#82, store_wholesale_cost#83, store_sales_price#84, other_chan_qty#85, other_chan_wholesale_cost#86, other_chan_sales_price#87] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (74) ++- * Filter (73) + +- * ColumnarToRow (72) + +- CometScan parquet spark_catalog.default.date_dim (71) + + +(71) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#12, d_year#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] +ReadSchema: struct + +(72) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#12, d_year#13] + +(73) Filter [codegen id : 1] +Input [2]: [d_date_sk#12, d_year#13] +Condition : ((isnotnull(d_year#13) AND (d_year#13 = 2000)) AND isnotnull(d_date_sk#12)) + +(74) BroadcastExchange +Input [2]: [d_date_sk#12, d_year#13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] + +Subquery:2 Hosting operator id = 22 Hosting Expression = ws_sold_date_sk#33 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 46 Hosting Expression = cs_sold_date_sk#60 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt new file mode 100644 index 000000000..f962e8fb8 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt @@ -0,0 +1,127 @@ +TakeOrderedAndProject [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp,other_chan_qty,other_chan_wholesale_cost,other_chan_sales_price,ratio,store_qty,store_wholesale_cost,store_sales_price] + WholeStageCodegen (23) + Project [ss_qty,ws_qty,cs_qty,ss_wc,ss_sp,ws_wc,cs_wc,ws_sp,cs_sp,ss_sold_year,ss_item_sk,ss_customer_sk] + SortMergeJoin [ss_sold_year,ss_item_sk,ss_customer_sk,cs_sold_year,cs_item_sk,cs_customer_sk] + InputAdapter + WholeStageCodegen (15) + Project [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp,ws_qty,ws_wc,ws_sp] + SortMergeJoin [ss_sold_year,ss_item_sk,ss_customer_sk,ws_sold_year,ws_item_sk,ws_customer_sk] + InputAdapter + WholeStageCodegen (7) + Sort [ss_sold_year,ss_item_sk,ss_customer_sk] + HashAggregate [d_year,ss_item_sk,ss_customer_sk,sum,sum,sum] [sum(ss_quantity),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_sales_price)),ss_sold_year,ss_qty,ss_wc,ss_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,ss_item_sk,ss_customer_sk] #1 + WholeStageCodegen (6) + HashAggregate [d_year,ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price] [sum,sum,sum,sum,sum,sum] + Project [ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price,d_year] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_customer_sk,ss_quantity,ss_wholesale_cost,ss_sales_price,ss_sold_date_sk] + Filter [sr_ticket_number] + SortMergeJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + InputAdapter + WholeStageCodegen (2) + Sort [ss_ticket_number,ss_item_sk] + InputAdapter + Exchange [ss_ticket_number,ss_item_sk] #2 + WholeStageCodegen (1) + Filter [ss_item_sk,ss_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_wholesale_cost,ss_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + Filter [d_year,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + InputAdapter + WholeStageCodegen (4) + Sort [sr_ticket_number,sr_item_sk] + InputAdapter + Exchange [sr_ticket_number,sr_item_sk] #4 + WholeStageCodegen (3) + Project [sr_item_sk,sr_ticket_number] + Filter [sr_ticket_number,sr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + WholeStageCodegen (14) + Sort [ws_sold_year,ws_item_sk,ws_customer_sk] + Filter [ws_qty] + HashAggregate [d_year,ws_item_sk,ws_bill_customer_sk,sum,sum,sum] [sum(ws_quantity),sum(UnscaledValue(ws_wholesale_cost)),sum(UnscaledValue(ws_sales_price)),ws_sold_year,ws_customer_sk,ws_qty,ws_wc,ws_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,ws_item_sk,ws_bill_customer_sk] #5 + WholeStageCodegen (13) + HashAggregate [d_year,ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price] [sum,sum,sum,sum,sum,sum] + Project [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price,d_year] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_wholesale_cost,ws_sales_price,ws_sold_date_sk] + Filter [wr_order_number] + SortMergeJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + InputAdapter + WholeStageCodegen (9) + Sort [ws_order_number,ws_item_sk] + InputAdapter + Exchange [ws_order_number,ws_item_sk] #6 + WholeStageCodegen (8) + Filter [ws_item_sk,ws_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_order_number,ws_quantity,ws_wholesale_cost,ws_sales_price,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (11) + Sort [wr_order_number,wr_item_sk] + InputAdapter + Exchange [wr_order_number,wr_item_sk] #7 + WholeStageCodegen (10) + Project [wr_item_sk,wr_order_number] + Filter [wr_order_number,wr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 + InputAdapter + WholeStageCodegen (22) + Sort [cs_sold_year,cs_item_sk,cs_customer_sk] + Filter [cs_qty] + HashAggregate [d_year,cs_item_sk,cs_bill_customer_sk,sum,sum,sum] [sum(cs_quantity),sum(UnscaledValue(cs_wholesale_cost)),sum(UnscaledValue(cs_sales_price)),cs_sold_year,cs_customer_sk,cs_qty,cs_wc,cs_sp,sum,sum,sum] + InputAdapter + Exchange [d_year,cs_item_sk,cs_bill_customer_sk] #8 + WholeStageCodegen (21) + HashAggregate [d_year,cs_item_sk,cs_bill_customer_sk,cs_quantity,cs_wholesale_cost,cs_sales_price] [sum,sum,sum,sum,sum,sum] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_wholesale_cost,cs_sales_price,d_year] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_wholesale_cost,cs_sales_price,cs_sold_date_sk] + Filter [cr_order_number] + SortMergeJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + InputAdapter + WholeStageCodegen (17) + Sort [cs_order_number,cs_item_sk] + InputAdapter + Exchange [cs_order_number,cs_item_sk] #9 + WholeStageCodegen (16) + Filter [cs_item_sk,cs_bill_customer_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_order_number,cs_quantity,cs_wholesale_cost,cs_sales_price,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (19) + Sort [cr_order_number,cr_item_sk] + InputAdapter + Exchange [cr_order_number,cr_item_sk] #10 + WholeStageCodegen (18) + Project [cr_item_sk,cr_order_number] + Filter [cr_order_number,cr_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk,d_year] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt new file mode 100644 index 000000000..d01fc085a --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt @@ -0,0 +1,730 @@ +== Physical Plan == +TakeOrderedAndProject (120) ++- * HashAggregate (119) + +- Exchange (118) + +- * HashAggregate (117) + +- Union (116) + :- * HashAggregate (105) + : +- Exchange (104) + : +- * HashAggregate (103) + : +- Union (102) + : :- * HashAggregate (39) + : : +- Exchange (38) + : : +- * HashAggregate (37) + : : +- * Project (36) + : : +- * BroadcastHashJoin Inner BuildRight (35) + : : :- * Project (29) + : : : +- * BroadcastHashJoin Inner BuildRight (28) + : : : :- * Project (22) + : : : : +- * BroadcastHashJoin Inner BuildRight (21) + : : : : :- * Project (16) + : : : : : +- * BroadcastHashJoin Inner BuildRight (15) + : : : : : :- * Project (13) + : : : : : : +- * SortMergeJoin LeftOuter (12) + : : : : : : :- * Sort (5) + : : : : : : : +- Exchange (4) + : : : : : : : +- * Filter (3) + : : : : : : : +- * ColumnarToRow (2) + : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : +- * Sort (11) + : : : : : : +- Exchange (10) + : : : : : : +- * Project (9) + : : : : : : +- * Filter (8) + : : : : : : +- * ColumnarToRow (7) + : : : : : : +- CometScan parquet spark_catalog.default.store_returns (6) + : : : : : +- ReusedExchange (14) + : : : : +- BroadcastExchange (20) + : : : : +- * Filter (19) + : : : : +- * ColumnarToRow (18) + : : : : +- CometScan parquet spark_catalog.default.store (17) + : : : +- BroadcastExchange (27) + : : : +- * Project (26) + : : : +- * Filter (25) + : : : +- * ColumnarToRow (24) + : : : +- CometScan parquet spark_catalog.default.item (23) + : : +- BroadcastExchange (34) + : : +- * Project (33) + : : +- * Filter (32) + : : +- * ColumnarToRow (31) + : : +- CometScan parquet spark_catalog.default.promotion (30) + : :- * HashAggregate (70) + : : +- Exchange (69) + : : +- * HashAggregate (68) + : : +- * Project (67) + : : +- * BroadcastHashJoin Inner BuildRight (66) + : : :- * Project (64) + : : : +- * BroadcastHashJoin Inner BuildRight (63) + : : : :- * Project (61) + : : : : +- * BroadcastHashJoin Inner BuildRight (60) + : : : : :- * Project (55) + : : : : : +- * BroadcastHashJoin Inner BuildRight (54) + : : : : : :- * Project (52) + : : : : : : +- * SortMergeJoin LeftOuter (51) + : : : : : : :- * Sort (44) + : : : : : : : +- Exchange (43) + : : : : : : : +- * Filter (42) + : : : : : : : +- * ColumnarToRow (41) + : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (40) + : : : : : : +- * Sort (50) + : : : : : : +- Exchange (49) + : : : : : : +- * Project (48) + : : : : : : +- * Filter (47) + : : : : : : +- * ColumnarToRow (46) + : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (45) + : : : : : +- ReusedExchange (53) + : : : : +- BroadcastExchange (59) + : : : : +- * Filter (58) + : : : : +- * ColumnarToRow (57) + : : : : +- CometScan parquet spark_catalog.default.catalog_page (56) + : : : +- ReusedExchange (62) + : : +- ReusedExchange (65) + : +- * HashAggregate (101) + : +- Exchange (100) + : +- * HashAggregate (99) + : +- * Project (98) + : +- * BroadcastHashJoin Inner BuildRight (97) + : :- * Project (95) + : : +- * BroadcastHashJoin Inner BuildRight (94) + : : :- * Project (92) + : : : +- * BroadcastHashJoin Inner BuildRight (91) + : : : :- * Project (86) + : : : : +- * BroadcastHashJoin Inner BuildRight (85) + : : : : :- * Project (83) + : : : : : +- * SortMergeJoin LeftOuter (82) + : : : : : :- * Sort (75) + : : : : : : +- Exchange (74) + : : : : : : +- * Filter (73) + : : : : : : +- * ColumnarToRow (72) + : : : : : : +- CometScan parquet spark_catalog.default.web_sales (71) + : : : : : +- * Sort (81) + : : : : : +- Exchange (80) + : : : : : +- * Project (79) + : : : : : +- * Filter (78) + : : : : : +- * ColumnarToRow (77) + : : : : : +- CometScan parquet spark_catalog.default.web_returns (76) + : : : : +- ReusedExchange (84) + : : : +- BroadcastExchange (90) + : : : +- * Filter (89) + : : : +- * ColumnarToRow (88) + : : : +- CometScan parquet spark_catalog.default.web_site (87) + : : +- ReusedExchange (93) + : +- ReusedExchange (96) + :- * HashAggregate (110) + : +- Exchange (109) + : +- * HashAggregate (108) + : +- * HashAggregate (107) + : +- ReusedExchange (106) + +- * HashAggregate (115) + +- Exchange (114) + +- * HashAggregate (113) + +- * HashAggregate (112) + +- ReusedExchange (111) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)] +PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk), IsNotNull(ss_promo_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] + +(3) Filter [codegen id : 1] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Condition : ((isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) + +(4) Exchange +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Arguments: hashpartitioning(ss_item_sk#1, ss_ticket_number#4, 5), ENSURE_REQUIREMENTS, [plan_id=1] + +(5) Sort [codegen id : 2] +Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Arguments: [ss_item_sk#1 ASC NULLS FIRST, ss_ticket_number#4 ASC NULLS FIRST], false, 0 + +(6) Scan parquet spark_catalog.default.store_returns +Output [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store_returns] +PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] +ReadSchema: struct + +(7) ColumnarToRow [codegen id : 3] +Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] + +(8) Filter [codegen id : 3] +Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Condition : (isnotnull(sr_item_sk#9) AND isnotnull(sr_ticket_number#10)) + +(9) Project [codegen id : 3] +Output [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] + +(10) Exchange +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +Arguments: hashpartitioning(sr_item_sk#9, sr_ticket_number#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(11) Sort [codegen id : 4] +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +Arguments: [sr_item_sk#9 ASC NULLS FIRST, sr_ticket_number#10 ASC NULLS FIRST], false, 0 + +(12) SortMergeJoin [codegen id : 9] +Left keys [2]: [ss_item_sk#1, ss_ticket_number#4] +Right keys [2]: [sr_item_sk#9, sr_ticket_number#10] +Join type: LeftOuter +Join condition: None + +(13) Project [codegen id : 9] +Output [8]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_return_amt#11, sr_net_loss#12] +Input [11]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] + +(14) ReusedExchange [Reuses operator id: 125] +Output [1]: [d_date_sk#14] + +(15) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_sold_date_sk#7] +Right keys [1]: [d_date_sk#14] +Join type: Inner +Join condition: None + +(16) Project [codegen id : 9] +Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, sr_return_amt#11, sr_net_loss#12, d_date_sk#14] + +(17) Scan parquet spark_catalog.default.store +Output [2]: [s_store_sk#15, s_store_id#16] +Batched: true +Location [not included in comparison]/{warehouse_dir}/store] +PushedFilters: [IsNotNull(s_store_sk)] +ReadSchema: struct + +(18) ColumnarToRow [codegen id : 6] +Input [2]: [s_store_sk#15, s_store_id#16] + +(19) Filter [codegen id : 6] +Input [2]: [s_store_sk#15, s_store_id#16] +Condition : isnotnull(s_store_sk#15) + +(20) BroadcastExchange +Input [2]: [s_store_sk#15, s_store_id#16] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] + +(21) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_store_sk#2] +Right keys [1]: [s_store_sk#15] +Join type: Inner +Join condition: None + +(22) Project [codegen id : 9] +Output [7]: [ss_item_sk#1, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_sk#15, s_store_id#16] + +(23) Scan parquet spark_catalog.default.item +Output [2]: [i_item_sk#17, i_current_price#18] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_current_price), GreaterThan(i_current_price,50.00), IsNotNull(i_item_sk)] +ReadSchema: struct + +(24) ColumnarToRow [codegen id : 7] +Input [2]: [i_item_sk#17, i_current_price#18] + +(25) Filter [codegen id : 7] +Input [2]: [i_item_sk#17, i_current_price#18] +Condition : ((isnotnull(i_current_price#18) AND (i_current_price#18 > 50.00)) AND isnotnull(i_item_sk#17)) + +(26) Project [codegen id : 7] +Output [1]: [i_item_sk#17] +Input [2]: [i_item_sk#17, i_current_price#18] + +(27) BroadcastExchange +Input [1]: [i_item_sk#17] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(28) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#17] +Join type: Inner +Join condition: None + +(29) Project [codegen id : 9] +Output [6]: [ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [8]: [ss_item_sk#1, ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16, i_item_sk#17] + +(30) Scan parquet spark_catalog.default.promotion +Output [2]: [p_promo_sk#19, p_channel_tv#20] +Batched: true +Location [not included in comparison]/{warehouse_dir}/promotion] +PushedFilters: [IsNotNull(p_channel_tv), EqualTo(p_channel_tv,N), IsNotNull(p_promo_sk)] +ReadSchema: struct + +(31) ColumnarToRow [codegen id : 8] +Input [2]: [p_promo_sk#19, p_channel_tv#20] + +(32) Filter [codegen id : 8] +Input [2]: [p_promo_sk#19, p_channel_tv#20] +Condition : ((isnotnull(p_channel_tv#20) AND (p_channel_tv#20 = N)) AND isnotnull(p_promo_sk#19)) + +(33) Project [codegen id : 8] +Output [1]: [p_promo_sk#19] +Input [2]: [p_promo_sk#19, p_channel_tv#20] + +(34) BroadcastExchange +Input [1]: [p_promo_sk#19] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + +(35) BroadcastHashJoin [codegen id : 9] +Left keys [1]: [ss_promo_sk#3] +Right keys [1]: [p_promo_sk#19] +Join type: Inner +Join condition: None + +(36) Project [codegen id : 9] +Output [5]: [ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Input [7]: [ss_promo_sk#3, ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16, p_promo_sk#19] + +(37) HashAggregate [codegen id : 9] +Input [5]: [ss_ext_sales_price#5, ss_net_profit#6, sr_return_amt#11, sr_net_loss#12, s_store_id#16] +Keys [1]: [s_store_id#16] +Functions [3]: [partial_sum(UnscaledValue(ss_ext_sales_price#5)), partial_sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00)), partial_sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] +Results [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] + +(38) Exchange +Input [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] +Arguments: hashpartitioning(s_store_id#16, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(39) HashAggregate [codegen id : 10] +Input [6]: [s_store_id#16, sum#26, sum#27, isEmpty#28, sum#29, isEmpty#30] +Keys [1]: [s_store_id#16] +Functions [3]: [sum(UnscaledValue(ss_ext_sales_price#5)), sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00)), sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(ss_ext_sales_price#5))#31, sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00))#32, sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))#33] +Results [5]: [store channel AS channel#34, concat(store, s_store_id#16) AS id#35, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#5))#31,17,2) AS sales#36, sum(coalesce(cast(sr_return_amt#11 as decimal(12,2)), 0.00))#32 AS returns#37, sum((ss_net_profit#6 - coalesce(cast(sr_net_loss#12 as decimal(12,2)), 0.00)))#33 AS profit#38] + +(40) Scan parquet spark_catalog.default.catalog_sales +Output [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_sold_date_sk#45 IN dynamicpruning#46)] +PushedFilters: [IsNotNull(cs_catalog_page_sk), IsNotNull(cs_item_sk), IsNotNull(cs_promo_sk)] +ReadSchema: struct + +(41) ColumnarToRow [codegen id : 11] +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] + +(42) Filter [codegen id : 11] +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Condition : ((isnotnull(cs_catalog_page_sk#39) AND isnotnull(cs_item_sk#40)) AND isnotnull(cs_promo_sk#41)) + +(43) Exchange +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: hashpartitioning(cs_item_sk#40, cs_order_number#42, 5), ENSURE_REQUIREMENTS, [plan_id=7] + +(44) Sort [codegen id : 12] +Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: [cs_item_sk#40 ASC NULLS FIRST, cs_order_number#42 ASC NULLS FIRST], false, 0 + +(45) Scan parquet spark_catalog.default.catalog_returns +Output [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_returns] +PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] +ReadSchema: struct + +(46) ColumnarToRow [codegen id : 13] +Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] + +(47) Filter [codegen id : 13] +Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Condition : (isnotnull(cr_item_sk#47) AND isnotnull(cr_order_number#48)) + +(48) Project [codegen id : 13] +Output [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] + +(49) Exchange +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +Arguments: hashpartitioning(cr_item_sk#47, cr_order_number#48, 5), ENSURE_REQUIREMENTS, [plan_id=8] + +(50) Sort [codegen id : 14] +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +Arguments: [cr_item_sk#47 ASC NULLS FIRST, cr_order_number#48 ASC NULLS FIRST], false, 0 + +(51) SortMergeJoin [codegen id : 19] +Left keys [2]: [cs_item_sk#40, cs_order_number#42] +Right keys [2]: [cr_item_sk#47, cr_order_number#48] +Join type: LeftOuter +Join condition: None + +(52) Project [codegen id : 19] +Output [8]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_return_amount#49, cr_net_loss#50] +Input [11]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] + +(53) ReusedExchange [Reuses operator id: 125] +Output [1]: [d_date_sk#52] + +(54) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_sold_date_sk#45] +Right keys [1]: [d_date_sk#52] +Join type: Inner +Join condition: None + +(55) Project [codegen id : 19] +Output [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50] +Input [9]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45, cr_return_amount#49, cr_net_loss#50, d_date_sk#52] + +(56) Scan parquet spark_catalog.default.catalog_page +Output [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Batched: true +Location [not included in comparison]/{warehouse_dir}/catalog_page] +PushedFilters: [IsNotNull(cp_catalog_page_sk)] +ReadSchema: struct + +(57) ColumnarToRow [codegen id : 16] +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] + +(58) Filter [codegen id : 16] +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Condition : isnotnull(cp_catalog_page_sk#53) + +(59) BroadcastExchange +Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] + +(60) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_catalog_page_sk#39] +Right keys [1]: [cp_catalog_page_sk#53] +Join type: Inner +Join condition: None + +(61) Project [codegen id : 19] +Output [7]: [cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [9]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_sk#53, cp_catalog_page_id#54] + +(62) ReusedExchange [Reuses operator id: 27] +Output [1]: [i_item_sk#55] + +(63) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_item_sk#40] +Right keys [1]: [i_item_sk#55] +Join type: Inner +Join condition: None + +(64) Project [codegen id : 19] +Output [6]: [cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [8]: [cs_item_sk#40, cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54, i_item_sk#55] + +(65) ReusedExchange [Reuses operator id: 34] +Output [1]: [p_promo_sk#56] + +(66) BroadcastHashJoin [codegen id : 19] +Left keys [1]: [cs_promo_sk#41] +Right keys [1]: [p_promo_sk#56] +Join type: Inner +Join condition: None + +(67) Project [codegen id : 19] +Output [5]: [cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Input [7]: [cs_promo_sk#41, cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54, p_promo_sk#56] + +(68) HashAggregate [codegen id : 19] +Input [5]: [cs_ext_sales_price#43, cs_net_profit#44, cr_return_amount#49, cr_net_loss#50, cp_catalog_page_id#54] +Keys [1]: [cp_catalog_page_id#54] +Functions [3]: [partial_sum(UnscaledValue(cs_ext_sales_price#43)), partial_sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00)), partial_sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#57, sum#58, isEmpty#59, sum#60, isEmpty#61] +Results [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] + +(69) Exchange +Input [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] +Arguments: hashpartitioning(cp_catalog_page_id#54, 5), ENSURE_REQUIREMENTS, [plan_id=10] + +(70) HashAggregate [codegen id : 20] +Input [6]: [cp_catalog_page_id#54, sum#62, sum#63, isEmpty#64, sum#65, isEmpty#66] +Keys [1]: [cp_catalog_page_id#54] +Functions [3]: [sum(UnscaledValue(cs_ext_sales_price#43)), sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00)), sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(cs_ext_sales_price#43))#67, sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00))#68, sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))#69] +Results [5]: [catalog channel AS channel#70, concat(catalog_page, cp_catalog_page_id#54) AS id#71, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#43))#67,17,2) AS sales#72, sum(coalesce(cast(cr_return_amount#49 as decimal(12,2)), 0.00))#68 AS returns#73, sum((cs_net_profit#44 - coalesce(cast(cr_net_loss#50 as decimal(12,2)), 0.00)))#69 AS profit#74] + +(71) Scan parquet spark_catalog.default.web_sales +Output [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#81), dynamicpruningexpression(ws_sold_date_sk#81 IN dynamicpruning#82)] +PushedFilters: [IsNotNull(ws_web_site_sk), IsNotNull(ws_item_sk), IsNotNull(ws_promo_sk)] +ReadSchema: struct + +(72) ColumnarToRow [codegen id : 21] +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] + +(73) Filter [codegen id : 21] +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Condition : ((isnotnull(ws_web_site_sk#76) AND isnotnull(ws_item_sk#75)) AND isnotnull(ws_promo_sk#77)) + +(74) Exchange +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Arguments: hashpartitioning(ws_item_sk#75, ws_order_number#78, 5), ENSURE_REQUIREMENTS, [plan_id=11] + +(75) Sort [codegen id : 22] +Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Arguments: [ws_item_sk#75 ASC NULLS FIRST, ws_order_number#78 ASC NULLS FIRST], false, 0 + +(76) Scan parquet spark_catalog.default.web_returns +Output [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_returns] +PushedFilters: [IsNotNull(wr_item_sk), IsNotNull(wr_order_number)] +ReadSchema: struct + +(77) ColumnarToRow [codegen id : 23] +Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] + +(78) Filter [codegen id : 23] +Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Condition : (isnotnull(wr_item_sk#83) AND isnotnull(wr_order_number#84)) + +(79) Project [codegen id : 23] +Output [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] + +(80) Exchange +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +Arguments: hashpartitioning(wr_item_sk#83, wr_order_number#84, 5), ENSURE_REQUIREMENTS, [plan_id=12] + +(81) Sort [codegen id : 24] +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +Arguments: [wr_item_sk#83 ASC NULLS FIRST, wr_order_number#84 ASC NULLS FIRST], false, 0 + +(82) SortMergeJoin [codegen id : 29] +Left keys [2]: [ws_item_sk#75, ws_order_number#78] +Right keys [2]: [wr_item_sk#83, wr_order_number#84] +Join type: LeftOuter +Join condition: None + +(83) Project [codegen id : 29] +Output [8]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_return_amt#85, wr_net_loss#86] +Input [11]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] + +(84) ReusedExchange [Reuses operator id: 125] +Output [1]: [d_date_sk#88] + +(85) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_sold_date_sk#81] +Right keys [1]: [d_date_sk#88] +Join type: Inner +Join condition: None + +(86) Project [codegen id : 29] +Output [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86] +Input [9]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81, wr_return_amt#85, wr_net_loss#86, d_date_sk#88] + +(87) Scan parquet spark_catalog.default.web_site +Output [2]: [web_site_sk#89, web_site_id#90] +Batched: true +Location [not included in comparison]/{warehouse_dir}/web_site] +PushedFilters: [IsNotNull(web_site_sk)] +ReadSchema: struct + +(88) ColumnarToRow [codegen id : 26] +Input [2]: [web_site_sk#89, web_site_id#90] + +(89) Filter [codegen id : 26] +Input [2]: [web_site_sk#89, web_site_id#90] +Condition : isnotnull(web_site_sk#89) + +(90) BroadcastExchange +Input [2]: [web_site_sk#89, web_site_id#90] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] + +(91) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_web_site_sk#76] +Right keys [1]: [web_site_sk#89] +Join type: Inner +Join condition: None + +(92) Project [codegen id : 29] +Output [7]: [ws_item_sk#75, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [9]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_sk#89, web_site_id#90] + +(93) ReusedExchange [Reuses operator id: 27] +Output [1]: [i_item_sk#91] + +(94) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_item_sk#75] +Right keys [1]: [i_item_sk#91] +Join type: Inner +Join condition: None + +(95) Project [codegen id : 29] +Output [6]: [ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [8]: [ws_item_sk#75, ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90, i_item_sk#91] + +(96) ReusedExchange [Reuses operator id: 34] +Output [1]: [p_promo_sk#92] + +(97) BroadcastHashJoin [codegen id : 29] +Left keys [1]: [ws_promo_sk#77] +Right keys [1]: [p_promo_sk#92] +Join type: Inner +Join condition: None + +(98) Project [codegen id : 29] +Output [5]: [ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Input [7]: [ws_promo_sk#77, ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90, p_promo_sk#92] + +(99) HashAggregate [codegen id : 29] +Input [5]: [ws_ext_sales_price#79, ws_net_profit#80, wr_return_amt#85, wr_net_loss#86, web_site_id#90] +Keys [1]: [web_site_id#90] +Functions [3]: [partial_sum(UnscaledValue(ws_ext_sales_price#79)), partial_sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00)), partial_sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))] +Aggregate Attributes [5]: [sum#93, sum#94, isEmpty#95, sum#96, isEmpty#97] +Results [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] + +(100) Exchange +Input [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] +Arguments: hashpartitioning(web_site_id#90, 5), ENSURE_REQUIREMENTS, [plan_id=14] + +(101) HashAggregate [codegen id : 30] +Input [6]: [web_site_id#90, sum#98, sum#99, isEmpty#100, sum#101, isEmpty#102] +Keys [1]: [web_site_id#90] +Functions [3]: [sum(UnscaledValue(ws_ext_sales_price#79)), sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00)), sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))] +Aggregate Attributes [3]: [sum(UnscaledValue(ws_ext_sales_price#79))#103, sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00))#104, sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))#105] +Results [5]: [web channel AS channel#106, concat(web_site, web_site_id#90) AS id#107, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#79))#103,17,2) AS sales#108, sum(coalesce(cast(wr_return_amt#85 as decimal(12,2)), 0.00))#104 AS returns#109, sum((ws_net_profit#80 - coalesce(cast(wr_net_loss#86 as decimal(12,2)), 0.00)))#105 AS profit#110] + +(102) Union + +(103) HashAggregate [codegen id : 31] +Input [5]: [channel#34, id#35, sales#36, returns#37, profit#38] +Keys [2]: [channel#34, id#35] +Functions [3]: [partial_sum(sales#36), partial_sum(returns#37), partial_sum(profit#38)] +Aggregate Attributes [6]: [sum#111, isEmpty#112, sum#113, isEmpty#114, sum#115, isEmpty#116] +Results [8]: [channel#34, id#35, sum#117, isEmpty#118, sum#119, isEmpty#120, sum#121, isEmpty#122] + +(104) Exchange +Input [8]: [channel#34, id#35, sum#117, isEmpty#118, sum#119, isEmpty#120, sum#121, isEmpty#122] +Arguments: hashpartitioning(channel#34, id#35, 5), ENSURE_REQUIREMENTS, [plan_id=15] + +(105) HashAggregate [codegen id : 32] +Input [8]: [channel#34, id#35, sum#117, isEmpty#118, sum#119, isEmpty#120, sum#121, isEmpty#122] +Keys [2]: [channel#34, id#35] +Functions [3]: [sum(sales#36), sum(returns#37), sum(profit#38)] +Aggregate Attributes [3]: [sum(sales#36)#123, sum(returns#37)#124, sum(profit#38)#125] +Results [5]: [channel#34, id#35, cast(sum(sales#36)#123 as decimal(37,2)) AS sales#126, cast(sum(returns#37)#124 as decimal(38,2)) AS returns#127, cast(sum(profit#38)#125 as decimal(38,2)) AS profit#128] + +(106) ReusedExchange [Reuses operator id: 104] +Output [8]: [channel#129, id#130, sum#131, isEmpty#132, sum#133, isEmpty#134, sum#135, isEmpty#136] + +(107) HashAggregate [codegen id : 64] +Input [8]: [channel#129, id#130, sum#131, isEmpty#132, sum#133, isEmpty#134, sum#135, isEmpty#136] +Keys [2]: [channel#129, id#130] +Functions [3]: [sum(sales#137), sum(returns#138), sum(profit#139)] +Aggregate Attributes [3]: [sum(sales#137)#123, sum(returns#138)#124, sum(profit#139)#125] +Results [4]: [channel#129, sum(sales#137)#123 AS sales#140, sum(returns#138)#124 AS returns#141, sum(profit#139)#125 AS profit#142] + +(108) HashAggregate [codegen id : 64] +Input [4]: [channel#129, sales#140, returns#141, profit#142] +Keys [1]: [channel#129] +Functions [3]: [partial_sum(sales#140), partial_sum(returns#141), partial_sum(profit#142)] +Aggregate Attributes [6]: [sum#143, isEmpty#144, sum#145, isEmpty#146, sum#147, isEmpty#148] +Results [7]: [channel#129, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] + +(109) Exchange +Input [7]: [channel#129, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] +Arguments: hashpartitioning(channel#129, 5), ENSURE_REQUIREMENTS, [plan_id=16] + +(110) HashAggregate [codegen id : 65] +Input [7]: [channel#129, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] +Keys [1]: [channel#129] +Functions [3]: [sum(sales#140), sum(returns#141), sum(profit#142)] +Aggregate Attributes [3]: [sum(sales#140)#155, sum(returns#141)#156, sum(profit#142)#157] +Results [5]: [channel#129, null AS id#158, sum(sales#140)#155 AS sales#159, sum(returns#141)#156 AS returns#160, sum(profit#142)#157 AS profit#161] + +(111) ReusedExchange [Reuses operator id: 104] +Output [8]: [channel#162, id#163, sum#164, isEmpty#165, sum#166, isEmpty#167, sum#168, isEmpty#169] + +(112) HashAggregate [codegen id : 97] +Input [8]: [channel#162, id#163, sum#164, isEmpty#165, sum#166, isEmpty#167, sum#168, isEmpty#169] +Keys [2]: [channel#162, id#163] +Functions [3]: [sum(sales#170), sum(returns#171), sum(profit#172)] +Aggregate Attributes [3]: [sum(sales#170)#123, sum(returns#171)#124, sum(profit#172)#125] +Results [3]: [sum(sales#170)#123 AS sales#173, sum(returns#171)#124 AS returns#174, sum(profit#172)#125 AS profit#175] + +(113) HashAggregate [codegen id : 97] +Input [3]: [sales#173, returns#174, profit#175] +Keys: [] +Functions [3]: [partial_sum(sales#173), partial_sum(returns#174), partial_sum(profit#175)] +Aggregate Attributes [6]: [sum#176, isEmpty#177, sum#178, isEmpty#179, sum#180, isEmpty#181] +Results [6]: [sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] + +(114) Exchange +Input [6]: [sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=17] + +(115) HashAggregate [codegen id : 98] +Input [6]: [sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] +Keys: [] +Functions [3]: [sum(sales#173), sum(returns#174), sum(profit#175)] +Aggregate Attributes [3]: [sum(sales#173)#188, sum(returns#174)#189, sum(profit#175)#190] +Results [5]: [null AS channel#191, null AS id#192, sum(sales#173)#188 AS sales#193, sum(returns#174)#189 AS returns#194, sum(profit#175)#190 AS profit#195] + +(116) Union + +(117) HashAggregate [codegen id : 99] +Input [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Keys [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#34, id#35, sales#126, returns#127, profit#128] + +(118) Exchange +Input [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Arguments: hashpartitioning(channel#34, id#35, sales#126, returns#127, profit#128, 5), ENSURE_REQUIREMENTS, [plan_id=18] + +(119) HashAggregate [codegen id : 100] +Input [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Keys [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Functions: [] +Aggregate Attributes: [] +Results [5]: [channel#34, id#35, sales#126, returns#127, profit#128] + +(120) TakeOrderedAndProject +Input [5]: [channel#34, id#35, sales#126, returns#127, profit#128] +Arguments: 100, [channel#34 ASC NULLS FIRST, id#35 ASC NULLS FIRST], [channel#34, id#35, sales#126, returns#127, profit#128] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 +BroadcastExchange (125) ++- * Project (124) + +- * Filter (123) + +- * ColumnarToRow (122) + +- CometScan parquet spark_catalog.default.date_dim (121) + + +(121) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#14, d_date#196] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1998-08-04), LessThanOrEqual(d_date,1998-09-03), IsNotNull(d_date_sk)] +ReadSchema: struct + +(122) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#14, d_date#196] + +(123) Filter [codegen id : 1] +Input [2]: [d_date_sk#14, d_date#196] +Condition : (((isnotnull(d_date#196) AND (d_date#196 >= 1998-08-04)) AND (d_date#196 <= 1998-09-03)) AND isnotnull(d_date_sk#14)) + +(124) Project [codegen id : 1] +Output [1]: [d_date_sk#14] +Input [2]: [d_date_sk#14, d_date#196] + +(125) BroadcastExchange +Input [1]: [d_date_sk#14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=19] + +Subquery:2 Hosting operator id = 40 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#8 + +Subquery:3 Hosting operator id = 71 Hosting Expression = ws_sold_date_sk#81 IN dynamicpruning#8 + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt new file mode 100644 index 000000000..047ac07a6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt @@ -0,0 +1,207 @@ +TakeOrderedAndProject [channel,id,sales,returns,profit] + WholeStageCodegen (100) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Exchange [channel,id,sales,returns,profit] #1 + WholeStageCodegen (99) + HashAggregate [channel,id,sales,returns,profit] + InputAdapter + Union + WholeStageCodegen (32) + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel,id] #2 + WholeStageCodegen (31) + HashAggregate [channel,id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Union + WholeStageCodegen (10) + HashAggregate [s_store_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(ss_ext_sales_price)),sum(coalesce(cast(sr_return_amt as decimal(12,2)), 0.00)),sum((ss_net_profit - coalesce(cast(sr_net_loss as decimal(12,2)), 0.00))),channel,id,sales,returns,profit,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [s_store_id] #3 + WholeStageCodegen (9) + HashAggregate [s_store_id,ss_ext_sales_price,sr_return_amt,ss_net_profit,sr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_promo_sk,p_promo_sk] + Project [ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Project [ss_item_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss,s_store_id] + BroadcastHashJoin [ss_store_sk,s_store_sk] + Project [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,sr_return_amt,sr_net_loss] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk,sr_return_amt,sr_net_loss] + SortMergeJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + InputAdapter + WholeStageCodegen (2) + Sort [ss_item_sk,ss_ticket_number] + InputAdapter + Exchange [ss_item_sk,ss_ticket_number] #4 + WholeStageCodegen (1) + Filter [ss_store_sk,ss_item_sk,ss_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + WholeStageCodegen (4) + Sort [sr_item_sk,sr_ticket_number] + InputAdapter + Exchange [sr_item_sk,sr_ticket_number] #6 + WholeStageCodegen (3) + Project [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss] + Filter [sr_item_sk,sr_ticket_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss,sr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + InputAdapter + BroadcastExchange #7 + WholeStageCodegen (6) + Filter [s_store_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] + InputAdapter + BroadcastExchange #8 + WholeStageCodegen (7) + Project [i_item_sk] + Filter [i_current_price,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price] + InputAdapter + BroadcastExchange #9 + WholeStageCodegen (8) + Project [p_promo_sk] + Filter [p_channel_tv,p_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_tv] + WholeStageCodegen (20) + HashAggregate [cp_catalog_page_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(cs_ext_sales_price)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum((cs_net_profit - coalesce(cast(cr_net_loss as decimal(12,2)), 0.00))),channel,id,sales,returns,profit,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [cp_catalog_page_id] #10 + WholeStageCodegen (19) + HashAggregate [cp_catalog_page_id,cs_ext_sales_price,cr_return_amount,cs_net_profit,cr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_promo_sk,p_promo_sk] + Project [cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_item_sk,i_item_sk] + Project [cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss,cp_catalog_page_id] + BroadcastHashJoin [cs_catalog_page_sk,cp_catalog_page_sk] + Project [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cr_return_amount,cr_net_loss] + BroadcastHashJoin [cs_sold_date_sk,d_date_sk] + Project [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk,cr_return_amount,cr_net_loss] + SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] + InputAdapter + WholeStageCodegen (12) + Sort [cs_item_sk,cs_order_number] + InputAdapter + Exchange [cs_item_sk,cs_order_number] #11 + WholeStageCodegen (11) + Filter [cs_catalog_page_sk,cs_item_sk,cs_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (14) + Sort [cr_item_sk,cr_order_number] + InputAdapter + Exchange [cr_item_sk,cr_order_number] #12 + WholeStageCodegen (13) + Project [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss] + Filter [cr_item_sk,cr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss,cr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + InputAdapter + BroadcastExchange #13 + WholeStageCodegen (16) + Filter [cp_catalog_page_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] + InputAdapter + ReusedExchange [i_item_sk] #8 + InputAdapter + ReusedExchange [p_promo_sk] #9 + WholeStageCodegen (30) + HashAggregate [web_site_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(ws_ext_sales_price)),sum(coalesce(cast(wr_return_amt as decimal(12,2)), 0.00)),sum((ws_net_profit - coalesce(cast(wr_net_loss as decimal(12,2)), 0.00))),channel,id,sales,returns,profit,sum,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [web_site_id] #14 + WholeStageCodegen (29) + HashAggregate [web_site_id,ws_ext_sales_price,wr_return_amt,ws_net_profit,wr_net_loss] [sum,sum,isEmpty,sum,isEmpty,sum,sum,isEmpty,sum,isEmpty] + Project [ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_promo_sk,p_promo_sk] + Project [ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss,web_site_id] + BroadcastHashJoin [ws_web_site_sk,web_site_sk] + Project [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,wr_return_amt,wr_net_loss] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Project [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk,wr_return_amt,wr_net_loss] + SortMergeJoin [ws_item_sk,ws_order_number,wr_item_sk,wr_order_number] + InputAdapter + WholeStageCodegen (22) + Sort [ws_item_sk,ws_order_number] + InputAdapter + Exchange [ws_item_sk,ws_order_number] #15 + WholeStageCodegen (21) + Filter [ws_web_site_sk,ws_item_sk,ws_promo_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_order_number,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + InputAdapter + WholeStageCodegen (24) + Sort [wr_item_sk,wr_order_number] + InputAdapter + Exchange [wr_item_sk,wr_order_number] #16 + WholeStageCodegen (23) + Project [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss] + Filter [wr_item_sk,wr_order_number] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] + InputAdapter + ReusedExchange [d_date_sk] #5 + InputAdapter + BroadcastExchange #17 + WholeStageCodegen (26) + Filter [web_site_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] + InputAdapter + ReusedExchange [i_item_sk] #8 + InputAdapter + ReusedExchange [p_promo_sk] #9 + WholeStageCodegen (65) + HashAggregate [channel,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),id,sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange [channel] #18 + WholeStageCodegen (64) + HashAggregate [channel,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 + WholeStageCodegen (98) + HashAggregate [sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),channel,id,sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + Exchange #19 + WholeStageCodegen (97) + HashAggregate [sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] + HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] + InputAdapter + ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt new file mode 100644 index 000000000..7aac30e5f --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt @@ -0,0 +1,240 @@ +== Physical Plan == +TakeOrderedAndProject (34) ++- * Project (33) + +- Window (32) + +- * Sort (31) + +- Exchange (30) + +- * HashAggregate (29) + +- Exchange (28) + +- * HashAggregate (27) + +- Union (26) + :- * HashAggregate (15) + : +- Exchange (14) + : +- * HashAggregate (13) + : +- * Project (12) + : +- * BroadcastHashJoin Inner BuildRight (11) + : :- * Project (6) + : : +- * BroadcastHashJoin Inner BuildRight (5) + : : :- * Filter (3) + : : : +- * ColumnarToRow (2) + : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : +- ReusedExchange (4) + : +- BroadcastExchange (10) + : +- * Filter (9) + : +- * ColumnarToRow (8) + : +- CometScan parquet spark_catalog.default.item (7) + :- * HashAggregate (20) + : +- Exchange (19) + : +- * HashAggregate (18) + : +- * HashAggregate (17) + : +- ReusedExchange (16) + +- * HashAggregate (25) + +- Exchange (24) + +- * HashAggregate (23) + +- * HashAggregate (22) + +- ReusedExchange (21) + + +(1) Scan parquet spark_catalog.default.web_sales +Output [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ws_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] + +(3) Filter [codegen id : 3] +Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) + +(4) ReusedExchange [Reuses operator id: 39] +Output [1]: [d_date_sk#5] + +(5) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_sold_date_sk#3] +Right keys [1]: [d_date_sk#5] +Join type: Inner +Join condition: None + +(6) Project [codegen id : 3] +Output [2]: [ws_item_sk#1, ws_net_paid#2] +Input [4]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3, d_date_sk#5] + +(7) Scan parquet spark_catalog.default.item +Output [3]: [i_item_sk#6, i_class#7, i_category#8] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [IsNotNull(i_item_sk)] +ReadSchema: struct + +(8) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#6, i_class#7, i_category#8] + +(9) Filter [codegen id : 2] +Input [3]: [i_item_sk#6, i_class#7, i_category#8] +Condition : isnotnull(i_item_sk#6) + +(10) BroadcastExchange +Input [3]: [i_item_sk#6, i_class#7, i_category#8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ws_item_sk#1] +Right keys [1]: [i_item_sk#6] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [3]: [ws_net_paid#2, i_class#7, i_category#8] +Input [5]: [ws_item_sk#1, ws_net_paid#2, i_item_sk#6, i_class#7, i_category#8] + +(13) HashAggregate [codegen id : 3] +Input [3]: [ws_net_paid#2, i_class#7, i_category#8] +Keys [2]: [i_category#8, i_class#7] +Functions [1]: [partial_sum(UnscaledValue(ws_net_paid#2))] +Aggregate Attributes [1]: [sum#9] +Results [3]: [i_category#8, i_class#7, sum#10] + +(14) Exchange +Input [3]: [i_category#8, i_class#7, sum#10] +Arguments: hashpartitioning(i_category#8, i_class#7, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [3]: [i_category#8, i_class#7, sum#10] +Keys [2]: [i_category#8, i_class#7] +Functions [1]: [sum(UnscaledValue(ws_net_paid#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#2))#11] +Results [6]: [cast(MakeDecimal(sum(UnscaledValue(ws_net_paid#2))#11,17,2) as decimal(27,2)) AS total_sum#12, i_category#8, i_class#7, 0 AS g_category#13, 0 AS g_class#14, 0 AS lochierarchy#15] + +(16) ReusedExchange [Reuses operator id: 14] +Output [3]: [i_category#16, i_class#17, sum#18] + +(17) HashAggregate [codegen id : 8] +Input [3]: [i_category#16, i_class#17, sum#18] +Keys [2]: [i_category#16, i_class#17] +Functions [1]: [sum(UnscaledValue(ws_net_paid#19))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#19))#11] +Results [2]: [MakeDecimal(sum(UnscaledValue(ws_net_paid#19))#11,17,2) AS total_sum#20, i_category#16] + +(18) HashAggregate [codegen id : 8] +Input [2]: [total_sum#20, i_category#16] +Keys [1]: [i_category#16] +Functions [1]: [partial_sum(total_sum#20)] +Aggregate Attributes [2]: [sum#21, isEmpty#22] +Results [3]: [i_category#16, sum#23, isEmpty#24] + +(19) Exchange +Input [3]: [i_category#16, sum#23, isEmpty#24] +Arguments: hashpartitioning(i_category#16, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(20) HashAggregate [codegen id : 9] +Input [3]: [i_category#16, sum#23, isEmpty#24] +Keys [1]: [i_category#16] +Functions [1]: [sum(total_sum#20)] +Aggregate Attributes [1]: [sum(total_sum#20)#25] +Results [6]: [sum(total_sum#20)#25 AS total_sum#26, i_category#16, null AS i_class#27, 0 AS g_category#28, 1 AS g_class#29, 1 AS lochierarchy#30] + +(21) ReusedExchange [Reuses operator id: 14] +Output [3]: [i_category#31, i_class#32, sum#33] + +(22) HashAggregate [codegen id : 13] +Input [3]: [i_category#31, i_class#32, sum#33] +Keys [2]: [i_category#31, i_class#32] +Functions [1]: [sum(UnscaledValue(ws_net_paid#34))] +Aggregate Attributes [1]: [sum(UnscaledValue(ws_net_paid#34))#11] +Results [1]: [MakeDecimal(sum(UnscaledValue(ws_net_paid#34))#11,17,2) AS total_sum#35] + +(23) HashAggregate [codegen id : 13] +Input [1]: [total_sum#35] +Keys: [] +Functions [1]: [partial_sum(total_sum#35)] +Aggregate Attributes [2]: [sum#36, isEmpty#37] +Results [2]: [sum#38, isEmpty#39] + +(24) Exchange +Input [2]: [sum#38, isEmpty#39] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] + +(25) HashAggregate [codegen id : 14] +Input [2]: [sum#38, isEmpty#39] +Keys: [] +Functions [1]: [sum(total_sum#35)] +Aggregate Attributes [1]: [sum(total_sum#35)#40] +Results [6]: [sum(total_sum#35)#40 AS total_sum#41, null AS i_category#42, null AS i_class#43, 1 AS g_category#44, 1 AS g_class#45, 2 AS lochierarchy#46] + +(26) Union + +(27) HashAggregate [codegen id : 15] +Input [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] +Keys [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] +Functions: [] +Aggregate Attributes: [] +Results [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] + +(28) Exchange +Input [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] +Arguments: hashpartitioning(total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15, 5), ENSURE_REQUIREMENTS, [plan_id=5] + +(29) HashAggregate [codegen id : 16] +Input [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] +Keys [6]: [total_sum#12, i_category#8, i_class#7, g_category#13, g_class#14, lochierarchy#15] +Functions: [] +Aggregate Attributes: [] +Results [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, CASE WHEN (g_class#14 = 0) THEN i_category#8 END AS _w0#47] + +(30) Exchange +Input [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, _w0#47] +Arguments: hashpartitioning(lochierarchy#15, _w0#47, 5), ENSURE_REQUIREMENTS, [plan_id=6] + +(31) Sort [codegen id : 17] +Input [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, _w0#47] +Arguments: [lochierarchy#15 ASC NULLS FIRST, _w0#47 ASC NULLS FIRST, total_sum#12 DESC NULLS LAST], false, 0 + +(32) Window +Input [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, _w0#47] +Arguments: [rank(total_sum#12) windowspecdefinition(lochierarchy#15, _w0#47, total_sum#12 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#48], [lochierarchy#15, _w0#47], [total_sum#12 DESC NULLS LAST] + +(33) Project [codegen id : 18] +Output [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, rank_within_parent#48] +Input [6]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, _w0#47, rank_within_parent#48] + +(34) TakeOrderedAndProject +Input [5]: [total_sum#12, i_category#8, i_class#7, lochierarchy#15, rank_within_parent#48] +Arguments: 100, [lochierarchy#15 DESC NULLS LAST, CASE WHEN (lochierarchy#15 = 0) THEN i_category#8 END ASC NULLS FIRST, rank_within_parent#48 ASC NULLS FIRST], [total_sum#12, i_category#8, i_class#7, lochierarchy#15, rank_within_parent#48] + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (39) ++- * Project (38) + +- * Filter (37) + +- * ColumnarToRow (36) + +- CometScan parquet spark_catalog.default.date_dim (35) + + +(35) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#5, d_month_seq#49] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] +ReadSchema: struct + +(36) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#49] + +(37) Filter [codegen id : 1] +Input [2]: [d_date_sk#5, d_month_seq#49] +Condition : (((isnotnull(d_month_seq#49) AND (d_month_seq#49 >= 1212)) AND (d_month_seq#49 <= 1223)) AND isnotnull(d_date_sk#5)) + +(38) Project [codegen id : 1] +Output [1]: [d_date_sk#5] +Input [2]: [d_date_sk#5, d_month_seq#49] + +(39) BroadcastExchange +Input [1]: [d_date_sk#5] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt new file mode 100644 index 000000000..5146ee0d2 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt @@ -0,0 +1,66 @@ +TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,total_sum,i_class] + WholeStageCodegen (18) + Project [total_sum,i_category,i_class,lochierarchy,rank_within_parent] + InputAdapter + Window [total_sum,lochierarchy,_w0] + WholeStageCodegen (17) + Sort [lochierarchy,_w0,total_sum] + InputAdapter + Exchange [lochierarchy,_w0] #1 + WholeStageCodegen (16) + HashAggregate [total_sum,i_category,i_class,g_category,g_class,lochierarchy] [_w0] + InputAdapter + Exchange [total_sum,i_category,i_class,g_category,g_class,lochierarchy] #2 + WholeStageCodegen (15) + HashAggregate [total_sum,i_category,i_class,g_category,g_class,lochierarchy] + InputAdapter + Union + WholeStageCodegen (4) + HashAggregate [i_category,i_class,sum] [sum(UnscaledValue(ws_net_paid)),total_sum,g_category,g_class,lochierarchy,sum] + InputAdapter + Exchange [i_category,i_class] #3 + WholeStageCodegen (3) + HashAggregate [i_category,i_class,ws_net_paid] [sum,sum] + Project [ws_net_paid,i_class,i_category] + BroadcastHashJoin [ws_item_sk,i_item_sk] + Project [ws_item_sk,ws_net_paid] + BroadcastHashJoin [ws_sold_date_sk,d_date_sk] + Filter [ws_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_net_paid,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_month_seq,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] + InputAdapter + ReusedExchange [d_date_sk] #4 + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (2) + Filter [i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] + WholeStageCodegen (9) + HashAggregate [i_category,sum,isEmpty] [sum(total_sum),total_sum,i_class,g_category,g_class,lochierarchy,sum,isEmpty] + InputAdapter + Exchange [i_category] #6 + WholeStageCodegen (8) + HashAggregate [i_category,total_sum] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,sum] [sum(UnscaledValue(ws_net_paid)),total_sum,sum] + InputAdapter + ReusedExchange [i_category,i_class,sum] #3 + WholeStageCodegen (14) + HashAggregate [sum,isEmpty] [sum(total_sum),total_sum,i_category,i_class,g_category,g_class,lochierarchy,sum,isEmpty] + InputAdapter + Exchange #7 + WholeStageCodegen (13) + HashAggregate [total_sum] [sum,isEmpty,sum,isEmpty] + HashAggregate [i_category,i_class,sum] [sum(UnscaledValue(ws_net_paid)),total_sum,sum] + InputAdapter + ReusedExchange [i_category,i_class,sum] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt new file mode 100644 index 000000000..a2f3cffb6 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt @@ -0,0 +1,155 @@ +== Physical Plan == +* Sort (21) ++- Exchange (20) + +- * Project (19) + +- Window (18) + +- * Sort (17) + +- Exchange (16) + +- * HashAggregate (15) + +- Exchange (14) + +- * HashAggregate (13) + +- * Project (12) + +- * BroadcastHashJoin Inner BuildRight (11) + :- * Project (9) + : +- * BroadcastHashJoin Inner BuildRight (8) + : :- * Filter (3) + : : +- * ColumnarToRow (2) + : : +- CometScan parquet spark_catalog.default.store_sales (1) + : +- BroadcastExchange (7) + : +- * Filter (6) + : +- * ColumnarToRow (5) + : +- CometScan parquet spark_catalog.default.item (4) + +- ReusedExchange (10) + + +(1) Scan parquet spark_catalog.default.store_sales +Output [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Batched: true +Location: InMemoryFileIndex [] +PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)] +PushedFilters: [IsNotNull(ss_item_sk)] +ReadSchema: struct + +(2) ColumnarToRow [codegen id : 3] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] + +(3) Filter [codegen id : 3] +Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_item_sk#1) + +(4) Scan parquet spark_catalog.default.item +Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Batched: true +Location [not included in comparison]/{warehouse_dir}/item] +PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] +ReadSchema: struct + +(5) ColumnarToRow [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(6) Filter [codegen id : 1] +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) + +(7) BroadcastExchange +Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] + +(8) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_item_sk#1] +Right keys [1]: [i_item_sk#5] +Join type: Inner +Join condition: None + +(9) Project [codegen id : 3] +Output [7]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [9]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] + +(10) ReusedExchange [Reuses operator id: 26] +Output [1]: [d_date_sk#11] + +(11) BroadcastHashJoin [codegen id : 3] +Left keys [1]: [ss_sold_date_sk#3] +Right keys [1]: [d_date_sk#11] +Join type: Inner +Join condition: None + +(12) Project [codegen id : 3] +Output [6]: [ss_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Input [8]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10, d_date_sk#11] + +(13) HashAggregate [codegen id : 3] +Input [6]: [ss_ext_sales_price#2, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum#12] +Results [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] + +(14) Exchange +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Arguments: hashpartitioning(i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, 5), ENSURE_REQUIREMENTS, [plan_id=2] + +(15) HashAggregate [codegen id : 4] +Input [6]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, sum#13] +Keys [5]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8] +Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#2))] +Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#2))#14] +Results [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#14,17,2) AS itemrevenue#15, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#14,17,2) AS _w0#16] + +(16) Exchange +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: hashpartitioning(i_class#9, 5), ENSURE_REQUIREMENTS, [plan_id=3] + +(17) Sort [codegen id : 5] +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [i_class#9 ASC NULLS FIRST], false, 0 + +(18) Window +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16] +Arguments: [sum(_w0#16) windowspecdefinition(i_class#9, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS _we0#17], [i_class#9] + +(19) Project [codegen id : 6] +Output [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, ((_w0#16 * 100) / _we0#17) AS revenueratio#18] +Input [8]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, _w0#16, _we0#17] + +(20) Exchange +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] +Arguments: rangepartitioning(i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=4] + +(21) Sort [codegen id : 7] +Input [7]: [i_item_id#6, i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemrevenue#15, revenueratio#18] +Arguments: [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id#6 ASC NULLS FIRST, i_item_desc#7 ASC NULLS FIRST, revenueratio#18 ASC NULLS FIRST], true, 0 + +===== Subqueries ===== + +Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 +BroadcastExchange (26) ++- * Project (25) + +- * Filter (24) + +- * ColumnarToRow (23) + +- CometScan parquet spark_catalog.default.date_dim (22) + + +(22) Scan parquet spark_catalog.default.date_dim +Output [2]: [d_date_sk#11, d_date#19] +Batched: true +Location [not included in comparison]/{warehouse_dir}/date_dim] +PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] +ReadSchema: struct + +(23) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] + +(24) Filter [codegen id : 1] +Input [2]: [d_date_sk#11, d_date#19] +Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) + +(25) Project [codegen id : 1] +Output [1]: [d_date_sk#11] +Input [2]: [d_date_sk#11, d_date#19] + +(26) BroadcastExchange +Input [1]: [d_date_sk#11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] + + diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt new file mode 100644 index 000000000..5aa7c17f1 --- /dev/null +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt @@ -0,0 +1,43 @@ +WholeStageCodegen (7) + Sort [i_category,i_class,i_item_id,i_item_desc,revenueratio] + InputAdapter + Exchange [i_category,i_class,i_item_id,i_item_desc,revenueratio] #1 + WholeStageCodegen (6) + Project [i_item_id,i_item_desc,i_category,i_class,i_current_price,itemrevenue,_w0,_we0] + InputAdapter + Window [_w0,i_class] + WholeStageCodegen (5) + Sort [i_class] + InputAdapter + Exchange [i_class] #2 + WholeStageCodegen (4) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,sum] [sum(UnscaledValue(ss_ext_sales_price)),itemrevenue,_w0,sum] + InputAdapter + Exchange [i_item_id,i_item_desc,i_category,i_class,i_current_price] #3 + WholeStageCodegen (3) + HashAggregate [i_item_id,i_item_desc,i_category,i_class,i_current_price,ss_ext_sales_price] [sum,sum] + Project [ss_ext_sales_price,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ss_sold_date_sk,d_date_sk] + Project [ss_ext_sales_price,ss_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + BroadcastHashJoin [ss_item_sk,i_item_sk] + Filter [ss_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + Project [d_date_sk] + Filter [d_date,d_date_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + InputAdapter + BroadcastExchange #5 + WholeStageCodegen (1) + Filter [i_category,i_item_sk] + ColumnarToRow + InputAdapter + CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] + InputAdapter + ReusedExchange [d_date_sk] #4 diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala index ac6c17d2a..22d016c66 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala @@ -298,8 +298,9 @@ trait CometPlanStabilitySuite extends DisableAdaptiveExecutionSuite with TPCDSBa } class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { - private val planName = if (isSpark40Plus) { "approved-plans-v1_4-spark4_0" } - else { "approved-plans-v1_4" } + // TODO: remove the Spark 4.0 golden file once ANSI is fully supported + private val planName = + if (isSpark40Plus) "approved-plans-v1_4-spark4_0" else "approved-plans-v1_4" override val goldenFilePath: String = new File(baseResourcePath, planName).getAbsolutePath @@ -311,8 +312,9 @@ class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { } class CometTPCDSV2_7_PlanStabilitySuite extends CometPlanStabilitySuite { - private val planName = if (isSpark40Plus) { "approved-plans-v2_7-spark4_0" } - else { "approved-plans-v2_7" } + // TODO: remove the Spark 4.0 golden file once ANSI is fully supported + private val planName = + if (isSpark40Plus) "approved-plans-v2_7-spark4_0" else "approved-plans-v2_7" override val goldenFilePath: String = new File(baseResourcePath, planName).getAbsolutePath From e258273ef01743a4a9c081994feb4b963d4c83f9 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 16 May 2024 23:23:40 -0700 Subject: [PATCH 29/68] build: Enable spark-4.0 tests --- .../org/apache/comet/exec/CometColumnarShuffleSuite.scala | 2 +- .../test/scala/org/apache/comet/exec/CometJoinSuite.scala | 4 ++-- .../src/test/scala/org/apache/spark/CometPluginsSuite.scala | 4 ++-- .../apache/spark/sql/comet/CometPlanStabilitySuite.scala | 6 +++--- .../apache/spark/sql/comet/ParquetEncryptionITCase.scala | 4 ++-- 5 files changed, 10 insertions(+), 10 deletions(-) diff --git a/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala b/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala index 74a1dd5a8..35cb0055d 100644 --- a/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala +++ b/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala @@ -1003,7 +1003,7 @@ class CometShuffleSuite extends CometColumnarShuffleSuite with DisableSuite { } } -class DisableAQECometShuffleSuite extends CometColumnarShuffleSuite { +class DisableAQECometShuffleSuite extends CometColumnarShuffleSuite with DisableSuite { override protected val asyncShuffleEnable: Boolean = false protected val adaptiveExecutionEnabled: Boolean = false diff --git a/spark/src/test/scala/org/apache/comet/exec/CometJoinSuite.scala b/spark/src/test/scala/org/apache/comet/exec/CometJoinSuite.scala index 91d88c76e..4e23b01fc 100644 --- a/spark/src/test/scala/org/apache/comet/exec/CometJoinSuite.scala +++ b/spark/src/test/scala/org/apache/comet/exec/CometJoinSuite.scala @@ -22,14 +22,14 @@ package org.apache.comet.exec import org.scalactic.source.Position import org.scalatest.Tag -import org.apache.spark.sql.CometTestBase +import org.apache.spark.sql.{CometTestBase, DisableSuite} import org.apache.spark.sql.comet.{CometBroadcastExchangeExec, CometBroadcastHashJoinExec} import org.apache.spark.sql.internal.SQLConf import org.apache.comet.CometConf import org.apache.comet.CometSparkSessionExtensions.isSpark34Plus -class CometJoinSuite extends CometTestBase { +class CometJoinSuite extends CometTestBase with DisableSuite { override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit pos: Position): Unit = { diff --git a/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala b/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala index 83e1257e4..c5ab61bd5 100644 --- a/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala +++ b/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala @@ -21,7 +21,7 @@ package org.apache.spark import org.apache.spark.sql.{CometTestBase, DisableSuite} -class CometPluginsSuite extends CometTestBase { +class CometPluginsSuite extends CometTestBase with DisableSuite { override protected def sparkConf: SparkConf = { val conf = new SparkConf() conf.set("spark.driver.memory", "1G") @@ -47,7 +47,7 @@ class CometPluginsSuite extends CometTestBase { } } -class CometPluginsDefaultSuite extends CometTestBase { +class CometPluginsDefaultSuite extends CometTestBase with DisableSuite { override protected def sparkConf: SparkConf = { val conf = new SparkConf() conf.set("spark.driver.memory", "1G") diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala index 22d016c66..07c633c5a 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala @@ -26,7 +26,7 @@ import scala.collection.mutable import org.apache.commons.io.FileUtils import org.apache.spark.SparkContext -import org.apache.spark.sql.TPCDSBase +import org.apache.spark.sql.{DisableSuite, TPCDSBase} import org.apache.spark.sql.catalyst.expressions.AttributeSet import org.apache.spark.sql.catalyst.util.resourceToString import org.apache.spark.sql.execution.{FormattedMode, ReusedSubqueryExec, SparkPlan, SubqueryBroadcastExec, SubqueryExec} @@ -297,7 +297,7 @@ trait CometPlanStabilitySuite extends DisableAdaptiveExecutionSuite with TPCDSBa System.getenv("SPARK_GENERATE_GOLDEN_FILES") == "1" } -class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { +class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite with DisableSuite { // TODO: remove the Spark 4.0 golden file once ANSI is fully supported private val planName = if (isSpark40Plus) "approved-plans-v1_4-spark4_0" else "approved-plans-v1_4" @@ -311,7 +311,7 @@ class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { } } -class CometTPCDSV2_7_PlanStabilitySuite extends CometPlanStabilitySuite { +class CometTPCDSV2_7_PlanStabilitySuite extends CometPlanStabilitySuite with DisableSuite { // TODO: remove the Spark 4.0 golden file once ANSI is fully supported private val planName = if (isSpark40Plus) "approved-plans-v2_7-spark4_0" else "approved-plans-v2_7" diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetEncryptionITCase.scala b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetEncryptionITCase.scala index 0d1a105ff..1cb9a1e9f 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetEncryptionITCase.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetEncryptionITCase.scala @@ -30,7 +30,7 @@ import org.scalatest.Tag import org.scalatestplus.junit.JUnitRunner import org.apache.spark.{DebugFilesystem, SparkConf} -import org.apache.spark.sql.{QueryTest, SparkSession, SQLContext} +import org.apache.spark.sql.{DisableSuite, QueryTest, SparkSession, SQLContext} import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.test.SQLTestUtils @@ -41,7 +41,7 @@ import org.apache.comet.{CometConf, CometSparkSessionExtensions, IntegrationTest */ @RunWith(classOf[JUnitRunner]) @IntegrationTestSuite -class ParquetEncryptionITCase extends QueryTest with SQLTestUtils { +class ParquetEncryptionITCase extends QueryTest with SQLTestUtils with DisableSuite { private val encoder = Base64.getEncoder private val footerKey = encoder.encodeToString("0123456789012345".getBytes(StandardCharsets.UTF_8)) From c1fd154494aa9ba0673776d09215d6019e2331cb Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Fri, 17 May 2024 01:58:39 -0700 Subject: [PATCH 30/68] build: Enable spark-4.0 tests --- .../spark/sql/comet/ParquetDatetimeRebaseSuite.scala | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala index 5bb7e8f70..a829d7449 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala @@ -27,6 +27,7 @@ import org.apache.spark.sql.{CometTestBase, DataFrame, Dataset, Row} import org.apache.spark.sql.internal.SQLConf import org.apache.comet.CometConf +import org.apache.comet.CometSparkSessionExtensions.isSpark40Plus // This test checks if Comet reads ancient dates & timestamps that are before 1582, as if they are // read according to the `LegacyBehaviorPolicy.CORRECTED` mode (i.e., no rebase) in Spark. @@ -48,7 +49,8 @@ abstract class ParquetDatetimeRebaseSuite extends CometTestBase { val df = spark.read.parquet(file) // Parquet file written by 2.4.5 should throw exception for both Spark and Comet - if (exceptionOnRebase || sparkVersion == "2_4_5") { + // For Spark 4.0+, Parquet file written by 2.4.5 should not throw exception + if ((exceptionOnRebase || sparkVersion == "2_4_5") && (!isSpark40Plus || sparkVersion != "2_4_5")) { intercept[SparkException](df.collect()) } else { checkSparkNoRebaseAnswer(df) @@ -70,7 +72,8 @@ abstract class ParquetDatetimeRebaseSuite extends CometTestBase { val df = spark.read.parquet(file) // Parquet file written by 2.4.5 should throw exception for both Spark and Comet - if (exceptionOnRebase || sparkVersion == "2_4_5") { + // For Spark 4.0+, Parquet file written by 2.4.5 should not throw exception + if ((exceptionOnRebase || sparkVersion == "2_4_5") && (!isSpark40Plus || sparkVersion != "2_4_5")) { intercept[SparkException](df.collect()) } else { checkSparkNoRebaseAnswer(df) @@ -93,7 +96,8 @@ abstract class ParquetDatetimeRebaseSuite extends CometTestBase { val df = spark.read.parquet(file) // Parquet file written by 2.4.5 should throw exception for both Spark and Comet - if (exceptionOnRebase || sparkVersion == "2_4_5") { + // For Spark 4.0+, Parquet file written by 2.4.5 should not throw exception + if ((exceptionOnRebase || sparkVersion == "2_4_5") && (!isSpark40Plus || sparkVersion != "2_4_5")) { intercept[SparkException](df.collect()) } else { checkSparkNoRebaseAnswer(df) From 80a292b7a92b9e3fac0b8c1f8d3e51992443d3e2 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Fri, 17 May 2024 02:34:34 -0700 Subject: [PATCH 31/68] build: Enable spark-4.0 tests --- .../apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala index a829d7449..bacbd048b 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala @@ -23,7 +23,7 @@ import org.scalactic.source.Position import org.scalatest.Tag import org.apache.spark.SparkException -import org.apache.spark.sql.{CometTestBase, DataFrame, Dataset, Row} +import org.apache.spark.sql.{CometTestBase, DataFrame, Dataset, DisableSuite, Row} import org.apache.spark.sql.internal.SQLConf import org.apache.comet.CometConf @@ -31,7 +31,7 @@ import org.apache.comet.CometSparkSessionExtensions.isSpark40Plus // This test checks if Comet reads ancient dates & timestamps that are before 1582, as if they are // read according to the `LegacyBehaviorPolicy.CORRECTED` mode (i.e., no rebase) in Spark. -abstract class ParquetDatetimeRebaseSuite extends CometTestBase { +abstract class ParquetDatetimeRebaseSuite extends CometTestBase with DisableSuite { // This is a flag defined in Spark's `org.apache.spark.internal.config.Tests` but is only // visible under package `spark`. From 3335e4d17f31f01f2351aa2fde2a0935b149f4a8 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Mon, 20 May 2024 13:00:31 -0700 Subject: [PATCH 32/68] address review comments --- .../spark/sql/comet/DecimalPrecision.scala | 11 +++++-- .../comet/shims/ShimDecimalPrecision.scala | 33 ------------------- .../comet/shims/ShimDecimalPrecision.scala | 29 ---------------- 3 files changed, 9 insertions(+), 64 deletions(-) delete mode 100644 spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala delete mode 100644 spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala b/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala index baeb4de03..a2cdf421c 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/DecimalPrecision.scala @@ -22,7 +22,6 @@ package org.apache.spark.sql.comet import scala.math.{max, min} import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.comet.shims.ShimDecimalPrecision import org.apache.spark.sql.types.DecimalType /** @@ -41,7 +40,7 @@ import org.apache.spark.sql.types.DecimalType * TODO: instead of relying on this rule, it's probably better to enhance arithmetic kernels to * handle different decimal precisions */ -object DecimalPrecision extends ShimDecimalPrecision { +object DecimalPrecision { def promote( allowPrecisionLoss: Boolean, expr: Expression, @@ -108,4 +107,12 @@ object DecimalPrecision extends ShimDecimalPrecision { case e => e } } + + // TODO: consider to use `org.apache.spark.sql.types.DecimalExpression` for Spark 3.5+ + object DecimalExpression { + def unapply(e: Expression): Option[(Int, Int)] = e.dataType match { + case t: DecimalType => Some((t.precision, t.scale)) + case _ => None + } + } } diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala deleted file mode 100644 index 28416ff8c..000000000 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala +++ /dev/null @@ -1,33 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -package org.apache.spark.sql.comet.shims - -import org.apache.spark.sql.catalyst.expressions.Expression -import org.apache.spark.sql.types.DecimalType - -trait ShimDecimalPrecision { - // `org.apache.spark.sql.types.DecimalExpression` is added in Spark 3.5 - object DecimalExpression { - def unapply(e: Expression): Option[(Int, Int)] = e.dataType match { - case t: DecimalType => Some((t.precision, t.scale)) - case _ => None - } - } -} diff --git a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala deleted file mode 100644 index ab123695b..000000000 --- a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimDecimalPrecision.scala +++ /dev/null @@ -1,29 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -package org.apache.spark.sql.comet.shims - -import org.apache.spark.sql.catalyst.expressions.Expression - -trait ShimDecimalPrecision { - object DecimalExpression { - def unapply(e: Expression): Option[(Int, Int)] = - org.apache.spark.sql.types.DecimalExpression.unapply(e) - } -} From f0f8b0cfe64c01de61ba8bc5679f01113723577e Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 21 May 2024 14:14:05 -0700 Subject: [PATCH 33/68] address review comments --- .../comet/execution/shuffle/CometShuffleExchangeExec.scala | 5 +++-- .../sql/comet/shims/ShimCometShuffleWriteProcessor.scala | 4 +--- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala b/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala index 94d3b7cac..3f4d7bfd3 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/execution/shuffle/CometShuffleExchangeExec.scala @@ -458,7 +458,6 @@ class CometShuffleWriteProcessor( new SQLShuffleWriteMetricsReporter(context.taskMetrics().shuffleWriteMetrics, metrics) } - // FIXME: we need actually prev of rdd? override def write( inputs: Iterator[_], dep: ShuffleDependency[_, _, _], @@ -483,8 +482,10 @@ class CometShuffleWriteProcessor( "elapsed_compute" -> metrics("shuffleReadElapsedCompute")) val nativeMetrics = CometMetricNode(nativeSQLMetrics) + // Getting rid of the fake partitionId + val newInputs = inputs.asInstanceOf[Iterator[_ <: Product2[Any, Any]]].map(_._2) val cometIter = CometExec.getCometIterator( - Seq(inputs.asInstanceOf[Iterator[ColumnarBatch]]), + Seq(newInputs.asInstanceOf[Iterator[ColumnarBatch]]), nativePlan, nativeMetrics) diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala index 0712352ff..36fb3a609 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala @@ -32,9 +32,7 @@ trait ShimCometShuffleWriteProcessor extends ShuffleWriteProcessor { mapId: Long, context: TaskContext, partition: Partition): MapStatus = { - // Getting rid of the fake partitionId - val cometRDD = rdd.asInstanceOf[MapPartitionsRDD[_, _]].prev.asInstanceOf[RDD[ColumnarBatch]] - val rawIter = cometRDD.iterator(partition, context) + val rawIter = rdd.iterator(partition, context) write(rawIter, dep, mapId, partition.index, context) } From f5aa2b448aa9a57f375ee1204c016fe6d96f72c2 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 21 May 2024 14:43:55 -0700 Subject: [PATCH 34/68] build: Enable spark-4.0 tests --- .../org/apache/comet/CometCastSuite.scala | 4 +-- .../comet/CometExpressionCoverageSuite.scala | 7 ++-- .../apache/comet/CometExpressionSuite.scala | 4 +-- .../CometSparkSessionExtensionsSuite.scala | 2 +- .../exec/CometColumnarShuffleSuite.scala | 14 ++++---- .../apache/comet/exec/CometJoinSuite.scala | 4 +-- .../comet/parquet/ParquetReadSuite.scala | 6 ++-- .../org/apache/spark/CometPluginsSuite.scala | 8 ++--- .../org/apache/spark/sql/DisableSuite.scala | 32 ------------------- .../sql/comet/CometPlanStabilitySuite.scala | 6 ++-- .../comet/ParquetDatetimeRebaseSuite.scala | 4 +-- .../sql/comet/ParquetEncryptionITCase.scala | 4 +-- .../comet/CometExpression3_3PlusSuite.scala | 4 +-- .../comet/exec/CometExec3_4PlusSuite.scala | 4 +-- 14 files changed, 34 insertions(+), 69 deletions(-) delete mode 100644 spark/src/test/scala/org/apache/spark/sql/DisableSuite.scala diff --git a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala index 1f0c97d52..10a7ae456 100644 --- a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala @@ -23,7 +23,7 @@ import java.io.File import scala.util.Random -import org.apache.spark.sql.{CometTestBase, DataFrame, DisableSuite, SaveMode} +import org.apache.spark.sql.{CometTestBase, DataFrame, SaveMode} import org.apache.spark.sql.catalyst.expressions.Cast import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper import org.apache.spark.sql.functions.col @@ -32,7 +32,7 @@ import org.apache.spark.sql.types.{DataType, DataTypes, DecimalType} import org.apache.comet.expressions.{CometCast, Compatible} -class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper with DisableSuite { +class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper { import testImplicits._ /** Create a data generator using a fixed seed so that tests are reproducible */ diff --git a/spark/src/test/scala/org/apache/comet/CometExpressionCoverageSuite.scala b/spark/src/test/scala/org/apache/comet/CometExpressionCoverageSuite.scala index 1dfd417b8..2011dcd4b 100644 --- a/spark/src/test/scala/org/apache/comet/CometExpressionCoverageSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometExpressionCoverageSuite.scala @@ -27,7 +27,7 @@ import scala.collection.mutable import org.scalatest.Ignore import org.scalatest.exceptions.TestFailedException -import org.apache.spark.sql.{CometTestBase, DisableSuite} +import org.apache.spark.sql.CometTestBase import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper /** @@ -37,10 +37,7 @@ import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper * doc/spark_builtin_expr_coverage_agg.txt */ @Ignore -class CometExpressionCoverageSuite - extends CometTestBase - with AdaptiveSparkPlanHelper - with DisableSuite { +class CometExpressionCoverageSuite extends CometTestBase with AdaptiveSparkPlanHelper { import testImplicits._ diff --git a/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala b/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala index 234d1e274..98a2bad02 100644 --- a/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala @@ -20,7 +20,7 @@ package org.apache.comet import org.apache.hadoop.fs.Path -import org.apache.spark.sql.{CometTestBase, DataFrame, DisableSuite, Row} +import org.apache.spark.sql.{CometTestBase, DataFrame, Row} import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper import org.apache.spark.sql.functions.expr import org.apache.spark.sql.internal.SQLConf @@ -29,7 +29,7 @@ import org.apache.spark.sql.types.{Decimal, DecimalType} import org.apache.comet.CometSparkSessionExtensions.{isSpark32, isSpark33Plus, isSpark34Plus} -class CometExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelper with DisableSuite { +class CometExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelper { import testImplicits._ test("coalesce should return correct datatype") { diff --git a/spark/src/test/scala/org/apache/comet/CometSparkSessionExtensionsSuite.scala b/spark/src/test/scala/org/apache/comet/CometSparkSessionExtensionsSuite.scala index 426dfa40a..fdcd307be 100644 --- a/spark/src/test/scala/org/apache/comet/CometSparkSessionExtensionsSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometSparkSessionExtensionsSuite.scala @@ -24,7 +24,7 @@ import org.apache.spark.sql._ import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.types._ -class CometSparkSessionExtensionsSuite extends CometTestBase with DisableSuite { +class CometSparkSessionExtensionsSuite extends CometTestBase { test("unsupported Spark types") { Seq( NullType -> false, diff --git a/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala b/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala index 35cb0055d..600f9c44f 100644 --- a/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala +++ b/spark/src/test/scala/org/apache/comet/exec/CometColumnarShuffleSuite.scala @@ -24,7 +24,7 @@ import org.scalatest.Tag import org.apache.hadoop.fs.Path import org.apache.spark.{Partitioner, SparkConf} -import org.apache.spark.sql.{CometTestBase, DataFrame, DisableSuite, Row} +import org.apache.spark.sql.{CometTestBase, DataFrame, Row} import org.apache.spark.sql.comet.execution.shuffle.{CometShuffleDependency, CometShuffleExchangeExec, CometShuffleManager} import org.apache.spark.sql.execution.adaptive.{AdaptiveSparkPlanHelper, AQEShuffleReadExec, ShuffleQueryStageExec} import org.apache.spark.sql.execution.exchange.ReusedExchangeExec @@ -944,13 +944,13 @@ abstract class CometColumnarShuffleSuite extends CometTestBase with AdaptiveSpar } } -class CometAsyncShuffleSuite extends CometColumnarShuffleSuite with DisableSuite { +class CometAsyncShuffleSuite extends CometColumnarShuffleSuite { override protected val asyncShuffleEnable: Boolean = true protected val adaptiveExecutionEnabled: Boolean = true } -class CometShuffleSuite extends CometColumnarShuffleSuite with DisableSuite { +class CometShuffleSuite extends CometColumnarShuffleSuite { override protected val asyncShuffleEnable: Boolean = false protected val adaptiveExecutionEnabled: Boolean = true @@ -1003,7 +1003,7 @@ class CometShuffleSuite extends CometColumnarShuffleSuite with DisableSuite { } } -class DisableAQECometShuffleSuite extends CometColumnarShuffleSuite with DisableSuite { +class DisableAQECometShuffleSuite extends CometColumnarShuffleSuite { override protected val asyncShuffleEnable: Boolean = false protected val adaptiveExecutionEnabled: Boolean = false @@ -1035,13 +1035,13 @@ class DisableAQECometShuffleSuite extends CometColumnarShuffleSuite with Disable } } -class DisableAQECometAsyncShuffleSuite extends CometColumnarShuffleSuite with DisableSuite { +class DisableAQECometAsyncShuffleSuite extends CometColumnarShuffleSuite { override protected val asyncShuffleEnable: Boolean = true protected val adaptiveExecutionEnabled: Boolean = false } -class CometShuffleEncryptionSuite extends CometTestBase with DisableSuite { +class CometShuffleEncryptionSuite extends CometTestBase { import testImplicits._ override protected def sparkConf: SparkConf = { @@ -1078,7 +1078,7 @@ class CometShuffleEncryptionSuite extends CometTestBase with DisableSuite { } } -class CometShuffleManagerSuite extends CometTestBase with DisableSuite { +class CometShuffleManagerSuite extends CometTestBase { test("should not bypass merge sort if executor cores are too high") { withSQLConf(CometConf.COMET_COLUMNAR_SHUFFLE_ASYNC_MAX_THREAD_NUM.key -> "100") { diff --git a/spark/src/test/scala/org/apache/comet/exec/CometJoinSuite.scala b/spark/src/test/scala/org/apache/comet/exec/CometJoinSuite.scala index 4e23b01fc..91d88c76e 100644 --- a/spark/src/test/scala/org/apache/comet/exec/CometJoinSuite.scala +++ b/spark/src/test/scala/org/apache/comet/exec/CometJoinSuite.scala @@ -22,14 +22,14 @@ package org.apache.comet.exec import org.scalactic.source.Position import org.scalatest.Tag -import org.apache.spark.sql.{CometTestBase, DisableSuite} +import org.apache.spark.sql.CometTestBase import org.apache.spark.sql.comet.{CometBroadcastExchangeExec, CometBroadcastHashJoinExec} import org.apache.spark.sql.internal.SQLConf import org.apache.comet.CometConf import org.apache.comet.CometSparkSessionExtensions.isSpark34Plus -class CometJoinSuite extends CometTestBase with DisableSuite { +class CometJoinSuite extends CometTestBase { override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit pos: Position): Unit = { diff --git a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala index 78bc6fc2d..85d7b9a0d 100644 --- a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala +++ b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala @@ -34,7 +34,7 @@ import org.apache.hadoop.fs.Path import org.apache.parquet.example.data.simple.SimpleGroup import org.apache.parquet.schema.MessageTypeParser import org.apache.spark.SparkException -import org.apache.spark.sql.{CometTestBase, DataFrame, DisableSuite, Row} +import org.apache.spark.sql.{CometTestBase, DataFrame, Row} import org.apache.spark.sql.catalyst.expressions.GenericInternalRow import org.apache.spark.sql.catalyst.util.DateTimeUtils import org.apache.spark.sql.comet.CometBatchScanExec @@ -1287,7 +1287,7 @@ abstract class ParquetReadSuite extends CometTestBase { } } -class ParquetReadV1Suite extends ParquetReadSuite with AdaptiveSparkPlanHelper with DisableSuite { +class ParquetReadV1Suite extends ParquetReadSuite with AdaptiveSparkPlanHelper { override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit pos: Position): Unit = { super.test(testName, testTags: _*)(withSQLConf(SQLConf.USE_V1_SOURCE_LIST.key -> "parquet") { @@ -1318,7 +1318,7 @@ class ParquetReadV1Suite extends ParquetReadSuite with AdaptiveSparkPlanHelper w } } -class ParquetReadV2Suite extends ParquetReadSuite with AdaptiveSparkPlanHelper with DisableSuite { +class ParquetReadV2Suite extends ParquetReadSuite with AdaptiveSparkPlanHelper { override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit pos: Position): Unit = { super.test(testName, testTags: _*)(withSQLConf(SQLConf.USE_V1_SOURCE_LIST.key -> "") { diff --git a/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala b/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala index c5ab61bd5..2263b2f99 100644 --- a/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala +++ b/spark/src/test/scala/org/apache/spark/CometPluginsSuite.scala @@ -19,9 +19,9 @@ package org.apache.spark -import org.apache.spark.sql.{CometTestBase, DisableSuite} +import org.apache.spark.sql.CometTestBase -class CometPluginsSuite extends CometTestBase with DisableSuite { +class CometPluginsSuite extends CometTestBase { override protected def sparkConf: SparkConf = { val conf = new SparkConf() conf.set("spark.driver.memory", "1G") @@ -47,7 +47,7 @@ class CometPluginsSuite extends CometTestBase with DisableSuite { } } -class CometPluginsDefaultSuite extends CometTestBase with DisableSuite { +class CometPluginsDefaultSuite extends CometTestBase { override protected def sparkConf: SparkConf = { val conf = new SparkConf() conf.set("spark.driver.memory", "1G") @@ -74,7 +74,7 @@ class CometPluginsDefaultSuite extends CometTestBase with DisableSuite { } } -class CometPluginsNonOverrideSuite extends CometTestBase with DisableSuite { +class CometPluginsNonOverrideSuite extends CometTestBase { override protected def sparkConf: SparkConf = { val conf = new SparkConf() conf.set("spark.driver.memory", "1G") diff --git a/spark/src/test/scala/org/apache/spark/sql/DisableSuite.scala b/spark/src/test/scala/org/apache/spark/sql/DisableSuite.scala deleted file mode 100644 index d6ad298f0..000000000 --- a/spark/src/test/scala/org/apache/spark/sql/DisableSuite.scala +++ /dev/null @@ -1,32 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -package org.apache.spark.sql - -import org.scalactic.source.Position -import org.scalatest.Tag - -import org.apache.spark.sql.test.SQLTestUtils - -trait DisableSuite extends SQLTestUtils { - override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit - pos: Position): Unit = { - ignore(testName + " (disabled)", testTags: _*)(testFun) - } -} diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala index 07c633c5a..22d016c66 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala @@ -26,7 +26,7 @@ import scala.collection.mutable import org.apache.commons.io.FileUtils import org.apache.spark.SparkContext -import org.apache.spark.sql.{DisableSuite, TPCDSBase} +import org.apache.spark.sql.TPCDSBase import org.apache.spark.sql.catalyst.expressions.AttributeSet import org.apache.spark.sql.catalyst.util.resourceToString import org.apache.spark.sql.execution.{FormattedMode, ReusedSubqueryExec, SparkPlan, SubqueryBroadcastExec, SubqueryExec} @@ -297,7 +297,7 @@ trait CometPlanStabilitySuite extends DisableAdaptiveExecutionSuite with TPCDSBa System.getenv("SPARK_GENERATE_GOLDEN_FILES") == "1" } -class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite with DisableSuite { +class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { // TODO: remove the Spark 4.0 golden file once ANSI is fully supported private val planName = if (isSpark40Plus) "approved-plans-v1_4-spark4_0" else "approved-plans-v1_4" @@ -311,7 +311,7 @@ class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite with Dis } } -class CometTPCDSV2_7_PlanStabilitySuite extends CometPlanStabilitySuite with DisableSuite { +class CometTPCDSV2_7_PlanStabilitySuite extends CometPlanStabilitySuite { // TODO: remove the Spark 4.0 golden file once ANSI is fully supported private val planName = if (isSpark40Plus) "approved-plans-v2_7-spark4_0" else "approved-plans-v2_7" diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala index bacbd048b..a829d7449 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetDatetimeRebaseSuite.scala @@ -23,7 +23,7 @@ import org.scalactic.source.Position import org.scalatest.Tag import org.apache.spark.SparkException -import org.apache.spark.sql.{CometTestBase, DataFrame, Dataset, DisableSuite, Row} +import org.apache.spark.sql.{CometTestBase, DataFrame, Dataset, Row} import org.apache.spark.sql.internal.SQLConf import org.apache.comet.CometConf @@ -31,7 +31,7 @@ import org.apache.comet.CometSparkSessionExtensions.isSpark40Plus // This test checks if Comet reads ancient dates & timestamps that are before 1582, as if they are // read according to the `LegacyBehaviorPolicy.CORRECTED` mode (i.e., no rebase) in Spark. -abstract class ParquetDatetimeRebaseSuite extends CometTestBase with DisableSuite { +abstract class ParquetDatetimeRebaseSuite extends CometTestBase { // This is a flag defined in Spark's `org.apache.spark.internal.config.Tests` but is only // visible under package `spark`. diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetEncryptionITCase.scala b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetEncryptionITCase.scala index 1cb9a1e9f..0d1a105ff 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/ParquetEncryptionITCase.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/ParquetEncryptionITCase.scala @@ -30,7 +30,7 @@ import org.scalatest.Tag import org.scalatestplus.junit.JUnitRunner import org.apache.spark.{DebugFilesystem, SparkConf} -import org.apache.spark.sql.{DisableSuite, QueryTest, SparkSession, SQLContext} +import org.apache.spark.sql.{QueryTest, SparkSession, SQLContext} import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.test.SQLTestUtils @@ -41,7 +41,7 @@ import org.apache.comet.{CometConf, CometSparkSessionExtensions, IntegrationTest */ @RunWith(classOf[JUnitRunner]) @IntegrationTestSuite -class ParquetEncryptionITCase extends QueryTest with SQLTestUtils with DisableSuite { +class ParquetEncryptionITCase extends QueryTest with SQLTestUtils { private val encoder = Base64.getEncoder private val footerKey = encoder.encodeToString("0123456789012345".getBytes(StandardCharsets.UTF_8)) diff --git a/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala b/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala index 179344db9..d54c8dad0 100644 --- a/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala +++ b/spark/src/test/spark-3.3-plus/org/apache/comet/CometExpression3_3PlusSuite.scala @@ -19,7 +19,7 @@ package org.apache.comet -import org.apache.spark.sql.{Column, CometTestBase, DisableSuite} +import org.apache.spark.sql.{Column, CometTestBase} import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper import org.apache.spark.sql.catalyst.FunctionIdentifier import org.apache.spark.sql.catalyst.expressions.{BloomFilterMightContain, Expression, ExpressionInfo} @@ -28,7 +28,7 @@ import org.apache.spark.util.sketch.BloomFilter import java.io.ByteArrayOutputStream import scala.util.Random -class CometExpression3_3PlusSuite extends CometTestBase with AdaptiveSparkPlanHelper with DisableSuite { +class CometExpression3_3PlusSuite extends CometTestBase with AdaptiveSparkPlanHelper { import testImplicits._ val func_might_contain = new FunctionIdentifier("might_contain") diff --git a/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala index 69fa84dfe..9116d588b 100644 --- a/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala +++ b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala @@ -22,13 +22,13 @@ package org.apache.comet.exec import org.scalactic.source.Position import org.scalatest.Tag -import org.apache.spark.sql.{CometTestBase, DisableSuite} +import org.apache.spark.sql.CometTestBase import org.apache.comet.CometConf /** * This test suite contains tests for only Spark 3.4. */ -class CometExec3_4PlusSuite extends CometTestBase with DisableSuite { +class CometExec3_4PlusSuite extends CometTestBase { import testImplicits._ override protected def test(testName: String, testTags: Tag*)(testFun: => Any)(implicit From 1910927cc226624133a19d083395d25dfeae1e46 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 21 May 2024 15:06:08 -0700 Subject: [PATCH 35/68] build: Enable spark-4.0 tests --- .github/workflows/pr_build.yml | 18 ++++++------------ 1 file changed, 6 insertions(+), 12 deletions(-) diff --git a/.github/workflows/pr_build.yml b/.github/workflows/pr_build.yml index 483e663a2..e20137ed0 100644 --- a/.github/workflows/pr_build.yml +++ b/.github/workflows/pr_build.yml @@ -115,10 +115,8 @@ jobs: name: Java test steps uses: ./.github/actions/java-test with: - # TODO: remove -DskipTests after fixing tests - maven_opts: "-Pspark-${{ matrix.spark-version }} -DskipTests" - # TODO: upload test reports after enabling tests - upload-test-reports: false + maven_opts: -Pspark-${{ matrix.spark-version }} + upload-test-reports: true linux-test-with-old-spark: strategy: @@ -249,10 +247,8 @@ jobs: name: Java test steps uses: ./.github/actions/java-test with: - # TODO: remove -DskipTests after fixing tests - maven_opts: "-Pspark-${{ matrix.spark-version }} -DskipTests" - # TODO: upload test reports after enabling tests - upload-test-reports: false + maven_opts: -Pspark-${{ matrix.spark-version }} + upload-test-reports: true macos-aarch64-test-with-spark4_0: strategy: @@ -295,10 +291,8 @@ jobs: name: Java test steps uses: ./.github/actions/java-test with: - # TODO: remove -DskipTests after fixing tests - maven_opts: "-Pspark-${{ matrix.spark-version }} -DskipTests" - # TODO: upload test reports after enabling tests - upload-test-reports: false + maven_opts: -Pspark-${{ matrix.spark-version }} + upload-test-reports: true macos-aarch64-test-with-old-spark: strategy: From 443bee8304e41f42dc9e5bf5e296a075b70064f2 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 21 May 2024 23:27:13 -0700 Subject: [PATCH 36/68] address review comments --- .../spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala index 36fb3a609..9100b90c2 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometShuffleWriteProcessor.scala @@ -20,10 +20,9 @@ package org.apache.spark.sql.comet.shims import org.apache.spark.{Partition, ShuffleDependency, TaskContext} -import org.apache.spark.rdd.{MapPartitionsRDD, RDD} +import org.apache.spark.rdd.RDD import org.apache.spark.scheduler.MapStatus import org.apache.spark.shuffle.ShuffleWriteProcessor -import org.apache.spark.sql.vectorized.ColumnarBatch trait ShimCometShuffleWriteProcessor extends ShuffleWriteProcessor { override def write( From 894985e9e503ec25d6a0d894d61d939b9b7b3ffb Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 22 May 2024 17:00:28 -0700 Subject: [PATCH 37/68] build: Enable spark-4.0 Spark tests --- common/src/main/scala/org/apache/comet/CometConf.scala | 6 ++++-- .../spark-3.x/org/apache/comet/shims/ShimCometConf.scala | 5 +++++ .../spark-4.0/org/apache/comet/shims/ShimCometConf.scala | 5 +++++ .../scala/org/apache/comet/parquet/ParquetReadSuite.scala | 2 +- 4 files changed, 15 insertions(+), 3 deletions(-) create mode 100644 common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala create mode 100644 common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala diff --git a/common/src/main/scala/org/apache/comet/CometConf.scala b/common/src/main/scala/org/apache/comet/CometConf.scala index 463de90c2..72c35b4d9 100644 --- a/common/src/main/scala/org/apache/comet/CometConf.scala +++ b/common/src/main/scala/org/apache/comet/CometConf.scala @@ -28,6 +28,8 @@ import org.apache.spark.network.util.JavaUtils import org.apache.spark.sql.comet.util.Utils import org.apache.spark.sql.internal.SQLConf +import org.apache.comet.shims.ShimCometConf + /** * Configurations for a Comet application. Mostly inspired by [[SQLConf]] in Spark. * @@ -40,7 +42,7 @@ import org.apache.spark.sql.internal.SQLConf * which retrieves the config value from the thread-local [[SQLConf]] object. Alternatively, you * can also explicitly pass a [[SQLConf]] object to the `get` method. */ -object CometConf { +object CometConf extends ShimCometConf { /** List of all configs that is used for generating documentation */ val allConfs = new ListBuffer[ConfigEntry[_]] @@ -357,7 +359,7 @@ object CometConf { "column to a long column, a float column to a double column, etc. This is automatically" + "enabled when reading from Iceberg tables.") .booleanConf - .createWithDefault(false) + .createWithDefault(COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT) val COMET_ROW_TO_COLUMNAR_ENABLED: ConfigEntry[Boolean] = conf("spark.comet.rowToColumnar.enabled") diff --git a/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala b/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala new file mode 100644 index 000000000..b1080dd88 --- /dev/null +++ b/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala @@ -0,0 +1,5 @@ +package org.apache.comet.shims + +trait ShimCometConf { + protected val COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT = false +} diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala new file mode 100644 index 000000000..315c3a94e --- /dev/null +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala @@ -0,0 +1,5 @@ +package org.apache.comet.shims + +trait ShimCometConf { + protected val COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT = true +} diff --git a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala index 85d7b9a0d..0ed822380 100644 --- a/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala +++ b/spark/src/test/scala/org/apache/comet/parquet/ParquetReadSuite.scala @@ -1123,7 +1123,7 @@ abstract class ParquetReadSuite extends CometTestBase { } test("row group skipping doesn't overflow when reading into larger type") { - // Spark 4.0 no longer fails for widening types + // Spark 4.0 no longer fails for widening types SPARK-40876 // https://github.com/apache/spark/commit/3361f25dc0ff6e5233903c26ee105711b79ba967 assume(isSpark34Plus && !isSpark34Plus) From 7959b1f351d975448b4fd877b0672d77a1f341c1 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 22 May 2024 22:26:31 -0700 Subject: [PATCH 38/68] address review comments --- .github/workflows/pr_build.yml | 42 ++++++------------- .../apache/comet/shims/CometExprShim.scala | 4 +- .../apache/comet/shims/CometExprShim.scala | 4 +- .../apache/comet/shims/CometExprShim.scala | 4 +- .../apache/comet/shims/CometExprShim.scala | 4 +- .../comet/exec/CometExec3_4PlusSuite.scala | 2 +- 6 files changed, 21 insertions(+), 39 deletions(-) diff --git a/.github/workflows/pr_build.yml b/.github/workflows/pr_build.yml index e20137ed0..7de198a47 100644 --- a/.github/workflows/pr_build.yml +++ b/.github/workflows/pr_build.yml @@ -81,7 +81,7 @@ jobs: matrix: os: [ubuntu-latest] java_version: [17] - test-target: [rust, java] + test-target: [java] spark-version: ['4.0'] is_push_event: - ${{ github.event_name == 'push' }} @@ -97,22 +97,16 @@ jobs: with: rust-version: ${{env.RUST_VERSION}} jdk-version: ${{ matrix.java_version }} - - if: matrix.test-target == 'rust' - name: Rust test steps - uses: ./.github/actions/rust-test - - if: matrix.test-target == 'java' - name: Clone Spark + - name: Clone Spark uses: actions/checkout@v4 with: repository: "apache/spark" path: "apache-spark" - - if: matrix.test-target == 'java' - name: Install Spark + - name: Install Spark shell: bash working-directory: ./apache-spark run: build/mvn install -Phive -Phadoop-cloud -DskipTests - - if: matrix.test-target == 'java' - name: Java test steps + - name: Java test steps uses: ./.github/actions/java-test with: maven_opts: -Pspark-${{ matrix.spark-version }} @@ -216,7 +210,7 @@ jobs: matrix: os: [macos-13] java_version: [17] - test-target: [rust, java] + test-target: [java] spark-version: ['4.0'] fail-fast: false if: github.event_name == 'push' @@ -229,22 +223,16 @@ jobs: with: rust-version: ${{env.RUST_VERSION}} jdk-version: ${{ matrix.java_version }} - - if: matrix.test-target == 'rust' - name: Rust test steps - uses: ./.github/actions/rust-test - - if: matrix.test-target == 'java' - name: Clone Spark + - name: Clone Spark uses: actions/checkout@v4 with: repository: "apache/spark" path: "apache-spark" - - if: matrix.test-target == 'java' - name: Install Spark + - name: Install Spark shell: bash working-directory: ./apache-spark run: build/mvn install -Phive -Phadoop-cloud -DskipTests - - if: matrix.test-target == 'java' - name: Java test steps + - name: Java test steps uses: ./.github/actions/java-test with: maven_opts: -Pspark-${{ matrix.spark-version }} @@ -254,7 +242,7 @@ jobs: strategy: matrix: java_version: [17] - test-target: [rust, java] + test-target: [java] spark-version: ['4.0'] is_push_event: - ${{ github.event_name == 'push' }} @@ -273,22 +261,16 @@ jobs: jdk-version: ${{ matrix.java_version }} jdk-architecture: aarch64 protoc-architecture: aarch_64 - - if: matrix.test-target == 'rust' - name: Rust test steps - uses: ./.github/actions/rust-test - - if: matrix.test-target == 'java' - name: Clone Spark + - name: Clone Spark uses: actions/checkout@v4 with: repository: "apache/spark" path: "apache-spark" - - if: matrix.test-target == 'java' - name: Install Spark + - name: Install Spark shell: bash working-directory: ./apache-spark run: build/mvn install -Phive -Phadoop-cloud -DskipTests - - if: matrix.test-target == 'java' - name: Java test steps + - name: Java test steps uses: ./.github/actions/java-test with: maven_opts: -Pspark-${{ matrix.spark-version }} diff --git a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala index 0c45a9c2c..f5a578f82 100644 --- a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala @@ -25,8 +25,8 @@ import org.apache.spark.sql.catalyst.expressions._ */ trait CometExprShim { /** - * Returns a tuple of expressions for the `unhex` function. - */ + * Returns a tuple of expressions for the `unhex` function. + */ def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(false)) } diff --git a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala index 0c45a9c2c..f5a578f82 100644 --- a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala @@ -25,8 +25,8 @@ import org.apache.spark.sql.catalyst.expressions._ */ trait CometExprShim { /** - * Returns a tuple of expressions for the `unhex` function. - */ + * Returns a tuple of expressions for the `unhex` function. + */ def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(false)) } diff --git a/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala index 409e1c94b..3f2301f0a 100644 --- a/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala @@ -25,8 +25,8 @@ import org.apache.spark.sql.catalyst.expressions._ */ trait CometExprShim { /** - * Returns a tuple of expressions for the `unhex` function. - */ + * Returns a tuple of expressions for the `unhex` function. + */ def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(unhex.failOnError)) } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala index 7d4ec1537..01f923206 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala @@ -25,8 +25,8 @@ import org.apache.spark.sql.catalyst.expressions._ */ trait CometExprShim { /** - * Returns a tuple of expressions for the `unhex` function. - */ + * Returns a tuple of expressions for the `unhex` function. + */ protected def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(unhex.failOnError)) } diff --git a/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala index 9116d588b..75765bd9b 100644 --- a/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala +++ b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala @@ -26,7 +26,7 @@ import org.apache.spark.sql.CometTestBase import org.apache.comet.CometConf /** - * This test suite contains tests for only Spark 3.4. + * This test suite contains tests for only Spark 3.4+. */ class CometExec3_4PlusSuite extends CometTestBase { import testImplicits._ From 8036660fa3048409443c6b7dc7afd596716824b5 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 22 May 2024 22:26:31 -0700 Subject: [PATCH 39/68] address review comments --- .github/workflows/pr_build.yml | 42 ++++++------------- .../apache/comet/shims/CometExprShim.scala | 4 +- .../apache/comet/shims/CometExprShim.scala | 4 +- .../apache/comet/shims/CometExprShim.scala | 4 +- .../apache/comet/shims/CometExprShim.scala | 4 +- .../comet/exec/CometExec3_4PlusSuite.scala | 2 +- 6 files changed, 21 insertions(+), 39 deletions(-) diff --git a/.github/workflows/pr_build.yml b/.github/workflows/pr_build.yml index e20137ed0..7de198a47 100644 --- a/.github/workflows/pr_build.yml +++ b/.github/workflows/pr_build.yml @@ -81,7 +81,7 @@ jobs: matrix: os: [ubuntu-latest] java_version: [17] - test-target: [rust, java] + test-target: [java] spark-version: ['4.0'] is_push_event: - ${{ github.event_name == 'push' }} @@ -97,22 +97,16 @@ jobs: with: rust-version: ${{env.RUST_VERSION}} jdk-version: ${{ matrix.java_version }} - - if: matrix.test-target == 'rust' - name: Rust test steps - uses: ./.github/actions/rust-test - - if: matrix.test-target == 'java' - name: Clone Spark + - name: Clone Spark uses: actions/checkout@v4 with: repository: "apache/spark" path: "apache-spark" - - if: matrix.test-target == 'java' - name: Install Spark + - name: Install Spark shell: bash working-directory: ./apache-spark run: build/mvn install -Phive -Phadoop-cloud -DskipTests - - if: matrix.test-target == 'java' - name: Java test steps + - name: Java test steps uses: ./.github/actions/java-test with: maven_opts: -Pspark-${{ matrix.spark-version }} @@ -216,7 +210,7 @@ jobs: matrix: os: [macos-13] java_version: [17] - test-target: [rust, java] + test-target: [java] spark-version: ['4.0'] fail-fast: false if: github.event_name == 'push' @@ -229,22 +223,16 @@ jobs: with: rust-version: ${{env.RUST_VERSION}} jdk-version: ${{ matrix.java_version }} - - if: matrix.test-target == 'rust' - name: Rust test steps - uses: ./.github/actions/rust-test - - if: matrix.test-target == 'java' - name: Clone Spark + - name: Clone Spark uses: actions/checkout@v4 with: repository: "apache/spark" path: "apache-spark" - - if: matrix.test-target == 'java' - name: Install Spark + - name: Install Spark shell: bash working-directory: ./apache-spark run: build/mvn install -Phive -Phadoop-cloud -DskipTests - - if: matrix.test-target == 'java' - name: Java test steps + - name: Java test steps uses: ./.github/actions/java-test with: maven_opts: -Pspark-${{ matrix.spark-version }} @@ -254,7 +242,7 @@ jobs: strategy: matrix: java_version: [17] - test-target: [rust, java] + test-target: [java] spark-version: ['4.0'] is_push_event: - ${{ github.event_name == 'push' }} @@ -273,22 +261,16 @@ jobs: jdk-version: ${{ matrix.java_version }} jdk-architecture: aarch64 protoc-architecture: aarch_64 - - if: matrix.test-target == 'rust' - name: Rust test steps - uses: ./.github/actions/rust-test - - if: matrix.test-target == 'java' - name: Clone Spark + - name: Clone Spark uses: actions/checkout@v4 with: repository: "apache/spark" path: "apache-spark" - - if: matrix.test-target == 'java' - name: Install Spark + - name: Install Spark shell: bash working-directory: ./apache-spark run: build/mvn install -Phive -Phadoop-cloud -DskipTests - - if: matrix.test-target == 'java' - name: Java test steps + - name: Java test steps uses: ./.github/actions/java-test with: maven_opts: -Pspark-${{ matrix.spark-version }} diff --git a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala index 0c45a9c2c..f5a578f82 100644 --- a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala @@ -25,8 +25,8 @@ import org.apache.spark.sql.catalyst.expressions._ */ trait CometExprShim { /** - * Returns a tuple of expressions for the `unhex` function. - */ + * Returns a tuple of expressions for the `unhex` function. + */ def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(false)) } diff --git a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala index 0c45a9c2c..f5a578f82 100644 --- a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala @@ -25,8 +25,8 @@ import org.apache.spark.sql.catalyst.expressions._ */ trait CometExprShim { /** - * Returns a tuple of expressions for the `unhex` function. - */ + * Returns a tuple of expressions for the `unhex` function. + */ def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(false)) } diff --git a/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala index 409e1c94b..3f2301f0a 100644 --- a/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala @@ -25,8 +25,8 @@ import org.apache.spark.sql.catalyst.expressions._ */ trait CometExprShim { /** - * Returns a tuple of expressions for the `unhex` function. - */ + * Returns a tuple of expressions for the `unhex` function. + */ def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(unhex.failOnError)) } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala index 7d4ec1537..01f923206 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala @@ -25,8 +25,8 @@ import org.apache.spark.sql.catalyst.expressions._ */ trait CometExprShim { /** - * Returns a tuple of expressions for the `unhex` function. - */ + * Returns a tuple of expressions for the `unhex` function. + */ protected def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(unhex.failOnError)) } diff --git a/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala index 9116d588b..75765bd9b 100644 --- a/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala +++ b/spark/src/test/spark-3.4-plus/org/apache/comet/exec/CometExec3_4PlusSuite.scala @@ -26,7 +26,7 @@ import org.apache.spark.sql.CometTestBase import org.apache.comet.CometConf /** - * This test suite contains tests for only Spark 3.4. + * This test suite contains tests for only Spark 3.4+. */ class CometExec3_4PlusSuite extends CometTestBase { import testImplicits._ From eaa42955ef39fb882388bdc0aa7abfc7db0282d5 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 22 May 2024 23:58:16 -0700 Subject: [PATCH 40/68] build: Enable spark-4.0 Spark tests --- .github/workflows/spark_sql_test_ansi.yml | 26 +- .../scala/org/apache/comet/CometConf.scala | 2 +- .../apache/comet/shims/ShimCometConf.scala | 1 + .../apache/comet/shims/ShimCometConf.scala | 1 + dev/diffs/4.0.0.diff | 2555 +++++++++++++++++ pom.xml | 1 - 6 files changed, 2571 insertions(+), 15 deletions(-) create mode 100644 dev/diffs/4.0.0.diff diff --git a/.github/workflows/spark_sql_test_ansi.yml b/.github/workflows/spark_sql_test_ansi.yml index 5c5d28589..8be2ea9e6 100644 --- a/.github/workflows/spark_sql_test_ansi.yml +++ b/.github/workflows/spark_sql_test_ansi.yml @@ -22,17 +22,17 @@ concurrency: cancel-in-progress: true on: - # enable the following once Ansi support is completed - # push: - # paths-ignore: - # - "doc/**" - # - "**.md" - # pull_request: - # paths-ignore: - # - "doc/**" - # - "**.md" - - # manual trigger ONLY + push: + paths-ignore: + - "doc/**" + - "docs/**" + - "**.md" + pull_request: + paths-ignore: + - "doc/**" + - "docs/**" + - "**.md" + # manual trigger # https://docs.github.com/en/actions/managing-workflow-runs/manually-running-a-workflow workflow_dispatch: @@ -44,8 +44,8 @@ jobs: strategy: matrix: os: [ubuntu-latest] - java-version: [11] - spark-version: [{short: '3.4', full: '3.4.2'}] + java-version: [17] + spark-version: [{short: '4.0', full: '4.0.0'}] module: - {name: "catalyst", args1: "catalyst/test", args2: ""} - {name: "sql/core-1", args1: "", args2: sql/testOnly * -- -l org.apache.spark.tags.ExtendedSQLTest -l org.apache.spark.tags.SlowSQLTest} diff --git a/common/src/main/scala/org/apache/comet/CometConf.scala b/common/src/main/scala/org/apache/comet/CometConf.scala index 72c35b4d9..4e1a505cd 100644 --- a/common/src/main/scala/org/apache/comet/CometConf.scala +++ b/common/src/main/scala/org/apache/comet/CometConf.scala @@ -385,7 +385,7 @@ object CometConf extends ShimCometConf { "queries when ansi mode is enabled. Enable this setting to test Comet's experimental " + "support for ANSI mode. This should not be used in production.") .booleanConf - .createWithDefault(false) + .createWithDefault(COMET_ANSI_MODE_ENABLED_DEFAULT) val COMET_CAST_ALLOW_INCOMPATIBLE: ConfigEntry[Boolean] = conf("spark.comet.cast.allowIncompatible") diff --git a/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala b/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala index b1080dd88..ecd46185b 100644 --- a/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala +++ b/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala @@ -2,4 +2,5 @@ package org.apache.comet.shims trait ShimCometConf { protected val COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT = false + protected val COMET_ANSI_MODE_ENABLED_DEFAULT = false } diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala index 315c3a94e..76faa0d0b 100644 --- a/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala @@ -2,4 +2,5 @@ package org.apache.comet.shims trait ShimCometConf { protected val COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT = true + protected val COMET_ANSI_MODE_ENABLED_DEFAULT = true } diff --git a/dev/diffs/4.0.0.diff b/dev/diffs/4.0.0.diff new file mode 100644 index 000000000..19bf6dd41 --- /dev/null +++ b/dev/diffs/4.0.0.diff @@ -0,0 +1,2555 @@ +diff --git a/pom.xml b/pom.xml +index fab98342498..f2156d790d1 100644 +--- a/pom.xml ++++ b/pom.xml +@@ -148,6 +148,8 @@ + 0.10.0 + 2.5.1 + 2.0.8 ++ 3.4 ++ 0.1.0-SNAPSHOT + spark-4.0 From 46bddfa46f87db9cf6a8458d403c7cb5d9d888bb Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Fri, 24 May 2024 01:14:15 -0700 Subject: [PATCH 41/68] build: Enable spark-4.0 tests --- .../scala/org/apache/comet/CometConf.scala | 9 +- .../apache/comet/shims/ShimCometConf.scala | 25 + .../apache/comet/shims/ShimCometConf.scala | 25 + docs/source/user-guide/configs.md | 1 - .../q1/explain.txt | 66 +- .../q1/simplified.txt | 34 +- .../q10/explain.txt | 56 +- .../q10/simplified.txt | 28 +- .../q11/explain.txt | 100 +- .../q11/simplified.txt | 60 +- .../q12/explain.txt | 38 +- .../q12/simplified.txt | 20 +- .../q13/explain.txt | 76 +- .../q13/simplified.txt | 40 +- .../q14a/explain.txt | 136 +-- .../q14a/simplified.txt | 76 +- .../q14b/explain.txt | 184 ++-- .../q14b/simplified.txt | 98 +- .../q15/explain.txt | 48 +- .../q15/simplified.txt | 26 +- .../q16/explain.txt | 96 +- .../q16/simplified.txt | 44 +- .../q17/explain.txt | 86 +- .../q17/simplified.txt | 46 +- .../q18/explain.txt | 94 +- .../q18/simplified.txt | 48 +- .../q19/explain.txt | 76 +- .../q19/simplified.txt | 40 +- .../q2/explain.txt | 168 ++-- .../q2/simplified.txt | 55 +- .../q20/explain.txt | 38 +- .../q20/simplified.txt | 20 +- .../q21/explain.txt | 48 +- .../q21/simplified.txt | 26 +- .../q22/explain.txt | 48 +- .../q22/simplified.txt | 26 +- .../q23a/explain.txt | 112 +-- .../q23a/simplified.txt | 56 +- .../q23b/explain.txt | 142 +-- .../q23b/simplified.txt | 74 +- .../q24a/explain.txt | 94 +- .../q24a/simplified.txt | 48 +- .../q24b/explain.txt | 94 +- .../q24b/simplified.txt | 48 +- .../q25/explain.txt | 86 +- .../q25/simplified.txt | 46 +- .../q26/explain.txt | 74 +- .../q26/simplified.txt | 36 +- .../q27/explain.txt | 66 +- .../q27/simplified.txt | 34 +- .../q28/explain.txt | 108 +-- .../q28/simplified.txt | 48 +- .../q29/explain.txt | 104 +-- .../q29/simplified.txt | 54 +- .../q3/explain.txt | 46 +- .../q3/simplified.txt | 22 +- .../q30/explain.txt | 76 +- .../q30/simplified.txt | 40 +- .../q31/explain.txt | 100 +- .../q31/simplified.txt | 60 +- .../q32/explain.txt | 56 +- .../q32/simplified.txt | 28 +- .../q33/explain.txt | 94 +- .../q33/simplified.txt | 48 +- .../q34/explain.txt | 74 +- .../q34/simplified.txt | 36 +- .../q35/explain.txt | 48 +- .../q35/simplified.txt | 26 +- .../q36/explain.txt | 56 +- .../q36/simplified.txt | 28 +- .../q37/explain.txt | 72 +- .../q37/simplified.txt | 32 +- .../q38/explain.txt | 58 +- .../q38/simplified.txt | 32 +- .../q39a/explain.txt | 76 +- .../q39a/simplified.txt | 40 +- .../q39b/explain.txt | 76 +- .../q39b/simplified.txt | 40 +- .../q4/explain.txt | 140 +-- .../q4/simplified.txt | 84 +- .../q40/explain.txt | 66 +- .../q40/simplified.txt | 34 +- .../q41/explain.txt | 56 +- .../q41/simplified.txt | 18 +- .../q42/explain.txt | 46 +- .../q42/simplified.txt | 22 +- .../q43/explain.txt | 46 +- .../q43/simplified.txt | 22 +- .../q44/explain.txt | 46 +- .../q44/simplified.txt | 22 +- .../q45/explain.txt | 76 +- .../q45/simplified.txt | 40 +- .../q46/explain.txt | 84 +- .../q46/simplified.txt | 42 +- .../q47/explain.txt | 40 +- .../q47/simplified.txt | 24 +- .../q48/explain.txt | 66 +- .../q48/simplified.txt | 34 +- .../q49/explain.txt | 409 ++++---- .../q49/simplified.txt | 126 ++- .../q5/explain.txt | 385 ++++---- .../q5/simplified.txt | 147 ++- .../q50/explain.txt | 58 +- .../q50/simplified.txt | 32 +- .../q51/explain.txt | 38 +- .../q51/simplified.txt | 20 +- .../q52/explain.txt | 46 +- .../q52/simplified.txt | 22 +- .../q53/explain.txt | 56 +- .../q53/simplified.txt | 28 +- .../q54/explain.txt | 382 ++++---- .../q54/simplified.txt | 123 ++- .../q55/explain.txt | 46 +- .../q55/simplified.txt | 22 +- .../q56/explain.txt | 94 +- .../q56/simplified.txt | 48 +- .../q57/explain.txt | 40 +- .../q57/simplified.txt | 24 +- .../q58/explain.txt | 88 +- .../q58/simplified.txt | 48 +- .../q59/explain.txt | 76 +- .../q59/simplified.txt | 40 +- .../q6/explain.txt | 94 +- .../q6/simplified.txt | 50 +- .../q60/explain.txt | 94 +- .../q60/simplified.txt | 48 +- .../q61/explain.txt | 120 +-- .../q61/simplified.txt | 58 +- .../q62/explain.txt | 58 +- .../q62/simplified.txt | 32 +- .../q63/explain.txt | 56 +- .../q63/simplified.txt | 28 +- .../q64/explain.txt | 874 +++++++++--------- .../q64/simplified.txt | 196 ++-- .../q65/explain.txt | 58 +- .../q65/simplified.txt | 32 +- .../q66/explain.txt | 76 +- .../q66/simplified.txt | 40 +- .../q67/explain.txt | 48 +- .../q67/simplified.txt | 26 +- .../q68/explain.txt | 84 +- .../q68/simplified.txt | 42 +- .../q69/explain.txt | 56 +- .../q69/simplified.txt | 28 +- .../q7/explain.txt | 74 +- .../q7/simplified.txt | 36 +- .../q70/explain.txt | 58 +- .../q70/simplified.txt | 32 +- .../q71/explain.txt | 84 +- .../q71/simplified.txt | 42 +- .../q72/explain.txt | 142 +-- .../q72/simplified.txt | 74 +- .../q73/explain.txt | 74 +- .../q73/simplified.txt | 36 +- .../q74/explain.txt | 100 +- .../q74/simplified.txt | 60 +- .../q75/explain.txt | 152 +-- .../q75/simplified.txt | 80 +- .../q76/explain.txt | 50 +- .../q76/simplified.txt | 30 +- .../q77/explain.txt | 78 +- .../q77/simplified.txt | 44 +- .../q78/explain.txt | 94 +- .../q78/simplified.txt | 48 +- .../q79/explain.txt | 74 +- .../q79/simplified.txt | 36 +- .../q8/explain.txt | 84 +- .../q8/simplified.txt | 42 +- .../q80/explain.txt | 168 ++-- .../q80/simplified.txt | 84 +- .../q81/explain.txt | 68 +- .../q81/simplified.txt | 38 +- .../q82/explain.txt | 72 +- .../q82/simplified.txt | 32 +- .../q83.ansi/explain.txt | 68 +- .../q83.ansi/simplified.txt | 38 +- .../q84/explain.txt | 84 +- .../q84/simplified.txt | 42 +- .../q85/explain.txt | 261 +++--- .../q85/simplified.txt | 84 +- .../q86/explain.txt | 38 +- .../q86/simplified.txt | 20 +- .../q87/explain.txt | 58 +- .../q87/simplified.txt | 32 +- .../q88/explain.txt | 324 +++---- .../q88/simplified.txt | 144 +-- .../q89/explain.txt | 48 +- .../q89/simplified.txt | 26 +- .../q9/explain.txt | 100 +- .../q9/simplified.txt | 46 +- .../q90/explain.txt | 108 +-- .../q90/simplified.txt | 48 +- .../q91/explain.txt | 94 +- .../q91/simplified.txt | 48 +- .../q92/explain.txt | 56 +- .../q92/simplified.txt | 28 +- .../q93/explain.txt | 48 +- .../q93/simplified.txt | 22 +- .../q94/explain.txt | 96 +- .../q94/simplified.txt | 44 +- .../q95/explain.txt | 108 +-- .../q95/simplified.txt | 48 +- .../q96/explain.txt | 72 +- .../q96/simplified.txt | 32 +- .../q97/explain.txt | 18 +- .../q97/simplified.txt | 8 +- .../q98/explain.txt | 38 +- .../q98/simplified.txt | 20 +- .../q99/explain.txt | 58 +- .../q99/simplified.txt | 32 +- .../q10a/explain.txt | 56 +- .../q10a/simplified.txt | 28 +- .../q11/explain.txt | 100 +- .../q11/simplified.txt | 60 +- .../q12/explain.txt | 38 +- .../q12/simplified.txt | 20 +- .../q14/explain.txt | 184 ++-- .../q14/simplified.txt | 98 +- .../q14a/explain.txt | 154 +-- .../q14a/simplified.txt | 84 +- .../q18a/explain.txt | 190 ++-- .../q18a/simplified.txt | 100 +- .../q20/explain.txt | 38 +- .../q20/simplified.txt | 20 +- .../q22/explain.txt | 38 +- .../q22/simplified.txt | 20 +- .../q22a/explain.txt | 48 +- .../q22a/simplified.txt | 26 +- .../q24/explain.txt | 94 +- .../q24/simplified.txt | 48 +- .../q27a/explain.txt | 114 +-- .../q27a/simplified.txt | 60 +- .../q34/explain.txt | 74 +- .../q34/simplified.txt | 36 +- .../q35/explain.txt | 48 +- .../q35/simplified.txt | 26 +- .../q35a/explain.txt | 48 +- .../q35a/simplified.txt | 26 +- .../q36a/explain.txt | 56 +- .../q36a/simplified.txt | 28 +- .../q47/explain.txt | 40 +- .../q47/simplified.txt | 24 +- .../q49/explain.txt | 409 ++++---- .../q49/simplified.txt | 126 ++- .../q51a/explain.txt | 38 +- .../q51a/simplified.txt | 20 +- .../q57/explain.txt | 40 +- .../q57/simplified.txt | 24 +- .../q5a/explain.txt | 443 +++++---- .../q5a/simplified.txt | 159 ++-- .../q6/explain.txt | 94 +- .../q6/simplified.txt | 50 +- .../q64/explain.txt | 874 +++++++++--------- .../q64/simplified.txt | 196 ++-- .../q67a/explain.txt | 48 +- .../q67a/simplified.txt | 26 +- .../q70a/explain.txt | 58 +- .../q70a/simplified.txt | 32 +- .../q72/explain.txt | 142 +-- .../q72/simplified.txt | 74 +- .../q74/explain.txt | 100 +- .../q74/simplified.txt | 60 +- .../q75/explain.txt | 152 +-- .../q75/simplified.txt | 80 +- .../q77a/explain.txt | 78 +- .../q77a/simplified.txt | 44 +- .../q78/explain.txt | 94 +- .../q78/simplified.txt | 48 +- .../q80a/explain.txt | 168 ++-- .../q80a/simplified.txt | 84 +- .../q86a/explain.txt | 38 +- .../q86a/simplified.txt | 20 +- .../q98/explain.txt | 38 +- .../q98/simplified.txt | 20 +- .../org/apache/comet/CometCastSuite.scala | 7 +- .../sql/comet/CometPlanStabilitySuite.scala | 2 - 276 files changed, 10298 insertions(+), 10434 deletions(-) create mode 100644 common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala create mode 100644 common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala diff --git a/common/src/main/scala/org/apache/comet/CometConf.scala b/common/src/main/scala/org/apache/comet/CometConf.scala index 5aee02f11..42fb5fb4c 100644 --- a/common/src/main/scala/org/apache/comet/CometConf.scala +++ b/common/src/main/scala/org/apache/comet/CometConf.scala @@ -29,6 +29,8 @@ import org.apache.spark.network.util.JavaUtils import org.apache.spark.sql.comet.util.Utils import org.apache.spark.sql.internal.SQLConf +import org.apache.comet.shims.ShimCometConf + /** * Configurations for a Comet application. Mostly inspired by [[SQLConf]] in Spark. * @@ -41,7 +43,7 @@ import org.apache.spark.sql.internal.SQLConf * which retrieves the config value from the thread-local [[SQLConf]] object. Alternatively, you * can also explicitly pass a [[SQLConf]] object to the `get` method. */ -object CometConf { +object CometConf extends ShimCometConf { /** List of all configs that is used for generating documentation */ val allConfs = new ListBuffer[ConfigEntry[_]] @@ -361,7 +363,7 @@ object CometConf { "column to a long column, a float column to a double column, etc. This is automatically" + "enabled when reading from Iceberg tables.") .booleanConf - .createWithDefault(false) + .createWithDefault(COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT) val COMET_ROW_TO_COLUMNAR_ENABLED: ConfigEntry[Boolean] = conf("spark.comet.rowToColumnar.enabled") @@ -382,12 +384,13 @@ object CometConf { .createWithDefault(Seq("Range,InMemoryTableScan")) val COMET_ANSI_MODE_ENABLED: ConfigEntry[Boolean] = conf("spark.comet.ansi.enabled") + .internal() .doc( "Comet does not respect ANSI mode in most cases and by default will not accelerate " + "queries when ansi mode is enabled. Enable this setting to test Comet's experimental " + "support for ANSI mode. This should not be used in production.") .booleanConf - .createWithDefault(false) + .createWithDefault(COMET_ANSI_MODE_ENABLED_DEFAULT) val COMET_CAST_ALLOW_INCOMPATIBLE: ConfigEntry[Boolean] = conf("spark.comet.cast.allowIncompatible") diff --git a/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala b/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala new file mode 100644 index 000000000..dc84a7525 --- /dev/null +++ b/common/src/main/spark-3.x/org/apache/comet/shims/ShimCometConf.scala @@ -0,0 +1,25 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +trait ShimCometConf { + protected val COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT = false + protected val COMET_ANSI_MODE_ENABLED_DEFAULT = false +} diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala new file mode 100644 index 000000000..13da6bc10 --- /dev/null +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimCometConf.scala @@ -0,0 +1,25 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.comet.shims + +trait ShimCometConf { + protected val COMET_SCHEMA_EVOLUTION_ENABLED_DEFAULT = true + protected val COMET_ANSI_MODE_ENABLED_DEFAULT = true +} diff --git a/docs/source/user-guide/configs.md b/docs/source/user-guide/configs.md index eb349b349..104f29ce8 100644 --- a/docs/source/user-guide/configs.md +++ b/docs/source/user-guide/configs.md @@ -23,7 +23,6 @@ Comet provides the following configuration settings. | Config | Description | Default Value | |--------|-------------|---------------| -| spark.comet.ansi.enabled | Comet does not respect ANSI mode in most cases and by default will not accelerate queries when ansi mode is enabled. Enable this setting to test Comet's experimental support for ANSI mode. This should not be used in production. | false | | spark.comet.batchSize | The columnar batch size, i.e., the maximum number of rows that a batch can contain. | 8192 | | spark.comet.cast.allowIncompatible | Comet is not currently fully compatible with Spark for all cast operations. Set this config to true to allow them anyway. See compatibility guide for more information. | false | | spark.comet.columnar.shuffle.async.enabled | Whether to enable asynchronous shuffle for Arrow-based shuffle. By default, this config is false. | false | diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt index d4d5ff424..762f3a4f6 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/explain.txt @@ -12,8 +12,8 @@ TakeOrderedAndProject (40) : : : +- * HashAggregate (7) : : : +- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_returns (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (24) @@ -26,18 +26,18 @@ TakeOrderedAndProject (40) : : +- * HashAggregate (17) : : +- * Project (16) : : +- * BroadcastHashJoin Inner BuildRight (15) - : : :- * Filter (13) - : : : +- * ColumnarToRow (12) + : : :- * ColumnarToRow (13) + : : : +- CometFilter (12) : : : +- CometScan parquet spark_catalog.default.store_returns (11) : : +- ReusedExchange (14) : +- BroadcastExchange (31) - : +- * Project (30) - : +- * Filter (29) - : +- * ColumnarToRow (28) + : +- * ColumnarToRow (30) + : +- CometProject (29) + : +- CometFilter (28) : +- CometScan parquet spark_catalog.default.store (27) +- BroadcastExchange (37) - +- * Filter (36) - +- * ColumnarToRow (35) + +- * ColumnarToRow (36) + +- CometFilter (35) +- CometScan parquet spark_catalog.default.customer (34) @@ -49,12 +49,12 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#4), dynamicpruningexpression(sr PushedFilters: [IsNotNull(sr_store_sk), IsNotNull(sr_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 2] +(2) CometFilter Input [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4] +Condition : (isnotnull(sr_store_sk#2) AND isnotnull(sr_customer_sk#1)) -(3) Filter [codegen id : 2] +(3) ColumnarToRow [codegen id : 2] Input [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4] -Condition : (isnotnull(sr_store_sk#2) AND isnotnull(sr_customer_sk#1)) (4) ReusedExchange [Reuses operator id: 45] Output [1]: [d_date_sk#6] @@ -99,12 +99,12 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#16), dynamicpruningexpression(s PushedFilters: [IsNotNull(sr_store_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 4] +(12) CometFilter Input [4]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15, sr_returned_date_sk#16] +Condition : isnotnull(sr_store_sk#14) -(13) Filter [codegen id : 4] +(13) ColumnarToRow [codegen id : 4] Input [4]: [sr_customer_sk#13, sr_store_sk#14, sr_return_amt#15, sr_returned_date_sk#16] -Condition : isnotnull(sr_store_sk#14) (14) ReusedExchange [Reuses operator id: 45] Output [1]: [d_date_sk#18] @@ -180,16 +180,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] ReadSchema: struct -(28) ColumnarToRow [codegen id : 7] -Input [2]: [s_store_sk#29, s_state#30] - -(29) Filter [codegen id : 7] +(28) CometFilter Input [2]: [s_store_sk#29, s_state#30] Condition : ((isnotnull(s_state#30) AND (s_state#30 = TN)) AND isnotnull(s_store_sk#29)) -(30) Project [codegen id : 7] -Output [1]: [s_store_sk#29] +(29) CometProject Input [2]: [s_store_sk#29, s_state#30] +Arguments: [s_store_sk#29], [s_store_sk#29] + +(30) ColumnarToRow [codegen id : 7] +Input [1]: [s_store_sk#29] (31) BroadcastExchange Input [1]: [s_store_sk#29] @@ -212,12 +212,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 8] +(35) CometFilter Input [2]: [c_customer_sk#31, c_customer_id#32] +Condition : isnotnull(c_customer_sk#31) -(36) Filter [codegen id : 8] +(36) ColumnarToRow [codegen id : 8] Input [2]: [c_customer_sk#31, c_customer_id#32] -Condition : isnotnull(c_customer_sk#31) (37) BroadcastExchange Input [2]: [c_customer_sk#31, c_customer_id#32] @@ -241,9 +241,9 @@ Arguments: 100, [c_customer_id#32 ASC NULLS FIRST], [c_customer_id#32] Subquery:1 Hosting operator id = 1 Hosting Expression = sr_returned_date_sk#4 IN dynamicpruning#5 BroadcastExchange (45) -+- * Project (44) - +- * Filter (43) - +- * ColumnarToRow (42) ++- * ColumnarToRow (44) + +- CometProject (43) + +- CometFilter (42) +- CometScan parquet spark_catalog.default.date_dim (41) @@ -254,16 +254,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(42) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#6, d_year#33] - -(43) Filter [codegen id : 1] +(42) CometFilter Input [2]: [d_date_sk#6, d_year#33] Condition : ((isnotnull(d_year#33) AND (d_year#33 = 2000)) AND isnotnull(d_date_sk#6)) -(44) Project [codegen id : 1] -Output [1]: [d_date_sk#6] +(43) CometProject Input [2]: [d_date_sk#6, d_year#33] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(44) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] (45) BroadcastExchange Input [1]: [d_date_sk#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt index 1475a3732..688fb69a8 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q1/simplified.txt @@ -14,17 +14,17 @@ TakeOrderedAndProject [c_customer_id] HashAggregate [sr_customer_sk,sr_store_sk,sr_return_amt] [sum,sum] Project [sr_customer_sk,sr_store_sk,sr_return_amt] BroadcastHashJoin [sr_returned_date_sk,d_date_sk] - Filter [sr_store_sk,sr_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sr_store_sk,sr_customer_sk] CometScan parquet spark_catalog.default.store_returns [sr_customer_sk,sr_store_sk,sr_return_amt,sr_returned_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk] #2 @@ -44,9 +44,9 @@ TakeOrderedAndProject [c_customer_id] HashAggregate [sr_customer_sk,sr_store_sk,sr_return_amt] [sum,sum] Project [sr_customer_sk,sr_store_sk,sr_return_amt] BroadcastHashJoin [sr_returned_date_sk,d_date_sk] - Filter [sr_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sr_store_sk] CometScan parquet spark_catalog.default.store_returns [sr_customer_sk,sr_store_sk,sr_return_amt,sr_returned_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -54,15 +54,15 @@ TakeOrderedAndProject [c_customer_id] InputAdapter BroadcastExchange #6 WholeStageCodegen (7) - Project [s_store_sk] - Filter [s_state,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_state,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_state] InputAdapter BroadcastExchange #7 WholeStageCodegen (8) - Filter [c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt index 5c21b8b9b..15490b87d 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/explain.txt @@ -12,8 +12,8 @@ TakeOrderedAndProject (43) : : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (24) : : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (17) : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : : +- BroadcastExchange (9) : : : : +- * Project (8) @@ -34,13 +34,13 @@ TakeOrderedAndProject (43) : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) : : +- ReusedExchange (20) : +- BroadcastExchange (31) - : +- * Project (30) - : +- * Filter (29) - : +- * ColumnarToRow (28) + : +- * ColumnarToRow (30) + : +- CometProject (29) + : +- CometFilter (28) : +- CometScan parquet spark_catalog.default.customer_address (27) +- BroadcastExchange (37) - +- * Filter (36) - +- * ColumnarToRow (35) + +- * ColumnarToRow (36) + +- CometFilter (35) +- CometScan parquet spark_catalog.default.customer_demographics (34) @@ -51,12 +51,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 9] +(2) CometFilter Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) -(3) Filter [codegen id : 9] +(3) ColumnarToRow [codegen id : 9] Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] -Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) (4) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_customer_sk#6, ss_sold_date_sk#7] @@ -172,16 +172,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [In(ca_county, [Dona Ana County,Jefferson County,La Porte County,Rush County,Toole County]), IsNotNull(ca_address_sk)] ReadSchema: struct -(28) ColumnarToRow [codegen id : 7] -Input [2]: [ca_address_sk#18, ca_county#19] - -(29) Filter [codegen id : 7] +(28) CometFilter Input [2]: [ca_address_sk#18, ca_county#19] Condition : (ca_county#19 IN (Rush County,Toole County,Jefferson County,Dona Ana County,La Porte County) AND isnotnull(ca_address_sk#18)) -(30) Project [codegen id : 7] -Output [1]: [ca_address_sk#18] +(29) CometProject Input [2]: [ca_address_sk#18, ca_county#19] +Arguments: [ca_address_sk#18], [ca_address_sk#18] + +(30) ColumnarToRow [codegen id : 7] +Input [1]: [ca_address_sk#18] (31) BroadcastExchange Input [1]: [ca_address_sk#18] @@ -204,12 +204,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 8] +(35) CometFilter Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Condition : isnotnull(cd_demo_sk#20) -(36) Filter [codegen id : 8] +(36) ColumnarToRow [codegen id : 8] Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] -Condition : isnotnull(cd_demo_sk#20) (37) BroadcastExchange Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] @@ -251,9 +251,9 @@ Arguments: 100, [cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FI Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (48) -+- * Project (47) - +- * Filter (46) - +- * ColumnarToRow (45) ++- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) +- CometScan parquet spark_catalog.default.date_dim (44) @@ -264,16 +264,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2002), GreaterThanOrEqual(d_moy,1), LessThanOrEqual(d_moy,4), IsNotNull(d_date_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#9, d_year#38, d_moy#39] - -(46) Filter [codegen id : 1] +(45) CometFilter Input [3]: [d_date_sk#9, d_year#38, d_moy#39] Condition : (((((isnotnull(d_year#38) AND isnotnull(d_moy#39)) AND (d_year#38 = 2002)) AND (d_moy#39 >= 1)) AND (d_moy#39 <= 4)) AND isnotnull(d_date_sk#9)) -(47) Project [codegen id : 1] -Output [1]: [d_date_sk#9] +(46) CometProject Input [3]: [d_date_sk#9, d_year#38, d_moy#39] +Arguments: [d_date_sk#9], [d_date_sk#9] + +(47) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#9] (48) BroadcastExchange Input [1]: [d_date_sk#9] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt index e31b38b47..89893c831 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q10/simplified.txt @@ -14,9 +14,9 @@ TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purcha BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_current_addr_sk,c_current_cdemo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] InputAdapter BroadcastExchange #2 @@ -29,10 +29,10 @@ TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purcha SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk] #3 @@ -61,15 +61,15 @@ TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purcha InputAdapter BroadcastExchange #6 WholeStageCodegen (7) - Project [ca_address_sk] - Filter [ca_county,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_county,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county] InputAdapter BroadcastExchange #7 WholeStageCodegen (8) - Filter [cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt index f821d2a67..c663d4688 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/explain.txt @@ -14,12 +14,12 @@ TakeOrderedAndProject (72) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.store_sales (4) : : : +- ReusedExchange (10) : : +- BroadcastExchange (32) @@ -30,12 +30,12 @@ TakeOrderedAndProject (72) : : +- * BroadcastHashJoin Inner BuildRight (27) : : :- * Project (25) : : : +- * BroadcastHashJoin Inner BuildRight (24) - : : : :- * Filter (19) - : : : : +- * ColumnarToRow (18) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) : : : : +- CometScan parquet spark_catalog.default.customer (17) : : : +- BroadcastExchange (23) - : : : +- * Filter (22) - : : : +- * ColumnarToRow (21) + : : : +- * ColumnarToRow (22) + : : : +- CometFilter (21) : : : +- CometScan parquet spark_catalog.default.store_sales (20) : : +- ReusedExchange (26) : +- BroadcastExchange (51) @@ -47,12 +47,12 @@ TakeOrderedAndProject (72) : +- * BroadcastHashJoin Inner BuildRight (45) : :- * Project (43) : : +- * BroadcastHashJoin Inner BuildRight (42) - : : :- * Filter (37) - : : : +- * ColumnarToRow (36) + : : :- * ColumnarToRow (37) + : : : +- CometFilter (36) : : : +- CometScan parquet spark_catalog.default.customer (35) : : +- BroadcastExchange (41) - : : +- * Filter (40) - : : +- * ColumnarToRow (39) + : : +- * ColumnarToRow (40) + : : +- CometFilter (39) : : +- CometScan parquet spark_catalog.default.web_sales (38) : +- ReusedExchange (44) +- BroadcastExchange (69) @@ -63,12 +63,12 @@ TakeOrderedAndProject (72) +- * BroadcastHashJoin Inner BuildRight (64) :- * Project (62) : +- * BroadcastHashJoin Inner BuildRight (61) - : :- * Filter (56) - : : +- * ColumnarToRow (55) + : :- * ColumnarToRow (56) + : : +- CometFilter (55) : : +- CometScan parquet spark_catalog.default.customer (54) : +- BroadcastExchange (60) - : +- * Filter (59) - : +- * ColumnarToRow (58) + : +- * ColumnarToRow (59) + : +- CometFilter (58) : +- CometScan parquet spark_catalog.default.web_sales (57) +- ReusedExchange (63) @@ -80,12 +80,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] -Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) (4) Scan parquet spark_catalog.default.store_sales Output [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] @@ -95,12 +95,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Condition : isnotnull(ss_customer_sk#9) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] -Condition : isnotnull(ss_customer_sk#9) (7) BroadcastExchange Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] @@ -158,12 +158,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 6] +(18) CometFilter Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_customer_id#22)) -(19) Filter [codegen id : 6] +(19) ColumnarToRow [codegen id : 6] Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] -Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_customer_id#22)) (20) Scan parquet spark_catalog.default.store_sales Output [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] @@ -173,12 +173,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#32), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] +(21) CometFilter Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Condition : isnotnull(ss_customer_sk#29) -(22) Filter [codegen id : 4] +(22) ColumnarToRow [codegen id : 4] Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] -Condition : isnotnull(ss_customer_sk#29) (23) BroadcastExchange Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] @@ -246,12 +246,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(36) ColumnarToRow [codegen id : 10] +(36) CometFilter Input [8]: [c_customer_sk#41, c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48] +Condition : (isnotnull(c_customer_sk#41) AND isnotnull(c_customer_id#42)) -(37) Filter [codegen id : 10] +(37) ColumnarToRow [codegen id : 10] Input [8]: [c_customer_sk#41, c_customer_id#42, c_first_name#43, c_last_name#44, c_preferred_cust_flag#45, c_birth_country#46, c_login#47, c_email_address#48] -Condition : (isnotnull(c_customer_sk#41) AND isnotnull(c_customer_id#42)) (38) Scan parquet spark_catalog.default.web_sales Output [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] @@ -261,12 +261,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#52), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(39) ColumnarToRow [codegen id : 8] +(39) CometFilter Input [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] +Condition : isnotnull(ws_bill_customer_sk#49) -(40) Filter [codegen id : 8] +(40) ColumnarToRow [codegen id : 8] Input [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] -Condition : isnotnull(ws_bill_customer_sk#49) (41) BroadcastExchange Input [4]: [ws_bill_customer_sk#49, ws_ext_discount_amt#50, ws_ext_list_price#51, ws_sold_date_sk#52] @@ -338,12 +338,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(55) ColumnarToRow [codegen id : 14] +(55) CometFilter Input [8]: [c_customer_sk#61, c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68] +Condition : (isnotnull(c_customer_sk#61) AND isnotnull(c_customer_id#62)) -(56) Filter [codegen id : 14] +(56) ColumnarToRow [codegen id : 14] Input [8]: [c_customer_sk#61, c_customer_id#62, c_first_name#63, c_last_name#64, c_preferred_cust_flag#65, c_birth_country#66, c_login#67, c_email_address#68] -Condition : (isnotnull(c_customer_sk#61) AND isnotnull(c_customer_id#62)) (57) Scan parquet spark_catalog.default.web_sales Output [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] @@ -353,12 +353,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#72), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(58) ColumnarToRow [codegen id : 12] +(58) CometFilter Input [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] +Condition : isnotnull(ws_bill_customer_sk#69) -(59) Filter [codegen id : 12] +(59) ColumnarToRow [codegen id : 12] Input [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] -Condition : isnotnull(ws_bill_customer_sk#69) (60) BroadcastExchange Input [4]: [ws_bill_customer_sk#69, ws_ext_discount_amt#70, ws_ext_list_price#71, ws_sold_date_sk#72] @@ -427,8 +427,8 @@ Arguments: 100, [customer_preferred_cust_flag#39 ASC NULLS FIRST], [customer_pre Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 BroadcastExchange (76) -+- * Filter (75) - +- * ColumnarToRow (74) ++- * ColumnarToRow (75) + +- CometFilter (74) +- CometScan parquet spark_catalog.default.date_dim (73) @@ -439,12 +439,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(74) ColumnarToRow [codegen id : 1] +(74) CometFilter Input [2]: [d_date_sk#14, d_year#15] +Condition : ((isnotnull(d_year#15) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#14)) -(75) Filter [codegen id : 1] +(75) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#14, d_year#15] -Condition : ((isnotnull(d_year#15) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#14)) (76) BroadcastExchange Input [2]: [d_date_sk#14, d_year#15] @@ -452,8 +452,8 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint) Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#32 IN dynamicpruning#33 BroadcastExchange (80) -+- * Filter (79) - +- * ColumnarToRow (78) ++- * ColumnarToRow (79) + +- CometFilter (78) +- CometScan parquet spark_catalog.default.date_dim (77) @@ -464,12 +464,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] ReadSchema: struct -(78) ColumnarToRow [codegen id : 1] +(78) CometFilter Input [2]: [d_date_sk#34, d_year#35] +Condition : ((isnotnull(d_year#35) AND (d_year#35 = 2002)) AND isnotnull(d_date_sk#34)) -(79) Filter [codegen id : 1] +(79) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#34, d_year#35] -Condition : ((isnotnull(d_year#35) AND (d_year#35 = 2002)) AND isnotnull(d_date_sk#34)) (80) BroadcastExchange Input [2]: [d_date_sk#34, d_year#35] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt index 55c995970..562b5fdf2 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q11/simplified.txt @@ -16,23 +16,23 @@ TakeOrderedAndProject [customer_preferred_cust_flag] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #3 @@ -48,23 +48,23 @@ TakeOrderedAndProject [customer_preferred_cust_flag] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #6 WholeStageCodegen (4) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #7 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #7 @@ -81,16 +81,16 @@ TakeOrderedAndProject [customer_preferred_cust_flag] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #10 WholeStageCodegen (8) - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -107,16 +107,16 @@ TakeOrderedAndProject [customer_preferred_cust_flag] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #13 WholeStageCodegen (12) - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt index 49faad274..6cf7f4b08 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/explain.txt @@ -11,12 +11,12 @@ TakeOrderedAndProject (20) +- * BroadcastHashJoin Inner BuildRight (11) :- * Project (9) : +- * BroadcastHashJoin Inner BuildRight (8) - : :- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.web_sales (1) : +- BroadcastExchange (7) - : +- * Filter (6) - : +- * ColumnarToRow (5) + : +- * ColumnarToRow (6) + : +- CometFilter (5) : +- CometScan parquet spark_catalog.default.item (4) +- ReusedExchange (10) @@ -29,12 +29,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] -Condition : isnotnull(ws_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -43,12 +43,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] -Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) (7) BroadcastExchange Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -119,9 +119,9 @@ Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_ite Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (25) -+- * Project (24) - +- * Filter (23) - +- * ColumnarToRow (22) ++- * ColumnarToRow (24) + +- CometProject (23) + +- CometFilter (22) +- CometScan parquet spark_catalog.default.date_dim (21) @@ -132,16 +132,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] ReadSchema: struct -(22) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#11, d_date#19] - -(23) Filter [codegen id : 1] +(22) CometFilter Input [2]: [d_date_sk#11, d_date#19] Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) -(24) Project [codegen id : 1] -Output [1]: [d_date_sk#11] +(23) CometProject Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(24) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] (25) BroadcastExchange Input [1]: [d_date_sk#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt index 59f27988d..fae1c6dba 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q12/simplified.txt @@ -17,24 +17,24 @@ TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_c BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_ext_sales_price,ws_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Filter [i_category,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] InputAdapter ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt index 238d32e1b..a647b1f05 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/explain.txt @@ -12,26 +12,26 @@ : : : +- * BroadcastHashJoin Inner BuildRight (15) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.store (4) : : : +- BroadcastExchange (14) - : : : +- * Project (13) - : : : +- * Filter (12) - : : : +- * ColumnarToRow (11) + : : : +- * ColumnarToRow (13) + : : : +- CometProject (12) + : : : +- CometFilter (11) : : : +- CometScan parquet spark_catalog.default.customer_address (10) : : +- ReusedExchange (17) : +- BroadcastExchange (23) - : +- * Filter (22) - : +- * ColumnarToRow (21) + : +- * ColumnarToRow (22) + : +- CometFilter (21) : +- CometScan parquet spark_catalog.default.customer_demographics (20) +- BroadcastExchange (29) - +- * Filter (28) - +- * ColumnarToRow (27) + +- * ColumnarToRow (28) + +- CometFilter (27) +- CometScan parquet spark_catalog.default.household_demographics (26) @@ -43,12 +43,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#10), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_hdemo_sk), Or(Or(And(GreaterThanOrEqual(ss_net_profit,100.00),LessThanOrEqual(ss_net_profit,200.00)),And(GreaterThanOrEqual(ss_net_profit,150.00),LessThanOrEqual(ss_net_profit,300.00))),And(GreaterThanOrEqual(ss_net_profit,50.00),LessThanOrEqual(ss_net_profit,250.00))), Or(Or(And(GreaterThanOrEqual(ss_sales_price,100.00),LessThanOrEqual(ss_sales_price,150.00)),And(GreaterThanOrEqual(ss_sales_price,50.00),LessThanOrEqual(ss_sales_price,100.00))),And(GreaterThanOrEqual(ss_sales_price,150.00),LessThanOrEqual(ss_sales_price,200.00)))] ReadSchema: struct -(2) ColumnarToRow [codegen id : 6] +(2) CometFilter Input [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10] +Condition : (((((isnotnull(ss_store_sk#4) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_cdemo_sk#1)) AND isnotnull(ss_hdemo_sk#2)) AND ((((ss_net_profit#9 >= 100.00) AND (ss_net_profit#9 <= 200.00)) OR ((ss_net_profit#9 >= 150.00) AND (ss_net_profit#9 <= 300.00))) OR ((ss_net_profit#9 >= 50.00) AND (ss_net_profit#9 <= 250.00)))) AND ((((ss_sales_price#6 >= 100.00) AND (ss_sales_price#6 <= 150.00)) OR ((ss_sales_price#6 >= 50.00) AND (ss_sales_price#6 <= 100.00))) OR ((ss_sales_price#6 >= 150.00) AND (ss_sales_price#6 <= 200.00)))) -(3) Filter [codegen id : 6] +(3) ColumnarToRow [codegen id : 6] Input [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10] -Condition : (((((isnotnull(ss_store_sk#4) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_cdemo_sk#1)) AND isnotnull(ss_hdemo_sk#2)) AND ((((ss_net_profit#9 >= 100.00) AND (ss_net_profit#9 <= 200.00)) OR ((ss_net_profit#9 >= 150.00) AND (ss_net_profit#9 <= 300.00))) OR ((ss_net_profit#9 >= 50.00) AND (ss_net_profit#9 <= 250.00)))) AND ((((ss_sales_price#6 >= 100.00) AND (ss_sales_price#6 <= 150.00)) OR ((ss_sales_price#6 >= 50.00) AND (ss_sales_price#6 <= 100.00))) OR ((ss_sales_price#6 >= 150.00) AND (ss_sales_price#6 <= 200.00)))) (4) Scan parquet spark_catalog.default.store Output [1]: [s_store_sk#12] @@ -57,12 +57,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [1]: [s_store_sk#12] +Condition : isnotnull(s_store_sk#12) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [1]: [s_store_sk#12] -Condition : isnotnull(s_store_sk#12) (7) BroadcastExchange Input [1]: [s_store_sk#12] @@ -85,16 +85,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [OH,TX]),In(ca_state, [KY,NM,OR])),In(ca_state, [MS,TX,VA]))] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] -Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] - -(12) Filter [codegen id : 2] +(11) CometFilter Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] Condition : (((isnotnull(ca_country#15) AND (ca_country#15 = United States)) AND isnotnull(ca_address_sk#13)) AND ((ca_state#14 IN (TX,OH) OR ca_state#14 IN (OR,NM,KY)) OR ca_state#14 IN (VA,TX,MS))) -(13) Project [codegen id : 2] -Output [2]: [ca_address_sk#13, ca_state#14] +(12) CometProject Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Arguments: [ca_address_sk#13, ca_state#14], [ca_address_sk#13, ca_state#14] + +(13) ColumnarToRow [codegen id : 2] +Input [2]: [ca_address_sk#13, ca_state#14] (14) BroadcastExchange Input [2]: [ca_address_sk#13, ca_state#14] @@ -130,12 +130,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,Advanced Degree )),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College ))),And(EqualTo(cd_marital_status,W),EqualTo(cd_education_status,2 yr Degree )))] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] +(21) CometFilter Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Condition : (isnotnull(cd_demo_sk#17) AND ((((cd_marital_status#18 = M) AND (cd_education_status#19 = Advanced Degree )) OR ((cd_marital_status#18 = S) AND (cd_education_status#19 = College ))) OR ((cd_marital_status#18 = W) AND (cd_education_status#19 = 2 yr Degree )))) -(22) Filter [codegen id : 4] +(22) ColumnarToRow [codegen id : 4] Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] -Condition : (isnotnull(cd_demo_sk#17) AND ((((cd_marital_status#18 = M) AND (cd_education_status#19 = Advanced Degree )) OR ((cd_marital_status#18 = S) AND (cd_education_status#19 = College ))) OR ((cd_marital_status#18 = W) AND (cd_education_status#19 = 2 yr Degree )))) (23) BroadcastExchange Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] @@ -158,12 +158,12 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_demo_sk), Or(EqualTo(hd_dep_count,3),EqualTo(hd_dep_count,1))] ReadSchema: struct -(27) ColumnarToRow [codegen id : 5] +(27) CometFilter Input [2]: [hd_demo_sk#20, hd_dep_count#21] +Condition : (isnotnull(hd_demo_sk#20) AND ((hd_dep_count#21 = 3) OR (hd_dep_count#21 = 1))) -(28) Filter [codegen id : 5] +(28) ColumnarToRow [codegen id : 5] Input [2]: [hd_demo_sk#20, hd_dep_count#21] -Condition : (isnotnull(hd_demo_sk#20) AND ((hd_dep_count#21 = 3) OR (hd_dep_count#21 = 1))) (29) BroadcastExchange Input [2]: [hd_demo_sk#20, hd_dep_count#21] @@ -201,9 +201,9 @@ Results [4]: [avg(ss_quantity#5)#36 AS avg(ss_quantity)#40, cast((avg(UnscaledVa Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#10 IN dynamicpruning#11 BroadcastExchange (39) -+- * Project (38) - +- * Filter (37) - +- * ColumnarToRow (36) ++- * ColumnarToRow (38) + +- CometProject (37) + +- CometFilter (36) +- CometScan parquet spark_catalog.default.date_dim (35) @@ -214,16 +214,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(36) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#16, d_year#44] - -(37) Filter [codegen id : 1] +(36) CometFilter Input [2]: [d_date_sk#16, d_year#44] Condition : ((isnotnull(d_year#44) AND (d_year#44 = 2001)) AND isnotnull(d_date_sk#16)) -(38) Project [codegen id : 1] -Output [1]: [d_date_sk#16] +(37) CometProject Input [2]: [d_date_sk#16, d_year#44] +Arguments: [d_date_sk#16], [d_date_sk#16] + +(38) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#16] (39) BroadcastExchange Input [1]: [d_date_sk#16] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt index 5e9dda7b9..5e5fc41f8 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q13/simplified.txt @@ -14,46 +14,46 @@ WholeStageCodegen (7) BroadcastHashJoin [ss_addr_sk,ca_address_sk,ca_state,ss_net_profit] Project [ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost,ss_net_profit,ss_sold_date_sk] BroadcastHashJoin [ss_store_sk,s_store_sk] - Filter [ss_store_sk,ss_addr_sk,ss_cdemo_sk,ss_hdemo_sk,ss_net_profit,ss_sales_price] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_addr_sk,ss_cdemo_sk,ss_hdemo_sk,ss_net_profit,ss_sales_price] CometScan parquet spark_catalog.default.store_sales [ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_ext_sales_price,ss_ext_wholesale_cost,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk] InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [ca_address_sk,ca_state] - Filter [ca_country,ca_address_sk,ca_state] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk,ca_state] + CometFilter [ca_country,ca_address_sk,ca_state] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Filter [cd_demo_sk,cd_marital_status,cd_education_status] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status,cd_education_status] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] InputAdapter BroadcastExchange #6 WholeStageCodegen (5) - Filter [hd_demo_sk,hd_dep_count] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [hd_demo_sk,hd_dep_count] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt index fc94f648f..565cb97da 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/explain.txt @@ -15,14 +15,14 @@ TakeOrderedAndProject (105) : :- * Project (59) : : +- * BroadcastHashJoin Inner BuildRight (58) : : :- * BroadcastHashJoin LeftSemi BuildRight (51) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- BroadcastExchange (50) : : : +- * Project (49) : : : +- * BroadcastHashJoin Inner BuildRight (48) - : : : :- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : :- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.item (4) : : : +- BroadcastExchange (47) : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) @@ -33,25 +33,25 @@ TakeOrderedAndProject (105) : : : : +- * BroadcastHashJoin Inner BuildRight (31) : : : : :- * Project (29) : : : : : +- * BroadcastHashJoin Inner BuildRight (28) - : : : : : :- * Filter (9) - : : : : : : +- * ColumnarToRow (8) + : : : : : :- * ColumnarToRow (9) + : : : : : : +- CometFilter (8) : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) : : : : : +- BroadcastExchange (27) : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) - : : : : : :- * Filter (12) - : : : : : : +- * ColumnarToRow (11) + : : : : : :- * ColumnarToRow (12) + : : : : : : +- CometFilter (11) : : : : : : +- CometScan parquet spark_catalog.default.item (10) : : : : : +- BroadcastExchange (25) : : : : : +- * Project (24) : : : : : +- * BroadcastHashJoin Inner BuildRight (23) : : : : : :- * Project (21) : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) - : : : : : : :- * Filter (15) - : : : : : : : +- * ColumnarToRow (14) + : : : : : : :- * ColumnarToRow (15) + : : : : : : : +- CometFilter (14) : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) : : : : : : +- BroadcastExchange (19) - : : : : : : +- * Filter (18) - : : : : : : +- * ColumnarToRow (17) + : : : : : : +- * ColumnarToRow (18) + : : : : : : +- CometFilter (17) : : : : : : +- CometScan parquet spark_catalog.default.item (16) : : : : : +- ReusedExchange (22) : : : : +- ReusedExchange (30) @@ -60,15 +60,15 @@ TakeOrderedAndProject (105) : : : +- * BroadcastHashJoin Inner BuildRight (43) : : : :- * Project (41) : : : : +- * BroadcastHashJoin Inner BuildRight (40) - : : : : :- * Filter (38) - : : : : : +- * ColumnarToRow (37) + : : : : :- * ColumnarToRow (38) + : : : : : +- CometFilter (37) : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) : : : : +- ReusedExchange (39) : : : +- ReusedExchange (42) : : +- BroadcastExchange (57) : : +- * BroadcastHashJoin LeftSemi BuildRight (56) - : : :- * Filter (54) - : : : +- * ColumnarToRow (53) + : : :- * ColumnarToRow (54) + : : : +- CometFilter (53) : : : +- CometScan parquet spark_catalog.default.item (52) : : +- ReusedExchange (55) : +- ReusedExchange (60) @@ -82,8 +82,8 @@ TakeOrderedAndProject (105) : :- * Project (75) : : +- * BroadcastHashJoin Inner BuildRight (74) : : :- * BroadcastHashJoin LeftSemi BuildRight (72) - : : : :- * Filter (70) - : : : : +- * ColumnarToRow (69) + : : : :- * ColumnarToRow (70) + : : : : +- CometFilter (69) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (68) : : : +- ReusedExchange (71) : : +- ReusedExchange (73) @@ -98,8 +98,8 @@ TakeOrderedAndProject (105) :- * Project (91) : +- * BroadcastHashJoin Inner BuildRight (90) : :- * BroadcastHashJoin LeftSemi BuildRight (88) - : : :- * Filter (86) - : : : +- * ColumnarToRow (85) + : : :- * ColumnarToRow (86) + : : : +- CometFilter (85) : : : +- CometScan parquet spark_catalog.default.web_sales (84) : : +- ReusedExchange (87) : +- ReusedExchange (89) @@ -114,12 +114,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 25] +(2) CometFilter Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) -(3) Filter [codegen id : 25] +(3) ColumnarToRow [codegen id : 25] Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] -Condition : isnotnull(ss_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] @@ -128,12 +128,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 11] +(5) CometFilter Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) -(6) Filter [codegen id : 11] +(6) ColumnarToRow [codegen id : 11] Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] -Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) (7) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] @@ -143,12 +143,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 6] +(8) CometFilter Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) -(9) Filter [codegen id : 6] +(9) ColumnarToRow [codegen id : 6] Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] -Condition : isnotnull(ss_item_sk#10) (10) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] @@ -157,12 +157,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 4] +(11) CometFilter Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) -(12) Filter [codegen id : 4] +(12) ColumnarToRow [codegen id : 4] Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] -Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) (13) Scan parquet spark_catalog.default.catalog_sales Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] @@ -172,12 +172,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] -Condition : isnotnull(cs_item_sk#17) (16) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] @@ -186,12 +186,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 1] +(17) CometFilter Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) -(18) Filter [codegen id : 1] +(18) ColumnarToRow [codegen id : 1] Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] -Condition : isnotnull(i_item_sk#20) (19) BroadcastExchange Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] @@ -283,12 +283,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(37) ColumnarToRow [codegen id : 9] +(37) CometFilter Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) -(38) Filter [codegen id : 9] +(38) ColumnarToRow [codegen id : 9] Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] -Condition : isnotnull(ws_item_sk#29) (39) ReusedExchange [Reuses operator id: 19] Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] @@ -357,12 +357,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(53) ColumnarToRow [codegen id : 23] +(53) CometFilter Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : isnotnull(i_item_sk#38) -(54) Filter [codegen id : 23] +(54) ColumnarToRow [codegen id : 23] Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] -Condition : isnotnull(i_item_sk#38) (55) ReusedExchange [Reuses operator id: 50] Output [1]: [ss_item_sk#37] @@ -434,12 +434,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#62), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(69) ColumnarToRow [codegen id : 51] +(69) CometFilter Input [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62] +Condition : isnotnull(cs_item_sk#59) -(70) Filter [codegen id : 51] +(70) ColumnarToRow [codegen id : 51] Input [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62] -Condition : isnotnull(cs_item_sk#59) (71) ReusedExchange [Reuses operator id: 50] Output [1]: [ss_item_sk#64] @@ -510,12 +510,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#84), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(85) ColumnarToRow [codegen id : 77] +(85) CometFilter Input [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84] +Condition : isnotnull(ws_item_sk#81) -(86) Filter [codegen id : 77] +(86) ColumnarToRow [codegen id : 77] Input [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84] -Condition : isnotnull(ws_item_sk#81) (87) ReusedExchange [Reuses operator id: 50] Output [1]: [ss_item_sk#86] @@ -727,9 +727,9 @@ Subquery:4 Hosting operator id = 116 Hosting Expression = ws_sold_date_sk#134 IN Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 BroadcastExchange (129) -+- * Project (128) - +- * Filter (127) - +- * ColumnarToRow (126) ++- * ColumnarToRow (128) + +- CometProject (127) + +- CometFilter (126) +- CometScan parquet spark_catalog.default.date_dim (125) @@ -740,16 +740,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,11), IsNotNull(d_date_sk)] ReadSchema: struct -(126) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#42, d_year#145, d_moy#146] - -(127) Filter [codegen id : 1] +(126) CometFilter Input [3]: [d_date_sk#42, d_year#145, d_moy#146] Condition : ((((isnotnull(d_year#145) AND isnotnull(d_moy#146)) AND (d_year#145 = 2001)) AND (d_moy#146 = 11)) AND isnotnull(d_date_sk#42)) -(128) Project [codegen id : 1] -Output [1]: [d_date_sk#42] +(127) CometProject Input [3]: [d_date_sk#42, d_year#145, d_moy#146] +Arguments: [d_date_sk#42], [d_date_sk#42] + +(128) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#42] (129) BroadcastExchange Input [1]: [d_date_sk#42] @@ -757,9 +757,9 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)) Subquery:6 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 BroadcastExchange (134) -+- * Project (133) - +- * Filter (132) - +- * ColumnarToRow (131) ++- * ColumnarToRow (133) + +- CometProject (132) + +- CometFilter (131) +- CometScan parquet spark_catalog.default.date_dim (130) @@ -770,16 +770,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(131) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#25, d_year#147] - -(132) Filter [codegen id : 1] +(131) CometFilter Input [2]: [d_date_sk#25, d_year#147] Condition : (((isnotnull(d_year#147) AND (d_year#147 >= 1999)) AND (d_year#147 <= 2001)) AND isnotnull(d_date_sk#25)) -(133) Project [codegen id : 1] -Output [1]: [d_date_sk#25] +(132) CometProject Input [2]: [d_date_sk#25, d_year#147] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(133) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] (134) BroadcastExchange Input [1]: [d_date_sk#25] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt index a76997516..cf688c448 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14a/simplified.txt @@ -57,26 +57,26 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum(sales),su Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ss_item_sk,i_item_sk] BroadcastHashJoin [ss_item_sk,ss_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #4 WholeStageCodegen (11) Project [i_item_sk] BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] - Filter [i_brand_id,i_class_id,i_category_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_brand_id,i_class_id,i_category_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter BroadcastExchange #5 @@ -91,25 +91,25 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum(sales),su BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #7 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #8 WholeStageCodegen (4) BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] - Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter BroadcastExchange #9 @@ -118,17 +118,17 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum(sales),su BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter BroadcastExchange #10 WholeStageCodegen (1) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter ReusedExchange [d_date_sk] #7 @@ -141,9 +141,9 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum(sales),su BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter @@ -154,9 +154,9 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum(sales),su BroadcastExchange #12 WholeStageCodegen (23) BroadcastHashJoin [i_item_sk,ss_item_sk] - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter ReusedExchange [ss_item_sk] #4 @@ -176,9 +176,9 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum(sales),su Project [cs_quantity,cs_list_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [cs_item_sk,i_item_sk] BroadcastHashJoin [cs_item_sk,ss_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -201,9 +201,9 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum(sales),su Project [ws_quantity,ws_list_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ws_item_sk,i_item_sk] BroadcastHashJoin [ws_item_sk,ss_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_quantity,ws_list_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt index c6b42f19c..265909ec2 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/explain.txt @@ -10,14 +10,14 @@ TakeOrderedAndProject (84) : :- * Project (59) : : +- * BroadcastHashJoin Inner BuildRight (58) : : :- * BroadcastHashJoin LeftSemi BuildRight (51) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- BroadcastExchange (50) : : : +- * Project (49) : : : +- * BroadcastHashJoin Inner BuildRight (48) - : : : :- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : :- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.item (4) : : : +- BroadcastExchange (47) : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) @@ -28,25 +28,25 @@ TakeOrderedAndProject (84) : : : : +- * BroadcastHashJoin Inner BuildRight (31) : : : : :- * Project (29) : : : : : +- * BroadcastHashJoin Inner BuildRight (28) - : : : : : :- * Filter (9) - : : : : : : +- * ColumnarToRow (8) + : : : : : :- * ColumnarToRow (9) + : : : : : : +- CometFilter (8) : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) : : : : : +- BroadcastExchange (27) : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) - : : : : : :- * Filter (12) - : : : : : : +- * ColumnarToRow (11) + : : : : : :- * ColumnarToRow (12) + : : : : : : +- CometFilter (11) : : : : : : +- CometScan parquet spark_catalog.default.item (10) : : : : : +- BroadcastExchange (25) : : : : : +- * Project (24) : : : : : +- * BroadcastHashJoin Inner BuildRight (23) : : : : : :- * Project (21) : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) - : : : : : : :- * Filter (15) - : : : : : : : +- * ColumnarToRow (14) + : : : : : : :- * ColumnarToRow (15) + : : : : : : : +- CometFilter (14) : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) : : : : : : +- BroadcastExchange (19) - : : : : : : +- * Filter (18) - : : : : : : +- * ColumnarToRow (17) + : : : : : : +- * ColumnarToRow (18) + : : : : : : +- CometFilter (17) : : : : : : +- CometScan parquet spark_catalog.default.item (16) : : : : : +- ReusedExchange (22) : : : : +- ReusedExchange (30) @@ -55,15 +55,15 @@ TakeOrderedAndProject (84) : : : +- * BroadcastHashJoin Inner BuildRight (43) : : : :- * Project (41) : : : : +- * BroadcastHashJoin Inner BuildRight (40) - : : : : :- * Filter (38) - : : : : : +- * ColumnarToRow (37) + : : : : :- * ColumnarToRow (38) + : : : : : +- CometFilter (37) : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) : : : : +- ReusedExchange (39) : : : +- ReusedExchange (42) : : +- BroadcastExchange (57) : : +- * BroadcastHashJoin LeftSemi BuildRight (56) - : : :- * Filter (54) - : : : +- * ColumnarToRow (53) + : : :- * ColumnarToRow (54) + : : : +- CometFilter (53) : : : +- CometScan parquet spark_catalog.default.item (52) : : +- ReusedExchange (55) : +- ReusedExchange (60) @@ -77,8 +77,8 @@ TakeOrderedAndProject (84) :- * Project (74) : +- * BroadcastHashJoin Inner BuildRight (73) : :- * BroadcastHashJoin LeftSemi BuildRight (71) - : : :- * Filter (69) - : : : +- * ColumnarToRow (68) + : : :- * ColumnarToRow (69) + : : : +- CometFilter (68) : : : +- CometScan parquet spark_catalog.default.store_sales (67) : : +- ReusedExchange (70) : +- ReusedExchange (72) @@ -93,12 +93,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 25] +(2) CometFilter Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) -(3) Filter [codegen id : 25] +(3) ColumnarToRow [codegen id : 25] Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] -Condition : isnotnull(ss_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] @@ -107,12 +107,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 11] +(5) CometFilter Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) -(6) Filter [codegen id : 11] +(6) ColumnarToRow [codegen id : 11] Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] -Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) (7) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] @@ -122,12 +122,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 6] +(8) CometFilter Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) -(9) Filter [codegen id : 6] +(9) ColumnarToRow [codegen id : 6] Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] -Condition : isnotnull(ss_item_sk#10) (10) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] @@ -136,12 +136,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 4] +(11) CometFilter Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) -(12) Filter [codegen id : 4] +(12) ColumnarToRow [codegen id : 4] Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] -Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) (13) Scan parquet spark_catalog.default.catalog_sales Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] @@ -151,12 +151,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] -Condition : isnotnull(cs_item_sk#17) (16) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] @@ -165,12 +165,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 1] +(17) CometFilter Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) -(18) Filter [codegen id : 1] +(18) ColumnarToRow [codegen id : 1] Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] -Condition : isnotnull(i_item_sk#20) (19) BroadcastExchange Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] @@ -262,12 +262,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(37) ColumnarToRow [codegen id : 9] +(37) CometFilter Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) -(38) Filter [codegen id : 9] +(38) ColumnarToRow [codegen id : 9] Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] -Condition : isnotnull(ws_item_sk#29) (39) ReusedExchange [Reuses operator id: 19] Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] @@ -336,12 +336,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] ReadSchema: struct -(53) ColumnarToRow [codegen id : 23] +(53) CometFilter Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : (((isnotnull(i_item_sk#38) AND isnotnull(i_brand_id#39)) AND isnotnull(i_class_id#40)) AND isnotnull(i_category_id#41)) -(54) Filter [codegen id : 23] +(54) ColumnarToRow [codegen id : 23] Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] -Condition : (((isnotnull(i_item_sk#38) AND isnotnull(i_brand_id#39)) AND isnotnull(i_class_id#40)) AND isnotnull(i_category_id#41)) (55) ReusedExchange [Reuses operator id: 50] Output [1]: [ss_item_sk#37] @@ -409,12 +409,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#59), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(68) ColumnarToRow [codegen id : 50] +(68) CometFilter Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] +Condition : isnotnull(ss_item_sk#56) -(69) Filter [codegen id : 50] +(69) ColumnarToRow [codegen id : 50] Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] -Condition : isnotnull(ss_item_sk#56) (70) ReusedExchange [Reuses operator id: 50] Output [1]: [ss_item_sk#61] @@ -608,9 +608,9 @@ Subquery:4 Hosting operator id = 95 Hosting Expression = ws_sold_date_sk#94 IN d Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 BroadcastExchange (108) -+- * Project (107) - +- * Filter (106) - +- * ColumnarToRow (105) ++- * ColumnarToRow (107) + +- CometProject (106) + +- CometFilter (105) +- CometScan parquet spark_catalog.default.date_dim (104) @@ -621,27 +621,27 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#106), IsNotNull(d_date_sk)] ReadSchema: struct -(105) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#42, d_week_seq#105] - -(106) Filter [codegen id : 1] +(105) CometFilter Input [2]: [d_date_sk#42, d_week_seq#105] Condition : ((isnotnull(d_week_seq#105) AND (d_week_seq#105 = ReusedSubquery Subquery scalar-subquery#106, [id=#107])) AND isnotnull(d_date_sk#42)) -(107) Project [codegen id : 1] -Output [1]: [d_date_sk#42] +(106) CometProject Input [2]: [d_date_sk#42, d_week_seq#105] +Arguments: [d_date_sk#42], [d_date_sk#42] + +(107) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#42] (108) BroadcastExchange Input [1]: [d_date_sk#42] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] -Subquery:6 Hosting operator id = 106 Hosting Expression = ReusedSubquery Subquery scalar-subquery#106, [id=#107] +Subquery:6 Hosting operator id = 105 Hosting Expression = ReusedSubquery Subquery scalar-subquery#106, [id=#107] Subquery:7 Hosting operator id = 104 Hosting Expression = Subquery scalar-subquery#106, [id=#107] -* Project (112) -+- * Filter (111) - +- * ColumnarToRow (110) +* ColumnarToRow (112) ++- CometProject (111) + +- CometFilter (110) +- CometScan parquet spark_catalog.default.date_dim (109) @@ -652,22 +652,22 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,2000), EqualTo(d_moy,12), EqualTo(d_dom,11)] ReadSchema: struct -(110) ColumnarToRow [codegen id : 1] -Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] - -(111) Filter [codegen id : 1] +(110) CometFilter Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] Condition : (((((isnotnull(d_year#109) AND isnotnull(d_moy#110)) AND isnotnull(d_dom#111)) AND (d_year#109 = 2000)) AND (d_moy#110 = 12)) AND (d_dom#111 = 11)) -(112) Project [codegen id : 1] -Output [1]: [d_week_seq#108] +(111) CometProject Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Arguments: [d_week_seq#108], [d_week_seq#108] + +(112) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#108] Subquery:8 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 BroadcastExchange (117) -+- * Project (116) - +- * Filter (115) - +- * ColumnarToRow (114) ++- * ColumnarToRow (116) + +- CometProject (115) + +- CometFilter (114) +- CometScan parquet spark_catalog.default.date_dim (113) @@ -678,16 +678,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(114) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#25, d_year#112] - -(115) Filter [codegen id : 1] +(114) CometFilter Input [2]: [d_date_sk#25, d_year#112] Condition : (((isnotnull(d_year#112) AND (d_year#112 >= 1999)) AND (d_year#112 <= 2001)) AND isnotnull(d_date_sk#25)) -(116) Project [codegen id : 1] -Output [1]: [d_date_sk#25] +(115) CometProject Input [2]: [d_date_sk#25, d_year#112] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(116) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] (117) BroadcastExchange Input [1]: [d_date_sk#25] @@ -701,9 +701,9 @@ Subquery:11 Hosting operator id = 81 Hosting Expression = ReusedSubquery Subquer Subquery:12 Hosting operator id = 67 Hosting Expression = ss_sold_date_sk#59 IN dynamicpruning#60 BroadcastExchange (122) -+- * Project (121) - +- * Filter (120) - +- * ColumnarToRow (119) ++- * ColumnarToRow (121) + +- CometProject (120) + +- CometFilter (119) +- CometScan parquet spark_catalog.default.date_dim (118) @@ -714,27 +714,27 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#114), IsNotNull(d_date_sk)] ReadSchema: struct -(119) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#66, d_week_seq#113] - -(120) Filter [codegen id : 1] +(119) CometFilter Input [2]: [d_date_sk#66, d_week_seq#113] Condition : ((isnotnull(d_week_seq#113) AND (d_week_seq#113 = ReusedSubquery Subquery scalar-subquery#114, [id=#115])) AND isnotnull(d_date_sk#66)) -(121) Project [codegen id : 1] -Output [1]: [d_date_sk#66] +(120) CometProject Input [2]: [d_date_sk#66, d_week_seq#113] +Arguments: [d_date_sk#66], [d_date_sk#66] + +(121) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#66] (122) BroadcastExchange Input [1]: [d_date_sk#66] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15] -Subquery:13 Hosting operator id = 120 Hosting Expression = ReusedSubquery Subquery scalar-subquery#114, [id=#115] +Subquery:13 Hosting operator id = 119 Hosting Expression = ReusedSubquery Subquery scalar-subquery#114, [id=#115] Subquery:14 Hosting operator id = 118 Hosting Expression = Subquery scalar-subquery#114, [id=#115] -* Project (126) -+- * Filter (125) - +- * ColumnarToRow (124) +* ColumnarToRow (126) ++- CometProject (125) + +- CometFilter (124) +- CometScan parquet spark_catalog.default.date_dim (123) @@ -745,15 +745,15 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1999), EqualTo(d_moy,12), EqualTo(d_dom,11)] ReadSchema: struct -(124) ColumnarToRow [codegen id : 1] -Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] - -(125) Filter [codegen id : 1] +(124) CometFilter Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] Condition : (((((isnotnull(d_year#117) AND isnotnull(d_moy#118)) AND isnotnull(d_dom#119)) AND (d_year#117 = 1999)) AND (d_moy#118 = 12)) AND (d_dom#119 = 11)) -(126) Project [codegen id : 1] -Output [1]: [d_week_seq#116] +(125) CometProject Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Arguments: [d_week_seq#116], [d_week_seq#116] + +(126) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#116] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt index 64646b717..55aa823ab 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q14b/simplified.txt @@ -48,34 +48,34 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ss_item_sk,i_item_sk] BroadcastHashJoin [ss_item_sk,ss_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_week_seq,d_date_sk] - ReusedSubquery [d_week_seq] #2 - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #2 CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] Subquery #2 WholeStageCodegen (1) - Project [d_week_seq] - Filter [d_year,d_moy,d_dom] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_moy,d_dom] CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] InputAdapter BroadcastExchange #3 WholeStageCodegen (11) Project [i_item_sk] BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] - Filter [i_brand_id,i_class_id,i_category_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_brand_id,i_class_id,i_category_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter BroadcastExchange #4 @@ -90,25 +90,25 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #3 BroadcastExchange #6 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #7 WholeStageCodegen (4) BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] - Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter BroadcastExchange #8 @@ -117,17 +117,17 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] ReusedSubquery [d_date_sk] #3 InputAdapter BroadcastExchange #9 WholeStageCodegen (1) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter ReusedExchange [d_date_sk] #6 @@ -140,9 +140,9 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] ReusedSubquery [d_date_sk] #3 InputAdapter @@ -153,9 +153,9 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ BroadcastExchange #11 WholeStageCodegen (23) BroadcastHashJoin [i_item_sk,ss_item_sk] - Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter ReusedExchange [ss_item_sk] #3 @@ -176,25 +176,25 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ss_item_sk,i_item_sk] BroadcastHashJoin [ss_item_sk,ss_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #5 BroadcastExchange #15 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_week_seq,d_date_sk] - ReusedSubquery [d_week_seq] #6 - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #6 CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] Subquery #6 WholeStageCodegen (1) - Project [d_week_seq] - Filter [d_year,d_moy,d_dom] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_moy,d_dom] CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] InputAdapter ReusedExchange [ss_item_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt index 10ae4b11b..13a621f77 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/explain.txt @@ -9,16 +9,16 @@ TakeOrderedAndProject (22) : +- * BroadcastHashJoin Inner BuildRight (14) : :- * Project (9) : : +- * BroadcastHashJoin Inner BuildRight (8) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : +- BroadcastExchange (7) - : : +- * Filter (6) - : : +- * ColumnarToRow (5) + : : +- * ColumnarToRow (6) + : : +- CometFilter (5) : : +- CometScan parquet spark_catalog.default.customer (4) : +- BroadcastExchange (13) - : +- * Filter (12) - : +- * ColumnarToRow (11) + : +- * ColumnarToRow (12) + : +- CometFilter (11) : +- CometScan parquet spark_catalog.default.customer_address (10) +- ReusedExchange (16) @@ -31,12 +31,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_bill_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [3]: [cs_bill_customer_sk#1, cs_sales_price#2, cs_sold_date_sk#3] +Condition : isnotnull(cs_bill_customer_sk#1) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [3]: [cs_bill_customer_sk#1, cs_sales_price#2, cs_sold_date_sk#3] -Condition : isnotnull(cs_bill_customer_sk#1) (4) Scan parquet spark_catalog.default.customer Output [2]: [c_customer_sk#5, c_current_addr_sk#6] @@ -45,12 +45,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [2]: [c_customer_sk#5, c_current_addr_sk#6] +Condition : (isnotnull(c_customer_sk#5) AND isnotnull(c_current_addr_sk#6)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [2]: [c_customer_sk#5, c_current_addr_sk#6] -Condition : (isnotnull(c_customer_sk#5) AND isnotnull(c_current_addr_sk#6)) (7) BroadcastExchange Input [2]: [c_customer_sk#5, c_current_addr_sk#6] @@ -73,12 +73,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] +Condition : isnotnull(ca_address_sk#7) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] -Condition : isnotnull(ca_address_sk#7) (13) BroadcastExchange Input [3]: [ca_address_sk#7, ca_state#8, ca_zip#9] @@ -133,9 +133,9 @@ Arguments: 100, [ca_zip#9 ASC NULLS FIRST], [ca_zip#9, sum(cs_sales_price)#14] Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (27) -+- * Project (26) - +- * Filter (25) - +- * ColumnarToRow (24) ++- * ColumnarToRow (26) + +- CometProject (25) + +- CometFilter (24) +- CometScan parquet spark_catalog.default.date_dim (23) @@ -146,16 +146,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(24) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#10, d_year#15, d_qoy#16] - -(25) Filter [codegen id : 1] +(24) CometFilter Input [3]: [d_date_sk#10, d_year#15, d_qoy#16] Condition : ((((isnotnull(d_qoy#16) AND isnotnull(d_year#15)) AND (d_qoy#16 = 2)) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#10)) -(26) Project [codegen id : 1] -Output [1]: [d_date_sk#10] +(25) CometProject Input [3]: [d_date_sk#10, d_year#15, d_qoy#16] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(26) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] (27) BroadcastExchange Input [1]: [d_date_sk#10] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt index 4b916d78f..5c750b2db 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q15/simplified.txt @@ -11,31 +11,31 @@ TakeOrderedAndProject [ca_zip,sum(cs_sales_price)] BroadcastHashJoin [c_current_addr_sk,ca_address_sk,ca_zip,ca_state,cs_sales_price] Project [cs_sales_price,cs_sold_date_sk,c_current_addr_sk] BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] - Filter [cs_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_sales_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_qoy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_qoy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [c_customer_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_zip] InputAdapter ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt index d21c24281..ccec341ad 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/explain.txt @@ -15,34 +15,34 @@ : : : : +- * SortMergeJoin LeftSemi (12) : : : : :- * Sort (6) : : : : : +- Exchange (5) - : : : : : +- * Project (4) - : : : : : +- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : : +- * Sort (11) : : : : +- Exchange (10) - : : : : +- * Project (9) - : : : : +- * ColumnarToRow (8) + : : : : +- * ColumnarToRow (9) + : : : : +- CometProject (8) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (7) : : : +- * Sort (18) : : : +- Exchange (17) - : : : +- * Project (16) - : : : +- * ColumnarToRow (15) + : : : +- * ColumnarToRow (16) + : : : +- CometProject (15) : : : +- CometScan parquet spark_catalog.default.catalog_returns (14) : : +- BroadcastExchange (24) - : : +- * Project (23) - : : +- * Filter (22) - : : +- * ColumnarToRow (21) + : : +- * ColumnarToRow (23) + : : +- CometProject (22) + : : +- CometFilter (21) : : +- CometScan parquet spark_catalog.default.date_dim (20) : +- BroadcastExchange (31) - : +- * Project (30) - : +- * Filter (29) - : +- * ColumnarToRow (28) + : +- * ColumnarToRow (30) + : +- CometProject (29) + : +- CometFilter (28) : +- CometScan parquet spark_catalog.default.customer_address (27) +- BroadcastExchange (38) - +- * Project (37) - +- * Filter (36) - +- * ColumnarToRow (35) + +- * ColumnarToRow (37) + +- CometProject (36) + +- CometFilter (35) +- CometScan parquet spark_catalog.default.call_center (34) @@ -53,16 +53,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_sales] PushedFilters: [IsNotNull(cs_ship_date_sk), IsNotNull(cs_ship_addr_sk), IsNotNull(cs_call_center_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [8]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cs_sold_date_sk#8] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [8]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cs_sold_date_sk#8] Condition : ((isnotnull(cs_ship_date_sk#1) AND isnotnull(cs_ship_addr_sk#2)) AND isnotnull(cs_call_center_sk#3)) -(4) Project [codegen id : 1] -Output [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] +(3) CometProject Input [8]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7, cs_sold_date_sk#8] +Arguments: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7], [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] + +(4) ColumnarToRow [codegen id : 1] +Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] (5) Exchange Input [7]: [cs_ship_date_sk#1, cs_ship_addr_sk#2, cs_call_center_sk#3, cs_warehouse_sk#4, cs_order_number#5, cs_ext_ship_cost#6, cs_net_profit#7] @@ -78,12 +78,12 @@ Batched: true Location [not included in comparison]/{warehouse_dir}/catalog_sales] ReadSchema: struct -(8) ColumnarToRow [codegen id : 3] +(8) CometProject Input [3]: [cs_warehouse_sk#9, cs_order_number#10, cs_sold_date_sk#11] +Arguments: [cs_warehouse_sk#9, cs_order_number#10], [cs_warehouse_sk#9, cs_order_number#10] -(9) Project [codegen id : 3] -Output [2]: [cs_warehouse_sk#9, cs_order_number#10] -Input [3]: [cs_warehouse_sk#9, cs_order_number#10, cs_sold_date_sk#11] +(9) ColumnarToRow [codegen id : 3] +Input [2]: [cs_warehouse_sk#9, cs_order_number#10] (10) Exchange Input [2]: [cs_warehouse_sk#9, cs_order_number#10] @@ -109,12 +109,12 @@ Batched: true Location [not included in comparison]/{warehouse_dir}/catalog_returns] ReadSchema: struct -(15) ColumnarToRow [codegen id : 6] +(15) CometProject Input [2]: [cr_order_number#12, cr_returned_date_sk#13] +Arguments: [cr_order_number#12], [cr_order_number#12] -(16) Project [codegen id : 6] -Output [1]: [cr_order_number#12] -Input [2]: [cr_order_number#12, cr_returned_date_sk#13] +(16) ColumnarToRow [codegen id : 6] +Input [1]: [cr_order_number#12] (17) Exchange Input [1]: [cr_order_number#12] @@ -137,16 +137,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2002-02-01), LessThanOrEqual(d_date,2002-04-02), IsNotNull(d_date_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 8] -Input [2]: [d_date_sk#14, d_date#15] - -(22) Filter [codegen id : 8] +(21) CometFilter Input [2]: [d_date_sk#14, d_date#15] Condition : (((isnotnull(d_date#15) AND (d_date#15 >= 2002-02-01)) AND (d_date#15 <= 2002-04-02)) AND isnotnull(d_date_sk#14)) -(23) Project [codegen id : 8] -Output [1]: [d_date_sk#14] +(22) CometProject Input [2]: [d_date_sk#14, d_date#15] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(23) ColumnarToRow [codegen id : 8] +Input [1]: [d_date_sk#14] (24) BroadcastExchange Input [1]: [d_date_sk#14] @@ -169,16 +169,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,GA), IsNotNull(ca_address_sk)] ReadSchema: struct -(28) ColumnarToRow [codegen id : 9] -Input [2]: [ca_address_sk#16, ca_state#17] - -(29) Filter [codegen id : 9] +(28) CometFilter Input [2]: [ca_address_sk#16, ca_state#17] Condition : ((isnotnull(ca_state#17) AND (ca_state#17 = GA)) AND isnotnull(ca_address_sk#16)) -(30) Project [codegen id : 9] -Output [1]: [ca_address_sk#16] +(29) CometProject Input [2]: [ca_address_sk#16, ca_state#17] +Arguments: [ca_address_sk#16], [ca_address_sk#16] + +(30) ColumnarToRow [codegen id : 9] +Input [1]: [ca_address_sk#16] (31) BroadcastExchange Input [1]: [ca_address_sk#16] @@ -201,16 +201,16 @@ Location [not included in comparison]/{warehouse_dir}/call_center] PushedFilters: [IsNotNull(cc_county), EqualTo(cc_county,Williamson County), IsNotNull(cc_call_center_sk)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 10] -Input [2]: [cc_call_center_sk#18, cc_county#19] - -(36) Filter [codegen id : 10] +(35) CometFilter Input [2]: [cc_call_center_sk#18, cc_county#19] Condition : ((isnotnull(cc_county#19) AND (cc_county#19 = Williamson County)) AND isnotnull(cc_call_center_sk#18)) -(37) Project [codegen id : 10] -Output [1]: [cc_call_center_sk#18] +(36) CometProject Input [2]: [cc_call_center_sk#18, cc_county#19] +Arguments: [cc_call_center_sk#18], [cc_call_center_sk#18] + +(37) ColumnarToRow [codegen id : 10] +Input [1]: [cc_call_center_sk#18] (38) BroadcastExchange Input [1]: [cc_call_center_sk#18] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt index 5feaa702a..a55c182be 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q16/simplified.txt @@ -23,10 +23,10 @@ WholeStageCodegen (12) InputAdapter Exchange [cs_order_number] #2 WholeStageCodegen (1) - Project [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk,cs_warehouse_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit] - Filter [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk,cs_warehouse_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit] + CometFilter [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_ship_addr_sk,cs_call_center_sk,cs_warehouse_sk,cs_order_number,cs_ext_ship_cost,cs_net_profit,cs_sold_date_sk] InputAdapter WholeStageCodegen (4) @@ -34,9 +34,9 @@ WholeStageCodegen (12) InputAdapter Exchange [cs_order_number] #3 WholeStageCodegen (3) - Project [cs_warehouse_sk,cs_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cs_warehouse_sk,cs_order_number] CometScan parquet spark_catalog.default.catalog_sales [cs_warehouse_sk,cs_order_number,cs_sold_date_sk] InputAdapter WholeStageCodegen (7) @@ -44,31 +44,31 @@ WholeStageCodegen (12) InputAdapter Exchange [cr_order_number] #4 WholeStageCodegen (6) - Project [cr_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cr_order_number] CometScan parquet spark_catalog.default.catalog_returns [cr_order_number,cr_returned_date_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (8) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #6 WholeStageCodegen (9) - Project [ca_address_sk] - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #7 WholeStageCodegen (10) - Project [cc_call_center_sk] - Filter [cc_county,cc_call_center_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cc_call_center_sk] + CometFilter [cc_county,cc_call_center_sk] CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_county] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt index 4548704d0..0de98cfb0 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/explain.txt @@ -17,27 +17,27 @@ TakeOrderedAndProject (40) : : : : : +- * BroadcastHashJoin Inner BuildRight (14) : : : : : :- * Project (9) : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : : : :- * Filter (3) - : : : : : : : +- * ColumnarToRow (2) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : : : +- BroadcastExchange (7) - : : : : : : +- * Filter (6) - : : : : : : +- * ColumnarToRow (5) + : : : : : : +- * ColumnarToRow (6) + : : : : : : +- CometFilter (5) : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) : : : : : +- BroadcastExchange (13) - : : : : : +- * Filter (12) - : : : : : +- * ColumnarToRow (11) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometFilter (11) : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (10) : : : : +- ReusedExchange (16) : : : +- ReusedExchange (19) : : +- ReusedExchange (22) : +- BroadcastExchange (28) - : +- * Filter (27) - : +- * ColumnarToRow (26) + : +- * ColumnarToRow (27) + : +- CometFilter (26) : +- CometScan parquet spark_catalog.default.store (25) +- BroadcastExchange (34) - +- * Filter (33) - +- * ColumnarToRow (32) + +- * ColumnarToRow (33) + +- CometFilter (32) +- CometScan parquet spark_catalog.default.item (31) @@ -49,12 +49,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 8] +(2) CometFilter Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) -(3) Filter [codegen id : 8] +(3) ColumnarToRow [codegen id : 8] Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] -Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) (4) Scan parquet spark_catalog.default.store_returns Output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] @@ -64,12 +64,12 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#12), dynamicpruningexpression(s PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] -Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) (7) BroadcastExchange Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] @@ -93,12 +93,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] -Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) (13) BroadcastExchange Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] @@ -160,12 +160,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 6] +(26) CometFilter Input [2]: [s_store_sk#22, s_state#23] +Condition : isnotnull(s_store_sk#22) -(27) Filter [codegen id : 6] +(27) ColumnarToRow [codegen id : 6] Input [2]: [s_store_sk#22, s_state#23] -Condition : isnotnull(s_store_sk#22) (28) BroadcastExchange Input [2]: [s_store_sk#22, s_state#23] @@ -188,12 +188,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(32) ColumnarToRow [codegen id : 7] +(32) CometFilter Input [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] +Condition : isnotnull(i_item_sk#24) -(33) Filter [codegen id : 7] +(33) ColumnarToRow [codegen id : 7] Input [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] -Condition : isnotnull(i_item_sk#24) (34) BroadcastExchange Input [3]: [i_item_sk#24, i_item_id#25, i_item_desc#26] @@ -235,9 +235,9 @@ Arguments: 100, [i_item_id#25 ASC NULLS FIRST, i_item_desc#26 ASC NULLS FIRST, s Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 BroadcastExchange (45) -+- * Project (44) - +- * Filter (43) - +- * ColumnarToRow (42) ++- * ColumnarToRow (44) + +- CometProject (43) + +- CometFilter (42) +- CometScan parquet spark_catalog.default.date_dim (41) @@ -248,16 +248,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_quarter_name), EqualTo(d_quarter_name,2001Q1), IsNotNull(d_date_sk)] ReadSchema: struct -(42) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#19, d_quarter_name#84] - -(43) Filter [codegen id : 1] +(42) CometFilter Input [2]: [d_date_sk#19, d_quarter_name#84] Condition : ((isnotnull(d_quarter_name#84) AND (d_quarter_name#84 = 2001Q1)) AND isnotnull(d_date_sk#19)) -(44) Project [codegen id : 1] -Output [1]: [d_date_sk#19] +(43) CometProject Input [2]: [d_date_sk#19, d_quarter_name#84] +Arguments: [d_date_sk#19], [d_date_sk#19] + +(44) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#19] (45) BroadcastExchange Input [1]: [d_date_sk#19] @@ -265,9 +265,9 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)) Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#12 IN dynamicpruning#13 BroadcastExchange (50) -+- * Project (49) - +- * Filter (48) - +- * ColumnarToRow (47) ++- * ColumnarToRow (49) + +- CometProject (48) + +- CometFilter (47) +- CometScan parquet spark_catalog.default.date_dim (46) @@ -278,16 +278,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [In(d_quarter_name, [2001Q1,2001Q2,2001Q3]), IsNotNull(d_date_sk)] ReadSchema: struct -(47) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#20, d_quarter_name#85] - -(48) Filter [codegen id : 1] +(47) CometFilter Input [2]: [d_date_sk#20, d_quarter_name#85] Condition : (d_quarter_name#85 IN (2001Q1,2001Q2,2001Q3) AND isnotnull(d_date_sk#20)) -(49) Project [codegen id : 1] -Output [1]: [d_date_sk#20] +(48) CometProject Input [2]: [d_date_sk#20, d_quarter_name#85] +Arguments: [d_date_sk#20], [d_date_sk#20] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#20] (50) BroadcastExchange Input [1]: [d_date_sk#20] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt index 2e1e780a7..9f4d67dec 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q17/simplified.txt @@ -19,39 +19,39 @@ TakeOrderedAndProject [i_item_id,i_item_desc,s_state,store_sales_quantitycount,s BroadcastHashJoin [sr_customer_sk,sr_item_sk,cs_bill_customer_sk,cs_item_sk] Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sold_date_sk,sr_item_sk,sr_customer_sk,sr_return_quantity,sr_returned_date_sk] BroadcastHashJoin [ss_customer_sk,ss_item_sk,ss_ticket_number,sr_customer_sk,sr_item_sk,sr_ticket_number] - Filter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_quantity,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_quarter_name,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_quarter_name,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_quarter_name] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [sr_customer_sk,sr_item_sk,sr_ticket_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sr_customer_sk,sr_item_sk,sr_ticket_number] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_return_quantity,sr_returned_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_quarter_name,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_quarter_name,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_quarter_name] InputAdapter BroadcastExchange #5 WholeStageCodegen (2) - Filter [cs_bill_customer_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter @@ -63,14 +63,14 @@ TakeOrderedAndProject [i_item_id,i_item_desc,s_state,store_sales_quantitycount,s InputAdapter BroadcastExchange #6 WholeStageCodegen (6) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_state] InputAdapter BroadcastExchange #7 WholeStageCodegen (7) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt index 34421b640..1e9c660c5 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/explain.txt @@ -16,31 +16,31 @@ TakeOrderedAndProject (43) : : : : +- * BroadcastHashJoin Inner BuildRight (16) : : : : :- * Project (10) : : : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : : : :- * Filter (3) - : : : : : : +- * ColumnarToRow (2) + : : : : : :- * ColumnarToRow (3) + : : : : : : +- CometFilter (2) : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : : : +- BroadcastExchange (8) - : : : : : +- * Project (7) - : : : : : +- * Filter (6) - : : : : : +- * ColumnarToRow (5) + : : : : : +- * ColumnarToRow (7) + : : : : : +- CometProject (6) + : : : : : +- CometFilter (5) : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) : : : : +- BroadcastExchange (15) - : : : : +- * Project (14) - : : : : +- * Filter (13) - : : : : +- * ColumnarToRow (12) + : : : : +- * ColumnarToRow (14) + : : : : +- CometProject (13) + : : : : +- CometFilter (12) : : : : +- CometScan parquet spark_catalog.default.customer (11) : : : +- BroadcastExchange (21) - : : : +- * Filter (20) - : : : +- * ColumnarToRow (19) + : : : +- * ColumnarToRow (20) + : : : +- CometFilter (19) : : : +- CometScan parquet spark_catalog.default.customer_demographics (18) : : +- BroadcastExchange (27) - : : +- * Filter (26) - : : +- * ColumnarToRow (25) + : : +- * ColumnarToRow (26) + : : +- CometFilter (25) : : +- CometScan parquet spark_catalog.default.customer_address (24) : +- ReusedExchange (30) +- BroadcastExchange (36) - +- * Filter (35) - +- * ColumnarToRow (34) + +- * ColumnarToRow (35) + +- CometFilter (34) +- CometScan parquet spark_catalog.default.item (33) @@ -52,12 +52,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#9), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 7] +(2) CometFilter Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] +Condition : ((isnotnull(cs_bill_cdemo_sk#2) AND isnotnull(cs_bill_customer_sk#1)) AND isnotnull(cs_item_sk#3)) -(3) Filter [codegen id : 7] +(3) ColumnarToRow [codegen id : 7] Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] -Condition : ((isnotnull(cs_bill_cdemo_sk#2) AND isnotnull(cs_bill_customer_sk#1)) AND isnotnull(cs_item_sk#3)) (4) Scan parquet spark_catalog.default.customer_demographics Output [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] @@ -66,16 +66,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_education_status), EqualTo(cd_gender,F), EqualTo(cd_education_status,Unknown ), IsNotNull(cd_demo_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] Condition : ((((isnotnull(cd_gender#12) AND isnotnull(cd_education_status#13)) AND (cd_gender#12 = F)) AND (cd_education_status#13 = Unknown )) AND isnotnull(cd_demo_sk#11)) -(7) Project [codegen id : 1] -Output [2]: [cd_demo_sk#11, cd_dep_count#14] +(6) CometProject Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Arguments: [cd_demo_sk#11, cd_dep_count#14], [cd_demo_sk#11, cd_dep_count#14] + +(7) ColumnarToRow [codegen id : 1] +Input [2]: [cd_demo_sk#11, cd_dep_count#14] (8) BroadcastExchange Input [2]: [cd_demo_sk#11, cd_dep_count#14] @@ -98,16 +98,16 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [In(c_birth_month, [1,12,2,6,8,9]), IsNotNull(c_customer_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] -Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] - -(13) Filter [codegen id : 2] +(12) CometFilter Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] Condition : (((c_birth_month#18 IN (1,6,8,9,12,2) AND isnotnull(c_customer_sk#15)) AND isnotnull(c_current_cdemo_sk#16)) AND isnotnull(c_current_addr_sk#17)) -(14) Project [codegen id : 2] -Output [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +(13) CometProject Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Arguments: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19], [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] + +(14) ColumnarToRow [codegen id : 2] +Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] (15) BroadcastExchange Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] @@ -130,12 +130,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk)] ReadSchema: struct -(19) ColumnarToRow [codegen id : 3] +(19) CometFilter Input [1]: [cd_demo_sk#20] +Condition : isnotnull(cd_demo_sk#20) -(20) Filter [codegen id : 3] +(20) ColumnarToRow [codegen id : 3] Input [1]: [cd_demo_sk#20] -Condition : isnotnull(cd_demo_sk#20) (21) BroadcastExchange Input [1]: [cd_demo_sk#20] @@ -158,12 +158,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [In(ca_state, [IN,MS,ND,NM,OK,VA]), IsNotNull(ca_address_sk)] ReadSchema: struct -(25) ColumnarToRow [codegen id : 4] +(25) CometFilter Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Condition : (ca_state#23 IN (MS,IN,ND,OK,NM,VA) AND isnotnull(ca_address_sk#21)) -(26) Filter [codegen id : 4] +(26) ColumnarToRow [codegen id : 4] Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] -Condition : (ca_state#23 IN (MS,IN,ND,OK,NM,VA) AND isnotnull(ca_address_sk#21)) (27) BroadcastExchange Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] @@ -199,12 +199,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(34) ColumnarToRow [codegen id : 6] +(34) CometFilter Input [2]: [i_item_sk#26, i_item_id#27] +Condition : isnotnull(i_item_sk#26) -(35) Filter [codegen id : 6] +(35) ColumnarToRow [codegen id : 6] Input [2]: [i_item_sk#26, i_item_id#27] -Condition : isnotnull(i_item_sk#26) (36) BroadcastExchange Input [2]: [i_item_sk#26, i_item_id#27] @@ -250,9 +250,9 @@ Arguments: 100, [ca_country#29 ASC NULLS FIRST, ca_state#30 ASC NULLS FIRST, ca_ Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#9 IN dynamicpruning#10 BroadcastExchange (48) -+- * Project (47) - +- * Filter (46) - +- * ColumnarToRow (45) ++- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) +- CometScan parquet spark_catalog.default.date_dim (44) @@ -263,16 +263,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1998), IsNotNull(d_date_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#25, d_year#75] - -(46) Filter [codegen id : 1] +(45) CometFilter Input [2]: [d_date_sk#25, d_year#75] Condition : ((isnotnull(d_year#75) AND (d_year#75 = 1998)) AND isnotnull(d_date_sk#25)) -(47) Project [codegen id : 1] -Output [1]: [d_date_sk#25] +(46) CometProject Input [2]: [d_date_sk#25, d_year#75] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(47) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] (48) BroadcastExchange Input [1]: [d_date_sk#25] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt index 723e30a44..47911b9ba 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q18/simplified.txt @@ -18,54 +18,54 @@ TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,ag BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] - Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [cd_demo_sk,cd_dep_count] - Filter [cd_gender,cd_education_status,cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk,cd_dep_count] + CometFilter [cd_gender,cd_education_status,cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_education_status,cd_dep_count] InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] - Filter [c_birth_month,c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + CometFilter [c_birth_month,c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_month,c_birth_year] InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk] InputAdapter BroadcastExchange #6 WholeStageCodegen (4) - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county,ca_state,ca_country] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #7 WholeStageCodegen (6) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt index 8a13a8dc7..999fec838 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/explain.txt @@ -13,30 +13,30 @@ TakeOrderedAndProject (39) : : : +- * BroadcastHashJoin Inner BuildRight (16) : : : :- * Project (10) : : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : : :- * Project (4) - : : : : : +- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.date_dim (1) : : : : +- BroadcastExchange (8) - : : : : +- * Filter (7) - : : : : +- * ColumnarToRow (6) + : : : : +- * ColumnarToRow (7) + : : : : +- CometFilter (6) : : : : +- CometScan parquet spark_catalog.default.store_sales (5) : : : +- BroadcastExchange (15) - : : : +- * Project (14) - : : : +- * Filter (13) - : : : +- * ColumnarToRow (12) + : : : +- * ColumnarToRow (14) + : : : +- CometProject (13) + : : : +- CometFilter (12) : : : +- CometScan parquet spark_catalog.default.item (11) : : +- BroadcastExchange (21) - : : +- * Filter (20) - : : +- * ColumnarToRow (19) + : : +- * ColumnarToRow (20) + : : +- CometFilter (19) : : +- CometScan parquet spark_catalog.default.customer (18) : +- BroadcastExchange (27) - : +- * Filter (26) - : +- * ColumnarToRow (25) + : +- * ColumnarToRow (26) + : +- CometFilter (25) : +- CometScan parquet spark_catalog.default.customer_address (24) +- BroadcastExchange (33) - +- * Filter (32) - +- * ColumnarToRow (31) + +- * ColumnarToRow (32) + +- CometFilter (31) +- CometScan parquet spark_catalog.default.store (30) @@ -47,16 +47,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,1998), IsNotNull(d_date_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 6] -Input [3]: [d_date_sk#1, d_year#2, d_moy#3] - -(3) Filter [codegen id : 6] +(2) CometFilter Input [3]: [d_date_sk#1, d_year#2, d_moy#3] Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 1998)) AND isnotnull(d_date_sk#1)) -(4) Project [codegen id : 6] -Output [1]: [d_date_sk#1] +(3) CometProject Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Arguments: [d_date_sk#1], [d_date_sk#1] + +(4) ColumnarToRow [codegen id : 6] +Input [1]: [d_date_sk#1] (5) Scan parquet spark_catalog.default.store_sales Output [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] @@ -66,12 +66,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(true)] PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] +(6) CometFilter Input [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_item_sk#4) AND isnotnull(ss_customer_sk#5)) AND isnotnull(ss_store_sk#6)) -(7) Filter [codegen id : 1] +(7) ColumnarToRow [codegen id : 1] Input [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] -Condition : ((isnotnull(ss_item_sk#4) AND isnotnull(ss_customer_sk#5)) AND isnotnull(ss_store_sk#6)) (8) BroadcastExchange Input [5]: [ss_item_sk#4, ss_customer_sk#5, ss_store_sk#6, ss_ext_sales_price#7, ss_sold_date_sk#8] @@ -94,16 +94,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,8), IsNotNull(i_item_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] -Input [6]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, i_manager_id#14] - -(13) Filter [codegen id : 2] +(12) CometFilter Input [6]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, i_manager_id#14] Condition : ((isnotnull(i_manager_id#14) AND (i_manager_id#14 = 8)) AND isnotnull(i_item_sk#9)) -(14) Project [codegen id : 2] -Output [5]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] +(13) CometProject Input [6]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13, i_manager_id#14] +Arguments: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13], [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] + +(14) ColumnarToRow [codegen id : 2] +Input [5]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] (15) BroadcastExchange Input [5]: [i_item_sk#9, i_brand_id#10, i_brand#11, i_manufact_id#12, i_manufact#13] @@ -126,12 +126,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(19) ColumnarToRow [codegen id : 3] +(19) CometFilter Input [2]: [c_customer_sk#15, c_current_addr_sk#16] +Condition : (isnotnull(c_customer_sk#15) AND isnotnull(c_current_addr_sk#16)) -(20) Filter [codegen id : 3] +(20) ColumnarToRow [codegen id : 3] Input [2]: [c_customer_sk#15, c_current_addr_sk#16] -Condition : (isnotnull(c_customer_sk#15) AND isnotnull(c_current_addr_sk#16)) (21) BroadcastExchange Input [2]: [c_customer_sk#15, c_current_addr_sk#16] @@ -154,12 +154,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_zip)] ReadSchema: struct -(25) ColumnarToRow [codegen id : 4] +(25) CometFilter Input [2]: [ca_address_sk#17, ca_zip#18] +Condition : (isnotnull(ca_address_sk#17) AND isnotnull(ca_zip#18)) -(26) Filter [codegen id : 4] +(26) ColumnarToRow [codegen id : 4] Input [2]: [ca_address_sk#17, ca_zip#18] -Condition : (isnotnull(ca_address_sk#17) AND isnotnull(ca_zip#18)) (27) BroadcastExchange Input [2]: [ca_address_sk#17, ca_zip#18] @@ -182,12 +182,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_zip), IsNotNull(s_store_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 5] +(31) CometFilter Input [2]: [s_store_sk#19, s_zip#20] +Condition : (isnotnull(s_zip#20) AND isnotnull(s_store_sk#19)) -(32) Filter [codegen id : 5] +(32) ColumnarToRow [codegen id : 5] Input [2]: [s_store_sk#19, s_zip#20] -Condition : (isnotnull(s_zip#20) AND isnotnull(s_store_sk#19)) (33) BroadcastExchange Input [2]: [s_store_sk#19, s_zip#20] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt index 85e4886d7..c2f5d1a87 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q19/simplified.txt @@ -15,44 +15,44 @@ TakeOrderedAndProject [ext_price,brand,brand_id,i_manufact_id,i_manufact] BroadcastHashJoin [ss_item_sk,i_item_sk] Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ext_sales_price] BroadcastHashJoin [d_date_sk,ss_sold_date_sk] - Project [d_date_sk] - Filter [d_moy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_item_sk,ss_customer_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_customer_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ext_sales_price,ss_sold_date_sk] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [i_item_sk,i_brand_id,i_brand,i_manufact_id,i_manufact] - Filter [i_manager_id,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_brand,i_manufact_id,i_manufact] + CometFilter [i_manager_id,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manufact_id,i_manufact,i_manager_id] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Filter [c_customer_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Filter [ca_address_sk,ca_zip] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_zip] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_zip] InputAdapter BroadcastExchange #6 WholeStageCodegen (5) - Filter [s_zip,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_zip,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_zip] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt index 4bfb19a38..1215adf3f 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/explain.txt @@ -1,41 +1,40 @@ == Physical Plan == -* Sort (37) -+- Exchange (36) - +- * Project (35) - +- * BroadcastHashJoin Inner BuildRight (34) - :- * Project (23) - : +- * BroadcastHashJoin Inner BuildRight (22) - : :- * HashAggregate (16) - : : +- Exchange (15) - : : +- * HashAggregate (14) - : : +- * Project (13) - : : +- * BroadcastHashJoin Inner BuildRight (12) - : : :- Union (7) - : : : :- * Project (3) - : : : : +- * ColumnarToRow (2) - : : : : +- CometScan parquet spark_catalog.default.web_sales (1) - : : : +- * Project (6) - : : : +- * ColumnarToRow (5) - : : : +- CometScan parquet spark_catalog.default.catalog_sales (4) - : : +- BroadcastExchange (11) - : : +- * Filter (10) - : : +- * ColumnarToRow (9) - : : +- CometScan parquet spark_catalog.default.date_dim (8) - : +- BroadcastExchange (21) - : +- * Project (20) - : +- * Filter (19) - : +- * ColumnarToRow (18) - : +- CometScan parquet spark_catalog.default.date_dim (17) - +- BroadcastExchange (33) - +- * Project (32) - +- * BroadcastHashJoin Inner BuildRight (31) - :- * HashAggregate (25) - : +- ReusedExchange (24) - +- BroadcastExchange (30) - +- * Project (29) - +- * Filter (28) - +- * ColumnarToRow (27) - +- CometScan parquet spark_catalog.default.date_dim (26) +* Sort (36) ++- Exchange (35) + +- * Project (34) + +- * BroadcastHashJoin Inner BuildRight (33) + :- * Project (22) + : +- * BroadcastHashJoin Inner BuildRight (21) + : :- * HashAggregate (15) + : : +- Exchange (14) + : : +- * HashAggregate (13) + : : +- * Project (12) + : : +- * BroadcastHashJoin Inner BuildRight (11) + : : :- * ColumnarToRow (6) + : : : +- CometUnion (5) + : : : :- CometProject (2) + : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : +- CometProject (4) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (3) + : : +- BroadcastExchange (10) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) + : : +- CometScan parquet spark_catalog.default.date_dim (7) + : +- BroadcastExchange (20) + : +- * ColumnarToRow (19) + : +- CometProject (18) + : +- CometFilter (17) + : +- CometScan parquet spark_catalog.default.date_dim (16) + +- BroadcastExchange (32) + +- * Project (31) + +- * BroadcastHashJoin Inner BuildRight (30) + :- * HashAggregate (24) + : +- ReusedExchange (23) + +- BroadcastExchange (29) + +- * ColumnarToRow (28) + +- CometProject (27) + +- CometFilter (26) + +- CometScan parquet spark_catalog.default.date_dim (25) (1) Scan parquet spark_catalog.default.web_sales @@ -45,168 +44,167 @@ Location: InMemoryFileIndex [] PartitionFilters: [isnotnull(ws_sold_date_sk#2)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] +(2) CometProject Input [2]: [ws_ext_sales_price#1, ws_sold_date_sk#2] +Arguments: [sold_date_sk#3, sales_price#4], [ws_sold_date_sk#2 AS sold_date_sk#3, ws_ext_sales_price#1 AS sales_price#4] -(3) Project [codegen id : 1] -Output [2]: [ws_sold_date_sk#2 AS sold_date_sk#3, ws_ext_sales_price#1 AS sales_price#4] -Input [2]: [ws_ext_sales_price#1, ws_sold_date_sk#2] - -(4) Scan parquet spark_catalog.default.catalog_sales +(3) Scan parquet spark_catalog.default.catalog_sales Output [2]: [cs_ext_sales_price#5, cs_sold_date_sk#6] Batched: true Location: InMemoryFileIndex [] PartitionFilters: [isnotnull(cs_sold_date_sk#6)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 2] +(4) CometProject Input [2]: [cs_ext_sales_price#5, cs_sold_date_sk#6] +Arguments: [sold_date_sk#7, sales_price#8], [cs_sold_date_sk#6 AS sold_date_sk#7, cs_ext_sales_price#5 AS sales_price#8] -(6) Project [codegen id : 2] -Output [2]: [cs_sold_date_sk#6 AS sold_date_sk#7, cs_ext_sales_price#5 AS sales_price#8] -Input [2]: [cs_ext_sales_price#5, cs_sold_date_sk#6] +(5) CometUnion +Child 0 Input [2]: [sold_date_sk#3, sales_price#4] +Child 1 Input [2]: [sold_date_sk#7, sales_price#8] -(7) Union +(6) ColumnarToRow [codegen id : 2] +Input [2]: [sold_date_sk#3, sales_price#4] -(8) Scan parquet spark_catalog.default.date_dim +(7) Scan parquet spark_catalog.default.date_dim Output [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date_sk), IsNotNull(d_week_seq)] ReadSchema: struct -(9) ColumnarToRow [codegen id : 3] +(8) CometFilter Input [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] +Condition : (isnotnull(d_date_sk#9) AND isnotnull(d_week_seq#10)) -(10) Filter [codegen id : 3] +(9) ColumnarToRow [codegen id : 1] Input [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] -Condition : (isnotnull(d_date_sk#9) AND isnotnull(d_week_seq#10)) -(11) BroadcastExchange +(10) BroadcastExchange Input [3]: [d_date_sk#9, d_week_seq#10, d_day_name#11] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] -(12) BroadcastHashJoin [codegen id : 4] +(11) BroadcastHashJoin [codegen id : 2] Left keys [1]: [sold_date_sk#3] Right keys [1]: [d_date_sk#9] Join type: Inner Join condition: None -(13) Project [codegen id : 4] +(12) Project [codegen id : 2] Output [3]: [sales_price#4, d_week_seq#10, d_day_name#11] Input [5]: [sold_date_sk#3, sales_price#4, d_date_sk#9, d_week_seq#10, d_day_name#11] -(14) HashAggregate [codegen id : 4] +(13) HashAggregate [codegen id : 2] Input [3]: [sales_price#4, d_week_seq#10, d_day_name#11] Keys [1]: [d_week_seq#10] Functions [7]: [partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))] Aggregate Attributes [7]: [sum#12, sum#13, sum#14, sum#15, sum#16, sum#17, sum#18] Results [8]: [d_week_seq#10, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24, sum#25] -(15) Exchange +(14) Exchange Input [8]: [d_week_seq#10, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24, sum#25] Arguments: hashpartitioning(d_week_seq#10, 5), ENSURE_REQUIREMENTS, [plan_id=2] -(16) HashAggregate [codegen id : 12] +(15) HashAggregate [codegen id : 8] Input [8]: [d_week_seq#10, sum#19, sum#20, sum#21, sum#22, sum#23, sum#24, sum#25] Keys [1]: [d_week_seq#10] Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END)), sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))] Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END))#27, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END))#28, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END))#29, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END))#30, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END))#31, sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))#32] Results [8]: [d_week_seq#10, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Sunday ) THEN sales_price#4 END))#26,17,2) AS sun_sales#33, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Monday ) THEN sales_price#4 END))#27,17,2) AS mon_sales#34, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Tuesday ) THEN sales_price#4 END))#28,17,2) AS tue_sales#35, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Wednesday) THEN sales_price#4 END))#29,17,2) AS wed_sales#36, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Thursday ) THEN sales_price#4 END))#30,17,2) AS thu_sales#37, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Friday ) THEN sales_price#4 END))#31,17,2) AS fri_sales#38, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#11 = Saturday ) THEN sales_price#4 END))#32,17,2) AS sat_sales#39] -(17) Scan parquet spark_catalog.default.date_dim +(16) Scan parquet spark_catalog.default.date_dim Output [2]: [d_week_seq#40, d_year#41] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_week_seq)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 5] -Input [2]: [d_week_seq#40, d_year#41] - -(19) Filter [codegen id : 5] +(17) CometFilter Input [2]: [d_week_seq#40, d_year#41] Condition : ((isnotnull(d_year#41) AND (d_year#41 = 2001)) AND isnotnull(d_week_seq#40)) -(20) Project [codegen id : 5] -Output [1]: [d_week_seq#40] +(18) CometProject Input [2]: [d_week_seq#40, d_year#41] +Arguments: [d_week_seq#40], [d_week_seq#40] -(21) BroadcastExchange +(19) ColumnarToRow [codegen id : 3] +Input [1]: [d_week_seq#40] + +(20) BroadcastExchange Input [1]: [d_week_seq#40] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3] -(22) BroadcastHashJoin [codegen id : 12] +(21) BroadcastHashJoin [codegen id : 8] Left keys [1]: [d_week_seq#10] Right keys [1]: [d_week_seq#40] Join type: Inner Join condition: None -(23) Project [codegen id : 12] +(22) Project [codegen id : 8] Output [8]: [d_week_seq#10 AS d_week_seq1#42, sun_sales#33 AS sun_sales1#43, mon_sales#34 AS mon_sales1#44, tue_sales#35 AS tue_sales1#45, wed_sales#36 AS wed_sales1#46, thu_sales#37 AS thu_sales1#47, fri_sales#38 AS fri_sales1#48, sat_sales#39 AS sat_sales1#49] Input [9]: [d_week_seq#10, sun_sales#33, mon_sales#34, tue_sales#35, wed_sales#36, thu_sales#37, fri_sales#38, sat_sales#39, d_week_seq#40] -(24) ReusedExchange [Reuses operator id: 15] +(23) ReusedExchange [Reuses operator id: 14] Output [8]: [d_week_seq#50, sum#51, sum#52, sum#53, sum#54, sum#55, sum#56, sum#57] -(25) HashAggregate [codegen id : 11] +(24) HashAggregate [codegen id : 7] Input [8]: [d_week_seq#50, sum#51, sum#52, sum#53, sum#54, sum#55, sum#56, sum#57] Keys [1]: [d_week_seq#50] Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#58 = Sunday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Monday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Tuesday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Wednesday) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Thursday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Friday ) THEN sales_price#59 END)), sum(UnscaledValue(CASE WHEN (d_day_name#58 = Saturday ) THEN sales_price#59 END))] Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#58 = Sunday ) THEN sales_price#59 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Monday ) THEN sales_price#59 END))#27, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Tuesday ) THEN sales_price#59 END))#28, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Wednesday) THEN sales_price#59 END))#29, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Thursday ) THEN sales_price#59 END))#30, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Friday ) THEN sales_price#59 END))#31, sum(UnscaledValue(CASE WHEN (d_day_name#58 = Saturday ) THEN sales_price#59 END))#32] Results [8]: [d_week_seq#50, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Sunday ) THEN sales_price#59 END))#26,17,2) AS sun_sales#60, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Monday ) THEN sales_price#59 END))#27,17,2) AS mon_sales#61, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Tuesday ) THEN sales_price#59 END))#28,17,2) AS tue_sales#62, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Wednesday) THEN sales_price#59 END))#29,17,2) AS wed_sales#63, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Thursday ) THEN sales_price#59 END))#30,17,2) AS thu_sales#64, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Friday ) THEN sales_price#59 END))#31,17,2) AS fri_sales#65, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#58 = Saturday ) THEN sales_price#59 END))#32,17,2) AS sat_sales#66] -(26) Scan parquet spark_catalog.default.date_dim +(25) Scan parquet spark_catalog.default.date_dim Output [2]: [d_week_seq#67, d_year#68] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_week_seq)] ReadSchema: struct -(27) ColumnarToRow [codegen id : 10] -Input [2]: [d_week_seq#67, d_year#68] - -(28) Filter [codegen id : 10] +(26) CometFilter Input [2]: [d_week_seq#67, d_year#68] Condition : ((isnotnull(d_year#68) AND (d_year#68 = 2002)) AND isnotnull(d_week_seq#67)) -(29) Project [codegen id : 10] -Output [1]: [d_week_seq#67] +(27) CometProject Input [2]: [d_week_seq#67, d_year#68] +Arguments: [d_week_seq#67], [d_week_seq#67] + +(28) ColumnarToRow [codegen id : 6] +Input [1]: [d_week_seq#67] -(30) BroadcastExchange +(29) BroadcastExchange Input [1]: [d_week_seq#67] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] -(31) BroadcastHashJoin [codegen id : 11] +(30) BroadcastHashJoin [codegen id : 7] Left keys [1]: [d_week_seq#50] Right keys [1]: [d_week_seq#67] Join type: Inner Join condition: None -(32) Project [codegen id : 11] +(31) Project [codegen id : 7] Output [8]: [d_week_seq#50 AS d_week_seq2#69, sun_sales#60 AS sun_sales2#70, mon_sales#61 AS mon_sales2#71, tue_sales#62 AS tue_sales2#72, wed_sales#63 AS wed_sales2#73, thu_sales#64 AS thu_sales2#74, fri_sales#65 AS fri_sales2#75, sat_sales#66 AS sat_sales2#76] Input [9]: [d_week_seq#50, sun_sales#60, mon_sales#61, tue_sales#62, wed_sales#63, thu_sales#64, fri_sales#65, sat_sales#66, d_week_seq#67] -(33) BroadcastExchange +(32) BroadcastExchange Input [8]: [d_week_seq2#69, sun_sales2#70, mon_sales2#71, tue_sales2#72, wed_sales2#73, thu_sales2#74, fri_sales2#75, sat_sales2#76] Arguments: HashedRelationBroadcastMode(List(cast((input[0, int, true] - 53) as bigint)),false), [plan_id=5] -(34) BroadcastHashJoin [codegen id : 12] +(33) BroadcastHashJoin [codegen id : 8] Left keys [1]: [d_week_seq1#42] Right keys [1]: [(d_week_seq2#69 - 53)] Join type: Inner Join condition: None -(35) Project [codegen id : 12] +(34) Project [codegen id : 8] Output [8]: [d_week_seq1#42, round((sun_sales1#43 / sun_sales2#70), 2) AS round((sun_sales1 / sun_sales2), 2)#77, round((mon_sales1#44 / mon_sales2#71), 2) AS round((mon_sales1 / mon_sales2), 2)#78, round((tue_sales1#45 / tue_sales2#72), 2) AS round((tue_sales1 / tue_sales2), 2)#79, round((wed_sales1#46 / wed_sales2#73), 2) AS round((wed_sales1 / wed_sales2), 2)#80, round((thu_sales1#47 / thu_sales2#74), 2) AS round((thu_sales1 / thu_sales2), 2)#81, round((fri_sales1#48 / fri_sales2#75), 2) AS round((fri_sales1 / fri_sales2), 2)#82, round((sat_sales1#49 / sat_sales2#76), 2) AS round((sat_sales1 / sat_sales2), 2)#83] Input [16]: [d_week_seq1#42, sun_sales1#43, mon_sales1#44, tue_sales1#45, wed_sales1#46, thu_sales1#47, fri_sales1#48, sat_sales1#49, d_week_seq2#69, sun_sales2#70, mon_sales2#71, tue_sales2#72, wed_sales2#73, thu_sales2#74, fri_sales2#75, sat_sales2#76] -(36) Exchange +(35) Exchange Input [8]: [d_week_seq1#42, round((sun_sales1 / sun_sales2), 2)#77, round((mon_sales1 / mon_sales2), 2)#78, round((tue_sales1 / tue_sales2), 2)#79, round((wed_sales1 / wed_sales2), 2)#80, round((thu_sales1 / thu_sales2), 2)#81, round((fri_sales1 / fri_sales2), 2)#82, round((sat_sales1 / sat_sales2), 2)#83] Arguments: rangepartitioning(d_week_seq1#42 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=6] -(37) Sort [codegen id : 13] +(36) Sort [codegen id : 9] Input [8]: [d_week_seq1#42, round((sun_sales1 / sun_sales2), 2)#77, round((mon_sales1 / mon_sales2), 2)#78, round((tue_sales1 / tue_sales2), 2)#79, round((wed_sales1 / wed_sales2), 2)#80, round((thu_sales1 / thu_sales2), 2)#81, round((fri_sales1 / fri_sales2), 2)#82, round((sat_sales1 / sat_sales2), 2)#83] Arguments: [d_week_seq1#42 ASC NULLS FIRST], true, 0 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt index 0008304e8..8856ce80d 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q2/simplified.txt @@ -1,8 +1,8 @@ -WholeStageCodegen (13) +WholeStageCodegen (9) Sort [d_week_seq1] InputAdapter Exchange [d_week_seq1] #1 - WholeStageCodegen (12) + WholeStageCodegen (8) Project [d_week_seq1,sun_sales1,sun_sales2,mon_sales1,mon_sales2,tue_sales1,tue_sales2,wed_sales1,wed_sales2,thu_sales1,thu_sales2,fri_sales1,fri_sales2,sat_sales1,sat_sales2] BroadcastHashJoin [d_week_seq1,d_week_seq2] Project [d_week_seq,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] @@ -10,40 +10,35 @@ WholeStageCodegen (13) HashAggregate [d_week_seq,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] InputAdapter Exchange [d_week_seq] #2 - WholeStageCodegen (4) + WholeStageCodegen (2) HashAggregate [d_week_seq,d_day_name,sales_price] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] Project [sales_price,d_week_seq,d_day_name] BroadcastHashJoin [sold_date_sk,d_date_sk] - InputAdapter - Union - WholeStageCodegen (1) - Project [ws_sold_date_sk,ws_ext_sales_price] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_sales [ws_ext_sales_price,ws_sold_date_sk] - WholeStageCodegen (2) - Project [cs_sold_date_sk,cs_ext_sales_price] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.catalog_sales [cs_ext_sales_price,cs_sold_date_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [ws_sold_date_sk,ws_ext_sales_price] [sold_date_sk,sales_price] + CometScan parquet spark_catalog.default.web_sales [ws_ext_sales_price,ws_sold_date_sk] + CometProject [cs_sold_date_sk,cs_ext_sales_price] [sold_date_sk,sales_price] + CometScan parquet spark_catalog.default.catalog_sales [cs_ext_sales_price,cs_sold_date_sk] InputAdapter BroadcastExchange #3 - WholeStageCodegen (3) - Filter [d_date_sk,d_week_seq] - ColumnarToRow - InputAdapter + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_date_sk,d_week_seq] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq,d_day_name] InputAdapter BroadcastExchange #4 - WholeStageCodegen (5) - Project [d_week_seq] - Filter [d_year,d_week_seq] - ColumnarToRow - InputAdapter + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_week_seq] CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year] InputAdapter BroadcastExchange #5 - WholeStageCodegen (11) + WholeStageCodegen (7) Project [d_week_seq,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales] BroadcastHashJoin [d_week_seq,d_week_seq] HashAggregate [d_week_seq,sum,sum,sum,sum,sum,sum,sum] [sum(UnscaledValue(CASE WHEN (d_day_name = Sunday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Monday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Tuesday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Wednesday) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Thursday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Friday ) THEN sales_price END)),sum(UnscaledValue(CASE WHEN (d_day_name = Saturday ) THEN sales_price END)),sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales,sum,sum,sum,sum,sum,sum,sum] @@ -51,9 +46,9 @@ WholeStageCodegen (13) ReusedExchange [d_week_seq,sum,sum,sum,sum,sum,sum,sum] #2 InputAdapter BroadcastExchange #6 - WholeStageCodegen (10) - Project [d_week_seq] - Filter [d_year,d_week_seq] - ColumnarToRow - InputAdapter + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_week_seq] CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt index f5455e62f..333ef218c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/explain.txt @@ -11,12 +11,12 @@ TakeOrderedAndProject (20) +- * BroadcastHashJoin Inner BuildRight (11) :- * Project (9) : +- * BroadcastHashJoin Inner BuildRight (8) - : :- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : +- BroadcastExchange (7) - : +- * Filter (6) - : +- * ColumnarToRow (5) + : +- * ColumnarToRow (6) + : +- CometFilter (5) : +- CometScan parquet spark_catalog.default.item (4) +- ReusedExchange (10) @@ -29,12 +29,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] +Condition : isnotnull(cs_item_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] -Condition : isnotnull(cs_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -43,12 +43,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] -Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) (7) BroadcastExchange Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -119,9 +119,9 @@ Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_ite Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (25) -+- * Project (24) - +- * Filter (23) - +- * ColumnarToRow (22) ++- * ColumnarToRow (24) + +- CometProject (23) + +- CometFilter (22) +- CometScan parquet spark_catalog.default.date_dim (21) @@ -132,16 +132,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] ReadSchema: struct -(22) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#11, d_date#19] - -(23) Filter [codegen id : 1] +(22) CometFilter Input [2]: [d_date_sk#11, d_date#19] Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) -(24) Project [codegen id : 1] -Output [1]: [d_date_sk#11] +(23) CometProject Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(24) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] (25) BroadcastExchange Input [1]: [d_date_sk#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt index fbbf149b5..52c42bdf2 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q20/simplified.txt @@ -17,24 +17,24 @@ TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_c BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_ext_sales_price,cs_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Filter [i_category,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] InputAdapter ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt index a5417a5b6..77f17c7f3 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/explain.txt @@ -10,17 +10,17 @@ TakeOrderedAndProject (24) : +- * BroadcastHashJoin Inner BuildRight (15) : :- * Project (9) : : +- * BroadcastHashJoin Inner BuildRight (8) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.inventory (1) : : +- BroadcastExchange (7) - : : +- * Filter (6) - : : +- * ColumnarToRow (5) + : : +- * ColumnarToRow (6) + : : +- CometFilter (5) : : +- CometScan parquet spark_catalog.default.warehouse (4) : +- BroadcastExchange (14) - : +- * Project (13) - : +- * Filter (12) - : +- * ColumnarToRow (11) + : +- * ColumnarToRow (13) + : +- CometProject (12) + : +- CometFilter (11) : +- CometScan parquet spark_catalog.default.item (10) +- ReusedExchange (17) @@ -33,12 +33,12 @@ PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_s PushedFilters: [IsNotNull(inv_warehouse_sk), IsNotNull(inv_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_warehouse_sk#2) AND isnotnull(inv_item_sk#1)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] -Condition : (isnotnull(inv_warehouse_sk#2) AND isnotnull(inv_item_sk#1)) (4) Scan parquet spark_catalog.default.warehouse Output [2]: [w_warehouse_sk#6, w_warehouse_name#7] @@ -47,12 +47,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Condition : isnotnull(w_warehouse_sk#6) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] -Condition : isnotnull(w_warehouse_sk#6) (7) BroadcastExchange Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] @@ -75,16 +75,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,0.99), LessThanOrEqual(i_current_price,1.49), IsNotNull(i_item_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] -Input [3]: [i_item_sk#8, i_item_id#9, i_current_price#10] - -(12) Filter [codegen id : 2] +(11) CometFilter Input [3]: [i_item_sk#8, i_item_id#9, i_current_price#10] Condition : (((isnotnull(i_current_price#10) AND (i_current_price#10 >= 0.99)) AND (i_current_price#10 <= 1.49)) AND isnotnull(i_item_sk#8)) -(13) Project [codegen id : 2] -Output [2]: [i_item_sk#8, i_item_id#9] +(12) CometProject Input [3]: [i_item_sk#8, i_item_id#9, i_current_price#10] +Arguments: [i_item_sk#8, i_item_id#9], [i_item_sk#8, i_item_id#9] + +(13) ColumnarToRow [codegen id : 2] +Input [2]: [i_item_sk#8, i_item_id#9] (14) BroadcastExchange Input [2]: [i_item_sk#8, i_item_id#9] @@ -143,8 +143,8 @@ Arguments: 100, [w_warehouse_name#7 ASC NULLS FIRST, i_item_id#9 ASC NULLS FIRST Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 BroadcastExchange (28) -+- * Filter (27) - +- * ColumnarToRow (26) ++- * ColumnarToRow (27) + +- CometFilter (26) +- CometScan parquet spark_catalog.default.date_dim (25) @@ -155,12 +155,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-02-10), LessThanOrEqual(d_date,2000-04-10), IsNotNull(d_date_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 1] +(26) CometFilter Input [2]: [d_date_sk#11, d_date#12] +Condition : (((isnotnull(d_date#12) AND (d_date#12 >= 2000-02-10)) AND (d_date#12 <= 2000-04-10)) AND isnotnull(d_date_sk#11)) -(27) Filter [codegen id : 1] +(27) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#11, d_date#12] -Condition : (((isnotnull(d_date#12) AND (d_date#12 >= 2000-02-10)) AND (d_date#12 <= 2000-04-10)) AND isnotnull(d_date_sk#11)) (28) BroadcastExchange Input [2]: [d_date_sk#11, d_date#12] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt index 912965257..e20755e12 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q21/simplified.txt @@ -12,31 +12,31 @@ TakeOrderedAndProject [w_warehouse_name,i_item_id,inv_before,inv_after] BroadcastHashJoin [inv_item_sk,i_item_sk] Project [inv_item_sk,inv_quantity_on_hand,inv_date_sk,w_warehouse_name] BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] - Filter [inv_warehouse_sk,inv_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [inv_warehouse_sk,inv_item_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [i_item_sk,i_item_id] - Filter [i_current_price,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_item_id] + CometFilter [i_current_price,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_current_price] InputAdapter ReusedExchange [d_date_sk,d_date] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt index c7f0a8f49..9f5771fed 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/explain.txt @@ -10,17 +10,17 @@ TakeOrderedAndProject (23) : +- * BroadcastHashJoin Inner BuildRight (11) : :- * Project (6) : : +- * BroadcastHashJoin Inner BuildRight (5) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.inventory (1) : : +- ReusedExchange (4) : +- BroadcastExchange (10) - : +- * Filter (9) - : +- * ColumnarToRow (8) + : +- * ColumnarToRow (9) + : +- CometFilter (8) : +- CometScan parquet spark_catalog.default.item (7) +- BroadcastExchange (16) - +- * Filter (15) - +- * ColumnarToRow (14) + +- * ColumnarToRow (15) + +- CometFilter (14) +- CometScan parquet spark_catalog.default.warehouse (13) @@ -32,12 +32,12 @@ PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_s PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] -Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) (4) ReusedExchange [Reuses operator id: 28] Output [1]: [d_date_sk#6] @@ -59,12 +59,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Condition : isnotnull(i_item_sk#7) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] -Condition : isnotnull(i_item_sk#7) (10) BroadcastExchange Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] @@ -87,12 +87,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [1]: [w_warehouse_sk#12] +Condition : isnotnull(w_warehouse_sk#12) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [1]: [w_warehouse_sk#12] -Condition : isnotnull(w_warehouse_sk#12) (16) BroadcastExchange Input [1]: [w_warehouse_sk#12] @@ -138,9 +138,9 @@ Arguments: 100, [qoh#23 ASC NULLS FIRST, i_product_name#13 ASC NULLS FIRST, i_br Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 BroadcastExchange (28) -+- * Project (27) - +- * Filter (26) - +- * ColumnarToRow (25) ++- * ColumnarToRow (27) + +- CometProject (26) + +- CometFilter (25) +- CometScan parquet spark_catalog.default.date_dim (24) @@ -151,16 +151,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(25) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#6, d_month_seq#24] - -(26) Filter [codegen id : 1] +(25) CometFilter Input [2]: [d_date_sk#6, d_month_seq#24] Condition : (((isnotnull(d_month_seq#24) AND (d_month_seq#24 >= 1200)) AND (d_month_seq#24 <= 1211)) AND isnotnull(d_date_sk#6)) -(27) Project [codegen id : 1] -Output [1]: [d_date_sk#6] +(26) CometProject Input [2]: [d_date_sk#6, d_month_seq#24] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(27) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] (28) BroadcastExchange Input [1]: [d_date_sk#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt index 495490277..92714bb02 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q22/simplified.txt @@ -12,31 +12,31 @@ TakeOrderedAndProject [qoh,i_product_name,i_brand,i_class,i_category] BroadcastHashJoin [inv_item_sk,i_item_sk] Project [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand] BroadcastHashJoin [inv_date_sk,d_date_sk] - Filter [inv_item_sk,inv_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt index 2f5140f7f..328a8d353 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/explain.txt @@ -23,13 +23,13 @@ : : : +- * BroadcastHashJoin Inner BuildRight (13) : : : :- * Project (8) : : : : +- * BroadcastHashJoin Inner BuildRight (7) - : : : : :- * Filter (5) - : : : : : +- * ColumnarToRow (4) + : : : : :- * ColumnarToRow (5) + : : : : : +- CometFilter (4) : : : : : +- CometScan parquet spark_catalog.default.store_sales (3) : : : : +- ReusedExchange (6) : : : +- BroadcastExchange (12) - : : : +- * Filter (11) - : : : +- * ColumnarToRow (10) + : : : +- * ColumnarToRow (11) + : : : +- CometFilter (10) : : : +- CometScan parquet spark_catalog.default.item (9) : : +- * Sort (40) : : +- * Project (39) @@ -39,13 +39,13 @@ : : +- * HashAggregate (35) : : +- * Project (34) : : +- * BroadcastHashJoin Inner BuildRight (33) - : : :- * Project (28) - : : : +- * Filter (27) - : : : +- * ColumnarToRow (26) + : : :- * ColumnarToRow (28) + : : : +- CometProject (27) + : : : +- CometFilter (26) : : : +- CometScan parquet spark_catalog.default.store_sales (25) : : +- BroadcastExchange (32) - : : +- * Filter (31) - : : +- * ColumnarToRow (30) + : : +- * ColumnarToRow (31) + : : +- CometFilter (30) : : +- CometScan parquet spark_catalog.default.customer (29) : +- ReusedExchange (43) +- * Project (62) @@ -85,12 +85,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(4) ColumnarToRow [codegen id : 3] +(4) CometFilter Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] +Condition : isnotnull(ss_item_sk#7) -(5) Filter [codegen id : 3] +(5) ColumnarToRow [codegen id : 3] Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] -Condition : isnotnull(ss_item_sk#7) (6) ReusedExchange [Reuses operator id: 76] Output [2]: [d_date_sk#10, d_date#11] @@ -112,12 +112,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(10) ColumnarToRow [codegen id : 2] +(10) CometFilter Input [2]: [i_item_sk#12, i_item_desc#13] +Condition : isnotnull(i_item_sk#12) -(11) Filter [codegen id : 2] +(11) ColumnarToRow [codegen id : 2] Input [2]: [i_item_sk#12, i_item_desc#13] -Condition : isnotnull(i_item_sk#12) (12) BroadcastExchange Input [2]: [i_item_sk#12, i_item_desc#13] @@ -188,16 +188,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 8] -Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] - -(27) Filter [codegen id : 8] +(26) CometFilter Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] Condition : isnotnull(ss_customer_sk#20) -(28) Project [codegen id : 8] -Output [3]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] +(27) CometProject Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Arguments: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22], [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] + +(28) ColumnarToRow [codegen id : 8] +Input [3]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] (29) Scan parquet spark_catalog.default.customer Output [1]: [c_customer_sk#24] @@ -206,12 +206,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 7] +(30) CometFilter Input [1]: [c_customer_sk#24] +Condition : isnotnull(c_customer_sk#24) -(31) Filter [codegen id : 7] +(31) ColumnarToRow [codegen id : 7] Input [1]: [c_customer_sk#24] -Condition : isnotnull(c_customer_sk#24) (32) BroadcastExchange Input [1]: [c_customer_sk#24] @@ -380,9 +380,9 @@ Results [1]: [sum(sales#34)#54 AS sum(sales)#55] Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (71) -+- * Project (70) - +- * Filter (69) - +- * ColumnarToRow (68) ++- * ColumnarToRow (70) + +- CometProject (69) + +- CometFilter (68) +- CometScan parquet spark_catalog.default.date_dim (67) @@ -393,16 +393,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,2), IsNotNull(d_date_sk)] ReadSchema: struct -(68) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#33, d_year#56, d_moy#57] - -(69) Filter [codegen id : 1] +(68) CometFilter Input [3]: [d_date_sk#33, d_year#56, d_moy#57] Condition : ((((isnotnull(d_year#56) AND isnotnull(d_moy#57)) AND (d_year#56 = 2000)) AND (d_moy#57 = 2)) AND isnotnull(d_date_sk#33)) -(70) Project [codegen id : 1] -Output [1]: [d_date_sk#33] +(69) CometProject Input [3]: [d_date_sk#33, d_year#56, d_moy#57] +Arguments: [d_date_sk#33], [d_date_sk#33] + +(70) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#33] (71) BroadcastExchange Input [1]: [d_date_sk#33] @@ -410,9 +410,9 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)) Subquery:2 Hosting operator id = 3 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (76) -+- * Project (75) - +- * Filter (74) - +- * ColumnarToRow (73) ++- * ColumnarToRow (75) + +- CometProject (74) + +- CometFilter (73) +- CometScan parquet spark_catalog.default.date_dim (72) @@ -423,16 +423,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] ReadSchema: struct -(73) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#10, d_date#11, d_year#58] - -(74) Filter [codegen id : 1] +(73) CometFilter Input [3]: [d_date_sk#10, d_date#11, d_year#58] Condition : (d_year#58 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#10)) -(75) Project [codegen id : 1] -Output [2]: [d_date_sk#10, d_date#11] +(74) CometProject Input [3]: [d_date_sk#10, d_date#11, d_year#58] +Arguments: [d_date_sk#10, d_date#11], [d_date_sk#10, d_date#11] + +(75) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#10, d_date#11] (76) BroadcastExchange Input [2]: [d_date_sk#10, d_date#11] @@ -449,8 +449,8 @@ Subquery:3 Hosting operator id = 38 Hosting Expression = Subquery scalar-subquer +- * BroadcastHashJoin Inner BuildRight (84) :- * Project (82) : +- * BroadcastHashJoin Inner BuildRight (81) - : :- * Filter (79) - : : +- * ColumnarToRow (78) + : :- * ColumnarToRow (79) + : : +- CometFilter (78) : : +- CometScan parquet spark_catalog.default.store_sales (77) : +- ReusedExchange (80) +- ReusedExchange (83) @@ -464,12 +464,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#62), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(78) ColumnarToRow [codegen id : 3] +(78) CometFilter Input [4]: [ss_customer_sk#59, ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62] +Condition : isnotnull(ss_customer_sk#59) -(79) Filter [codegen id : 3] +(79) ColumnarToRow [codegen id : 3] Input [4]: [ss_customer_sk#59, ss_quantity#60, ss_sales_price#61, ss_sold_date_sk#62] -Condition : isnotnull(ss_customer_sk#59) (80) ReusedExchange [Reuses operator id: 32] Output [1]: [c_customer_sk#64] @@ -535,9 +535,9 @@ Results [1]: [max(csales#71)#74 AS tpcds_cmax#75] Subquery:4 Hosting operator id = 77 Hosting Expression = ss_sold_date_sk#62 IN dynamicpruning#63 BroadcastExchange (96) -+- * Project (95) - +- * Filter (94) - +- * ColumnarToRow (93) ++- * ColumnarToRow (95) + +- CometProject (94) + +- CometFilter (93) +- CometScan parquet spark_catalog.default.date_dim (92) @@ -548,16 +548,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] ReadSchema: struct -(93) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#65, d_year#76] - -(94) Filter [codegen id : 1] +(93) CometFilter Input [2]: [d_date_sk#65, d_year#76] Condition : (d_year#76 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#65)) -(95) Project [codegen id : 1] -Output [1]: [d_date_sk#65] +(94) CometProject Input [2]: [d_date_sk#65, d_year#76] +Arguments: [d_date_sk#65], [d_date_sk#65] + +(95) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#65] (96) BroadcastExchange Input [1]: [d_date_sk#65] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt index 38098d6a6..0ec56d0e7 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23a/simplified.txt @@ -25,10 +25,10 @@ WholeStageCodegen (24) SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #4 @@ -44,26 +44,26 @@ WholeStageCodegen (24) BroadcastHashJoin [ss_item_sk,i_item_sk] Project [ss_item_sk,d_date] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #6 WholeStageCodegen (1) - Project [d_date_sk,d_date] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_year] InputAdapter ReusedExchange [d_date_sk,d_date] #6 InputAdapter BroadcastExchange #7 WholeStageCodegen (2) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] InputAdapter WholeStageCodegen (9) @@ -86,17 +86,17 @@ WholeStageCodegen (24) BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_quantity,ss_sales_price,ss_sold_date_sk,c_customer_sk] BroadcastHashJoin [ss_customer_sk,c_customer_sk] - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #4 BroadcastExchange #12 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [c_customer_sk] #9 @@ -109,17 +109,17 @@ WholeStageCodegen (24) HashAggregate [c_customer_sk,ss_quantity,ss_sales_price] [sum,isEmpty,sum,isEmpty] Project [ss_quantity,ss_sales_price,c_customer_sk] BroadcastHashJoin [ss_customer_sk,c_customer_sk] - Project [ss_customer_sk,ss_quantity,ss_sales_price] - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_customer_sk,ss_quantity,ss_sales_price] + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] InputAdapter BroadcastExchange #9 WholeStageCodegen (7) - Filter [c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk] InputAdapter ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt index 7ee05d453..840f9734a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/explain.txt @@ -13,8 +13,8 @@ TakeOrderedAndProject (87) : : : : +- Exchange (24) : : : : +- * Project (23) : : : : +- * BroadcastHashJoin LeftSemi BuildRight (22) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : : +- BroadcastExchange (21) : : : : +- * Project (20) @@ -26,13 +26,13 @@ TakeOrderedAndProject (87) : : : : +- * BroadcastHashJoin Inner BuildRight (14) : : : : :- * Project (9) : : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : : :- * Filter (6) - : : : : : : +- * ColumnarToRow (5) + : : : : : :- * ColumnarToRow (6) + : : : : : : +- CometFilter (5) : : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) : : : : : +- ReusedExchange (7) : : : : +- BroadcastExchange (13) - : : : : +- * Filter (12) - : : : : +- * ColumnarToRow (11) + : : : : +- * ColumnarToRow (12) + : : : : +- CometFilter (11) : : : : +- CometScan parquet spark_catalog.default.item (10) : : : +- * Sort (41) : : : +- * Project (40) @@ -42,20 +42,20 @@ TakeOrderedAndProject (87) : : : +- * HashAggregate (36) : : : +- * Project (35) : : : +- * BroadcastHashJoin Inner BuildRight (34) - : : : :- * Project (29) - : : : : +- * Filter (28) - : : : : +- * ColumnarToRow (27) + : : : :- * ColumnarToRow (29) + : : : : +- CometProject (28) + : : : : +- CometFilter (27) : : : : +- CometScan parquet spark_catalog.default.store_sales (26) : : : +- BroadcastExchange (33) - : : : +- * Filter (32) - : : : +- * ColumnarToRow (31) + : : : +- * ColumnarToRow (32) + : : : +- CometFilter (31) : : : +- CometScan parquet spark_catalog.default.customer (30) : : +- BroadcastExchange (54) : : +- * SortMergeJoin LeftSemi (53) : : :- * Sort (47) : : : +- Exchange (46) - : : : +- * Filter (45) - : : : +- * ColumnarToRow (44) + : : : +- * ColumnarToRow (45) + : : : +- CometFilter (44) : : : +- CometScan parquet spark_catalog.default.customer (43) : : +- * Sort (52) : : +- * Project (51) @@ -75,8 +75,8 @@ TakeOrderedAndProject (87) : : : +- Exchange (69) : : : +- * Project (68) : : : +- * BroadcastHashJoin LeftSemi BuildRight (67) - : : : :- * Filter (65) - : : : : +- * ColumnarToRow (64) + : : : :- * ColumnarToRow (65) + : : : : +- CometFilter (64) : : : : +- CometScan parquet spark_catalog.default.web_sales (63) : : : +- ReusedExchange (66) : : +- * Sort (75) @@ -96,12 +96,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_bill_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] +Condition : isnotnull(cs_bill_customer_sk#1) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [5]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_quantity#3, cs_list_price#4, cs_sold_date_sk#5] -Condition : isnotnull(cs_bill_customer_sk#1) (4) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_item_sk#7, ss_sold_date_sk#8] @@ -111,12 +111,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 3] +(5) CometFilter Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] +Condition : isnotnull(ss_item_sk#7) -(6) Filter [codegen id : 3] +(6) ColumnarToRow [codegen id : 3] Input [2]: [ss_item_sk#7, ss_sold_date_sk#8] -Condition : isnotnull(ss_item_sk#7) (7) ReusedExchange [Reuses operator id: 97] Output [2]: [d_date_sk#10, d_date#11] @@ -138,12 +138,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [2]: [i_item_sk#12, i_item_desc#13] +Condition : isnotnull(i_item_sk#12) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [2]: [i_item_sk#12, i_item_desc#13] -Condition : isnotnull(i_item_sk#12) (13) BroadcastExchange Input [2]: [i_item_sk#12, i_item_desc#13] @@ -214,16 +214,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(27) ColumnarToRow [codegen id : 8] -Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] - -(28) Filter [codegen id : 8] +(27) CometFilter Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] Condition : isnotnull(ss_customer_sk#20) -(29) Project [codegen id : 8] -Output [3]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] +(28) CometProject Input [4]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22, ss_sold_date_sk#23] +Arguments: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22], [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] + +(29) ColumnarToRow [codegen id : 8] +Input [3]: [ss_customer_sk#20, ss_quantity#21, ss_sales_price#22] (30) Scan parquet spark_catalog.default.customer Output [1]: [c_customer_sk#24] @@ -232,12 +232,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 7] +(31) CometFilter Input [1]: [c_customer_sk#24] +Condition : isnotnull(c_customer_sk#24) -(32) Filter [codegen id : 7] +(32) ColumnarToRow [codegen id : 7] Input [1]: [c_customer_sk#24] -Condition : isnotnull(c_customer_sk#24) (33) BroadcastExchange Input [1]: [c_customer_sk#24] @@ -296,12 +296,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk)] ReadSchema: struct -(44) ColumnarToRow [codegen id : 10] +(44) CometFilter Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] +Condition : isnotnull(c_customer_sk#33) -(45) Filter [codegen id : 10] +(45) ColumnarToRow [codegen id : 10] Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] -Condition : isnotnull(c_customer_sk#33) (46) Exchange Input [3]: [c_customer_sk#33, c_first_name#34, c_last_name#35] @@ -392,12 +392,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#47), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(64) ColumnarToRow [codegen id : 23] +(64) CometFilter Input [5]: [ws_item_sk#43, ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] +Condition : isnotnull(ws_bill_customer_sk#44) -(65) Filter [codegen id : 23] +(65) ColumnarToRow [codegen id : 23] Input [5]: [ws_item_sk#43, ws_bill_customer_sk#44, ws_quantity#45, ws_list_price#46, ws_sold_date_sk#47] -Condition : isnotnull(ws_bill_customer_sk#44) (66) ReusedExchange [Reuses operator id: 21] Output [1]: [item_sk#49] @@ -502,9 +502,9 @@ Arguments: 100, [c_last_name#35 ASC NULLS FIRST, c_first_name#34 ASC NULLS FIRST Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (92) -+- * Project (91) - +- * Filter (90) - +- * ColumnarToRow (89) ++- * ColumnarToRow (91) + +- CometProject (90) + +- CometFilter (89) +- CometScan parquet spark_catalog.default.date_dim (88) @@ -515,16 +515,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,2), IsNotNull(d_date_sk)] ReadSchema: struct -(89) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#36, d_year#66, d_moy#67] - -(90) Filter [codegen id : 1] +(89) CometFilter Input [3]: [d_date_sk#36, d_year#66, d_moy#67] Condition : ((((isnotnull(d_year#66) AND isnotnull(d_moy#67)) AND (d_year#66 = 2000)) AND (d_moy#67 = 2)) AND isnotnull(d_date_sk#36)) -(91) Project [codegen id : 1] -Output [1]: [d_date_sk#36] +(90) CometProject Input [3]: [d_date_sk#36, d_year#66, d_moy#67] +Arguments: [d_date_sk#36], [d_date_sk#36] + +(91) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#36] (92) BroadcastExchange Input [1]: [d_date_sk#36] @@ -532,9 +532,9 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)) Subquery:2 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (97) -+- * Project (96) - +- * Filter (95) - +- * ColumnarToRow (94) ++- * ColumnarToRow (96) + +- CometProject (95) + +- CometFilter (94) +- CometScan parquet spark_catalog.default.date_dim (93) @@ -545,16 +545,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] ReadSchema: struct -(94) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#10, d_date#11, d_year#68] - -(95) Filter [codegen id : 1] +(94) CometFilter Input [3]: [d_date_sk#10, d_date#11, d_year#68] Condition : (d_year#68 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#10)) -(96) Project [codegen id : 1] -Output [2]: [d_date_sk#10, d_date#11] +(95) CometProject Input [3]: [d_date_sk#10, d_date#11, d_year#68] +Arguments: [d_date_sk#10, d_date#11], [d_date_sk#10, d_date#11] + +(96) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#10, d_date#11] (97) BroadcastExchange Input [2]: [d_date_sk#10, d_date#11] @@ -571,8 +571,8 @@ Subquery:3 Hosting operator id = 39 Hosting Expression = Subquery scalar-subquer +- * BroadcastHashJoin Inner BuildRight (105) :- * Project (103) : +- * BroadcastHashJoin Inner BuildRight (102) - : :- * Filter (100) - : : +- * ColumnarToRow (99) + : :- * ColumnarToRow (100) + : : +- CometFilter (99) : : +- CometScan parquet spark_catalog.default.store_sales (98) : +- ReusedExchange (101) +- ReusedExchange (104) @@ -586,12 +586,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#72), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(99) ColumnarToRow [codegen id : 3] +(99) CometFilter Input [4]: [ss_customer_sk#69, ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72] +Condition : isnotnull(ss_customer_sk#69) -(100) Filter [codegen id : 3] +(100) ColumnarToRow [codegen id : 3] Input [4]: [ss_customer_sk#69, ss_quantity#70, ss_sales_price#71, ss_sold_date_sk#72] -Condition : isnotnull(ss_customer_sk#69) (101) ReusedExchange [Reuses operator id: 33] Output [1]: [c_customer_sk#74] @@ -657,9 +657,9 @@ Results [1]: [max(csales#81)#84 AS tpcds_cmax#85] Subquery:4 Hosting operator id = 98 Hosting Expression = ss_sold_date_sk#72 IN dynamicpruning#73 BroadcastExchange (117) -+- * Project (116) - +- * Filter (115) - +- * ColumnarToRow (114) ++- * ColumnarToRow (116) + +- CometProject (115) + +- CometFilter (114) +- CometScan parquet spark_catalog.default.date_dim (113) @@ -670,16 +670,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [In(d_year, [2000,2001,2002,2003]), IsNotNull(d_date_sk)] ReadSchema: struct -(114) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#75, d_year#86] - -(115) Filter [codegen id : 1] +(114) CometFilter Input [2]: [d_date_sk#75, d_year#86] Condition : (d_year#86 IN (2000,2001,2002,2003) AND isnotnull(d_date_sk#75)) -(116) Project [codegen id : 1] -Output [1]: [d_date_sk#75] +(115) CometProject Input [2]: [d_date_sk#75, d_year#86] +Arguments: [d_date_sk#75], [d_date_sk#75] + +(116) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#75] (117) BroadcastExchange Input [1]: [d_date_sk#75] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt index cfb8acd14..49ddeaef8 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q23b/simplified.txt @@ -19,17 +19,17 @@ TakeOrderedAndProject [c_last_name,c_first_name,sales] WholeStageCodegen (5) Project [cs_bill_customer_sk,cs_quantity,cs_list_price,cs_sold_date_sk] BroadcastHashJoin [cs_item_sk,item_sk] - Filter [cs_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #4 @@ -45,26 +45,26 @@ TakeOrderedAndProject [c_last_name,c_first_name,sales] BroadcastHashJoin [ss_item_sk,i_item_sk] Project [ss_item_sk,d_date] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #6 WholeStageCodegen (1) - Project [d_date_sk,d_date] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_year] InputAdapter ReusedExchange [d_date_sk,d_date] #6 InputAdapter BroadcastExchange #7 WholeStageCodegen (2) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] InputAdapter WholeStageCodegen (9) @@ -87,17 +87,17 @@ TakeOrderedAndProject [c_last_name,c_first_name,sales] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_quantity,ss_sales_price,ss_sold_date_sk,c_customer_sk] BroadcastHashJoin [ss_customer_sk,c_customer_sk] - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #4 BroadcastExchange #12 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [c_customer_sk] #9 @@ -110,17 +110,17 @@ TakeOrderedAndProject [c_last_name,c_first_name,sales] HashAggregate [c_customer_sk,ss_quantity,ss_sales_price] [sum,isEmpty,sum,isEmpty] Project [ss_quantity,ss_sales_price,c_customer_sk] BroadcastHashJoin [ss_customer_sk,c_customer_sk] - Project [ss_customer_sk,ss_quantity,ss_sales_price] - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_customer_sk,ss_quantity,ss_sales_price] + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] InputAdapter BroadcastExchange #9 WholeStageCodegen (7) - Filter [c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk] InputAdapter BroadcastExchange #13 @@ -132,9 +132,9 @@ TakeOrderedAndProject [c_last_name,c_first_name,sales] InputAdapter Exchange [c_customer_sk] #14 WholeStageCodegen (10) - Filter [c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] InputAdapter WholeStageCodegen (14) @@ -166,9 +166,9 @@ TakeOrderedAndProject [c_last_name,c_first_name,sales] WholeStageCodegen (23) Project [ws_bill_customer_sk,ws_quantity,ws_list_price,ws_sold_date_sk] BroadcastHashJoin [ws_item_sk,item_sk] - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_quantity,ws_list_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt index b27379f24..7241b5ea0 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/explain.txt @@ -18,32 +18,32 @@ : : : : +- * SortMergeJoin Inner (13) : : : : :- * Sort (6) : : : : : +- Exchange (5) - : : : : : +- * Project (4) - : : : : : +- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : +- * Sort (12) : : : : +- Exchange (11) - : : : : +- * Project (10) - : : : : +- * Filter (9) - : : : : +- * ColumnarToRow (8) + : : : : +- * ColumnarToRow (10) + : : : : +- CometProject (9) + : : : : +- CometFilter (8) : : : : +- CometScan parquet spark_catalog.default.store_returns (7) : : : +- BroadcastExchange (19) - : : : +- * Project (18) - : : : +- * Filter (17) - : : : +- * ColumnarToRow (16) + : : : +- * ColumnarToRow (18) + : : : +- CometProject (17) + : : : +- CometFilter (16) : : : +- CometScan parquet spark_catalog.default.store (15) : : +- BroadcastExchange (25) - : : +- * Filter (24) - : : +- * ColumnarToRow (23) + : : +- * ColumnarToRow (24) + : : +- CometFilter (23) : : +- CometScan parquet spark_catalog.default.item (22) : +- BroadcastExchange (31) - : +- * Filter (30) - : +- * ColumnarToRow (29) + : +- * ColumnarToRow (30) + : +- CometFilter (29) : +- CometScan parquet spark_catalog.default.customer (28) +- BroadcastExchange (37) - +- * Filter (36) - +- * ColumnarToRow (35) + +- * ColumnarToRow (36) + +- CometFilter (35) +- CometScan parquet spark_catalog.default.customer_address (34) @@ -54,16 +54,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_customer_sk#2)) -(4) Project [codegen id : 1] -Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +(3) CometProject Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5], [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] + +(4) ColumnarToRow [codegen id : 1] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] (5) Exchange Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] @@ -80,16 +80,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 3] -Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] - -(9) Filter [codegen id : 3] +(8) CometFilter Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] Condition : (isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#7)) -(10) Project [codegen id : 3] -Output [2]: [sr_item_sk#7, sr_ticket_number#8] +(9) CometProject Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Arguments: [sr_item_sk#7, sr_ticket_number#8], [sr_item_sk#7, sr_ticket_number#8] + +(10) ColumnarToRow [codegen id : 3] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] (11) Exchange Input [2]: [sr_item_sk#7, sr_ticket_number#8] @@ -116,16 +116,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_market_id), EqualTo(s_market_id,8), IsNotNull(s_store_sk), IsNotNull(s_zip)] ReadSchema: struct -(16) ColumnarToRow [codegen id : 5] -Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] - -(17) Filter [codegen id : 5] +(16) CometFilter Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] Condition : (((isnotnull(s_market_id#12) AND (s_market_id#12 = 8)) AND isnotnull(s_store_sk#10)) AND isnotnull(s_zip#14)) -(18) Project [codegen id : 5] -Output [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +(17) CometProject Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Arguments: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14], [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(18) ColumnarToRow [codegen id : 5] +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] (19) BroadcastExchange Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] @@ -148,12 +148,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_color), EqualTo(i_color,pale ), IsNotNull(i_item_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 6] +(23) CometFilter Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Condition : ((isnotnull(i_color#18) AND (i_color#18 = pale )) AND isnotnull(i_item_sk#15)) -(24) Filter [codegen id : 6] +(24) ColumnarToRow [codegen id : 6] Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] -Condition : ((isnotnull(i_color#18) AND (i_color#18 = pale )) AND isnotnull(i_item_sk#15)) (25) BroadcastExchange Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] @@ -176,12 +176,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_birth_country)] ReadSchema: struct -(29) ColumnarToRow [codegen id : 7] +(29) CometFilter Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_birth_country#24)) -(30) Filter [codegen id : 7] +(30) ColumnarToRow [codegen id : 7] Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] -Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_birth_country#24)) (31) BroadcastExchange Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] @@ -204,12 +204,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_country), IsNotNull(ca_zip)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 8] +(35) CometFilter Input [3]: [ca_state#25, ca_zip#26, ca_country#27] +Condition : (isnotnull(ca_country#27) AND isnotnull(ca_zip#26)) -(36) Filter [codegen id : 8] +(36) ColumnarToRow [codegen id : 8] Input [3]: [ca_state#25, ca_zip#26, ca_country#27] -Condition : (isnotnull(ca_country#27) AND isnotnull(ca_zip#26)) (37) BroadcastExchange Input [3]: [ca_state#25, ca_zip#26, ca_country#27] @@ -290,8 +290,8 @@ Subquery:1 Hosting operator id = 46 Hosting Expression = Subquery scalar-subquer : : : : +- ReusedExchange (49) : : : +- ReusedExchange (53) : : +- BroadcastExchange (59) - : : +- * Filter (58) - : : +- * ColumnarToRow (57) + : : +- * ColumnarToRow (58) + : : +- CometFilter (57) : : +- CometScan parquet spark_catalog.default.item (56) : +- ReusedExchange (62) +- ReusedExchange (65) @@ -341,12 +341,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(57) ColumnarToRow [codegen id : 6] +(57) CometFilter Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Condition : isnotnull(i_item_sk#51) -(58) Filter [codegen id : 6] +(58) ColumnarToRow [codegen id : 6] Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] -Condition : isnotnull(i_item_sk#51) (59) BroadcastExchange Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt index 4cdde1b6f..8ebd45fd1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24a/simplified.txt @@ -37,9 +37,9 @@ WholeStageCodegen (11) InputAdapter BroadcastExchange #11 WholeStageCodegen (6) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] InputAdapter ReusedExchange [c_customer_sk,c_first_name,c_last_name,c_birth_country] #7 @@ -71,10 +71,10 @@ WholeStageCodegen (11) InputAdapter Exchange [ss_ticket_number,ss_item_sk] #3 WholeStageCodegen (1) - Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] - Filter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] + CometFilter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid,ss_sold_date_sk] InputAdapter WholeStageCodegen (4) @@ -82,37 +82,37 @@ WholeStageCodegen (11) InputAdapter Exchange [sr_ticket_number,sr_item_sk] #4 WholeStageCodegen (3) - Project [sr_item_sk,sr_ticket_number] - Filter [sr_ticket_number,sr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_ticket_number,sr_item_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (5) - Project [s_store_sk,s_store_name,s_state,s_zip] - Filter [s_market_id,s_store_sk,s_zip] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk,s_store_name,s_state,s_zip] + CometFilter [s_market_id,s_store_sk,s_zip] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_market_id,s_state,s_zip] InputAdapter BroadcastExchange #6 WholeStageCodegen (6) - Filter [i_color,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_color,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] InputAdapter BroadcastExchange #7 WholeStageCodegen (7) - Filter [c_customer_sk,c_birth_country] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_birth_country] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name,c_birth_country] InputAdapter BroadcastExchange #8 WholeStageCodegen (8) - Filter [ca_country,ca_zip] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_country,ca_zip] CometScan parquet spark_catalog.default.customer_address [ca_state,ca_zip,ca_country] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt index a198578da..0ac5639b7 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/explain.txt @@ -18,32 +18,32 @@ : : : : +- * SortMergeJoin Inner (13) : : : : :- * Sort (6) : : : : : +- Exchange (5) - : : : : : +- * Project (4) - : : : : : +- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : +- * Sort (12) : : : : +- Exchange (11) - : : : : +- * Project (10) - : : : : +- * Filter (9) - : : : : +- * ColumnarToRow (8) + : : : : +- * ColumnarToRow (10) + : : : : +- CometProject (9) + : : : : +- CometFilter (8) : : : : +- CometScan parquet spark_catalog.default.store_returns (7) : : : +- BroadcastExchange (19) - : : : +- * Project (18) - : : : +- * Filter (17) - : : : +- * ColumnarToRow (16) + : : : +- * ColumnarToRow (18) + : : : +- CometProject (17) + : : : +- CometFilter (16) : : : +- CometScan parquet spark_catalog.default.store (15) : : +- BroadcastExchange (25) - : : +- * Filter (24) - : : +- * ColumnarToRow (23) + : : +- * ColumnarToRow (24) + : : +- CometFilter (23) : : +- CometScan parquet spark_catalog.default.item (22) : +- BroadcastExchange (31) - : +- * Filter (30) - : +- * ColumnarToRow (29) + : +- * ColumnarToRow (30) + : +- CometFilter (29) : +- CometScan parquet spark_catalog.default.customer (28) +- BroadcastExchange (37) - +- * Filter (36) - +- * ColumnarToRow (35) + +- * ColumnarToRow (36) + +- CometFilter (35) +- CometScan parquet spark_catalog.default.customer_address (34) @@ -54,16 +54,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_customer_sk#2)) -(4) Project [codegen id : 1] -Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +(3) CometProject Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5], [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] + +(4) ColumnarToRow [codegen id : 1] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] (5) Exchange Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] @@ -80,16 +80,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 3] -Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] - -(9) Filter [codegen id : 3] +(8) CometFilter Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] Condition : (isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#7)) -(10) Project [codegen id : 3] -Output [2]: [sr_item_sk#7, sr_ticket_number#8] +(9) CometProject Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Arguments: [sr_item_sk#7, sr_ticket_number#8], [sr_item_sk#7, sr_ticket_number#8] + +(10) ColumnarToRow [codegen id : 3] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] (11) Exchange Input [2]: [sr_item_sk#7, sr_ticket_number#8] @@ -116,16 +116,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_market_id), EqualTo(s_market_id,8), IsNotNull(s_store_sk), IsNotNull(s_zip)] ReadSchema: struct -(16) ColumnarToRow [codegen id : 5] -Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] - -(17) Filter [codegen id : 5] +(16) CometFilter Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] Condition : (((isnotnull(s_market_id#12) AND (s_market_id#12 = 8)) AND isnotnull(s_store_sk#10)) AND isnotnull(s_zip#14)) -(18) Project [codegen id : 5] -Output [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +(17) CometProject Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Arguments: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14], [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(18) ColumnarToRow [codegen id : 5] +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] (19) BroadcastExchange Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] @@ -148,12 +148,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_color), EqualTo(i_color,chiffon ), IsNotNull(i_item_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 6] +(23) CometFilter Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Condition : ((isnotnull(i_color#18) AND (i_color#18 = chiffon )) AND isnotnull(i_item_sk#15)) -(24) Filter [codegen id : 6] +(24) ColumnarToRow [codegen id : 6] Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] -Condition : ((isnotnull(i_color#18) AND (i_color#18 = chiffon )) AND isnotnull(i_item_sk#15)) (25) BroadcastExchange Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] @@ -176,12 +176,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_birth_country)] ReadSchema: struct -(29) ColumnarToRow [codegen id : 7] +(29) CometFilter Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_birth_country#24)) -(30) Filter [codegen id : 7] +(30) ColumnarToRow [codegen id : 7] Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] -Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_birth_country#24)) (31) BroadcastExchange Input [4]: [c_customer_sk#21, c_first_name#22, c_last_name#23, c_birth_country#24] @@ -204,12 +204,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_country), IsNotNull(ca_zip)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 8] +(35) CometFilter Input [3]: [ca_state#25, ca_zip#26, ca_country#27] +Condition : (isnotnull(ca_country#27) AND isnotnull(ca_zip#26)) -(36) Filter [codegen id : 8] +(36) ColumnarToRow [codegen id : 8] Input [3]: [ca_state#25, ca_zip#26, ca_country#27] -Condition : (isnotnull(ca_country#27) AND isnotnull(ca_zip#26)) (37) BroadcastExchange Input [3]: [ca_state#25, ca_zip#26, ca_country#27] @@ -290,8 +290,8 @@ Subquery:1 Hosting operator id = 46 Hosting Expression = Subquery scalar-subquer : : : : +- ReusedExchange (49) : : : +- ReusedExchange (53) : : +- BroadcastExchange (59) - : : +- * Filter (58) - : : +- * ColumnarToRow (57) + : : +- * ColumnarToRow (58) + : : +- CometFilter (57) : : +- CometScan parquet spark_catalog.default.item (56) : +- ReusedExchange (62) +- ReusedExchange (65) @@ -341,12 +341,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(57) ColumnarToRow [codegen id : 6] +(57) CometFilter Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] +Condition : isnotnull(i_item_sk#51) -(58) Filter [codegen id : 6] +(58) ColumnarToRow [codegen id : 6] Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] -Condition : isnotnull(i_item_sk#51) (59) BroadcastExchange Input [6]: [i_item_sk#51, i_current_price#52, i_size#53, i_color#54, i_units#55, i_manager_id#56] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt index 4cdde1b6f..8ebd45fd1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q24b/simplified.txt @@ -37,9 +37,9 @@ WholeStageCodegen (11) InputAdapter BroadcastExchange #11 WholeStageCodegen (6) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] InputAdapter ReusedExchange [c_customer_sk,c_first_name,c_last_name,c_birth_country] #7 @@ -71,10 +71,10 @@ WholeStageCodegen (11) InputAdapter Exchange [ss_ticket_number,ss_item_sk] #3 WholeStageCodegen (1) - Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] - Filter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] + CometFilter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid,ss_sold_date_sk] InputAdapter WholeStageCodegen (4) @@ -82,37 +82,37 @@ WholeStageCodegen (11) InputAdapter Exchange [sr_ticket_number,sr_item_sk] #4 WholeStageCodegen (3) - Project [sr_item_sk,sr_ticket_number] - Filter [sr_ticket_number,sr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_ticket_number,sr_item_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (5) - Project [s_store_sk,s_store_name,s_state,s_zip] - Filter [s_market_id,s_store_sk,s_zip] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk,s_store_name,s_state,s_zip] + CometFilter [s_market_id,s_store_sk,s_zip] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_market_id,s_state,s_zip] InputAdapter BroadcastExchange #6 WholeStageCodegen (6) - Filter [i_color,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_color,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] InputAdapter BroadcastExchange #7 WholeStageCodegen (7) - Filter [c_customer_sk,c_birth_country] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_birth_country] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name,c_birth_country] InputAdapter BroadcastExchange #8 WholeStageCodegen (8) - Filter [ca_country,ca_zip] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_country,ca_zip] CometScan parquet spark_catalog.default.customer_address [ca_state,ca_zip,ca_country] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt index f2e9a4eaf..2635546e4 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/explain.txt @@ -17,27 +17,27 @@ TakeOrderedAndProject (40) : : : : : +- * BroadcastHashJoin Inner BuildRight (14) : : : : : :- * Project (9) : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : : : :- * Filter (3) - : : : : : : : +- * ColumnarToRow (2) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : : : +- BroadcastExchange (7) - : : : : : : +- * Filter (6) - : : : : : : +- * ColumnarToRow (5) + : : : : : : +- * ColumnarToRow (6) + : : : : : : +- CometFilter (5) : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) : : : : : +- BroadcastExchange (13) - : : : : : +- * Filter (12) - : : : : : +- * ColumnarToRow (11) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometFilter (11) : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (10) : : : : +- ReusedExchange (16) : : : +- ReusedExchange (19) : : +- ReusedExchange (22) : +- BroadcastExchange (28) - : +- * Filter (27) - : +- * ColumnarToRow (26) + : +- * ColumnarToRow (27) + : +- CometFilter (26) : +- CometScan parquet spark_catalog.default.store (25) +- BroadcastExchange (34) - +- * Filter (33) - +- * ColumnarToRow (32) + +- * ColumnarToRow (33) + +- CometFilter (32) +- CometScan parquet spark_catalog.default.item (31) @@ -49,12 +49,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 8] +(2) CometFilter Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_profit#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) -(3) Filter [codegen id : 8] +(3) ColumnarToRow [codegen id : 8] Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_profit#5, ss_sold_date_sk#6] -Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) (4) Scan parquet spark_catalog.default.store_returns Output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] @@ -64,12 +64,12 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#12), dynamicpruningexpression(s PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] +Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] -Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) (7) BroadcastExchange Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_net_loss#11, sr_returned_date_sk#12] @@ -93,12 +93,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] -Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) (13) BroadcastExchange Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_net_profit#16, cs_sold_date_sk#17] @@ -160,12 +160,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 6] +(26) CometFilter Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Condition : isnotnull(s_store_sk#22) -(27) Filter [codegen id : 6] +(27) ColumnarToRow [codegen id : 6] Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] -Condition : isnotnull(s_store_sk#22) (28) BroadcastExchange Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] @@ -188,12 +188,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(32) ColumnarToRow [codegen id : 7] +(32) CometFilter Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Condition : isnotnull(i_item_sk#25) -(33) Filter [codegen id : 7] +(33) ColumnarToRow [codegen id : 7] Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] -Condition : isnotnull(i_item_sk#25) (34) BroadcastExchange Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] @@ -235,9 +235,9 @@ Arguments: 100, [i_item_id#26 ASC NULLS FIRST, i_item_desc#27 ASC NULLS FIRST, s Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 BroadcastExchange (45) -+- * Project (44) - +- * Filter (43) - +- * ColumnarToRow (42) ++- * ColumnarToRow (44) + +- CometProject (43) + +- CometFilter (42) +- CometScan parquet spark_catalog.default.date_dim (41) @@ -248,16 +248,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,4), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(42) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#19, d_year#40, d_moy#41] - -(43) Filter [codegen id : 1] +(42) CometFilter Input [3]: [d_date_sk#19, d_year#40, d_moy#41] Condition : ((((isnotnull(d_moy#41) AND isnotnull(d_year#40)) AND (d_moy#41 = 4)) AND (d_year#40 = 2001)) AND isnotnull(d_date_sk#19)) -(44) Project [codegen id : 1] -Output [1]: [d_date_sk#19] +(43) CometProject Input [3]: [d_date_sk#19, d_year#40, d_moy#41] +Arguments: [d_date_sk#19], [d_date_sk#19] + +(44) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#19] (45) BroadcastExchange Input [1]: [d_date_sk#19] @@ -265,9 +265,9 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)) Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#12 IN dynamicpruning#13 BroadcastExchange (50) -+- * Project (49) - +- * Filter (48) - +- * ColumnarToRow (47) ++- * ColumnarToRow (49) + +- CometProject (48) + +- CometFilter (47) +- CometScan parquet spark_catalog.default.date_dim (46) @@ -278,16 +278,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), GreaterThanOrEqual(d_moy,4), LessThanOrEqual(d_moy,10), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(47) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#20, d_year#42, d_moy#43] - -(48) Filter [codegen id : 1] +(47) CometFilter Input [3]: [d_date_sk#20, d_year#42, d_moy#43] Condition : (((((isnotnull(d_moy#43) AND isnotnull(d_year#42)) AND (d_moy#43 >= 4)) AND (d_moy#43 <= 10)) AND (d_year#42 = 2001)) AND isnotnull(d_date_sk#20)) -(49) Project [codegen id : 1] -Output [1]: [d_date_sk#20] +(48) CometProject Input [3]: [d_date_sk#20, d_year#42, d_moy#43] +Arguments: [d_date_sk#20], [d_date_sk#20] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#20] (50) BroadcastExchange Input [1]: [d_date_sk#20] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt index f45de0daf..eda7f6b64 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q25/simplified.txt @@ -19,39 +19,39 @@ TakeOrderedAndProject [i_item_id,i_item_desc,s_store_id,s_store_name,store_sales BroadcastHashJoin [sr_customer_sk,sr_item_sk,cs_bill_customer_sk,cs_item_sk] Project [ss_item_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk,sr_item_sk,sr_customer_sk,sr_net_loss,sr_returned_date_sk] BroadcastHashJoin [ss_customer_sk,ss_item_sk,ss_ticket_number,sr_customer_sk,sr_item_sk,sr_ticket_number] - Filter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_moy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [sr_customer_sk,sr_item_sk,sr_ticket_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sr_customer_sk,sr_item_sk,sr_ticket_number] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_net_loss,sr_returned_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_moy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #5 WholeStageCodegen (2) - Filter [cs_bill_customer_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_net_profit,cs_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter @@ -63,14 +63,14 @@ TakeOrderedAndProject [i_item_id,i_item_desc,s_store_id,s_store_name,store_sales InputAdapter BroadcastExchange #6 WholeStageCodegen (6) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name] InputAdapter BroadcastExchange #7 WholeStageCodegen (7) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt index 8782d99fb..c90dcd024 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/explain.txt @@ -11,23 +11,23 @@ TakeOrderedAndProject (30) : : +- * BroadcastHashJoin Inner BuildRight (12) : : :- * Project (10) : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : +- BroadcastExchange (8) - : : : +- * Project (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (7) + : : : +- CometProject (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) : : +- ReusedExchange (11) : +- BroadcastExchange (17) - : +- * Filter (16) - : +- * ColumnarToRow (15) + : +- * ColumnarToRow (16) + : +- CometFilter (15) : +- CometScan parquet spark_catalog.default.item (14) +- BroadcastExchange (24) - +- * Project (23) - +- * Filter (22) - +- * ColumnarToRow (21) + +- * ColumnarToRow (23) + +- CometProject (22) + +- CometFilter (21) +- CometScan parquet spark_catalog.default.promotion (20) @@ -39,12 +39,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#8), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_item_sk), IsNotNull(cs_promo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [8]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8] +Condition : ((isnotnull(cs_bill_cdemo_sk#1) AND isnotnull(cs_item_sk#2)) AND isnotnull(cs_promo_sk#3)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [8]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8] -Condition : ((isnotnull(cs_bill_cdemo_sk#1) AND isnotnull(cs_item_sk#2)) AND isnotnull(cs_promo_sk#3)) (4) Scan parquet spark_catalog.default.customer_demographics Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] @@ -53,16 +53,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#10)) -(7) Project [codegen id : 1] -Output [1]: [cd_demo_sk#10] +(6) CometProject Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Arguments: [cd_demo_sk#10], [cd_demo_sk#10] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [cd_demo_sk#10] (8) BroadcastExchange Input [1]: [cd_demo_sk#10] @@ -98,12 +98,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] +(15) CometFilter Input [2]: [i_item_sk#15, i_item_id#16] +Condition : isnotnull(i_item_sk#15) -(16) Filter [codegen id : 3] +(16) ColumnarToRow [codegen id : 3] Input [2]: [i_item_sk#15, i_item_id#16] -Condition : isnotnull(i_item_sk#15) (17) BroadcastExchange Input [2]: [i_item_sk#15, i_item_id#16] @@ -126,16 +126,16 @@ Location [not included in comparison]/{warehouse_dir}/promotion] PushedFilters: [Or(EqualTo(p_channel_email,N),EqualTo(p_channel_event,N)), IsNotNull(p_promo_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] -Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] - -(22) Filter [codegen id : 4] +(21) CometFilter Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] Condition : (((p_channel_email#18 = N) OR (p_channel_event#19 = N)) AND isnotnull(p_promo_sk#17)) -(23) Project [codegen id : 4] -Output [1]: [p_promo_sk#17] +(22) CometProject Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Arguments: [p_promo_sk#17], [p_promo_sk#17] + +(23) ColumnarToRow [codegen id : 4] +Input [1]: [p_promo_sk#17] (24) BroadcastExchange Input [1]: [p_promo_sk#17] @@ -177,9 +177,9 @@ Arguments: 100, [i_item_id#16 ASC NULLS FIRST], [i_item_id#16, agg1#40, agg2#41, Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (35) -+- * Project (34) - +- * Filter (33) - +- * ColumnarToRow (32) ++- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) +- CometScan parquet spark_catalog.default.date_dim (31) @@ -190,16 +190,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(32) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#14, d_year#44] - -(33) Filter [codegen id : 1] +(32) CometFilter Input [2]: [d_date_sk#14, d_year#44] Condition : ((isnotnull(d_year#44) AND (d_year#44 = 2000)) AND isnotnull(d_date_sk#14)) -(34) Project [codegen id : 1] -Output [1]: [d_date_sk#14] +(33) CometProject Input [2]: [d_date_sk#14, d_year#44] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(34) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] (35) BroadcastExchange Input [1]: [d_date_sk#14] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt index 41f3e4a7a..7d3893624 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q26/simplified.txt @@ -13,40 +13,40 @@ TakeOrderedAndProject [i_item_id,agg1,agg2,agg3,agg4] BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_item_sk,cs_promo_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_sold_date_sk] BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] - Filter [cs_bill_cdemo_sk,cs_item_sk,cs_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_item_sk,cs_promo_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_cdemo_sk,cs_item_sk,cs_promo_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [cd_demo_sk] - Filter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Project [p_promo_sk] - Filter [p_channel_email,p_channel_event,p_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [p_promo_sk] + CometFilter [p_channel_email,p_channel_event,p_promo_sk] CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_email,p_channel_event] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt index 6c2819610..e41077ed3 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/explain.txt @@ -12,22 +12,22 @@ TakeOrderedAndProject (30) : : +- * BroadcastHashJoin Inner BuildRight (12) : : :- * Project (10) : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- BroadcastExchange (8) - : : : +- * Project (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (7) + : : : +- CometProject (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) : : +- ReusedExchange (11) : +- BroadcastExchange (17) - : +- * Filter (16) - : +- * ColumnarToRow (15) + : +- * ColumnarToRow (16) + : +- CometFilter (15) : +- CometScan parquet spark_catalog.default.store (14) +- BroadcastExchange (23) - +- * Filter (22) - +- * ColumnarToRow (21) + +- * ColumnarToRow (22) + +- CometFilter (21) +- CometScan parquet spark_catalog.default.item (20) @@ -39,12 +39,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_item_sk#1)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] -Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_item_sk#1)) (4) Scan parquet spark_catalog.default.customer_demographics Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] @@ -53,16 +53,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#10)) -(7) Project [codegen id : 1] -Output [1]: [cd_demo_sk#10] +(6) CometProject Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Arguments: [cd_demo_sk#10], [cd_demo_sk#10] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [cd_demo_sk#10] (8) BroadcastExchange Input [1]: [cd_demo_sk#10] @@ -98,12 +98,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] +(15) CometFilter Input [2]: [s_store_sk#15, s_state#16] +Condition : ((isnotnull(s_state#16) AND (s_state#16 = TN)) AND isnotnull(s_store_sk#15)) -(16) Filter [codegen id : 3] +(16) ColumnarToRow [codegen id : 3] Input [2]: [s_store_sk#15, s_state#16] -Condition : ((isnotnull(s_state#16) AND (s_state#16 = TN)) AND isnotnull(s_store_sk#15)) (17) BroadcastExchange Input [2]: [s_store_sk#15, s_state#16] @@ -126,12 +126,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] +(21) CometFilter Input [2]: [i_item_sk#17, i_item_id#18] +Condition : isnotnull(i_item_sk#17) -(22) Filter [codegen id : 4] +(22) ColumnarToRow [codegen id : 4] Input [2]: [i_item_sk#17, i_item_id#18] -Condition : isnotnull(i_item_sk#17) (23) BroadcastExchange Input [2]: [i_item_sk#17, i_item_id#18] @@ -177,9 +177,9 @@ Arguments: 100, [i_item_id#19 ASC NULLS FIRST, s_state#20 ASC NULLS FIRST], [i_i Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (35) -+- * Project (34) - +- * Filter (33) - +- * ColumnarToRow (32) ++- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) +- CometScan parquet spark_catalog.default.date_dim (31) @@ -190,16 +190,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] ReadSchema: struct -(32) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#14, d_year#47] - -(33) Filter [codegen id : 1] +(32) CometFilter Input [2]: [d_date_sk#14, d_year#47] Condition : ((isnotnull(d_year#47) AND (d_year#47 = 2002)) AND isnotnull(d_date_sk#14)) -(34) Project [codegen id : 1] -Output [1]: [d_date_sk#14] +(33) CometProject Input [2]: [d_date_sk#14, d_year#47] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(34) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] (35) BroadcastExchange Input [1]: [d_date_sk#14] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt index 9cecdee29..9d073ff67 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q27/simplified.txt @@ -14,39 +14,39 @@ TakeOrderedAndProject [i_item_id,s_state,g_state,agg1,agg2,agg3,agg4] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] - Filter [ss_cdemo_sk,ss_store_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_cdemo_sk,ss_store_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [cd_demo_sk] - Filter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Filter [s_state,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_state,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_state] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt index ccab165e2..de4ab3a2c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/explain.txt @@ -10,9 +10,9 @@ : : : : : +- * HashAggregate (7) : : : : : +- Exchange (6) : : : : : +- * HashAggregate (5) -: : : : : +- * Project (4) -: : : : : +- * Filter (3) -: : : : : +- * ColumnarToRow (2) +: : : : : +- * ColumnarToRow (4) +: : : : : +- CometProject (3) +: : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : +- BroadcastExchange (21) : : : : +- * HashAggregate (20) @@ -21,9 +21,9 @@ : : : : +- * HashAggregate (17) : : : : +- Exchange (16) : : : : +- * HashAggregate (15) -: : : : +- * Project (14) -: : : : +- * Filter (13) -: : : : +- * ColumnarToRow (12) +: : : : +- * ColumnarToRow (14) +: : : : +- CometProject (13) +: : : : +- CometFilter (12) : : : : +- CometScan parquet spark_catalog.default.store_sales (11) : : : +- BroadcastExchange (33) : : : +- * HashAggregate (32) @@ -32,9 +32,9 @@ : : : +- * HashAggregate (29) : : : +- Exchange (28) : : : +- * HashAggregate (27) -: : : +- * Project (26) -: : : +- * Filter (25) -: : : +- * ColumnarToRow (24) +: : : +- * ColumnarToRow (26) +: : : +- CometProject (25) +: : : +- CometFilter (24) : : : +- CometScan parquet spark_catalog.default.store_sales (23) : : +- BroadcastExchange (45) : : +- * HashAggregate (44) @@ -43,9 +43,9 @@ : : +- * HashAggregate (41) : : +- Exchange (40) : : +- * HashAggregate (39) -: : +- * Project (38) -: : +- * Filter (37) -: : +- * ColumnarToRow (36) +: : +- * ColumnarToRow (38) +: : +- CometProject (37) +: : +- CometFilter (36) : : +- CometScan parquet spark_catalog.default.store_sales (35) : +- BroadcastExchange (57) : +- * HashAggregate (56) @@ -54,9 +54,9 @@ : +- * HashAggregate (53) : +- Exchange (52) : +- * HashAggregate (51) -: +- * Project (50) -: +- * Filter (49) -: +- * ColumnarToRow (48) +: +- * ColumnarToRow (50) +: +- CometProject (49) +: +- CometFilter (48) : +- CometScan parquet spark_catalog.default.store_sales (47) +- BroadcastExchange (69) +- * HashAggregate (68) @@ -65,9 +65,9 @@ +- * HashAggregate (65) +- Exchange (64) +- * HashAggregate (63) - +- * Project (62) - +- * Filter (61) - +- * ColumnarToRow (60) + +- * ColumnarToRow (62) + +- CometProject (61) + +- CometFilter (60) +- CometScan parquet spark_catalog.default.store_sales (59) @@ -78,16 +78,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,0), LessThanOrEqual(ss_quantity,5), Or(Or(And(GreaterThanOrEqual(ss_list_price,8.00),LessThanOrEqual(ss_list_price,18.00)),And(GreaterThanOrEqual(ss_coupon_amt,459.00),LessThanOrEqual(ss_coupon_amt,1459.00))),And(GreaterThanOrEqual(ss_wholesale_cost,57.00),LessThanOrEqual(ss_wholesale_cost,77.00)))] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [5]: [ss_quantity#1, ss_wholesale_cost#2, ss_list_price#3, ss_coupon_amt#4, ss_sold_date_sk#5] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [5]: [ss_quantity#1, ss_wholesale_cost#2, ss_list_price#3, ss_coupon_amt#4, ss_sold_date_sk#5] Condition : (((isnotnull(ss_quantity#1) AND (ss_quantity#1 >= 0)) AND (ss_quantity#1 <= 5)) AND ((((ss_list_price#3 >= 8.00) AND (ss_list_price#3 <= 18.00)) OR ((ss_coupon_amt#4 >= 459.00) AND (ss_coupon_amt#4 <= 1459.00))) OR ((ss_wholesale_cost#2 >= 57.00) AND (ss_wholesale_cost#2 <= 77.00)))) -(4) Project [codegen id : 1] -Output [1]: [ss_list_price#3] +(3) CometProject Input [5]: [ss_quantity#1, ss_wholesale_cost#2, ss_list_price#3, ss_coupon_amt#4, ss_sold_date_sk#5] +Arguments: [ss_list_price#3], [ss_list_price#3] + +(4) ColumnarToRow [codegen id : 1] +Input [1]: [ss_list_price#3] (5) HashAggregate [codegen id : 1] Input [1]: [ss_list_price#3] @@ -132,16 +132,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,6), LessThanOrEqual(ss_quantity,10), Or(Or(And(GreaterThanOrEqual(ss_list_price,90.00),LessThanOrEqual(ss_list_price,100.00)),And(GreaterThanOrEqual(ss_coupon_amt,2323.00),LessThanOrEqual(ss_coupon_amt,3323.00))),And(GreaterThanOrEqual(ss_wholesale_cost,31.00),LessThanOrEqual(ss_wholesale_cost,51.00)))] ReadSchema: struct -(12) ColumnarToRow [codegen id : 3] -Input [5]: [ss_quantity#16, ss_wholesale_cost#17, ss_list_price#18, ss_coupon_amt#19, ss_sold_date_sk#20] - -(13) Filter [codegen id : 3] +(12) CometFilter Input [5]: [ss_quantity#16, ss_wholesale_cost#17, ss_list_price#18, ss_coupon_amt#19, ss_sold_date_sk#20] Condition : (((isnotnull(ss_quantity#16) AND (ss_quantity#16 >= 6)) AND (ss_quantity#16 <= 10)) AND ((((ss_list_price#18 >= 90.00) AND (ss_list_price#18 <= 100.00)) OR ((ss_coupon_amt#19 >= 2323.00) AND (ss_coupon_amt#19 <= 3323.00))) OR ((ss_wholesale_cost#17 >= 31.00) AND (ss_wholesale_cost#17 <= 51.00)))) -(14) Project [codegen id : 3] -Output [1]: [ss_list_price#18] +(13) CometProject Input [5]: [ss_quantity#16, ss_wholesale_cost#17, ss_list_price#18, ss_coupon_amt#19, ss_sold_date_sk#20] +Arguments: [ss_list_price#18], [ss_list_price#18] + +(14) ColumnarToRow [codegen id : 3] +Input [1]: [ss_list_price#18] (15) HashAggregate [codegen id : 3] Input [1]: [ss_list_price#18] @@ -194,16 +194,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,11), LessThanOrEqual(ss_quantity,15), Or(Or(And(GreaterThanOrEqual(ss_list_price,142.00),LessThanOrEqual(ss_list_price,152.00)),And(GreaterThanOrEqual(ss_coupon_amt,12214.00),LessThanOrEqual(ss_coupon_amt,13214.00))),And(GreaterThanOrEqual(ss_wholesale_cost,79.00),LessThanOrEqual(ss_wholesale_cost,99.00)))] ReadSchema: struct -(24) ColumnarToRow [codegen id : 6] -Input [5]: [ss_quantity#31, ss_wholesale_cost#32, ss_list_price#33, ss_coupon_amt#34, ss_sold_date_sk#35] - -(25) Filter [codegen id : 6] +(24) CometFilter Input [5]: [ss_quantity#31, ss_wholesale_cost#32, ss_list_price#33, ss_coupon_amt#34, ss_sold_date_sk#35] Condition : (((isnotnull(ss_quantity#31) AND (ss_quantity#31 >= 11)) AND (ss_quantity#31 <= 15)) AND ((((ss_list_price#33 >= 142.00) AND (ss_list_price#33 <= 152.00)) OR ((ss_coupon_amt#34 >= 12214.00) AND (ss_coupon_amt#34 <= 13214.00))) OR ((ss_wholesale_cost#32 >= 79.00) AND (ss_wholesale_cost#32 <= 99.00)))) -(26) Project [codegen id : 6] -Output [1]: [ss_list_price#33] +(25) CometProject Input [5]: [ss_quantity#31, ss_wholesale_cost#32, ss_list_price#33, ss_coupon_amt#34, ss_sold_date_sk#35] +Arguments: [ss_list_price#33], [ss_list_price#33] + +(26) ColumnarToRow [codegen id : 6] +Input [1]: [ss_list_price#33] (27) HashAggregate [codegen id : 6] Input [1]: [ss_list_price#33] @@ -256,16 +256,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,16), LessThanOrEqual(ss_quantity,20), Or(Or(And(GreaterThanOrEqual(ss_list_price,135.00),LessThanOrEqual(ss_list_price,145.00)),And(GreaterThanOrEqual(ss_coupon_amt,6071.00),LessThanOrEqual(ss_coupon_amt,7071.00))),And(GreaterThanOrEqual(ss_wholesale_cost,38.00),LessThanOrEqual(ss_wholesale_cost,58.00)))] ReadSchema: struct -(36) ColumnarToRow [codegen id : 9] -Input [5]: [ss_quantity#46, ss_wholesale_cost#47, ss_list_price#48, ss_coupon_amt#49, ss_sold_date_sk#50] - -(37) Filter [codegen id : 9] +(36) CometFilter Input [5]: [ss_quantity#46, ss_wholesale_cost#47, ss_list_price#48, ss_coupon_amt#49, ss_sold_date_sk#50] Condition : (((isnotnull(ss_quantity#46) AND (ss_quantity#46 >= 16)) AND (ss_quantity#46 <= 20)) AND ((((ss_list_price#48 >= 135.00) AND (ss_list_price#48 <= 145.00)) OR ((ss_coupon_amt#49 >= 6071.00) AND (ss_coupon_amt#49 <= 7071.00))) OR ((ss_wholesale_cost#47 >= 38.00) AND (ss_wholesale_cost#47 <= 58.00)))) -(38) Project [codegen id : 9] -Output [1]: [ss_list_price#48] +(37) CometProject Input [5]: [ss_quantity#46, ss_wholesale_cost#47, ss_list_price#48, ss_coupon_amt#49, ss_sold_date_sk#50] +Arguments: [ss_list_price#48], [ss_list_price#48] + +(38) ColumnarToRow [codegen id : 9] +Input [1]: [ss_list_price#48] (39) HashAggregate [codegen id : 9] Input [1]: [ss_list_price#48] @@ -318,16 +318,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,21), LessThanOrEqual(ss_quantity,25), Or(Or(And(GreaterThanOrEqual(ss_list_price,122.00),LessThanOrEqual(ss_list_price,132.00)),And(GreaterThanOrEqual(ss_coupon_amt,836.00),LessThanOrEqual(ss_coupon_amt,1836.00))),And(GreaterThanOrEqual(ss_wholesale_cost,17.00),LessThanOrEqual(ss_wholesale_cost,37.00)))] ReadSchema: struct -(48) ColumnarToRow [codegen id : 12] -Input [5]: [ss_quantity#61, ss_wholesale_cost#62, ss_list_price#63, ss_coupon_amt#64, ss_sold_date_sk#65] - -(49) Filter [codegen id : 12] +(48) CometFilter Input [5]: [ss_quantity#61, ss_wholesale_cost#62, ss_list_price#63, ss_coupon_amt#64, ss_sold_date_sk#65] Condition : (((isnotnull(ss_quantity#61) AND (ss_quantity#61 >= 21)) AND (ss_quantity#61 <= 25)) AND ((((ss_list_price#63 >= 122.00) AND (ss_list_price#63 <= 132.00)) OR ((ss_coupon_amt#64 >= 836.00) AND (ss_coupon_amt#64 <= 1836.00))) OR ((ss_wholesale_cost#62 >= 17.00) AND (ss_wholesale_cost#62 <= 37.00)))) -(50) Project [codegen id : 12] -Output [1]: [ss_list_price#63] +(49) CometProject Input [5]: [ss_quantity#61, ss_wholesale_cost#62, ss_list_price#63, ss_coupon_amt#64, ss_sold_date_sk#65] +Arguments: [ss_list_price#63], [ss_list_price#63] + +(50) ColumnarToRow [codegen id : 12] +Input [1]: [ss_list_price#63] (51) HashAggregate [codegen id : 12] Input [1]: [ss_list_price#63] @@ -380,16 +380,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,26), LessThanOrEqual(ss_quantity,30), Or(Or(And(GreaterThanOrEqual(ss_list_price,154.00),LessThanOrEqual(ss_list_price,164.00)),And(GreaterThanOrEqual(ss_coupon_amt,7326.00),LessThanOrEqual(ss_coupon_amt,8326.00))),And(GreaterThanOrEqual(ss_wholesale_cost,7.00),LessThanOrEqual(ss_wholesale_cost,27.00)))] ReadSchema: struct -(60) ColumnarToRow [codegen id : 15] -Input [5]: [ss_quantity#76, ss_wholesale_cost#77, ss_list_price#78, ss_coupon_amt#79, ss_sold_date_sk#80] - -(61) Filter [codegen id : 15] +(60) CometFilter Input [5]: [ss_quantity#76, ss_wholesale_cost#77, ss_list_price#78, ss_coupon_amt#79, ss_sold_date_sk#80] Condition : (((isnotnull(ss_quantity#76) AND (ss_quantity#76 >= 26)) AND (ss_quantity#76 <= 30)) AND ((((ss_list_price#78 >= 154.00) AND (ss_list_price#78 <= 164.00)) OR ((ss_coupon_amt#79 >= 7326.00) AND (ss_coupon_amt#79 <= 8326.00))) OR ((ss_wholesale_cost#77 >= 7.00) AND (ss_wholesale_cost#77 <= 27.00)))) -(62) Project [codegen id : 15] -Output [1]: [ss_list_price#78] +(61) CometProject Input [5]: [ss_quantity#76, ss_wholesale_cost#77, ss_list_price#78, ss_coupon_amt#79, ss_sold_date_sk#80] +Arguments: [ss_list_price#78], [ss_list_price#78] + +(62) ColumnarToRow [codegen id : 15] +Input [1]: [ss_list_price#78] (63) HashAggregate [codegen id : 15] Input [1]: [ss_list_price#78] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt index 7f5641ec2..a7a3f9537 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q28/simplified.txt @@ -14,10 +14,10 @@ WholeStageCodegen (18) Exchange [ss_list_price] #2 WholeStageCodegen (1) HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] - Project [ss_list_price] - Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] InputAdapter BroadcastExchange #3 @@ -32,10 +32,10 @@ WholeStageCodegen (18) Exchange [ss_list_price] #5 WholeStageCodegen (3) HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] - Project [ss_list_price] - Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] InputAdapter BroadcastExchange #6 @@ -50,10 +50,10 @@ WholeStageCodegen (18) Exchange [ss_list_price] #8 WholeStageCodegen (6) HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] - Project [ss_list_price] - Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] InputAdapter BroadcastExchange #9 @@ -68,10 +68,10 @@ WholeStageCodegen (18) Exchange [ss_list_price] #11 WholeStageCodegen (9) HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] - Project [ss_list_price] - Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] InputAdapter BroadcastExchange #12 @@ -86,10 +86,10 @@ WholeStageCodegen (18) Exchange [ss_list_price] #14 WholeStageCodegen (12) HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] - Project [ss_list_price] - Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] InputAdapter BroadcastExchange #15 @@ -104,8 +104,8 @@ WholeStageCodegen (18) Exchange [ss_list_price] #17 WholeStageCodegen (15) HashAggregate [ss_list_price] [avg(UnscaledValue(ss_list_price)),count(ss_list_price),sum,count,count,sum,count,count] - Project [ss_list_price] - Filter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_list_price] + CometFilter [ss_quantity,ss_list_price,ss_coupon_amt,ss_wholesale_cost] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt index 9a5be8c4d..522754cbc 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/explain.txt @@ -17,27 +17,27 @@ TakeOrderedAndProject (40) : : : : : +- * BroadcastHashJoin Inner BuildRight (14) : : : : : :- * Project (9) : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : : : :- * Filter (3) - : : : : : : : +- * ColumnarToRow (2) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : : : +- BroadcastExchange (7) - : : : : : : +- * Filter (6) - : : : : : : +- * ColumnarToRow (5) + : : : : : : +- * ColumnarToRow (6) + : : : : : : +- CometFilter (5) : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) : : : : : +- BroadcastExchange (13) - : : : : : +- * Filter (12) - : : : : : +- * ColumnarToRow (11) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometFilter (11) : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (10) : : : : +- ReusedExchange (16) : : : +- ReusedExchange (19) : : +- ReusedExchange (22) : +- BroadcastExchange (28) - : +- * Filter (27) - : +- * ColumnarToRow (26) + : +- * ColumnarToRow (27) + : +- CometFilter (26) : +- CometScan parquet spark_catalog.default.store (25) +- BroadcastExchange (34) - +- * Filter (33) - +- * ColumnarToRow (32) + +- * ColumnarToRow (33) + +- CometFilter (32) +- CometScan parquet spark_catalog.default.item (31) @@ -49,12 +49,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 8] +(2) CometFilter Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) -(3) Filter [codegen id : 8] +(3) ColumnarToRow [codegen id : 8] Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6] -Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3)) (4) Scan parquet spark_catalog.default.store_returns Output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] @@ -64,12 +64,12 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#12), dynamicpruningexpression(s PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] +Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] -Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10)) (7) BroadcastExchange Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12] @@ -93,12 +93,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] -Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15)) (13) BroadcastExchange Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17] @@ -160,12 +160,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 6] +(26) CometFilter Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] +Condition : isnotnull(s_store_sk#22) -(27) Filter [codegen id : 6] +(27) ColumnarToRow [codegen id : 6] Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] -Condition : isnotnull(s_store_sk#22) (28) BroadcastExchange Input [3]: [s_store_sk#22, s_store_id#23, s_store_name#24] @@ -188,12 +188,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(32) ColumnarToRow [codegen id : 7] +(32) CometFilter Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] +Condition : isnotnull(i_item_sk#25) -(33) Filter [codegen id : 7] +(33) ColumnarToRow [codegen id : 7] Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] -Condition : isnotnull(i_item_sk#25) (34) BroadcastExchange Input [3]: [i_item_sk#25, i_item_id#26, i_item_desc#27] @@ -235,9 +235,9 @@ Arguments: 100, [i_item_id#26 ASC NULLS FIRST, i_item_desc#27 ASC NULLS FIRST, s Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 BroadcastExchange (45) -+- * Project (44) - +- * Filter (43) - +- * ColumnarToRow (42) ++- * ColumnarToRow (44) + +- CometProject (43) + +- CometFilter (42) +- CometScan parquet spark_catalog.default.date_dim (41) @@ -248,16 +248,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,9), EqualTo(d_year,1999), IsNotNull(d_date_sk)] ReadSchema: struct -(42) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#19, d_year#40, d_moy#41] - -(43) Filter [codegen id : 1] +(42) CometFilter Input [3]: [d_date_sk#19, d_year#40, d_moy#41] Condition : ((((isnotnull(d_moy#41) AND isnotnull(d_year#40)) AND (d_moy#41 = 9)) AND (d_year#40 = 1999)) AND isnotnull(d_date_sk#19)) -(44) Project [codegen id : 1] -Output [1]: [d_date_sk#19] +(43) CometProject Input [3]: [d_date_sk#19, d_year#40, d_moy#41] +Arguments: [d_date_sk#19], [d_date_sk#19] + +(44) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#19] (45) BroadcastExchange Input [1]: [d_date_sk#19] @@ -265,9 +265,9 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)) Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#12 IN dynamicpruning#13 BroadcastExchange (50) -+- * Project (49) - +- * Filter (48) - +- * ColumnarToRow (47) ++- * ColumnarToRow (49) + +- CometProject (48) + +- CometFilter (47) +- CometScan parquet spark_catalog.default.date_dim (46) @@ -278,16 +278,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), GreaterThanOrEqual(d_moy,9), LessThanOrEqual(d_moy,12), EqualTo(d_year,1999), IsNotNull(d_date_sk)] ReadSchema: struct -(47) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#20, d_year#42, d_moy#43] - -(48) Filter [codegen id : 1] +(47) CometFilter Input [3]: [d_date_sk#20, d_year#42, d_moy#43] Condition : (((((isnotnull(d_moy#43) AND isnotnull(d_year#42)) AND (d_moy#43 >= 9)) AND (d_moy#43 <= 12)) AND (d_year#42 = 1999)) AND isnotnull(d_date_sk#20)) -(49) Project [codegen id : 1] -Output [1]: [d_date_sk#20] +(48) CometProject Input [3]: [d_date_sk#20, d_year#42, d_moy#43] +Arguments: [d_date_sk#20], [d_date_sk#20] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#20] (50) BroadcastExchange Input [1]: [d_date_sk#20] @@ -295,9 +295,9 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)) Subquery:3 Hosting operator id = 10 Hosting Expression = cs_sold_date_sk#17 IN dynamicpruning#18 BroadcastExchange (55) -+- * Project (54) - +- * Filter (53) - +- * ColumnarToRow (52) ++- * ColumnarToRow (54) + +- CometProject (53) + +- CometFilter (52) +- CometScan parquet spark_catalog.default.date_dim (51) @@ -308,16 +308,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] ReadSchema: struct -(52) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#21, d_year#44] - -(53) Filter [codegen id : 1] +(52) CometFilter Input [2]: [d_date_sk#21, d_year#44] Condition : (d_year#44 IN (1999,2000,2001) AND isnotnull(d_date_sk#21)) -(54) Project [codegen id : 1] -Output [1]: [d_date_sk#21] +(53) CometProject Input [2]: [d_date_sk#21, d_year#44] +Arguments: [d_date_sk#21], [d_date_sk#21] + +(54) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#21] (55) BroadcastExchange Input [1]: [d_date_sk#21] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt index 101893d07..68a127d35 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q29/simplified.txt @@ -19,47 +19,47 @@ TakeOrderedAndProject [i_item_id,i_item_desc,s_store_id,s_store_name,store_sales BroadcastHashJoin [sr_customer_sk,sr_item_sk,cs_bill_customer_sk,cs_item_sk] Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sold_date_sk,sr_item_sk,sr_customer_sk,sr_return_quantity,sr_returned_date_sk] BroadcastHashJoin [ss_customer_sk,ss_item_sk,ss_ticket_number,sr_customer_sk,sr_item_sk,sr_ticket_number] - Filter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk,ss_item_sk,ss_ticket_number,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_quantity,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_moy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [sr_customer_sk,sr_item_sk,sr_ticket_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sr_customer_sk,sr_item_sk,sr_ticket_number] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_return_quantity,sr_returned_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_moy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #5 WholeStageCodegen (2) - Filter [cs_bill_customer_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #3 BroadcastExchange #6 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk] #2 @@ -70,14 +70,14 @@ TakeOrderedAndProject [i_item_id,i_item_desc,s_store_id,s_store_name,store_sales InputAdapter BroadcastExchange #7 WholeStageCodegen (6) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name] InputAdapter BroadcastExchange #8 WholeStageCodegen (7) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt index 6fdc0d461..e89cfe1ff 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/explain.txt @@ -7,18 +7,18 @@ TakeOrderedAndProject (21) +- * BroadcastHashJoin Inner BuildRight (16) :- * Project (10) : +- * BroadcastHashJoin Inner BuildRight (9) - : :- * Project (4) - : : +- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.date_dim (1) : +- BroadcastExchange (8) - : +- * Filter (7) - : +- * ColumnarToRow (6) + : +- * ColumnarToRow (7) + : +- CometFilter (6) : +- CometScan parquet spark_catalog.default.store_sales (5) +- BroadcastExchange (15) - +- * Project (14) - +- * Filter (13) - +- * ColumnarToRow (12) + +- * ColumnarToRow (14) + +- CometProject (13) + +- CometFilter (12) +- CometScan parquet spark_catalog.default.item (11) @@ -29,16 +29,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), EqualTo(d_moy,11), IsNotNull(d_date_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] -Input [3]: [d_date_sk#1, d_year#2, d_moy#3] - -(3) Filter [codegen id : 3] +(2) CometFilter Input [3]: [d_date_sk#1, d_year#2, d_moy#3] Condition : ((isnotnull(d_moy#3) AND (d_moy#3 = 11)) AND isnotnull(d_date_sk#1)) -(4) Project [codegen id : 3] -Output [2]: [d_date_sk#1, d_year#2] +(3) CometProject Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Arguments: [d_date_sk#1, d_year#2], [d_date_sk#1, d_year#2] + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [d_date_sk#1, d_year#2] (5) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] @@ -48,12 +48,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] +(6) CometFilter Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) -(7) Filter [codegen id : 1] +(7) ColumnarToRow [codegen id : 1] Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] -Condition : isnotnull(ss_item_sk#4) (8) BroadcastExchange Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] @@ -76,16 +76,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_manufact_id), EqualTo(i_manufact_id,128), IsNotNull(i_item_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] -Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manufact_id#10] - -(13) Filter [codegen id : 2] +(12) CometFilter Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manufact_id#10] Condition : ((isnotnull(i_manufact_id#10) AND (i_manufact_id#10 = 128)) AND isnotnull(i_item_sk#7)) -(14) Project [codegen id : 2] -Output [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +(13) CometProject Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manufact_id#10] +Arguments: [i_item_sk#7, i_brand_id#8, i_brand#9], [i_item_sk#7, i_brand_id#8, i_brand#9] + +(14) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] (15) BroadcastExchange Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt index a869b17dd..3946c0cd8 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q3/simplified.txt @@ -9,23 +9,23 @@ TakeOrderedAndProject [d_year,sum_agg,brand_id,brand] BroadcastHashJoin [ss_item_sk,i_item_sk] Project [d_year,ss_item_sk,ss_ext_sales_price] BroadcastHashJoin [d_date_sk,ss_sold_date_sk] - Project [d_date_sk,d_year] - Filter [d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_year] + CometFilter [d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [i_item_sk,i_brand_id,i_brand] - Filter [i_manufact_id,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_brand] + CometFilter [i_manufact_id,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manufact_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt index 344c57efd..098d00824 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/explain.txt @@ -14,13 +14,13 @@ TakeOrderedAndProject (49) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (6) : : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.web_returns (1) : : : : +- ReusedExchange (4) : : : +- BroadcastExchange (10) - : : : +- * Filter (9) - : : : +- * ColumnarToRow (8) + : : : +- * ColumnarToRow (9) + : : : +- CometFilter (8) : : : +- CometScan parquet spark_catalog.default.customer_address (7) : : +- BroadcastExchange (33) : : +- * Filter (32) @@ -34,19 +34,19 @@ TakeOrderedAndProject (49) : : +- * BroadcastHashJoin Inner BuildRight (24) : : :- * Project (22) : : : +- * BroadcastHashJoin Inner BuildRight (21) - : : : :- * Filter (19) - : : : : +- * ColumnarToRow (18) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) : : : : +- CometScan parquet spark_catalog.default.web_returns (17) : : : +- ReusedExchange (20) : : +- ReusedExchange (23) : +- BroadcastExchange (39) - : +- * Filter (38) - : +- * ColumnarToRow (37) + : +- * ColumnarToRow (38) + : +- CometFilter (37) : +- CometScan parquet spark_catalog.default.customer (36) +- BroadcastExchange (46) - +- * Project (45) - +- * Filter (44) - +- * ColumnarToRow (43) + +- * ColumnarToRow (45) + +- CometProject (44) + +- CometFilter (43) +- CometScan parquet spark_catalog.default.customer_address (42) @@ -58,12 +58,12 @@ PartitionFilters: [isnotnull(wr_returned_date_sk#4), dynamicpruningexpression(wr PushedFilters: [IsNotNull(wr_returning_addr_sk), IsNotNull(wr_returning_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [4]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, wr_returned_date_sk#4] +Condition : (isnotnull(wr_returning_addr_sk#2) AND isnotnull(wr_returning_customer_sk#1)) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [4]: [wr_returning_customer_sk#1, wr_returning_addr_sk#2, wr_return_amt#3, wr_returned_date_sk#4] -Condition : (isnotnull(wr_returning_addr_sk#2) AND isnotnull(wr_returning_customer_sk#1)) (4) ReusedExchange [Reuses operator id: 54] Output [1]: [d_date_sk#6] @@ -85,12 +85,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_state)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [2]: [ca_address_sk#7, ca_state#8] +Condition : (isnotnull(ca_address_sk#7) AND isnotnull(ca_state#8)) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [2]: [ca_address_sk#7, ca_state#8] -Condition : (isnotnull(ca_address_sk#7) AND isnotnull(ca_state#8)) (10) BroadcastExchange Input [2]: [ca_address_sk#7, ca_state#8] @@ -136,12 +136,12 @@ PartitionFilters: [isnotnull(wr_returned_date_sk#18), dynamicpruningexpression(w PushedFilters: [IsNotNull(wr_returning_addr_sk)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 6] +(18) CometFilter Input [4]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, wr_returned_date_sk#18] +Condition : isnotnull(wr_returning_addr_sk#16) -(19) Filter [codegen id : 6] +(19) ColumnarToRow [codegen id : 6] Input [4]: [wr_returning_customer_sk#15, wr_returning_addr_sk#16, wr_return_amt#17, wr_returned_date_sk#18] -Condition : isnotnull(wr_returning_addr_sk#16) (20) ReusedExchange [Reuses operator id: 54] Output [1]: [d_date_sk#20] @@ -230,12 +230,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(37) ColumnarToRow [codegen id : 9] +(37) CometFilter Input [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] +Condition : (isnotnull(c_customer_sk#33) AND isnotnull(c_current_addr_sk#35)) -(38) Filter [codegen id : 9] +(38) ColumnarToRow [codegen id : 9] Input [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] -Condition : (isnotnull(c_customer_sk#33) AND isnotnull(c_current_addr_sk#35)) (39) BroadcastExchange Input [14]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38, c_preferred_cust_flag#39, c_birth_day#40, c_birth_month#41, c_birth_year#42, c_birth_country#43, c_login#44, c_email_address#45, c_last_review_date#46] @@ -258,16 +258,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,GA), IsNotNull(ca_address_sk)] ReadSchema: struct -(43) ColumnarToRow [codegen id : 10] -Input [2]: [ca_address_sk#47, ca_state#48] - -(44) Filter [codegen id : 10] +(43) CometFilter Input [2]: [ca_address_sk#47, ca_state#48] Condition : ((isnotnull(ca_state#48) AND (ca_state#48 = GA)) AND isnotnull(ca_address_sk#47)) -(45) Project [codegen id : 10] -Output [1]: [ca_address_sk#47] +(44) CometProject Input [2]: [ca_address_sk#47, ca_state#48] +Arguments: [ca_address_sk#47], [ca_address_sk#47] + +(45) ColumnarToRow [codegen id : 10] +Input [1]: [ca_address_sk#47] (46) BroadcastExchange Input [1]: [ca_address_sk#47] @@ -291,9 +291,9 @@ Arguments: 100, [c_customer_id#34 ASC NULLS FIRST, c_salutation#36 ASC NULLS FIR Subquery:1 Hosting operator id = 1 Hosting Expression = wr_returned_date_sk#4 IN dynamicpruning#5 BroadcastExchange (54) -+- * Project (53) - +- * Filter (52) - +- * ColumnarToRow (51) ++- * ColumnarToRow (53) + +- CometProject (52) + +- CometFilter (51) +- CometScan parquet spark_catalog.default.date_dim (50) @@ -304,16 +304,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] ReadSchema: struct -(51) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#6, d_year#49] - -(52) Filter [codegen id : 1] +(51) CometFilter Input [2]: [d_date_sk#6, d_year#49] Condition : ((isnotnull(d_year#49) AND (d_year#49 = 2002)) AND isnotnull(d_date_sk#6)) -(53) Project [codegen id : 1] -Output [1]: [d_date_sk#6] +(52) CometProject Input [2]: [d_date_sk#6, d_year#49] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(53) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] (54) BroadcastExchange Input [1]: [d_date_sk#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/simplified.txt index b0935ef25..365f7f973 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q30/simplified.txt @@ -16,26 +16,26 @@ TakeOrderedAndProject [c_customer_id,c_salutation,c_first_name,c_last_name,c_pre BroadcastHashJoin [wr_returning_addr_sk,ca_address_sk] Project [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt] BroadcastHashJoin [wr_returned_date_sk,d_date_sk] - Filter [wr_returning_addr_sk,wr_returning_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [wr_returning_addr_sk,wr_returning_customer_sk] CometScan parquet spark_catalog.default.web_returns [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt,wr_returned_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [ca_address_sk,ca_state] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_state] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #4 @@ -55,9 +55,9 @@ TakeOrderedAndProject [c_customer_id,c_salutation,c_first_name,c_last_name,c_pre BroadcastHashJoin [wr_returning_addr_sk,ca_address_sk] Project [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt] BroadcastHashJoin [wr_returned_date_sk,d_date_sk] - Filter [wr_returning_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [wr_returning_addr_sk] CometScan parquet spark_catalog.default.web_returns [wr_returning_customer_sk,wr_returning_addr_sk,wr_return_amt,wr_returned_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -67,15 +67,15 @@ TakeOrderedAndProject [c_customer_id,c_salutation,c_first_name,c_last_name,c_pre InputAdapter BroadcastExchange #7 WholeStageCodegen (9) - Filter [c_customer_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_current_addr_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address,c_last_review_date] InputAdapter BroadcastExchange #8 WholeStageCodegen (10) - Project [ca_address_sk] - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/explain.txt index 4810517ca..e20d45486 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/explain.txt @@ -16,13 +16,13 @@ : : : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : : : :- * Project (6) : : : : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : : : : :- * Filter (3) - : : : : : : : +- * ColumnarToRow (2) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : : : +- ReusedExchange (4) : : : : : +- BroadcastExchange (10) - : : : : : +- * Filter (9) - : : : : : +- * ColumnarToRow (8) + : : : : : +- * ColumnarToRow (9) + : : : : : +- CometFilter (8) : : : : : +- CometScan parquet spark_catalog.default.customer_address (7) : : : : +- BroadcastExchange (28) : : : : +- * HashAggregate (27) @@ -32,8 +32,8 @@ : : : : +- * BroadcastHashJoin Inner BuildRight (23) : : : : :- * Project (21) : : : : : +- * BroadcastHashJoin Inner BuildRight (20) - : : : : : :- * Filter (18) - : : : : : : +- * ColumnarToRow (17) + : : : : : :- * ColumnarToRow (18) + : : : : : : +- CometFilter (17) : : : : : : +- CometScan parquet spark_catalog.default.store_sales (16) : : : : : +- ReusedExchange (19) : : : : +- ReusedExchange (22) @@ -45,8 +45,8 @@ : : : +- * BroadcastHashJoin Inner BuildRight (37) : : : :- * Project (35) : : : : +- * BroadcastHashJoin Inner BuildRight (34) - : : : : :- * Filter (32) - : : : : : +- * ColumnarToRow (31) + : : : : :- * ColumnarToRow (32) + : : : : : +- CometFilter (31) : : : : : +- CometScan parquet spark_catalog.default.store_sales (30) : : : : +- ReusedExchange (33) : : : +- ReusedExchange (36) @@ -58,8 +58,8 @@ : : +- * BroadcastHashJoin Inner BuildRight (52) : : :- * Project (50) : : : +- * BroadcastHashJoin Inner BuildRight (49) - : : : :- * Filter (47) - : : : : +- * ColumnarToRow (46) + : : : :- * ColumnarToRow (47) + : : : : +- CometFilter (46) : : : : +- CometScan parquet spark_catalog.default.web_sales (45) : : : +- ReusedExchange (48) : : +- ReusedExchange (51) @@ -71,8 +71,8 @@ : +- * BroadcastHashJoin Inner BuildRight (66) : :- * Project (64) : : +- * BroadcastHashJoin Inner BuildRight (63) - : : :- * Filter (61) - : : : +- * ColumnarToRow (60) + : : :- * ColumnarToRow (61) + : : : +- CometFilter (60) : : : +- CometScan parquet spark_catalog.default.web_sales (59) : : +- ReusedExchange (62) : +- ReusedExchange (65) @@ -84,8 +84,8 @@ +- * BroadcastHashJoin Inner BuildRight (81) :- * Project (79) : +- * BroadcastHashJoin Inner BuildRight (78) - : :- * Filter (76) - : : +- * ColumnarToRow (75) + : :- * ColumnarToRow (76) + : : +- CometFilter (75) : : +- CometScan parquet spark_catalog.default.web_sales (74) : +- ReusedExchange (77) +- ReusedExchange (80) @@ -99,12 +99,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_addr_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [3]: [ss_addr_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_addr_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [3]: [ss_addr_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] -Condition : isnotnull(ss_addr_sk#1) (4) ReusedExchange [Reuses operator id: 94] Output [3]: [d_date_sk#5, d_year#6, d_qoy#7] @@ -126,12 +126,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_county)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [2]: [ca_address_sk#8, ca_county#9] +Condition : (isnotnull(ca_address_sk#8) AND isnotnull(ca_county#9)) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [2]: [ca_address_sk#8, ca_county#9] -Condition : (isnotnull(ca_address_sk#8) AND isnotnull(ca_county#9)) (10) BroadcastExchange Input [2]: [ca_address_sk#8, ca_county#9] @@ -173,12 +173,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#16), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_addr_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 6] +(17) CometFilter Input [3]: [ss_addr_sk#14, ss_ext_sales_price#15, ss_sold_date_sk#16] +Condition : isnotnull(ss_addr_sk#14) -(18) Filter [codegen id : 6] +(18) ColumnarToRow [codegen id : 6] Input [3]: [ss_addr_sk#14, ss_ext_sales_price#15, ss_sold_date_sk#16] -Condition : isnotnull(ss_addr_sk#14) (19) ReusedExchange [Reuses operator id: 98] Output [3]: [d_date_sk#18, d_year#19, d_qoy#20] @@ -242,12 +242,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#28), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_addr_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 10] +(31) CometFilter Input [3]: [ss_addr_sk#26, ss_ext_sales_price#27, ss_sold_date_sk#28] +Condition : isnotnull(ss_addr_sk#26) -(32) Filter [codegen id : 10] +(32) ColumnarToRow [codegen id : 10] Input [3]: [ss_addr_sk#26, ss_ext_sales_price#27, ss_sold_date_sk#28] -Condition : isnotnull(ss_addr_sk#26) (33) ReusedExchange [Reuses operator id: 102] Output [3]: [d_date_sk#30, d_year#31, d_qoy#32] @@ -315,12 +315,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#40), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_addr_sk)] ReadSchema: struct -(46) ColumnarToRow [codegen id : 14] +(46) CometFilter Input [3]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, ws_sold_date_sk#40] +Condition : isnotnull(ws_bill_addr_sk#38) -(47) Filter [codegen id : 14] +(47) ColumnarToRow [codegen id : 14] Input [3]: [ws_bill_addr_sk#38, ws_ext_sales_price#39, ws_sold_date_sk#40] -Condition : isnotnull(ws_bill_addr_sk#38) (48) ReusedExchange [Reuses operator id: 94] Output [3]: [d_date_sk#42, d_year#43, d_qoy#44] @@ -384,12 +384,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#53), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_addr_sk)] ReadSchema: struct -(60) ColumnarToRow [codegen id : 18] +(60) CometFilter Input [3]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, ws_sold_date_sk#53] +Condition : isnotnull(ws_bill_addr_sk#51) -(61) Filter [codegen id : 18] +(61) ColumnarToRow [codegen id : 18] Input [3]: [ws_bill_addr_sk#51, ws_ext_sales_price#52, ws_sold_date_sk#53] -Condition : isnotnull(ws_bill_addr_sk#51) (62) ReusedExchange [Reuses operator id: 98] Output [3]: [d_date_sk#55, d_year#56, d_qoy#57] @@ -457,12 +457,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#65), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_addr_sk)] ReadSchema: struct -(75) ColumnarToRow [codegen id : 22] +(75) CometFilter Input [3]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, ws_sold_date_sk#65] +Condition : isnotnull(ws_bill_addr_sk#63) -(76) Filter [codegen id : 22] +(76) ColumnarToRow [codegen id : 22] Input [3]: [ws_bill_addr_sk#63, ws_ext_sales_price#64, ws_sold_date_sk#65] -Condition : isnotnull(ws_bill_addr_sk#63) (77) ReusedExchange [Reuses operator id: 102] Output [3]: [d_date_sk#67, d_year#68, d_qoy#69] @@ -534,8 +534,8 @@ Arguments: [ca_county#9 ASC NULLS FIRST], true, 0 Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (94) -+- * Filter (93) - +- * ColumnarToRow (92) ++- * ColumnarToRow (93) + +- CometFilter (92) +- CometScan parquet spark_catalog.default.date_dim (91) @@ -546,12 +546,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,1), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(92) ColumnarToRow [codegen id : 1] +(92) CometFilter Input [3]: [d_date_sk#5, d_year#6, d_qoy#7] +Condition : ((((isnotnull(d_qoy#7) AND isnotnull(d_year#6)) AND (d_qoy#7 = 1)) AND (d_year#6 = 2000)) AND isnotnull(d_date_sk#5)) -(93) Filter [codegen id : 1] +(93) ColumnarToRow [codegen id : 1] Input [3]: [d_date_sk#5, d_year#6, d_qoy#7] -Condition : ((((isnotnull(d_qoy#7) AND isnotnull(d_year#6)) AND (d_qoy#7 = 1)) AND (d_year#6 = 2000)) AND isnotnull(d_date_sk#5)) (94) BroadcastExchange Input [3]: [d_date_sk#5, d_year#6, d_qoy#7] @@ -559,8 +559,8 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint) Subquery:2 Hosting operator id = 16 Hosting Expression = ss_sold_date_sk#16 IN dynamicpruning#17 BroadcastExchange (98) -+- * Filter (97) - +- * ColumnarToRow (96) ++- * ColumnarToRow (97) + +- CometFilter (96) +- CometScan parquet spark_catalog.default.date_dim (95) @@ -571,12 +571,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(96) ColumnarToRow [codegen id : 1] +(96) CometFilter Input [3]: [d_date_sk#18, d_year#19, d_qoy#20] +Condition : ((((isnotnull(d_qoy#20) AND isnotnull(d_year#19)) AND (d_qoy#20 = 2)) AND (d_year#19 = 2000)) AND isnotnull(d_date_sk#18)) -(97) Filter [codegen id : 1] +(97) ColumnarToRow [codegen id : 1] Input [3]: [d_date_sk#18, d_year#19, d_qoy#20] -Condition : ((((isnotnull(d_qoy#20) AND isnotnull(d_year#19)) AND (d_qoy#20 = 2)) AND (d_year#19 = 2000)) AND isnotnull(d_date_sk#18)) (98) BroadcastExchange Input [3]: [d_date_sk#18, d_year#19, d_qoy#20] @@ -584,8 +584,8 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint) Subquery:3 Hosting operator id = 30 Hosting Expression = ss_sold_date_sk#28 IN dynamicpruning#29 BroadcastExchange (102) -+- * Filter (101) - +- * ColumnarToRow (100) ++- * ColumnarToRow (101) + +- CometFilter (100) +- CometScan parquet spark_catalog.default.date_dim (99) @@ -596,12 +596,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,3), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(100) ColumnarToRow [codegen id : 1] +(100) CometFilter Input [3]: [d_date_sk#30, d_year#31, d_qoy#32] +Condition : ((((isnotnull(d_qoy#32) AND isnotnull(d_year#31)) AND (d_qoy#32 = 3)) AND (d_year#31 = 2000)) AND isnotnull(d_date_sk#30)) -(101) Filter [codegen id : 1] +(101) ColumnarToRow [codegen id : 1] Input [3]: [d_date_sk#30, d_year#31, d_qoy#32] -Condition : ((((isnotnull(d_qoy#32) AND isnotnull(d_year#31)) AND (d_qoy#32 = 3)) AND (d_year#31 = 2000)) AND isnotnull(d_date_sk#30)) (102) BroadcastExchange Input [3]: [d_date_sk#30, d_year#31, d_qoy#32] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/simplified.txt index 67bc75cd0..f4bf6a89d 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q31/simplified.txt @@ -20,25 +20,25 @@ WholeStageCodegen (25) BroadcastHashJoin [ss_addr_sk,ca_address_sk] Project [ss_addr_sk,ss_ext_sales_price,d_year,d_qoy] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk] CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Filter [d_qoy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_qoy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] InputAdapter ReusedExchange [d_date_sk,d_year,d_qoy] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [ca_address_sk,ca_county] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_county] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county] InputAdapter BroadcastExchange #5 @@ -52,16 +52,16 @@ WholeStageCodegen (25) BroadcastHashJoin [ss_addr_sk,ca_address_sk] Project [ss_addr_sk,ss_ext_sales_price,d_year,d_qoy] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk] CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #7 WholeStageCodegen (1) - Filter [d_qoy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_qoy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] InputAdapter ReusedExchange [d_date_sk,d_year,d_qoy] #7 @@ -79,16 +79,16 @@ WholeStageCodegen (25) BroadcastHashJoin [ss_addr_sk,ca_address_sk] Project [ss_addr_sk,ss_ext_sales_price,d_year,d_qoy] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk] CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #3 BroadcastExchange #10 WholeStageCodegen (1) - Filter [d_qoy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_qoy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] InputAdapter ReusedExchange [d_date_sk,d_year,d_qoy] #10 @@ -106,9 +106,9 @@ WholeStageCodegen (25) BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] Project [ws_bill_addr_sk,ws_ext_sales_price,d_year,d_qoy] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_bill_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -127,9 +127,9 @@ WholeStageCodegen (25) BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] Project [ws_bill_addr_sk,ws_ext_sales_price,d_year,d_qoy] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_bill_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter @@ -148,9 +148,9 @@ WholeStageCodegen (25) BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] Project [ws_bill_addr_sk,ws_ext_sales_price,d_year,d_qoy] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_bill_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #3 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/explain.txt index 6fbaa6fab..bd7caaaa1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/explain.txt @@ -8,13 +8,13 @@ : +- * BroadcastHashJoin Inner BuildRight (22) : :- * Project (10) : : +- * BroadcastHashJoin Inner BuildRight (9) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : +- BroadcastExchange (8) - : : +- * Project (7) - : : +- * Filter (6) - : : +- * ColumnarToRow (5) + : : +- * ColumnarToRow (7) + : : +- CometProject (6) + : : +- CometFilter (5) : : +- CometScan parquet spark_catalog.default.item (4) : +- BroadcastExchange (21) : +- * Filter (20) @@ -23,8 +23,8 @@ : +- * HashAggregate (17) : +- * Project (16) : +- * BroadcastHashJoin Inner BuildRight (15) - : :- * Filter (13) - : : +- * ColumnarToRow (12) + : :- * ColumnarToRow (13) + : : +- CometFilter (12) : : +- CometScan parquet spark_catalog.default.catalog_sales (11) : +- ReusedExchange (14) +- ReusedExchange (24) @@ -38,12 +38,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_ext_discount_amt)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 6] +(2) CometFilter Input [3]: [cs_item_sk#1, cs_ext_discount_amt#2, cs_sold_date_sk#3] +Condition : (isnotnull(cs_item_sk#1) AND isnotnull(cs_ext_discount_amt#2)) -(3) Filter [codegen id : 6] +(3) ColumnarToRow [codegen id : 6] Input [3]: [cs_item_sk#1, cs_ext_discount_amt#2, cs_sold_date_sk#3] -Condition : (isnotnull(cs_item_sk#1) AND isnotnull(cs_ext_discount_amt#2)) (4) Scan parquet spark_catalog.default.item Output [2]: [i_item_sk#5, i_manufact_id#6] @@ -52,16 +52,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_manufact_id), EqualTo(i_manufact_id,977), IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [2]: [i_item_sk#5, i_manufact_id#6] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [2]: [i_item_sk#5, i_manufact_id#6] Condition : ((isnotnull(i_manufact_id#6) AND (i_manufact_id#6 = 977)) AND isnotnull(i_item_sk#5)) -(7) Project [codegen id : 1] -Output [1]: [i_item_sk#5] +(6) CometProject Input [2]: [i_item_sk#5, i_manufact_id#6] +Arguments: [i_item_sk#5], [i_item_sk#5] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [i_item_sk#5] (8) BroadcastExchange Input [1]: [i_item_sk#5] @@ -85,12 +85,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#9), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 3] +(12) CometFilter Input [3]: [cs_item_sk#7, cs_ext_discount_amt#8, cs_sold_date_sk#9] +Condition : isnotnull(cs_item_sk#7) -(13) Filter [codegen id : 3] +(13) ColumnarToRow [codegen id : 3] Input [3]: [cs_item_sk#7, cs_ext_discount_amt#8, cs_sold_date_sk#9] -Condition : isnotnull(cs_item_sk#7) (14) ReusedExchange [Reuses operator id: 34] Output [1]: [d_date_sk#11] @@ -176,9 +176,9 @@ Results [1]: [MakeDecimal(sum(UnscaledValue(cs_ext_discount_amt#2))#21,17,2) AS Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (34) -+- * Project (33) - +- * Filter (32) - +- * ColumnarToRow (31) ++- * ColumnarToRow (33) + +- CometProject (32) + +- CometFilter (31) +- CometScan parquet spark_catalog.default.date_dim (30) @@ -189,16 +189,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-01-27), LessThanOrEqual(d_date,2000-04-26), IsNotNull(d_date_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#18, d_date#23] - -(32) Filter [codegen id : 1] +(31) CometFilter Input [2]: [d_date_sk#18, d_date#23] Condition : (((isnotnull(d_date#23) AND (d_date#23 >= 2000-01-27)) AND (d_date#23 <= 2000-04-26)) AND isnotnull(d_date_sk#18)) -(33) Project [codegen id : 1] -Output [1]: [d_date_sk#18] +(32) CometProject Input [2]: [d_date_sk#18, d_date#23] +Arguments: [d_date_sk#18], [d_date_sk#18] + +(33) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#18] (34) BroadcastExchange Input [1]: [d_date_sk#18] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/simplified.txt index a87a0a7e1..146a33fdd 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q32/simplified.txt @@ -10,25 +10,25 @@ WholeStageCodegen (7) BroadcastHashJoin [i_item_sk,cs_item_sk,cs_ext_discount_amt,(1.3 * avg(cs_ext_discount_amt))] Project [cs_ext_discount_amt,cs_sold_date_sk,i_item_sk] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk,cs_ext_discount_amt] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_ext_discount_amt] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_discount_amt,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [i_item_sk] - Filter [i_manufact_id,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_manufact_id,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_manufact_id] InputAdapter BroadcastExchange #4 @@ -41,9 +41,9 @@ WholeStageCodegen (7) HashAggregate [cs_item_sk,cs_ext_discount_amt] [sum,count,sum,count] Project [cs_item_sk,cs_ext_discount_amt] BroadcastHashJoin [cs_sold_date_sk,d_date_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_discount_amt,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/explain.txt index 940b542a2..f9541481c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/explain.txt @@ -13,24 +13,24 @@ TakeOrderedAndProject (63) : : +- * BroadcastHashJoin Inner BuildRight (12) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (11) - : : +- * Project (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.customer_address (7) : +- BroadcastExchange (23) : +- * BroadcastHashJoin LeftSemi BuildRight (22) - : :- * Filter (16) - : : +- * ColumnarToRow (15) + : :- * ColumnarToRow (16) + : : +- CometFilter (15) : : +- CometScan parquet spark_catalog.default.item (14) : +- BroadcastExchange (21) - : +- * Project (20) - : +- * Filter (19) - : +- * ColumnarToRow (18) + : +- * ColumnarToRow (20) + : +- CometProject (19) + : +- CometFilter (18) : +- CometScan parquet spark_catalog.default.item (17) :- * HashAggregate (43) : +- Exchange (42) @@ -41,8 +41,8 @@ TakeOrderedAndProject (63) : : +- * BroadcastHashJoin Inner BuildRight (36) : : :- * Project (34) : : : +- * BroadcastHashJoin Inner BuildRight (33) - : : : :- * Filter (31) - : : : : +- * ColumnarToRow (30) + : : : :- * ColumnarToRow (31) + : : : : +- CometFilter (30) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (29) : : : +- ReusedExchange (32) : : +- ReusedExchange (35) @@ -56,8 +56,8 @@ TakeOrderedAndProject (63) : +- * BroadcastHashJoin Inner BuildRight (51) : :- * Project (49) : : +- * BroadcastHashJoin Inner BuildRight (48) - : : :- * Filter (46) - : : : +- * ColumnarToRow (45) + : : :- * ColumnarToRow (46) + : : : +- CometFilter (45) : : : +- CometScan parquet spark_catalog.default.web_sales (44) : : +- ReusedExchange (47) : +- ReusedExchange (50) @@ -72,12 +72,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_addr_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] -Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) (4) ReusedExchange [Reuses operator id: 68] Output [1]: [d_date_sk#6] @@ -99,16 +99,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] -Input [2]: [ca_address_sk#7, ca_gmt_offset#8] - -(9) Filter [codegen id : 2] +(8) CometFilter Input [2]: [ca_address_sk#7, ca_gmt_offset#8] Condition : ((isnotnull(ca_gmt_offset#8) AND (ca_gmt_offset#8 = -5.00)) AND isnotnull(ca_address_sk#7)) -(10) Project [codegen id : 2] -Output [1]: [ca_address_sk#7] +(9) CometProject Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Arguments: [ca_address_sk#7], [ca_address_sk#7] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [ca_address_sk#7] (11) BroadcastExchange Input [1]: [ca_address_sk#7] @@ -131,12 +131,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 4] +(15) CometFilter Input [2]: [i_item_sk#9, i_manufact_id#10] +Condition : isnotnull(i_item_sk#9) -(16) Filter [codegen id : 4] +(16) ColumnarToRow [codegen id : 4] Input [2]: [i_item_sk#9, i_manufact_id#10] -Condition : isnotnull(i_item_sk#9) (17) Scan parquet spark_catalog.default.item Output [2]: [i_category#11, i_manufact_id#12] @@ -145,16 +145,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Electronics )] ReadSchema: struct -(18) ColumnarToRow [codegen id : 3] -Input [2]: [i_category#11, i_manufact_id#12] - -(19) Filter [codegen id : 3] +(18) CometFilter Input [2]: [i_category#11, i_manufact_id#12] Condition : (isnotnull(i_category#11) AND (i_category#11 = Electronics )) -(20) Project [codegen id : 3] -Output [1]: [i_manufact_id#12] +(19) CometProject Input [2]: [i_category#11, i_manufact_id#12] +Arguments: [i_manufact_id#12], [i_manufact_id#12] + +(20) ColumnarToRow [codegen id : 3] +Input [1]: [i_manufact_id#12] (21) BroadcastExchange Input [1]: [i_manufact_id#12] @@ -206,12 +206,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#20), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_addr_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 11] +(30) CometFilter Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) -(31) Filter [codegen id : 11] +(31) ColumnarToRow [codegen id : 11] Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] -Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) (32) ReusedExchange [Reuses operator id: 68] Output [1]: [d_date_sk#22] @@ -278,12 +278,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_addr_sk), IsNotNull(ws_item_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 17] +(45) CometFilter Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) -(46) Filter [codegen id : 17] +(46) ColumnarToRow [codegen id : 17] Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] -Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) (47) ReusedExchange [Reuses operator id: 68] Output [1]: [d_date_sk#35] @@ -370,9 +370,9 @@ Arguments: 100, [total_sales#48 ASC NULLS FIRST], [i_manufact_id#10, total_sales Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 BroadcastExchange (68) -+- * Project (67) - +- * Filter (66) - +- * ColumnarToRow (65) ++- * ColumnarToRow (67) + +- CometProject (66) + +- CometFilter (65) +- CometScan parquet spark_catalog.default.date_dim (64) @@ -383,16 +383,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,5), IsNotNull(d_date_sk)] ReadSchema: struct -(65) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#6, d_year#49, d_moy#50] - -(66) Filter [codegen id : 1] +(65) CometFilter Input [3]: [d_date_sk#6, d_year#49, d_moy#50] Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#50)) AND (d_year#49 = 1998)) AND (d_moy#50 = 5)) AND isnotnull(d_date_sk#6)) -(67) Project [codegen id : 1] -Output [1]: [d_date_sk#6] +(66) CometProject Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(67) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] (68) BroadcastExchange Input [1]: [d_date_sk#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/simplified.txt index 007a3be47..4ab82379f 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q33/simplified.txt @@ -19,43 +19,43 @@ TakeOrderedAndProject [total_sales,i_manufact_id] BroadcastHashJoin [ss_addr_sk,ca_address_sk] Project [ss_item_sk,ss_addr_sk,ss_ext_sales_price] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_addr_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [ca_address_sk] - Filter [ca_gmt_offset,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_gmt_offset,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) BroadcastHashJoin [i_manufact_id,i_manufact_id] - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_manufact_id] InputAdapter BroadcastExchange #6 WholeStageCodegen (3) - Project [i_manufact_id] - Filter [i_category] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_manufact_id] + CometFilter [i_category] CometScan parquet spark_catalog.default.item [i_category,i_manufact_id] WholeStageCodegen (12) HashAggregate [i_manufact_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),total_sales,sum] @@ -69,9 +69,9 @@ TakeOrderedAndProject [total_sales,i_manufact_id] BroadcastHashJoin [cs_bill_addr_sk,ca_address_sk] Project [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price] BroadcastHashJoin [cs_sold_date_sk,d_date_sk] - Filter [cs_bill_addr_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_addr_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -92,9 +92,9 @@ TakeOrderedAndProject [total_sales,i_manufact_id] BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] Project [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_bill_addr_sk,ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk,ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/explain.txt index 63dacf973..d0f166fe9 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/explain.txt @@ -13,23 +13,23 @@ : : +- * BroadcastHashJoin Inner BuildRight (12) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (11) - : : +- * Project (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.store (7) : +- BroadcastExchange (18) - : +- * Project (17) - : +- * Filter (16) - : +- * ColumnarToRow (15) + : +- * ColumnarToRow (17) + : +- CometProject (16) + : +- CometFilter (15) : +- CometScan parquet spark_catalog.default.household_demographics (14) +- BroadcastExchange (28) - +- * Filter (27) - +- * ColumnarToRow (26) + +- * ColumnarToRow (27) + +- CometFilter (26) +- CometScan parquet spark_catalog.default.customer (25) @@ -41,12 +41,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] -Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) (4) ReusedExchange [Reuses operator id: 37] Output [1]: [d_date_sk#7] @@ -68,16 +68,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_county), EqualTo(s_county,Williamson County), IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] -Input [2]: [s_store_sk#8, s_county#9] - -(9) Filter [codegen id : 2] +(8) CometFilter Input [2]: [s_store_sk#8, s_county#9] Condition : ((isnotnull(s_county#9) AND (s_county#9 = Williamson County)) AND isnotnull(s_store_sk#8)) -(10) Project [codegen id : 2] -Output [1]: [s_store_sk#8] +(9) CometProject Input [2]: [s_store_sk#8, s_county#9] +Arguments: [s_store_sk#8], [s_store_sk#8] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#8] (11) BroadcastExchange Input [1]: [s_store_sk#8] @@ -100,16 +100,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_vehicle_count), Or(EqualTo(hd_buy_potential,>10000 ),EqualTo(hd_buy_potential,unknown )), GreaterThan(hd_vehicle_count,0), IsNotNull(hd_demo_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] -Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] - -(16) Filter [codegen id : 3] +(15) CometFilter Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] Condition : ((((isnotnull(hd_vehicle_count#13) AND ((hd_buy_potential#11 = >10000 ) OR (hd_buy_potential#11 = unknown ))) AND (hd_vehicle_count#13 > 0)) AND CASE WHEN (hd_vehicle_count#13 > 0) THEN ((cast(hd_dep_count#12 as double) / cast(hd_vehicle_count#13 as double)) > 1.2) END) AND isnotnull(hd_demo_sk#10)) -(17) Project [codegen id : 3] -Output [1]: [hd_demo_sk#10] +(16) CometProject Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Arguments: [hd_demo_sk#10], [hd_demo_sk#10] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#10] (18) BroadcastExchange Input [1]: [hd_demo_sk#10] @@ -154,12 +154,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 5] +(26) CometFilter Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Condition : isnotnull(c_customer_sk#18) -(27) Filter [codegen id : 5] +(27) ColumnarToRow [codegen id : 5] Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] -Condition : isnotnull(c_customer_sk#18) (28) BroadcastExchange Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] @@ -187,9 +187,9 @@ Arguments: [c_last_name#21 ASC NULLS FIRST, c_first_name#20 ASC NULLS FIRST, c_s Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (37) -+- * Project (36) - +- * Filter (35) - +- * ColumnarToRow (34) ++- * ColumnarToRow (36) + +- CometProject (35) + +- CometFilter (34) +- CometScan parquet spark_catalog.default.date_dim (33) @@ -200,16 +200,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [Or(And(GreaterThanOrEqual(d_dom,1),LessThanOrEqual(d_dom,3)),And(GreaterThanOrEqual(d_dom,25),LessThanOrEqual(d_dom,28))), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] ReadSchema: struct -(34) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#7, d_year#23, d_dom#24] - -(35) Filter [codegen id : 1] +(34) CometFilter Input [3]: [d_date_sk#7, d_year#23, d_dom#24] Condition : (((((d_dom#24 >= 1) AND (d_dom#24 <= 3)) OR ((d_dom#24 >= 25) AND (d_dom#24 <= 28))) AND d_year#23 IN (1999,2000,2001)) AND isnotnull(d_date_sk#7)) -(36) Project [codegen id : 1] -Output [1]: [d_date_sk#7] +(35) CometProject Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(36) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] (37) BroadcastExchange Input [1]: [d_date_sk#7] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/simplified.txt index 91e0cbf9a..80405a784 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q34/simplified.txt @@ -17,40 +17,40 @@ WholeStageCodegen (7) BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_dom,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dom,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [s_store_sk] - Filter [s_county,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_county,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_county] InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Project [hd_demo_sk] - Filter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential,hd_dep_count,hd_vehicle_count] InputAdapter BroadcastExchange #6 WholeStageCodegen (5) - Filter [c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt index c4a94f735..a46018cdd 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/explain.txt @@ -12,8 +12,8 @@ TakeOrderedAndProject (42) : : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (24) : : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (17) : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : : +- BroadcastExchange (9) : : : : +- * Project (8) @@ -34,12 +34,12 @@ TakeOrderedAndProject (42) : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) : : +- ReusedExchange (20) : +- BroadcastExchange (30) - : +- * Filter (29) - : +- * ColumnarToRow (28) + : +- * ColumnarToRow (29) + : +- CometFilter (28) : +- CometScan parquet spark_catalog.default.customer_address (27) +- BroadcastExchange (36) - +- * Filter (35) - +- * ColumnarToRow (34) + +- * ColumnarToRow (35) + +- CometFilter (34) +- CometScan parquet spark_catalog.default.customer_demographics (33) @@ -50,12 +50,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 9] +(2) CometFilter Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) -(3) Filter [codegen id : 9] +(3) ColumnarToRow [codegen id : 9] Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] -Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) (4) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_customer_sk#6, ss_sold_date_sk#7] @@ -171,12 +171,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk)] ReadSchema: struct -(28) ColumnarToRow [codegen id : 7] +(28) CometFilter Input [2]: [ca_address_sk#18, ca_state#19] +Condition : isnotnull(ca_address_sk#18) -(29) Filter [codegen id : 7] +(29) ColumnarToRow [codegen id : 7] Input [2]: [ca_address_sk#18, ca_state#19] -Condition : isnotnull(ca_address_sk#18) (30) BroadcastExchange Input [2]: [ca_address_sk#18, ca_state#19] @@ -199,12 +199,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk)] ReadSchema: struct -(34) ColumnarToRow [codegen id : 8] +(34) CometFilter Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Condition : isnotnull(cd_demo_sk#20) -(35) Filter [codegen id : 8] +(35) ColumnarToRow [codegen id : 8] Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] -Condition : isnotnull(cd_demo_sk#20) (36) BroadcastExchange Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] @@ -246,9 +246,9 @@ Arguments: 100, [ca_state#19 ASC NULLS FIRST, cd_gender#21 ASC NULLS FIRST, cd_m Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (47) -+- * Project (46) - +- * Filter (45) - +- * ColumnarToRow (44) ++- * ColumnarToRow (46) + +- CometProject (45) + +- CometFilter (44) +- CometScan parquet spark_catalog.default.date_dim (43) @@ -259,16 +259,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,2002), LessThan(d_qoy,4), IsNotNull(d_date_sk)] ReadSchema: struct -(44) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] - -(45) Filter [codegen id : 1] +(44) CometFilter Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] Condition : ((((isnotnull(d_year#74) AND isnotnull(d_qoy#75)) AND (d_year#74 = 2002)) AND (d_qoy#75 < 4)) AND isnotnull(d_date_sk#9)) -(46) Project [codegen id : 1] -Output [1]: [d_date_sk#9] +(45) CometProject Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Arguments: [d_date_sk#9], [d_date_sk#9] + +(46) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#9] (47) BroadcastExchange Input [1]: [d_date_sk#9] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt index 67a9e3d11..ea0ef274e 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q35/simplified.txt @@ -14,9 +14,9 @@ TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_ BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_current_addr_sk,c_current_cdemo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] InputAdapter BroadcastExchange #2 @@ -29,10 +29,10 @@ TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_ SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_qoy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_qoy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] InputAdapter ReusedExchange [d_date_sk] #3 @@ -61,14 +61,14 @@ TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_ InputAdapter BroadcastExchange #6 WholeStageCodegen (7) - Filter [ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #7 WholeStageCodegen (8) - Filter [cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt index b82dfae23..39b838157 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/explain.txt @@ -14,18 +14,18 @@ TakeOrderedAndProject (28) : +- * BroadcastHashJoin Inner BuildRight (11) : :- * Project (6) : : +- * BroadcastHashJoin Inner BuildRight (5) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : +- ReusedExchange (4) : +- BroadcastExchange (10) - : +- * Filter (9) - : +- * ColumnarToRow (8) + : +- * ColumnarToRow (9) + : +- CometFilter (8) : +- CometScan parquet spark_catalog.default.item (7) +- BroadcastExchange (17) - +- * Project (16) - +- * Filter (15) - +- * ColumnarToRow (14) + +- * ColumnarToRow (16) + +- CometProject (15) + +- CometFilter (14) +- CometScan parquet spark_catalog.default.store (13) @@ -37,12 +37,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_store_sk#2)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] -Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_store_sk#2)) (4) ReusedExchange [Reuses operator id: 33] Output [1]: [d_date_sk#7] @@ -64,12 +64,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [3]: [i_item_sk#8, i_class#9, i_category#10] +Condition : isnotnull(i_item_sk#8) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [3]: [i_item_sk#8, i_class#9, i_category#10] -Condition : isnotnull(i_item_sk#8) (10) BroadcastExchange Input [3]: [i_item_sk#8, i_class#9, i_category#10] @@ -92,16 +92,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] -Input [2]: [s_store_sk#11, s_state#12] - -(15) Filter [codegen id : 3] +(14) CometFilter Input [2]: [s_store_sk#11, s_state#12] Condition : ((isnotnull(s_state#12) AND (s_state#12 = TN)) AND isnotnull(s_store_sk#11)) -(16) Project [codegen id : 3] -Output [1]: [s_store_sk#11] +(15) CometProject Input [2]: [s_store_sk#11, s_state#12] +Arguments: [s_store_sk#11], [s_store_sk#11] + +(16) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#11] (17) BroadcastExchange Input [1]: [s_store_sk#11] @@ -163,9 +163,9 @@ Arguments: 100, [lochierarchy#23 DESC NULLS LAST, CASE WHEN (lochierarchy#23 = 0 Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (33) -+- * Project (32) - +- * Filter (31) - +- * ColumnarToRow (30) ++- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) +- CometScan parquet spark_catalog.default.date_dim (29) @@ -176,16 +176,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#7, d_year#28] - -(31) Filter [codegen id : 1] +(30) CometFilter Input [2]: [d_date_sk#7, d_year#28] Condition : ((isnotnull(d_year#28) AND (d_year#28 = 2001)) AND isnotnull(d_date_sk#7)) -(32) Project [codegen id : 1] -Output [1]: [d_date_sk#7] +(31) CometProject Input [2]: [d_date_sk#7, d_year#28] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(32) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] (33) BroadcastExchange Input [1]: [d_date_sk#7] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt index acd050607..7eeb607c3 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q36/simplified.txt @@ -20,32 +20,32 @@ TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,gross_margin,i BroadcastHashJoin [ss_item_sk,i_item_sk] Project [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_item_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Project [s_store_sk] - Filter [s_state,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_state,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_state] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt index eeb841412..23c4ae742 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/explain.txt @@ -10,19 +10,19 @@ TakeOrderedAndProject (25) : +- * BroadcastHashJoin Inner BuildRight (13) : :- * Project (11) : : +- * BroadcastHashJoin Inner BuildRight (10) - : : :- * Project (4) - : : : +- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.item (1) : : +- BroadcastExchange (9) - : : +- * Project (8) - : : +- * Filter (7) - : : +- * ColumnarToRow (6) + : : +- * ColumnarToRow (8) + : : +- CometProject (7) + : : +- CometFilter (6) : : +- CometScan parquet spark_catalog.default.inventory (5) : +- ReusedExchange (12) - +- * Project (19) - +- * Filter (18) - +- * ColumnarToRow (17) + +- * ColumnarToRow (19) + +- CometProject (18) + +- CometFilter (17) +- CometScan parquet spark_catalog.default.catalog_sales (16) @@ -33,16 +33,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,68.00), LessThanOrEqual(i_current_price,98.00), In(i_manufact_id, [677,694,808,940]), IsNotNull(i_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] -Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] - -(3) Filter [codegen id : 3] +(2) CometFilter Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] Condition : ((((isnotnull(i_current_price#4) AND (i_current_price#4 >= 68.00)) AND (i_current_price#4 <= 98.00)) AND i_manufact_id#5 IN (677,940,694,808)) AND isnotnull(i_item_sk#1)) -(4) Project [codegen id : 3] -Output [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +(3) CometProject Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Arguments: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4], [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] + +(4) ColumnarToRow [codegen id : 3] +Input [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] (5) Scan parquet spark_catalog.default.inventory Output [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] @@ -52,16 +52,16 @@ PartitionFilters: [isnotnull(inv_date_sk#8), dynamicpruningexpression(inv_date_s PushedFilters: [IsNotNull(inv_quantity_on_hand), GreaterThanOrEqual(inv_quantity_on_hand,100), LessThanOrEqual(inv_quantity_on_hand,500), IsNotNull(inv_item_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] -Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] - -(7) Filter [codegen id : 1] +(6) CometFilter Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] Condition : (((isnotnull(inv_quantity_on_hand#7) AND (inv_quantity_on_hand#7 >= 100)) AND (inv_quantity_on_hand#7 <= 500)) AND isnotnull(inv_item_sk#6)) -(8) Project [codegen id : 1] -Output [2]: [inv_item_sk#6, inv_date_sk#8] +(7) CometProject Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Arguments: [inv_item_sk#6, inv_date_sk#8], [inv_item_sk#6, inv_date_sk#8] + +(8) ColumnarToRow [codegen id : 1] +Input [2]: [inv_item_sk#6, inv_date_sk#8] (9) BroadcastExchange Input [2]: [inv_item_sk#6, inv_date_sk#8] @@ -101,16 +101,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_sales] PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(17) ColumnarToRow -Input [2]: [cs_item_sk#11, cs_sold_date_sk#12] - -(18) Filter +(17) CometFilter Input [2]: [cs_item_sk#11, cs_sold_date_sk#12] Condition : isnotnull(cs_item_sk#11) -(19) Project -Output [1]: [cs_item_sk#11] +(18) CometProject Input [2]: [cs_item_sk#11, cs_sold_date_sk#12] +Arguments: [cs_item_sk#11], [cs_item_sk#11] + +(19) ColumnarToRow +Input [1]: [cs_item_sk#11] (20) BroadcastHashJoin [codegen id : 4] Left keys [1]: [i_item_sk#1] @@ -148,9 +148,9 @@ Arguments: 100, [i_item_id#2 ASC NULLS FIRST], [i_item_id#2, i_item_desc#3, i_cu Subquery:1 Hosting operator id = 5 Hosting Expression = inv_date_sk#8 IN dynamicpruning#9 BroadcastExchange (30) -+- * Project (29) - +- * Filter (28) - +- * ColumnarToRow (27) ++- * ColumnarToRow (29) + +- CometProject (28) + +- CometFilter (27) +- CometScan parquet spark_catalog.default.date_dim (26) @@ -161,16 +161,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-02-01), LessThanOrEqual(d_date,2000-04-01), IsNotNull(d_date_sk)] ReadSchema: struct -(27) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#10, d_date#13] - -(28) Filter [codegen id : 1] +(27) CometFilter Input [2]: [d_date_sk#10, d_date#13] Condition : (((isnotnull(d_date#13) AND (d_date#13 >= 2000-02-01)) AND (d_date#13 <= 2000-04-01)) AND isnotnull(d_date_sk#10)) -(29) Project [codegen id : 1] -Output [1]: [d_date_sk#10] +(28) CometProject Input [2]: [d_date_sk#10, d_date#13] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(29) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] (30) BroadcastExchange Input [1]: [d_date_sk#10] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt index 1b469ce06..65bb06348 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q37/simplified.txt @@ -14,31 +14,31 @@ TakeOrderedAndProject [i_item_id,i_item_desc,i_current_price] BroadcastHashJoin [inv_date_sk,d_date_sk] Project [i_item_sk,i_item_id,i_item_desc,i_current_price,inv_date_sk] BroadcastHashJoin [i_item_sk,inv_item_sk] - Project [i_item_sk,i_item_id,i_item_desc,i_current_price] - Filter [i_current_price,i_manufact_id,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_item_id,i_item_desc,i_current_price] + CometFilter [i_current_price,i_manufact_id,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_manufact_id] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [inv_item_sk,inv_date_sk] - Filter [inv_quantity_on_hand,inv_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [inv_item_sk,inv_date_sk] + CometFilter [inv_quantity_on_hand,inv_item_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_quantity_on_hand,inv_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter ReusedExchange [d_date_sk] #4 - Project [cs_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cs_item_sk] + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt index 66dd23ca6..5503439ee 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/explain.txt @@ -12,13 +12,13 @@ : : +- * BroadcastHashJoin Inner BuildRight (11) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.customer (7) : +- BroadcastExchange (28) : +- * HashAggregate (27) @@ -28,8 +28,8 @@ : +- * BroadcastHashJoin Inner BuildRight (23) : :- * Project (21) : : +- * BroadcastHashJoin Inner BuildRight (20) - : : :- * Filter (18) - : : : +- * ColumnarToRow (17) + : : :- * ColumnarToRow (18) + : : : +- CometFilter (17) : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) : : +- ReusedExchange (19) : +- ReusedExchange (22) @@ -41,8 +41,8 @@ +- * BroadcastHashJoin Inner BuildRight (37) :- * Project (35) : +- * BroadcastHashJoin Inner BuildRight (34) - : :- * Filter (32) - : : +- * ColumnarToRow (31) + : :- * ColumnarToRow (32) + : : +- CometFilter (31) : : +- CometScan parquet spark_catalog.default.web_sales (30) : +- ReusedExchange (33) +- ReusedExchange (36) @@ -56,12 +56,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#2), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] +Condition : isnotnull(ss_customer_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] -Condition : isnotnull(ss_customer_sk#1) (4) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#4, d_date#5] @@ -83,12 +83,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Condition : isnotnull(c_customer_sk#6) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] -Condition : isnotnull(c_customer_sk#6) (10) BroadcastExchange Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] @@ -130,12 +130,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#10), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_customer_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 6] +(17) CometFilter Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] +Condition : isnotnull(cs_bill_customer_sk#9) -(18) Filter [codegen id : 6] +(18) ColumnarToRow [codegen id : 6] Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] -Condition : isnotnull(cs_bill_customer_sk#9) (19) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#12, d_date#13] @@ -199,12 +199,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#18), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 10] +(31) CometFilter Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] +Condition : isnotnull(ws_bill_customer_sk#17) -(32) Filter [codegen id : 10] +(32) ColumnarToRow [codegen id : 10] Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] -Condition : isnotnull(ws_bill_customer_sk#17) (33) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#20, d_date#21] @@ -286,9 +286,9 @@ Results [1]: [count(1)#27 AS count(1)#28] Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#2 IN dynamicpruning#3 BroadcastExchange (52) -+- * Project (51) - +- * Filter (50) - +- * ColumnarToRow (49) ++- * ColumnarToRow (51) + +- CometProject (50) + +- CometFilter (49) +- CometScan parquet spark_catalog.default.date_dim (48) @@ -299,16 +299,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(49) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] - -(50) Filter [codegen id : 1] +(49) CometFilter Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] Condition : (((isnotnull(d_month_seq#29) AND (d_month_seq#29 >= 1200)) AND (d_month_seq#29 <= 1211)) AND isnotnull(d_date_sk#4)) -(51) Project [codegen id : 1] -Output [2]: [d_date_sk#4, d_date#5] +(50) CometProject Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Arguments: [d_date_sk#4, d_date#5], [d_date_sk#4, d_date#5] + +(51) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#4, d_date#5] (52) BroadcastExchange Input [2]: [d_date_sk#4, d_date#5] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt index 27489c0a9..315afe660 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q38/simplified.txt @@ -16,26 +16,26 @@ WholeStageCodegen (13) BroadcastHashJoin [ss_customer_sk,c_customer_sk] Project [ss_customer_sk,d_date] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk,d_date] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] InputAdapter ReusedExchange [d_date_sk,d_date] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] InputAdapter BroadcastExchange #5 @@ -49,9 +49,9 @@ WholeStageCodegen (13) BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] Project [cs_bill_customer_sk,d_date] BroadcastHashJoin [cs_sold_date_sk,d_date_sk] - Filter [cs_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -70,9 +70,9 @@ WholeStageCodegen (13) BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] Project [ws_bill_customer_sk,d_date] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt index 7dd8fcc08..d851f61bf 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/explain.txt @@ -13,16 +13,16 @@ : : +- * BroadcastHashJoin Inner BuildRight (14) : : :- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.inventory (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.item (4) : : +- BroadcastExchange (13) - : : +- * Filter (12) - : : +- * ColumnarToRow (11) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) : : +- CometScan parquet spark_catalog.default.warehouse (10) : +- ReusedExchange (16) +- BroadcastExchange (41) @@ -37,8 +37,8 @@ : +- * BroadcastHashJoin Inner BuildRight (31) : :- * Project (29) : : +- * BroadcastHashJoin Inner BuildRight (28) - : : :- * Filter (26) - : : : +- * ColumnarToRow (25) + : : :- * ColumnarToRow (26) + : : : +- CometFilter (25) : : : +- CometScan parquet spark_catalog.default.inventory (24) : : +- ReusedExchange (27) : +- ReusedExchange (30) @@ -53,12 +53,12 @@ PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_s PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] -Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) (4) Scan parquet spark_catalog.default.item Output [1]: [i_item_sk#6] @@ -67,12 +67,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [1]: [i_item_sk#6] +Condition : isnotnull(i_item_sk#6) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [1]: [i_item_sk#6] -Condition : isnotnull(i_item_sk#6) (7) BroadcastExchange Input [1]: [i_item_sk#6] @@ -95,12 +95,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Condition : isnotnull(w_warehouse_sk#7) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] -Condition : isnotnull(w_warehouse_sk#7) (13) BroadcastExchange Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] @@ -163,12 +163,12 @@ PartitionFilters: [isnotnull(inv_date_sk#29), dynamicpruningexpression(inv_date_ PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] ReadSchema: struct -(25) ColumnarToRow [codegen id : 8] +(25) CometFilter Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] +Condition : (isnotnull(inv_item_sk#26) AND isnotnull(inv_warehouse_sk#27)) -(26) Filter [codegen id : 8] +(26) ColumnarToRow [codegen id : 8] Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] -Condition : (isnotnull(inv_item_sk#26) AND isnotnull(inv_warehouse_sk#27)) (27) ReusedExchange [Reuses operator id: 7] Output [1]: [i_item_sk#31] @@ -257,9 +257,9 @@ Arguments: [w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 BroadcastExchange (49) -+- * Project (48) - +- * Filter (47) - +- * ColumnarToRow (46) ++- * ColumnarToRow (48) + +- CometProject (47) + +- CometFilter (46) +- CometScan parquet spark_catalog.default.date_dim (45) @@ -270,16 +270,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,1), IsNotNull(d_date_sk)] ReadSchema: struct -(46) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#9, d_year#49, d_moy#10] - -(47) Filter [codegen id : 1] +(46) CometFilter Input [3]: [d_date_sk#9, d_year#49, d_moy#10] Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#10)) AND (d_year#49 = 2001)) AND (d_moy#10 = 1)) AND isnotnull(d_date_sk#9)) -(48) Project [codegen id : 1] -Output [2]: [d_date_sk#9, d_moy#10] +(47) CometProject Input [3]: [d_date_sk#9, d_year#49, d_moy#10] +Arguments: [d_date_sk#9, d_moy#10], [d_date_sk#9, d_moy#10] + +(48) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#9, d_moy#10] (49) BroadcastExchange Input [2]: [d_date_sk#9, d_moy#10] @@ -287,9 +287,9 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)) Subquery:2 Hosting operator id = 24 Hosting Expression = inv_date_sk#29 IN dynamicpruning#30 BroadcastExchange (54) -+- * Project (53) - +- * Filter (52) - +- * ColumnarToRow (51) ++- * ColumnarToRow (53) + +- CometProject (52) + +- CometFilter (51) +- CometScan parquet spark_catalog.default.date_dim (50) @@ -300,16 +300,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)] ReadSchema: struct -(51) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#34, d_year#50, d_moy#35] - -(52) Filter [codegen id : 1] +(51) CometFilter Input [3]: [d_date_sk#34, d_year#50, d_moy#35] Condition : ((((isnotnull(d_year#50) AND isnotnull(d_moy#35)) AND (d_year#50 = 2001)) AND (d_moy#35 = 2)) AND isnotnull(d_date_sk#34)) -(53) Project [codegen id : 1] -Output [2]: [d_date_sk#34, d_moy#35] +(52) CometProject Input [3]: [d_date_sk#34, d_year#50, d_moy#35] +Arguments: [d_date_sk#34, d_moy#35], [d_date_sk#34, d_moy#35] + +(53) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#34, d_moy#35] (54) BroadcastExchange Input [2]: [d_date_sk#34, d_moy#35] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/simplified.txt index 138e386cb..002266e76 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39a/simplified.txt @@ -17,31 +17,31 @@ WholeStageCodegen (11) BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] BroadcastHashJoin [inv_item_sk,i_item_sk] - Filter [inv_item_sk,inv_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk,d_moy] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (2) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] InputAdapter ReusedExchange [d_date_sk,d_moy] #3 @@ -61,17 +61,17 @@ WholeStageCodegen (11) BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] BroadcastHashJoin [inv_item_sk,i_item_sk] - Filter [inv_item_sk,inv_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #8 WholeStageCodegen (1) - Project [d_date_sk,d_moy] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [i_item_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/explain.txt index 4befb027a..a4184150e 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/explain.txt @@ -13,16 +13,16 @@ : : +- * BroadcastHashJoin Inner BuildRight (14) : : :- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.inventory (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.item (4) : : +- BroadcastExchange (13) - : : +- * Filter (12) - : : +- * ColumnarToRow (11) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) : : +- CometScan parquet spark_catalog.default.warehouse (10) : +- ReusedExchange (16) +- BroadcastExchange (41) @@ -37,8 +37,8 @@ : +- * BroadcastHashJoin Inner BuildRight (31) : :- * Project (29) : : +- * BroadcastHashJoin Inner BuildRight (28) - : : :- * Filter (26) - : : : +- * ColumnarToRow (25) + : : :- * ColumnarToRow (26) + : : : +- CometFilter (25) : : : +- CometScan parquet spark_catalog.default.inventory (24) : : +- ReusedExchange (27) : +- ReusedExchange (30) @@ -53,12 +53,12 @@ PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_s PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] -Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) (4) Scan parquet spark_catalog.default.item Output [1]: [i_item_sk#6] @@ -67,12 +67,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [1]: [i_item_sk#6] +Condition : isnotnull(i_item_sk#6) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [1]: [i_item_sk#6] -Condition : isnotnull(i_item_sk#6) (7) BroadcastExchange Input [1]: [i_item_sk#6] @@ -95,12 +95,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] +Condition : isnotnull(w_warehouse_sk#7) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] -Condition : isnotnull(w_warehouse_sk#7) (13) BroadcastExchange Input [2]: [w_warehouse_sk#7, w_warehouse_name#8] @@ -163,12 +163,12 @@ PartitionFilters: [isnotnull(inv_date_sk#29), dynamicpruningexpression(inv_date_ PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] ReadSchema: struct -(25) ColumnarToRow [codegen id : 8] +(25) CometFilter Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] +Condition : (isnotnull(inv_item_sk#26) AND isnotnull(inv_warehouse_sk#27)) -(26) Filter [codegen id : 8] +(26) ColumnarToRow [codegen id : 8] Input [4]: [inv_item_sk#26, inv_warehouse_sk#27, inv_quantity_on_hand#28, inv_date_sk#29] -Condition : (isnotnull(inv_item_sk#26) AND isnotnull(inv_warehouse_sk#27)) (27) ReusedExchange [Reuses operator id: 7] Output [1]: [i_item_sk#31] @@ -257,9 +257,9 @@ Arguments: [w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 BroadcastExchange (49) -+- * Project (48) - +- * Filter (47) - +- * ColumnarToRow (46) ++- * ColumnarToRow (48) + +- CometProject (47) + +- CometFilter (46) +- CometScan parquet spark_catalog.default.date_dim (45) @@ -270,16 +270,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,1), IsNotNull(d_date_sk)] ReadSchema: struct -(46) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#9, d_year#49, d_moy#10] - -(47) Filter [codegen id : 1] +(46) CometFilter Input [3]: [d_date_sk#9, d_year#49, d_moy#10] Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#10)) AND (d_year#49 = 2001)) AND (d_moy#10 = 1)) AND isnotnull(d_date_sk#9)) -(48) Project [codegen id : 1] -Output [2]: [d_date_sk#9, d_moy#10] +(47) CometProject Input [3]: [d_date_sk#9, d_year#49, d_moy#10] +Arguments: [d_date_sk#9, d_moy#10], [d_date_sk#9, d_moy#10] + +(48) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#9, d_moy#10] (49) BroadcastExchange Input [2]: [d_date_sk#9, d_moy#10] @@ -287,9 +287,9 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)) Subquery:2 Hosting operator id = 24 Hosting Expression = inv_date_sk#29 IN dynamicpruning#30 BroadcastExchange (54) -+- * Project (53) - +- * Filter (52) - +- * ColumnarToRow (51) ++- * ColumnarToRow (53) + +- CometProject (52) + +- CometFilter (51) +- CometScan parquet spark_catalog.default.date_dim (50) @@ -300,16 +300,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)] ReadSchema: struct -(51) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#34, d_year#50, d_moy#35] - -(52) Filter [codegen id : 1] +(51) CometFilter Input [3]: [d_date_sk#34, d_year#50, d_moy#35] Condition : ((((isnotnull(d_year#50) AND isnotnull(d_moy#35)) AND (d_year#50 = 2001)) AND (d_moy#35 = 2)) AND isnotnull(d_date_sk#34)) -(53) Project [codegen id : 1] -Output [2]: [d_date_sk#34, d_moy#35] +(52) CometProject Input [3]: [d_date_sk#34, d_year#50, d_moy#35] +Arguments: [d_date_sk#34, d_moy#35], [d_date_sk#34, d_moy#35] + +(53) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#34, d_moy#35] (54) BroadcastExchange Input [2]: [d_date_sk#34, d_moy#35] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/simplified.txt index 138e386cb..002266e76 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q39b/simplified.txt @@ -17,31 +17,31 @@ WholeStageCodegen (11) BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] BroadcastHashJoin [inv_item_sk,i_item_sk] - Filter [inv_item_sk,inv_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk,d_moy] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (2) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] InputAdapter ReusedExchange [d_date_sk,d_moy] #3 @@ -61,17 +61,17 @@ WholeStageCodegen (11) BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] Project [inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk,i_item_sk] BroadcastHashJoin [inv_item_sk,i_item_sk] - Filter [inv_item_sk,inv_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #8 WholeStageCodegen (1) - Project [d_date_sk,d_moy] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [i_item_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/explain.txt index 3bc53a09a..a854a1041 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/explain.txt @@ -17,12 +17,12 @@ TakeOrderedAndProject (108) : : : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : : : :- * Project (9) : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : : : :- * Filter (3) - : : : : : : : +- * ColumnarToRow (2) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) : : : : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : : : : +- BroadcastExchange (7) - : : : : : : +- * Filter (6) - : : : : : : +- * ColumnarToRow (5) + : : : : : : +- * ColumnarToRow (6) + : : : : : : +- CometFilter (5) : : : : : : +- CometScan parquet spark_catalog.default.store_sales (4) : : : : : +- ReusedExchange (10) : : : : +- BroadcastExchange (32) @@ -33,12 +33,12 @@ TakeOrderedAndProject (108) : : : : +- * BroadcastHashJoin Inner BuildRight (27) : : : : :- * Project (25) : : : : : +- * BroadcastHashJoin Inner BuildRight (24) - : : : : : :- * Filter (19) - : : : : : : +- * ColumnarToRow (18) + : : : : : :- * ColumnarToRow (19) + : : : : : : +- CometFilter (18) : : : : : : +- CometScan parquet spark_catalog.default.customer (17) : : : : : +- BroadcastExchange (23) - : : : : : +- * Filter (22) - : : : : : +- * ColumnarToRow (21) + : : : : : +- * ColumnarToRow (22) + : : : : : +- CometFilter (21) : : : : : +- CometScan parquet spark_catalog.default.store_sales (20) : : : : +- ReusedExchange (26) : : : +- BroadcastExchange (50) @@ -50,12 +50,12 @@ TakeOrderedAndProject (108) : : : +- * BroadcastHashJoin Inner BuildRight (44) : : : :- * Project (42) : : : : +- * BroadcastHashJoin Inner BuildRight (41) - : : : : :- * Filter (36) - : : : : : +- * ColumnarToRow (35) + : : : : :- * ColumnarToRow (36) + : : : : : +- CometFilter (35) : : : : : +- CometScan parquet spark_catalog.default.customer (34) : : : : +- BroadcastExchange (40) - : : : : +- * Filter (39) - : : : : +- * ColumnarToRow (38) + : : : : +- * ColumnarToRow (39) + : : : : +- CometFilter (38) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (37) : : : +- ReusedExchange (43) : : +- BroadcastExchange (68) @@ -66,12 +66,12 @@ TakeOrderedAndProject (108) : : +- * BroadcastHashJoin Inner BuildRight (63) : : :- * Project (61) : : : +- * BroadcastHashJoin Inner BuildRight (60) - : : : :- * Filter (55) - : : : : +- * ColumnarToRow (54) + : : : :- * ColumnarToRow (55) + : : : : +- CometFilter (54) : : : : +- CometScan parquet spark_catalog.default.customer (53) : : : +- BroadcastExchange (59) - : : : +- * Filter (58) - : : : +- * ColumnarToRow (57) + : : : +- * ColumnarToRow (58) + : : : +- CometFilter (57) : : : +- CometScan parquet spark_catalog.default.catalog_sales (56) : : +- ReusedExchange (62) : +- BroadcastExchange (87) @@ -83,12 +83,12 @@ TakeOrderedAndProject (108) : +- * BroadcastHashJoin Inner BuildRight (81) : :- * Project (79) : : +- * BroadcastHashJoin Inner BuildRight (78) - : : :- * Filter (73) - : : : +- * ColumnarToRow (72) + : : :- * ColumnarToRow (73) + : : : +- CometFilter (72) : : : +- CometScan parquet spark_catalog.default.customer (71) : : +- BroadcastExchange (77) - : : +- * Filter (76) - : : +- * ColumnarToRow (75) + : : +- * ColumnarToRow (76) + : : +- CometFilter (75) : : +- CometScan parquet spark_catalog.default.web_sales (74) : +- ReusedExchange (80) +- BroadcastExchange (105) @@ -99,12 +99,12 @@ TakeOrderedAndProject (108) +- * BroadcastHashJoin Inner BuildRight (100) :- * Project (98) : +- * BroadcastHashJoin Inner BuildRight (97) - : :- * Filter (92) - : : +- * ColumnarToRow (91) + : :- * ColumnarToRow (92) + : : +- CometFilter (91) : : +- CometScan parquet spark_catalog.default.customer (90) : +- BroadcastExchange (96) - : +- * Filter (95) - : +- * ColumnarToRow (94) + : +- * ColumnarToRow (95) + : +- CometFilter (94) : +- CometScan parquet spark_catalog.default.web_sales (93) +- ReusedExchange (99) @@ -116,12 +116,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] -Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) (4) Scan parquet spark_catalog.default.store_sales Output [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] @@ -131,12 +131,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#14), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] +Condition : isnotnull(ss_customer_sk#9) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] -Condition : isnotnull(ss_customer_sk#9) (7) BroadcastExchange Input [6]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_sales_price#11, ss_ext_wholesale_cost#12, ss_ext_list_price#13, ss_sold_date_sk#14] @@ -194,12 +194,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 6] +(18) CometFilter Input [8]: [c_customer_sk#25, c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32] +Condition : (isnotnull(c_customer_sk#25) AND isnotnull(c_customer_id#26)) -(19) Filter [codegen id : 6] +(19) ColumnarToRow [codegen id : 6] Input [8]: [c_customer_sk#25, c_customer_id#26, c_first_name#27, c_last_name#28, c_preferred_cust_flag#29, c_birth_country#30, c_login#31, c_email_address#32] -Condition : (isnotnull(c_customer_sk#25) AND isnotnull(c_customer_id#26)) (20) Scan parquet spark_catalog.default.store_sales Output [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] @@ -209,12 +209,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#38), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] +(21) CometFilter Input [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] +Condition : isnotnull(ss_customer_sk#33) -(22) Filter [codegen id : 4] +(22) ColumnarToRow [codegen id : 4] Input [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] -Condition : isnotnull(ss_customer_sk#33) (23) BroadcastExchange Input [6]: [ss_customer_sk#33, ss_ext_discount_amt#34, ss_ext_sales_price#35, ss_ext_wholesale_cost#36, ss_ext_list_price#37, ss_sold_date_sk#38] @@ -278,12 +278,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 10] +(35) CometFilter Input [8]: [c_customer_sk#54, c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61] +Condition : (isnotnull(c_customer_sk#54) AND isnotnull(c_customer_id#55)) -(36) Filter [codegen id : 10] +(36) ColumnarToRow [codegen id : 10] Input [8]: [c_customer_sk#54, c_customer_id#55, c_first_name#56, c_last_name#57, c_preferred_cust_flag#58, c_birth_country#59, c_login#60, c_email_address#61] -Condition : (isnotnull(c_customer_sk#54) AND isnotnull(c_customer_id#55)) (37) Scan parquet spark_catalog.default.catalog_sales Output [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] @@ -293,12 +293,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#67), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_customer_sk)] ReadSchema: struct -(38) ColumnarToRow [codegen id : 8] +(38) CometFilter Input [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] +Condition : isnotnull(cs_bill_customer_sk#62) -(39) Filter [codegen id : 8] +(39) ColumnarToRow [codegen id : 8] Input [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] -Condition : isnotnull(cs_bill_customer_sk#62) (40) BroadcastExchange Input [6]: [cs_bill_customer_sk#62, cs_ext_discount_amt#63, cs_ext_sales_price#64, cs_ext_wholesale_cost#65, cs_ext_list_price#66, cs_sold_date_sk#67] @@ -370,12 +370,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(54) ColumnarToRow [codegen id : 14] +(54) CometFilter Input [8]: [c_customer_sk#78, c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85] +Condition : (isnotnull(c_customer_sk#78) AND isnotnull(c_customer_id#79)) -(55) Filter [codegen id : 14] +(55) ColumnarToRow [codegen id : 14] Input [8]: [c_customer_sk#78, c_customer_id#79, c_first_name#80, c_last_name#81, c_preferred_cust_flag#82, c_birth_country#83, c_login#84, c_email_address#85] -Condition : (isnotnull(c_customer_sk#78) AND isnotnull(c_customer_id#79)) (56) Scan parquet spark_catalog.default.catalog_sales Output [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] @@ -385,12 +385,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#91), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_customer_sk)] ReadSchema: struct -(57) ColumnarToRow [codegen id : 12] +(57) CometFilter Input [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] +Condition : isnotnull(cs_bill_customer_sk#86) -(58) Filter [codegen id : 12] +(58) ColumnarToRow [codegen id : 12] Input [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] -Condition : isnotnull(cs_bill_customer_sk#86) (59) BroadcastExchange Input [6]: [cs_bill_customer_sk#86, cs_ext_discount_amt#87, cs_ext_sales_price#88, cs_ext_wholesale_cost#89, cs_ext_list_price#90, cs_sold_date_sk#91] @@ -458,12 +458,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(72) ColumnarToRow [codegen id : 18] +(72) CometFilter Input [8]: [c_customer_sk#101, c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108] +Condition : (isnotnull(c_customer_sk#101) AND isnotnull(c_customer_id#102)) -(73) Filter [codegen id : 18] +(73) ColumnarToRow [codegen id : 18] Input [8]: [c_customer_sk#101, c_customer_id#102, c_first_name#103, c_last_name#104, c_preferred_cust_flag#105, c_birth_country#106, c_login#107, c_email_address#108] -Condition : (isnotnull(c_customer_sk#101) AND isnotnull(c_customer_id#102)) (74) Scan parquet spark_catalog.default.web_sales Output [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] @@ -473,12 +473,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#114), dynamicpruningexpression(ws_s PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(75) ColumnarToRow [codegen id : 16] +(75) CometFilter Input [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] +Condition : isnotnull(ws_bill_customer_sk#109) -(76) Filter [codegen id : 16] +(76) ColumnarToRow [codegen id : 16] Input [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] -Condition : isnotnull(ws_bill_customer_sk#109) (77) BroadcastExchange Input [6]: [ws_bill_customer_sk#109, ws_ext_discount_amt#110, ws_ext_sales_price#111, ws_ext_wholesale_cost#112, ws_ext_list_price#113, ws_sold_date_sk#114] @@ -550,12 +550,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(91) ColumnarToRow [codegen id : 22] +(91) CometFilter Input [8]: [c_customer_sk#125, c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132] +Condition : (isnotnull(c_customer_sk#125) AND isnotnull(c_customer_id#126)) -(92) Filter [codegen id : 22] +(92) ColumnarToRow [codegen id : 22] Input [8]: [c_customer_sk#125, c_customer_id#126, c_first_name#127, c_last_name#128, c_preferred_cust_flag#129, c_birth_country#130, c_login#131, c_email_address#132] -Condition : (isnotnull(c_customer_sk#125) AND isnotnull(c_customer_id#126)) (93) Scan parquet spark_catalog.default.web_sales Output [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] @@ -565,12 +565,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#138), dynamicpruningexpression(ws_s PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(94) ColumnarToRow [codegen id : 20] +(94) CometFilter Input [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] +Condition : isnotnull(ws_bill_customer_sk#133) -(95) Filter [codegen id : 20] +(95) ColumnarToRow [codegen id : 20] Input [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] -Condition : isnotnull(ws_bill_customer_sk#133) (96) BroadcastExchange Input [6]: [ws_bill_customer_sk#133, ws_ext_discount_amt#134, ws_ext_sales_price#135, ws_ext_wholesale_cost#136, ws_ext_list_price#137, ws_sold_date_sk#138] @@ -639,8 +639,8 @@ Arguments: 100, [customer_id#46 ASC NULLS FIRST, customer_first_name#47 ASC NULL Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#14 IN dynamicpruning#15 BroadcastExchange (112) -+- * Filter (111) - +- * ColumnarToRow (110) ++- * ColumnarToRow (111) + +- CometFilter (110) +- CometScan parquet spark_catalog.default.date_dim (109) @@ -651,12 +651,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(110) ColumnarToRow [codegen id : 1] +(110) CometFilter Input [2]: [d_date_sk#16, d_year#17] +Condition : ((isnotnull(d_year#17) AND (d_year#17 = 2001)) AND isnotnull(d_date_sk#16)) -(111) Filter [codegen id : 1] +(111) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#16, d_year#17] -Condition : ((isnotnull(d_year#17) AND (d_year#17 = 2001)) AND isnotnull(d_date_sk#16)) (112) BroadcastExchange Input [2]: [d_date_sk#16, d_year#17] @@ -664,8 +664,8 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint) Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#38 IN dynamicpruning#39 BroadcastExchange (116) -+- * Filter (115) - +- * ColumnarToRow (114) ++- * ColumnarToRow (115) + +- CometFilter (114) +- CometScan parquet spark_catalog.default.date_dim (113) @@ -676,12 +676,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] ReadSchema: struct -(114) ColumnarToRow [codegen id : 1] +(114) CometFilter Input [2]: [d_date_sk#40, d_year#41] +Condition : ((isnotnull(d_year#41) AND (d_year#41 = 2002)) AND isnotnull(d_date_sk#40)) -(115) Filter [codegen id : 1] +(115) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#40, d_year#41] -Condition : ((isnotnull(d_year#41) AND (d_year#41 = 2002)) AND isnotnull(d_date_sk#40)) (116) BroadcastExchange Input [2]: [d_date_sk#40, d_year#41] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/simplified.txt index f21b1c557..99e255a0e 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q4/simplified.txt @@ -19,23 +19,23 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,custom BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #3 @@ -51,23 +51,23 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,custom BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #6 WholeStageCodegen (4) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_sales_price,ss_ext_wholesale_cost,ss_ext_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #7 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #7 @@ -84,16 +84,16 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,custom BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] BroadcastHashJoin [c_customer_sk,cs_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #10 WholeStageCodegen (8) - Filter [cs_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -110,16 +110,16 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,custom BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] BroadcastHashJoin [c_customer_sk,cs_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #13 WholeStageCodegen (12) - Filter [cs_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_ext_discount_amt,cs_ext_sales_price,cs_ext_wholesale_cost,cs_ext_list_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter @@ -137,16 +137,16 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,custom BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #16 WholeStageCodegen (16) - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -163,16 +163,16 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,custom BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #19 WholeStageCodegen (20) - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_sales_price,ws_ext_wholesale_cost,ws_ext_list_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/explain.txt index 67e36b91f..f63b94658 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/explain.txt @@ -13,23 +13,23 @@ TakeOrderedAndProject (33) : : : +- * SortMergeJoin LeftOuter (12) : : : :- * Sort (5) : : : : +- Exchange (4) - : : : : +- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : : +- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : +- * Sort (11) : : : +- Exchange (10) - : : : +- * Project (9) - : : : +- * Filter (8) - : : : +- * ColumnarToRow (7) + : : : +- * ColumnarToRow (9) + : : : +- CometProject (8) + : : : +- CometFilter (7) : : : +- CometScan parquet spark_catalog.default.catalog_returns (6) : : +- BroadcastExchange (17) - : : +- * Filter (16) - : : +- * ColumnarToRow (15) + : : +- * ColumnarToRow (16) + : : +- CometFilter (15) : : +- CometScan parquet spark_catalog.default.warehouse (14) : +- BroadcastExchange (24) - : +- * Project (23) - : +- * Filter (22) - : +- * ColumnarToRow (21) + : +- * ColumnarToRow (23) + : +- CometProject (22) + : +- CometFilter (21) : +- CometScan parquet spark_catalog.default.item (20) +- ReusedExchange (27) @@ -42,12 +42,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_warehouse_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] +(2) CometFilter Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] +Condition : (isnotnull(cs_warehouse_sk#1) AND isnotnull(cs_item_sk#2)) -(3) Filter [codegen id : 1] +(3) ColumnarToRow [codegen id : 1] Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] -Condition : (isnotnull(cs_warehouse_sk#1) AND isnotnull(cs_item_sk#2)) (4) Exchange Input [5]: [cs_warehouse_sk#1, cs_item_sk#2, cs_order_number#3, cs_sales_price#4, cs_sold_date_sk#5] @@ -64,16 +64,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] ReadSchema: struct -(7) ColumnarToRow [codegen id : 3] -Input [4]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9, cr_returned_date_sk#10] - -(8) Filter [codegen id : 3] +(7) CometFilter Input [4]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9, cr_returned_date_sk#10] Condition : (isnotnull(cr_order_number#8) AND isnotnull(cr_item_sk#7)) -(9) Project [codegen id : 3] -Output [3]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] +(8) CometProject Input [4]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9, cr_returned_date_sk#10] +Arguments: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9], [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] + +(9) ColumnarToRow [codegen id : 3] +Input [3]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] (10) Exchange Input [3]: [cr_item_sk#7, cr_order_number#8, cr_refunded_cash#9] @@ -100,12 +100,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 5] +(15) CometFilter Input [2]: [w_warehouse_sk#11, w_state#12] +Condition : isnotnull(w_warehouse_sk#11) -(16) Filter [codegen id : 5] +(16) ColumnarToRow [codegen id : 5] Input [2]: [w_warehouse_sk#11, w_state#12] -Condition : isnotnull(w_warehouse_sk#11) (17) BroadcastExchange Input [2]: [w_warehouse_sk#11, w_state#12] @@ -128,16 +128,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,0.99), LessThanOrEqual(i_current_price,1.49), IsNotNull(i_item_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 6] -Input [3]: [i_item_sk#13, i_item_id#14, i_current_price#15] - -(22) Filter [codegen id : 6] +(21) CometFilter Input [3]: [i_item_sk#13, i_item_id#14, i_current_price#15] Condition : (((isnotnull(i_current_price#15) AND (i_current_price#15 >= 0.99)) AND (i_current_price#15 <= 1.49)) AND isnotnull(i_item_sk#13)) -(23) Project [codegen id : 6] -Output [2]: [i_item_sk#13, i_item_id#14] +(22) CometProject Input [3]: [i_item_sk#13, i_item_id#14, i_current_price#15] +Arguments: [i_item_sk#13, i_item_id#14], [i_item_sk#13, i_item_id#14] + +(23) ColumnarToRow [codegen id : 6] +Input [2]: [i_item_sk#13, i_item_id#14] (24) BroadcastExchange Input [2]: [i_item_sk#13, i_item_id#14] @@ -192,8 +192,8 @@ Arguments: 100, [w_state#12 ASC NULLS FIRST, i_item_id#14 ASC NULLS FIRST], [w_s Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (37) -+- * Filter (36) - +- * ColumnarToRow (35) ++- * ColumnarToRow (36) + +- CometFilter (35) +- CometScan parquet spark_catalog.default.date_dim (34) @@ -204,12 +204,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-02-10), LessThanOrEqual(d_date,2000-04-10), IsNotNull(d_date_sk)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 1] +(35) CometFilter Input [2]: [d_date_sk#16, d_date#17] +Condition : (((isnotnull(d_date#17) AND (d_date#17 >= 2000-02-10)) AND (d_date#17 <= 2000-04-10)) AND isnotnull(d_date_sk#16)) -(36) Filter [codegen id : 1] +(36) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#16, d_date#17] -Condition : (((isnotnull(d_date#17) AND (d_date#17 >= 2000-02-10)) AND (d_date#17 <= 2000-04-10)) AND isnotnull(d_date_sk#16)) (37) BroadcastExchange Input [2]: [d_date_sk#16, d_date#17] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/simplified.txt index 6234f2520..10e0735b4 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q40/simplified.txt @@ -19,16 +19,16 @@ TakeOrderedAndProject [w_state,i_item_id,sales_before,sales_after] InputAdapter Exchange [cs_order_number,cs_item_sk] #2 WholeStageCodegen (1) - Filter [cs_warehouse_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_warehouse_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_warehouse_sk,cs_item_sk,cs_order_number,cs_sales_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter WholeStageCodegen (4) @@ -36,25 +36,25 @@ TakeOrderedAndProject [w_state,i_item_id,sales_before,sales_after] InputAdapter Exchange [cr_order_number,cr_item_sk] #4 WholeStageCodegen (3) - Project [cr_item_sk,cr_order_number,cr_refunded_cash] - Filter [cr_order_number,cr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_refunded_cash] + CometFilter [cr_order_number,cr_item_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_refunded_cash,cr_returned_date_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (5) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_state] InputAdapter BroadcastExchange #6 WholeStageCodegen (6) - Project [i_item_sk,i_item_id] - Filter [i_current_price,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_item_id] + CometFilter [i_current_price,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_current_price] InputAdapter ReusedExchange [d_date_sk,d_date] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/explain.txt index 38fe288b5..07196ba8c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/explain.txt @@ -5,19 +5,19 @@ TakeOrderedAndProject (20) +- * HashAggregate (17) +- * Project (16) +- * BroadcastHashJoin Inner BuildRight (15) - :- * Project (4) - : +- * Filter (3) - : +- * ColumnarToRow (2) + :- * ColumnarToRow (4) + : +- CometProject (3) + : +- CometFilter (2) : +- CometScan parquet spark_catalog.default.item (1) +- BroadcastExchange (14) +- * Project (13) +- * Filter (12) +- * HashAggregate (11) +- Exchange (10) - +- * HashAggregate (9) - +- * Project (8) - +- * Filter (7) - +- * ColumnarToRow (6) + +- * ColumnarToRow (9) + +- CometHashAggregate (8) + +- CometProject (7) + +- CometFilter (6) +- CometScan parquet spark_catalog.default.item (5) @@ -28,16 +28,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_manufact_id), GreaterThanOrEqual(i_manufact_id,738), LessThanOrEqual(i_manufact_id,778), IsNotNull(i_manufact)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] -Input [3]: [i_manufact_id#1, i_manufact#2, i_product_name#3] - -(3) Filter [codegen id : 3] +(2) CometFilter Input [3]: [i_manufact_id#1, i_manufact#2, i_product_name#3] Condition : (((isnotnull(i_manufact_id#1) AND (i_manufact_id#1 >= 738)) AND (i_manufact_id#1 <= 778)) AND isnotnull(i_manufact#2)) -(4) Project [codegen id : 3] -Output [2]: [i_manufact#2, i_product_name#3] +(3) CometProject Input [3]: [i_manufact_id#1, i_manufact#2, i_product_name#3] +Arguments: [i_manufact#2, i_product_name#3], [i_manufact#2, i_product_name#3] + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [i_manufact#2, i_product_name#3] (5) Scan parquet spark_catalog.default.item Output [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] @@ -46,42 +46,40 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [Or(Or(And(EqualTo(i_category,Women ),Or(And(And(Or(EqualTo(i_color,powder ),EqualTo(i_color,khaki )),Or(EqualTo(i_units,Ounce ),EqualTo(i_units,Oz ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large ))),And(And(Or(EqualTo(i_color,brown ),EqualTo(i_color,honeydew )),Or(EqualTo(i_units,Bunch ),EqualTo(i_units,Ton ))),Or(EqualTo(i_size,N/A ),EqualTo(i_size,small ))))),And(EqualTo(i_category,Men ),Or(And(And(Or(EqualTo(i_color,floral ),EqualTo(i_color,deep )),Or(EqualTo(i_units,N/A ),EqualTo(i_units,Dozen ))),Or(EqualTo(i_size,petite ),EqualTo(i_size,large ))),And(And(Or(EqualTo(i_color,light ),EqualTo(i_color,cornflower )),Or(EqualTo(i_units,Box ),EqualTo(i_units,Pound ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large )))))),Or(And(EqualTo(i_category,Women ),Or(And(And(Or(EqualTo(i_color,midnight ),EqualTo(i_color,snow )),Or(EqualTo(i_units,Pallet ),EqualTo(i_units,Gross ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large ))),And(And(Or(EqualTo(i_color,cyan ),EqualTo(i_color,papaya )),Or(EqualTo(i_units,Cup ),EqualTo(i_units,Dram ))),Or(EqualTo(i_size,N/A ),EqualTo(i_size,small ))))),And(EqualTo(i_category,Men ),Or(And(And(Or(EqualTo(i_color,orange ),EqualTo(i_color,frosted )),Or(EqualTo(i_units,Each ),EqualTo(i_units,Tbl ))),Or(EqualTo(i_size,petite ),EqualTo(i_size,large ))),And(And(Or(EqualTo(i_color,forest ),EqualTo(i_color,ghost )),Or(EqualTo(i_units,Lb ),EqualTo(i_units,Bundle ))),Or(EqualTo(i_size,medium ),EqualTo(i_size,extra large ))))))), IsNotNull(i_manufact)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] -Input [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] - -(7) Filter [codegen id : 1] +(6) CometFilter Input [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] Condition : (((((i_category#4 = Women ) AND (((((i_color#7 = powder ) OR (i_color#7 = khaki )) AND ((i_units#8 = Ounce ) OR (i_units#8 = Oz ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large ))) OR ((((i_color#7 = brown ) OR (i_color#7 = honeydew )) AND ((i_units#8 = Bunch ) OR (i_units#8 = Ton ))) AND ((i_size#6 = N/A ) OR (i_size#6 = small ))))) OR ((i_category#4 = Men ) AND (((((i_color#7 = floral ) OR (i_color#7 = deep )) AND ((i_units#8 = N/A ) OR (i_units#8 = Dozen ))) AND ((i_size#6 = petite ) OR (i_size#6 = large ))) OR ((((i_color#7 = light ) OR (i_color#7 = cornflower )) AND ((i_units#8 = Box ) OR (i_units#8 = Pound ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large )))))) OR (((i_category#4 = Women ) AND (((((i_color#7 = midnight ) OR (i_color#7 = snow )) AND ((i_units#8 = Pallet ) OR (i_units#8 = Gross ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large ))) OR ((((i_color#7 = cyan ) OR (i_color#7 = papaya )) AND ((i_units#8 = Cup ) OR (i_units#8 = Dram ))) AND ((i_size#6 = N/A ) OR (i_size#6 = small ))))) OR ((i_category#4 = Men ) AND (((((i_color#7 = orange ) OR (i_color#7 = frosted )) AND ((i_units#8 = Each ) OR (i_units#8 = Tbl ))) AND ((i_size#6 = petite ) OR (i_size#6 = large ))) OR ((((i_color#7 = forest ) OR (i_color#7 = ghost )) AND ((i_units#8 = Lb ) OR (i_units#8 = Bundle ))) AND ((i_size#6 = medium ) OR (i_size#6 = extra large ))))))) AND isnotnull(i_manufact#5)) -(8) Project [codegen id : 1] -Output [1]: [i_manufact#5] +(7) CometProject Input [5]: [i_category#4, i_manufact#5, i_size#6, i_color#7, i_units#8] +Arguments: [i_manufact#5], [i_manufact#5] -(9) HashAggregate [codegen id : 1] +(8) CometHashAggregate Input [1]: [i_manufact#5] Keys [1]: [i_manufact#5] Functions [1]: [partial_count(1)] -Aggregate Attributes [1]: [count#9] -Results [2]: [i_manufact#5, count#10] + +(9) ColumnarToRow [codegen id : 1] +Input [2]: [i_manufact#5, count#9] (10) Exchange -Input [2]: [i_manufact#5, count#10] +Input [2]: [i_manufact#5, count#9] Arguments: hashpartitioning(i_manufact#5, 5), ENSURE_REQUIREMENTS, [plan_id=1] (11) HashAggregate [codegen id : 2] -Input [2]: [i_manufact#5, count#10] +Input [2]: [i_manufact#5, count#9] Keys [1]: [i_manufact#5] Functions [1]: [count(1)] -Aggregate Attributes [1]: [count(1)#11] -Results [2]: [count(1)#11 AS item_cnt#12, i_manufact#5] +Aggregate Attributes [1]: [count(1)#10] +Results [2]: [count(1)#10 AS item_cnt#11, i_manufact#5] (12) Filter [codegen id : 2] -Input [2]: [item_cnt#12, i_manufact#5] -Condition : (item_cnt#12 > 0) +Input [2]: [item_cnt#11, i_manufact#5] +Condition : (item_cnt#11 > 0) (13) Project [codegen id : 2] Output [1]: [i_manufact#5] -Input [2]: [item_cnt#12, i_manufact#5] +Input [2]: [item_cnt#11, i_manufact#5] (14) BroadcastExchange Input [1]: [i_manufact#5] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/simplified.txt index 3d12af6f4..e31217066 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q41/simplified.txt @@ -7,10 +7,10 @@ TakeOrderedAndProject [i_product_name] HashAggregate [i_product_name] Project [i_product_name] BroadcastHashJoin [i_manufact,i_manufact] - Project [i_manufact,i_product_name] - Filter [i_manufact_id,i_manufact] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_manufact,i_product_name] + CometFilter [i_manufact_id,i_manufact] CometScan parquet spark_catalog.default.item [i_manufact_id,i_manufact,i_product_name] InputAdapter BroadcastExchange #2 @@ -21,9 +21,9 @@ TakeOrderedAndProject [i_product_name] InputAdapter Exchange [i_manufact] #3 WholeStageCodegen (1) - HashAggregate [i_manufact] [count,count] - Project [i_manufact] - Filter [i_category,i_color,i_units,i_size,i_manufact] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometHashAggregate [i_manufact] + CometProject [i_manufact] + CometFilter [i_category,i_color,i_units,i_size,i_manufact] CometScan parquet spark_catalog.default.item [i_category,i_manufact,i_size,i_color,i_units] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/explain.txt index b458c6b45..d51d63d8a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/explain.txt @@ -7,18 +7,18 @@ TakeOrderedAndProject (21) +- * BroadcastHashJoin Inner BuildRight (16) :- * Project (10) : +- * BroadcastHashJoin Inner BuildRight (9) - : :- * Project (4) - : : +- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.date_dim (1) : +- BroadcastExchange (8) - : +- * Filter (7) - : +- * ColumnarToRow (6) + : +- * ColumnarToRow (7) + : +- CometFilter (6) : +- CometScan parquet spark_catalog.default.store_sales (5) +- BroadcastExchange (15) - +- * Project (14) - +- * Filter (13) - +- * ColumnarToRow (12) + +- * ColumnarToRow (14) + +- CometProject (13) + +- CometFilter (12) +- CometScan parquet spark_catalog.default.item (11) @@ -29,16 +29,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] -Input [3]: [d_date_sk#1, d_year#2, d_moy#3] - -(3) Filter [codegen id : 3] +(2) CometFilter Input [3]: [d_date_sk#1, d_year#2, d_moy#3] Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 2000)) AND isnotnull(d_date_sk#1)) -(4) Project [codegen id : 3] -Output [2]: [d_date_sk#1, d_year#2] +(3) CometProject Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Arguments: [d_date_sk#1, d_year#2], [d_date_sk#1, d_year#2] + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [d_date_sk#1, d_year#2] (5) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] @@ -48,12 +48,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] +(6) CometFilter Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) -(7) Filter [codegen id : 1] +(7) ColumnarToRow [codegen id : 1] Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] -Condition : isnotnull(ss_item_sk#4) (8) BroadcastExchange Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] @@ -76,16 +76,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,1), IsNotNull(i_item_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] -Input [4]: [i_item_sk#7, i_category_id#8, i_category#9, i_manager_id#10] - -(13) Filter [codegen id : 2] +(12) CometFilter Input [4]: [i_item_sk#7, i_category_id#8, i_category#9, i_manager_id#10] Condition : ((isnotnull(i_manager_id#10) AND (i_manager_id#10 = 1)) AND isnotnull(i_item_sk#7)) -(14) Project [codegen id : 2] -Output [3]: [i_item_sk#7, i_category_id#8, i_category#9] +(13) CometProject Input [4]: [i_item_sk#7, i_category_id#8, i_category#9, i_manager_id#10] +Arguments: [i_item_sk#7, i_category_id#8, i_category#9], [i_item_sk#7, i_category_id#8, i_category#9] + +(14) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#7, i_category_id#8, i_category#9] (15) BroadcastExchange Input [3]: [i_item_sk#7, i_category_id#8, i_category#9] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/simplified.txt index 2b6ed6411..67906b8c7 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q42/simplified.txt @@ -9,23 +9,23 @@ TakeOrderedAndProject [sum(ss_ext_sales_price),d_year,i_category_id,i_category] BroadcastHashJoin [ss_item_sk,i_item_sk] Project [d_year,ss_item_sk,ss_ext_sales_price] BroadcastHashJoin [d_date_sk,ss_sold_date_sk] - Project [d_date_sk,d_year] - Filter [d_moy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_year] + CometFilter [d_moy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [i_item_sk,i_category_id,i_category] - Filter [i_manager_id,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_category_id,i_category] + CometFilter [i_manager_id,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_category_id,i_category,i_manager_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/explain.txt index 925d9f3df..e892aa469 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/explain.txt @@ -7,18 +7,18 @@ TakeOrderedAndProject (21) +- * BroadcastHashJoin Inner BuildRight (16) :- * Project (10) : +- * BroadcastHashJoin Inner BuildRight (9) - : :- * Project (4) - : : +- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.date_dim (1) : +- BroadcastExchange (8) - : +- * Filter (7) - : +- * ColumnarToRow (6) + : +- * ColumnarToRow (7) + : +- CometFilter (6) : +- CometScan parquet spark_catalog.default.store_sales (5) +- BroadcastExchange (15) - +- * Project (14) - +- * Filter (13) - +- * ColumnarToRow (12) + +- * ColumnarToRow (14) + +- CometProject (13) + +- CometFilter (12) +- CometScan parquet spark_catalog.default.store (11) @@ -29,16 +29,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] -Input [3]: [d_date_sk#1, d_year#2, d_day_name#3] - -(3) Filter [codegen id : 3] +(2) CometFilter Input [3]: [d_date_sk#1, d_year#2, d_day_name#3] Condition : ((isnotnull(d_year#2) AND (d_year#2 = 2000)) AND isnotnull(d_date_sk#1)) -(4) Project [codegen id : 3] -Output [2]: [d_date_sk#1, d_day_name#3] +(3) CometProject Input [3]: [d_date_sk#1, d_year#2, d_day_name#3] +Arguments: [d_date_sk#1, d_day_name#3], [d_date_sk#1, d_day_name#3] + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [d_date_sk#1, d_day_name#3] (5) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] @@ -48,12 +48,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] +(6) CometFilter Input [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_store_sk#4) -(7) Filter [codegen id : 1] +(7) ColumnarToRow [codegen id : 1] Input [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] -Condition : isnotnull(ss_store_sk#4) (8) BroadcastExchange Input [3]: [ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] @@ -76,16 +76,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_gmt_offset), EqualTo(s_gmt_offset,-5.00), IsNotNull(s_store_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] -Input [4]: [s_store_sk#7, s_store_id#8, s_store_name#9, s_gmt_offset#10] - -(13) Filter [codegen id : 2] +(12) CometFilter Input [4]: [s_store_sk#7, s_store_id#8, s_store_name#9, s_gmt_offset#10] Condition : ((isnotnull(s_gmt_offset#10) AND (s_gmt_offset#10 = -5.00)) AND isnotnull(s_store_sk#7)) -(14) Project [codegen id : 2] -Output [3]: [s_store_sk#7, s_store_id#8, s_store_name#9] +(13) CometProject Input [4]: [s_store_sk#7, s_store_id#8, s_store_name#9, s_gmt_offset#10] +Arguments: [s_store_sk#7, s_store_id#8, s_store_name#9], [s_store_sk#7, s_store_id#8, s_store_name#9] + +(14) ColumnarToRow [codegen id : 2] +Input [3]: [s_store_sk#7, s_store_id#8, s_store_name#9] (15) BroadcastExchange Input [3]: [s_store_sk#7, s_store_id#8, s_store_name#9] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/simplified.txt index b00665aed..ef2043096 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q43/simplified.txt @@ -9,23 +9,23 @@ TakeOrderedAndProject [s_store_name,s_store_id,sun_sales,mon_sales,tue_sales,wed BroadcastHashJoin [ss_store_sk,s_store_sk] Project [d_day_name,ss_store_sk,ss_sales_price] BroadcastHashJoin [d_date_sk,ss_sold_date_sk] - Project [d_date_sk,d_day_name] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_day_name] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_day_name] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_sales_price,ss_sold_date_sk] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [s_store_sk,s_store_id,s_store_name] - Filter [s_gmt_offset,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk,s_store_id,s_store_name] + CometFilter [s_gmt_offset,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name,s_gmt_offset] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/explain.txt index ba9e48ec7..812f9f391 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/explain.txt @@ -20,9 +20,9 @@ TakeOrderedAndProject (43) : : : +- * HashAggregate (7) : : : +- Exchange (6) : : : +- * HashAggregate (5) - : : : +- * Project (4) - : : : +- * Filter (3) - : : : +- * ColumnarToRow (2) + : : : +- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : +- * Sort (31) : : +- Exchange (30) @@ -38,8 +38,8 @@ TakeOrderedAndProject (43) : : +- * HashAggregate (20) : : +- ReusedExchange (19) : +- BroadcastExchange (37) - : +- * Filter (36) - : +- * ColumnarToRow (35) + : +- * ColumnarToRow (36) + : +- CometFilter (35) : +- CometScan parquet spark_catalog.default.item (34) +- ReusedExchange (40) @@ -51,16 +51,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_store_sk), EqualTo(ss_store_sk,4)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_net_profit#3, ss_sold_date_sk#4] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_net_profit#3, ss_sold_date_sk#4] Condition : (isnotnull(ss_store_sk#2) AND (ss_store_sk#2 = 4)) -(4) Project [codegen id : 1] -Output [2]: [ss_item_sk#1, ss_net_profit#3] +(3) CometProject Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_net_profit#3, ss_sold_date_sk#4] +Arguments: [ss_item_sk#1, ss_net_profit#3], [ss_item_sk#1, ss_net_profit#3] + +(4) ColumnarToRow [codegen id : 1] +Input [2]: [ss_item_sk#1, ss_net_profit#3] (5) HashAggregate [codegen id : 1] Input [2]: [ss_item_sk#1, ss_net_profit#3] @@ -195,12 +195,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 11] +(35) CometFilter Input [2]: [i_item_sk#23, i_product_name#24] +Condition : isnotnull(i_item_sk#23) -(36) Filter [codegen id : 11] +(36) ColumnarToRow [codegen id : 11] Input [2]: [i_item_sk#23, i_product_name#24] -Condition : isnotnull(i_item_sk#23) (37) BroadcastExchange Input [2]: [i_item_sk#23, i_product_name#24] @@ -239,9 +239,9 @@ Subquery:1 Hosting operator id = 8 Hosting Expression = Subquery scalar-subquery * HashAggregate (50) +- Exchange (49) +- * HashAggregate (48) - +- * Project (47) - +- * Filter (46) - +- * ColumnarToRow (45) + +- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) +- CometScan parquet spark_catalog.default.store_sales (44) @@ -252,16 +252,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_store_sk), EqualTo(ss_store_sk,4), IsNull(ss_addr_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 1] -Input [4]: [ss_addr_sk#29, ss_store_sk#30, ss_net_profit#31, ss_sold_date_sk#32] - -(46) Filter [codegen id : 1] +(45) CometFilter Input [4]: [ss_addr_sk#29, ss_store_sk#30, ss_net_profit#31, ss_sold_date_sk#32] Condition : ((isnotnull(ss_store_sk#30) AND (ss_store_sk#30 = 4)) AND isnull(ss_addr_sk#29)) -(47) Project [codegen id : 1] -Output [2]: [ss_store_sk#30, ss_net_profit#31] +(46) CometProject Input [4]: [ss_addr_sk#29, ss_store_sk#30, ss_net_profit#31, ss_sold_date_sk#32] +Arguments: [ss_store_sk#30, ss_net_profit#31], [ss_store_sk#30, ss_net_profit#31] + +(47) ColumnarToRow [codegen id : 1] +Input [2]: [ss_store_sk#30, ss_net_profit#31] (48) HashAggregate [codegen id : 1] Input [2]: [ss_store_sk#30, ss_net_profit#31] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/simplified.txt index adcad1417..35a3e9efa 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q44/simplified.txt @@ -32,20 +32,20 @@ TakeOrderedAndProject [rnk,best_performing,worst_performing] Exchange [ss_store_sk] #4 WholeStageCodegen (1) HashAggregate [ss_store_sk,ss_net_profit] [sum,count,sum,count] - Project [ss_store_sk,ss_net_profit] - Filter [ss_store_sk,ss_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_store_sk,ss_net_profit] + CometFilter [ss_store_sk,ss_addr_sk] CometScan parquet spark_catalog.default.store_sales [ss_addr_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk] HashAggregate [ss_item_sk,sum,count] [avg(UnscaledValue(ss_net_profit)),item_sk,rank_col,sum,count] InputAdapter Exchange [ss_item_sk] #3 WholeStageCodegen (1) HashAggregate [ss_item_sk,ss_net_profit] [sum,count,sum,count] - Project [ss_item_sk,ss_net_profit] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_net_profit] + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_net_profit,ss_sold_date_sk] InputAdapter WholeStageCodegen (10) @@ -73,9 +73,9 @@ TakeOrderedAndProject [rnk,best_performing,worst_performing] InputAdapter BroadcastExchange #7 WholeStageCodegen (11) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_product_name] InputAdapter ReusedExchange [i_item_sk,i_product_name] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/explain.txt index aaf17cf45..d0d74569b 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/explain.txt @@ -14,26 +14,26 @@ TakeOrderedAndProject (36) : : : +- * BroadcastHashJoin Inner BuildRight (14) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.customer (4) : : : +- BroadcastExchange (13) - : : : +- * Filter (12) - : : : +- * ColumnarToRow (11) + : : : +- * ColumnarToRow (12) + : : : +- CometFilter (11) : : : +- CometScan parquet spark_catalog.default.customer_address (10) : : +- ReusedExchange (16) : +- BroadcastExchange (22) - : +- * Filter (21) - : +- * ColumnarToRow (20) + : +- * ColumnarToRow (21) + : +- CometFilter (20) : +- CometScan parquet spark_catalog.default.item (19) +- BroadcastExchange (29) - +- * Project (28) - +- * Filter (27) - +- * ColumnarToRow (26) + +- * ColumnarToRow (28) + +- CometProject (27) + +- CometFilter (26) +- CometScan parquet spark_catalog.default.item (25) @@ -45,12 +45,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#5), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_bill_customer_sk), IsNotNull(ws_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 6] +(2) CometFilter Input [4]: [ws_item_sk#2, ws_bill_customer_sk#3, ws_sales_price#4, ws_sold_date_sk#5] +Condition : (isnotnull(ws_bill_customer_sk#3) AND isnotnull(ws_item_sk#2)) -(3) Filter [codegen id : 6] +(3) ColumnarToRow [codegen id : 6] Input [4]: [ws_item_sk#2, ws_bill_customer_sk#3, ws_sales_price#4, ws_sold_date_sk#5] -Condition : (isnotnull(ws_bill_customer_sk#3) AND isnotnull(ws_item_sk#2)) (4) Scan parquet spark_catalog.default.customer Output [2]: [c_customer_sk#7, c_current_addr_sk#8] @@ -59,12 +59,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [2]: [c_customer_sk#7, c_current_addr_sk#8] +Condition : (isnotnull(c_customer_sk#7) AND isnotnull(c_current_addr_sk#8)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [2]: [c_customer_sk#7, c_current_addr_sk#8] -Condition : (isnotnull(c_customer_sk#7) AND isnotnull(c_current_addr_sk#8)) (7) BroadcastExchange Input [2]: [c_customer_sk#7, c_current_addr_sk#8] @@ -87,12 +87,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] +Condition : isnotnull(ca_address_sk#9) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] -Condition : isnotnull(ca_address_sk#9) (13) BroadcastExchange Input [3]: [ca_address_sk#9, ca_city#10, ca_zip#11] @@ -128,12 +128,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(20) ColumnarToRow [codegen id : 4] +(20) CometFilter Input [2]: [i_item_sk#13, i_item_id#14] +Condition : isnotnull(i_item_sk#13) -(21) Filter [codegen id : 4] +(21) ColumnarToRow [codegen id : 4] Input [2]: [i_item_sk#13, i_item_id#14] -Condition : isnotnull(i_item_sk#13) (22) BroadcastExchange Input [2]: [i_item_sk#13, i_item_id#14] @@ -156,16 +156,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [In(i_item_sk, [11,13,17,19,2,23,29,3,5,7])] ReadSchema: struct -(26) ColumnarToRow [codegen id : 5] -Input [2]: [i_item_sk#15, i_item_id#16] - -(27) Filter [codegen id : 5] +(26) CometFilter Input [2]: [i_item_sk#15, i_item_id#16] Condition : i_item_sk#15 IN (2,3,5,7,11,13,17,19,23,29) -(28) Project [codegen id : 5] -Output [1]: [i_item_id#16] +(27) CometProject Input [2]: [i_item_sk#15, i_item_id#16] +Arguments: [i_item_id#16], [i_item_id#16] + +(28) ColumnarToRow [codegen id : 5] +Input [1]: [i_item_id#16] (29) BroadcastExchange Input [1]: [i_item_id#16] @@ -211,9 +211,9 @@ Arguments: 100, [ca_zip#11 ASC NULLS FIRST, ca_city#10 ASC NULLS FIRST], [ca_zip Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (41) -+- * Project (40) - +- * Filter (39) - +- * ColumnarToRow (38) ++- * ColumnarToRow (40) + +- CometProject (39) + +- CometFilter (38) +- CometScan parquet spark_catalog.default.date_dim (37) @@ -224,16 +224,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(38) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#12, d_year#21, d_qoy#22] - -(39) Filter [codegen id : 1] +(38) CometFilter Input [3]: [d_date_sk#12, d_year#21, d_qoy#22] Condition : ((((isnotnull(d_qoy#22) AND isnotnull(d_year#21)) AND (d_qoy#22 = 2)) AND (d_year#21 = 2001)) AND isnotnull(d_date_sk#12)) -(40) Project [codegen id : 1] -Output [1]: [d_date_sk#12] +(39) CometProject Input [3]: [d_date_sk#12, d_year#21, d_qoy#22] +Arguments: [d_date_sk#12], [d_date_sk#12] + +(40) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#12] (41) BroadcastExchange Input [1]: [d_date_sk#12] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/simplified.txt index 05579f166..383cbb7e3 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q45/simplified.txt @@ -16,46 +16,46 @@ TakeOrderedAndProject [ca_zip,ca_city,sum(ws_sales_price)] BroadcastHashJoin [c_current_addr_sk,ca_address_sk] Project [ws_item_sk,ws_sales_price,ws_sold_date_sk,c_current_addr_sk] BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] - Filter [ws_bill_customer_sk,ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk,ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_sales_price,ws_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_qoy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_qoy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [c_customer_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city,ca_zip] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] InputAdapter BroadcastExchange #6 WholeStageCodegen (5) - Project [i_item_id] - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_id] + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/explain.txt index d51633680..e07e2ab24 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/explain.txt @@ -15,27 +15,27 @@ TakeOrderedAndProject (39) : : : : +- * BroadcastHashJoin Inner BuildRight (12) : : : : :- * Project (6) : : : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : : : :- * Filter (3) - : : : : : : +- * ColumnarToRow (2) + : : : : : :- * ColumnarToRow (3) + : : : : : : +- CometFilter (2) : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : : +- ReusedExchange (4) : : : : +- BroadcastExchange (11) - : : : : +- * Project (10) - : : : : +- * Filter (9) - : : : : +- * ColumnarToRow (8) + : : : : +- * ColumnarToRow (10) + : : : : +- CometProject (9) + : : : : +- CometFilter (8) : : : : +- CometScan parquet spark_catalog.default.store (7) : : : +- BroadcastExchange (18) - : : : +- * Project (17) - : : : +- * Filter (16) - : : : +- * ColumnarToRow (15) + : : : +- * ColumnarToRow (17) + : : : +- CometProject (16) + : : : +- CometFilter (15) : : : +- CometScan parquet spark_catalog.default.household_demographics (14) : : +- BroadcastExchange (24) - : : +- * Filter (23) - : : +- * ColumnarToRow (22) + : : +- * ColumnarToRow (23) + : : +- CometFilter (22) : : +- CometScan parquet spark_catalog.default.customer_address (21) : +- BroadcastExchange (33) - : +- * Filter (32) - : +- * ColumnarToRow (31) + : +- * ColumnarToRow (32) + : +- CometFilter (31) : +- CometScan parquet spark_catalog.default.customer (30) +- ReusedExchange (36) @@ -48,12 +48,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] +Condition : (((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_customer_sk#1)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] -Condition : (((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_customer_sk#1)) (4) ReusedExchange [Reuses operator id: 44] Output [1]: [d_date_sk#10] @@ -75,16 +75,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [In(s_city, [Fairview,Midway]), IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] -Input [2]: [s_store_sk#11, s_city#12] - -(9) Filter [codegen id : 2] +(8) CometFilter Input [2]: [s_store_sk#11, s_city#12] Condition : (s_city#12 IN (Fairview,Midway) AND isnotnull(s_store_sk#11)) -(10) Project [codegen id : 2] -Output [1]: [s_store_sk#11] +(9) CometProject Input [2]: [s_store_sk#11, s_city#12] +Arguments: [s_store_sk#11], [s_store_sk#11] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#11] (11) BroadcastExchange Input [1]: [s_store_sk#11] @@ -107,16 +107,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [Or(EqualTo(hd_dep_count,4),EqualTo(hd_vehicle_count,3)), IsNotNull(hd_demo_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] -Input [3]: [hd_demo_sk#13, hd_dep_count#14, hd_vehicle_count#15] - -(16) Filter [codegen id : 3] +(15) CometFilter Input [3]: [hd_demo_sk#13, hd_dep_count#14, hd_vehicle_count#15] Condition : (((hd_dep_count#14 = 4) OR (hd_vehicle_count#15 = 3)) AND isnotnull(hd_demo_sk#13)) -(17) Project [codegen id : 3] -Output [1]: [hd_demo_sk#13] +(16) CometProject Input [3]: [hd_demo_sk#13, hd_dep_count#14, hd_vehicle_count#15] +Arguments: [hd_demo_sk#13], [hd_demo_sk#13] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#13] (18) BroadcastExchange Input [1]: [hd_demo_sk#13] @@ -139,12 +139,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_city)] ReadSchema: struct -(22) ColumnarToRow [codegen id : 4] +(22) CometFilter Input [2]: [ca_address_sk#16, ca_city#17] +Condition : (isnotnull(ca_address_sk#16) AND isnotnull(ca_city#17)) -(23) Filter [codegen id : 4] +(23) ColumnarToRow [codegen id : 4] Input [2]: [ca_address_sk#16, ca_city#17] -Condition : (isnotnull(ca_address_sk#16) AND isnotnull(ca_city#17)) (24) BroadcastExchange Input [2]: [ca_address_sk#16, ca_city#17] @@ -185,12 +185,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 6] +(31) CometFilter Input [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] +Condition : (isnotnull(c_customer_sk#27) AND isnotnull(c_current_addr_sk#28)) -(32) Filter [codegen id : 6] +(32) ColumnarToRow [codegen id : 6] Input [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] -Condition : (isnotnull(c_customer_sk#27) AND isnotnull(c_current_addr_sk#28)) (33) BroadcastExchange Input [4]: [c_customer_sk#27, c_current_addr_sk#28, c_first_name#29, c_last_name#30] @@ -227,9 +227,9 @@ Arguments: 100, [c_last_name#30 ASC NULLS FIRST, c_first_name#29 ASC NULLS FIRST Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (44) -+- * Project (43) - +- * Filter (42) - +- * ColumnarToRow (41) ++- * ColumnarToRow (43) + +- CometProject (42) + +- CometFilter (41) +- CometScan parquet spark_catalog.default.date_dim (40) @@ -240,16 +240,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [In(d_dow, [0,6]), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] ReadSchema: struct -(41) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#10, d_year#33, d_dow#34] - -(42) Filter [codegen id : 1] +(41) CometFilter Input [3]: [d_date_sk#10, d_year#33, d_dow#34] Condition : ((d_dow#34 IN (6,0) AND d_year#33 IN (1999,2000,2001)) AND isnotnull(d_date_sk#10)) -(43) Project [codegen id : 1] -Output [1]: [d_date_sk#10] +(42) CometProject Input [3]: [d_date_sk#10, d_year#33, d_dow#34] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(43) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] (44) BroadcastExchange Input [1]: [d_date_sk#10] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/simplified.txt index 376fc2f62..04c59a2d3 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q46/simplified.txt @@ -17,49 +17,49 @@ TakeOrderedAndProject [c_last_name,c_first_name,ca_city,bought_city,ss_ticket_nu BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk,ss_hdemo_sk,ss_addr_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_addr_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_dow,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dow,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dow] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [s_store_sk] - Filter [s_city,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_city,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_city] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Project [hd_demo_sk] - Filter [hd_dep_count,hd_vehicle_count,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_vehicle_count,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Filter [ca_address_sk,ca_city] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_city] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city] InputAdapter BroadcastExchange #6 WholeStageCodegen (6) - Filter [c_customer_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name] InputAdapter ReusedExchange [ca_address_sk,ca_city] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/explain.txt index 74b0ed8ff..fca7362ce 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/explain.txt @@ -20,17 +20,17 @@ TakeOrderedAndProject (45) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.item (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.store_sales (4) : : : +- ReusedExchange (10) : : +- BroadcastExchange (16) - : : +- * Filter (15) - : : +- * ColumnarToRow (14) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) : : +- CometScan parquet spark_catalog.default.store (13) : +- BroadcastExchange (35) : +- * Project (34) @@ -53,12 +53,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [3]: [i_item_sk#1, i_brand#2, i_category#3] -Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) (4) Scan parquet spark_catalog.default.store_sales Output [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] @@ -68,12 +68,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#4) AND isnotnull(ss_store_sk#5)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] -Condition : (isnotnull(ss_item_sk#4) AND isnotnull(ss_store_sk#5)) (7) BroadcastExchange Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] @@ -109,12 +109,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_company_name)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Condition : ((isnotnull(s_store_sk#12) AND isnotnull(s_store_name#13)) AND isnotnull(s_company_name#14)) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] -Condition : ((isnotnull(s_store_sk#12) AND isnotnull(s_store_name#13)) AND isnotnull(s_company_name#14)) (16) BroadcastExchange Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] @@ -253,8 +253,8 @@ Arguments: 100, [(sum_sales#18 - avg_monthly_sales#21) ASC NULLS FIRST, s_store_ Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (49) -+- * Filter (48) - +- * ColumnarToRow (47) ++- * ColumnarToRow (48) + +- CometFilter (47) +- CometScan parquet spark_catalog.default.date_dim (46) @@ -265,12 +265,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] ReadSchema: struct -(47) ColumnarToRow [codegen id : 1] +(47) CometFilter Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) -(48) Filter [codegen id : 1] +(48) ColumnarToRow [codegen id : 1] Input [3]: [d_date_sk#9, d_year#10, d_moy#11] -Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) (49) BroadcastExchange Input [3]: [d_date_sk#9, d_year#10, d_moy#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/simplified.txt index 5dba00296..80b8da7b1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q47/simplified.txt @@ -28,32 +28,32 @@ TakeOrderedAndProject [sum_sales,avg_monthly_sales,s_store_name,i_category,i_bra BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [i_brand,i_category,ss_store_sk,ss_sales_price,ss_sold_date_sk] BroadcastHashJoin [i_item_sk,ss_item_sk] - Filter [i_item_sk,i_category,i_brand] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_category,i_brand] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [ss_item_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk,d_year,d_moy] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [s_store_sk,s_store_name,s_company_name] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_name,s_company_name] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_name] InputAdapter BroadcastExchange #6 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/explain.txt index c2b675c34..718f3fb31 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/explain.txt @@ -10,21 +10,21 @@ : : +- * BroadcastHashJoin Inner BuildRight (14) : : :- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.store (4) : : +- BroadcastExchange (13) - : : +- * Filter (12) - : : +- * ColumnarToRow (11) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) : : +- CometScan parquet spark_catalog.default.customer_demographics (10) : +- BroadcastExchange (20) - : +- * Project (19) - : +- * Filter (18) - : +- * ColumnarToRow (17) + : +- * ColumnarToRow (19) + : +- CometProject (18) + : +- CometFilter (17) : +- CometScan parquet spark_catalog.default.customer_address (16) +- ReusedExchange (23) @@ -37,12 +37,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_addr_sk), Or(Or(And(GreaterThanOrEqual(ss_sales_price,100.00),LessThanOrEqual(ss_sales_price,150.00)),And(GreaterThanOrEqual(ss_sales_price,50.00),LessThanOrEqual(ss_sales_price,100.00))),And(GreaterThanOrEqual(ss_sales_price,150.00),LessThanOrEqual(ss_sales_price,200.00))), Or(Or(And(GreaterThanOrEqual(ss_net_profit,0.00),LessThanOrEqual(ss_net_profit,2000.00)),And(GreaterThanOrEqual(ss_net_profit,150.00),LessThanOrEqual(ss_net_profit,3000.00))),And(GreaterThanOrEqual(ss_net_profit,50.00),LessThanOrEqual(ss_net_profit,25000.00)))] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [7]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Condition : ((((isnotnull(ss_store_sk#3) AND isnotnull(ss_cdemo_sk#1)) AND isnotnull(ss_addr_sk#2)) AND ((((ss_sales_price#5 >= 100.00) AND (ss_sales_price#5 <= 150.00)) OR ((ss_sales_price#5 >= 50.00) AND (ss_sales_price#5 <= 100.00))) OR ((ss_sales_price#5 >= 150.00) AND (ss_sales_price#5 <= 200.00)))) AND ((((ss_net_profit#6 >= 0.00) AND (ss_net_profit#6 <= 2000.00)) OR ((ss_net_profit#6 >= 150.00) AND (ss_net_profit#6 <= 3000.00))) OR ((ss_net_profit#6 >= 50.00) AND (ss_net_profit#6 <= 25000.00)))) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [7]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] -Condition : ((((isnotnull(ss_store_sk#3) AND isnotnull(ss_cdemo_sk#1)) AND isnotnull(ss_addr_sk#2)) AND ((((ss_sales_price#5 >= 100.00) AND (ss_sales_price#5 <= 150.00)) OR ((ss_sales_price#5 >= 50.00) AND (ss_sales_price#5 <= 100.00))) OR ((ss_sales_price#5 >= 150.00) AND (ss_sales_price#5 <= 200.00)))) AND ((((ss_net_profit#6 >= 0.00) AND (ss_net_profit#6 <= 2000.00)) OR ((ss_net_profit#6 >= 150.00) AND (ss_net_profit#6 <= 3000.00))) OR ((ss_net_profit#6 >= 50.00) AND (ss_net_profit#6 <= 25000.00)))) (4) Scan parquet spark_catalog.default.store Output [1]: [s_store_sk#9] @@ -51,12 +51,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [1]: [s_store_sk#9] +Condition : isnotnull(s_store_sk#9) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [1]: [s_store_sk#9] -Condition : isnotnull(s_store_sk#9) (7) BroadcastExchange Input [1]: [s_store_sk#9] @@ -79,12 +79,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,4 yr Degree )),And(EqualTo(cd_marital_status,D),EqualTo(cd_education_status,2 yr Degree ))),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College )))] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] +Condition : (isnotnull(cd_demo_sk#10) AND ((((cd_marital_status#11 = M) AND (cd_education_status#12 = 4 yr Degree )) OR ((cd_marital_status#11 = D) AND (cd_education_status#12 = 2 yr Degree ))) OR ((cd_marital_status#11 = S) AND (cd_education_status#12 = College )))) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] -Condition : (isnotnull(cd_demo_sk#10) AND ((((cd_marital_status#11 = M) AND (cd_education_status#12 = 4 yr Degree )) OR ((cd_marital_status#11 = D) AND (cd_education_status#12 = 2 yr Degree ))) OR ((cd_marital_status#11 = S) AND (cd_education_status#12 = College )))) (13) BroadcastExchange Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12] @@ -107,16 +107,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [CO,OH,TX]),In(ca_state, [KY,MN,OR])),In(ca_state, [CA,MS,VA]))] ReadSchema: struct -(17) ColumnarToRow [codegen id : 3] -Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] - -(18) Filter [codegen id : 3] +(17) CometFilter Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] Condition : (((isnotnull(ca_country#15) AND (ca_country#15 = United States)) AND isnotnull(ca_address_sk#13)) AND ((ca_state#14 IN (CO,OH,TX) OR ca_state#14 IN (OR,MN,KY)) OR ca_state#14 IN (VA,CA,MS))) -(19) Project [codegen id : 3] -Output [2]: [ca_address_sk#13, ca_state#14] +(18) CometProject Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15] +Arguments: [ca_address_sk#13, ca_state#14], [ca_address_sk#13, ca_state#14] + +(19) ColumnarToRow [codegen id : 3] +Input [2]: [ca_address_sk#13, ca_state#14] (20) BroadcastExchange Input [2]: [ca_address_sk#13, ca_state#14] @@ -167,9 +167,9 @@ Results [1]: [sum(ss_quantity#4)#19 AS sum(ss_quantity)#20] Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (33) -+- * Project (32) - +- * Filter (31) - +- * ColumnarToRow (30) ++- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) +- CometScan parquet spark_catalog.default.date_dim (29) @@ -180,16 +180,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#16, d_year#21] - -(31) Filter [codegen id : 1] +(30) CometFilter Input [2]: [d_date_sk#16, d_year#21] Condition : ((isnotnull(d_year#21) AND (d_year#21 = 2001)) AND isnotnull(d_date_sk#16)) -(32) Project [codegen id : 1] -Output [1]: [d_date_sk#16] +(31) CometProject Input [2]: [d_date_sk#16, d_year#21] +Arguments: [d_date_sk#16], [d_date_sk#16] + +(32) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#16] (33) BroadcastExchange Input [1]: [d_date_sk#16] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/simplified.txt index 5cc7040fb..4022da74f 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q48/simplified.txt @@ -12,39 +12,39 @@ WholeStageCodegen (6) BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk,cd_marital_status,cd_education_status,ss_sales_price] Project [ss_cdemo_sk,ss_addr_sk,ss_quantity,ss_sales_price,ss_net_profit,ss_sold_date_sk] BroadcastHashJoin [ss_store_sk,s_store_sk] - Filter [ss_store_sk,ss_cdemo_sk,ss_addr_sk,ss_sales_price,ss_net_profit] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_cdemo_sk,ss_addr_sk,ss_sales_price,ss_net_profit] CometScan parquet spark_catalog.default.store_sales [ss_cdemo_sk,ss_addr_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk] InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [cd_demo_sk,cd_marital_status,cd_education_status] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status,cd_education_status] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Project [ca_address_sk,ca_state] - Filter [ca_country,ca_address_sk,ca_state] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk,ca_state] + CometFilter [ca_country,ca_address_sk,ca_state] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] InputAdapter ReusedExchange [d_date_sk] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/explain.txt index 1ad84da7d..bbb550e05 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/explain.txt @@ -1,81 +1,78 @@ == Physical Plan == -TakeOrderedAndProject (77) -+- * HashAggregate (76) - +- Exchange (75) - +- * HashAggregate (74) - +- Union (73) - :- * Project (24) - : +- * Filter (23) - : +- Window (22) - : +- * Sort (21) - : +- Window (20) - : +- * Sort (19) - : +- Exchange (18) - : +- * HashAggregate (17) - : +- Exchange (16) - : +- * HashAggregate (15) - : +- * Project (14) - : +- * BroadcastHashJoin Inner BuildRight (13) - : :- * Project (11) - : : +- * BroadcastHashJoin Inner BuildLeft (10) - : : :- BroadcastExchange (5) - : : : +- * Project (4) - : : : +- * Filter (3) - : : : +- * ColumnarToRow (2) - : : : +- CometScan parquet spark_catalog.default.web_sales (1) - : : +- * Project (9) - : : +- * Filter (8) - : : +- * ColumnarToRow (7) - : : +- CometScan parquet spark_catalog.default.web_returns (6) - : +- ReusedExchange (12) - :- * Project (48) - : +- * Filter (47) - : +- Window (46) - : +- * Sort (45) - : +- Window (44) - : +- * Sort (43) - : +- Exchange (42) - : +- * HashAggregate (41) - : +- Exchange (40) - : +- * HashAggregate (39) - : +- * Project (38) - : +- * BroadcastHashJoin Inner BuildRight (37) - : :- * Project (35) - : : +- * BroadcastHashJoin Inner BuildLeft (34) - : : :- BroadcastExchange (29) - : : : +- * Project (28) - : : : +- * Filter (27) - : : : +- * ColumnarToRow (26) - : : : +- CometScan parquet spark_catalog.default.catalog_sales (25) - : : +- * Project (33) - : : +- * Filter (32) - : : +- * ColumnarToRow (31) - : : +- CometScan parquet spark_catalog.default.catalog_returns (30) - : +- ReusedExchange (36) - +- * Project (72) - +- * Filter (71) - +- Window (70) - +- * Sort (69) - +- Window (68) - +- * Sort (67) - +- Exchange (66) - +- * HashAggregate (65) - +- Exchange (64) - +- * HashAggregate (63) - +- * Project (62) - +- * BroadcastHashJoin Inner BuildRight (61) - :- * Project (59) - : +- * BroadcastHashJoin Inner BuildLeft (58) - : :- BroadcastExchange (53) - : : +- * Project (52) - : : +- * Filter (51) - : : +- * ColumnarToRow (50) - : : +- CometScan parquet spark_catalog.default.store_sales (49) - : +- * Project (57) - : +- * Filter (56) - : +- * ColumnarToRow (55) - : +- CometScan parquet spark_catalog.default.store_returns (54) - +- ReusedExchange (60) +TakeOrderedAndProject (74) ++- * HashAggregate (73) + +- Exchange (72) + +- * HashAggregate (71) + +- Union (70) + :- * Project (23) + : +- * Filter (22) + : +- Window (21) + : +- * Sort (20) + : +- Window (19) + : +- * Sort (18) + : +- Exchange (17) + : +- * HashAggregate (16) + : +- Exchange (15) + : +- * HashAggregate (14) + : +- * Project (13) + : +- * BroadcastHashJoin Inner BuildRight (12) + : :- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometBroadcastHashJoin (8) + : : :- CometBroadcastExchange (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : +- CometProject (7) + : : +- CometFilter (6) + : : +- CometScan parquet spark_catalog.default.web_returns (5) + : +- ReusedExchange (11) + :- * Project (46) + : +- * Filter (45) + : +- Window (44) + : +- * Sort (43) + : +- Window (42) + : +- * Sort (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- Exchange (38) + : +- * HashAggregate (37) + : +- * Project (36) + : +- * BroadcastHashJoin Inner BuildRight (35) + : :- * ColumnarToRow (33) + : : +- CometProject (32) + : : +- CometBroadcastHashJoin (31) + : : :- CometBroadcastExchange (27) + : : : +- CometProject (26) + : : : +- CometFilter (25) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (24) + : : +- CometProject (30) + : : +- CometFilter (29) + : : +- CometScan parquet spark_catalog.default.catalog_returns (28) + : +- ReusedExchange (34) + +- * Project (69) + +- * Filter (68) + +- Window (67) + +- * Sort (66) + +- Window (65) + +- * Sort (64) + +- Exchange (63) + +- * HashAggregate (62) + +- Exchange (61) + +- * HashAggregate (60) + +- * Project (59) + +- * BroadcastHashJoin Inner BuildRight (58) + :- * ColumnarToRow (56) + : +- CometProject (55) + : +- CometBroadcastHashJoin (54) + : :- CometBroadcastExchange (50) + : : +- CometProject (49) + : : +- CometFilter (48) + : : +- CometScan parquet spark_catalog.default.store_sales (47) + : +- CometProject (53) + : +- CometFilter (52) + : +- CometScan parquet spark_catalog.default.store_returns (51) + +- ReusedExchange (57) (1) Scan parquet spark_catalog.default.web_sales @@ -86,109 +83,105 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#6), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_net_profit), IsNotNull(ws_net_paid), IsNotNull(ws_quantity), GreaterThan(ws_net_profit,1.00), GreaterThan(ws_net_paid,0.00), GreaterThan(ws_quantity,0), IsNotNull(ws_order_number), IsNotNull(ws_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] Condition : (((((((isnotnull(ws_net_profit#5) AND isnotnull(ws_net_paid#4)) AND isnotnull(ws_quantity#3)) AND (ws_net_profit#5 > 1.00)) AND (ws_net_paid#4 > 0.00)) AND (ws_quantity#3 > 0)) AND isnotnull(ws_order_number#2)) AND isnotnull(ws_item_sk#1)) -(4) Project [codegen id : 1] -Output [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +(3) CometProject Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Arguments: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6], [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] -(5) BroadcastExchange +(4) CometBroadcastExchange Input [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=1] +Arguments: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] -(6) Scan parquet spark_catalog.default.web_returns +(5) Scan parquet spark_catalog.default.web_returns Output [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] Batched: true Location [not included in comparison]/{warehouse_dir}/web_returns] PushedFilters: [IsNotNull(wr_return_amt), GreaterThan(wr_return_amt,10000.00), IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] ReadSchema: struct -(7) ColumnarToRow -Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] - -(8) Filter +(6) CometFilter Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] Condition : (((isnotnull(wr_return_amt#11) AND (wr_return_amt#11 > 10000.00)) AND isnotnull(wr_order_number#9)) AND isnotnull(wr_item_sk#8)) -(9) Project -Output [4]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +(7) CometProject Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Arguments: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11], [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] -(10) BroadcastHashJoin [codegen id : 3] -Left keys [2]: [ws_order_number#2, ws_item_sk#1] -Right keys [2]: [wr_order_number#9, wr_item_sk#8] -Join type: Inner -Join condition: None +(8) CometBroadcastHashJoin +Left output [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +Right output [4]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +Arguments: [ws_order_number#2, ws_item_sk#1], [wr_order_number#9, wr_item_sk#8], Inner -(11) Project [codegen id : 3] -Output [6]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] +(9) CometProject Input [9]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +Arguments: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11], [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] -(12) ReusedExchange [Reuses operator id: 82] +(10) ColumnarToRow [codegen id : 2] +Input [6]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] + +(11) ReusedExchange [Reuses operator id: 79] Output [1]: [d_date_sk#13] -(13) BroadcastHashJoin [codegen id : 3] +(12) BroadcastHashJoin [codegen id : 2] Left keys [1]: [ws_sold_date_sk#6] Right keys [1]: [d_date_sk#13] Join type: Inner Join condition: None -(14) Project [codegen id : 3] +(13) Project [codegen id : 2] Output [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] Input [7]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11, d_date_sk#13] -(15) HashAggregate [codegen id : 3] +(14) HashAggregate [codegen id : 2] Input [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] Keys [1]: [ws_item_sk#1] Functions [4]: [partial_sum(coalesce(wr_return_quantity#10, 0)), partial_sum(coalesce(ws_quantity#3, 0)), partial_sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] Aggregate Attributes [6]: [sum#14, sum#15, sum#16, isEmpty#17, sum#18, isEmpty#19] Results [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] -(16) Exchange +(15) Exchange Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] -Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] +Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] -(17) HashAggregate [codegen id : 4] +(16) HashAggregate [codegen id : 3] Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] Keys [1]: [ws_item_sk#1] Functions [4]: [sum(coalesce(wr_return_quantity#10, 0)), sum(coalesce(ws_quantity#3, 0)), sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] Aggregate Attributes [4]: [sum(coalesce(wr_return_quantity#10, 0))#26, sum(coalesce(ws_quantity#3, 0))#27, sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28, sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29] Results [3]: [ws_item_sk#1 AS item#30, (cast(sum(coalesce(wr_return_quantity#10, 0))#26 as decimal(15,4)) / cast(sum(coalesce(ws_quantity#3, 0))#27 as decimal(15,4))) AS return_ratio#31, (cast(sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28 as decimal(15,4)) / cast(sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29 as decimal(15,4))) AS currency_ratio#32] -(18) Exchange +(17) Exchange Input [3]: [item#30, return_ratio#31, currency_ratio#32] -Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=3] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=2] -(19) Sort [codegen id : 5] +(18) Sort [codegen id : 4] Input [3]: [item#30, return_ratio#31, currency_ratio#32] Arguments: [return_ratio#31 ASC NULLS FIRST], false, 0 -(20) Window +(19) Window Input [3]: [item#30, return_ratio#31, currency_ratio#32] Arguments: [rank(return_ratio#31) windowspecdefinition(return_ratio#31 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#33], [return_ratio#31 ASC NULLS FIRST] -(21) Sort [codegen id : 6] +(20) Sort [codegen id : 5] Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] Arguments: [currency_ratio#32 ASC NULLS FIRST], false, 0 -(22) Window +(21) Window Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] Arguments: [rank(currency_ratio#32) windowspecdefinition(currency_ratio#32 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#34], [currency_ratio#32 ASC NULLS FIRST] -(23) Filter [codegen id : 7] +(22) Filter [codegen id : 6] Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] Condition : ((return_rank#33 <= 10) OR (currency_rank#34 <= 10)) -(24) Project [codegen id : 7] +(23) Project [codegen id : 6] Output [5]: [web AS channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] -(25) Scan parquet spark_catalog.default.catalog_sales +(24) Scan parquet spark_catalog.default.catalog_sales Output [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] Batched: true Location: InMemoryFileIndex [] @@ -196,109 +189,105 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#41), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_net_profit), IsNotNull(cs_net_paid), IsNotNull(cs_quantity), GreaterThan(cs_net_profit,1.00), GreaterThan(cs_net_paid,0.00), GreaterThan(cs_quantity,0), IsNotNull(cs_order_number), IsNotNull(cs_item_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 8] -Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] - -(27) Filter [codegen id : 8] +(25) CometFilter Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] Condition : (((((((isnotnull(cs_net_profit#40) AND isnotnull(cs_net_paid#39)) AND isnotnull(cs_quantity#38)) AND (cs_net_profit#40 > 1.00)) AND (cs_net_paid#39 > 0.00)) AND (cs_quantity#38 > 0)) AND isnotnull(cs_order_number#37)) AND isnotnull(cs_item_sk#36)) -(28) Project [codegen id : 8] -Output [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +(26) CometProject Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Arguments: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41], [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] -(29) BroadcastExchange +(27) CometBroadcastExchange Input [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=4] +Arguments: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] -(30) Scan parquet spark_catalog.default.catalog_returns +(28) Scan parquet spark_catalog.default.catalog_returns Output [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] Batched: true Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_return_amount), GreaterThan(cr_return_amount,10000.00), IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] ReadSchema: struct -(31) ColumnarToRow -Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] - -(32) Filter +(29) CometFilter Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] Condition : (((isnotnull(cr_return_amount#46) AND (cr_return_amount#46 > 10000.00)) AND isnotnull(cr_order_number#44)) AND isnotnull(cr_item_sk#43)) -(33) Project -Output [4]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +(30) CometProject Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Arguments: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46], [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] -(34) BroadcastHashJoin [codegen id : 10] -Left keys [2]: [cs_order_number#37, cs_item_sk#36] -Right keys [2]: [cr_order_number#44, cr_item_sk#43] -Join type: Inner -Join condition: None +(31) CometBroadcastHashJoin +Left output [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +Right output [4]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +Arguments: [cs_order_number#37, cs_item_sk#36], [cr_order_number#44, cr_item_sk#43], Inner -(35) Project [codegen id : 10] -Output [6]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] +(32) CometProject Input [9]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +Arguments: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46], [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] + +(33) ColumnarToRow [codegen id : 8] +Input [6]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] -(36) ReusedExchange [Reuses operator id: 82] +(34) ReusedExchange [Reuses operator id: 79] Output [1]: [d_date_sk#48] -(37) BroadcastHashJoin [codegen id : 10] +(35) BroadcastHashJoin [codegen id : 8] Left keys [1]: [cs_sold_date_sk#41] Right keys [1]: [d_date_sk#48] Join type: Inner Join condition: None -(38) Project [codegen id : 10] +(36) Project [codegen id : 8] Output [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] Input [7]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46, d_date_sk#48] -(39) HashAggregate [codegen id : 10] +(37) HashAggregate [codegen id : 8] Input [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] Keys [1]: [cs_item_sk#36] Functions [4]: [partial_sum(coalesce(cr_return_quantity#45, 0)), partial_sum(coalesce(cs_quantity#38, 0)), partial_sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] Aggregate Attributes [6]: [sum#49, sum#50, sum#51, isEmpty#52, sum#53, isEmpty#54] Results [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] -(40) Exchange +(38) Exchange Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] -Arguments: hashpartitioning(cs_item_sk#36, 5), ENSURE_REQUIREMENTS, [plan_id=5] +Arguments: hashpartitioning(cs_item_sk#36, 5), ENSURE_REQUIREMENTS, [plan_id=3] -(41) HashAggregate [codegen id : 11] +(39) HashAggregate [codegen id : 9] Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] Keys [1]: [cs_item_sk#36] Functions [4]: [sum(coalesce(cr_return_quantity#45, 0)), sum(coalesce(cs_quantity#38, 0)), sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] Aggregate Attributes [4]: [sum(coalesce(cr_return_quantity#45, 0))#61, sum(coalesce(cs_quantity#38, 0))#62, sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63, sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64] Results [3]: [cs_item_sk#36 AS item#65, (cast(sum(coalesce(cr_return_quantity#45, 0))#61 as decimal(15,4)) / cast(sum(coalesce(cs_quantity#38, 0))#62 as decimal(15,4))) AS return_ratio#66, (cast(sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63 as decimal(15,4)) / cast(sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64 as decimal(15,4))) AS currency_ratio#67] -(42) Exchange +(40) Exchange Input [3]: [item#65, return_ratio#66, currency_ratio#67] -Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] -(43) Sort [codegen id : 12] +(41) Sort [codegen id : 10] Input [3]: [item#65, return_ratio#66, currency_ratio#67] Arguments: [return_ratio#66 ASC NULLS FIRST], false, 0 -(44) Window +(42) Window Input [3]: [item#65, return_ratio#66, currency_ratio#67] Arguments: [rank(return_ratio#66) windowspecdefinition(return_ratio#66 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#68], [return_ratio#66 ASC NULLS FIRST] -(45) Sort [codegen id : 13] +(43) Sort [codegen id : 11] Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] Arguments: [currency_ratio#67 ASC NULLS FIRST], false, 0 -(46) Window +(44) Window Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] Arguments: [rank(currency_ratio#67) windowspecdefinition(currency_ratio#67 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#69], [currency_ratio#67 ASC NULLS FIRST] -(47) Filter [codegen id : 14] +(45) Filter [codegen id : 12] Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] Condition : ((return_rank#68 <= 10) OR (currency_rank#69 <= 10)) -(48) Project [codegen id : 14] +(46) Project [codegen id : 12] Output [5]: [catalog AS channel#70, item#65, return_ratio#66, return_rank#68, currency_rank#69] Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] -(49) Scan parquet spark_catalog.default.store_sales +(47) Scan parquet spark_catalog.default.store_sales Output [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] Batched: true Location: InMemoryFileIndex [] @@ -306,166 +295,162 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#76), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_net_profit), IsNotNull(ss_net_paid), IsNotNull(ss_quantity), GreaterThan(ss_net_profit,1.00), GreaterThan(ss_net_paid,0.00), GreaterThan(ss_quantity,0), IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk)] ReadSchema: struct -(50) ColumnarToRow [codegen id : 15] -Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] - -(51) Filter [codegen id : 15] +(48) CometFilter Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] Condition : (((((((isnotnull(ss_net_profit#75) AND isnotnull(ss_net_paid#74)) AND isnotnull(ss_quantity#73)) AND (ss_net_profit#75 > 1.00)) AND (ss_net_paid#74 > 0.00)) AND (ss_quantity#73 > 0)) AND isnotnull(ss_ticket_number#72)) AND isnotnull(ss_item_sk#71)) -(52) Project [codegen id : 15] -Output [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +(49) CometProject Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Arguments: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76], [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] -(53) BroadcastExchange +(50) CometBroadcastExchange Input [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=7] +Arguments: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] -(54) Scan parquet spark_catalog.default.store_returns +(51) Scan parquet spark_catalog.default.store_returns Output [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] Batched: true Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_return_amt), GreaterThan(sr_return_amt,10000.00), IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] ReadSchema: struct -(55) ColumnarToRow -Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] - -(56) Filter +(52) CometFilter Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] Condition : (((isnotnull(sr_return_amt#81) AND (sr_return_amt#81 > 10000.00)) AND isnotnull(sr_ticket_number#79)) AND isnotnull(sr_item_sk#78)) -(57) Project -Output [4]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +(53) CometProject Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Arguments: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81], [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] -(58) BroadcastHashJoin [codegen id : 17] -Left keys [2]: [ss_ticket_number#72, ss_item_sk#71] -Right keys [2]: [sr_ticket_number#79, sr_item_sk#78] -Join type: Inner -Join condition: None +(54) CometBroadcastHashJoin +Left output [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +Right output [4]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +Arguments: [ss_ticket_number#72, ss_item_sk#71], [sr_ticket_number#79, sr_item_sk#78], Inner -(59) Project [codegen id : 17] -Output [6]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] +(55) CometProject Input [9]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +Arguments: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81], [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] + +(56) ColumnarToRow [codegen id : 14] +Input [6]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] -(60) ReusedExchange [Reuses operator id: 82] +(57) ReusedExchange [Reuses operator id: 79] Output [1]: [d_date_sk#83] -(61) BroadcastHashJoin [codegen id : 17] +(58) BroadcastHashJoin [codegen id : 14] Left keys [1]: [ss_sold_date_sk#76] Right keys [1]: [d_date_sk#83] Join type: Inner Join condition: None -(62) Project [codegen id : 17] +(59) Project [codegen id : 14] Output [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] Input [7]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81, d_date_sk#83] -(63) HashAggregate [codegen id : 17] +(60) HashAggregate [codegen id : 14] Input [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] Keys [1]: [ss_item_sk#71] Functions [4]: [partial_sum(coalesce(sr_return_quantity#80, 0)), partial_sum(coalesce(ss_quantity#73, 0)), partial_sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] Aggregate Attributes [6]: [sum#84, sum#85, sum#86, isEmpty#87, sum#88, isEmpty#89] Results [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] -(64) Exchange +(61) Exchange Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] -Arguments: hashpartitioning(ss_item_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=8] +Arguments: hashpartitioning(ss_item_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=5] -(65) HashAggregate [codegen id : 18] +(62) HashAggregate [codegen id : 15] Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] Keys [1]: [ss_item_sk#71] Functions [4]: [sum(coalesce(sr_return_quantity#80, 0)), sum(coalesce(ss_quantity#73, 0)), sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] Aggregate Attributes [4]: [sum(coalesce(sr_return_quantity#80, 0))#96, sum(coalesce(ss_quantity#73, 0))#97, sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98, sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99] Results [3]: [ss_item_sk#71 AS item#100, (cast(sum(coalesce(sr_return_quantity#80, 0))#96 as decimal(15,4)) / cast(sum(coalesce(ss_quantity#73, 0))#97 as decimal(15,4))) AS return_ratio#101, (cast(sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98 as decimal(15,4)) / cast(sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99 as decimal(15,4))) AS currency_ratio#102] -(66) Exchange +(63) Exchange Input [3]: [item#100, return_ratio#101, currency_ratio#102] -Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=9] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] -(67) Sort [codegen id : 19] +(64) Sort [codegen id : 16] Input [3]: [item#100, return_ratio#101, currency_ratio#102] Arguments: [return_ratio#101 ASC NULLS FIRST], false, 0 -(68) Window +(65) Window Input [3]: [item#100, return_ratio#101, currency_ratio#102] Arguments: [rank(return_ratio#101) windowspecdefinition(return_ratio#101 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#103], [return_ratio#101 ASC NULLS FIRST] -(69) Sort [codegen id : 20] +(66) Sort [codegen id : 17] Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] Arguments: [currency_ratio#102 ASC NULLS FIRST], false, 0 -(70) Window +(67) Window Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] Arguments: [rank(currency_ratio#102) windowspecdefinition(currency_ratio#102 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#104], [currency_ratio#102 ASC NULLS FIRST] -(71) Filter [codegen id : 21] +(68) Filter [codegen id : 18] Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] Condition : ((return_rank#103 <= 10) OR (currency_rank#104 <= 10)) -(72) Project [codegen id : 21] +(69) Project [codegen id : 18] Output [5]: [store AS channel#105, item#100, return_ratio#101, return_rank#103, currency_rank#104] Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] -(73) Union +(70) Union -(74) HashAggregate [codegen id : 22] +(71) HashAggregate [codegen id : 19] Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Functions: [] Aggregate Attributes: [] Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] -(75) Exchange +(72) Exchange Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] -Arguments: hashpartitioning(channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34, 5), ENSURE_REQUIREMENTS, [plan_id=10] +Arguments: hashpartitioning(channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34, 5), ENSURE_REQUIREMENTS, [plan_id=7] -(76) HashAggregate [codegen id : 23] +(73) HashAggregate [codegen id : 20] Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Functions: [] Aggregate Attributes: [] Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] -(77) TakeOrderedAndProject +(74) TakeOrderedAndProject Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Arguments: 100, [channel#35 ASC NULLS FIRST, return_rank#33 ASC NULLS FIRST, currency_rank#34 ASC NULLS FIRST], [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] ===== Subqueries ===== Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#6 IN dynamicpruning#7 -BroadcastExchange (82) -+- * Project (81) - +- * Filter (80) - +- * ColumnarToRow (79) - +- CometScan parquet spark_catalog.default.date_dim (78) +BroadcastExchange (79) ++- * ColumnarToRow (78) + +- CometProject (77) + +- CometFilter (76) + +- CometScan parquet spark_catalog.default.date_dim (75) -(78) Scan parquet spark_catalog.default.date_dim +(75) Scan parquet spark_catalog.default.date_dim Output [3]: [d_date_sk#13, d_year#106, d_moy#107] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,12), IsNotNull(d_date_sk)] ReadSchema: struct -(79) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#13, d_year#106, d_moy#107] - -(80) Filter [codegen id : 1] +(76) CometFilter Input [3]: [d_date_sk#13, d_year#106, d_moy#107] Condition : ((((isnotnull(d_year#106) AND isnotnull(d_moy#107)) AND (d_year#106 = 2001)) AND (d_moy#107 = 12)) AND isnotnull(d_date_sk#13)) -(81) Project [codegen id : 1] -Output [1]: [d_date_sk#13] +(77) CometProject Input [3]: [d_date_sk#13, d_year#106, d_moy#107] +Arguments: [d_date_sk#13], [d_date_sk#13] + +(78) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#13] -(82) BroadcastExchange +(79) BroadcastExchange Input [1]: [d_date_sk#13] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] -Subquery:2 Hosting operator id = 25 Hosting Expression = cs_sold_date_sk#41 IN dynamicpruning#7 +Subquery:2 Hosting operator id = 24 Hosting Expression = cs_sold_date_sk#41 IN dynamicpruning#7 -Subquery:3 Hosting operator id = 49 Hosting Expression = ss_sold_date_sk#76 IN dynamicpruning#7 +Subquery:3 Hosting operator id = 47 Hosting Expression = ss_sold_date_sk#76 IN dynamicpruning#7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/simplified.txt index b707750da..43ebf34cc 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q49/simplified.txt @@ -1,133 +1,121 @@ TakeOrderedAndProject [channel,return_rank,currency_rank,item,return_ratio] - WholeStageCodegen (23) + WholeStageCodegen (20) HashAggregate [channel,item,return_ratio,return_rank,currency_rank] InputAdapter Exchange [channel,item,return_ratio,return_rank,currency_rank] #1 - WholeStageCodegen (22) + WholeStageCodegen (19) HashAggregate [channel,item,return_ratio,return_rank,currency_rank] InputAdapter Union - WholeStageCodegen (7) + WholeStageCodegen (6) Project [item,return_ratio,return_rank,currency_rank] Filter [return_rank,currency_rank] InputAdapter Window [currency_ratio] - WholeStageCodegen (6) + WholeStageCodegen (5) Sort [currency_ratio] InputAdapter Window [return_ratio] - WholeStageCodegen (5) + WholeStageCodegen (4) Sort [return_ratio] InputAdapter Exchange #2 - WholeStageCodegen (4) + WholeStageCodegen (3) HashAggregate [ws_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(wr_return_quantity, 0)),sum(coalesce(ws_quantity, 0)),sum(coalesce(cast(wr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ws_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] InputAdapter Exchange [ws_item_sk] #3 - WholeStageCodegen (3) + WholeStageCodegen (2) HashAggregate [ws_item_sk,wr_return_quantity,ws_quantity,wr_return_amt,ws_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] Project [ws_item_sk,ws_quantity,ws_net_paid,wr_return_quantity,wr_return_amt] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Project [ws_item_sk,ws_quantity,ws_net_paid,ws_sold_date_sk,wr_return_quantity,wr_return_amt] - BroadcastHashJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] - InputAdapter - BroadcastExchange #4 - WholeStageCodegen (1) - Project [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_sold_date_sk] - Filter [ws_net_profit,ws_net_paid,ws_quantity,ws_order_number,ws_item_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_net_profit,ws_sold_date_sk] - SubqueryBroadcast [d_date_sk] #1 - BroadcastExchange #5 - WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] - Project [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] - Filter [wr_return_amt,wr_order_number,wr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ws_item_sk,ws_quantity,ws_net_paid,ws_sold_date_sk,wr_return_quantity,wr_return_amt] + CometBroadcastHashJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + CometBroadcastExchange #4 + CometProject [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_sold_date_sk] + CometFilter [ws_net_profit,ws_net_paid,ws_quantity,ws_order_number,ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_net_profit,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + CometProject [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + CometFilter [wr_return_amt,wr_order_number,wr_item_sk] CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #5 - WholeStageCodegen (14) + WholeStageCodegen (12) Project [item,return_ratio,return_rank,currency_rank] Filter [return_rank,currency_rank] InputAdapter Window [currency_ratio] - WholeStageCodegen (13) + WholeStageCodegen (11) Sort [currency_ratio] InputAdapter Window [return_ratio] - WholeStageCodegen (12) + WholeStageCodegen (10) Sort [return_ratio] InputAdapter Exchange #6 - WholeStageCodegen (11) + WholeStageCodegen (9) HashAggregate [cs_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(cr_return_quantity, 0)),sum(coalesce(cs_quantity, 0)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum(coalesce(cast(cs_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] InputAdapter Exchange [cs_item_sk] #7 - WholeStageCodegen (10) + WholeStageCodegen (8) HashAggregate [cs_item_sk,cr_return_quantity,cs_quantity,cr_return_amount,cs_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] Project [cs_item_sk,cs_quantity,cs_net_paid,cr_return_quantity,cr_return_amount] BroadcastHashJoin [cs_sold_date_sk,d_date_sk] - Project [cs_item_sk,cs_quantity,cs_net_paid,cs_sold_date_sk,cr_return_quantity,cr_return_amount] - BroadcastHashJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] - InputAdapter - BroadcastExchange #8 - WholeStageCodegen (8) - Project [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_sold_date_sk] - Filter [cs_net_profit,cs_net_paid,cs_quantity,cs_order_number,cs_item_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_net_profit,cs_sold_date_sk] - ReusedSubquery [d_date_sk] #1 - Project [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] - Filter [cr_return_amount,cr_order_number,cr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cs_item_sk,cs_quantity,cs_net_paid,cs_sold_date_sk,cr_return_quantity,cr_return_amount] + CometBroadcastHashJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + CometBroadcastExchange #8 + CometProject [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_sold_date_sk] + CometFilter [cs_net_profit,cs_net_paid,cs_quantity,cs_order_number,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + CometFilter [cr_return_amount,cr_order_number,cr_item_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #5 - WholeStageCodegen (21) + WholeStageCodegen (18) Project [item,return_ratio,return_rank,currency_rank] Filter [return_rank,currency_rank] InputAdapter Window [currency_ratio] - WholeStageCodegen (20) + WholeStageCodegen (17) Sort [currency_ratio] InputAdapter Window [return_ratio] - WholeStageCodegen (19) + WholeStageCodegen (16) Sort [return_ratio] InputAdapter Exchange #9 - WholeStageCodegen (18) + WholeStageCodegen (15) HashAggregate [ss_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(sr_return_quantity, 0)),sum(coalesce(ss_quantity, 0)),sum(coalesce(cast(sr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ss_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] InputAdapter Exchange [ss_item_sk] #10 - WholeStageCodegen (17) + WholeStageCodegen (14) HashAggregate [ss_item_sk,sr_return_quantity,ss_quantity,sr_return_amt,ss_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] Project [ss_item_sk,ss_quantity,ss_net_paid,sr_return_quantity,sr_return_amt] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Project [ss_item_sk,ss_quantity,ss_net_paid,ss_sold_date_sk,sr_return_quantity,sr_return_amt] - BroadcastHashJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] - InputAdapter - BroadcastExchange #11 - WholeStageCodegen (15) - Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_sold_date_sk] - Filter [ss_net_profit,ss_net_paid,ss_quantity,ss_ticket_number,ss_item_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_net_profit,ss_sold_date_sk] - ReusedSubquery [d_date_sk] #1 - Project [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] - Filter [sr_return_amt,sr_ticket_number,sr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_quantity,ss_net_paid,ss_sold_date_sk,sr_return_quantity,sr_return_amt] + CometBroadcastHashJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + CometBroadcastExchange #11 + CometProject [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_sold_date_sk] + CometFilter [ss_net_profit,ss_net_paid,ss_quantity,ss_ticket_number,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_net_profit,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + CometFilter [sr_return_amt,sr_ticket_number,sr_item_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/explain.txt index b62cad834..e3f7538d1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/explain.txt @@ -1,78 +1,74 @@ == Physical Plan == -TakeOrderedAndProject (74) -+- * HashAggregate (73) - +- Exchange (72) - +- * HashAggregate (71) - +- * Expand (70) - +- Union (69) - :- * HashAggregate (21) - : +- Exchange (20) - : +- * HashAggregate (19) - : +- * Project (18) - : +- * BroadcastHashJoin Inner BuildRight (17) - : :- * Project (12) - : : +- * BroadcastHashJoin Inner BuildRight (11) - : : :- Union (9) - : : : :- * Project (4) - : : : : +- * Filter (3) - : : : : +- * ColumnarToRow (2) - : : : : +- CometScan parquet spark_catalog.default.store_sales (1) - : : : +- * Project (8) - : : : +- * Filter (7) - : : : +- * ColumnarToRow (6) - : : : +- CometScan parquet spark_catalog.default.store_returns (5) - : : +- ReusedExchange (10) - : +- BroadcastExchange (16) - : +- * Filter (15) - : +- * ColumnarToRow (14) - : +- CometScan parquet spark_catalog.default.store (13) - :- * HashAggregate (42) - : +- Exchange (41) - : +- * HashAggregate (40) - : +- * Project (39) - : +- * BroadcastHashJoin Inner BuildRight (38) - : :- * Project (33) - : : +- * BroadcastHashJoin Inner BuildRight (32) - : : :- Union (30) - : : : :- * Project (25) - : : : : +- * Filter (24) - : : : : +- * ColumnarToRow (23) - : : : : +- CometScan parquet spark_catalog.default.catalog_sales (22) - : : : +- * Project (29) - : : : +- * Filter (28) - : : : +- * ColumnarToRow (27) - : : : +- CometScan parquet spark_catalog.default.catalog_returns (26) - : : +- ReusedExchange (31) - : +- BroadcastExchange (37) - : +- * Filter (36) - : +- * ColumnarToRow (35) - : +- CometScan parquet spark_catalog.default.catalog_page (34) - +- * HashAggregate (68) - +- Exchange (67) - +- * HashAggregate (66) - +- * Project (65) - +- * BroadcastHashJoin Inner BuildRight (64) - :- * Project (59) - : +- * BroadcastHashJoin Inner BuildRight (58) - : :- Union (56) - : : :- * Project (46) - : : : +- * Filter (45) - : : : +- * ColumnarToRow (44) - : : : +- CometScan parquet spark_catalog.default.web_sales (43) - : : +- * Project (55) - : : +- * BroadcastHashJoin Inner BuildLeft (54) - : : :- BroadcastExchange (49) - : : : +- * ColumnarToRow (48) - : : : +- CometScan parquet spark_catalog.default.web_returns (47) - : : +- * Project (53) - : : +- * Filter (52) - : : +- * ColumnarToRow (51) - : : +- CometScan parquet spark_catalog.default.web_sales (50) - : +- ReusedExchange (57) - +- BroadcastExchange (63) - +- * Filter (62) - +- * ColumnarToRow (61) - +- CometScan parquet spark_catalog.default.web_site (60) +TakeOrderedAndProject (70) ++- * HashAggregate (69) + +- Exchange (68) + +- * HashAggregate (67) + +- * Expand (66) + +- Union (65) + :- * HashAggregate (20) + : +- Exchange (19) + : +- * HashAggregate (18) + : +- * Project (17) + : +- * BroadcastHashJoin Inner BuildRight (16) + : :- * Project (11) + : : +- * BroadcastHashJoin Inner BuildRight (10) + : : :- * ColumnarToRow (8) + : : : +- CometUnion (7) + : : : :- CometProject (3) + : : : : +- CometFilter (2) + : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : +- CometProject (6) + : : : +- CometFilter (5) + : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : +- ReusedExchange (9) + : +- BroadcastExchange (15) + : +- * ColumnarToRow (14) + : +- CometFilter (13) + : +- CometScan parquet spark_catalog.default.store (12) + :- * HashAggregate (40) + : +- Exchange (39) + : +- * HashAggregate (38) + : +- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (31) + : : +- * BroadcastHashJoin Inner BuildRight (30) + : : :- * ColumnarToRow (28) + : : : +- CometUnion (27) + : : : :- CometProject (23) + : : : : +- CometFilter (22) + : : : : +- CometScan parquet spark_catalog.default.catalog_sales (21) + : : : +- CometProject (26) + : : : +- CometFilter (25) + : : : +- CometScan parquet spark_catalog.default.catalog_returns (24) + : : +- ReusedExchange (29) + : +- BroadcastExchange (35) + : +- * ColumnarToRow (34) + : +- CometFilter (33) + : +- CometScan parquet spark_catalog.default.catalog_page (32) + +- * HashAggregate (64) + +- Exchange (63) + +- * HashAggregate (62) + +- * Project (61) + +- * BroadcastHashJoin Inner BuildRight (60) + :- * Project (55) + : +- * BroadcastHashJoin Inner BuildRight (54) + : :- * ColumnarToRow (52) + : : +- CometUnion (51) + : : :- CometProject (43) + : : : +- CometFilter (42) + : : : +- CometScan parquet spark_catalog.default.web_sales (41) + : : +- CometProject (50) + : : +- CometBroadcastHashJoin (49) + : : :- CometBroadcastExchange (45) + : : : +- CometScan parquet spark_catalog.default.web_returns (44) + : : +- CometProject (48) + : : +- CometFilter (47) + : : +- CometScan parquet spark_catalog.default.web_sales (46) + : +- ReusedExchange (53) + +- BroadcastExchange (59) + +- * ColumnarToRow (58) + +- CometFilter (57) + +- CometScan parquet spark_catalog.default.web_site (56) (1) Scan parquet spark_catalog.default.store_sales @@ -83,18 +79,15 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] Condition : isnotnull(ss_store_sk#1) -(4) Project [codegen id : 1] -Output [6]: [ss_store_sk#1 AS store_sk#6, ss_sold_date_sk#4 AS date_sk#7, ss_ext_sales_price#2 AS sales_price#8, ss_net_profit#3 AS profit#9, 0.00 AS return_amt#10, 0.00 AS net_loss#11] +(3) CometProject Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Arguments: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11], [ss_store_sk#1 AS store_sk#6, ss_sold_date_sk#4 AS date_sk#7, ss_ext_sales_price#2 AS sales_price#8, ss_net_profit#3 AS profit#9, 0.00 AS return_amt#10, 0.00 AS net_loss#11] -(5) Scan parquet spark_catalog.default.store_returns +(4) Scan parquet spark_catalog.default.store_returns Output [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] Batched: true Location: InMemoryFileIndex [] @@ -102,79 +95,81 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#15), dynamicpruningexpression(s PushedFilters: [IsNotNull(sr_store_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 2] -Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] - -(7) Filter [codegen id : 2] +(5) CometFilter Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] Condition : isnotnull(sr_store_sk#12) -(8) Project [codegen id : 2] -Output [6]: [sr_store_sk#12 AS store_sk#16, sr_returned_date_sk#15 AS date_sk#17, 0.00 AS sales_price#18, 0.00 AS profit#19, sr_return_amt#13 AS return_amt#20, sr_net_loss#14 AS net_loss#21] +(6) CometProject Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Arguments: [store_sk#16, date_sk#17, sales_price#18, profit#19, return_amt#20, net_loss#21], [sr_store_sk#12 AS store_sk#16, sr_returned_date_sk#15 AS date_sk#17, 0.00 AS sales_price#18, 0.00 AS profit#19, sr_return_amt#13 AS return_amt#20, sr_net_loss#14 AS net_loss#21] -(9) Union +(7) CometUnion +Child 0 Input [6]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11] +Child 1 Input [6]: [store_sk#16, date_sk#17, sales_price#18, profit#19, return_amt#20, net_loss#21] -(10) ReusedExchange [Reuses operator id: 79] +(8) ColumnarToRow [codegen id : 3] +Input [6]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11] + +(9) ReusedExchange [Reuses operator id: 75] Output [1]: [d_date_sk#22] -(11) BroadcastHashJoin [codegen id : 5] +(10) BroadcastHashJoin [codegen id : 3] Left keys [1]: [date_sk#7] Right keys [1]: [d_date_sk#22] Join type: Inner Join condition: None -(12) Project [codegen id : 5] +(11) Project [codegen id : 3] Output [5]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11] Input [7]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11, d_date_sk#22] -(13) Scan parquet spark_catalog.default.store +(12) Scan parquet spark_catalog.default.store Output [2]: [s_store_sk#23, s_store_id#24] Batched: true Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 4] +(13) CometFilter Input [2]: [s_store_sk#23, s_store_id#24] +Condition : isnotnull(s_store_sk#23) -(15) Filter [codegen id : 4] +(14) ColumnarToRow [codegen id : 2] Input [2]: [s_store_sk#23, s_store_id#24] -Condition : isnotnull(s_store_sk#23) -(16) BroadcastExchange +(15) BroadcastExchange Input [2]: [s_store_sk#23, s_store_id#24] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] -(17) BroadcastHashJoin [codegen id : 5] +(16) BroadcastHashJoin [codegen id : 3] Left keys [1]: [store_sk#6] Right keys [1]: [s_store_sk#23] Join type: Inner Join condition: None -(18) Project [codegen id : 5] +(17) Project [codegen id : 3] Output [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] Input [7]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_sk#23, s_store_id#24] -(19) HashAggregate [codegen id : 5] +(18) HashAggregate [codegen id : 3] Input [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] Keys [1]: [s_store_id#24] Functions [4]: [partial_sum(UnscaledValue(sales_price#8)), partial_sum(UnscaledValue(return_amt#10)), partial_sum(UnscaledValue(profit#9)), partial_sum(UnscaledValue(net_loss#11))] Aggregate Attributes [4]: [sum#25, sum#26, sum#27, sum#28] Results [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] -(20) Exchange +(19) Exchange Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] Arguments: hashpartitioning(s_store_id#24, 5), ENSURE_REQUIREMENTS, [plan_id=2] -(21) HashAggregate [codegen id : 6] +(20) HashAggregate [codegen id : 4] Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] Keys [1]: [s_store_id#24] Functions [4]: [sum(UnscaledValue(sales_price#8)), sum(UnscaledValue(return_amt#10)), sum(UnscaledValue(profit#9)), sum(UnscaledValue(net_loss#11))] Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#8))#33, sum(UnscaledValue(return_amt#10))#34, sum(UnscaledValue(profit#9))#35, sum(UnscaledValue(net_loss#11))#36] Results [5]: [MakeDecimal(sum(UnscaledValue(sales_price#8))#33,17,2) AS sales#37, MakeDecimal(sum(UnscaledValue(return_amt#10))#34,17,2) AS returns#38, (MakeDecimal(sum(UnscaledValue(profit#9))#35,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#11))#36,17,2)) AS profit#39, store channel AS channel#40, concat(store, s_store_id#24) AS id#41] -(22) Scan parquet spark_catalog.default.catalog_sales +(21) Scan parquet spark_catalog.default.catalog_sales Output [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] Batched: true Location: InMemoryFileIndex [] @@ -182,18 +177,15 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_catalog_page_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 7] -Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] - -(24) Filter [codegen id : 7] +(22) CometFilter Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] Condition : isnotnull(cs_catalog_page_sk#42) -(25) Project [codegen id : 7] -Output [6]: [cs_catalog_page_sk#42 AS page_sk#47, cs_sold_date_sk#45 AS date_sk#48, cs_ext_sales_price#43 AS sales_price#49, cs_net_profit#44 AS profit#50, 0.00 AS return_amt#51, 0.00 AS net_loss#52] +(23) CometProject Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52], [cs_catalog_page_sk#42 AS page_sk#47, cs_sold_date_sk#45 AS date_sk#48, cs_ext_sales_price#43 AS sales_price#49, cs_net_profit#44 AS profit#50, 0.00 AS return_amt#51, 0.00 AS net_loss#52] -(26) Scan parquet spark_catalog.default.catalog_returns +(24) Scan parquet spark_catalog.default.catalog_returns Output [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] Batched: true Location: InMemoryFileIndex [] @@ -201,79 +193,81 @@ PartitionFilters: [isnotnull(cr_returned_date_sk#56), dynamicpruningexpression(c PushedFilters: [IsNotNull(cr_catalog_page_sk)] ReadSchema: struct -(27) ColumnarToRow [codegen id : 8] -Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] - -(28) Filter [codegen id : 8] +(25) CometFilter Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] Condition : isnotnull(cr_catalog_page_sk#53) -(29) Project [codegen id : 8] -Output [6]: [cr_catalog_page_sk#53 AS page_sk#57, cr_returned_date_sk#56 AS date_sk#58, 0.00 AS sales_price#59, 0.00 AS profit#60, cr_return_amount#54 AS return_amt#61, cr_net_loss#55 AS net_loss#62] +(26) CometProject Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Arguments: [page_sk#57, date_sk#58, sales_price#59, profit#60, return_amt#61, net_loss#62], [cr_catalog_page_sk#53 AS page_sk#57, cr_returned_date_sk#56 AS date_sk#58, 0.00 AS sales_price#59, 0.00 AS profit#60, cr_return_amount#54 AS return_amt#61, cr_net_loss#55 AS net_loss#62] + +(27) CometUnion +Child 0 Input [6]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52] +Child 1 Input [6]: [page_sk#57, date_sk#58, sales_price#59, profit#60, return_amt#61, net_loss#62] -(30) Union +(28) ColumnarToRow [codegen id : 7] +Input [6]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52] -(31) ReusedExchange [Reuses operator id: 79] +(29) ReusedExchange [Reuses operator id: 75] Output [1]: [d_date_sk#63] -(32) BroadcastHashJoin [codegen id : 11] +(30) BroadcastHashJoin [codegen id : 7] Left keys [1]: [date_sk#48] Right keys [1]: [d_date_sk#63] Join type: Inner Join condition: None -(33) Project [codegen id : 11] +(31) Project [codegen id : 7] Output [5]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52] Input [7]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52, d_date_sk#63] -(34) Scan parquet spark_catalog.default.catalog_page +(32) Scan parquet spark_catalog.default.catalog_page Output [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] Batched: true Location [not included in comparison]/{warehouse_dir}/catalog_page] PushedFilters: [IsNotNull(cp_catalog_page_sk)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 10] +(33) CometFilter Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Condition : isnotnull(cp_catalog_page_sk#64) -(36) Filter [codegen id : 10] +(34) ColumnarToRow [codegen id : 6] Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] -Condition : isnotnull(cp_catalog_page_sk#64) -(37) BroadcastExchange +(35) BroadcastExchange Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] -(38) BroadcastHashJoin [codegen id : 11] +(36) BroadcastHashJoin [codegen id : 7] Left keys [1]: [page_sk#47] Right keys [1]: [cp_catalog_page_sk#64] Join type: Inner Join condition: None -(39) Project [codegen id : 11] +(37) Project [codegen id : 7] Output [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] Input [7]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_sk#64, cp_catalog_page_id#65] -(40) HashAggregate [codegen id : 11] +(38) HashAggregate [codegen id : 7] Input [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] Keys [1]: [cp_catalog_page_id#65] Functions [4]: [partial_sum(UnscaledValue(sales_price#49)), partial_sum(UnscaledValue(return_amt#51)), partial_sum(UnscaledValue(profit#50)), partial_sum(UnscaledValue(net_loss#52))] Aggregate Attributes [4]: [sum#66, sum#67, sum#68, sum#69] Results [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] -(41) Exchange +(39) Exchange Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] Arguments: hashpartitioning(cp_catalog_page_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=4] -(42) HashAggregate [codegen id : 12] +(40) HashAggregate [codegen id : 8] Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] Keys [1]: [cp_catalog_page_id#65] Functions [4]: [sum(UnscaledValue(sales_price#49)), sum(UnscaledValue(return_amt#51)), sum(UnscaledValue(profit#50)), sum(UnscaledValue(net_loss#52))] Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#49))#74, sum(UnscaledValue(return_amt#51))#75, sum(UnscaledValue(profit#50))#76, sum(UnscaledValue(net_loss#52))#77] Results [5]: [MakeDecimal(sum(UnscaledValue(sales_price#49))#74,17,2) AS sales#78, MakeDecimal(sum(UnscaledValue(return_amt#51))#75,17,2) AS returns#79, (MakeDecimal(sum(UnscaledValue(profit#50))#76,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#52))#77,17,2)) AS profit#80, catalog channel AS channel#81, concat(catalog_page, cp_catalog_page_id#65) AS id#82] -(43) Scan parquet spark_catalog.default.web_sales +(41) Scan parquet spark_catalog.default.web_sales Output [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] Batched: true Location: InMemoryFileIndex [] @@ -281,188 +275,183 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#86), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_web_site_sk)] ReadSchema: struct -(44) ColumnarToRow [codegen id : 13] -Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] - -(45) Filter [codegen id : 13] +(42) CometFilter Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] Condition : isnotnull(ws_web_site_sk#83) -(46) Project [codegen id : 13] -Output [6]: [ws_web_site_sk#83 AS wsr_web_site_sk#88, ws_sold_date_sk#86 AS date_sk#89, ws_ext_sales_price#84 AS sales_price#90, ws_net_profit#85 AS profit#91, 0.00 AS return_amt#92, 0.00 AS net_loss#93] +(43) CometProject Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Arguments: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93], [ws_web_site_sk#83 AS wsr_web_site_sk#88, ws_sold_date_sk#86 AS date_sk#89, ws_ext_sales_price#84 AS sales_price#90, ws_net_profit#85 AS profit#91, 0.00 AS return_amt#92, 0.00 AS net_loss#93] -(47) Scan parquet spark_catalog.default.web_returns +(44) Scan parquet spark_catalog.default.web_returns Output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] Batched: true Location: InMemoryFileIndex [] PartitionFilters: [isnotnull(wr_returned_date_sk#98), dynamicpruningexpression(wr_returned_date_sk#98 IN dynamicpruning#87)] ReadSchema: struct -(48) ColumnarToRow [codegen id : 14] -Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] - -(49) BroadcastExchange +(45) CometBroadcastExchange Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, true] as bigint), 32) | (cast(input[1, int, true] as bigint) & 4294967295))),false), [plan_id=5] +Arguments: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] -(50) Scan parquet spark_catalog.default.web_sales +(46) Scan parquet spark_catalog.default.web_sales Output [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] Batched: true Location [not included in comparison]/{warehouse_dir}/web_sales] PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_site_sk)] ReadSchema: struct -(51) ColumnarToRow -Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] - -(52) Filter +(47) CometFilter Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] Condition : ((isnotnull(ws_item_sk#99) AND isnotnull(ws_order_number#101)) AND isnotnull(ws_web_site_sk#100)) -(53) Project -Output [3]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +(48) CometProject Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Arguments: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101], [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] -(54) BroadcastHashJoin [codegen id : 15] -Left keys [2]: [wr_item_sk#94, wr_order_number#95] -Right keys [2]: [ws_item_sk#99, ws_order_number#101] -Join type: Inner -Join condition: None +(49) CometBroadcastHashJoin +Left output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Right output [3]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +Arguments: [wr_item_sk#94, wr_order_number#95], [ws_item_sk#99, ws_order_number#101], Inner -(55) Project [codegen id : 15] -Output [6]: [ws_web_site_sk#100 AS wsr_web_site_sk#103, wr_returned_date_sk#98 AS date_sk#104, 0.00 AS sales_price#105, 0.00 AS profit#106, wr_return_amt#96 AS return_amt#107, wr_net_loss#97 AS net_loss#108] +(50) CometProject Input [8]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98, ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +Arguments: [wsr_web_site_sk#103, date_sk#104, sales_price#105, profit#106, return_amt#107, net_loss#108], [ws_web_site_sk#100 AS wsr_web_site_sk#103, wr_returned_date_sk#98 AS date_sk#104, 0.00 AS sales_price#105, 0.00 AS profit#106, wr_return_amt#96 AS return_amt#107, wr_net_loss#97 AS net_loss#108] + +(51) CometUnion +Child 0 Input [6]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93] +Child 1 Input [6]: [wsr_web_site_sk#103, date_sk#104, sales_price#105, profit#106, return_amt#107, net_loss#108] -(56) Union +(52) ColumnarToRow [codegen id : 11] +Input [6]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93] -(57) ReusedExchange [Reuses operator id: 79] +(53) ReusedExchange [Reuses operator id: 75] Output [1]: [d_date_sk#109] -(58) BroadcastHashJoin [codegen id : 18] +(54) BroadcastHashJoin [codegen id : 11] Left keys [1]: [date_sk#89] Right keys [1]: [d_date_sk#109] Join type: Inner Join condition: None -(59) Project [codegen id : 18] +(55) Project [codegen id : 11] Output [5]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93] Input [7]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93, d_date_sk#109] -(60) Scan parquet spark_catalog.default.web_site +(56) Scan parquet spark_catalog.default.web_site Output [2]: [web_site_sk#110, web_site_id#111] Batched: true Location [not included in comparison]/{warehouse_dir}/web_site] PushedFilters: [IsNotNull(web_site_sk)] ReadSchema: struct -(61) ColumnarToRow [codegen id : 17] +(57) CometFilter Input [2]: [web_site_sk#110, web_site_id#111] +Condition : isnotnull(web_site_sk#110) -(62) Filter [codegen id : 17] +(58) ColumnarToRow [codegen id : 10] Input [2]: [web_site_sk#110, web_site_id#111] -Condition : isnotnull(web_site_sk#110) -(63) BroadcastExchange +(59) BroadcastExchange Input [2]: [web_site_sk#110, web_site_id#111] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] -(64) BroadcastHashJoin [codegen id : 18] +(60) BroadcastHashJoin [codegen id : 11] Left keys [1]: [wsr_web_site_sk#88] Right keys [1]: [web_site_sk#110] Join type: Inner Join condition: None -(65) Project [codegen id : 18] +(61) Project [codegen id : 11] Output [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] Input [7]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_sk#110, web_site_id#111] -(66) HashAggregate [codegen id : 18] +(62) HashAggregate [codegen id : 11] Input [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] Keys [1]: [web_site_id#111] Functions [4]: [partial_sum(UnscaledValue(sales_price#90)), partial_sum(UnscaledValue(return_amt#92)), partial_sum(UnscaledValue(profit#91)), partial_sum(UnscaledValue(net_loss#93))] Aggregate Attributes [4]: [sum#112, sum#113, sum#114, sum#115] Results [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] -(67) Exchange +(63) Exchange Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] -Arguments: hashpartitioning(web_site_id#111, 5), ENSURE_REQUIREMENTS, [plan_id=7] +Arguments: hashpartitioning(web_site_id#111, 5), ENSURE_REQUIREMENTS, [plan_id=6] -(68) HashAggregate [codegen id : 19] +(64) HashAggregate [codegen id : 12] Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] Keys [1]: [web_site_id#111] Functions [4]: [sum(UnscaledValue(sales_price#90)), sum(UnscaledValue(return_amt#92)), sum(UnscaledValue(profit#91)), sum(UnscaledValue(net_loss#93))] Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#90))#120, sum(UnscaledValue(return_amt#92))#121, sum(UnscaledValue(profit#91))#122, sum(UnscaledValue(net_loss#93))#123] Results [5]: [MakeDecimal(sum(UnscaledValue(sales_price#90))#120,17,2) AS sales#124, MakeDecimal(sum(UnscaledValue(return_amt#92))#121,17,2) AS returns#125, (MakeDecimal(sum(UnscaledValue(profit#91))#122,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#93))#123,17,2)) AS profit#126, web channel AS channel#127, concat(web_site, web_site_id#111) AS id#128] -(69) Union +(65) Union -(70) Expand [codegen id : 20] +(66) Expand [codegen id : 13] Input [5]: [sales#37, returns#38, profit#39, channel#40, id#41] Arguments: [[sales#37, returns#38, profit#39, channel#40, id#41, 0], [sales#37, returns#38, profit#39, channel#40, null, 1], [sales#37, returns#38, profit#39, null, null, 3]], [sales#37, returns#38, profit#39, channel#129, id#130, spark_grouping_id#131] -(71) HashAggregate [codegen id : 20] +(67) HashAggregate [codegen id : 13] Input [6]: [sales#37, returns#38, profit#39, channel#129, id#130, spark_grouping_id#131] Keys [3]: [channel#129, id#130, spark_grouping_id#131] Functions [3]: [partial_sum(sales#37), partial_sum(returns#38), partial_sum(profit#39)] Aggregate Attributes [6]: [sum#132, isEmpty#133, sum#134, isEmpty#135, sum#136, isEmpty#137] Results [9]: [channel#129, id#130, spark_grouping_id#131, sum#138, isEmpty#139, sum#140, isEmpty#141, sum#142, isEmpty#143] -(72) Exchange +(68) Exchange Input [9]: [channel#129, id#130, spark_grouping_id#131, sum#138, isEmpty#139, sum#140, isEmpty#141, sum#142, isEmpty#143] -Arguments: hashpartitioning(channel#129, id#130, spark_grouping_id#131, 5), ENSURE_REQUIREMENTS, [plan_id=8] +Arguments: hashpartitioning(channel#129, id#130, spark_grouping_id#131, 5), ENSURE_REQUIREMENTS, [plan_id=7] -(73) HashAggregate [codegen id : 21] +(69) HashAggregate [codegen id : 14] Input [9]: [channel#129, id#130, spark_grouping_id#131, sum#138, isEmpty#139, sum#140, isEmpty#141, sum#142, isEmpty#143] Keys [3]: [channel#129, id#130, spark_grouping_id#131] Functions [3]: [sum(sales#37), sum(returns#38), sum(profit#39)] Aggregate Attributes [3]: [sum(sales#37)#144, sum(returns#38)#145, sum(profit#39)#146] Results [5]: [channel#129, id#130, sum(sales#37)#144 AS sales#147, sum(returns#38)#145 AS returns#148, sum(profit#39)#146 AS profit#149] -(74) TakeOrderedAndProject +(70) TakeOrderedAndProject Input [5]: [channel#129, id#130, sales#147, returns#148, profit#149] Arguments: 100, [channel#129 ASC NULLS FIRST, id#130 ASC NULLS FIRST], [channel#129, id#130, sales#147, returns#148, profit#149] ===== Subqueries ===== Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 -BroadcastExchange (79) -+- * Project (78) - +- * Filter (77) - +- * ColumnarToRow (76) - +- CometScan parquet spark_catalog.default.date_dim (75) +BroadcastExchange (75) ++- * ColumnarToRow (74) + +- CometProject (73) + +- CometFilter (72) + +- CometScan parquet spark_catalog.default.date_dim (71) -(75) Scan parquet spark_catalog.default.date_dim +(71) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date_sk#22, d_date#150] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-08-23), LessThanOrEqual(d_date,2000-09-06), IsNotNull(d_date_sk)] ReadSchema: struct -(76) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#22, d_date#150] - -(77) Filter [codegen id : 1] +(72) CometFilter Input [2]: [d_date_sk#22, d_date#150] Condition : (((isnotnull(d_date#150) AND (d_date#150 >= 2000-08-23)) AND (d_date#150 <= 2000-09-06)) AND isnotnull(d_date_sk#22)) -(78) Project [codegen id : 1] -Output [1]: [d_date_sk#22] +(73) CometProject Input [2]: [d_date_sk#22, d_date#150] +Arguments: [d_date_sk#22], [d_date_sk#22] + +(74) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#22] -(79) BroadcastExchange +(75) BroadcastExchange Input [1]: [d_date_sk#22] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] -Subquery:2 Hosting operator id = 5 Hosting Expression = sr_returned_date_sk#15 IN dynamicpruning#5 +Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#15 IN dynamicpruning#5 -Subquery:3 Hosting operator id = 22 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#5 +Subquery:3 Hosting operator id = 21 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#5 -Subquery:4 Hosting operator id = 26 Hosting Expression = cr_returned_date_sk#56 IN dynamicpruning#5 +Subquery:4 Hosting operator id = 24 Hosting Expression = cr_returned_date_sk#56 IN dynamicpruning#5 -Subquery:5 Hosting operator id = 43 Hosting Expression = ws_sold_date_sk#86 IN dynamicpruning#5 +Subquery:5 Hosting operator id = 41 Hosting Expression = ws_sold_date_sk#86 IN dynamicpruning#5 -Subquery:6 Hosting operator id = 47 Hosting Expression = wr_returned_date_sk#98 IN dynamicpruning#5 +Subquery:6 Hosting operator id = 44 Hosting Expression = wr_returned_date_sk#98 IN dynamicpruning#5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/simplified.txt index cf9a7db64..3d539d591 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q5/simplified.txt @@ -1,130 +1,111 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] - WholeStageCodegen (21) + WholeStageCodegen (14) HashAggregate [channel,id,spark_grouping_id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] InputAdapter Exchange [channel,id,spark_grouping_id] #1 - WholeStageCodegen (20) + WholeStageCodegen (13) HashAggregate [channel,id,spark_grouping_id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] Expand [sales,returns,profit,channel,id] InputAdapter Union - WholeStageCodegen (6) + WholeStageCodegen (4) HashAggregate [s_store_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),sales,returns,profit,channel,id,sum,sum,sum,sum] InputAdapter Exchange [s_store_id] #2 - WholeStageCodegen (5) + WholeStageCodegen (3) HashAggregate [s_store_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] Project [sales_price,profit,return_amt,net_loss,s_store_id] BroadcastHashJoin [store_sk,s_store_sk] Project [store_sk,sales_price,profit,return_amt,net_loss] BroadcastHashJoin [date_sk,d_date_sk] - InputAdapter - Union - WholeStageCodegen (1) - Project [ss_store_sk,ss_sold_date_sk,ss_ext_sales_price,ss_net_profit] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] - SubqueryBroadcast [d_date_sk] #1 - BroadcastExchange #3 - WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] - WholeStageCodegen (2) - Project [sr_store_sk,sr_returned_date_sk,sr_return_amt,sr_net_loss] - Filter [sr_store_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] - ReusedSubquery [d_date_sk] #1 + ColumnarToRow + InputAdapter + CometUnion + CometProject [ss_store_sk,ss_sold_date_sk,ss_ext_sales_price,ss_net_profit] [store_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + CometProject [sr_store_sk,sr_returned_date_sk,sr_return_amt,sr_net_loss] [store_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [sr_store_sk] + CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 - WholeStageCodegen (4) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] - WholeStageCodegen (12) + WholeStageCodegen (8) HashAggregate [cp_catalog_page_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),sales,returns,profit,channel,id,sum,sum,sum,sum] InputAdapter Exchange [cp_catalog_page_id] #5 - WholeStageCodegen (11) + WholeStageCodegen (7) HashAggregate [cp_catalog_page_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] Project [sales_price,profit,return_amt,net_loss,cp_catalog_page_id] BroadcastHashJoin [page_sk,cp_catalog_page_sk] Project [page_sk,sales_price,profit,return_amt,net_loss] BroadcastHashJoin [date_sk,d_date_sk] - InputAdapter - Union - WholeStageCodegen (7) - Project [cs_catalog_page_sk,cs_sold_date_sk,cs_ext_sales_price,cs_net_profit] - Filter [cs_catalog_page_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] - ReusedSubquery [d_date_sk] #1 - WholeStageCodegen (8) - Project [cr_catalog_page_sk,cr_returned_date_sk,cr_return_amount,cr_net_loss] - Filter [cr_catalog_page_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.catalog_returns [cr_catalog_page_sk,cr_return_amount,cr_net_loss,cr_returned_date_sk] - ReusedSubquery [d_date_sk] #1 + ColumnarToRow + InputAdapter + CometUnion + CometProject [cs_catalog_page_sk,cs_sold_date_sk,cs_ext_sales_price,cs_net_profit] [page_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [cs_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [cr_catalog_page_sk,cr_returned_date_sk,cr_return_amount,cr_net_loss] [page_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [cr_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_catalog_page_sk,cr_return_amount,cr_net_loss,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #6 - WholeStageCodegen (10) - Filter [cp_catalog_page_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [cp_catalog_page_sk] CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] - WholeStageCodegen (19) + WholeStageCodegen (12) HashAggregate [web_site_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),sales,returns,profit,channel,id,sum,sum,sum,sum] InputAdapter Exchange [web_site_id] #7 - WholeStageCodegen (18) + WholeStageCodegen (11) HashAggregate [web_site_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] Project [sales_price,profit,return_amt,net_loss,web_site_id] BroadcastHashJoin [wsr_web_site_sk,web_site_sk] Project [wsr_web_site_sk,sales_price,profit,return_amt,net_loss] BroadcastHashJoin [date_sk,d_date_sk] - InputAdapter - Union - WholeStageCodegen (13) - Project [ws_web_site_sk,ws_sold_date_sk,ws_ext_sales_price,ws_net_profit] - Filter [ws_web_site_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_sales [ws_web_site_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] - ReusedSubquery [d_date_sk] #1 - WholeStageCodegen (15) - Project [ws_web_site_sk,wr_returned_date_sk,wr_return_amt,wr_net_loss] - BroadcastHashJoin [wr_item_sk,wr_order_number,ws_item_sk,ws_order_number] - InputAdapter - BroadcastExchange #8 - WholeStageCodegen (14) - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] - ReusedSubquery [d_date_sk] #1 - Project [ws_item_sk,ws_web_site_sk,ws_order_number] - Filter [ws_item_sk,ws_order_number,ws_web_site_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_order_number,ws_sold_date_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [ws_web_site_sk,ws_sold_date_sk,ws_ext_sales_price,ws_net_profit] [wsr_web_site_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [ws_web_site_sk] + CometScan parquet spark_catalog.default.web_sales [ws_web_site_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [ws_web_site_sk,wr_returned_date_sk,wr_return_amt,wr_net_loss] [wsr_web_site_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometBroadcastHashJoin [wr_item_sk,wr_order_number,ws_item_sk,ws_order_number] + CometBroadcastExchange #8 + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [ws_item_sk,ws_web_site_sk,ws_order_number] + CometFilter [ws_item_sk,ws_order_number,ws_web_site_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_order_number,ws_sold_date_sk] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #9 - WholeStageCodegen (17) - Filter [web_site_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometFilter [web_site_sk] CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/explain.txt index 8422950c2..0182e0ac1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/explain.txt @@ -11,20 +11,20 @@ TakeOrderedAndProject (28) : : +- * BroadcastHashJoin Inner BuildRight (14) : : :- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.store_returns (4) : : +- BroadcastExchange (13) - : : +- * Filter (12) - : : +- * ColumnarToRow (11) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) : : +- CometScan parquet spark_catalog.default.store (10) : +- BroadcastExchange (19) - : +- * Filter (18) - : +- * ColumnarToRow (17) + : +- * ColumnarToRow (18) + : +- CometFilter (17) : +- CometScan parquet spark_catalog.default.date_dim (16) +- ReusedExchange (22) @@ -37,12 +37,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#5)] PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_store_sk#3)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] -Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_store_sk#3)) (4) Scan parquet spark_catalog.default.store_returns Output [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] @@ -52,12 +52,12 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#9), dynamicpruningexpression(sr PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk), IsNotNull(sr_customer_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Condition : ((isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#6)) AND isnotnull(sr_customer_sk#7)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] -Condition : ((isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#6)) AND isnotnull(sr_customer_sk#7)) (7) BroadcastExchange Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] @@ -80,12 +80,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] +Condition : isnotnull(s_store_sk#11) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] -Condition : isnotnull(s_store_sk#11) (13) BroadcastExchange Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21] @@ -108,12 +108,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 3] +(17) CometFilter Input [1]: [d_date_sk#22] +Condition : isnotnull(d_date_sk#22) -(18) Filter [codegen id : 3] +(18) ColumnarToRow [codegen id : 3] Input [1]: [d_date_sk#22] -Condition : isnotnull(d_date_sk#22) (19) BroadcastExchange Input [1]: [d_date_sk#22] @@ -168,9 +168,9 @@ Arguments: 100, [s_store_name#12 ASC NULLS FIRST, s_company_id#13 ASC NULLS FIRS Subquery:1 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#9 IN dynamicpruning#10 BroadcastExchange (33) -+- * Project (32) - +- * Filter (31) - +- * ColumnarToRow (30) ++- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) +- CometScan parquet spark_catalog.default.date_dim (29) @@ -181,16 +181,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,8), IsNotNull(d_date_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#23, d_year#44, d_moy#45] - -(31) Filter [codegen id : 1] +(30) CometFilter Input [3]: [d_date_sk#23, d_year#44, d_moy#45] Condition : ((((isnotnull(d_year#44) AND isnotnull(d_moy#45)) AND (d_year#44 = 2001)) AND (d_moy#45 = 8)) AND isnotnull(d_date_sk#23)) -(32) Project [codegen id : 1] -Output [1]: [d_date_sk#23] +(31) CometProject Input [3]: [d_date_sk#23, d_year#44, d_moy#45] +Arguments: [d_date_sk#23], [d_date_sk#23] + +(32) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#23] (33) BroadcastExchange Input [1]: [d_date_sk#23] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/simplified.txt index 67c991f71..dfdcaf497 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q50/simplified.txt @@ -13,38 +13,38 @@ TakeOrderedAndProject [s_store_name,s_company_id,s_street_number,s_street_name,s BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_store_sk,ss_sold_date_sk,sr_returned_date_sk] BroadcastHashJoin [ss_ticket_number,ss_item_sk,ss_customer_sk,sr_ticket_number,sr_item_sk,sr_customer_sk] - Filter [ss_ticket_number,ss_item_sk,ss_customer_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_ticket_number,ss_item_sk,ss_customer_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [sr_ticket_number,sr_item_sk,sr_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sr_ticket_number,sr_item_sk,sr_customer_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_customer_sk,sr_ticket_number,sr_returned_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_id,s_street_number,s_street_name,s_street_type,s_suite_number,s_city,s_county,s_state,s_zip] InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk] InputAdapter ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/explain.txt index dd0fdb3f0..2613551f0 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/explain.txt @@ -17,8 +17,8 @@ TakeOrderedAndProject (37) : +- * HashAggregate (7) : +- * Project (6) : +- * BroadcastHashJoin Inner BuildRight (5) - : :- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.web_sales (1) : +- ReusedExchange (4) +- * Sort (30) @@ -32,8 +32,8 @@ TakeOrderedAndProject (37) +- * HashAggregate (22) +- * Project (21) +- * BroadcastHashJoin Inner BuildRight (20) - :- * Filter (18) - : +- * ColumnarToRow (17) + :- * ColumnarToRow (18) + : +- CometFilter (17) : +- CometScan parquet spark_catalog.default.store_sales (16) +- ReusedExchange (19) @@ -46,12 +46,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 2] +(2) CometFilter Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) -(3) Filter [codegen id : 2] +(3) ColumnarToRow [codegen id : 2] Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] -Condition : isnotnull(ws_item_sk#1) (4) ReusedExchange [Reuses operator id: 42] Output [2]: [d_date_sk#5, d_date#6] @@ -116,12 +116,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#15), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 8] +(17) CometFilter Input [3]: [ss_item_sk#13, ss_sales_price#14, ss_sold_date_sk#15] +Condition : isnotnull(ss_item_sk#13) -(18) Filter [codegen id : 8] +(18) ColumnarToRow [codegen id : 8] Input [3]: [ss_item_sk#13, ss_sales_price#14, ss_sold_date_sk#15] -Condition : isnotnull(ss_item_sk#13) (19) ReusedExchange [Reuses operator id: 42] Output [2]: [d_date_sk#17, d_date#18] @@ -212,9 +212,9 @@ Arguments: 100, [item_sk#25 ASC NULLS FIRST, d_date#26 ASC NULLS FIRST], [item_s Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (42) -+- * Project (41) - +- * Filter (40) - +- * ColumnarToRow (39) ++- * ColumnarToRow (41) + +- CometProject (40) + +- CometFilter (39) +- CometScan parquet spark_catalog.default.date_dim (38) @@ -225,16 +225,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(39) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#5, d_date#6, d_month_seq#31] - -(40) Filter [codegen id : 1] +(39) CometFilter Input [3]: [d_date_sk#5, d_date#6, d_month_seq#31] Condition : (((isnotnull(d_month_seq#31) AND (d_month_seq#31 >= 1200)) AND (d_month_seq#31 <= 1211)) AND isnotnull(d_date_sk#5)) -(41) Project [codegen id : 1] -Output [2]: [d_date_sk#5, d_date#6] +(40) CometProject Input [3]: [d_date_sk#5, d_date#6, d_month_seq#31] +Arguments: [d_date_sk#5, d_date#6], [d_date_sk#5, d_date#6] + +(41) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#5, d_date#6] (42) BroadcastExchange Input [2]: [d_date_sk#5, d_date#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/simplified.txt index a6ce8a445..181cd1b98 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q51/simplified.txt @@ -31,17 +31,17 @@ TakeOrderedAndProject [item_sk,d_date,web_sales,store_sales,web_cumulative,store HashAggregate [ws_item_sk,d_date,ws_sales_price] [sum,sum] Project [ws_item_sk,ws_sales_price,d_date] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sales_price,ws_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #5 WholeStageCodegen (1) - Project [d_date_sk,d_date] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] InputAdapter ReusedExchange [d_date_sk,d_date] #5 @@ -66,9 +66,9 @@ TakeOrderedAndProject [item_sk,d_date,web_sales,store_sales,web_cumulative,store HashAggregate [ss_item_sk,d_date,ss_sales_price] [sum,sum] Project [ss_item_sk,ss_sales_price,d_date] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sales_price,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/explain.txt index f8131fa11..3d5317eb0 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/explain.txt @@ -7,18 +7,18 @@ TakeOrderedAndProject (21) +- * BroadcastHashJoin Inner BuildRight (16) :- * Project (10) : +- * BroadcastHashJoin Inner BuildRight (9) - : :- * Project (4) - : : +- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.date_dim (1) : +- BroadcastExchange (8) - : +- * Filter (7) - : +- * ColumnarToRow (6) + : +- * ColumnarToRow (7) + : +- CometFilter (6) : +- CometScan parquet spark_catalog.default.store_sales (5) +- BroadcastExchange (15) - +- * Project (14) - +- * Filter (13) - +- * ColumnarToRow (12) + +- * ColumnarToRow (14) + +- CometProject (13) + +- CometFilter (12) +- CometScan parquet spark_catalog.default.item (11) @@ -29,16 +29,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] -Input [3]: [d_date_sk#1, d_year#2, d_moy#3] - -(3) Filter [codegen id : 3] +(2) CometFilter Input [3]: [d_date_sk#1, d_year#2, d_moy#3] Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 2000)) AND isnotnull(d_date_sk#1)) -(4) Project [codegen id : 3] -Output [2]: [d_date_sk#1, d_year#2] +(3) CometProject Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Arguments: [d_date_sk#1, d_year#2], [d_date_sk#1, d_year#2] + +(4) ColumnarToRow [codegen id : 3] +Input [2]: [d_date_sk#1, d_year#2] (5) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] @@ -48,12 +48,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] +(6) CometFilter Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) -(7) Filter [codegen id : 1] +(7) ColumnarToRow [codegen id : 1] Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] -Condition : isnotnull(ss_item_sk#4) (8) BroadcastExchange Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] @@ -76,16 +76,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,1), IsNotNull(i_item_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] -Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] - -(13) Filter [codegen id : 2] +(12) CometFilter Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] Condition : ((isnotnull(i_manager_id#10) AND (i_manager_id#10 = 1)) AND isnotnull(i_item_sk#7)) -(14) Project [codegen id : 2] -Output [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +(13) CometProject Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Arguments: [i_item_sk#7, i_brand_id#8, i_brand#9], [i_item_sk#7, i_brand_id#8, i_brand#9] + +(14) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] (15) BroadcastExchange Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/simplified.txt index 591ba96c2..91fdc2f17 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q52/simplified.txt @@ -9,23 +9,23 @@ TakeOrderedAndProject [d_year,ext_price,brand_id,brand] BroadcastHashJoin [ss_item_sk,i_item_sk] Project [d_year,ss_item_sk,ss_ext_sales_price] BroadcastHashJoin [d_date_sk,ss_sold_date_sk] - Project [d_date_sk,d_year] - Filter [d_moy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_year] + CometFilter [d_moy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [i_item_sk,i_brand_id,i_brand] - Filter [i_manager_id,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_brand] + CometFilter [i_manager_id,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manager_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/explain.txt index 741e1e050..335dc7fa2 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/explain.txt @@ -14,18 +14,18 @@ TakeOrderedAndProject (28) : +- * BroadcastHashJoin Inner BuildRight (12) : :- * Project (10) : : +- * BroadcastHashJoin Inner BuildRight (9) - : : :- * Project (4) - : : : +- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.item (1) : : +- BroadcastExchange (8) - : : +- * Filter (7) - : : +- * ColumnarToRow (6) + : : +- * ColumnarToRow (7) + : : +- CometFilter (6) : : +- CometScan parquet spark_catalog.default.store_sales (5) : +- ReusedExchange (11) +- BroadcastExchange (17) - +- * Filter (16) - +- * ColumnarToRow (15) + +- * ColumnarToRow (16) + +- CometFilter (15) +- CometScan parquet spark_catalog.default.store (14) @@ -36,16 +36,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [Or(And(And(In(i_category, [Books ,Children ,Electronics ]),In(i_class, [personal ,portable ,reference ,self-help ])),In(i_brand, [exportiunivamalg #6 ,scholaramalgamalg #7 ,scholaramalgamalg #8 ,scholaramalgamalg #6 ])),And(And(In(i_category, [Men ,Music ,Women ]),In(i_class, [accessories ,classical ,fragrances ,pants ])),In(i_brand, [amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ]))), IsNotNull(i_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] -Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5] - -(3) Filter [codegen id : 4] +(2) CometFilter Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5] Condition : ((((i_category#4 IN (Books ,Children ,Electronics ) AND i_class#3 IN (personal ,portable ,reference ,self-help )) AND i_brand#2 IN (scholaramalgamalg #7 ,scholaramalgamalg #8 ,exportiunivamalg #6 ,scholaramalgamalg #6 )) OR ((i_category#4 IN (Women ,Music ,Men ) AND i_class#3 IN (accessories ,classical ,fragrances ,pants )) AND i_brand#2 IN (amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ))) AND isnotnull(i_item_sk#1)) -(4) Project [codegen id : 4] -Output [2]: [i_item_sk#1, i_manufact_id#5] +(3) CometProject Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5] +Arguments: [i_item_sk#1, i_manufact_id#5], [i_item_sk#1, i_manufact_id#5] + +(4) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#1, i_manufact_id#5] (5) Scan parquet spark_catalog.default.store_sales Output [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] @@ -55,12 +55,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#13), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] +(6) CometFilter Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Condition : (isnotnull(ss_item_sk#10) AND isnotnull(ss_store_sk#11)) -(7) Filter [codegen id : 1] +(7) ColumnarToRow [codegen id : 1] Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] -Condition : (isnotnull(ss_item_sk#10) AND isnotnull(ss_store_sk#11)) (8) BroadcastExchange Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] @@ -96,12 +96,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] +(15) CometFilter Input [1]: [s_store_sk#17] +Condition : isnotnull(s_store_sk#17) -(16) Filter [codegen id : 3] +(16) ColumnarToRow [codegen id : 3] Input [1]: [s_store_sk#17] -Condition : isnotnull(s_store_sk#17) (17) BroadcastExchange Input [1]: [s_store_sk#17] @@ -163,9 +163,9 @@ Arguments: 100, [avg_quarterly_sales#23 ASC NULLS FIRST, sum_sales#21 ASC NULLS Subquery:1 Hosting operator id = 5 Hosting Expression = ss_sold_date_sk#13 IN dynamicpruning#14 BroadcastExchange (33) -+- * Project (32) - +- * Filter (31) - +- * ColumnarToRow (30) ++- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) +- CometScan parquet spark_catalog.default.date_dim (29) @@ -176,16 +176,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [In(d_month_seq, [1200,1201,1202,1203,1204,1205,1206,1207,1208,1209,1210,1211]), IsNotNull(d_date_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#15, d_month_seq#24, d_qoy#16] - -(31) Filter [codegen id : 1] +(30) CometFilter Input [3]: [d_date_sk#15, d_month_seq#24, d_qoy#16] Condition : (d_month_seq#24 INSET 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211 AND isnotnull(d_date_sk#15)) -(32) Project [codegen id : 1] -Output [2]: [d_date_sk#15, d_qoy#16] +(31) CometProject Input [3]: [d_date_sk#15, d_month_seq#24, d_qoy#16] +Arguments: [d_date_sk#15, d_qoy#16], [d_date_sk#15, d_qoy#16] + +(32) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#15, d_qoy#16] (33) BroadcastExchange Input [2]: [d_date_sk#15, d_qoy#16] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/simplified.txt index 5e254d2ac..adda5c34f 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q53/simplified.txt @@ -20,32 +20,32 @@ TakeOrderedAndProject [avg_quarterly_sales,sum_sales,i_manufact_id] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [i_manufact_id,ss_store_sk,ss_sales_price,ss_sold_date_sk] BroadcastHashJoin [i_item_sk,ss_item_sk] - Project [i_item_sk,i_manufact_id] - Filter [i_category,i_class,i_brand,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_manufact_id] + CometFilter [i_category,i_class,i_brand,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_manufact_id] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [ss_item_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk,d_qoy] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_qoy] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_qoy] InputAdapter ReusedExchange [d_date_sk,d_qoy] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/explain.txt index 7ceab6eaa..ca308b19a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/explain.txt @@ -1,60 +1,59 @@ == Physical Plan == -TakeOrderedAndProject (56) -+- * HashAggregate (55) - +- Exchange (54) - +- * HashAggregate (53) - +- * HashAggregate (52) - +- Exchange (51) - +- * HashAggregate (50) - +- * Project (49) - +- * BroadcastHashJoin Inner BuildRight (48) - :- * Project (46) - : +- * BroadcastHashJoin Inner BuildRight (45) - : :- * Project (40) - : : +- * BroadcastHashJoin Inner BuildRight (39) - : : :- * Project (34) - : : : +- * BroadcastHashJoin Inner BuildRight (33) - : : : :- * HashAggregate (28) - : : : : +- Exchange (27) - : : : : +- * HashAggregate (26) - : : : : +- * Project (25) - : : : : +- * BroadcastHashJoin Inner BuildRight (24) - : : : : :- * Project (19) - : : : : : +- * BroadcastHashJoin Inner BuildRight (18) - : : : : : :- * Project (16) - : : : : : : +- * BroadcastHashJoin Inner BuildRight (15) - : : : : : : :- Union (9) - : : : : : : : :- * Project (4) - : : : : : : : : +- * Filter (3) - : : : : : : : : +- * ColumnarToRow (2) - : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) - : : : : : : : +- * Project (8) - : : : : : : : +- * Filter (7) - : : : : : : : +- * ColumnarToRow (6) - : : : : : : : +- CometScan parquet spark_catalog.default.web_sales (5) - : : : : : : +- BroadcastExchange (14) - : : : : : : +- * Project (13) - : : : : : : +- * Filter (12) - : : : : : : +- * ColumnarToRow (11) - : : : : : : +- CometScan parquet spark_catalog.default.item (10) - : : : : : +- ReusedExchange (17) - : : : : +- BroadcastExchange (23) - : : : : +- * Filter (22) - : : : : +- * ColumnarToRow (21) - : : : : +- CometScan parquet spark_catalog.default.customer (20) - : : : +- BroadcastExchange (32) - : : : +- * Filter (31) - : : : +- * ColumnarToRow (30) - : : : +- CometScan parquet spark_catalog.default.store_sales (29) - : : +- BroadcastExchange (38) - : : +- * Filter (37) - : : +- * ColumnarToRow (36) - : : +- CometScan parquet spark_catalog.default.customer_address (35) - : +- BroadcastExchange (44) - : +- * Filter (43) - : +- * ColumnarToRow (42) - : +- CometScan parquet spark_catalog.default.store (41) - +- ReusedExchange (47) +TakeOrderedAndProject (55) ++- * HashAggregate (54) + +- Exchange (53) + +- * HashAggregate (52) + +- * HashAggregate (51) + +- Exchange (50) + +- * HashAggregate (49) + +- * Project (48) + +- * BroadcastHashJoin Inner BuildRight (47) + :- * Project (45) + : +- * BroadcastHashJoin Inner BuildRight (44) + : :- * Project (39) + : : +- * BroadcastHashJoin Inner BuildRight (38) + : : :- * Project (33) + : : : +- * BroadcastHashJoin Inner BuildRight (32) + : : : :- * HashAggregate (27) + : : : : +- Exchange (26) + : : : : +- * HashAggregate (25) + : : : : +- * Project (24) + : : : : +- * BroadcastHashJoin Inner BuildRight (23) + : : : : :- * Project (18) + : : : : : +- * BroadcastHashJoin Inner BuildRight (17) + : : : : : :- * Project (15) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : : :- * ColumnarToRow (8) + : : : : : : : +- CometUnion (7) + : : : : : : : :- CometProject (3) + : : : : : : : : +- CometFilter (2) + : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) + : : : : : : : +- CometProject (6) + : : : : : : : +- CometFilter (5) + : : : : : : : +- CometScan parquet spark_catalog.default.web_sales (4) + : : : : : : +- BroadcastExchange (13) + : : : : : : +- * ColumnarToRow (12) + : : : : : : +- CometProject (11) + : : : : : : +- CometFilter (10) + : : : : : : +- CometScan parquet spark_catalog.default.item (9) + : : : : : +- ReusedExchange (16) + : : : : +- BroadcastExchange (22) + : : : : +- * ColumnarToRow (21) + : : : : +- CometFilter (20) + : : : : +- CometScan parquet spark_catalog.default.customer (19) + : : : +- BroadcastExchange (31) + : : : +- * ColumnarToRow (30) + : : : +- CometFilter (29) + : : : +- CometScan parquet spark_catalog.default.store_sales (28) + : : +- BroadcastExchange (37) + : : +- * ColumnarToRow (36) + : : +- CometFilter (35) + : : +- CometScan parquet spark_catalog.default.customer_address (34) + : +- BroadcastExchange (43) + : +- * ColumnarToRow (42) + : +- CometFilter (41) + : +- CometScan parquet spark_catalog.default.store (40) + +- ReusedExchange (46) (1) Scan parquet spark_catalog.default.catalog_sales @@ -65,18 +64,15 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_bill_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [3]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_sold_date_sk#3] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [3]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_sold_date_sk#3] Condition : (isnotnull(cs_item_sk#2) AND isnotnull(cs_bill_customer_sk#1)) -(4) Project [codegen id : 1] -Output [3]: [cs_sold_date_sk#3 AS sold_date_sk#5, cs_bill_customer_sk#1 AS customer_sk#6, cs_item_sk#2 AS item_sk#7] +(3) CometProject Input [3]: [cs_bill_customer_sk#1, cs_item_sk#2, cs_sold_date_sk#3] +Arguments: [sold_date_sk#5, customer_sk#6, item_sk#7], [cs_sold_date_sk#3 AS sold_date_sk#5, cs_bill_customer_sk#1 AS customer_sk#6, cs_item_sk#2 AS item_sk#7] -(5) Scan parquet spark_catalog.default.web_sales +(4) Scan parquet spark_catalog.default.web_sales Output [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] Batched: true Location: InMemoryFileIndex [] @@ -84,111 +80,113 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#10), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 2] -Input [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] - -(7) Filter [codegen id : 2] +(5) CometFilter Input [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] Condition : (isnotnull(ws_item_sk#8) AND isnotnull(ws_bill_customer_sk#9)) -(8) Project [codegen id : 2] -Output [3]: [ws_sold_date_sk#10 AS sold_date_sk#11, ws_bill_customer_sk#9 AS customer_sk#12, ws_item_sk#8 AS item_sk#13] +(6) CometProject Input [3]: [ws_item_sk#8, ws_bill_customer_sk#9, ws_sold_date_sk#10] +Arguments: [sold_date_sk#11, customer_sk#12, item_sk#13], [ws_sold_date_sk#10 AS sold_date_sk#11, ws_bill_customer_sk#9 AS customer_sk#12, ws_item_sk#8 AS item_sk#13] + +(7) CometUnion +Child 0 Input [3]: [sold_date_sk#5, customer_sk#6, item_sk#7] +Child 1 Input [3]: [sold_date_sk#11, customer_sk#12, item_sk#13] -(9) Union +(8) ColumnarToRow [codegen id : 4] +Input [3]: [sold_date_sk#5, customer_sk#6, item_sk#7] -(10) Scan parquet spark_catalog.default.item +(9) Scan parquet spark_catalog.default.item Output [3]: [i_item_sk#14, i_class#15, i_category#16] Batched: true Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_category), IsNotNull(i_class), EqualTo(i_category,Women ), EqualTo(i_class,maternity ), IsNotNull(i_item_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 3] -Input [3]: [i_item_sk#14, i_class#15, i_category#16] - -(12) Filter [codegen id : 3] +(10) CometFilter Input [3]: [i_item_sk#14, i_class#15, i_category#16] Condition : ((((isnotnull(i_category#16) AND isnotnull(i_class#15)) AND (i_category#16 = Women )) AND (i_class#15 = maternity )) AND isnotnull(i_item_sk#14)) -(13) Project [codegen id : 3] -Output [1]: [i_item_sk#14] +(11) CometProject Input [3]: [i_item_sk#14, i_class#15, i_category#16] +Arguments: [i_item_sk#14], [i_item_sk#14] -(14) BroadcastExchange +(12) ColumnarToRow [codegen id : 1] +Input [1]: [i_item_sk#14] + +(13) BroadcastExchange Input [1]: [i_item_sk#14] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1] -(15) BroadcastHashJoin [codegen id : 6] +(14) BroadcastHashJoin [codegen id : 4] Left keys [1]: [item_sk#7] Right keys [1]: [i_item_sk#14] Join type: Inner Join condition: None -(16) Project [codegen id : 6] +(15) Project [codegen id : 4] Output [2]: [sold_date_sk#5, customer_sk#6] Input [4]: [sold_date_sk#5, customer_sk#6, item_sk#7, i_item_sk#14] -(17) ReusedExchange [Reuses operator id: 61] +(16) ReusedExchange [Reuses operator id: 60] Output [1]: [d_date_sk#17] -(18) BroadcastHashJoin [codegen id : 6] +(17) BroadcastHashJoin [codegen id : 4] Left keys [1]: [sold_date_sk#5] Right keys [1]: [d_date_sk#17] Join type: Inner Join condition: None -(19) Project [codegen id : 6] +(18) Project [codegen id : 4] Output [1]: [customer_sk#6] Input [3]: [sold_date_sk#5, customer_sk#6, d_date_sk#17] -(20) Scan parquet spark_catalog.default.customer +(19) Scan parquet spark_catalog.default.customer Output [2]: [c_customer_sk#18, c_current_addr_sk#19] Batched: true Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 5] +(20) CometFilter Input [2]: [c_customer_sk#18, c_current_addr_sk#19] +Condition : (isnotnull(c_customer_sk#18) AND isnotnull(c_current_addr_sk#19)) -(22) Filter [codegen id : 5] +(21) ColumnarToRow [codegen id : 3] Input [2]: [c_customer_sk#18, c_current_addr_sk#19] -Condition : (isnotnull(c_customer_sk#18) AND isnotnull(c_current_addr_sk#19)) -(23) BroadcastExchange +(22) BroadcastExchange Input [2]: [c_customer_sk#18, c_current_addr_sk#19] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] -(24) BroadcastHashJoin [codegen id : 6] +(23) BroadcastHashJoin [codegen id : 4] Left keys [1]: [customer_sk#6] Right keys [1]: [c_customer_sk#18] Join type: Inner Join condition: None -(25) Project [codegen id : 6] +(24) Project [codegen id : 4] Output [2]: [c_customer_sk#18, c_current_addr_sk#19] Input [3]: [customer_sk#6, c_customer_sk#18, c_current_addr_sk#19] -(26) HashAggregate [codegen id : 6] +(25) HashAggregate [codegen id : 4] Input [2]: [c_customer_sk#18, c_current_addr_sk#19] Keys [2]: [c_customer_sk#18, c_current_addr_sk#19] Functions: [] Aggregate Attributes: [] Results [2]: [c_customer_sk#18, c_current_addr_sk#19] -(27) Exchange +(26) Exchange Input [2]: [c_customer_sk#18, c_current_addr_sk#19] Arguments: hashpartitioning(c_customer_sk#18, c_current_addr_sk#19, 5), ENSURE_REQUIREMENTS, [plan_id=3] -(28) HashAggregate [codegen id : 11] +(27) HashAggregate [codegen id : 9] Input [2]: [c_customer_sk#18, c_current_addr_sk#19] Keys [2]: [c_customer_sk#18, c_current_addr_sk#19] Functions: [] Aggregate Attributes: [] Results [2]: [c_customer_sk#18, c_current_addr_sk#19] -(29) Scan parquet spark_catalog.default.store_sales +(28) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] Batched: true Location: InMemoryFileIndex [] @@ -196,290 +194,286 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#22), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 7] +(29) CometFilter Input [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] +Condition : isnotnull(ss_customer_sk#20) -(31) Filter [codegen id : 7] +(30) ColumnarToRow [codegen id : 5] Input [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] -Condition : isnotnull(ss_customer_sk#20) -(32) BroadcastExchange +(31) BroadcastExchange Input [3]: [ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4] -(33) BroadcastHashJoin [codegen id : 11] +(32) BroadcastHashJoin [codegen id : 9] Left keys [1]: [c_customer_sk#18] Right keys [1]: [ss_customer_sk#20] Join type: Inner Join condition: None -(34) Project [codegen id : 11] +(33) Project [codegen id : 9] Output [4]: [c_customer_sk#18, c_current_addr_sk#19, ss_ext_sales_price#21, ss_sold_date_sk#22] Input [5]: [c_customer_sk#18, c_current_addr_sk#19, ss_customer_sk#20, ss_ext_sales_price#21, ss_sold_date_sk#22] -(35) Scan parquet spark_catalog.default.customer_address +(34) Scan parquet spark_catalog.default.customer_address Output [3]: [ca_address_sk#24, ca_county#25, ca_state#26] Batched: true Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_county), IsNotNull(ca_state)] ReadSchema: struct -(36) ColumnarToRow [codegen id : 8] +(35) CometFilter Input [3]: [ca_address_sk#24, ca_county#25, ca_state#26] +Condition : ((isnotnull(ca_address_sk#24) AND isnotnull(ca_county#25)) AND isnotnull(ca_state#26)) -(37) Filter [codegen id : 8] +(36) ColumnarToRow [codegen id : 6] Input [3]: [ca_address_sk#24, ca_county#25, ca_state#26] -Condition : ((isnotnull(ca_address_sk#24) AND isnotnull(ca_county#25)) AND isnotnull(ca_state#26)) -(38) BroadcastExchange +(37) BroadcastExchange Input [3]: [ca_address_sk#24, ca_county#25, ca_state#26] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] -(39) BroadcastHashJoin [codegen id : 11] +(38) BroadcastHashJoin [codegen id : 9] Left keys [1]: [c_current_addr_sk#19] Right keys [1]: [ca_address_sk#24] Join type: Inner Join condition: None -(40) Project [codegen id : 11] +(39) Project [codegen id : 9] Output [5]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22, ca_county#25, ca_state#26] Input [7]: [c_customer_sk#18, c_current_addr_sk#19, ss_ext_sales_price#21, ss_sold_date_sk#22, ca_address_sk#24, ca_county#25, ca_state#26] -(41) Scan parquet spark_catalog.default.store +(40) Scan parquet spark_catalog.default.store Output [2]: [s_county#27, s_state#28] Batched: true Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_county), IsNotNull(s_state)] ReadSchema: struct -(42) ColumnarToRow [codegen id : 9] +(41) CometFilter Input [2]: [s_county#27, s_state#28] +Condition : (isnotnull(s_county#27) AND isnotnull(s_state#28)) -(43) Filter [codegen id : 9] +(42) ColumnarToRow [codegen id : 7] Input [2]: [s_county#27, s_state#28] -Condition : (isnotnull(s_county#27) AND isnotnull(s_state#28)) -(44) BroadcastExchange +(43) BroadcastExchange Input [2]: [s_county#27, s_state#28] Arguments: HashedRelationBroadcastMode(List(input[0, string, false], input[1, string, false]),false), [plan_id=6] -(45) BroadcastHashJoin [codegen id : 11] +(44) BroadcastHashJoin [codegen id : 9] Left keys [2]: [ca_county#25, ca_state#26] Right keys [2]: [s_county#27, s_state#28] Join type: Inner Join condition: None -(46) Project [codegen id : 11] +(45) Project [codegen id : 9] Output [3]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22] Input [7]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22, ca_county#25, ca_state#26, s_county#27, s_state#28] -(47) ReusedExchange [Reuses operator id: 66] +(46) ReusedExchange [Reuses operator id: 65] Output [1]: [d_date_sk#29] -(48) BroadcastHashJoin [codegen id : 11] +(47) BroadcastHashJoin [codegen id : 9] Left keys [1]: [ss_sold_date_sk#22] Right keys [1]: [d_date_sk#29] Join type: Inner Join condition: None -(49) Project [codegen id : 11] +(48) Project [codegen id : 9] Output [2]: [c_customer_sk#18, ss_ext_sales_price#21] Input [4]: [c_customer_sk#18, ss_ext_sales_price#21, ss_sold_date_sk#22, d_date_sk#29] -(50) HashAggregate [codegen id : 11] +(49) HashAggregate [codegen id : 9] Input [2]: [c_customer_sk#18, ss_ext_sales_price#21] Keys [1]: [c_customer_sk#18] Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#21))] Aggregate Attributes [1]: [sum#30] Results [2]: [c_customer_sk#18, sum#31] -(51) Exchange +(50) Exchange Input [2]: [c_customer_sk#18, sum#31] Arguments: hashpartitioning(c_customer_sk#18, 5), ENSURE_REQUIREMENTS, [plan_id=7] -(52) HashAggregate [codegen id : 12] +(51) HashAggregate [codegen id : 10] Input [2]: [c_customer_sk#18, sum#31] Keys [1]: [c_customer_sk#18] Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#21))] Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#21))#32] Results [1]: [cast((MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#21))#32,17,2) / 50) as int) AS segment#33] -(53) HashAggregate [codegen id : 12] +(52) HashAggregate [codegen id : 10] Input [1]: [segment#33] Keys [1]: [segment#33] Functions [1]: [partial_count(1)] Aggregate Attributes [1]: [count#34] Results [2]: [segment#33, count#35] -(54) Exchange +(53) Exchange Input [2]: [segment#33, count#35] Arguments: hashpartitioning(segment#33, 5), ENSURE_REQUIREMENTS, [plan_id=8] -(55) HashAggregate [codegen id : 13] +(54) HashAggregate [codegen id : 11] Input [2]: [segment#33, count#35] Keys [1]: [segment#33] Functions [1]: [count(1)] Aggregate Attributes [1]: [count(1)#36] Results [3]: [segment#33, count(1)#36 AS num_customers#37, (segment#33 * 50) AS segment_base#38] -(56) TakeOrderedAndProject +(55) TakeOrderedAndProject Input [3]: [segment#33, num_customers#37, segment_base#38] Arguments: 100, [segment#33 ASC NULLS FIRST, num_customers#37 ASC NULLS FIRST], [segment#33, num_customers#37, segment_base#38] ===== Subqueries ===== Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 -BroadcastExchange (61) -+- * Project (60) - +- * Filter (59) - +- * ColumnarToRow (58) - +- CometScan parquet spark_catalog.default.date_dim (57) +BroadcastExchange (60) ++- * ColumnarToRow (59) + +- CometProject (58) + +- CometFilter (57) + +- CometScan parquet spark_catalog.default.date_dim (56) -(57) Scan parquet spark_catalog.default.date_dim +(56) Scan parquet spark_catalog.default.date_dim Output [3]: [d_date_sk#17, d_year#39, d_moy#40] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,12), EqualTo(d_year,1998), IsNotNull(d_date_sk)] ReadSchema: struct -(58) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#17, d_year#39, d_moy#40] - -(59) Filter [codegen id : 1] +(57) CometFilter Input [3]: [d_date_sk#17, d_year#39, d_moy#40] Condition : ((((isnotnull(d_moy#40) AND isnotnull(d_year#39)) AND (d_moy#40 = 12)) AND (d_year#39 = 1998)) AND isnotnull(d_date_sk#17)) -(60) Project [codegen id : 1] -Output [1]: [d_date_sk#17] +(58) CometProject Input [3]: [d_date_sk#17, d_year#39, d_moy#40] +Arguments: [d_date_sk#17], [d_date_sk#17] -(61) BroadcastExchange +(59) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#17] + +(60) BroadcastExchange Input [1]: [d_date_sk#17] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9] -Subquery:2 Hosting operator id = 5 Hosting Expression = ws_sold_date_sk#10 IN dynamicpruning#4 +Subquery:2 Hosting operator id = 4 Hosting Expression = ws_sold_date_sk#10 IN dynamicpruning#4 -Subquery:3 Hosting operator id = 29 Hosting Expression = ss_sold_date_sk#22 IN dynamicpruning#23 -BroadcastExchange (66) -+- * Project (65) - +- * Filter (64) - +- * ColumnarToRow (63) - +- CometScan parquet spark_catalog.default.date_dim (62) +Subquery:3 Hosting operator id = 28 Hosting Expression = ss_sold_date_sk#22 IN dynamicpruning#23 +BroadcastExchange (65) ++- * ColumnarToRow (64) + +- CometProject (63) + +- CometFilter (62) + +- CometScan parquet spark_catalog.default.date_dim (61) -(62) Scan parquet spark_catalog.default.date_dim +(61) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date_sk#29, d_month_seq#41] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,ScalarSubquery#42), LessThanOrEqual(d_month_seq,ScalarSubquery#43), IsNotNull(d_date_sk)] ReadSchema: struct -(63) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#29, d_month_seq#41] - -(64) Filter [codegen id : 1] +(62) CometFilter Input [2]: [d_date_sk#29, d_month_seq#41] Condition : (((isnotnull(d_month_seq#41) AND (d_month_seq#41 >= ReusedSubquery Subquery scalar-subquery#42, [id=#44])) AND (d_month_seq#41 <= ReusedSubquery Subquery scalar-subquery#43, [id=#45])) AND isnotnull(d_date_sk#29)) -(65) Project [codegen id : 1] -Output [1]: [d_date_sk#29] +(63) CometProject Input [2]: [d_date_sk#29, d_month_seq#41] +Arguments: [d_date_sk#29], [d_date_sk#29] -(66) BroadcastExchange +(64) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#29] + +(65) BroadcastExchange Input [1]: [d_date_sk#29] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=10] -Subquery:4 Hosting operator id = 64 Hosting Expression = ReusedSubquery Subquery scalar-subquery#42, [id=#44] +Subquery:4 Hosting operator id = 62 Hosting Expression = ReusedSubquery Subquery scalar-subquery#42, [id=#44] -Subquery:5 Hosting operator id = 64 Hosting Expression = ReusedSubquery Subquery scalar-subquery#43, [id=#45] +Subquery:5 Hosting operator id = 62 Hosting Expression = ReusedSubquery Subquery scalar-subquery#43, [id=#45] -Subquery:6 Hosting operator id = 62 Hosting Expression = Subquery scalar-subquery#42, [id=#44] -* HashAggregate (73) -+- Exchange (72) - +- * HashAggregate (71) - +- * Project (70) - +- * Filter (69) - +- * ColumnarToRow (68) - +- CometScan parquet spark_catalog.default.date_dim (67) +Subquery:6 Hosting operator id = 61 Hosting Expression = Subquery scalar-subquery#42, [id=#44] +* HashAggregate (72) ++- Exchange (71) + +- * ColumnarToRow (70) + +- CometHashAggregate (69) + +- CometProject (68) + +- CometFilter (67) + +- CometScan parquet spark_catalog.default.date_dim (66) -(67) Scan parquet spark_catalog.default.date_dim +(66) Scan parquet spark_catalog.default.date_dim Output [3]: [d_month_seq#46, d_year#47, d_moy#48] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,12)] ReadSchema: struct -(68) ColumnarToRow [codegen id : 1] -Input [3]: [d_month_seq#46, d_year#47, d_moy#48] - -(69) Filter [codegen id : 1] +(67) CometFilter Input [3]: [d_month_seq#46, d_year#47, d_moy#48] Condition : (((isnotnull(d_year#47) AND isnotnull(d_moy#48)) AND (d_year#47 = 1998)) AND (d_moy#48 = 12)) -(70) Project [codegen id : 1] -Output [1]: [(d_month_seq#46 + 1) AS (d_month_seq + 1)#49] +(68) CometProject Input [3]: [d_month_seq#46, d_year#47, d_moy#48] +Arguments: [(d_month_seq + 1)#49], [(d_month_seq#46 + 1) AS (d_month_seq + 1)#49] -(71) HashAggregate [codegen id : 1] +(69) CometHashAggregate Input [1]: [(d_month_seq + 1)#49] Keys [1]: [(d_month_seq + 1)#49] Functions: [] -Aggregate Attributes: [] -Results [1]: [(d_month_seq + 1)#49] -(72) Exchange +(70) ColumnarToRow [codegen id : 1] +Input [1]: [(d_month_seq + 1)#49] + +(71) Exchange Input [1]: [(d_month_seq + 1)#49] Arguments: hashpartitioning((d_month_seq + 1)#49, 5), ENSURE_REQUIREMENTS, [plan_id=11] -(73) HashAggregate [codegen id : 2] +(72) HashAggregate [codegen id : 2] Input [1]: [(d_month_seq + 1)#49] Keys [1]: [(d_month_seq + 1)#49] Functions: [] Aggregate Attributes: [] Results [1]: [(d_month_seq + 1)#49] -Subquery:7 Hosting operator id = 62 Hosting Expression = Subquery scalar-subquery#43, [id=#45] -* HashAggregate (80) -+- Exchange (79) - +- * HashAggregate (78) - +- * Project (77) - +- * Filter (76) - +- * ColumnarToRow (75) - +- CometScan parquet spark_catalog.default.date_dim (74) +Subquery:7 Hosting operator id = 61 Hosting Expression = Subquery scalar-subquery#43, [id=#45] +* HashAggregate (79) ++- Exchange (78) + +- * ColumnarToRow (77) + +- CometHashAggregate (76) + +- CometProject (75) + +- CometFilter (74) + +- CometScan parquet spark_catalog.default.date_dim (73) -(74) Scan parquet spark_catalog.default.date_dim +(73) Scan parquet spark_catalog.default.date_dim Output [3]: [d_month_seq#50, d_year#51, d_moy#52] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,12)] ReadSchema: struct -(75) ColumnarToRow [codegen id : 1] -Input [3]: [d_month_seq#50, d_year#51, d_moy#52] - -(76) Filter [codegen id : 1] +(74) CometFilter Input [3]: [d_month_seq#50, d_year#51, d_moy#52] Condition : (((isnotnull(d_year#51) AND isnotnull(d_moy#52)) AND (d_year#51 = 1998)) AND (d_moy#52 = 12)) -(77) Project [codegen id : 1] -Output [1]: [(d_month_seq#50 + 3) AS (d_month_seq + 3)#53] +(75) CometProject Input [3]: [d_month_seq#50, d_year#51, d_moy#52] +Arguments: [(d_month_seq + 3)#53], [(d_month_seq#50 + 3) AS (d_month_seq + 3)#53] -(78) HashAggregate [codegen id : 1] +(76) CometHashAggregate Input [1]: [(d_month_seq + 3)#53] Keys [1]: [(d_month_seq + 3)#53] Functions: [] -Aggregate Attributes: [] -Results [1]: [(d_month_seq + 3)#53] -(79) Exchange +(77) ColumnarToRow [codegen id : 1] +Input [1]: [(d_month_seq + 3)#53] + +(78) Exchange Input [1]: [(d_month_seq + 3)#53] Arguments: hashpartitioning((d_month_seq + 3)#53, 5), ENSURE_REQUIREMENTS, [plan_id=12] -(80) HashAggregate [codegen id : 2] +(79) HashAggregate [codegen id : 2] Input [1]: [(d_month_seq + 3)#53] Keys [1]: [(d_month_seq + 3)#53] Functions: [] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/simplified.txt index fa7a009d3..30ba4b743 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q54/simplified.txt @@ -1,14 +1,14 @@ TakeOrderedAndProject [segment,num_customers,segment_base] - WholeStageCodegen (13) + WholeStageCodegen (11) HashAggregate [segment,count] [count(1),num_customers,segment_base,count] InputAdapter Exchange [segment] #1 - WholeStageCodegen (12) + WholeStageCodegen (10) HashAggregate [segment] [count,count] HashAggregate [c_customer_sk,sum] [sum(UnscaledValue(ss_ext_sales_price)),segment,sum] InputAdapter Exchange [c_customer_sk] #2 - WholeStageCodegen (11) + WholeStageCodegen (9) HashAggregate [c_customer_sk,ss_ext_sales_price] [sum,sum] Project [c_customer_sk,ss_ext_sales_price] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] @@ -21,7 +21,7 @@ TakeOrderedAndProject [segment,num_customers,segment_base] HashAggregate [c_customer_sk,c_current_addr_sk] InputAdapter Exchange [c_customer_sk,c_current_addr_sk] #3 - WholeStageCodegen (6) + WholeStageCodegen (4) HashAggregate [c_customer_sk,c_current_addr_sk] Project [c_customer_sk,c_current_addr_sk] BroadcastHashJoin [customer_sk,c_customer_sk] @@ -29,62 +29,57 @@ TakeOrderedAndProject [segment,num_customers,segment_base] BroadcastHashJoin [sold_date_sk,d_date_sk] Project [sold_date_sk,customer_sk] BroadcastHashJoin [item_sk,i_item_sk] - InputAdapter - Union - WholeStageCodegen (1) - Project [cs_sold_date_sk,cs_bill_customer_sk,cs_item_sk] - Filter [cs_item_sk,cs_bill_customer_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_sold_date_sk] - SubqueryBroadcast [d_date_sk] #1 - BroadcastExchange #4 - WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_moy,d_year,d_date_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] - WholeStageCodegen (2) - Project [ws_sold_date_sk,ws_bill_customer_sk,ws_item_sk] - Filter [ws_item_sk,ws_bill_customer_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_sold_date_sk] - ReusedSubquery [d_date_sk] #1 + ColumnarToRow + InputAdapter + CometUnion + CometProject [cs_sold_date_sk,cs_bill_customer_sk,cs_item_sk] [sold_date_sk,customer_sk,item_sk] + CometFilter [cs_item_sk,cs_bill_customer_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + CometProject [ws_sold_date_sk,ws_bill_customer_sk,ws_item_sk] [sold_date_sk,customer_sk,item_sk] + CometFilter [ws_item_sk,ws_bill_customer_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 InputAdapter BroadcastExchange #5 - WholeStageCodegen (3) - Project [i_item_sk] - Filter [i_category,i_class,i_item_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_category,i_class,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #6 - WholeStageCodegen (5) - Filter [c_customer_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] InputAdapter BroadcastExchange #7 - WholeStageCodegen (7) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #8 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ReusedSubquery [(d_month_seq + 1)] #3 - ReusedSubquery [(d_month_seq + 3)] #4 - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + ReusedSubquery [(d_month_seq + 1)] #3 + ReusedSubquery [(d_month_seq + 3)] #4 CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] Subquery #3 WholeStageCodegen (2) @@ -92,11 +87,11 @@ TakeOrderedAndProject [segment,num_customers,segment_base] InputAdapter Exchange [(d_month_seq + 1)] #9 WholeStageCodegen (1) - HashAggregate [(d_month_seq + 1)] - Project [d_month_seq] - Filter [d_year,d_moy] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometHashAggregate [(d_month_seq + 1)] + CometProject [d_month_seq] [(d_month_seq + 1)] + CometFilter [d_year,d_moy] CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] Subquery #4 WholeStageCodegen (2) @@ -104,25 +99,25 @@ TakeOrderedAndProject [segment,num_customers,segment_base] InputAdapter Exchange [(d_month_seq + 3)] #10 WholeStageCodegen (1) - HashAggregate [(d_month_seq + 3)] - Project [d_month_seq] - Filter [d_year,d_moy] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometHashAggregate [(d_month_seq + 3)] + CometProject [d_month_seq] [(d_month_seq + 3)] + CometFilter [d_year,d_moy] CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] InputAdapter BroadcastExchange #11 - WholeStageCodegen (8) - Filter [ca_address_sk,ca_county,ca_state] - ColumnarToRow - InputAdapter + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_county,ca_state] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county,ca_state] InputAdapter BroadcastExchange #12 - WholeStageCodegen (9) - Filter [s_county,s_state] - ColumnarToRow - InputAdapter + WholeStageCodegen (7) + ColumnarToRow + InputAdapter + CometFilter [s_county,s_state] CometScan parquet spark_catalog.default.store [s_county,s_state] InputAdapter ReusedExchange [d_date_sk] #8 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/explain.txt index 0deabf94b..3d1d689bc 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/explain.txt @@ -7,18 +7,18 @@ TakeOrderedAndProject (21) +- * BroadcastHashJoin Inner BuildRight (16) :- * Project (10) : +- * BroadcastHashJoin Inner BuildRight (9) - : :- * Project (4) - : : +- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.date_dim (1) : +- BroadcastExchange (8) - : +- * Filter (7) - : +- * ColumnarToRow (6) + : +- * ColumnarToRow (7) + : +- CometFilter (6) : +- CometScan parquet spark_catalog.default.store_sales (5) +- BroadcastExchange (15) - +- * Project (14) - +- * Filter (13) - +- * ColumnarToRow (12) + +- * ColumnarToRow (14) + +- CometProject (13) + +- CometFilter (12) +- CometScan parquet spark_catalog.default.item (11) @@ -29,16 +29,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,1999), IsNotNull(d_date_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] -Input [3]: [d_date_sk#1, d_year#2, d_moy#3] - -(3) Filter [codegen id : 3] +(2) CometFilter Input [3]: [d_date_sk#1, d_year#2, d_moy#3] Condition : ((((isnotnull(d_moy#3) AND isnotnull(d_year#2)) AND (d_moy#3 = 11)) AND (d_year#2 = 1999)) AND isnotnull(d_date_sk#1)) -(4) Project [codegen id : 3] -Output [1]: [d_date_sk#1] +(3) CometProject Input [3]: [d_date_sk#1, d_year#2, d_moy#3] +Arguments: [d_date_sk#1], [d_date_sk#1] + +(4) ColumnarToRow [codegen id : 3] +Input [1]: [d_date_sk#1] (5) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] @@ -48,12 +48,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(true)] PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] +(6) CometFilter Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : isnotnull(ss_item_sk#4) -(7) Filter [codegen id : 1] +(7) ColumnarToRow [codegen id : 1] Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] -Condition : isnotnull(ss_item_sk#4) (8) BroadcastExchange Input [3]: [ss_item_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] @@ -76,16 +76,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,28), IsNotNull(i_item_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] -Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] - -(13) Filter [codegen id : 2] +(12) CometFilter Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] Condition : ((isnotnull(i_manager_id#10) AND (i_manager_id#10 = 28)) AND isnotnull(i_item_sk#7)) -(14) Project [codegen id : 2] -Output [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] +(13) CometProject Input [4]: [i_item_sk#7, i_brand_id#8, i_brand#9, i_manager_id#10] +Arguments: [i_item_sk#7, i_brand_id#8, i_brand#9], [i_item_sk#7, i_brand_id#8, i_brand#9] + +(14) ColumnarToRow [codegen id : 2] +Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] (15) BroadcastExchange Input [3]: [i_item_sk#7, i_brand_id#8, i_brand#9] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/simplified.txt index 911fe96b3..7a0fe8863 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q55/simplified.txt @@ -9,23 +9,23 @@ TakeOrderedAndProject [ext_price,brand_id,brand] BroadcastHashJoin [ss_item_sk,i_item_sk] Project [ss_item_sk,ss_ext_sales_price] BroadcastHashJoin [d_date_sk,ss_sold_date_sk] - Project [d_date_sk] - Filter [d_moy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [i_item_sk,i_brand_id,i_brand] - Filter [i_manager_id,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_brand] + CometFilter [i_manager_id,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manager_id] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/explain.txt index fef08c190..bbed7eea6 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/explain.txt @@ -13,24 +13,24 @@ TakeOrderedAndProject (63) : : +- * BroadcastHashJoin Inner BuildRight (12) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (11) - : : +- * Project (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.customer_address (7) : +- BroadcastExchange (23) : +- * BroadcastHashJoin LeftSemi BuildRight (22) - : :- * Filter (16) - : : +- * ColumnarToRow (15) + : :- * ColumnarToRow (16) + : : +- CometFilter (15) : : +- CometScan parquet spark_catalog.default.item (14) : +- BroadcastExchange (21) - : +- * Project (20) - : +- * Filter (19) - : +- * ColumnarToRow (18) + : +- * ColumnarToRow (20) + : +- CometProject (19) + : +- CometFilter (18) : +- CometScan parquet spark_catalog.default.item (17) :- * HashAggregate (43) : +- Exchange (42) @@ -41,8 +41,8 @@ TakeOrderedAndProject (63) : : +- * BroadcastHashJoin Inner BuildRight (36) : : :- * Project (34) : : : +- * BroadcastHashJoin Inner BuildRight (33) - : : : :- * Filter (31) - : : : : +- * ColumnarToRow (30) + : : : :- * ColumnarToRow (31) + : : : : +- CometFilter (30) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (29) : : : +- ReusedExchange (32) : : +- ReusedExchange (35) @@ -56,8 +56,8 @@ TakeOrderedAndProject (63) : +- * BroadcastHashJoin Inner BuildRight (51) : :- * Project (49) : : +- * BroadcastHashJoin Inner BuildRight (48) - : : :- * Filter (46) - : : : +- * ColumnarToRow (45) + : : :- * ColumnarToRow (46) + : : : +- CometFilter (45) : : : +- CometScan parquet spark_catalog.default.web_sales (44) : : +- ReusedExchange (47) : +- ReusedExchange (50) @@ -72,12 +72,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_addr_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] -Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) (4) ReusedExchange [Reuses operator id: 68] Output [1]: [d_date_sk#6] @@ -99,16 +99,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] -Input [2]: [ca_address_sk#7, ca_gmt_offset#8] - -(9) Filter [codegen id : 2] +(8) CometFilter Input [2]: [ca_address_sk#7, ca_gmt_offset#8] Condition : ((isnotnull(ca_gmt_offset#8) AND (ca_gmt_offset#8 = -5.00)) AND isnotnull(ca_address_sk#7)) -(10) Project [codegen id : 2] -Output [1]: [ca_address_sk#7] +(9) CometProject Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Arguments: [ca_address_sk#7], [ca_address_sk#7] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [ca_address_sk#7] (11) BroadcastExchange Input [1]: [ca_address_sk#7] @@ -131,12 +131,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 4] +(15) CometFilter Input [2]: [i_item_sk#9, i_item_id#10] +Condition : isnotnull(i_item_sk#9) -(16) Filter [codegen id : 4] +(16) ColumnarToRow [codegen id : 4] Input [2]: [i_item_sk#9, i_item_id#10] -Condition : isnotnull(i_item_sk#9) (17) Scan parquet spark_catalog.default.item Output [2]: [i_item_id#11, i_color#12] @@ -145,16 +145,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [In(i_color, [blanched ,burnished ,slate ])] ReadSchema: struct -(18) ColumnarToRow [codegen id : 3] -Input [2]: [i_item_id#11, i_color#12] - -(19) Filter [codegen id : 3] +(18) CometFilter Input [2]: [i_item_id#11, i_color#12] Condition : i_color#12 IN (slate ,blanched ,burnished ) -(20) Project [codegen id : 3] -Output [1]: [i_item_id#11] +(19) CometProject Input [2]: [i_item_id#11, i_color#12] +Arguments: [i_item_id#11], [i_item_id#11] + +(20) ColumnarToRow [codegen id : 3] +Input [1]: [i_item_id#11] (21) BroadcastExchange Input [1]: [i_item_id#11] @@ -206,12 +206,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#20), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_addr_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 11] +(30) CometFilter Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) -(31) Filter [codegen id : 11] +(31) ColumnarToRow [codegen id : 11] Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] -Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) (32) ReusedExchange [Reuses operator id: 68] Output [1]: [d_date_sk#22] @@ -278,12 +278,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_addr_sk), IsNotNull(ws_item_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 17] +(45) CometFilter Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) -(46) Filter [codegen id : 17] +(46) ColumnarToRow [codegen id : 17] Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] -Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) (47) ReusedExchange [Reuses operator id: 68] Output [1]: [d_date_sk#35] @@ -370,9 +370,9 @@ Arguments: 100, [total_sales#48 ASC NULLS FIRST], [i_item_id#10, total_sales#48] Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 BroadcastExchange (68) -+- * Project (67) - +- * Filter (66) - +- * ColumnarToRow (65) ++- * ColumnarToRow (67) + +- CometProject (66) + +- CometFilter (65) +- CometScan parquet spark_catalog.default.date_dim (64) @@ -383,16 +383,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)] ReadSchema: struct -(65) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#6, d_year#49, d_moy#50] - -(66) Filter [codegen id : 1] +(65) CometFilter Input [3]: [d_date_sk#6, d_year#49, d_moy#50] Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#50)) AND (d_year#49 = 2001)) AND (d_moy#50 = 2)) AND isnotnull(d_date_sk#6)) -(67) Project [codegen id : 1] -Output [1]: [d_date_sk#6] +(66) CometProject Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(67) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] (68) BroadcastExchange Input [1]: [d_date_sk#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/simplified.txt index 42b2cbfd3..f781ed1f7 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q56/simplified.txt @@ -19,43 +19,43 @@ TakeOrderedAndProject [total_sales,i_item_id] BroadcastHashJoin [ss_addr_sk,ca_address_sk] Project [ss_item_sk,ss_addr_sk,ss_ext_sales_price] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_addr_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [ca_address_sk] - Filter [ca_gmt_offset,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_gmt_offset,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) BroadcastHashJoin [i_item_id,i_item_id] - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] InputAdapter BroadcastExchange #6 WholeStageCodegen (3) - Project [i_item_id] - Filter [i_color] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_id] + CometFilter [i_color] CometScan parquet spark_catalog.default.item [i_item_id,i_color] WholeStageCodegen (12) HashAggregate [i_item_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),total_sales,sum] @@ -69,9 +69,9 @@ TakeOrderedAndProject [total_sales,i_item_id] BroadcastHashJoin [cs_bill_addr_sk,ca_address_sk] Project [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price] BroadcastHashJoin [cs_sold_date_sk,d_date_sk] - Filter [cs_bill_addr_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_addr_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -92,9 +92,9 @@ TakeOrderedAndProject [total_sales,i_item_id] BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] Project [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_bill_addr_sk,ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk,ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/explain.txt index e7e6e9367..8746c36d6 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/explain.txt @@ -20,17 +20,17 @@ TakeOrderedAndProject (45) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.item (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (4) : : : +- ReusedExchange (10) : : +- BroadcastExchange (16) - : : +- * Filter (15) - : : +- * ColumnarToRow (14) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) : : +- CometScan parquet spark_catalog.default.call_center (13) : +- BroadcastExchange (35) : +- * Project (34) @@ -53,12 +53,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [3]: [i_item_sk#1, i_brand#2, i_category#3] -Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) (4) Scan parquet spark_catalog.default.catalog_sales Output [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] @@ -68,12 +68,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#7), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_call_center_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Condition : (isnotnull(cs_item_sk#5) AND isnotnull(cs_call_center_sk#4)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] -Condition : (isnotnull(cs_item_sk#5) AND isnotnull(cs_call_center_sk#4)) (7) BroadcastExchange Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] @@ -109,12 +109,12 @@ Location [not included in comparison]/{warehouse_dir}/call_center] PushedFilters: [IsNotNull(cc_call_center_sk), IsNotNull(cc_name)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [2]: [cc_call_center_sk#12, cc_name#13] +Condition : (isnotnull(cc_call_center_sk#12) AND isnotnull(cc_name#13)) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [2]: [cc_call_center_sk#12, cc_name#13] -Condition : (isnotnull(cc_call_center_sk#12) AND isnotnull(cc_name#13)) (16) BroadcastExchange Input [2]: [cc_call_center_sk#12, cc_name#13] @@ -253,8 +253,8 @@ Arguments: 100, [(sum_sales#17 - avg_monthly_sales#20) ASC NULLS FIRST, cc_name# Subquery:1 Hosting operator id = 4 Hosting Expression = cs_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (49) -+- * Filter (48) - +- * ColumnarToRow (47) ++- * ColumnarToRow (48) + +- CometFilter (47) +- CometScan parquet spark_catalog.default.date_dim (46) @@ -265,12 +265,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] ReadSchema: struct -(47) ColumnarToRow [codegen id : 1] +(47) CometFilter Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) -(48) Filter [codegen id : 1] +(48) ColumnarToRow [codegen id : 1] Input [3]: [d_date_sk#9, d_year#10, d_moy#11] -Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) (49) BroadcastExchange Input [3]: [d_date_sk#9, d_year#10, d_moy#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/simplified.txt index 84c5c5f83..3bc01343a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q57/simplified.txt @@ -28,32 +28,32 @@ TakeOrderedAndProject [sum_sales,avg_monthly_sales,cc_name,i_category,i_brand,d_ BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [i_brand,i_category,cs_call_center_sk,cs_sales_price,cs_sold_date_sk] BroadcastHashJoin [i_item_sk,cs_item_sk] - Filter [i_item_sk,i_category,i_brand] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_category,i_brand] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [cs_item_sk,cs_call_center_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_call_center_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_call_center_sk,cs_item_sk,cs_sales_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk,d_year,d_moy] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [cc_call_center_sk,cc_name] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cc_call_center_sk,cc_name] CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_name] InputAdapter BroadcastExchange #6 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/explain.txt index bd7b775d6..35fedb6d3 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/explain.txt @@ -12,12 +12,12 @@ TakeOrderedAndProject (49) : : +- * BroadcastHashJoin Inner BuildRight (11) : : :- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.item (4) : : +- ReusedExchange (10) : +- BroadcastExchange (30) @@ -29,8 +29,8 @@ TakeOrderedAndProject (49) : +- * BroadcastHashJoin Inner BuildRight (24) : :- * Project (22) : : +- * BroadcastHashJoin Inner BuildRight (21) - : : :- * Filter (19) - : : : +- * ColumnarToRow (18) + : : :- * ColumnarToRow (19) + : : : +- CometFilter (18) : : : +- CometScan parquet spark_catalog.default.catalog_sales (17) : : +- ReusedExchange (20) : +- ReusedExchange (23) @@ -43,8 +43,8 @@ TakeOrderedAndProject (49) +- * BroadcastHashJoin Inner BuildRight (40) :- * Project (38) : +- * BroadcastHashJoin Inner BuildRight (37) - : :- * Filter (35) - : : +- * ColumnarToRow (34) + : :- * ColumnarToRow (35) + : : +- CometFilter (34) : : +- CometScan parquet spark_catalog.default.web_sales (33) : +- ReusedExchange (36) +- ReusedExchange (39) @@ -58,12 +58,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_item_sk#1) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] -Condition : isnotnull(ss_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [2]: [i_item_sk#5, i_item_id#6] @@ -72,12 +72,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_item_id)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [2]: [i_item_sk#5, i_item_id#6] +Condition : (isnotnull(i_item_sk#5) AND isnotnull(i_item_id#6)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [2]: [i_item_sk#5, i_item_id#6] -Condition : (isnotnull(i_item_sk#5) AND isnotnull(i_item_id#6)) (7) BroadcastExchange Input [2]: [i_item_sk#5, i_item_id#6] @@ -136,12 +136,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#15), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 8] +(18) CometFilter Input [3]: [cs_item_sk#13, cs_ext_sales_price#14, cs_sold_date_sk#15] +Condition : isnotnull(cs_item_sk#13) -(19) Filter [codegen id : 8] +(19) ColumnarToRow [codegen id : 8] Input [3]: [cs_item_sk#13, cs_ext_sales_price#14, cs_sold_date_sk#15] -Condition : isnotnull(cs_item_sk#13) (20) ReusedExchange [Reuses operator id: 7] Output [2]: [i_item_sk#17, i_item_id#18] @@ -213,12 +213,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#27), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(34) ColumnarToRow [codegen id : 13] +(34) CometFilter Input [3]: [ws_item_sk#25, ws_ext_sales_price#26, ws_sold_date_sk#27] +Condition : isnotnull(ws_item_sk#25) -(35) Filter [codegen id : 13] +(35) ColumnarToRow [codegen id : 13] Input [3]: [ws_item_sk#25, ws_ext_sales_price#26, ws_sold_date_sk#27] -Condition : isnotnull(ws_item_sk#25) (36) ReusedExchange [Reuses operator id: 7] Output [2]: [i_item_sk#29, i_item_id#30] @@ -292,13 +292,13 @@ Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dyn BroadcastExchange (60) +- * Project (59) +- * BroadcastHashJoin LeftSemi BuildRight (58) - :- * Filter (52) - : +- * ColumnarToRow (51) + :- * ColumnarToRow (52) + : +- CometFilter (51) : +- CometScan parquet spark_catalog.default.date_dim (50) +- BroadcastExchange (57) - +- * Project (56) - +- * Filter (55) - +- * ColumnarToRow (54) + +- * ColumnarToRow (56) + +- CometProject (55) + +- CometFilter (54) +- CometScan parquet spark_catalog.default.date_dim (53) @@ -309,12 +309,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date_sk)] ReadSchema: struct -(51) ColumnarToRow [codegen id : 2] +(51) CometFilter Input [2]: [d_date_sk#7, d_date#41] +Condition : isnotnull(d_date_sk#7) -(52) Filter [codegen id : 2] +(52) ColumnarToRow [codegen id : 2] Input [2]: [d_date_sk#7, d_date#41] -Condition : isnotnull(d_date_sk#7) (53) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date#42, d_week_seq#43] @@ -323,16 +323,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#44)] ReadSchema: struct -(54) ColumnarToRow [codegen id : 1] -Input [2]: [d_date#42, d_week_seq#43] - -(55) Filter [codegen id : 1] +(54) CometFilter Input [2]: [d_date#42, d_week_seq#43] Condition : (isnotnull(d_week_seq#43) AND (d_week_seq#43 = ReusedSubquery Subquery scalar-subquery#44, [id=#45])) -(56) Project [codegen id : 1] -Output [1]: [d_date#42] +(55) CometProject Input [2]: [d_date#42, d_week_seq#43] +Arguments: [d_date#42], [d_date#42] + +(56) ColumnarToRow [codegen id : 1] +Input [1]: [d_date#42] (57) BroadcastExchange Input [1]: [d_date#42] @@ -352,12 +352,12 @@ Input [2]: [d_date_sk#7, d_date#41] Input [1]: [d_date_sk#7] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] -Subquery:2 Hosting operator id = 55 Hosting Expression = ReusedSubquery Subquery scalar-subquery#44, [id=#45] +Subquery:2 Hosting operator id = 54 Hosting Expression = ReusedSubquery Subquery scalar-subquery#44, [id=#45] Subquery:3 Hosting operator id = 53 Hosting Expression = Subquery scalar-subquery#44, [id=#45] -* Project (64) -+- * Filter (63) - +- * ColumnarToRow (62) +* ColumnarToRow (64) ++- CometProject (63) + +- CometFilter (62) +- CometScan parquet spark_catalog.default.date_dim (61) @@ -368,16 +368,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), EqualTo(d_date,2000-01-03)] ReadSchema: struct -(62) ColumnarToRow [codegen id : 1] -Input [2]: [d_date#46, d_week_seq#47] - -(63) Filter [codegen id : 1] +(62) CometFilter Input [2]: [d_date#46, d_week_seq#47] Condition : (isnotnull(d_date#46) AND (d_date#46 = 2000-01-03)) -(64) Project [codegen id : 1] -Output [1]: [d_week_seq#47] +(63) CometProject Input [2]: [d_date#46, d_week_seq#47] +Arguments: [d_week_seq#47], [d_week_seq#47] + +(64) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#47] Subquery:4 Hosting operator id = 17 Hosting Expression = cs_sold_date_sk#15 IN dynamicpruning#4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/simplified.txt index 007ac0887..c7ed479ad 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q58/simplified.txt @@ -14,41 +14,41 @@ TakeOrderedAndProject [item_id,ss_item_rev,ss_dev,cs_item_rev,cs_dev,ws_item_rev BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_ext_sales_price,ss_sold_date_sk,i_item_id] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (2) Project [d_date_sk] BroadcastHashJoin [d_date,d_date] - Filter [d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date] - Filter [d_week_seq] - ReusedSubquery [d_week_seq] #2 - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date] + CometFilter [d_week_seq] + ReusedSubquery [d_week_seq] #2 CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] Subquery #2 WholeStageCodegen (1) - Project [d_week_seq] - Filter [d_date] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_date] CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Filter [i_item_sk,i_item_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_item_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] InputAdapter ReusedExchange [d_date_sk] #2 @@ -65,9 +65,9 @@ TakeOrderedAndProject [item_id,ss_item_rev,ss_dev,cs_item_rev,cs_dev,ws_item_rev BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_ext_sales_price,cs_sold_date_sk,i_item_id] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -87,9 +87,9 @@ TakeOrderedAndProject [item_id,ss_item_rev,ss_dev,cs_item_rev,cs_dev,ws_item_rev BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_ext_sales_price,ws_sold_date_sk,i_item_id] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/explain.txt index aaea9f38f..023c54bdd 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/explain.txt @@ -11,21 +11,21 @@ TakeOrderedAndProject (44) : : : +- * HashAggregate (10) : : : +- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.date_dim (4) : : +- BroadcastExchange (16) - : : +- * Filter (15) - : : +- * ColumnarToRow (14) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) : : +- CometScan parquet spark_catalog.default.store (13) : +- BroadcastExchange (23) - : +- * Project (22) - : +- * Filter (21) - : +- * ColumnarToRow (20) + : +- * ColumnarToRow (22) + : +- CometProject (21) + : +- CometFilter (20) : +- CometScan parquet spark_catalog.default.date_dim (19) +- BroadcastExchange (41) +- * Project (40) @@ -35,13 +35,13 @@ TakeOrderedAndProject (44) : :- * HashAggregate (27) : : +- ReusedExchange (26) : +- BroadcastExchange (31) - : +- * Filter (30) - : +- * ColumnarToRow (29) + : +- * ColumnarToRow (30) + : +- CometFilter (29) : +- CometScan parquet spark_catalog.default.store (28) +- BroadcastExchange (38) - +- * Project (37) - +- * Filter (36) - +- * ColumnarToRow (35) + +- * ColumnarToRow (37) + +- CometProject (36) + +- CometFilter (35) +- CometScan parquet spark_catalog.default.date_dim (34) @@ -53,12 +53,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#3)] PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 2] +(2) CometFilter Input [3]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) -(3) Filter [codegen id : 2] +(3) ColumnarToRow [codegen id : 2] Input [3]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3] -Condition : isnotnull(ss_store_sk#1) (4) Scan parquet spark_catalog.default.date_dim Output [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] @@ -67,12 +67,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date_sk), IsNotNull(d_week_seq)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] +Condition : (isnotnull(d_date_sk#4) AND isnotnull(d_week_seq#5)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] -Condition : (isnotnull(d_date_sk#4) AND isnotnull(d_week_seq#5)) (7) BroadcastExchange Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6] @@ -113,12 +113,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_id)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] +Condition : (isnotnull(s_store_sk#35) AND isnotnull(s_store_id#36)) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] -Condition : (isnotnull(s_store_sk#35) AND isnotnull(s_store_id#36)) (16) BroadcastExchange Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37] @@ -141,16 +141,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_week_seq)] ReadSchema: struct -(20) ColumnarToRow [codegen id : 4] -Input [2]: [d_month_seq#38, d_week_seq#39] - -(21) Filter [codegen id : 4] +(20) CometFilter Input [2]: [d_month_seq#38, d_week_seq#39] Condition : (((isnotnull(d_month_seq#38) AND (d_month_seq#38 >= 1212)) AND (d_month_seq#38 <= 1223)) AND isnotnull(d_week_seq#39)) -(22) Project [codegen id : 4] -Output [1]: [d_week_seq#39] +(21) CometProject Input [2]: [d_month_seq#38, d_week_seq#39] +Arguments: [d_week_seq#39], [d_week_seq#39] + +(22) ColumnarToRow [codegen id : 4] +Input [1]: [d_week_seq#39] (23) BroadcastExchange Input [1]: [d_week_seq#39] @@ -183,12 +183,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_id)] ReadSchema: struct -(29) ColumnarToRow [codegen id : 7] +(29) CometFilter Input [2]: [s_store_sk#68, s_store_id#69] +Condition : (isnotnull(s_store_sk#68) AND isnotnull(s_store_id#69)) -(30) Filter [codegen id : 7] +(30) ColumnarToRow [codegen id : 7] Input [2]: [s_store_sk#68, s_store_id#69] -Condition : (isnotnull(s_store_sk#68) AND isnotnull(s_store_id#69)) (31) BroadcastExchange Input [2]: [s_store_sk#68, s_store_id#69] @@ -211,16 +211,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1224), LessThanOrEqual(d_month_seq,1235), IsNotNull(d_week_seq)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 8] -Input [2]: [d_month_seq#70, d_week_seq#71] - -(36) Filter [codegen id : 8] +(35) CometFilter Input [2]: [d_month_seq#70, d_week_seq#71] Condition : (((isnotnull(d_month_seq#70) AND (d_month_seq#70 >= 1224)) AND (d_month_seq#70 <= 1235)) AND isnotnull(d_week_seq#71)) -(37) Project [codegen id : 8] -Output [1]: [d_week_seq#71] +(36) CometProject Input [2]: [d_month_seq#70, d_week_seq#71] +Arguments: [d_week_seq#71], [d_week_seq#71] + +(37) ColumnarToRow [codegen id : 8] +Input [1]: [d_week_seq#71] (38) BroadcastExchange Input [1]: [d_week_seq#71] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/simplified.txt index 53d4d0b92..9ad61e946 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q59/simplified.txt @@ -13,31 +13,31 @@ TakeOrderedAndProject [s_store_name1,s_store_id1,d_week_seq1,(sun_sales1 / sun_s HashAggregate [d_week_seq,ss_store_sk,d_day_name,ss_sales_price] [sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum,sum] Project [ss_store_sk,ss_sales_price,d_week_seq,d_day_name] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_sales_price,ss_sold_date_sk] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [d_date_sk,d_week_seq] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_date_sk,d_week_seq] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq,d_day_name] InputAdapter BroadcastExchange #3 WholeStageCodegen (3) - Filter [s_store_sk,s_store_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_id] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id,s_store_name] InputAdapter BroadcastExchange #4 WholeStageCodegen (4) - Project [d_week_seq] - Filter [d_month_seq,d_week_seq] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_month_seq,d_week_seq] CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_week_seq] InputAdapter BroadcastExchange #5 @@ -52,15 +52,15 @@ TakeOrderedAndProject [s_store_name1,s_store_id1,d_week_seq1,(sun_sales1 / sun_s InputAdapter BroadcastExchange #6 WholeStageCodegen (7) - Filter [s_store_sk,s_store_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_id] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] InputAdapter BroadcastExchange #7 WholeStageCodegen (8) - Project [d_week_seq] - Filter [d_month_seq,d_week_seq] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_month_seq,d_week_seq] CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_week_seq] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/explain.txt index 6b4318918..f8ae10ebe 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/explain.txt @@ -12,31 +12,31 @@ TakeOrderedAndProject (39) : : +- * BroadcastHashJoin Inner BuildRight (14) : : :- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.customer_address (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.customer (4) : : +- BroadcastExchange (13) - : : +- * Filter (12) - : : +- * ColumnarToRow (11) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) : : +- CometScan parquet spark_catalog.default.store_sales (10) : +- ReusedExchange (16) +- BroadcastExchange (32) +- * Project (31) +- * BroadcastHashJoin Inner BuildRight (30) - :- * Filter (21) - : +- * ColumnarToRow (20) + :- * ColumnarToRow (21) + : +- CometFilter (20) : +- CometScan parquet spark_catalog.default.item (19) +- BroadcastExchange (29) +- * Filter (28) +- * HashAggregate (27) +- Exchange (26) +- * HashAggregate (25) - +- * Filter (24) - +- * ColumnarToRow (23) + +- * ColumnarToRow (24) + +- CometFilter (23) +- CometScan parquet spark_catalog.default.item (22) @@ -47,12 +47,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 7] +(2) CometFilter Input [2]: [ca_address_sk#1, ca_state#2] +Condition : isnotnull(ca_address_sk#1) -(3) Filter [codegen id : 7] +(3) ColumnarToRow [codegen id : 7] Input [2]: [ca_address_sk#1, ca_state#2] -Condition : isnotnull(ca_address_sk#1) (4) Scan parquet spark_catalog.default.customer Output [2]: [c_customer_sk#3, c_current_addr_sk#4] @@ -61,12 +61,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_customer_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [2]: [c_customer_sk#3, c_current_addr_sk#4] +Condition : (isnotnull(c_current_addr_sk#4) AND isnotnull(c_customer_sk#3)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [2]: [c_customer_sk#3, c_current_addr_sk#4] -Condition : (isnotnull(c_current_addr_sk#4) AND isnotnull(c_customer_sk#3)) (7) BroadcastExchange Input [2]: [c_customer_sk#3, c_current_addr_sk#4] @@ -90,12 +90,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_customer_sk#6) AND isnotnull(ss_item_sk#5)) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] -Condition : (isnotnull(ss_customer_sk#6) AND isnotnull(ss_item_sk#5)) (13) BroadcastExchange Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] @@ -131,12 +131,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_current_price), IsNotNull(i_category), IsNotNull(i_item_sk)] ReadSchema: struct -(20) ColumnarToRow [codegen id : 6] +(20) CometFilter Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] +Condition : ((isnotnull(i_current_price#11) AND isnotnull(i_category#12)) AND isnotnull(i_item_sk#10)) -(21) Filter [codegen id : 6] +(21) ColumnarToRow [codegen id : 6] Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] -Condition : ((isnotnull(i_current_price#11) AND isnotnull(i_category#12)) AND isnotnull(i_item_sk#10)) (22) Scan parquet spark_catalog.default.item Output [2]: [i_current_price#13, i_category#14] @@ -145,12 +145,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_category)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 4] +(23) CometFilter Input [2]: [i_current_price#13, i_category#14] +Condition : isnotnull(i_category#14) -(24) Filter [codegen id : 4] +(24) ColumnarToRow [codegen id : 4] Input [2]: [i_current_price#13, i_category#14] -Condition : isnotnull(i_category#14) (25) HashAggregate [codegen id : 4] Input [2]: [i_current_price#13, i_category#14] @@ -232,9 +232,9 @@ Arguments: 100, [cnt#25 ASC NULLS FIRST], [state#24, cnt#25] Subquery:1 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (44) -+- * Project (43) - +- * Filter (42) - +- * ColumnarToRow (41) ++- * ColumnarToRow (43) + +- CometProject (42) + +- CometFilter (41) +- CometScan parquet spark_catalog.default.date_dim (40) @@ -245,30 +245,30 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), EqualTo(d_month_seq,ScalarSubquery#27), IsNotNull(d_date_sk)] ReadSchema: struct -(41) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#9, d_month_seq#26] - -(42) Filter [codegen id : 1] +(41) CometFilter Input [2]: [d_date_sk#9, d_month_seq#26] Condition : ((isnotnull(d_month_seq#26) AND (d_month_seq#26 = ReusedSubquery Subquery scalar-subquery#27, [id=#28])) AND isnotnull(d_date_sk#9)) -(43) Project [codegen id : 1] -Output [1]: [d_date_sk#9] +(42) CometProject Input [2]: [d_date_sk#9, d_month_seq#26] +Arguments: [d_date_sk#9], [d_date_sk#9] + +(43) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#9] (44) BroadcastExchange Input [1]: [d_date_sk#9] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] -Subquery:2 Hosting operator id = 42 Hosting Expression = ReusedSubquery Subquery scalar-subquery#27, [id=#28] +Subquery:2 Hosting operator id = 41 Hosting Expression = ReusedSubquery Subquery scalar-subquery#27, [id=#28] Subquery:3 Hosting operator id = 40 Hosting Expression = Subquery scalar-subquery#27, [id=#28] * HashAggregate (51) +- Exchange (50) - +- * HashAggregate (49) - +- * Project (48) - +- * Filter (47) - +- * ColumnarToRow (46) + +- * ColumnarToRow (49) + +- CometHashAggregate (48) + +- CometProject (47) + +- CometFilter (46) +- CometScan parquet spark_catalog.default.date_dim (45) @@ -279,23 +279,21 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,1)] ReadSchema: struct -(46) ColumnarToRow [codegen id : 1] -Input [3]: [d_month_seq#29, d_year#30, d_moy#31] - -(47) Filter [codegen id : 1] +(46) CometFilter Input [3]: [d_month_seq#29, d_year#30, d_moy#31] Condition : (((isnotnull(d_year#30) AND isnotnull(d_moy#31)) AND (d_year#30 = 2000)) AND (d_moy#31 = 1)) -(48) Project [codegen id : 1] -Output [1]: [d_month_seq#29] +(47) CometProject Input [3]: [d_month_seq#29, d_year#30, d_moy#31] +Arguments: [d_month_seq#29], [d_month_seq#29] -(49) HashAggregate [codegen id : 1] +(48) CometHashAggregate Input [1]: [d_month_seq#29] Keys [1]: [d_month_seq#29] Functions: [] -Aggregate Attributes: [] -Results [1]: [d_month_seq#29] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_month_seq#29] (50) Exchange Input [1]: [d_month_seq#29] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/simplified.txt index 7078a77e4..c2d5a6ce8 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q6/simplified.txt @@ -14,32 +14,32 @@ TakeOrderedAndProject [cnt,state] BroadcastHashJoin [c_customer_sk,ss_customer_sk] Project [ca_state,c_customer_sk] BroadcastHashJoin [ca_address_sk,c_current_addr_sk] - Filter [ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [c_current_addr_sk,c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [ss_customer_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ReusedSubquery [d_month_seq] #2 - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + ReusedSubquery [d_month_seq] #2 CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] Subquery #2 WholeStageCodegen (2) @@ -47,11 +47,11 @@ TakeOrderedAndProject [cnt,state] InputAdapter Exchange [d_month_seq] #5 WholeStageCodegen (1) - HashAggregate [d_month_seq] - Project [d_month_seq] - Filter [d_year,d_moy] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometHashAggregate [d_month_seq] + CometProject [d_month_seq] + CometFilter [d_year,d_moy] CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk] #4 @@ -60,9 +60,9 @@ TakeOrderedAndProject [cnt,state] WholeStageCodegen (6) Project [i_item_sk] BroadcastHashJoin [i_category,i_category,i_current_price,avg(i_current_price)] - Filter [i_current_price,i_category,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_current_price,i_category,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_category] InputAdapter BroadcastExchange #7 @@ -73,7 +73,7 @@ TakeOrderedAndProject [cnt,state] Exchange [i_category] #8 WholeStageCodegen (4) HashAggregate [i_category,i_current_price] [sum,count,sum,count] - Filter [i_category] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_category] CometScan parquet spark_catalog.default.item [i_current_price,i_category] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/explain.txt index 98fb9f2f6..78f4b27ac 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/explain.txt @@ -13,24 +13,24 @@ TakeOrderedAndProject (63) : : +- * BroadcastHashJoin Inner BuildRight (12) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (11) - : : +- * Project (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.customer_address (7) : +- BroadcastExchange (23) : +- * BroadcastHashJoin LeftSemi BuildRight (22) - : :- * Filter (16) - : : +- * ColumnarToRow (15) + : :- * ColumnarToRow (16) + : : +- CometFilter (15) : : +- CometScan parquet spark_catalog.default.item (14) : +- BroadcastExchange (21) - : +- * Project (20) - : +- * Filter (19) - : +- * ColumnarToRow (18) + : +- * ColumnarToRow (20) + : +- CometProject (19) + : +- CometFilter (18) : +- CometScan parquet spark_catalog.default.item (17) :- * HashAggregate (43) : +- Exchange (42) @@ -41,8 +41,8 @@ TakeOrderedAndProject (63) : : +- * BroadcastHashJoin Inner BuildRight (36) : : :- * Project (34) : : : +- * BroadcastHashJoin Inner BuildRight (33) - : : : :- * Filter (31) - : : : : +- * ColumnarToRow (30) + : : : :- * ColumnarToRow (31) + : : : : +- CometFilter (30) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (29) : : : +- ReusedExchange (32) : : +- ReusedExchange (35) @@ -56,8 +56,8 @@ TakeOrderedAndProject (63) : +- * BroadcastHashJoin Inner BuildRight (51) : :- * Project (49) : : +- * BroadcastHashJoin Inner BuildRight (48) - : : :- * Filter (46) - : : : +- * ColumnarToRow (45) + : : :- * ColumnarToRow (46) + : : : +- CometFilter (45) : : : +- CometScan parquet spark_catalog.default.web_sales (44) : : +- ReusedExchange (47) : +- ReusedExchange (50) @@ -72,12 +72,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_addr_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [4]: [ss_item_sk#1, ss_addr_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] -Condition : (isnotnull(ss_addr_sk#2) AND isnotnull(ss_item_sk#1)) (4) ReusedExchange [Reuses operator id: 68] Output [1]: [d_date_sk#6] @@ -99,16 +99,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] -Input [2]: [ca_address_sk#7, ca_gmt_offset#8] - -(9) Filter [codegen id : 2] +(8) CometFilter Input [2]: [ca_address_sk#7, ca_gmt_offset#8] Condition : ((isnotnull(ca_gmt_offset#8) AND (ca_gmt_offset#8 = -5.00)) AND isnotnull(ca_address_sk#7)) -(10) Project [codegen id : 2] -Output [1]: [ca_address_sk#7] +(9) CometProject Input [2]: [ca_address_sk#7, ca_gmt_offset#8] +Arguments: [ca_address_sk#7], [ca_address_sk#7] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [ca_address_sk#7] (11) BroadcastExchange Input [1]: [ca_address_sk#7] @@ -131,12 +131,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 4] +(15) CometFilter Input [2]: [i_item_sk#9, i_item_id#10] +Condition : isnotnull(i_item_sk#9) -(16) Filter [codegen id : 4] +(16) ColumnarToRow [codegen id : 4] Input [2]: [i_item_sk#9, i_item_id#10] -Condition : isnotnull(i_item_sk#9) (17) Scan parquet spark_catalog.default.item Output [2]: [i_item_id#11, i_category#12] @@ -145,16 +145,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Music )] ReadSchema: struct -(18) ColumnarToRow [codegen id : 3] -Input [2]: [i_item_id#11, i_category#12] - -(19) Filter [codegen id : 3] +(18) CometFilter Input [2]: [i_item_id#11, i_category#12] Condition : (isnotnull(i_category#12) AND (i_category#12 = Music )) -(20) Project [codegen id : 3] -Output [1]: [i_item_id#11] +(19) CometProject Input [2]: [i_item_id#11, i_category#12] +Arguments: [i_item_id#11], [i_item_id#11] + +(20) ColumnarToRow [codegen id : 3] +Input [1]: [i_item_id#11] (21) BroadcastExchange Input [1]: [i_item_id#11] @@ -206,12 +206,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#20), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_addr_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 11] +(30) CometFilter Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] +Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) -(31) Filter [codegen id : 11] +(31) ColumnarToRow [codegen id : 11] Input [4]: [cs_bill_addr_sk#17, cs_item_sk#18, cs_ext_sales_price#19, cs_sold_date_sk#20] -Condition : (isnotnull(cs_bill_addr_sk#17) AND isnotnull(cs_item_sk#18)) (32) ReusedExchange [Reuses operator id: 68] Output [1]: [d_date_sk#22] @@ -278,12 +278,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_addr_sk), IsNotNull(ws_item_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 17] +(45) CometFilter Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) -(46) Filter [codegen id : 17] +(46) ColumnarToRow [codegen id : 17] Input [4]: [ws_item_sk#30, ws_bill_addr_sk#31, ws_ext_sales_price#32, ws_sold_date_sk#33] -Condition : (isnotnull(ws_bill_addr_sk#31) AND isnotnull(ws_item_sk#30)) (47) ReusedExchange [Reuses operator id: 68] Output [1]: [d_date_sk#35] @@ -370,9 +370,9 @@ Arguments: 100, [i_item_id#10 ASC NULLS FIRST, total_sales#48 ASC NULLS FIRST], Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 BroadcastExchange (68) -+- * Project (67) - +- * Filter (66) - +- * ColumnarToRow (65) ++- * ColumnarToRow (67) + +- CometProject (66) + +- CometFilter (65) +- CometScan parquet spark_catalog.default.date_dim (64) @@ -383,16 +383,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,9), IsNotNull(d_date_sk)] ReadSchema: struct -(65) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#6, d_year#49, d_moy#50] - -(66) Filter [codegen id : 1] +(65) CometFilter Input [3]: [d_date_sk#6, d_year#49, d_moy#50] Condition : ((((isnotnull(d_year#49) AND isnotnull(d_moy#50)) AND (d_year#49 = 1998)) AND (d_moy#50 = 9)) AND isnotnull(d_date_sk#6)) -(67) Project [codegen id : 1] -Output [1]: [d_date_sk#6] +(66) CometProject Input [3]: [d_date_sk#6, d_year#49, d_moy#50] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(67) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] (68) BroadcastExchange Input [1]: [d_date_sk#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/simplified.txt index 0af0fd412..b010414a8 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q60/simplified.txt @@ -19,43 +19,43 @@ TakeOrderedAndProject [i_item_id,total_sales] BroadcastHashJoin [ss_addr_sk,ca_address_sk] Project [ss_item_sk,ss_addr_sk,ss_ext_sales_price] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_addr_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_addr_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_addr_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [ca_address_sk] - Filter [ca_gmt_offset,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_gmt_offset,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) BroadcastHashJoin [i_item_id,i_item_id] - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] InputAdapter BroadcastExchange #6 WholeStageCodegen (3) - Project [i_item_id] - Filter [i_category] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_id] + CometFilter [i_category] CometScan parquet spark_catalog.default.item [i_item_id,i_category] WholeStageCodegen (12) HashAggregate [i_item_id,sum] [sum(UnscaledValue(cs_ext_sales_price)),total_sales,sum] @@ -69,9 +69,9 @@ TakeOrderedAndProject [i_item_id,total_sales] BroadcastHashJoin [cs_bill_addr_sk,ca_address_sk] Project [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price] BroadcastHashJoin [cs_sold_date_sk,d_date_sk] - Filter [cs_bill_addr_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_addr_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -92,9 +92,9 @@ TakeOrderedAndProject [i_item_id,total_sales] BroadcastHashJoin [ws_bill_addr_sk,ca_address_sk] Project [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_bill_addr_sk,ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_addr_sk,ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_addr_sk,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/explain.txt index b70ffc460..766362167 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/explain.txt @@ -16,33 +16,33 @@ : : : : : +- * BroadcastHashJoin Inner BuildRight (16) : : : : : :- * Project (10) : : : : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : : : : :- * Filter (3) - : : : : : : : +- * ColumnarToRow (2) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : : : +- BroadcastExchange (8) - : : : : : : +- * Project (7) - : : : : : : +- * Filter (6) - : : : : : : +- * ColumnarToRow (5) + : : : : : : +- * ColumnarToRow (7) + : : : : : : +- CometProject (6) + : : : : : : +- CometFilter (5) : : : : : : +- CometScan parquet spark_catalog.default.store (4) : : : : : +- BroadcastExchange (15) - : : : : : +- * Project (14) - : : : : : +- * Filter (13) - : : : : : +- * ColumnarToRow (12) + : : : : : +- * ColumnarToRow (14) + : : : : : +- CometProject (13) + : : : : : +- CometFilter (12) : : : : : +- CometScan parquet spark_catalog.default.promotion (11) : : : : +- ReusedExchange (18) : : : +- BroadcastExchange (24) - : : : +- * Filter (23) - : : : +- * ColumnarToRow (22) + : : : +- * ColumnarToRow (23) + : : : +- CometFilter (22) : : : +- CometScan parquet spark_catalog.default.customer (21) : : +- BroadcastExchange (31) - : : +- * Project (30) - : : +- * Filter (29) - : : +- * ColumnarToRow (28) + : : +- * ColumnarToRow (30) + : : +- CometProject (29) + : : +- CometFilter (28) : : +- CometScan parquet spark_catalog.default.customer_address (27) : +- BroadcastExchange (38) - : +- * Project (37) - : +- * Filter (36) - : +- * ColumnarToRow (35) + : +- * ColumnarToRow (37) + : +- CometProject (36) + : +- CometFilter (35) : +- CometScan parquet spark_catalog.default.item (34) +- BroadcastExchange (65) +- * HashAggregate (64) @@ -58,8 +58,8 @@ : : : +- * BroadcastHashJoin Inner BuildRight (51) : : : :- * Project (49) : : : : +- * BroadcastHashJoin Inner BuildRight (48) - : : : : :- * Filter (46) - : : : : : +- * ColumnarToRow (45) + : : : : :- * ColumnarToRow (46) + : : : : : +- CometFilter (45) : : : : : +- CometScan parquet spark_catalog.default.store_sales (44) : : : : +- ReusedExchange (47) : : : +- ReusedExchange (50) @@ -76,12 +76,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 7] +(2) CometFilter Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] +Condition : (((isnotnull(ss_store_sk#3) AND isnotnull(ss_promo_sk#4)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_item_sk#1)) -(3) Filter [codegen id : 7] +(3) ColumnarToRow [codegen id : 7] Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_promo_sk#4, ss_ext_sales_price#5, ss_sold_date_sk#6] -Condition : (((isnotnull(ss_store_sk#3) AND isnotnull(ss_promo_sk#4)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_item_sk#1)) (4) Scan parquet spark_catalog.default.store Output [2]: [s_store_sk#8, s_gmt_offset#9] @@ -90,16 +90,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_gmt_offset), EqualTo(s_gmt_offset,-5.00), IsNotNull(s_store_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [2]: [s_store_sk#8, s_gmt_offset#9] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [2]: [s_store_sk#8, s_gmt_offset#9] Condition : ((isnotnull(s_gmt_offset#9) AND (s_gmt_offset#9 = -5.00)) AND isnotnull(s_store_sk#8)) -(7) Project [codegen id : 1] -Output [1]: [s_store_sk#8] +(6) CometProject Input [2]: [s_store_sk#8, s_gmt_offset#9] +Arguments: [s_store_sk#8], [s_store_sk#8] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [s_store_sk#8] (8) BroadcastExchange Input [1]: [s_store_sk#8] @@ -122,16 +122,16 @@ Location [not included in comparison]/{warehouse_dir}/promotion] PushedFilters: [Or(Or(EqualTo(p_channel_dmail,Y),EqualTo(p_channel_email,Y)),EqualTo(p_channel_tv,Y)), IsNotNull(p_promo_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] -Input [4]: [p_promo_sk#10, p_channel_dmail#11, p_channel_email#12, p_channel_tv#13] - -(13) Filter [codegen id : 2] +(12) CometFilter Input [4]: [p_promo_sk#10, p_channel_dmail#11, p_channel_email#12, p_channel_tv#13] Condition : ((((p_channel_dmail#11 = Y) OR (p_channel_email#12 = Y)) OR (p_channel_tv#13 = Y)) AND isnotnull(p_promo_sk#10)) -(14) Project [codegen id : 2] -Output [1]: [p_promo_sk#10] +(13) CometProject Input [4]: [p_promo_sk#10, p_channel_dmail#11, p_channel_email#12, p_channel_tv#13] +Arguments: [p_promo_sk#10], [p_promo_sk#10] + +(14) ColumnarToRow [codegen id : 2] +Input [1]: [p_promo_sk#10] (15) BroadcastExchange Input [1]: [p_promo_sk#10] @@ -167,12 +167,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(22) ColumnarToRow [codegen id : 4] +(22) CometFilter Input [2]: [c_customer_sk#15, c_current_addr_sk#16] +Condition : (isnotnull(c_customer_sk#15) AND isnotnull(c_current_addr_sk#16)) -(23) Filter [codegen id : 4] +(23) ColumnarToRow [codegen id : 4] Input [2]: [c_customer_sk#15, c_current_addr_sk#16] -Condition : (isnotnull(c_customer_sk#15) AND isnotnull(c_current_addr_sk#16)) (24) BroadcastExchange Input [2]: [c_customer_sk#15, c_current_addr_sk#16] @@ -195,16 +195,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-5.00), IsNotNull(ca_address_sk)] ReadSchema: struct -(28) ColumnarToRow [codegen id : 5] -Input [2]: [ca_address_sk#17, ca_gmt_offset#18] - -(29) Filter [codegen id : 5] +(28) CometFilter Input [2]: [ca_address_sk#17, ca_gmt_offset#18] Condition : ((isnotnull(ca_gmt_offset#18) AND (ca_gmt_offset#18 = -5.00)) AND isnotnull(ca_address_sk#17)) -(30) Project [codegen id : 5] -Output [1]: [ca_address_sk#17] +(29) CometProject Input [2]: [ca_address_sk#17, ca_gmt_offset#18] +Arguments: [ca_address_sk#17], [ca_address_sk#17] + +(30) ColumnarToRow [codegen id : 5] +Input [1]: [ca_address_sk#17] (31) BroadcastExchange Input [1]: [ca_address_sk#17] @@ -227,16 +227,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Jewelry ), IsNotNull(i_item_sk)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 6] -Input [2]: [i_item_sk#19, i_category#20] - -(36) Filter [codegen id : 6] +(35) CometFilter Input [2]: [i_item_sk#19, i_category#20] Condition : ((isnotnull(i_category#20) AND (i_category#20 = Jewelry )) AND isnotnull(i_item_sk#19)) -(37) Project [codegen id : 6] -Output [1]: [i_item_sk#19] +(36) CometProject Input [2]: [i_item_sk#19, i_category#20] +Arguments: [i_item_sk#19], [i_item_sk#19] + +(37) ColumnarToRow [codegen id : 6] +Input [1]: [i_item_sk#19] (38) BroadcastExchange Input [1]: [i_item_sk#19] @@ -278,12 +278,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#29), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 13] +(45) CometFilter Input [5]: [ss_item_sk#25, ss_customer_sk#26, ss_store_sk#27, ss_ext_sales_price#28, ss_sold_date_sk#29] +Condition : ((isnotnull(ss_store_sk#27) AND isnotnull(ss_customer_sk#26)) AND isnotnull(ss_item_sk#25)) -(46) Filter [codegen id : 13] +(46) ColumnarToRow [codegen id : 13] Input [5]: [ss_item_sk#25, ss_customer_sk#26, ss_store_sk#27, ss_ext_sales_price#28, ss_sold_date_sk#29] -Condition : ((isnotnull(ss_store_sk#27) AND isnotnull(ss_customer_sk#26)) AND isnotnull(ss_item_sk#25)) (47) ReusedExchange [Reuses operator id: 8] Output [1]: [s_store_sk#31] @@ -384,9 +384,9 @@ Input [2]: [promotions#24, total#40] Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 BroadcastExchange (72) -+- * Project (71) - +- * Filter (70) - +- * ColumnarToRow (69) ++- * ColumnarToRow (71) + +- CometProject (70) + +- CometFilter (69) +- CometScan parquet spark_catalog.default.date_dim (68) @@ -397,16 +397,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,11), IsNotNull(d_date_sk)] ReadSchema: struct -(69) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#14, d_year#42, d_moy#43] - -(70) Filter [codegen id : 1] +(69) CometFilter Input [3]: [d_date_sk#14, d_year#42, d_moy#43] Condition : ((((isnotnull(d_year#42) AND isnotnull(d_moy#43)) AND (d_year#42 = 1998)) AND (d_moy#43 = 11)) AND isnotnull(d_date_sk#14)) -(71) Project [codegen id : 1] -Output [1]: [d_date_sk#14] +(70) CometProject Input [3]: [d_date_sk#14, d_year#42, d_moy#43] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(71) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] (72) BroadcastExchange Input [1]: [d_date_sk#14] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/simplified.txt index 2272a80ba..2c3d07ac6 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q61/simplified.txt @@ -18,58 +18,58 @@ WholeStageCodegen (15) BroadcastHashJoin [ss_promo_sk,p_promo_sk] Project [ss_item_sk,ss_customer_sk,ss_promo_sk,ss_ext_sales_price,ss_sold_date_sk] BroadcastHashJoin [ss_store_sk,s_store_sk] - Filter [ss_store_sk,ss_promo_sk,ss_customer_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_promo_sk,ss_customer_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_promo_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [s_store_sk] - Filter [s_gmt_offset,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_gmt_offset,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_gmt_offset] InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [p_promo_sk] - Filter [p_channel_dmail,p_channel_email,p_channel_tv,p_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [p_promo_sk] + CometFilter [p_channel_dmail,p_channel_email,p_channel_tv,p_promo_sk] CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_dmail,p_channel_email,p_channel_tv] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Filter [c_customer_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] InputAdapter BroadcastExchange #6 WholeStageCodegen (5) - Project [ca_address_sk] - Filter [ca_gmt_offset,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_gmt_offset,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] InputAdapter BroadcastExchange #7 WholeStageCodegen (6) - Project [i_item_sk] - Filter [i_category,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_category,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_category] InputAdapter BroadcastExchange #8 @@ -89,9 +89,9 @@ WholeStageCodegen (15) BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_item_sk,ss_customer_sk,ss_ext_sales_price,ss_sold_date_sk] BroadcastHashJoin [ss_store_sk,s_store_sk] - Filter [ss_store_sk,ss_customer_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_customer_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ext_sales_price,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/explain.txt index 55423bcd1..0607d8077 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/explain.txt @@ -11,25 +11,25 @@ TakeOrderedAndProject (32) : : +- * BroadcastHashJoin Inner BuildRight (14) : : :- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.web_sales (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.warehouse (4) : : +- BroadcastExchange (13) - : : +- * Filter (12) - : : +- * ColumnarToRow (11) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) : : +- CometScan parquet spark_catalog.default.ship_mode (10) : +- BroadcastExchange (19) - : +- * Filter (18) - : +- * ColumnarToRow (17) + : +- * ColumnarToRow (18) + : +- CometFilter (17) : +- CometScan parquet spark_catalog.default.web_site (16) +- BroadcastExchange (26) - +- * Project (25) - +- * Filter (24) - +- * ColumnarToRow (23) + +- * ColumnarToRow (25) + +- CometProject (24) + +- CometFilter (23) +- CometScan parquet spark_catalog.default.date_dim (22) @@ -40,12 +40,12 @@ Location [not included in comparison]/{warehouse_dir}/web_sales] PushedFilters: [IsNotNull(ws_warehouse_sk), IsNotNull(ws_ship_mode_sk), IsNotNull(ws_web_site_sk), IsNotNull(ws_ship_date_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_warehouse_sk#4, ws_sold_date_sk#5] +Condition : (((isnotnull(ws_warehouse_sk#4) AND isnotnull(ws_ship_mode_sk#3)) AND isnotnull(ws_web_site_sk#2)) AND isnotnull(ws_ship_date_sk#1)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [5]: [ws_ship_date_sk#1, ws_web_site_sk#2, ws_ship_mode_sk#3, ws_warehouse_sk#4, ws_sold_date_sk#5] -Condition : (((isnotnull(ws_warehouse_sk#4) AND isnotnull(ws_ship_mode_sk#3)) AND isnotnull(ws_web_site_sk#2)) AND isnotnull(ws_ship_date_sk#1)) (4) Scan parquet spark_catalog.default.warehouse Output [2]: [w_warehouse_sk#6, w_warehouse_name#7] @@ -54,12 +54,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Condition : isnotnull(w_warehouse_sk#6) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] -Condition : isnotnull(w_warehouse_sk#6) (7) BroadcastExchange Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] @@ -82,12 +82,12 @@ Location [not included in comparison]/{warehouse_dir}/ship_mode] PushedFilters: [IsNotNull(sm_ship_mode_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [2]: [sm_ship_mode_sk#8, sm_type#9] +Condition : isnotnull(sm_ship_mode_sk#8) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [2]: [sm_ship_mode_sk#8, sm_type#9] -Condition : isnotnull(sm_ship_mode_sk#8) (13) BroadcastExchange Input [2]: [sm_ship_mode_sk#8, sm_type#9] @@ -110,12 +110,12 @@ Location [not included in comparison]/{warehouse_dir}/web_site] PushedFilters: [IsNotNull(web_site_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 3] +(17) CometFilter Input [2]: [web_site_sk#10, web_name#11] +Condition : isnotnull(web_site_sk#10) -(18) Filter [codegen id : 3] +(18) ColumnarToRow [codegen id : 3] Input [2]: [web_site_sk#10, web_name#11] -Condition : isnotnull(web_site_sk#10) (19) BroadcastExchange Input [2]: [web_site_sk#10, web_name#11] @@ -138,16 +138,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 4] -Input [2]: [d_date_sk#12, d_month_seq#13] - -(24) Filter [codegen id : 4] +(23) CometFilter Input [2]: [d_date_sk#12, d_month_seq#13] Condition : (((isnotnull(d_month_seq#13) AND (d_month_seq#13 >= 1200)) AND (d_month_seq#13 <= 1211)) AND isnotnull(d_date_sk#12)) -(25) Project [codegen id : 4] -Output [1]: [d_date_sk#12] +(24) CometProject Input [2]: [d_date_sk#12, d_month_seq#13] +Arguments: [d_date_sk#12], [d_date_sk#12] + +(25) ColumnarToRow [codegen id : 4] +Input [1]: [d_date_sk#12] (26) BroadcastExchange Input [1]: [d_date_sk#12] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/simplified.txt index a49361cb6..5ae522ce1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q62/simplified.txt @@ -13,36 +13,36 @@ TakeOrderedAndProject [substr(w_warehouse_name, 1, 20),sm_type,web_name,30 days BroadcastHashJoin [ws_ship_mode_sk,sm_ship_mode_sk] Project [ws_ship_date_sk,ws_web_site_sk,ws_ship_mode_sk,ws_sold_date_sk,w_warehouse_name] BroadcastHashJoin [ws_warehouse_sk,w_warehouse_sk] - Filter [ws_warehouse_sk,ws_ship_mode_sk,ws_web_site_sk,ws_ship_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_warehouse_sk,ws_ship_mode_sk,ws_web_site_sk,ws_ship_date_sk] CometScan parquet spark_catalog.default.web_sales [ws_ship_date_sk,ws_web_site_sk,ws_ship_mode_sk,ws_warehouse_sk,ws_sold_date_sk] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [sm_ship_mode_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sm_ship_mode_sk] CometScan parquet spark_catalog.default.ship_mode [sm_ship_mode_sk,sm_type] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Filter [web_site_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [web_site_sk] CometScan parquet spark_catalog.default.web_site [web_site_sk,web_name] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/explain.txt index 78baf2df8..990bc3195 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/explain.txt @@ -14,18 +14,18 @@ TakeOrderedAndProject (28) : +- * BroadcastHashJoin Inner BuildRight (12) : :- * Project (10) : : +- * BroadcastHashJoin Inner BuildRight (9) - : : :- * Project (4) - : : : +- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.item (1) : : +- BroadcastExchange (8) - : : +- * Filter (7) - : : +- * ColumnarToRow (6) + : : +- * ColumnarToRow (7) + : : +- CometFilter (6) : : +- CometScan parquet spark_catalog.default.store_sales (5) : +- ReusedExchange (11) +- BroadcastExchange (17) - +- * Filter (16) - +- * ColumnarToRow (15) + +- * ColumnarToRow (16) + +- CometFilter (15) +- CometScan parquet spark_catalog.default.store (14) @@ -36,16 +36,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [Or(And(And(In(i_category, [Books ,Children ,Electronics ]),In(i_class, [personal ,portable ,refernece ,self-help ])),In(i_brand, [exportiunivamalg #6 ,scholaramalgamalg #7 ,scholaramalgamalg #8 ,scholaramalgamalg #6 ])),And(And(In(i_category, [Men ,Music ,Women ]),In(i_class, [accessories ,classical ,fragrances ,pants ])),In(i_brand, [amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ]))), IsNotNull(i_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] -Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manager_id#5] - -(3) Filter [codegen id : 4] +(2) CometFilter Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manager_id#5] Condition : ((((i_category#4 IN (Books ,Children ,Electronics ) AND i_class#3 IN (personal ,portable ,refernece ,self-help )) AND i_brand#2 IN (scholaramalgamalg #7 ,scholaramalgamalg #8 ,exportiunivamalg #6 ,scholaramalgamalg #6 )) OR ((i_category#4 IN (Women ,Music ,Men ) AND i_class#3 IN (accessories ,classical ,fragrances ,pants )) AND i_brand#2 IN (amalgimporto #9 ,edu packscholar #9 ,exportiimporto #9 ,importoamalg #9 ))) AND isnotnull(i_item_sk#1)) -(4) Project [codegen id : 4] -Output [2]: [i_item_sk#1, i_manager_id#5] +(3) CometProject Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manager_id#5] +Arguments: [i_item_sk#1, i_manager_id#5], [i_item_sk#1, i_manager_id#5] + +(4) ColumnarToRow [codegen id : 4] +Input [2]: [i_item_sk#1, i_manager_id#5] (5) Scan parquet spark_catalog.default.store_sales Output [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] @@ -55,12 +55,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#13), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] +(6) CometFilter Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] +Condition : (isnotnull(ss_item_sk#10) AND isnotnull(ss_store_sk#11)) -(7) Filter [codegen id : 1] +(7) ColumnarToRow [codegen id : 1] Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] -Condition : (isnotnull(ss_item_sk#10) AND isnotnull(ss_store_sk#11)) (8) BroadcastExchange Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13] @@ -96,12 +96,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] +(15) CometFilter Input [1]: [s_store_sk#17] +Condition : isnotnull(s_store_sk#17) -(16) Filter [codegen id : 3] +(16) ColumnarToRow [codegen id : 3] Input [1]: [s_store_sk#17] -Condition : isnotnull(s_store_sk#17) (17) BroadcastExchange Input [1]: [s_store_sk#17] @@ -163,9 +163,9 @@ Arguments: 100, [i_manager_id#5 ASC NULLS FIRST, avg_monthly_sales#23 ASC NULLS Subquery:1 Hosting operator id = 5 Hosting Expression = ss_sold_date_sk#13 IN dynamicpruning#14 BroadcastExchange (33) -+- * Project (32) - +- * Filter (31) - +- * ColumnarToRow (30) ++- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) +- CometScan parquet spark_catalog.default.date_dim (29) @@ -176,16 +176,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [In(d_month_seq, [1200,1201,1202,1203,1204,1205,1206,1207,1208,1209,1210,1211]), IsNotNull(d_date_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#15, d_month_seq#24, d_moy#16] - -(31) Filter [codegen id : 1] +(30) CometFilter Input [3]: [d_date_sk#15, d_month_seq#24, d_moy#16] Condition : (d_month_seq#24 INSET 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211 AND isnotnull(d_date_sk#15)) -(32) Project [codegen id : 1] -Output [2]: [d_date_sk#15, d_moy#16] +(31) CometProject Input [3]: [d_date_sk#15, d_month_seq#24, d_moy#16] +Arguments: [d_date_sk#15, d_moy#16], [d_date_sk#15, d_moy#16] + +(32) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#15, d_moy#16] (33) BroadcastExchange Input [2]: [d_date_sk#15, d_moy#16] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/simplified.txt index 2520efac5..7f6f8c137 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q63/simplified.txt @@ -20,32 +20,32 @@ TakeOrderedAndProject [i_manager_id,avg_monthly_sales,sum_sales] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [i_manager_id,ss_store_sk,ss_sales_price,ss_sold_date_sk] BroadcastHashJoin [i_item_sk,ss_item_sk] - Project [i_item_sk,i_manager_id] - Filter [i_category,i_class,i_brand,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_manager_id] + CometFilter [i_category,i_class,i_brand,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_manager_id] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [ss_item_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk,d_moy] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_moy] InputAdapter ReusedExchange [d_date_sk,d_moy] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/explain.txt index b4a82aa37..667362aa3 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/explain.txt @@ -1,187 +1,185 @@ == Physical Plan == -* Sort (183) -+- Exchange (182) - +- * Project (181) - +- * SortMergeJoin Inner (180) - :- * Sort (111) - : +- Exchange (110) - : +- * HashAggregate (109) - : +- * HashAggregate (108) - : +- * Project (107) - : +- * BroadcastHashJoin Inner BuildRight (106) - : :- * Project (100) - : : +- * BroadcastHashJoin Inner BuildRight (99) - : : :- * Project (97) - : : : +- * BroadcastHashJoin Inner BuildRight (96) - : : : :- * Project (91) - : : : : +- * BroadcastHashJoin Inner BuildRight (90) - : : : : :- * Project (88) - : : : : : +- * BroadcastHashJoin Inner BuildRight (87) - : : : : : :- * Project (82) - : : : : : : +- * BroadcastHashJoin Inner BuildRight (81) - : : : : : : :- * Project (79) - : : : : : : : +- * BroadcastHashJoin Inner BuildRight (78) - : : : : : : : :- * Project (73) - : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (72) - : : : : : : : : :- * Project (67) - : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (66) - : : : : : : : : : :- * Project (64) - : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (63) - : : : : : : : : : : :- * Project (58) - : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (57) - : : : : : : : : : : : :- * Project (55) - : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (54) - : : : : : : : : : : : : :- * Project (49) - : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (48) - : : : : : : : : : : : : : :- * Project (43) - : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (42) - : : : : : : : : : : : : : : :- * Project (37) - : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (36) - : : : : : : : : : : : : : : : :- * Project (34) - : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (33) - : : : : : : : : : : : : : : : : :- * Sort (12) - : : : : : : : : : : : : : : : : : +- Exchange (11) - : : : : : : : : : : : : : : : : : +- * Project (10) - : : : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildLeft (9) - : : : : : : : : : : : : : : : : : :- BroadcastExchange (4) - : : : : : : : : : : : : : : : : : : +- * Filter (3) - : : : : : : : : : : : : : : : : : : +- * ColumnarToRow (2) - : : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) - : : : : : : : : : : : : : : : : : +- * Project (8) - : : : : : : : : : : : : : : : : : +- * Filter (7) - : : : : : : : : : : : : : : : : : +- * ColumnarToRow (6) - : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (5) - : : : : : : : : : : : : : : : : +- * Sort (32) - : : : : : : : : : : : : : : : : +- * Project (31) - : : : : : : : : : : : : : : : : +- * Filter (30) - : : : : : : : : : : : : : : : : +- * HashAggregate (29) - : : : : : : : : : : : : : : : : +- Exchange (28) - : : : : : : : : : : : : : : : : +- * HashAggregate (27) - : : : : : : : : : : : : : : : : +- * Project (26) - : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (25) - : : : : : : : : : : : : : : : : :- * Sort (18) - : : : : : : : : : : : : : : : : : +- Exchange (17) - : : : : : : : : : : : : : : : : : +- * Project (16) - : : : : : : : : : : : : : : : : : +- * Filter (15) - : : : : : : : : : : : : : : : : : +- * ColumnarToRow (14) - : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) - : : : : : : : : : : : : : : : : +- * Sort (24) - : : : : : : : : : : : : : : : : +- Exchange (23) - : : : : : : : : : : : : : : : : +- * Project (22) - : : : : : : : : : : : : : : : : +- * Filter (21) - : : : : : : : : : : : : : : : : +- * ColumnarToRow (20) - : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (19) - : : : : : : : : : : : : : : : +- ReusedExchange (35) - : : : : : : : : : : : : : : +- BroadcastExchange (41) - : : : : : : : : : : : : : : +- * Filter (40) - : : : : : : : : : : : : : : +- * ColumnarToRow (39) - : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store (38) - : : : : : : : : : : : : : +- BroadcastExchange (47) - : : : : : : : : : : : : : +- * Filter (46) - : : : : : : : : : : : : : +- * ColumnarToRow (45) - : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer (44) - : : : : : : : : : : : : +- BroadcastExchange (53) - : : : : : : : : : : : : +- * Filter (52) - : : : : : : : : : : : : +- * ColumnarToRow (51) - : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.date_dim (50) - : : : : : : : : : : : +- ReusedExchange (56) - : : : : : : : : : : +- BroadcastExchange (62) - : : : : : : : : : : +- * Filter (61) - : : : : : : : : : : +- * ColumnarToRow (60) - : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (59) - : : : : : : : : : +- ReusedExchange (65) - : : : : : : : : +- BroadcastExchange (71) - : : : : : : : : +- * Filter (70) - : : : : : : : : +- * ColumnarToRow (69) - : : : : : : : : +- CometScan parquet spark_catalog.default.promotion (68) - : : : : : : : +- BroadcastExchange (77) - : : : : : : : +- * Filter (76) - : : : : : : : +- * ColumnarToRow (75) - : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (74) - : : : : : : +- ReusedExchange (80) - : : : : : +- BroadcastExchange (86) - : : : : : +- * Filter (85) - : : : : : +- * ColumnarToRow (84) - : : : : : +- CometScan parquet spark_catalog.default.customer_address (83) - : : : : +- ReusedExchange (89) - : : : +- BroadcastExchange (95) - : : : +- * Filter (94) - : : : +- * ColumnarToRow (93) - : : : +- CometScan parquet spark_catalog.default.income_band (92) - : : +- ReusedExchange (98) - : +- BroadcastExchange (105) - : +- * Project (104) - : +- * Filter (103) - : +- * ColumnarToRow (102) - : +- CometScan parquet spark_catalog.default.item (101) - +- * Sort (179) - +- Exchange (178) - +- * HashAggregate (177) - +- * HashAggregate (176) - +- * Project (175) - +- * BroadcastHashJoin Inner BuildRight (174) - :- * Project (172) - : +- * BroadcastHashJoin Inner BuildRight (171) - : :- * Project (169) - : : +- * BroadcastHashJoin Inner BuildRight (168) - : : :- * Project (166) - : : : +- * BroadcastHashJoin Inner BuildRight (165) - : : : :- * Project (163) - : : : : +- * BroadcastHashJoin Inner BuildRight (162) - : : : : :- * Project (160) - : : : : : +- * BroadcastHashJoin Inner BuildRight (159) - : : : : : :- * Project (157) - : : : : : : +- * BroadcastHashJoin Inner BuildRight (156) - : : : : : : :- * Project (154) - : : : : : : : +- * BroadcastHashJoin Inner BuildRight (153) - : : : : : : : :- * Project (151) - : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (150) - : : : : : : : : :- * Project (148) - : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (147) - : : : : : : : : : :- * Project (145) - : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (144) - : : : : : : : : : : :- * Project (142) - : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (141) - : : : : : : : : : : : :- * Project (139) - : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (138) - : : : : : : : : : : : : :- * Project (136) - : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (135) - : : : : : : : : : : : : : :- * Project (133) - : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (132) - : : : : : : : : : : : : : : :- * Project (130) - : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (129) - : : : : : : : : : : : : : : : :- * Sort (123) - : : : : : : : : : : : : : : : : +- Exchange (122) - : : : : : : : : : : : : : : : : +- * Project (121) - : : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildLeft (120) - : : : : : : : : : : : : : : : : :- BroadcastExchange (115) - : : : : : : : : : : : : : : : : : +- * Filter (114) - : : : : : : : : : : : : : : : : : +- * ColumnarToRow (113) - : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (112) - : : : : : : : : : : : : : : : : +- * Project (119) - : : : : : : : : : : : : : : : : +- * Filter (118) - : : : : : : : : : : : : : : : : +- * ColumnarToRow (117) - : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (116) - : : : : : : : : : : : : : : : +- * Sort (128) - : : : : : : : : : : : : : : : +- * Project (127) - : : : : : : : : : : : : : : : +- * Filter (126) - : : : : : : : : : : : : : : : +- * HashAggregate (125) - : : : : : : : : : : : : : : : +- ReusedExchange (124) - : : : : : : : : : : : : : : +- ReusedExchange (131) - : : : : : : : : : : : : : +- ReusedExchange (134) - : : : : : : : : : : : : +- ReusedExchange (137) - : : : : : : : : : : : +- ReusedExchange (140) - : : : : : : : : : : +- ReusedExchange (143) - : : : : : : : : : +- ReusedExchange (146) - : : : : : : : : +- ReusedExchange (149) - : : : : : : : +- ReusedExchange (152) - : : : : : : +- ReusedExchange (155) - : : : : : +- ReusedExchange (158) - : : : : +- ReusedExchange (161) - : : : +- ReusedExchange (164) - : : +- ReusedExchange (167) - : +- ReusedExchange (170) - +- ReusedExchange (173) +* Sort (181) ++- Exchange (180) + +- * Project (179) + +- * SortMergeJoin Inner (178) + :- * Sort (110) + : +- Exchange (109) + : +- * HashAggregate (108) + : +- * HashAggregate (107) + : +- * Project (106) + : +- * BroadcastHashJoin Inner BuildRight (105) + : :- * Project (99) + : : +- * BroadcastHashJoin Inner BuildRight (98) + : : :- * Project (96) + : : : +- * BroadcastHashJoin Inner BuildRight (95) + : : : :- * Project (90) + : : : : +- * BroadcastHashJoin Inner BuildRight (89) + : : : : :- * Project (87) + : : : : : +- * BroadcastHashJoin Inner BuildRight (86) + : : : : : :- * Project (81) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (80) + : : : : : : :- * Project (78) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (77) + : : : : : : : :- * Project (72) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (71) + : : : : : : : : :- * Project (66) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (65) + : : : : : : : : : :- * Project (63) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (62) + : : : : : : : : : : :- * Project (57) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (56) + : : : : : : : : : : : :- * Project (54) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (53) + : : : : : : : : : : : : :- * Project (48) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (47) + : : : : : : : : : : : : : :- * Project (42) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (41) + : : : : : : : : : : : : : : :- * Project (36) + : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (35) + : : : : : : : : : : : : : : : :- * Project (33) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (32) + : : : : : : : : : : : : : : : : :- * Sort (11) + : : : : : : : : : : : : : : : : : +- Exchange (10) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (9) + : : : : : : : : : : : : : : : : : +- CometProject (8) + : : : : : : : : : : : : : : : : : +- CometBroadcastHashJoin (7) + : : : : : : : : : : : : : : : : : :- CometBroadcastExchange (3) + : : : : : : : : : : : : : : : : : : +- CometFilter (2) + : : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : : : : : : : : : : : : +- CometProject (6) + : : : : : : : : : : : : : : : : : +- CometFilter (5) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : : : : : : : : : : : : : : +- * Sort (31) + : : : : : : : : : : : : : : : : +- * Project (30) + : : : : : : : : : : : : : : : : +- * Filter (29) + : : : : : : : : : : : : : : : : +- * HashAggregate (28) + : : : : : : : : : : : : : : : : +- Exchange (27) + : : : : : : : : : : : : : : : : +- * HashAggregate (26) + : : : : : : : : : : : : : : : : +- * Project (25) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (24) + : : : : : : : : : : : : : : : : :- * Sort (17) + : : : : : : : : : : : : : : : : : +- Exchange (16) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (15) + : : : : : : : : : : : : : : : : : +- CometProject (14) + : : : : : : : : : : : : : : : : : +- CometFilter (13) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (12) + : : : : : : : : : : : : : : : : +- * Sort (23) + : : : : : : : : : : : : : : : : +- Exchange (22) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (21) + : : : : : : : : : : : : : : : : +- CometProject (20) + : : : : : : : : : : : : : : : : +- CometFilter (19) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (18) + : : : : : : : : : : : : : : : +- ReusedExchange (34) + : : : : : : : : : : : : : : +- BroadcastExchange (40) + : : : : : : : : : : : : : : +- * ColumnarToRow (39) + : : : : : : : : : : : : : : +- CometFilter (38) + : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store (37) + : : : : : : : : : : : : : +- BroadcastExchange (46) + : : : : : : : : : : : : : +- * ColumnarToRow (45) + : : : : : : : : : : : : : +- CometFilter (44) + : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer (43) + : : : : : : : : : : : : +- BroadcastExchange (52) + : : : : : : : : : : : : +- * ColumnarToRow (51) + : : : : : : : : : : : : +- CometFilter (50) + : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.date_dim (49) + : : : : : : : : : : : +- ReusedExchange (55) + : : : : : : : : : : +- BroadcastExchange (61) + : : : : : : : : : : +- * ColumnarToRow (60) + : : : : : : : : : : +- CometFilter (59) + : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (58) + : : : : : : : : : +- ReusedExchange (64) + : : : : : : : : +- BroadcastExchange (70) + : : : : : : : : +- * ColumnarToRow (69) + : : : : : : : : +- CometFilter (68) + : : : : : : : : +- CometScan parquet spark_catalog.default.promotion (67) + : : : : : : : +- BroadcastExchange (76) + : : : : : : : +- * ColumnarToRow (75) + : : : : : : : +- CometFilter (74) + : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (73) + : : : : : : +- ReusedExchange (79) + : : : : : +- BroadcastExchange (85) + : : : : : +- * ColumnarToRow (84) + : : : : : +- CometFilter (83) + : : : : : +- CometScan parquet spark_catalog.default.customer_address (82) + : : : : +- ReusedExchange (88) + : : : +- BroadcastExchange (94) + : : : +- * ColumnarToRow (93) + : : : +- CometFilter (92) + : : : +- CometScan parquet spark_catalog.default.income_band (91) + : : +- ReusedExchange (97) + : +- BroadcastExchange (104) + : +- * ColumnarToRow (103) + : +- CometProject (102) + : +- CometFilter (101) + : +- CometScan parquet spark_catalog.default.item (100) + +- * Sort (177) + +- Exchange (176) + +- * HashAggregate (175) + +- * HashAggregate (174) + +- * Project (173) + +- * BroadcastHashJoin Inner BuildRight (172) + :- * Project (170) + : +- * BroadcastHashJoin Inner BuildRight (169) + : :- * Project (167) + : : +- * BroadcastHashJoin Inner BuildRight (166) + : : :- * Project (164) + : : : +- * BroadcastHashJoin Inner BuildRight (163) + : : : :- * Project (161) + : : : : +- * BroadcastHashJoin Inner BuildRight (160) + : : : : :- * Project (158) + : : : : : +- * BroadcastHashJoin Inner BuildRight (157) + : : : : : :- * Project (155) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (154) + : : : : : : :- * Project (152) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (151) + : : : : : : : :- * Project (149) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (148) + : : : : : : : : :- * Project (146) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (145) + : : : : : : : : : :- * Project (143) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (142) + : : : : : : : : : : :- * Project (140) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (139) + : : : : : : : : : : : :- * Project (137) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (136) + : : : : : : : : : : : : :- * Project (134) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (133) + : : : : : : : : : : : : : :- * Project (131) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (130) + : : : : : : : : : : : : : : :- * Project (128) + : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (127) + : : : : : : : : : : : : : : : :- * Sort (121) + : : : : : : : : : : : : : : : : +- Exchange (120) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (119) + : : : : : : : : : : : : : : : : +- CometProject (118) + : : : : : : : : : : : : : : : : +- CometBroadcastHashJoin (117) + : : : : : : : : : : : : : : : : :- CometBroadcastExchange (113) + : : : : : : : : : : : : : : : : : +- CometFilter (112) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (111) + : : : : : : : : : : : : : : : : +- CometProject (116) + : : : : : : : : : : : : : : : : +- CometFilter (115) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (114) + : : : : : : : : : : : : : : : +- * Sort (126) + : : : : : : : : : : : : : : : +- * Project (125) + : : : : : : : : : : : : : : : +- * Filter (124) + : : : : : : : : : : : : : : : +- * HashAggregate (123) + : : : : : : : : : : : : : : : +- ReusedExchange (122) + : : : : : : : : : : : : : : +- ReusedExchange (129) + : : : : : : : : : : : : : +- ReusedExchange (132) + : : : : : : : : : : : : +- ReusedExchange (135) + : : : : : : : : : : : +- ReusedExchange (138) + : : : : : : : : : : +- ReusedExchange (141) + : : : : : : : : : +- ReusedExchange (144) + : : : : : : : : +- ReusedExchange (147) + : : : : : : : +- ReusedExchange (150) + : : : : : : +- ReusedExchange (153) + : : : : : +- ReusedExchange (156) + : : : : +- ReusedExchange (159) + : : : +- ReusedExchange (162) + : : +- ReusedExchange (165) + : +- ReusedExchange (168) + +- ReusedExchange (171) (1) Scan parquet spark_catalog.default.store_sales @@ -192,512 +190,508 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] Condition : (((((((isnotnull(ss_item_sk#1) AND isnotnull(ss_ticket_number#8)) AND isnotnull(ss_store_sk#6)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_cdemo_sk#3)) AND isnotnull(ss_promo_sk#7)) AND isnotnull(ss_hdemo_sk#4)) AND isnotnull(ss_addr_sk#5)) -(4) BroadcastExchange +(3) CometBroadcastExchange Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[7, int, false] as bigint) & 4294967295))),false), [plan_id=1] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] -(5) Scan parquet spark_catalog.default.store_returns +(4) Scan parquet spark_catalog.default.store_returns Output [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] Batched: true Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] ReadSchema: struct -(6) ColumnarToRow -Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] - -(7) Filter +(5) CometFilter Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] Condition : (isnotnull(sr_item_sk#14) AND isnotnull(sr_ticket_number#15)) -(8) Project -Output [2]: [sr_item_sk#14, sr_ticket_number#15] +(6) CometProject Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Arguments: [sr_item_sk#14, sr_ticket_number#15], [sr_item_sk#14, sr_ticket_number#15] -(9) BroadcastHashJoin [codegen id : 2] -Left keys [2]: [ss_item_sk#1, ss_ticket_number#8] -Right keys [2]: [sr_item_sk#14, sr_ticket_number#15] -Join type: Inner -Join condition: None +(7) CometBroadcastHashJoin +Left output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Right output [2]: [sr_item_sk#14, sr_ticket_number#15] +Arguments: [ss_item_sk#1, ss_ticket_number#8], [sr_item_sk#14, sr_ticket_number#15], Inner -(10) Project [codegen id : 2] -Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +(8) CometProject Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, sr_item_sk#14, sr_ticket_number#15] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12], [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] + +(9) ColumnarToRow [codegen id : 1] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] -(11) Exchange +(10) Exchange Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] -Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] +Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] -(12) Sort [codegen id : 3] +(11) Sort [codegen id : 2] Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] Arguments: [ss_item_sk#1 ASC NULLS FIRST], false, 0 -(13) Scan parquet spark_catalog.default.catalog_sales +(12) Scan parquet spark_catalog.default.catalog_sales Output [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] Batched: true Location [not included in comparison]/{warehouse_dir}/catalog_sales] PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_order_number)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 4] -Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] - -(15) Filter [codegen id : 4] +(13) CometFilter Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] Condition : (isnotnull(cs_item_sk#17) AND isnotnull(cs_order_number#18)) -(16) Project [codegen id : 4] -Output [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +(14) CometProject Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Arguments: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19], [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] -(17) Exchange +(16) Exchange Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] -Arguments: hashpartitioning(cs_item_sk#17, cs_order_number#18, 5), ENSURE_REQUIREMENTS, [plan_id=3] +Arguments: hashpartitioning(cs_item_sk#17, cs_order_number#18, 5), ENSURE_REQUIREMENTS, [plan_id=2] -(18) Sort [codegen id : 5] +(17) Sort [codegen id : 4] Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] Arguments: [cs_item_sk#17 ASC NULLS FIRST, cs_order_number#18 ASC NULLS FIRST], false, 0 -(19) Scan parquet spark_catalog.default.catalog_returns +(18) Scan parquet spark_catalog.default.catalog_returns Output [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] Batched: true Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] ReadSchema: struct -(20) ColumnarToRow [codegen id : 6] -Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] - -(21) Filter [codegen id : 6] +(19) CometFilter Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] Condition : (isnotnull(cr_item_sk#21) AND isnotnull(cr_order_number#22)) -(22) Project [codegen id : 6] -Output [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +(20) CometProject Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Arguments: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25], [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] + +(21) ColumnarToRow [codegen id : 5] +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] -(23) Exchange +(22) Exchange Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] -Arguments: hashpartitioning(cr_item_sk#21, cr_order_number#22, 5), ENSURE_REQUIREMENTS, [plan_id=4] +Arguments: hashpartitioning(cr_item_sk#21, cr_order_number#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] -(24) Sort [codegen id : 7] +(23) Sort [codegen id : 6] Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] Arguments: [cr_item_sk#21 ASC NULLS FIRST, cr_order_number#22 ASC NULLS FIRST], false, 0 -(25) SortMergeJoin [codegen id : 8] +(24) SortMergeJoin [codegen id : 7] Left keys [2]: [cs_item_sk#17, cs_order_number#18] Right keys [2]: [cr_item_sk#21, cr_order_number#22] Join type: Inner Join condition: None -(26) Project [codegen id : 8] +(25) Project [codegen id : 7] Output [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] Input [8]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] -(27) HashAggregate [codegen id : 8] +(26) HashAggregate [codegen id : 7] Input [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] Keys [1]: [cs_item_sk#17] Functions [2]: [partial_sum(UnscaledValue(cs_ext_list_price#19)), partial_sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] Aggregate Attributes [3]: [sum#27, sum#28, isEmpty#29] Results [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] -(28) Exchange +(27) Exchange Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] -Arguments: hashpartitioning(cs_item_sk#17, 5), ENSURE_REQUIREMENTS, [plan_id=5] +Arguments: hashpartitioning(cs_item_sk#17, 5), ENSURE_REQUIREMENTS, [plan_id=4] -(29) HashAggregate [codegen id : 9] +(28) HashAggregate [codegen id : 8] Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] Keys [1]: [cs_item_sk#17] Functions [2]: [sum(UnscaledValue(cs_ext_list_price#19)), sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#19))#33, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34] Results [3]: [cs_item_sk#17, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#19))#33,17,2) AS sale#35, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34 AS refund#36] -(30) Filter [codegen id : 9] +(29) Filter [codegen id : 8] Input [3]: [cs_item_sk#17, sale#35, refund#36] Condition : ((isnotnull(sale#35) AND isnotnull(refund#36)) AND (cast(sale#35 as decimal(21,2)) > (2 * refund#36))) -(31) Project [codegen id : 9] +(30) Project [codegen id : 8] Output [1]: [cs_item_sk#17] Input [3]: [cs_item_sk#17, sale#35, refund#36] -(32) Sort [codegen id : 9] +(31) Sort [codegen id : 8] Input [1]: [cs_item_sk#17] Arguments: [cs_item_sk#17 ASC NULLS FIRST], false, 0 -(33) SortMergeJoin [codegen id : 25] +(32) SortMergeJoin [codegen id : 24] Left keys [1]: [ss_item_sk#1] Right keys [1]: [cs_item_sk#17] Join type: Inner Join condition: None -(34) Project [codegen id : 25] +(33) Project [codegen id : 24] Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, cs_item_sk#17] -(35) ReusedExchange [Reuses operator id: 187] +(34) ReusedExchange [Reuses operator id: 185] Output [2]: [d_date_sk#37, d_year#38] -(36) BroadcastHashJoin [codegen id : 25] +(35) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_sold_date_sk#12] Right keys [1]: [d_date_sk#37] Join type: Inner Join condition: None -(37) Project [codegen id : 25] +(36) Project [codegen id : 24] Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38] Input [13]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, d_date_sk#37, d_year#38] -(38) Scan parquet spark_catalog.default.store +(37) Scan parquet spark_catalog.default.store Output [3]: [s_store_sk#39, s_store_name#40, s_zip#41] Batched: true Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_zip)] ReadSchema: struct -(39) ColumnarToRow [codegen id : 11] +(38) CometFilter Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Condition : ((isnotnull(s_store_sk#39) AND isnotnull(s_store_name#40)) AND isnotnull(s_zip#41)) -(40) Filter [codegen id : 11] +(39) ColumnarToRow [codegen id : 10] Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] -Condition : ((isnotnull(s_store_sk#39) AND isnotnull(s_store_name#40)) AND isnotnull(s_zip#41)) -(41) BroadcastExchange +(40) BroadcastExchange Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] -(42) BroadcastHashJoin [codegen id : 25] +(41) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_store_sk#6] Right keys [1]: [s_store_sk#39] Join type: Inner Join condition: None -(43) Project [codegen id : 25] +(42) Project [codegen id : 24] Output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41] Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_sk#39, s_store_name#40, s_zip#41] -(44) Scan parquet spark_catalog.default.customer +(43) Scan parquet spark_catalog.default.customer Output [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] Batched: true Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_first_sales_date_sk), IsNotNull(c_first_shipto_date_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 12] +(44) CometFilter Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Condition : (((((isnotnull(c_customer_sk#42) AND isnotnull(c_first_sales_date_sk#47)) AND isnotnull(c_first_shipto_date_sk#46)) AND isnotnull(c_current_cdemo_sk#43)) AND isnotnull(c_current_hdemo_sk#44)) AND isnotnull(c_current_addr_sk#45)) -(46) Filter [codegen id : 12] +(45) ColumnarToRow [codegen id : 11] Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] -Condition : (((((isnotnull(c_customer_sk#42) AND isnotnull(c_first_sales_date_sk#47)) AND isnotnull(c_first_shipto_date_sk#46)) AND isnotnull(c_current_cdemo_sk#43)) AND isnotnull(c_current_hdemo_sk#44)) AND isnotnull(c_current_addr_sk#45)) -(47) BroadcastExchange +(46) BroadcastExchange Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] -(48) BroadcastHashJoin [codegen id : 25] +(47) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_customer_sk#2] Right keys [1]: [c_customer_sk#42] Join type: Inner Join condition: None -(49) Project [codegen id : 25] +(48) Project [codegen id : 24] Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] Input [18]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] -(50) Scan parquet spark_catalog.default.date_dim +(49) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date_sk#48, d_year#49] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date_sk)] ReadSchema: struct -(51) ColumnarToRow [codegen id : 13] +(50) CometFilter Input [2]: [d_date_sk#48, d_year#49] +Condition : isnotnull(d_date_sk#48) -(52) Filter [codegen id : 13] +(51) ColumnarToRow [codegen id : 12] Input [2]: [d_date_sk#48, d_year#49] -Condition : isnotnull(d_date_sk#48) -(53) BroadcastExchange +(52) BroadcastExchange Input [2]: [d_date_sk#48, d_year#49] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] -(54) BroadcastHashJoin [codegen id : 25] +(53) BroadcastHashJoin [codegen id : 24] Left keys [1]: [c_first_sales_date_sk#47] Right keys [1]: [d_date_sk#48] Join type: Inner Join condition: None -(55) Project [codegen id : 25] +(54) Project [codegen id : 24] Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49] Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47, d_date_sk#48, d_year#49] -(56) ReusedExchange [Reuses operator id: 53] +(55) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#50, d_year#51] -(57) BroadcastHashJoin [codegen id : 25] +(56) BroadcastHashJoin [codegen id : 24] Left keys [1]: [c_first_shipto_date_sk#46] Right keys [1]: [d_date_sk#50] Join type: Inner Join condition: None -(58) Project [codegen id : 25] +(57) Project [codegen id : 24] Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49, d_date_sk#50, d_year#51] -(59) Scan parquet spark_catalog.default.customer_demographics +(58) Scan parquet spark_catalog.default.customer_demographics Output [2]: [cd_demo_sk#52, cd_marital_status#53] Batched: true Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status)] ReadSchema: struct -(60) ColumnarToRow [codegen id : 15] +(59) CometFilter Input [2]: [cd_demo_sk#52, cd_marital_status#53] +Condition : (isnotnull(cd_demo_sk#52) AND isnotnull(cd_marital_status#53)) -(61) Filter [codegen id : 15] +(60) ColumnarToRow [codegen id : 14] Input [2]: [cd_demo_sk#52, cd_marital_status#53] -Condition : (isnotnull(cd_demo_sk#52) AND isnotnull(cd_marital_status#53)) -(62) BroadcastExchange +(61) BroadcastExchange Input [2]: [cd_demo_sk#52, cd_marital_status#53] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] -(63) BroadcastHashJoin [codegen id : 25] +(62) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_cdemo_sk#3] Right keys [1]: [cd_demo_sk#52] Join type: Inner Join condition: None -(64) Project [codegen id : 25] +(63) Project [codegen id : 24] Output [16]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53] Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_demo_sk#52, cd_marital_status#53] -(65) ReusedExchange [Reuses operator id: 62] +(64) ReusedExchange [Reuses operator id: 61] Output [2]: [cd_demo_sk#54, cd_marital_status#55] -(66) BroadcastHashJoin [codegen id : 25] +(65) BroadcastHashJoin [codegen id : 24] Left keys [1]: [c_current_cdemo_sk#43] Right keys [1]: [cd_demo_sk#54] Join type: Inner Join condition: NOT (cd_marital_status#53 = cd_marital_status#55) -(67) Project [codegen id : 25] +(66) Project [codegen id : 24] Output [14]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] Input [18]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53, cd_demo_sk#54, cd_marital_status#55] -(68) Scan parquet spark_catalog.default.promotion +(67) Scan parquet spark_catalog.default.promotion Output [1]: [p_promo_sk#56] Batched: true Location [not included in comparison]/{warehouse_dir}/promotion] PushedFilters: [IsNotNull(p_promo_sk)] ReadSchema: struct -(69) ColumnarToRow [codegen id : 17] +(68) CometFilter Input [1]: [p_promo_sk#56] +Condition : isnotnull(p_promo_sk#56) -(70) Filter [codegen id : 17] +(69) ColumnarToRow [codegen id : 16] Input [1]: [p_promo_sk#56] -Condition : isnotnull(p_promo_sk#56) -(71) BroadcastExchange +(70) BroadcastExchange Input [1]: [p_promo_sk#56] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] -(72) BroadcastHashJoin [codegen id : 25] +(71) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_promo_sk#7] Right keys [1]: [p_promo_sk#56] Join type: Inner Join condition: None -(73) Project [codegen id : 25] +(72) Project [codegen id : 24] Output [13]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, p_promo_sk#56] -(74) Scan parquet spark_catalog.default.household_demographics +(73) Scan parquet spark_catalog.default.household_demographics Output [2]: [hd_demo_sk#57, hd_income_band_sk#58] Batched: true Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_demo_sk), IsNotNull(hd_income_band_sk)] ReadSchema: struct -(75) ColumnarToRow [codegen id : 18] +(74) CometFilter Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Condition : (isnotnull(hd_demo_sk#57) AND isnotnull(hd_income_band_sk#58)) -(76) Filter [codegen id : 18] +(75) ColumnarToRow [codegen id : 17] Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] -Condition : (isnotnull(hd_demo_sk#57) AND isnotnull(hd_income_band_sk#58)) -(77) BroadcastExchange +(76) BroadcastExchange Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] -(78) BroadcastHashJoin [codegen id : 25] +(77) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_hdemo_sk#4] Right keys [1]: [hd_demo_sk#57] Join type: Inner Join condition: None -(79) Project [codegen id : 25] +(78) Project [codegen id : 24] Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58] Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_demo_sk#57, hd_income_band_sk#58] -(80) ReusedExchange [Reuses operator id: 77] +(79) ReusedExchange [Reuses operator id: 76] Output [2]: [hd_demo_sk#59, hd_income_band_sk#60] -(81) BroadcastHashJoin [codegen id : 25] +(80) BroadcastHashJoin [codegen id : 24] Left keys [1]: [c_current_hdemo_sk#44] Right keys [1]: [hd_demo_sk#59] Join type: Inner Join condition: None -(82) Project [codegen id : 25] +(81) Project [codegen id : 24] Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60] Input [15]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_demo_sk#59, hd_income_band_sk#60] -(83) Scan parquet spark_catalog.default.customer_address +(82) Scan parquet spark_catalog.default.customer_address Output [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] Batched: true Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk)] ReadSchema: struct -(84) ColumnarToRow [codegen id : 20] +(83) CometFilter Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Condition : isnotnull(ca_address_sk#61) -(85) Filter [codegen id : 20] +(84) ColumnarToRow [codegen id : 19] Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] -Condition : isnotnull(ca_address_sk#61) -(86) BroadcastExchange +(85) BroadcastExchange Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=11] -(87) BroadcastHashJoin [codegen id : 25] +(86) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_addr_sk#5] Right keys [1]: [ca_address_sk#61] Join type: Inner Join condition: None -(88) Project [codegen id : 25] +(87) Project [codegen id : 24] Output [16]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] Input [18]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] -(89) ReusedExchange [Reuses operator id: 86] +(88) ReusedExchange [Reuses operator id: 85] Output [5]: [ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] -(90) BroadcastHashJoin [codegen id : 25] +(89) BroadcastHashJoin [codegen id : 24] Left keys [1]: [c_current_addr_sk#45] Right keys [1]: [ca_address_sk#66] Join type: Inner Join condition: None -(91) Project [codegen id : 25] +(90) Project [codegen id : 24] Output [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] Input [21]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] -(92) Scan parquet spark_catalog.default.income_band +(91) Scan parquet spark_catalog.default.income_band Output [1]: [ib_income_band_sk#71] Batched: true Location [not included in comparison]/{warehouse_dir}/income_band] PushedFilters: [IsNotNull(ib_income_band_sk)] ReadSchema: struct -(93) ColumnarToRow [codegen id : 22] +(92) CometFilter Input [1]: [ib_income_band_sk#71] +Condition : isnotnull(ib_income_band_sk#71) -(94) Filter [codegen id : 22] +(93) ColumnarToRow [codegen id : 21] Input [1]: [ib_income_band_sk#71] -Condition : isnotnull(ib_income_band_sk#71) -(95) BroadcastExchange +(94) BroadcastExchange Input [1]: [ib_income_band_sk#71] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] -(96) BroadcastHashJoin [codegen id : 25] +(95) BroadcastHashJoin [codegen id : 24] Left keys [1]: [hd_income_band_sk#58] Right keys [1]: [ib_income_band_sk#71] Join type: Inner Join condition: None -(97) Project [codegen id : 25] +(96) Project [codegen id : 24] Output [18]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] Input [20]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#71] -(98) ReusedExchange [Reuses operator id: 95] +(97) ReusedExchange [Reuses operator id: 94] Output [1]: [ib_income_band_sk#72] -(99) BroadcastHashJoin [codegen id : 25] +(98) BroadcastHashJoin [codegen id : 24] Left keys [1]: [hd_income_band_sk#60] Right keys [1]: [ib_income_band_sk#72] Join type: Inner Join condition: None -(100) Project [codegen id : 25] +(99) Project [codegen id : 24] Output [17]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#72] -(101) Scan parquet spark_catalog.default.item +(100) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] Batched: true Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_current_price), In(i_color, [burlywood ,floral ,indian ,medium ,purple ,spring ]), GreaterThanOrEqual(i_current_price,64.00), LessThanOrEqual(i_current_price,74.00), GreaterThanOrEqual(i_current_price,65.00), LessThanOrEqual(i_current_price,79.00), IsNotNull(i_item_sk)] ReadSchema: struct -(102) ColumnarToRow [codegen id : 24] -Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] - -(103) Filter [codegen id : 24] +(101) CometFilter Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] Condition : ((((((isnotnull(i_current_price#74) AND i_color#75 IN (purple ,burlywood ,indian ,spring ,floral ,medium )) AND (i_current_price#74 >= 64.00)) AND (i_current_price#74 <= 74.00)) AND (i_current_price#74 >= 65.00)) AND (i_current_price#74 <= 79.00)) AND isnotnull(i_item_sk#73)) -(104) Project [codegen id : 24] -Output [2]: [i_item_sk#73, i_product_name#76] +(102) CometProject Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Arguments: [i_item_sk#73, i_product_name#76], [i_item_sk#73, i_product_name#76] + +(103) ColumnarToRow [codegen id : 23] +Input [2]: [i_item_sk#73, i_product_name#76] -(105) BroadcastExchange +(104) BroadcastExchange Input [2]: [i_item_sk#73, i_product_name#76] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] -(106) BroadcastHashJoin [codegen id : 25] +(105) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_item_sk#1] Right keys [1]: [i_item_sk#73] Join type: Inner Join condition: None -(107) Project [codegen id : 25] +(106) Project [codegen id : 24] Output [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] -(108) HashAggregate [codegen id : 25] +(107) HashAggregate [codegen id : 24] Input [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#9)), partial_sum(UnscaledValue(ss_list_price#10)), partial_sum(UnscaledValue(ss_coupon_amt#11))] Aggregate Attributes [4]: [count#77, sum#78, sum#79, sum#80] Results [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] -(109) HashAggregate [codegen id : 25] +(108) HashAggregate [codegen id : 24] Input [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#9)), sum(UnscaledValue(ss_list_price#10)), sum(UnscaledValue(ss_coupon_amt#11))] Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#9))#86, sum(UnscaledValue(ss_list_price#10))#87, sum(UnscaledValue(ss_coupon_amt#11))#88] Results [17]: [i_product_name#76 AS product_name#89, i_item_sk#73 AS item_sk#90, s_store_name#40 AS store_name#91, s_zip#41 AS store_zip#92, ca_street_number#62 AS b_street_number#93, ca_street_name#63 AS b_streen_name#94, ca_city#64 AS b_city#95, ca_zip#65 AS b_zip#96, ca_street_number#67 AS c_street_number#97, ca_street_name#68 AS c_street_name#98, ca_city#69 AS c_city#99, ca_zip#70 AS c_zip#100, d_year#38 AS syear#101, count(1)#85 AS cnt#102, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#9))#86,17,2) AS s1#103, MakeDecimal(sum(UnscaledValue(ss_list_price#10))#87,17,2) AS s2#104, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#11))#88,17,2) AS s3#105] -(110) Exchange +(109) Exchange Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] -Arguments: hashpartitioning(item_sk#90, store_name#91, store_zip#92, 5), ENSURE_REQUIREMENTS, [plan_id=15] +Arguments: hashpartitioning(item_sk#90, store_name#91, store_zip#92, 5), ENSURE_REQUIREMENTS, [plan_id=14] -(111) Sort [codegen id : 26] +(110) Sort [codegen id : 25] Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] Arguments: [item_sk#90 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, store_zip#92 ASC NULLS FIRST], false, 0 -(112) Scan parquet spark_catalog.default.store_sales +(111) Scan parquet spark_catalog.default.store_sales Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] Batched: true Location: InMemoryFileIndex [] @@ -705,370 +699,366 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#117), dynamicpruningexpression(ss_s PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] ReadSchema: struct -(113) ColumnarToRow [codegen id : 27] -Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] - -(114) Filter [codegen id : 27] +(112) CometFilter Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] Condition : (((((((isnotnull(ss_item_sk#106) AND isnotnull(ss_ticket_number#113)) AND isnotnull(ss_store_sk#111)) AND isnotnull(ss_customer_sk#107)) AND isnotnull(ss_cdemo_sk#108)) AND isnotnull(ss_promo_sk#112)) AND isnotnull(ss_hdemo_sk#109)) AND isnotnull(ss_addr_sk#110)) -(115) BroadcastExchange +(113) CometBroadcastExchange Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[7, int, false] as bigint) & 4294967295))),false), [plan_id=16] +Arguments: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] -(116) Scan parquet spark_catalog.default.store_returns +(114) Scan parquet spark_catalog.default.store_returns Output [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] Batched: true Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] ReadSchema: struct -(117) ColumnarToRow -Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] - -(118) Filter +(115) CometFilter Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] Condition : (isnotnull(sr_item_sk#119) AND isnotnull(sr_ticket_number#120)) -(119) Project -Output [2]: [sr_item_sk#119, sr_ticket_number#120] +(116) CometProject Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Arguments: [sr_item_sk#119, sr_ticket_number#120], [sr_item_sk#119, sr_ticket_number#120] -(120) BroadcastHashJoin [codegen id : 28] -Left keys [2]: [ss_item_sk#106, ss_ticket_number#113] -Right keys [2]: [sr_item_sk#119, sr_ticket_number#120] -Join type: Inner -Join condition: None +(117) CometBroadcastHashJoin +Left output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Right output [2]: [sr_item_sk#119, sr_ticket_number#120] +Arguments: [ss_item_sk#106, ss_ticket_number#113], [sr_item_sk#119, sr_ticket_number#120], Inner -(121) Project [codegen id : 28] -Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +(118) CometProject Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, sr_item_sk#119, sr_ticket_number#120] +Arguments: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117], [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] + +(119) ColumnarToRow [codegen id : 26] +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] -(122) Exchange +(120) Exchange Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] -Arguments: hashpartitioning(ss_item_sk#106, 5), ENSURE_REQUIREMENTS, [plan_id=17] +Arguments: hashpartitioning(ss_item_sk#106, 5), ENSURE_REQUIREMENTS, [plan_id=15] -(123) Sort [codegen id : 29] +(121) Sort [codegen id : 27] Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] Arguments: [ss_item_sk#106 ASC NULLS FIRST], false, 0 -(124) ReusedExchange [Reuses operator id: 28] +(122) ReusedExchange [Reuses operator id: 27] Output [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] -(125) HashAggregate [codegen id : 35] +(123) HashAggregate [codegen id : 33] Input [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] Keys [1]: [cs_item_sk#122] Functions [2]: [sum(UnscaledValue(cs_ext_list_price#126)), sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))] Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#126))#33, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34] Results [3]: [cs_item_sk#122, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#126))#33,17,2) AS sale#130, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34 AS refund#131] -(126) Filter [codegen id : 35] +(124) Filter [codegen id : 33] Input [3]: [cs_item_sk#122, sale#130, refund#131] Condition : ((isnotnull(sale#130) AND isnotnull(refund#131)) AND (cast(sale#130 as decimal(21,2)) > (2 * refund#131))) -(127) Project [codegen id : 35] +(125) Project [codegen id : 33] Output [1]: [cs_item_sk#122] Input [3]: [cs_item_sk#122, sale#130, refund#131] -(128) Sort [codegen id : 35] +(126) Sort [codegen id : 33] Input [1]: [cs_item_sk#122] Arguments: [cs_item_sk#122 ASC NULLS FIRST], false, 0 -(129) SortMergeJoin [codegen id : 51] +(127) SortMergeJoin [codegen id : 49] Left keys [1]: [ss_item_sk#106] Right keys [1]: [cs_item_sk#122] Join type: Inner Join condition: None -(130) Project [codegen id : 51] +(128) Project [codegen id : 49] Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, cs_item_sk#122] -(131) ReusedExchange [Reuses operator id: 191] +(129) ReusedExchange [Reuses operator id: 189] Output [2]: [d_date_sk#132, d_year#133] -(132) BroadcastHashJoin [codegen id : 51] +(130) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_sold_date_sk#117] Right keys [1]: [d_date_sk#132] Join type: Inner Join condition: None -(133) Project [codegen id : 51] +(131) Project [codegen id : 49] Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133] Input [13]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, d_date_sk#132, d_year#133] -(134) ReusedExchange [Reuses operator id: 41] +(132) ReusedExchange [Reuses operator id: 40] Output [3]: [s_store_sk#134, s_store_name#135, s_zip#136] -(135) BroadcastHashJoin [codegen id : 51] +(133) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_store_sk#111] Right keys [1]: [s_store_sk#134] Join type: Inner Join condition: None -(136) Project [codegen id : 51] +(134) Project [codegen id : 49] Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136] Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_sk#134, s_store_name#135, s_zip#136] -(137) ReusedExchange [Reuses operator id: 47] +(135) ReusedExchange [Reuses operator id: 46] Output [6]: [c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] -(138) BroadcastHashJoin [codegen id : 51] +(136) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_customer_sk#107] Right keys [1]: [c_customer_sk#137] Join type: Inner Join condition: None -(139) Project [codegen id : 51] +(137) Project [codegen id : 49] Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] Input [18]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] -(140) ReusedExchange [Reuses operator id: 53] +(138) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#143, d_year#144] -(141) BroadcastHashJoin [codegen id : 51] +(139) BroadcastHashJoin [codegen id : 49] Left keys [1]: [c_first_sales_date_sk#142] Right keys [1]: [d_date_sk#143] Join type: Inner Join condition: None -(142) Project [codegen id : 51] +(140) Project [codegen id : 49] Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144] Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142, d_date_sk#143, d_year#144] -(143) ReusedExchange [Reuses operator id: 53] +(141) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#145, d_year#146] -(144) BroadcastHashJoin [codegen id : 51] +(142) BroadcastHashJoin [codegen id : 49] Left keys [1]: [c_first_shipto_date_sk#141] Right keys [1]: [d_date_sk#145] Join type: Inner Join condition: None -(145) Project [codegen id : 51] +(143) Project [codegen id : 49] Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144, d_date_sk#145, d_year#146] -(146) ReusedExchange [Reuses operator id: 62] +(144) ReusedExchange [Reuses operator id: 61] Output [2]: [cd_demo_sk#147, cd_marital_status#148] -(147) BroadcastHashJoin [codegen id : 51] +(145) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_cdemo_sk#108] Right keys [1]: [cd_demo_sk#147] Join type: Inner Join condition: None -(148) Project [codegen id : 51] +(146) Project [codegen id : 49] Output [16]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148] Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_demo_sk#147, cd_marital_status#148] -(149) ReusedExchange [Reuses operator id: 62] +(147) ReusedExchange [Reuses operator id: 61] Output [2]: [cd_demo_sk#149, cd_marital_status#150] -(150) BroadcastHashJoin [codegen id : 51] +(148) BroadcastHashJoin [codegen id : 49] Left keys [1]: [c_current_cdemo_sk#138] Right keys [1]: [cd_demo_sk#149] Join type: Inner Join condition: NOT (cd_marital_status#148 = cd_marital_status#150) -(151) Project [codegen id : 51] +(149) Project [codegen id : 49] Output [14]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] Input [18]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148, cd_demo_sk#149, cd_marital_status#150] -(152) ReusedExchange [Reuses operator id: 71] +(150) ReusedExchange [Reuses operator id: 70] Output [1]: [p_promo_sk#151] -(153) BroadcastHashJoin [codegen id : 51] +(151) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_promo_sk#112] Right keys [1]: [p_promo_sk#151] Join type: Inner Join condition: None -(154) Project [codegen id : 51] +(152) Project [codegen id : 49] Output [13]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, p_promo_sk#151] -(155) ReusedExchange [Reuses operator id: 77] +(153) ReusedExchange [Reuses operator id: 76] Output [2]: [hd_demo_sk#152, hd_income_band_sk#153] -(156) BroadcastHashJoin [codegen id : 51] +(154) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_hdemo_sk#109] Right keys [1]: [hd_demo_sk#152] Join type: Inner Join condition: None -(157) Project [codegen id : 51] +(155) Project [codegen id : 49] Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153] Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_demo_sk#152, hd_income_band_sk#153] -(158) ReusedExchange [Reuses operator id: 77] +(156) ReusedExchange [Reuses operator id: 76] Output [2]: [hd_demo_sk#154, hd_income_band_sk#155] -(159) BroadcastHashJoin [codegen id : 51] +(157) BroadcastHashJoin [codegen id : 49] Left keys [1]: [c_current_hdemo_sk#139] Right keys [1]: [hd_demo_sk#154] Join type: Inner Join condition: None -(160) Project [codegen id : 51] +(158) Project [codegen id : 49] Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155] Input [15]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_demo_sk#154, hd_income_band_sk#155] -(161) ReusedExchange [Reuses operator id: 86] +(159) ReusedExchange [Reuses operator id: 85] Output [5]: [ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] -(162) BroadcastHashJoin [codegen id : 51] +(160) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_addr_sk#110] Right keys [1]: [ca_address_sk#156] Join type: Inner Join condition: None -(163) Project [codegen id : 51] +(161) Project [codegen id : 49] Output [16]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] Input [18]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] -(164) ReusedExchange [Reuses operator id: 86] +(162) ReusedExchange [Reuses operator id: 85] Output [5]: [ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] -(165) BroadcastHashJoin [codegen id : 51] +(163) BroadcastHashJoin [codegen id : 49] Left keys [1]: [c_current_addr_sk#140] Right keys [1]: [ca_address_sk#161] Join type: Inner Join condition: None -(166) Project [codegen id : 51] +(164) Project [codegen id : 49] Output [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] Input [21]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] -(167) ReusedExchange [Reuses operator id: 95] +(165) ReusedExchange [Reuses operator id: 94] Output [1]: [ib_income_band_sk#166] -(168) BroadcastHashJoin [codegen id : 51] +(166) BroadcastHashJoin [codegen id : 49] Left keys [1]: [hd_income_band_sk#153] Right keys [1]: [ib_income_band_sk#166] Join type: Inner Join condition: None -(169) Project [codegen id : 51] +(167) Project [codegen id : 49] Output [18]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] Input [20]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#166] -(170) ReusedExchange [Reuses operator id: 95] +(168) ReusedExchange [Reuses operator id: 94] Output [1]: [ib_income_band_sk#167] -(171) BroadcastHashJoin [codegen id : 51] +(169) BroadcastHashJoin [codegen id : 49] Left keys [1]: [hd_income_band_sk#155] Right keys [1]: [ib_income_band_sk#167] Join type: Inner Join condition: None -(172) Project [codegen id : 51] +(170) Project [codegen id : 49] Output [17]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#167] -(173) ReusedExchange [Reuses operator id: 105] +(171) ReusedExchange [Reuses operator id: 104] Output [2]: [i_item_sk#168, i_product_name#169] -(174) BroadcastHashJoin [codegen id : 51] +(172) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_item_sk#106] Right keys [1]: [i_item_sk#168] Join type: Inner Join condition: None -(175) Project [codegen id : 51] +(173) Project [codegen id : 49] Output [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] -(176) HashAggregate [codegen id : 51] +(174) HashAggregate [codegen id : 49] Input [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#114)), partial_sum(UnscaledValue(ss_list_price#115)), partial_sum(UnscaledValue(ss_coupon_amt#116))] Aggregate Attributes [4]: [count#77, sum#170, sum#171, sum#172] Results [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] -(177) HashAggregate [codegen id : 51] +(175) HashAggregate [codegen id : 49] Input [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#114)), sum(UnscaledValue(ss_list_price#115)), sum(UnscaledValue(ss_coupon_amt#116))] Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#114))#86, sum(UnscaledValue(ss_list_price#115))#87, sum(UnscaledValue(ss_coupon_amt#116))#88] Results [8]: [i_item_sk#168 AS item_sk#176, s_store_name#135 AS store_name#177, s_zip#136 AS store_zip#178, d_year#133 AS syear#179, count(1)#85 AS cnt#180, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#114))#86,17,2) AS s1#181, MakeDecimal(sum(UnscaledValue(ss_list_price#115))#87,17,2) AS s2#182, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#116))#88,17,2) AS s3#183] -(178) Exchange +(176) Exchange Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] -Arguments: hashpartitioning(item_sk#176, store_name#177, store_zip#178, 5), ENSURE_REQUIREMENTS, [plan_id=18] +Arguments: hashpartitioning(item_sk#176, store_name#177, store_zip#178, 5), ENSURE_REQUIREMENTS, [plan_id=16] -(179) Sort [codegen id : 52] +(177) Sort [codegen id : 50] Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] Arguments: [item_sk#176 ASC NULLS FIRST, store_name#177 ASC NULLS FIRST, store_zip#178 ASC NULLS FIRST], false, 0 -(180) SortMergeJoin [codegen id : 53] +(178) SortMergeJoin [codegen id : 51] Left keys [3]: [item_sk#90, store_name#91, store_zip#92] Right keys [3]: [item_sk#176, store_name#177, store_zip#178] Join type: Inner Join condition: (cnt#180 <= cnt#102) -(181) Project [codegen id : 53] +(179) Project [codegen id : 51] Output [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] Input [25]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] -(182) Exchange +(180) Exchange Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] -Arguments: rangepartitioning(product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=19] +Arguments: rangepartitioning(product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=17] -(183) Sort [codegen id : 54] +(181) Sort [codegen id : 52] Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] Arguments: [product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST], true, 0 ===== Subqueries ===== Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 -BroadcastExchange (187) -+- * Filter (186) - +- * ColumnarToRow (185) - +- CometScan parquet spark_catalog.default.date_dim (184) +BroadcastExchange (185) ++- * ColumnarToRow (184) + +- CometFilter (183) + +- CometScan parquet spark_catalog.default.date_dim (182) -(184) Scan parquet spark_catalog.default.date_dim +(182) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date_sk#37, d_year#38] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk)] ReadSchema: struct -(185) ColumnarToRow [codegen id : 1] +(183) CometFilter Input [2]: [d_date_sk#37, d_year#38] +Condition : ((isnotnull(d_year#38) AND (d_year#38 = 1999)) AND isnotnull(d_date_sk#37)) -(186) Filter [codegen id : 1] +(184) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#37, d_year#38] -Condition : ((isnotnull(d_year#38) AND (d_year#38 = 1999)) AND isnotnull(d_date_sk#37)) -(187) BroadcastExchange +(185) BroadcastExchange Input [2]: [d_date_sk#37, d_year#38] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=18] -Subquery:2 Hosting operator id = 112 Hosting Expression = ss_sold_date_sk#117 IN dynamicpruning#118 -BroadcastExchange (191) -+- * Filter (190) - +- * ColumnarToRow (189) - +- CometScan parquet spark_catalog.default.date_dim (188) +Subquery:2 Hosting operator id = 111 Hosting Expression = ss_sold_date_sk#117 IN dynamicpruning#118 +BroadcastExchange (189) ++- * ColumnarToRow (188) + +- CometFilter (187) + +- CometScan parquet spark_catalog.default.date_dim (186) -(188) Scan parquet spark_catalog.default.date_dim +(186) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date_sk#132, d_year#133] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(189) ColumnarToRow [codegen id : 1] +(187) CometFilter Input [2]: [d_date_sk#132, d_year#133] +Condition : ((isnotnull(d_year#133) AND (d_year#133 = 2000)) AND isnotnull(d_date_sk#132)) -(190) Filter [codegen id : 1] +(188) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#132, d_year#133] -Condition : ((isnotnull(d_year#133) AND (d_year#133 = 2000)) AND isnotnull(d_date_sk#132)) -(191) BroadcastExchange +(189) BroadcastExchange Input [2]: [d_date_sk#132, d_year#133] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=19] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/simplified.txt index 76cac39ea..d972e0082 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q64/simplified.txt @@ -1,16 +1,16 @@ -WholeStageCodegen (54) +WholeStageCodegen (52) Sort [product_name,store_name,cnt] InputAdapter Exchange [product_name,store_name,cnt] #1 - WholeStageCodegen (53) + WholeStageCodegen (51) Project [product_name,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,s1,s2,s3,syear,cnt] SortMergeJoin [item_sk,store_name,store_zip,item_sk,store_name,store_zip,cnt,cnt] InputAdapter - WholeStageCodegen (26) + WholeStageCodegen (25) Sort [item_sk,store_name,store_zip] InputAdapter Exchange [item_sk,store_name,store_zip] #2 - WholeStageCodegen (25) + WholeStageCodegen (24) HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),product_name,item_sk,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] @@ -46,148 +46,144 @@ WholeStageCodegen (54) Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] SortMergeJoin [ss_item_sk,cs_item_sk] InputAdapter - WholeStageCodegen (3) + WholeStageCodegen (2) Sort [ss_item_sk] InputAdapter Exchange [ss_item_sk] #3 - WholeStageCodegen (2) - Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] - BroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] - InputAdapter - BroadcastExchange #4 - WholeStageCodegen (1) - Filter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] - SubqueryBroadcast [d_date_sk] #1 - BroadcastExchange #5 - WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] - Project [sr_item_sk,sr_ticket_number] - Filter [sr_item_sk,sr_ticket_number] - ColumnarToRow - InputAdapter + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + CometBroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + CometBroadcastExchange #4 + CometFilter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_item_sk,sr_ticket_number] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] InputAdapter - WholeStageCodegen (9) + WholeStageCodegen (8) Sort [cs_item_sk] Project [cs_item_sk] Filter [sale,refund] HashAggregate [cs_item_sk,sum,sum,isEmpty] [sum(UnscaledValue(cs_ext_list_price)),sum(((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)),sale,refund,sum,sum,isEmpty] InputAdapter Exchange [cs_item_sk] #6 - WholeStageCodegen (8) + WholeStageCodegen (7) HashAggregate [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] [sum,sum,isEmpty,sum,sum,isEmpty] Project [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] InputAdapter - WholeStageCodegen (5) + WholeStageCodegen (4) Sort [cs_item_sk,cs_order_number] InputAdapter Exchange [cs_item_sk,cs_order_number] #7 - WholeStageCodegen (4) - Project [cs_item_sk,cs_order_number,cs_ext_list_price] - Filter [cs_item_sk,cs_order_number] - ColumnarToRow - InputAdapter + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [cs_item_sk,cs_order_number,cs_ext_list_price] + CometFilter [cs_item_sk,cs_order_number] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_ext_list_price,cs_sold_date_sk] InputAdapter - WholeStageCodegen (7) + WholeStageCodegen (6) Sort [cr_item_sk,cr_order_number] InputAdapter Exchange [cr_item_sk,cr_order_number] #8 - WholeStageCodegen (6) - Project [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit] - Filter [cr_item_sk,cr_order_number] - ColumnarToRow - InputAdapter + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit] + CometFilter [cr_item_sk,cr_order_number] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit,cr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk,d_year] #5 InputAdapter BroadcastExchange #9 - WholeStageCodegen (11) - Filter [s_store_sk,s_store_name,s_zip] - ColumnarToRow - InputAdapter + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_name,s_zip] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_zip] InputAdapter BroadcastExchange #10 - WholeStageCodegen (12) - Filter [c_customer_sk,c_first_sales_date_sk,c_first_shipto_date_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (11) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_first_sales_date_sk,c_first_shipto_date_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] InputAdapter BroadcastExchange #11 - WholeStageCodegen (13) - Filter [d_date_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #11 InputAdapter BroadcastExchange #12 - WholeStageCodegen (15) - Filter [cd_demo_sk,cd_marital_status] - ColumnarToRow - InputAdapter + WholeStageCodegen (14) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] InputAdapter ReusedExchange [cd_demo_sk,cd_marital_status] #12 InputAdapter BroadcastExchange #13 - WholeStageCodegen (17) - Filter [p_promo_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [p_promo_sk] CometScan parquet spark_catalog.default.promotion [p_promo_sk] InputAdapter BroadcastExchange #14 - WholeStageCodegen (18) - Filter [hd_demo_sk,hd_income_band_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (17) + ColumnarToRow + InputAdapter + CometFilter [hd_demo_sk,hd_income_band_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_income_band_sk] InputAdapter ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 InputAdapter BroadcastExchange #15 - WholeStageCodegen (20) - Filter [ca_address_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (19) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] InputAdapter ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 InputAdapter BroadcastExchange #16 - WholeStageCodegen (22) - Filter [ib_income_band_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (21) + ColumnarToRow + InputAdapter + CometFilter [ib_income_band_sk] CometScan parquet spark_catalog.default.income_band [ib_income_band_sk] InputAdapter ReusedExchange [ib_income_band_sk] #16 InputAdapter BroadcastExchange #17 - WholeStageCodegen (24) - Project [i_item_sk,i_product_name] - Filter [i_current_price,i_color,i_item_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (23) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_product_name] + CometFilter [i_current_price,i_color,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_color,i_product_name] InputAdapter - WholeStageCodegen (52) + WholeStageCodegen (50) Sort [item_sk,store_name,store_zip] InputAdapter Exchange [item_sk,store_name,store_zip] #18 - WholeStageCodegen (51) + WholeStageCodegen (49) HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),item_sk,store_name,store_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] @@ -223,34 +219,30 @@ WholeStageCodegen (54) Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] SortMergeJoin [ss_item_sk,cs_item_sk] InputAdapter - WholeStageCodegen (29) + WholeStageCodegen (27) Sort [ss_item_sk] InputAdapter Exchange [ss_item_sk] #19 - WholeStageCodegen (28) - Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] - BroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] - InputAdapter - BroadcastExchange #20 - WholeStageCodegen (27) - Filter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] - SubqueryBroadcast [d_date_sk] #2 - BroadcastExchange #21 - WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] - Project [sr_item_sk,sr_ticket_number] - Filter [sr_item_sk,sr_ticket_number] - ColumnarToRow - InputAdapter + WholeStageCodegen (26) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + CometBroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + CometBroadcastExchange #20 + CometFilter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #21 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_item_sk,sr_ticket_number] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] InputAdapter - WholeStageCodegen (35) + WholeStageCodegen (33) Sort [cs_item_sk] Project [cs_item_sk] Filter [sale,refund] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/explain.txt index b9107a072..eda84bb52 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/explain.txt @@ -6,8 +6,8 @@ TakeOrderedAndProject (39) : +- * BroadcastHashJoin Inner BuildRight (21) : :- * Project (16) : : +- * BroadcastHashJoin Inner BuildRight (15) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.store (1) : : +- BroadcastExchange (14) : : +- * Filter (13) @@ -16,13 +16,13 @@ TakeOrderedAndProject (39) : : +- * HashAggregate (10) : : +- * Project (9) : : +- * BroadcastHashJoin Inner BuildRight (8) - : : :- * Filter (6) - : : : +- * ColumnarToRow (5) + : : :- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.store_sales (4) : : +- ReusedExchange (7) : +- BroadcastExchange (20) - : +- * Filter (19) - : +- * ColumnarToRow (18) + : +- * ColumnarToRow (19) + : +- CometFilter (18) : +- CometScan parquet spark_catalog.default.item (17) +- BroadcastExchange (36) +- * Filter (35) @@ -34,8 +34,8 @@ TakeOrderedAndProject (39) +- * HashAggregate (29) +- * Project (28) +- * BroadcastHashJoin Inner BuildRight (27) - :- * Filter (25) - : +- * ColumnarToRow (24) + :- * ColumnarToRow (25) + : +- CometFilter (24) : +- CometScan parquet spark_catalog.default.store_sales (23) +- ReusedExchange (26) @@ -47,12 +47,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 9] +(2) CometFilter Input [2]: [s_store_sk#1, s_store_name#2] +Condition : isnotnull(s_store_sk#1) -(3) Filter [codegen id : 9] +(3) ColumnarToRow [codegen id : 9] Input [2]: [s_store_sk#1, s_store_name#2] -Condition : isnotnull(s_store_sk#1) (4) Scan parquet spark_catalog.default.store_sales Output [4]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] @@ -62,12 +62,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 2] +(5) CometFilter Input [4]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] +Condition : (isnotnull(ss_store_sk#4) AND isnotnull(ss_item_sk#3)) -(6) Filter [codegen id : 2] +(6) ColumnarToRow [codegen id : 2] Input [4]: [ss_item_sk#3, ss_store_sk#4, ss_sales_price#5, ss_sold_date_sk#6] -Condition : (isnotnull(ss_store_sk#4) AND isnotnull(ss_item_sk#3)) (7) ReusedExchange [Reuses operator id: 44] Output [1]: [d_date_sk#8] @@ -125,12 +125,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 4] +(18) CometFilter Input [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] +Condition : isnotnull(i_item_sk#13) -(19) Filter [codegen id : 4] +(19) ColumnarToRow [codegen id : 4] Input [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] -Condition : isnotnull(i_item_sk#13) (20) BroadcastExchange Input [5]: [i_item_sk#13, i_item_desc#14, i_current_price#15, i_wholesale_cost#16, i_brand#17] @@ -154,12 +154,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#21), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(24) ColumnarToRow [codegen id : 6] +(24) CometFilter Input [4]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20, ss_sold_date_sk#21] +Condition : isnotnull(ss_store_sk#19) -(25) Filter [codegen id : 6] +(25) ColumnarToRow [codegen id : 6] Input [4]: [ss_item_sk#18, ss_store_sk#19, ss_sales_price#20, ss_sold_date_sk#21] -Condition : isnotnull(ss_store_sk#19) (26) ReusedExchange [Reuses operator id: 44] Output [1]: [d_date_sk#23] @@ -236,9 +236,9 @@ Arguments: 100, [s_store_name#2 ASC NULLS FIRST, i_item_desc#14 ASC NULLS FIRST] Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7 BroadcastExchange (44) -+- * Project (43) - +- * Filter (42) - +- * ColumnarToRow (41) ++- * ColumnarToRow (43) + +- CometProject (42) + +- CometFilter (41) +- CometScan parquet spark_catalog.default.date_dim (40) @@ -249,16 +249,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1176), LessThanOrEqual(d_month_seq,1187), IsNotNull(d_date_sk)] ReadSchema: struct -(41) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#8, d_month_seq#34] - -(42) Filter [codegen id : 1] +(41) CometFilter Input [2]: [d_date_sk#8, d_month_seq#34] Condition : (((isnotnull(d_month_seq#34) AND (d_month_seq#34 >= 1176)) AND (d_month_seq#34 <= 1187)) AND isnotnull(d_date_sk#8)) -(43) Project [codegen id : 1] -Output [1]: [d_date_sk#8] +(42) CometProject Input [2]: [d_date_sk#8, d_month_seq#34] +Arguments: [d_date_sk#8], [d_date_sk#8] + +(43) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#8] (44) BroadcastExchange Input [1]: [d_date_sk#8] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/simplified.txt index 6670cbdac..33b695e81 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q65/simplified.txt @@ -6,9 +6,9 @@ TakeOrderedAndProject [s_store_name,i_item_desc,revenue,i_current_price,i_wholes BroadcastHashJoin [ss_item_sk,i_item_sk] Project [s_store_name,ss_store_sk,ss_item_sk,revenue] BroadcastHashJoin [s_store_sk,ss_store_sk] - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name] InputAdapter BroadcastExchange #1 @@ -21,26 +21,26 @@ TakeOrderedAndProject [s_store_name,i_item_desc,revenue,i_current_price,i_wholes HashAggregate [ss_store_sk,ss_item_sk,ss_sales_price] [sum,sum] Project [ss_item_sk,ss_store_sk,ss_sales_price] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (4) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc,i_current_price,i_wholesale_cost,i_brand] InputAdapter BroadcastExchange #5 @@ -58,9 +58,9 @@ TakeOrderedAndProject [s_store_name,i_item_desc,revenue,i_current_price,i_wholes HashAggregate [ss_store_sk,ss_item_sk,ss_sales_price] [sum,sum] Project [ss_item_sk,ss_store_sk,ss_sales_price] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/explain.txt index b3e8005c9..a26c457aa 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/explain.txt @@ -15,23 +15,23 @@ TakeOrderedAndProject (52) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.warehouse (4) : : : +- ReusedExchange (10) : : +- BroadcastExchange (17) - : : +- * Project (16) - : : +- * Filter (15) - : : +- * ColumnarToRow (14) + : : +- * ColumnarToRow (16) + : : +- CometProject (15) + : : +- CometFilter (14) : : +- CometScan parquet spark_catalog.default.time_dim (13) : +- BroadcastExchange (24) - : +- * Project (23) - : +- * Filter (22) - : +- * ColumnarToRow (21) + : +- * ColumnarToRow (23) + : +- CometProject (22) + : +- CometFilter (21) : +- CometScan parquet spark_catalog.default.ship_mode (20) +- * HashAggregate (47) +- Exchange (46) @@ -44,8 +44,8 @@ TakeOrderedAndProject (52) : : +- * BroadcastHashJoin Inner BuildRight (37) : : :- * Project (35) : : : +- * BroadcastHashJoin Inner BuildRight (34) - : : : :- * Filter (32) - : : : : +- * ColumnarToRow (31) + : : : :- * ColumnarToRow (32) + : : : : +- CometFilter (31) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (30) : : : +- ReusedExchange (33) : : +- ReusedExchange (36) @@ -61,12 +61,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#7), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_warehouse_sk), IsNotNull(ws_sold_time_sk), IsNotNull(ws_ship_mode_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [7]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_warehouse_sk#3, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7] +Condition : ((isnotnull(ws_warehouse_sk#3) AND isnotnull(ws_sold_time_sk#1)) AND isnotnull(ws_ship_mode_sk#2)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [7]: [ws_sold_time_sk#1, ws_ship_mode_sk#2, ws_warehouse_sk#3, ws_quantity#4, ws_ext_sales_price#5, ws_net_paid#6, ws_sold_date_sk#7] -Condition : ((isnotnull(ws_warehouse_sk#3) AND isnotnull(ws_sold_time_sk#1)) AND isnotnull(ws_ship_mode_sk#2)) (4) Scan parquet spark_catalog.default.warehouse Output [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] @@ -75,12 +75,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] +Condition : isnotnull(w_warehouse_sk#9) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] -Condition : isnotnull(w_warehouse_sk#9) (7) BroadcastExchange Input [7]: [w_warehouse_sk#9, w_warehouse_name#10, w_warehouse_sq_ft#11, w_city#12, w_county#13, w_state#14, w_country#15] @@ -116,16 +116,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_time), GreaterThanOrEqual(t_time,30838), LessThanOrEqual(t_time,59638), IsNotNull(t_time_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] -Input [2]: [t_time_sk#19, t_time#20] - -(15) Filter [codegen id : 3] +(14) CometFilter Input [2]: [t_time_sk#19, t_time#20] Condition : (((isnotnull(t_time#20) AND (t_time#20 >= 30838)) AND (t_time#20 <= 59638)) AND isnotnull(t_time_sk#19)) -(16) Project [codegen id : 3] -Output [1]: [t_time_sk#19] +(15) CometProject Input [2]: [t_time_sk#19, t_time#20] +Arguments: [t_time_sk#19], [t_time_sk#19] + +(16) ColumnarToRow [codegen id : 3] +Input [1]: [t_time_sk#19] (17) BroadcastExchange Input [1]: [t_time_sk#19] @@ -148,16 +148,16 @@ Location [not included in comparison]/{warehouse_dir}/ship_mode] PushedFilters: [In(sm_carrier, [BARIAN ,DHL ]), IsNotNull(sm_ship_mode_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] -Input [2]: [sm_ship_mode_sk#21, sm_carrier#22] - -(22) Filter [codegen id : 4] +(21) CometFilter Input [2]: [sm_ship_mode_sk#21, sm_carrier#22] Condition : (sm_carrier#22 IN (DHL ,BARIAN ) AND isnotnull(sm_ship_mode_sk#21)) -(23) Project [codegen id : 4] -Output [1]: [sm_ship_mode_sk#21] +(22) CometProject Input [2]: [sm_ship_mode_sk#21, sm_carrier#22] +Arguments: [sm_ship_mode_sk#21], [sm_ship_mode_sk#21] + +(23) ColumnarToRow [codegen id : 4] +Input [1]: [sm_ship_mode_sk#21] (24) BroadcastExchange Input [1]: [sm_ship_mode_sk#21] @@ -199,12 +199,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#175), dynamicpruningexpression(cs_s PushedFilters: [IsNotNull(cs_warehouse_sk), IsNotNull(cs_sold_time_sk), IsNotNull(cs_ship_mode_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 11] +(31) CometFilter Input [7]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_warehouse_sk#171, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175] +Condition : ((isnotnull(cs_warehouse_sk#171) AND isnotnull(cs_sold_time_sk#169)) AND isnotnull(cs_ship_mode_sk#170)) -(32) Filter [codegen id : 11] +(32) ColumnarToRow [codegen id : 11] Input [7]: [cs_sold_time_sk#169, cs_ship_mode_sk#170, cs_warehouse_sk#171, cs_quantity#172, cs_sales_price#173, cs_net_paid_inc_tax#174, cs_sold_date_sk#175] -Condition : ((isnotnull(cs_warehouse_sk#171) AND isnotnull(cs_sold_time_sk#169)) AND isnotnull(cs_ship_mode_sk#170)) (33) ReusedExchange [Reuses operator id: 7] Output [7]: [w_warehouse_sk#177, w_warehouse_name#178, w_warehouse_sq_ft#179, w_city#180, w_county#181, w_state#182, w_country#183] @@ -304,8 +304,8 @@ Arguments: 100, [w_warehouse_name#10 ASC NULLS FIRST], [w_warehouse_name#10, w_w Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (56) -+- * Filter (55) - +- * ColumnarToRow (54) ++- * ColumnarToRow (55) + +- CometFilter (54) +- CometScan parquet spark_catalog.default.date_dim (53) @@ -316,12 +316,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(54) ColumnarToRow [codegen id : 1] +(54) CometFilter Input [3]: [d_date_sk#16, d_year#17, d_moy#18] +Condition : ((isnotnull(d_year#17) AND (d_year#17 = 2001)) AND isnotnull(d_date_sk#16)) -(55) Filter [codegen id : 1] +(55) ColumnarToRow [codegen id : 1] Input [3]: [d_date_sk#16, d_year#17, d_moy#18] -Condition : ((isnotnull(d_year#17) AND (d_year#17 = 2001)) AND isnotnull(d_date_sk#16)) (56) BroadcastExchange Input [3]: [d_date_sk#16, d_year#17, d_moy#18] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/simplified.txt index 4c2daaa3e..8ed74582f 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q66/simplified.txt @@ -21,41 +21,41 @@ TakeOrderedAndProject [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_stat BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_sold_time_sk,ws_ship_mode_sk,ws_quantity,ws_ext_sales_price,ws_net_paid,ws_sold_date_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] BroadcastHashJoin [ws_warehouse_sk,w_warehouse_sk] - Filter [ws_warehouse_sk,ws_sold_time_sk,ws_ship_mode_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_warehouse_sk,ws_sold_time_sk,ws_ship_mode_sk] CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_ship_mode_sk,ws_warehouse_sk,ws_quantity,ws_ext_sales_price,ws_net_paid,ws_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] InputAdapter ReusedExchange [d_date_sk,d_year,d_moy] #3 InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Project [t_time_sk] - Filter [t_time,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_time,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_time] InputAdapter BroadcastExchange #6 WholeStageCodegen (4) - Project [sm_ship_mode_sk] - Filter [sm_carrier,sm_ship_mode_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sm_ship_mode_sk] + CometFilter [sm_carrier,sm_ship_mode_sk] CometScan parquet spark_catalog.default.ship_mode [sm_ship_mode_sk,sm_carrier] WholeStageCodegen (12) HashAggregate [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country,d_year,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(CASE WHEN (d_moy = 1) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 2) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 3) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 4) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 5) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 6) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 7) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 8) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 9) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 10) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 11) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 12) THEN (cs_sales_price * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 1) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 2) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 3) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 4) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 5) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 6) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 7) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 8) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 9) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 10) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 11) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),sum(CASE WHEN (d_moy = 12) THEN (cs_net_paid_inc_tax * cast(cs_quantity as decimal(10,0))) ELSE 0.00 END),ship_carriers,year,jan_sales,feb_sales,mar_sales,apr_sales,may_sales,jun_sales,jul_sales,aug_sales,sep_sales,oct_sales,nov_sales,dec_sales,jan_net,feb_net,mar_net,apr_net,may_net,jun_net,jul_net,aug_net,sep_net,oct_net,nov_net,dec_net,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] @@ -71,9 +71,9 @@ TakeOrderedAndProject [w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_stat BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_sold_time_sk,cs_ship_mode_sk,cs_quantity,cs_sales_price,cs_net_paid_inc_tax,cs_sold_date_sk,w_warehouse_name,w_warehouse_sq_ft,w_city,w_county,w_state,w_country] BroadcastHashJoin [cs_warehouse_sk,w_warehouse_sk] - Filter [cs_warehouse_sk,cs_sold_time_sk,cs_ship_mode_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_warehouse_sk,cs_sold_time_sk,cs_ship_mode_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_sold_time_sk,cs_ship_mode_sk,cs_warehouse_sk,cs_quantity,cs_sales_price,cs_net_paid_inc_tax,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/explain.txt index 192e065e5..d1a6a4f47 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/explain.txt @@ -17,17 +17,17 @@ TakeOrderedAndProject (30) : +- * BroadcastHashJoin Inner BuildRight (11) : :- * Project (6) : : +- * BroadcastHashJoin Inner BuildRight (5) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : +- ReusedExchange (4) : +- BroadcastExchange (10) - : +- * Filter (9) - : +- * ColumnarToRow (8) + : +- * ColumnarToRow (9) + : +- CometFilter (8) : +- CometScan parquet spark_catalog.default.store (7) +- BroadcastExchange (16) - +- * Filter (15) - +- * ColumnarToRow (14) + +- * ColumnarToRow (15) + +- CometFilter (14) +- CometScan parquet spark_catalog.default.item (13) @@ -39,12 +39,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] -Condition : (isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) (4) ReusedExchange [Reuses operator id: 35] Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] @@ -66,12 +66,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [2]: [s_store_sk#11, s_store_id#12] +Condition : isnotnull(s_store_sk#11) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [2]: [s_store_sk#11, s_store_id#12] -Condition : isnotnull(s_store_sk#11) (10) BroadcastExchange Input [2]: [s_store_sk#11, s_store_id#12] @@ -94,12 +94,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Condition : isnotnull(i_item_sk#13) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] -Condition : isnotnull(i_item_sk#13) (16) BroadcastExchange Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] @@ -173,9 +173,9 @@ Arguments: 100, [i_category#18 ASC NULLS FIRST, i_class#19 ASC NULLS FIRST, i_br Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (35) -+- * Project (34) - +- * Filter (33) - +- * ColumnarToRow (32) ++- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) +- CometScan parquet spark_catalog.default.date_dim (31) @@ -186,16 +186,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(32) ColumnarToRow [codegen id : 1] -Input [5]: [d_date_sk#7, d_month_seq#34, d_year#8, d_moy#9, d_qoy#10] - -(33) Filter [codegen id : 1] +(32) CometFilter Input [5]: [d_date_sk#7, d_month_seq#34, d_year#8, d_moy#9, d_qoy#10] Condition : (((isnotnull(d_month_seq#34) AND (d_month_seq#34 >= 1200)) AND (d_month_seq#34 <= 1211)) AND isnotnull(d_date_sk#7)) -(34) Project [codegen id : 1] -Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] +(33) CometProject Input [5]: [d_date_sk#7, d_month_seq#34, d_year#8, d_moy#9, d_qoy#10] +Arguments: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10], [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(34) ColumnarToRow [codegen id : 1] +Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] (35) BroadcastExchange Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/simplified.txt index ecc706b76..e10def397 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q67/simplified.txt @@ -23,31 +23,31 @@ TakeOrderedAndProject [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_ BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,d_year,d_moy,d_qoy] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk,d_year,d_moy,d_qoy] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_year,d_moy,d_qoy] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_year,d_moy,d_qoy] InputAdapter ReusedExchange [d_date_sk,d_year,d_moy,d_qoy] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/explain.txt index 48b46fab5..734b6c11c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/explain.txt @@ -15,27 +15,27 @@ TakeOrderedAndProject (39) : : : : +- * BroadcastHashJoin Inner BuildRight (12) : : : : :- * Project (6) : : : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : : : :- * Filter (3) - : : : : : : +- * ColumnarToRow (2) + : : : : : :- * ColumnarToRow (3) + : : : : : : +- CometFilter (2) : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : : +- ReusedExchange (4) : : : : +- BroadcastExchange (11) - : : : : +- * Project (10) - : : : : +- * Filter (9) - : : : : +- * ColumnarToRow (8) + : : : : +- * ColumnarToRow (10) + : : : : +- CometProject (9) + : : : : +- CometFilter (8) : : : : +- CometScan parquet spark_catalog.default.store (7) : : : +- BroadcastExchange (18) - : : : +- * Project (17) - : : : +- * Filter (16) - : : : +- * ColumnarToRow (15) + : : : +- * ColumnarToRow (17) + : : : +- CometProject (16) + : : : +- CometFilter (15) : : : +- CometScan parquet spark_catalog.default.household_demographics (14) : : +- BroadcastExchange (24) - : : +- * Filter (23) - : : +- * ColumnarToRow (22) + : : +- * ColumnarToRow (23) + : : +- CometFilter (22) : : +- CometScan parquet spark_catalog.default.customer_address (21) : +- BroadcastExchange (33) - : +- * Filter (32) - : +- * ColumnarToRow (31) + : +- * ColumnarToRow (32) + : +- CometFilter (31) : +- CometScan parquet spark_catalog.default.customer (30) +- ReusedExchange (36) @@ -48,12 +48,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#9), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ss_sold_date_sk#9] +Condition : (((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_customer_sk#1)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_ext_sales_price#6, ss_ext_list_price#7, ss_ext_tax#8, ss_sold_date_sk#9] -Condition : (((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_customer_sk#1)) (4) ReusedExchange [Reuses operator id: 44] Output [1]: [d_date_sk#11] @@ -75,16 +75,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [In(s_city, [Fairview,Midway]), IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] -Input [2]: [s_store_sk#12, s_city#13] - -(9) Filter [codegen id : 2] +(8) CometFilter Input [2]: [s_store_sk#12, s_city#13] Condition : (s_city#13 IN (Midway,Fairview) AND isnotnull(s_store_sk#12)) -(10) Project [codegen id : 2] -Output [1]: [s_store_sk#12] +(9) CometProject Input [2]: [s_store_sk#12, s_city#13] +Arguments: [s_store_sk#12], [s_store_sk#12] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#12] (11) BroadcastExchange Input [1]: [s_store_sk#12] @@ -107,16 +107,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [Or(EqualTo(hd_dep_count,4),EqualTo(hd_vehicle_count,3)), IsNotNull(hd_demo_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] -Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] - -(16) Filter [codegen id : 3] +(15) CometFilter Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] Condition : (((hd_dep_count#15 = 4) OR (hd_vehicle_count#16 = 3)) AND isnotnull(hd_demo_sk#14)) -(17) Project [codegen id : 3] -Output [1]: [hd_demo_sk#14] +(16) CometProject Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Arguments: [hd_demo_sk#14], [hd_demo_sk#14] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#14] (18) BroadcastExchange Input [1]: [hd_demo_sk#14] @@ -139,12 +139,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_city)] ReadSchema: struct -(22) ColumnarToRow [codegen id : 4] +(22) CometFilter Input [2]: [ca_address_sk#17, ca_city#18] +Condition : (isnotnull(ca_address_sk#17) AND isnotnull(ca_city#18)) -(23) Filter [codegen id : 4] +(23) ColumnarToRow [codegen id : 4] Input [2]: [ca_address_sk#17, ca_city#18] -Condition : (isnotnull(ca_address_sk#17) AND isnotnull(ca_city#18)) (24) BroadcastExchange Input [2]: [ca_address_sk#17, ca_city#18] @@ -185,12 +185,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 6] +(31) CometFilter Input [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] +Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_current_addr_sk#33)) -(32) Filter [codegen id : 6] +(32) ColumnarToRow [codegen id : 6] Input [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] -Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_current_addr_sk#33)) (33) BroadcastExchange Input [4]: [c_customer_sk#32, c_current_addr_sk#33, c_first_name#34, c_last_name#35] @@ -227,9 +227,9 @@ Arguments: 100, [c_last_name#35 ASC NULLS FIRST, ss_ticket_number#5 ASC NULLS FI Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#9 IN dynamicpruning#10 BroadcastExchange (44) -+- * Project (43) - +- * Filter (42) - +- * ColumnarToRow (41) ++- * ColumnarToRow (43) + +- CometProject (42) + +- CometFilter (41) +- CometScan parquet spark_catalog.default.date_dim (40) @@ -240,16 +240,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_dom), GreaterThanOrEqual(d_dom,1), LessThanOrEqual(d_dom,2), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] ReadSchema: struct -(41) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#11, d_year#38, d_dom#39] - -(42) Filter [codegen id : 1] +(41) CometFilter Input [3]: [d_date_sk#11, d_year#38, d_dom#39] Condition : ((((isnotnull(d_dom#39) AND (d_dom#39 >= 1)) AND (d_dom#39 <= 2)) AND d_year#38 IN (1999,2000,2001)) AND isnotnull(d_date_sk#11)) -(43) Project [codegen id : 1] -Output [1]: [d_date_sk#11] +(42) CometProject Input [3]: [d_date_sk#11, d_year#38, d_dom#39] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(43) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] (44) BroadcastExchange Input [1]: [d_date_sk#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/simplified.txt index 20d9432d1..f2680bebb 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q68/simplified.txt @@ -17,49 +17,49 @@ TakeOrderedAndProject [c_last_name,ss_ticket_number,c_first_name,ca_city,bought_ BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk,ss_hdemo_sk,ss_addr_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_addr_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_ext_sales_price,ss_ext_list_price,ss_ext_tax,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_dom,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dom,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [s_store_sk] - Filter [s_city,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_city,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_city] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Project [hd_demo_sk] - Filter [hd_dep_count,hd_vehicle_count,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_vehicle_count,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Filter [ca_address_sk,ca_city] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_city] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city] InputAdapter BroadcastExchange #6 WholeStageCodegen (6) - Filter [c_customer_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name] InputAdapter ReusedExchange [ca_address_sk,ca_city] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/explain.txt index 522bd93e5..d56b01d73 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/explain.txt @@ -11,8 +11,8 @@ TakeOrderedAndProject (42) : : +- * BroadcastHashJoin LeftAnti BuildRight (24) : : :- * BroadcastHashJoin LeftAnti BuildRight (17) : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : : +- BroadcastExchange (9) : : : : +- * Project (8) @@ -33,13 +33,13 @@ TakeOrderedAndProject (42) : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) : : +- ReusedExchange (20) : +- BroadcastExchange (30) - : +- * Project (29) - : +- * Filter (28) - : +- * ColumnarToRow (27) + : +- * ColumnarToRow (29) + : +- CometProject (28) + : +- CometFilter (27) : +- CometScan parquet spark_catalog.default.customer_address (26) +- BroadcastExchange (36) - +- * Filter (35) - +- * ColumnarToRow (34) + +- * ColumnarToRow (35) + +- CometFilter (34) +- CometScan parquet spark_catalog.default.customer_demographics (33) @@ -50,12 +50,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 9] +(2) CometFilter Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) -(3) Filter [codegen id : 9] +(3) ColumnarToRow [codegen id : 9] Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] -Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) (4) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_customer_sk#4, ss_sold_date_sk#5] @@ -167,16 +167,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [In(ca_state, [GA,KY,NM]), IsNotNull(ca_address_sk)] ReadSchema: struct -(27) ColumnarToRow [codegen id : 7] -Input [2]: [ca_address_sk#16, ca_state#17] - -(28) Filter [codegen id : 7] +(27) CometFilter Input [2]: [ca_address_sk#16, ca_state#17] Condition : (ca_state#17 IN (KY,GA,NM) AND isnotnull(ca_address_sk#16)) -(29) Project [codegen id : 7] -Output [1]: [ca_address_sk#16] +(28) CometProject Input [2]: [ca_address_sk#16, ca_state#17] +Arguments: [ca_address_sk#16], [ca_address_sk#16] + +(29) ColumnarToRow [codegen id : 7] +Input [1]: [ca_address_sk#16] (30) BroadcastExchange Input [1]: [ca_address_sk#16] @@ -199,12 +199,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk)] ReadSchema: struct -(34) ColumnarToRow [codegen id : 8] +(34) CometFilter Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] +Condition : isnotnull(cd_demo_sk#18) -(35) Filter [codegen id : 8] +(35) ColumnarToRow [codegen id : 8] Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] -Condition : isnotnull(cd_demo_sk#18) (36) BroadcastExchange Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_education_status#21, cd_purchase_estimate#22, cd_credit_rating#23] @@ -246,9 +246,9 @@ Arguments: 100, [cd_gender#19 ASC NULLS FIRST, cd_marital_status#20 ASC NULLS FI Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (47) -+- * Project (46) - +- * Filter (45) - +- * ColumnarToRow (44) ++- * ColumnarToRow (46) + +- CometProject (45) + +- CometFilter (44) +- CometScan parquet spark_catalog.default.date_dim (43) @@ -259,16 +259,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), GreaterThanOrEqual(d_moy,4), LessThanOrEqual(d_moy,6), IsNotNull(d_date_sk)] ReadSchema: struct -(44) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#7, d_year#30, d_moy#31] - -(45) Filter [codegen id : 1] +(44) CometFilter Input [3]: [d_date_sk#7, d_year#30, d_moy#31] Condition : (((((isnotnull(d_year#30) AND isnotnull(d_moy#31)) AND (d_year#30 = 2001)) AND (d_moy#31 >= 4)) AND (d_moy#31 <= 6)) AND isnotnull(d_date_sk#7)) -(46) Project [codegen id : 1] -Output [1]: [d_date_sk#7] +(45) CometProject Input [3]: [d_date_sk#7, d_year#30, d_moy#31] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(46) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] (47) BroadcastExchange Input [1]: [d_date_sk#7] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/simplified.txt index 90f6fc876..f5b4eccfb 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q69/simplified.txt @@ -13,9 +13,9 @@ TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purcha BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_current_addr_sk,c_current_cdemo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] InputAdapter BroadcastExchange #2 @@ -28,10 +28,10 @@ TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purcha SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk] #3 @@ -60,15 +60,15 @@ TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purcha InputAdapter BroadcastExchange #6 WholeStageCodegen (7) - Project [ca_address_sk] - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #7 WholeStageCodegen (8) - Filter [cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/explain.txt index 47e7253dd..790a917e3 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/explain.txt @@ -11,23 +11,23 @@ TakeOrderedAndProject (30) : : +- * BroadcastHashJoin Inner BuildRight (12) : : :- * Project (10) : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- BroadcastExchange (8) - : : : +- * Project (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (7) + : : : +- CometProject (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) : : +- ReusedExchange (11) : +- BroadcastExchange (17) - : +- * Filter (16) - : +- * ColumnarToRow (15) + : +- * ColumnarToRow (16) + : +- CometFilter (15) : +- CometScan parquet spark_catalog.default.item (14) +- BroadcastExchange (24) - +- * Project (23) - +- * Filter (22) - +- * ColumnarToRow (21) + +- * ColumnarToRow (23) + +- CometProject (22) + +- CometFilter (21) +- CometScan parquet spark_catalog.default.promotion (20) @@ -39,12 +39,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_item_sk), IsNotNull(ss_promo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] -Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) (4) Scan parquet spark_catalog.default.customer_demographics Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] @@ -53,16 +53,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#10)) -(7) Project [codegen id : 1] -Output [1]: [cd_demo_sk#10] +(6) CometProject Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Arguments: [cd_demo_sk#10], [cd_demo_sk#10] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [cd_demo_sk#10] (8) BroadcastExchange Input [1]: [cd_demo_sk#10] @@ -98,12 +98,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] +(15) CometFilter Input [2]: [i_item_sk#15, i_item_id#16] +Condition : isnotnull(i_item_sk#15) -(16) Filter [codegen id : 3] +(16) ColumnarToRow [codegen id : 3] Input [2]: [i_item_sk#15, i_item_id#16] -Condition : isnotnull(i_item_sk#15) (17) BroadcastExchange Input [2]: [i_item_sk#15, i_item_id#16] @@ -126,16 +126,16 @@ Location [not included in comparison]/{warehouse_dir}/promotion] PushedFilters: [Or(EqualTo(p_channel_email,N),EqualTo(p_channel_event,N)), IsNotNull(p_promo_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] -Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] - -(22) Filter [codegen id : 4] +(21) CometFilter Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] Condition : (((p_channel_email#18 = N) OR (p_channel_event#19 = N)) AND isnotnull(p_promo_sk#17)) -(23) Project [codegen id : 4] -Output [1]: [p_promo_sk#17] +(22) CometProject Input [3]: [p_promo_sk#17, p_channel_email#18, p_channel_event#19] +Arguments: [p_promo_sk#17], [p_promo_sk#17] + +(23) ColumnarToRow [codegen id : 4] +Input [1]: [p_promo_sk#17] (24) BroadcastExchange Input [1]: [p_promo_sk#17] @@ -177,9 +177,9 @@ Arguments: 100, [i_item_id#16 ASC NULLS FIRST], [i_item_id#16, agg1#40, agg2#41, Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (35) -+- * Project (34) - +- * Filter (33) - +- * ColumnarToRow (32) ++- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) +- CometScan parquet spark_catalog.default.date_dim (31) @@ -190,16 +190,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(32) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#14, d_year#44] - -(33) Filter [codegen id : 1] +(32) CometFilter Input [2]: [d_date_sk#14, d_year#44] Condition : ((isnotnull(d_year#44) AND (d_year#44 = 2000)) AND isnotnull(d_date_sk#14)) -(34) Project [codegen id : 1] -Output [1]: [d_date_sk#14] +(33) CometProject Input [2]: [d_date_sk#14, d_year#44] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(34) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] (35) BroadcastExchange Input [1]: [d_date_sk#14] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/simplified.txt index c09f5ad55..2471de20a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q7/simplified.txt @@ -13,40 +13,40 @@ TakeOrderedAndProject [i_item_id,agg1,agg2,agg3,agg4] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_item_sk,ss_promo_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] - Filter [ss_cdemo_sk,ss_item_sk,ss_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_cdemo_sk,ss_item_sk,ss_promo_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_promo_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [cd_demo_sk] - Filter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Project [p_promo_sk] - Filter [p_channel_email,p_channel_event,p_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [p_promo_sk] + CometFilter [p_channel_email,p_channel_event,p_promo_sk] CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_email,p_channel_event] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/explain.txt index f96ee1932..c3acf0a8d 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/explain.txt @@ -12,14 +12,14 @@ TakeOrderedAndProject (43) +- * BroadcastHashJoin Inner BuildRight (33) :- * Project (6) : +- * BroadcastHashJoin Inner BuildRight (5) - : :- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.store_sales (1) : +- ReusedExchange (4) +- BroadcastExchange (32) +- * BroadcastHashJoin LeftSemi BuildRight (31) - :- * Filter (9) - : +- * ColumnarToRow (8) + :- * ColumnarToRow (9) + : +- CometFilter (8) : +- CometScan parquet spark_catalog.default.store (7) +- BroadcastExchange (30) +- * Project (29) @@ -34,12 +34,12 @@ TakeOrderedAndProject (43) +- * BroadcastHashJoin Inner BuildRight (20) :- * Project (18) : +- * BroadcastHashJoin Inner BuildRight (17) - : :- * Filter (12) - : : +- * ColumnarToRow (11) + : :- * ColumnarToRow (12) + : : +- CometFilter (11) : : +- CometScan parquet spark_catalog.default.store_sales (10) : +- BroadcastExchange (16) - : +- * Filter (15) - : +- * ColumnarToRow (14) + : +- * ColumnarToRow (15) + : +- CometFilter (14) : +- CometScan parquet spark_catalog.default.store (13) +- ReusedExchange (19) @@ -52,12 +52,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 8] +(2) CometFilter Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) -(3) Filter [codegen id : 8] +(3) ColumnarToRow [codegen id : 8] Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] -Condition : isnotnull(ss_store_sk#1) (4) ReusedExchange [Reuses operator id: 48] Output [1]: [d_date_sk#5] @@ -79,12 +79,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 7] +(8) CometFilter Input [3]: [s_store_sk#6, s_county#7, s_state#8] +Condition : isnotnull(s_store_sk#6) -(9) Filter [codegen id : 7] +(9) ColumnarToRow [codegen id : 7] Input [3]: [s_store_sk#6, s_county#7, s_state#8] -Condition : isnotnull(s_store_sk#6) (10) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] @@ -94,12 +94,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 4] +(11) CometFilter Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_store_sk#9) -(12) Filter [codegen id : 4] +(12) ColumnarToRow [codegen id : 4] Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] -Condition : isnotnull(ss_store_sk#9) (13) Scan parquet spark_catalog.default.store Output [2]: [s_store_sk#13, s_state#14] @@ -108,12 +108,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 2] +(14) CometFilter Input [2]: [s_store_sk#13, s_state#14] +Condition : isnotnull(s_store_sk#13) -(15) Filter [codegen id : 2] +(15) ColumnarToRow [codegen id : 2] Input [2]: [s_store_sk#13, s_state#14] -Condition : isnotnull(s_store_sk#13) (16) BroadcastExchange Input [2]: [s_store_sk#13, s_state#14] @@ -250,9 +250,9 @@ Arguments: 100, [lochierarchy#28 DESC NULLS LAST, CASE WHEN (lochierarchy#28 = 0 Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (48) -+- * Project (47) - +- * Filter (46) - +- * ColumnarToRow (45) ++- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) +- CometScan parquet spark_catalog.default.date_dim (44) @@ -263,16 +263,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#5, d_month_seq#33] - -(46) Filter [codegen id : 1] +(45) CometFilter Input [2]: [d_date_sk#5, d_month_seq#33] Condition : (((isnotnull(d_month_seq#33) AND (d_month_seq#33 >= 1200)) AND (d_month_seq#33 <= 1211)) AND isnotnull(d_date_sk#5)) -(47) Project [codegen id : 1] -Output [1]: [d_date_sk#5] +(46) CometProject Input [2]: [d_date_sk#5, d_month_seq#33] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(47) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] (48) BroadcastExchange Input [1]: [d_date_sk#5] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/simplified.txt index a15af5f94..268af2e2f 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q70/simplified.txt @@ -18,17 +18,17 @@ TakeOrderedAndProject [lochierarchy,s_state,rank_within_parent,total_sum,s_count BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_store_sk,ss_net_profit] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] InputAdapter ReusedExchange [d_date_sk] #3 @@ -36,9 +36,9 @@ TakeOrderedAndProject [lochierarchy,s_state,rank_within_parent,total_sum,s_count BroadcastExchange #4 WholeStageCodegen (7) BroadcastHashJoin [s_state,s_state] - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_county,s_state] InputAdapter BroadcastExchange #5 @@ -59,17 +59,17 @@ TakeOrderedAndProject [lochierarchy,s_state,rank_within_parent,total_sum,s_count BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_net_profit,ss_sold_date_sk,s_state] BroadcastHashJoin [ss_store_sk,s_store_sk] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter BroadcastExchange #7 WholeStageCodegen (2) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_state] InputAdapter ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/explain.txt index 8bf7d4c97..624103b66 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/explain.txt @@ -9,33 +9,33 @@ :- * Project (26) : +- * BroadcastHashJoin Inner BuildLeft (25) : :- BroadcastExchange (5) - : : +- * Project (4) - : : +- * Filter (3) - : : +- * ColumnarToRow (2) + : : +- * ColumnarToRow (4) + : : +- CometProject (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.item (1) : +- Union (24) : :- * Project (11) : : +- * BroadcastHashJoin Inner BuildRight (10) - : : :- * Filter (8) - : : : +- * ColumnarToRow (7) + : : :- * ColumnarToRow (8) + : : : +- CometFilter (7) : : : +- CometScan parquet spark_catalog.default.web_sales (6) : : +- ReusedExchange (9) : :- * Project (17) : : +- * BroadcastHashJoin Inner BuildRight (16) - : : :- * Filter (14) - : : : +- * ColumnarToRow (13) + : : :- * ColumnarToRow (14) + : : : +- CometFilter (13) : : : +- CometScan parquet spark_catalog.default.catalog_sales (12) : : +- ReusedExchange (15) : +- * Project (23) : +- * BroadcastHashJoin Inner BuildRight (22) - : :- * Filter (20) - : : +- * ColumnarToRow (19) + : :- * ColumnarToRow (20) + : : +- CometFilter (19) : : +- CometScan parquet spark_catalog.default.store_sales (18) : +- ReusedExchange (21) +- BroadcastExchange (31) - +- * Project (30) - +- * Filter (29) - +- * ColumnarToRow (28) + +- * ColumnarToRow (30) + +- CometProject (29) + +- CometFilter (28) +- CometScan parquet spark_catalog.default.time_dim (27) @@ -46,16 +46,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_manager_id), EqualTo(i_manager_id,1), IsNotNull(i_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [4]: [i_item_sk#1, i_brand_id#2, i_brand#3, i_manager_id#4] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [4]: [i_item_sk#1, i_brand_id#2, i_brand#3, i_manager_id#4] Condition : ((isnotnull(i_manager_id#4) AND (i_manager_id#4 = 1)) AND isnotnull(i_item_sk#1)) -(4) Project [codegen id : 1] -Output [3]: [i_item_sk#1, i_brand_id#2, i_brand#3] +(3) CometProject Input [4]: [i_item_sk#1, i_brand_id#2, i_brand#3, i_manager_id#4] +Arguments: [i_item_sk#1, i_brand_id#2, i_brand#3], [i_item_sk#1, i_brand_id#2, i_brand#3] + +(4) ColumnarToRow [codegen id : 1] +Input [3]: [i_item_sk#1, i_brand_id#2, i_brand#3] (5) BroadcastExchange Input [3]: [i_item_sk#1, i_brand_id#2, i_brand#3] @@ -69,12 +69,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#8), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_sold_time_sk)] ReadSchema: struct -(7) ColumnarToRow [codegen id : 3] +(7) CometFilter Input [4]: [ws_sold_time_sk#5, ws_item_sk#6, ws_ext_sales_price#7, ws_sold_date_sk#8] +Condition : (isnotnull(ws_item_sk#6) AND isnotnull(ws_sold_time_sk#5)) -(8) Filter [codegen id : 3] +(8) ColumnarToRow [codegen id : 3] Input [4]: [ws_sold_time_sk#5, ws_item_sk#6, ws_ext_sales_price#7, ws_sold_date_sk#8] -Condition : (isnotnull(ws_item_sk#6) AND isnotnull(ws_sold_time_sk#5)) (9) ReusedExchange [Reuses operator id: 43] Output [1]: [d_date_sk#10] @@ -97,12 +97,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_sold_time_sk)] ReadSchema: struct -(13) ColumnarToRow [codegen id : 5] +(13) CometFilter Input [4]: [cs_sold_time_sk#14, cs_item_sk#15, cs_ext_sales_price#16, cs_sold_date_sk#17] +Condition : (isnotnull(cs_item_sk#15) AND isnotnull(cs_sold_time_sk#14)) -(14) Filter [codegen id : 5] +(14) ColumnarToRow [codegen id : 5] Input [4]: [cs_sold_time_sk#14, cs_item_sk#15, cs_ext_sales_price#16, cs_sold_date_sk#17] -Condition : (isnotnull(cs_item_sk#15) AND isnotnull(cs_sold_time_sk#14)) (15) ReusedExchange [Reuses operator id: 43] Output [1]: [d_date_sk#19] @@ -125,12 +125,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_sold_time_sk)] ReadSchema: struct -(19) ColumnarToRow [codegen id : 7] +(19) CometFilter Input [4]: [ss_sold_time_sk#23, ss_item_sk#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Condition : (isnotnull(ss_item_sk#24) AND isnotnull(ss_sold_time_sk#23)) -(20) Filter [codegen id : 7] +(20) ColumnarToRow [codegen id : 7] Input [4]: [ss_sold_time_sk#23, ss_item_sk#24, ss_ext_sales_price#25, ss_sold_date_sk#26] -Condition : (isnotnull(ss_item_sk#24) AND isnotnull(ss_sold_time_sk#23)) (21) ReusedExchange [Reuses operator id: 43] Output [1]: [d_date_sk#28] @@ -164,16 +164,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [Or(EqualTo(t_meal_time,breakfast ),EqualTo(t_meal_time,dinner )), IsNotNull(t_time_sk)] ReadSchema: struct -(28) ColumnarToRow [codegen id : 8] -Input [4]: [t_time_sk#32, t_hour#33, t_minute#34, t_meal_time#35] - -(29) Filter [codegen id : 8] +(28) CometFilter Input [4]: [t_time_sk#32, t_hour#33, t_minute#34, t_meal_time#35] Condition : (((t_meal_time#35 = breakfast ) OR (t_meal_time#35 = dinner )) AND isnotnull(t_time_sk#32)) -(30) Project [codegen id : 8] -Output [3]: [t_time_sk#32, t_hour#33, t_minute#34] +(29) CometProject Input [4]: [t_time_sk#32, t_hour#33, t_minute#34, t_meal_time#35] +Arguments: [t_time_sk#32, t_hour#33, t_minute#34], [t_time_sk#32, t_hour#33, t_minute#34] + +(30) ColumnarToRow [codegen id : 8] +Input [3]: [t_time_sk#32, t_hour#33, t_minute#34] (31) BroadcastExchange Input [3]: [t_time_sk#32, t_hour#33, t_minute#34] @@ -219,9 +219,9 @@ Arguments: [ext_price#41 DESC NULLS LAST, brand_id#39 ASC NULLS FIRST], true, 0 Subquery:1 Hosting operator id = 6 Hosting Expression = ws_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (43) -+- * Project (42) - +- * Filter (41) - +- * ColumnarToRow (40) ++- * ColumnarToRow (42) + +- CometProject (41) + +- CometFilter (40) +- CometScan parquet spark_catalog.default.date_dim (39) @@ -232,16 +232,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,11), EqualTo(d_year,1999), IsNotNull(d_date_sk)] ReadSchema: struct -(40) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#10, d_year#42, d_moy#43] - -(41) Filter [codegen id : 1] +(40) CometFilter Input [3]: [d_date_sk#10, d_year#42, d_moy#43] Condition : ((((isnotnull(d_moy#43) AND isnotnull(d_year#42)) AND (d_moy#43 = 11)) AND (d_year#42 = 1999)) AND isnotnull(d_date_sk#10)) -(42) Project [codegen id : 1] -Output [1]: [d_date_sk#10] +(41) CometProject Input [3]: [d_date_sk#10, d_year#42, d_moy#43] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(42) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] (43) BroadcastExchange Input [1]: [d_date_sk#10] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/simplified.txt index c47e3e146..bea5376a0 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q71/simplified.txt @@ -15,36 +15,36 @@ WholeStageCodegen (11) InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [i_item_sk,i_brand_id,i_brand] - Filter [i_manager_id,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_brand] + CometFilter [i_manager_id,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_brand,i_manager_id] InputAdapter Union WholeStageCodegen (3) Project [ws_ext_sales_price,ws_item_sk,ws_sold_time_sk] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_item_sk,ws_sold_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk,ws_sold_time_sk] CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_moy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_moy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk] #4 WholeStageCodegen (5) Project [cs_ext_sales_price,cs_item_sk,cs_sold_time_sk] BroadcastHashJoin [cs_sold_date_sk,d_date_sk] - Filter [cs_item_sk,cs_sold_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_sold_time_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_sold_time_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -52,9 +52,9 @@ WholeStageCodegen (11) WholeStageCodegen (7) Project [ss_ext_sales_price,ss_item_sk,ss_sold_time_sk] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_item_sk,ss_sold_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_sold_time_sk] CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -62,8 +62,8 @@ WholeStageCodegen (11) InputAdapter BroadcastExchange #5 WholeStageCodegen (8) - Project [t_time_sk,t_hour,t_minute] - Filter [t_meal_time,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk,t_hour,t_minute] + CometFilter [t_meal_time,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute,t_meal_time] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/explain.txt index 35cc300bf..4e5d9e9f6 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/explain.txt @@ -25,49 +25,49 @@ TakeOrderedAndProject (70) : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (14) : : : : : : : : :- * Project (9) : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : : : : : : :- * Filter (3) - : : : : : : : : : : +- * ColumnarToRow (2) + : : : : : : : : : :- * ColumnarToRow (3) + : : : : : : : : : : +- CometFilter (2) : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : : : : : : : +- BroadcastExchange (7) - : : : : : : : : : +- * Filter (6) - : : : : : : : : : +- * ColumnarToRow (5) + : : : : : : : : : +- * ColumnarToRow (6) + : : : : : : : : : +- CometFilter (5) : : : : : : : : : +- CometScan parquet spark_catalog.default.inventory (4) : : : : : : : : +- BroadcastExchange (13) - : : : : : : : : +- * Filter (12) - : : : : : : : : +- * ColumnarToRow (11) + : : : : : : : : +- * ColumnarToRow (12) + : : : : : : : : +- CometFilter (11) : : : : : : : : +- CometScan parquet spark_catalog.default.warehouse (10) : : : : : : : +- BroadcastExchange (19) - : : : : : : : +- * Filter (18) - : : : : : : : +- * ColumnarToRow (17) + : : : : : : : +- * ColumnarToRow (18) + : : : : : : : +- CometFilter (17) : : : : : : : +- CometScan parquet spark_catalog.default.item (16) : : : : : : +- BroadcastExchange (26) - : : : : : : +- * Project (25) - : : : : : : +- * Filter (24) - : : : : : : +- * ColumnarToRow (23) + : : : : : : +- * ColumnarToRow (25) + : : : : : : +- CometProject (24) + : : : : : : +- CometFilter (23) : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (22) : : : : : +- BroadcastExchange (33) - : : : : : +- * Project (32) - : : : : : +- * Filter (31) - : : : : : +- * ColumnarToRow (30) + : : : : : +- * ColumnarToRow (32) + : : : : : +- CometProject (31) + : : : : : +- CometFilter (30) : : : : : +- CometScan parquet spark_catalog.default.household_demographics (29) : : : : +- ReusedExchange (36) : : : +- BroadcastExchange (42) - : : : +- * Filter (41) - : : : +- * ColumnarToRow (40) + : : : +- * ColumnarToRow (41) + : : : +- CometFilter (40) : : : +- CometScan parquet spark_catalog.default.date_dim (39) : : +- BroadcastExchange (48) - : : +- * Filter (47) - : : +- * ColumnarToRow (46) + : : +- * ColumnarToRow (47) + : : +- CometFilter (46) : : +- CometScan parquet spark_catalog.default.date_dim (45) : +- BroadcastExchange (54) - : +- * Filter (53) - : +- * ColumnarToRow (52) + : +- * ColumnarToRow (53) + : +- CometFilter (52) : +- CometScan parquet spark_catalog.default.promotion (51) +- * Sort (64) +- Exchange (63) - +- * Project (62) - +- * Filter (61) - +- * ColumnarToRow (60) + +- * ColumnarToRow (62) + +- CometProject (61) + +- CometFilter (60) +- CometScan parquet spark_catalog.default.catalog_returns (59) @@ -79,12 +79,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#8), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_quantity), IsNotNull(cs_item_sk), IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_hdemo_sk), IsNotNull(cs_ship_date_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 10] +(2) CometFilter Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] +Condition : ((((isnotnull(cs_quantity#7) AND isnotnull(cs_item_sk#4)) AND isnotnull(cs_bill_cdemo_sk#2)) AND isnotnull(cs_bill_hdemo_sk#3)) AND isnotnull(cs_ship_date_sk#1)) -(3) Filter [codegen id : 10] +(3) ColumnarToRow [codegen id : 10] Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] -Condition : ((((isnotnull(cs_quantity#7) AND isnotnull(cs_item_sk#4)) AND isnotnull(cs_bill_cdemo_sk#2)) AND isnotnull(cs_bill_hdemo_sk#3)) AND isnotnull(cs_ship_date_sk#1)) (4) Scan parquet spark_catalog.default.inventory Output [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] @@ -94,12 +94,12 @@ PartitionFilters: [isnotnull(inv_date_sk#13)] PushedFilters: [IsNotNull(inv_quantity_on_hand), IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Condition : ((isnotnull(inv_quantity_on_hand#12) AND isnotnull(inv_item_sk#10)) AND isnotnull(inv_warehouse_sk#11)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] -Condition : ((isnotnull(inv_quantity_on_hand#12) AND isnotnull(inv_item_sk#10)) AND isnotnull(inv_warehouse_sk#11)) (7) BroadcastExchange Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] @@ -122,12 +122,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Condition : isnotnull(w_warehouse_sk#14) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] -Condition : isnotnull(w_warehouse_sk#14) (13) BroadcastExchange Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] @@ -150,12 +150,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 3] +(17) CometFilter Input [2]: [i_item_sk#16, i_item_desc#17] +Condition : isnotnull(i_item_sk#16) -(18) Filter [codegen id : 3] +(18) ColumnarToRow [codegen id : 3] Input [2]: [i_item_sk#16, i_item_desc#17] -Condition : isnotnull(i_item_sk#16) (19) BroadcastExchange Input [2]: [i_item_sk#16, i_item_desc#17] @@ -178,16 +178,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_marital_status), EqualTo(cd_marital_status,D), IsNotNull(cd_demo_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 4] -Input [2]: [cd_demo_sk#18, cd_marital_status#19] - -(24) Filter [codegen id : 4] +(23) CometFilter Input [2]: [cd_demo_sk#18, cd_marital_status#19] Condition : ((isnotnull(cd_marital_status#19) AND (cd_marital_status#19 = D)) AND isnotnull(cd_demo_sk#18)) -(25) Project [codegen id : 4] -Output [1]: [cd_demo_sk#18] +(24) CometProject Input [2]: [cd_demo_sk#18, cd_marital_status#19] +Arguments: [cd_demo_sk#18], [cd_demo_sk#18] + +(25) ColumnarToRow [codegen id : 4] +Input [1]: [cd_demo_sk#18] (26) BroadcastExchange Input [1]: [cd_demo_sk#18] @@ -210,16 +210,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_buy_potential), EqualTo(hd_buy_potential,>10000 ), IsNotNull(hd_demo_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 5] -Input [2]: [hd_demo_sk#20, hd_buy_potential#21] - -(31) Filter [codegen id : 5] +(30) CometFilter Input [2]: [hd_demo_sk#20, hd_buy_potential#21] Condition : ((isnotnull(hd_buy_potential#21) AND (hd_buy_potential#21 = >10000 )) AND isnotnull(hd_demo_sk#20)) -(32) Project [codegen id : 5] -Output [1]: [hd_demo_sk#20] +(31) CometProject Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Arguments: [hd_demo_sk#20], [hd_demo_sk#20] + +(32) ColumnarToRow [codegen id : 5] +Input [1]: [hd_demo_sk#20] (33) BroadcastExchange Input [1]: [hd_demo_sk#20] @@ -255,12 +255,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_week_seq), IsNotNull(d_date_sk)] ReadSchema: struct -(40) ColumnarToRow [codegen id : 7] +(40) CometFilter Input [2]: [d_date_sk#25, d_week_seq#26] +Condition : (isnotnull(d_week_seq#26) AND isnotnull(d_date_sk#25)) -(41) Filter [codegen id : 7] +(41) ColumnarToRow [codegen id : 7] Input [2]: [d_date_sk#25, d_week_seq#26] -Condition : (isnotnull(d_week_seq#26) AND isnotnull(d_date_sk#25)) (42) BroadcastExchange Input [2]: [d_date_sk#25, d_week_seq#26] @@ -283,12 +283,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), IsNotNull(d_date_sk)] ReadSchema: struct -(46) ColumnarToRow [codegen id : 8] +(46) CometFilter Input [2]: [d_date_sk#27, d_date#28] +Condition : (isnotnull(d_date#28) AND isnotnull(d_date_sk#27)) -(47) Filter [codegen id : 8] +(47) ColumnarToRow [codegen id : 8] Input [2]: [d_date_sk#27, d_date#28] -Condition : (isnotnull(d_date#28) AND isnotnull(d_date_sk#27)) (48) BroadcastExchange Input [2]: [d_date_sk#27, d_date#28] @@ -311,12 +311,12 @@ Location [not included in comparison]/{warehouse_dir}/promotion] PushedFilters: [IsNotNull(p_promo_sk)] ReadSchema: struct -(52) ColumnarToRow [codegen id : 9] +(52) CometFilter Input [1]: [p_promo_sk#29] +Condition : isnotnull(p_promo_sk#29) -(53) Filter [codegen id : 9] +(53) ColumnarToRow [codegen id : 9] Input [1]: [p_promo_sk#29] -Condition : isnotnull(p_promo_sk#29) (54) BroadcastExchange Input [1]: [p_promo_sk#29] @@ -347,16 +347,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] ReadSchema: struct -(60) ColumnarToRow [codegen id : 12] -Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] - -(61) Filter [codegen id : 12] +(60) CometFilter Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] Condition : (isnotnull(cr_item_sk#30) AND isnotnull(cr_order_number#31)) -(62) Project [codegen id : 12] -Output [2]: [cr_item_sk#30, cr_order_number#31] +(61) CometProject Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Arguments: [cr_item_sk#30, cr_order_number#31], [cr_item_sk#30, cr_order_number#31] + +(62) ColumnarToRow [codegen id : 12] +Input [2]: [cr_item_sk#30, cr_order_number#31] (63) Exchange Input [2]: [cr_item_sk#30, cr_order_number#31] @@ -402,9 +402,9 @@ Arguments: 100, [total_cnt#38 DESC NULLS LAST, i_item_desc#17 ASC NULLS FIRST, w Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (75) -+- * Project (74) - +- * Filter (73) - +- * ColumnarToRow (72) ++- * ColumnarToRow (74) + +- CometProject (73) + +- CometFilter (72) +- CometScan parquet spark_catalog.default.date_dim (71) @@ -415,16 +415,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk), IsNotNull(d_week_seq), IsNotNull(d_date)] ReadSchema: struct -(72) ColumnarToRow [codegen id : 1] -Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] - -(73) Filter [codegen id : 1] +(72) CometFilter Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] Condition : ((((isnotnull(d_year#39) AND (d_year#39 = 1999)) AND isnotnull(d_date_sk#22)) AND isnotnull(d_week_seq#24)) AND isnotnull(d_date#23)) -(74) Project [codegen id : 1] -Output [3]: [d_date_sk#22, d_date#23, d_week_seq#24] +(73) CometProject Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Arguments: [d_date_sk#22, d_date#23, d_week_seq#24], [d_date_sk#22, d_date#23, d_week_seq#24] + +(74) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24] (75) BroadcastExchange Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/simplified.txt index 59e1279ae..17fc9dee7 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q72/simplified.txt @@ -31,77 +31,77 @@ TakeOrderedAndProject [total_cnt,i_item_desc,w_warehouse_name,d_week_seq,no_prom BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_warehouse_sk,inv_date_sk] BroadcastHashJoin [cs_item_sk,inv_item_sk,inv_quantity_on_hand,cs_quantity] - Filter [cs_quantity,cs_item_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_ship_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_quantity,cs_item_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_ship_date_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_quantity,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk,d_date,d_week_seq] - Filter [d_year,d_date_sk,d_week_seq,d_date] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date,d_week_seq] + CometFilter [d_year,d_date_sk,d_week_seq,d_date] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_week_seq,d_year] InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Filter [inv_quantity_on_hand,inv_item_sk,inv_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [inv_quantity_on_hand,inv_item_sk,inv_warehouse_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (2) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] InputAdapter BroadcastExchange #6 WholeStageCodegen (3) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] InputAdapter BroadcastExchange #7 WholeStageCodegen (4) - Project [cd_demo_sk] - Filter [cd_marital_status,cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_marital_status,cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] InputAdapter BroadcastExchange #8 WholeStageCodegen (5) - Project [hd_demo_sk] - Filter [hd_buy_potential,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_buy_potential,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential] InputAdapter ReusedExchange [d_date_sk,d_date,d_week_seq] #3 InputAdapter BroadcastExchange #9 WholeStageCodegen (7) - Filter [d_week_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_week_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] InputAdapter BroadcastExchange #10 WholeStageCodegen (8) - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #11 WholeStageCodegen (9) - Filter [p_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [p_promo_sk] CometScan parquet spark_catalog.default.promotion [p_promo_sk] InputAdapter WholeStageCodegen (13) @@ -109,8 +109,8 @@ TakeOrderedAndProject [total_cnt,i_item_desc,w_warehouse_name,d_week_seq,no_prom InputAdapter Exchange [cr_item_sk,cr_order_number] #12 WholeStageCodegen (12) - Project [cr_item_sk,cr_order_number] - Filter [cr_item_sk,cr_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number] + CometFilter [cr_item_sk,cr_order_number] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/explain.txt index fb1ac906d..ef2c38aea 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/explain.txt @@ -13,23 +13,23 @@ : : +- * BroadcastHashJoin Inner BuildRight (12) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (11) - : : +- * Project (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.store (7) : +- BroadcastExchange (18) - : +- * Project (17) - : +- * Filter (16) - : +- * ColumnarToRow (15) + : +- * ColumnarToRow (17) + : +- CometProject (16) + : +- CometFilter (15) : +- CometScan parquet spark_catalog.default.household_demographics (14) +- BroadcastExchange (28) - +- * Filter (27) - +- * ColumnarToRow (26) + +- * ColumnarToRow (27) + +- CometFilter (26) +- CometScan parquet spark_catalog.default.customer (25) @@ -41,12 +41,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] -Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) (4) ReusedExchange [Reuses operator id: 37] Output [1]: [d_date_sk#7] @@ -68,16 +68,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [In(s_county, [Bronx County,Franklin Parish,Orange County,Williamson County]), IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] -Input [2]: [s_store_sk#8, s_county#9] - -(9) Filter [codegen id : 2] +(8) CometFilter Input [2]: [s_store_sk#8, s_county#9] Condition : (s_county#9 IN (Williamson County,Franklin Parish,Bronx County,Orange County) AND isnotnull(s_store_sk#8)) -(10) Project [codegen id : 2] -Output [1]: [s_store_sk#8] +(9) CometProject Input [2]: [s_store_sk#8, s_county#9] +Arguments: [s_store_sk#8], [s_store_sk#8] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#8] (11) BroadcastExchange Input [1]: [s_store_sk#8] @@ -100,16 +100,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_vehicle_count), Or(EqualTo(hd_buy_potential,>10000 ),EqualTo(hd_buy_potential,unknown )), GreaterThan(hd_vehicle_count,0), IsNotNull(hd_demo_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] -Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] - -(16) Filter [codegen id : 3] +(15) CometFilter Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] Condition : ((((isnotnull(hd_vehicle_count#13) AND ((hd_buy_potential#11 = >10000 ) OR (hd_buy_potential#11 = unknown ))) AND (hd_vehicle_count#13 > 0)) AND CASE WHEN (hd_vehicle_count#13 > 0) THEN ((cast(hd_dep_count#12 as double) / cast(hd_vehicle_count#13 as double)) > 1.0) END) AND isnotnull(hd_demo_sk#10)) -(17) Project [codegen id : 3] -Output [1]: [hd_demo_sk#10] +(16) CometProject Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Arguments: [hd_demo_sk#10], [hd_demo_sk#10] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#10] (18) BroadcastExchange Input [1]: [hd_demo_sk#10] @@ -154,12 +154,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 5] +(26) CometFilter Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Condition : isnotnull(c_customer_sk#18) -(27) Filter [codegen id : 5] +(27) ColumnarToRow [codegen id : 5] Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] -Condition : isnotnull(c_customer_sk#18) (28) BroadcastExchange Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] @@ -187,9 +187,9 @@ Arguments: [cnt#17 DESC NULLS LAST], true, 0 Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (37) -+- * Project (36) - +- * Filter (35) - +- * ColumnarToRow (34) ++- * ColumnarToRow (36) + +- CometProject (35) + +- CometFilter (34) +- CometScan parquet spark_catalog.default.date_dim (33) @@ -200,16 +200,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_dom), GreaterThanOrEqual(d_dom,1), LessThanOrEqual(d_dom,2), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] ReadSchema: struct -(34) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#7, d_year#23, d_dom#24] - -(35) Filter [codegen id : 1] +(34) CometFilter Input [3]: [d_date_sk#7, d_year#23, d_dom#24] Condition : ((((isnotnull(d_dom#24) AND (d_dom#24 >= 1)) AND (d_dom#24 <= 2)) AND d_year#23 IN (1999,2000,2001)) AND isnotnull(d_date_sk#7)) -(36) Project [codegen id : 1] -Output [1]: [d_date_sk#7] +(35) CometProject Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(36) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] (37) BroadcastExchange Input [1]: [d_date_sk#7] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/simplified.txt index a2c50bb62..7c5ee1ef5 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q73/simplified.txt @@ -17,40 +17,40 @@ WholeStageCodegen (7) BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_dom,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dom,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [s_store_sk] - Filter [s_county,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_county,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_county] InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Project [hd_demo_sk] - Filter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential,hd_dep_count,hd_vehicle_count] InputAdapter BroadcastExchange #6 WholeStageCodegen (5) - Filter [c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/explain.txt index 93c71adc4..dad94eb2c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/explain.txt @@ -13,12 +13,12 @@ TakeOrderedAndProject (71) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.store_sales (4) : : : +- ReusedExchange (10) : : +- BroadcastExchange (32) @@ -29,12 +29,12 @@ TakeOrderedAndProject (71) : : +- * BroadcastHashJoin Inner BuildRight (27) : : :- * Project (25) : : : +- * BroadcastHashJoin Inner BuildRight (24) - : : : :- * Filter (19) - : : : : +- * ColumnarToRow (18) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) : : : : +- CometScan parquet spark_catalog.default.customer (17) : : : +- BroadcastExchange (23) - : : : +- * Filter (22) - : : : +- * ColumnarToRow (21) + : : : +- * ColumnarToRow (22) + : : : +- CometFilter (21) : : : +- CometScan parquet spark_catalog.default.store_sales (20) : : +- ReusedExchange (26) : +- BroadcastExchange (50) @@ -46,12 +46,12 @@ TakeOrderedAndProject (71) : +- * BroadcastHashJoin Inner BuildRight (44) : :- * Project (42) : : +- * BroadcastHashJoin Inner BuildRight (41) - : : :- * Filter (36) - : : : +- * ColumnarToRow (35) + : : :- * ColumnarToRow (36) + : : : +- CometFilter (35) : : : +- CometScan parquet spark_catalog.default.customer (34) : : +- BroadcastExchange (40) - : : +- * Filter (39) - : : +- * ColumnarToRow (38) + : : +- * ColumnarToRow (39) + : : +- CometFilter (38) : : +- CometScan parquet spark_catalog.default.web_sales (37) : +- ReusedExchange (43) +- BroadcastExchange (68) @@ -62,12 +62,12 @@ TakeOrderedAndProject (71) +- * BroadcastHashJoin Inner BuildRight (63) :- * Project (61) : +- * BroadcastHashJoin Inner BuildRight (60) - : :- * Filter (55) - : : +- * ColumnarToRow (54) + : :- * ColumnarToRow (55) + : : +- CometFilter (54) : : +- CometScan parquet spark_catalog.default.customer (53) : +- BroadcastExchange (59) - : +- * Filter (58) - : +- * ColumnarToRow (57) + : +- * ColumnarToRow (58) + : +- CometFilter (57) : +- CometScan parquet spark_catalog.default.web_sales (56) +- ReusedExchange (62) @@ -79,12 +79,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] -Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) (4) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] @@ -94,12 +94,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Condition : isnotnull(ss_customer_sk#5) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] -Condition : isnotnull(ss_customer_sk#5) (7) BroadcastExchange Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] @@ -157,12 +157,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 6] +(18) CometFilter Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] +Condition : (isnotnull(c_customer_sk#16) AND isnotnull(c_customer_id#17)) -(19) Filter [codegen id : 6] +(19) ColumnarToRow [codegen id : 6] Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] -Condition : (isnotnull(c_customer_sk#16) AND isnotnull(c_customer_id#17)) (20) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] @@ -172,12 +172,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#22), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] +(21) CometFilter Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Condition : isnotnull(ss_customer_sk#20) -(22) Filter [codegen id : 4] +(22) ColumnarToRow [codegen id : 4] Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] -Condition : isnotnull(ss_customer_sk#20) (23) BroadcastExchange Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] @@ -241,12 +241,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 10] +(35) CometFilter Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] +Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_customer_id#33)) -(36) Filter [codegen id : 10] +(36) ColumnarToRow [codegen id : 10] Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] -Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_customer_id#33)) (37) Scan parquet spark_catalog.default.web_sales Output [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] @@ -256,12 +256,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#38), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(38) ColumnarToRow [codegen id : 8] +(38) CometFilter Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Condition : isnotnull(ws_bill_customer_sk#36) -(39) Filter [codegen id : 8] +(39) ColumnarToRow [codegen id : 8] Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] -Condition : isnotnull(ws_bill_customer_sk#36) (40) BroadcastExchange Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] @@ -333,12 +333,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(54) ColumnarToRow [codegen id : 14] +(54) CometFilter Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] +Condition : (isnotnull(c_customer_sk#47) AND isnotnull(c_customer_id#48)) -(55) Filter [codegen id : 14] +(55) ColumnarToRow [codegen id : 14] Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] -Condition : (isnotnull(c_customer_sk#47) AND isnotnull(c_customer_id#48)) (56) Scan parquet spark_catalog.default.web_sales Output [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] @@ -348,12 +348,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#53), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(57) ColumnarToRow [codegen id : 12] +(57) CometFilter Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Condition : isnotnull(ws_bill_customer_sk#51) -(58) Filter [codegen id : 12] +(58) ColumnarToRow [codegen id : 12] Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] -Condition : isnotnull(ws_bill_customer_sk#51) (59) BroadcastExchange Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] @@ -422,8 +422,8 @@ Arguments: 100, [customer_id#28 ASC NULLS FIRST, customer_id#28 ASC NULLS FIRST, Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (75) -+- * Filter (74) - +- * ColumnarToRow (73) ++- * ColumnarToRow (74) + +- CometFilter (73) +- CometScan parquet spark_catalog.default.date_dim (72) @@ -434,12 +434,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] ReadSchema: struct -(73) ColumnarToRow [codegen id : 1] +(73) CometFilter Input [2]: [d_date_sk#9, d_year#10] +Condition : (((isnotnull(d_year#10) AND (d_year#10 = 2001)) AND d_year#10 IN (2001,2002)) AND isnotnull(d_date_sk#9)) -(74) Filter [codegen id : 1] +(74) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#9, d_year#10] -Condition : (((isnotnull(d_year#10) AND (d_year#10 = 2001)) AND d_year#10 IN (2001,2002)) AND isnotnull(d_date_sk#9)) (75) BroadcastExchange Input [2]: [d_date_sk#9, d_year#10] @@ -447,8 +447,8 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint) Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#22 IN dynamicpruning#23 BroadcastExchange (79) -+- * Filter (78) - +- * ColumnarToRow (77) ++- * ColumnarToRow (78) + +- CometFilter (77) +- CometScan parquet spark_catalog.default.date_dim (76) @@ -459,12 +459,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] ReadSchema: struct -(77) ColumnarToRow [codegen id : 1] +(77) CometFilter Input [2]: [d_date_sk#24, d_year#25] +Condition : (((isnotnull(d_year#25) AND (d_year#25 = 2002)) AND d_year#25 IN (2001,2002)) AND isnotnull(d_date_sk#24)) -(78) Filter [codegen id : 1] +(78) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#24, d_year#25] -Condition : (((isnotnull(d_year#25) AND (d_year#25 = 2002)) AND d_year#25 IN (2001,2002)) AND isnotnull(d_date_sk#24)) (79) BroadcastExchange Input [2]: [d_date_sk#24, d_year#25] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/simplified.txt index e66974fba..9d3ae8fbe 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q74/simplified.txt @@ -15,23 +15,23 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #3 @@ -47,23 +47,23 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] InputAdapter BroadcastExchange #6 WholeStageCodegen (4) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #7 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #7 @@ -80,16 +80,16 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] InputAdapter BroadcastExchange #10 WholeStageCodegen (8) - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -106,16 +106,16 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] InputAdapter BroadcastExchange #13 WholeStageCodegen (12) - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/explain.txt index b18c8bbbf..a3d12a1d4 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/explain.txt @@ -20,20 +20,20 @@ TakeOrderedAndProject (129) : : : +- * BroadcastHashJoin Inner BuildRight (12) : : : :- * Project (10) : : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : : +- BroadcastExchange (8) - : : : : +- * Project (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (7) + : : : : +- CometProject (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.item (4) : : : +- ReusedExchange (11) : : +- * Sort (21) : : +- Exchange (20) - : : +- * Project (19) - : : +- * Filter (18) - : : +- * ColumnarToRow (17) + : : +- * ColumnarToRow (19) + : : +- CometProject (18) + : : +- CometFilter (17) : : +- CometScan parquet spark_catalog.default.catalog_returns (16) : :- * Project (42) : : +- * SortMergeJoin LeftOuter (41) @@ -43,16 +43,16 @@ TakeOrderedAndProject (129) : : : +- * BroadcastHashJoin Inner BuildRight (31) : : : :- * Project (29) : : : : +- * BroadcastHashJoin Inner BuildRight (28) - : : : : :- * Filter (26) - : : : : : +- * ColumnarToRow (25) + : : : : :- * ColumnarToRow (26) + : : : : : +- CometFilter (25) : : : : : +- CometScan parquet spark_catalog.default.store_sales (24) : : : : +- ReusedExchange (27) : : : +- ReusedExchange (30) : : +- * Sort (40) : : +- Exchange (39) - : : +- * Project (38) - : : +- * Filter (37) - : : +- * ColumnarToRow (36) + : : +- * ColumnarToRow (38) + : : +- CometProject (37) + : : +- CometFilter (36) : : +- CometScan parquet spark_catalog.default.store_returns (35) : +- * Project (61) : +- * SortMergeJoin LeftOuter (60) @@ -62,16 +62,16 @@ TakeOrderedAndProject (129) : : +- * BroadcastHashJoin Inner BuildRight (50) : : :- * Project (48) : : : +- * BroadcastHashJoin Inner BuildRight (47) - : : : :- * Filter (45) - : : : : +- * ColumnarToRow (44) + : : : :- * ColumnarToRow (45) + : : : : +- CometFilter (44) : : : : +- CometScan parquet spark_catalog.default.web_sales (43) : : : +- ReusedExchange (46) : : +- ReusedExchange (49) : +- * Sort (59) : +- Exchange (58) - : +- * Project (57) - : +- * Filter (56) - : +- * ColumnarToRow (55) + : +- * ColumnarToRow (57) + : +- CometProject (56) + : +- CometFilter (55) : +- CometScan parquet spark_catalog.default.web_returns (54) +- * Sort (126) +- Exchange (125) @@ -91,8 +91,8 @@ TakeOrderedAndProject (129) : : +- * BroadcastHashJoin Inner BuildRight (79) : : :- * Project (77) : : : +- * BroadcastHashJoin Inner BuildRight (76) - : : : :- * Filter (74) - : : : : +- * ColumnarToRow (73) + : : : :- * ColumnarToRow (74) + : : : : +- CometFilter (73) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (72) : : : +- ReusedExchange (75) : : +- ReusedExchange (78) @@ -106,8 +106,8 @@ TakeOrderedAndProject (129) : : +- * BroadcastHashJoin Inner BuildRight (94) : : :- * Project (92) : : : +- * BroadcastHashJoin Inner BuildRight (91) - : : : :- * Filter (89) - : : : : +- * ColumnarToRow (88) + : : : :- * ColumnarToRow (89) + : : : : +- CometFilter (88) : : : : +- CometScan parquet spark_catalog.default.store_sales (87) : : : +- ReusedExchange (90) : : +- ReusedExchange (93) @@ -121,8 +121,8 @@ TakeOrderedAndProject (129) : +- * BroadcastHashJoin Inner BuildRight (109) : :- * Project (107) : : +- * BroadcastHashJoin Inner BuildRight (106) - : : :- * Filter (104) - : : : +- * ColumnarToRow (103) + : : :- * ColumnarToRow (104) + : : : +- CometFilter (103) : : : +- CometScan parquet spark_catalog.default.web_sales (102) : : +- ReusedExchange (105) : +- ReusedExchange (108) @@ -138,12 +138,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] +Condition : isnotnull(cs_item_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] -Condition : isnotnull(cs_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] @@ -152,16 +152,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Books ), IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id), IsNotNull(i_manufact_id)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] Condition : ((((((isnotnull(i_category#11) AND (i_category#11 = Books )) AND isnotnull(i_item_sk#7)) AND isnotnull(i_brand_id#8)) AND isnotnull(i_class_id#9)) AND isnotnull(i_category_id#10)) AND isnotnull(i_manufact_id#12)) -(7) Project [codegen id : 1] -Output [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +(6) CometProject Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Arguments: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12], [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] + +(7) ColumnarToRow [codegen id : 1] +Input [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] (8) BroadcastExchange Input [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] @@ -205,16 +205,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 5] -Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] - -(18) Filter [codegen id : 5] +(17) CometFilter Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] Condition : (isnotnull(cr_order_number#16) AND isnotnull(cr_item_sk#15)) -(19) Project [codegen id : 5] -Output [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +(18) CometProject Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Arguments: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18], [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] + +(19) ColumnarToRow [codegen id : 5] +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] (20) Exchange Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] @@ -242,12 +242,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(25) ColumnarToRow [codegen id : 10] +(25) CometFilter Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Condition : isnotnull(ss_item_sk#22) -(26) Filter [codegen id : 10] +(26) ColumnarToRow [codegen id : 10] Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] -Condition : isnotnull(ss_item_sk#22) (27) ReusedExchange [Reuses operator id: 8] Output [5]: [i_item_sk#28, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] @@ -290,16 +290,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] ReadSchema: struct -(36) ColumnarToRow [codegen id : 12] -Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] - -(37) Filter [codegen id : 12] +(36) CometFilter Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] Condition : (isnotnull(sr_ticket_number#36) AND isnotnull(sr_item_sk#35)) -(38) Project [codegen id : 12] -Output [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +(37) CometProject Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Arguments: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38], [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] + +(38) ColumnarToRow [codegen id : 12] +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] (39) Exchange Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] @@ -327,12 +327,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#46), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(44) ColumnarToRow [codegen id : 17] +(44) CometFilter Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] +Condition : isnotnull(ws_item_sk#42) -(45) Filter [codegen id : 17] +(45) ColumnarToRow [codegen id : 17] Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] -Condition : isnotnull(ws_item_sk#42) (46) ReusedExchange [Reuses operator id: 8] Output [5]: [i_item_sk#48, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] @@ -375,16 +375,16 @@ Location [not included in comparison]/{warehouse_dir}/web_returns] PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] ReadSchema: struct -(55) ColumnarToRow [codegen id : 19] -Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] - -(56) Filter [codegen id : 19] +(55) CometFilter Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] Condition : (isnotnull(wr_order_number#56) AND isnotnull(wr_item_sk#55)) -(57) Project [codegen id : 19] -Output [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +(56) CometProject Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Arguments: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58], [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] + +(57) ColumnarToRow [codegen id : 19] +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] (58) Exchange Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] @@ -462,12 +462,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#74), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(73) ColumnarToRow [codegen id : 28] +(73) CometFilter Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] +Condition : isnotnull(cs_item_sk#70) -(74) Filter [codegen id : 28] +(74) ColumnarToRow [codegen id : 28] Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] -Condition : isnotnull(cs_item_sk#70) (75) ReusedExchange [Reuses operator id: 8] Output [5]: [i_item_sk#76, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] @@ -528,12 +528,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#93), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(88) ColumnarToRow [codegen id : 35] +(88) CometFilter Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] +Condition : isnotnull(ss_item_sk#89) -(89) Filter [codegen id : 35] +(89) ColumnarToRow [codegen id : 35] Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] -Condition : isnotnull(ss_item_sk#89) (90) ReusedExchange [Reuses operator id: 8] Output [5]: [i_item_sk#95, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] @@ -594,12 +594,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#112), dynamicpruningexpression(ws_s PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(103) ColumnarToRow [codegen id : 42] +(103) CometFilter Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] +Condition : isnotnull(ws_item_sk#108) -(104) Filter [codegen id : 42] +(104) ColumnarToRow [codegen id : 42] Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] -Condition : isnotnull(ws_item_sk#108) (105) ReusedExchange [Reuses operator id: 8] Output [5]: [i_item_sk#114, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] @@ -720,8 +720,8 @@ Arguments: 100, [sales_cnt_diff#137 ASC NULLS FIRST], [prev_year#133, year#134, Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (133) -+- * Filter (132) - +- * ColumnarToRow (131) ++- * ColumnarToRow (132) + +- CometFilter (131) +- CometScan parquet spark_catalog.default.date_dim (130) @@ -732,12 +732,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] ReadSchema: struct -(131) ColumnarToRow [codegen id : 1] +(131) CometFilter Input [2]: [d_date_sk#13, d_year#14] +Condition : ((isnotnull(d_year#14) AND (d_year#14 = 2002)) AND isnotnull(d_date_sk#13)) -(132) Filter [codegen id : 1] +(132) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#13, d_year#14] -Condition : ((isnotnull(d_year#14) AND (d_year#14 = 2002)) AND isnotnull(d_date_sk#13)) (133) BroadcastExchange Input [2]: [d_date_sk#13, d_year#14] @@ -749,8 +749,8 @@ Subquery:3 Hosting operator id = 43 Hosting Expression = ws_sold_date_sk#46 IN d Subquery:4 Hosting operator id = 72 Hosting Expression = cs_sold_date_sk#74 IN dynamicpruning#75 BroadcastExchange (137) -+- * Filter (136) - +- * ColumnarToRow (135) ++- * ColumnarToRow (136) + +- CometFilter (135) +- CometScan parquet spark_catalog.default.date_dim (134) @@ -761,12 +761,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(135) ColumnarToRow [codegen id : 1] +(135) CometFilter Input [2]: [d_date_sk#81, d_year#82] +Condition : ((isnotnull(d_year#82) AND (d_year#82 = 2001)) AND isnotnull(d_date_sk#81)) -(136) Filter [codegen id : 1] +(136) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#81, d_year#82] -Condition : ((isnotnull(d_year#82) AND (d_year#82 = 2001)) AND isnotnull(d_date_sk#81)) (137) BroadcastExchange Input [2]: [d_date_sk#81, d_year#82] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/simplified.txt index 021cddf2b..44bcabcdb 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q75/simplified.txt @@ -34,24 +34,24 @@ TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_cat BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #5 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #6 WholeStageCodegen (1) - Project [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] - Filter [i_category,i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + CometFilter [i_category,i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id,i_category,i_manufact_id] InputAdapter ReusedExchange [d_date_sk,d_year] #5 @@ -61,10 +61,10 @@ TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_cat InputAdapter Exchange [cr_order_number,cr_item_sk] #7 WholeStageCodegen (5) - Project [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] - Filter [cr_order_number,cr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + CometFilter [cr_order_number,cr_item_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] WholeStageCodegen (14) Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ss_quantity,sr_return_quantity,ss_ext_sales_price,sr_return_amt] @@ -79,9 +79,9 @@ TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_cat BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -94,10 +94,10 @@ TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_cat InputAdapter Exchange [sr_ticket_number,sr_item_sk] #9 WholeStageCodegen (12) - Project [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] - Filter [sr_ticket_number,sr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + CometFilter [sr_ticket_number,sr_item_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] WholeStageCodegen (21) Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ws_quantity,wr_return_quantity,ws_ext_sales_price,wr_return_amt] @@ -112,9 +112,9 @@ TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_cat BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -127,10 +127,10 @@ TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_cat InputAdapter Exchange [wr_order_number,wr_item_sk] #11 WholeStageCodegen (19) - Project [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] - Filter [wr_order_number,wr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + CometFilter [wr_order_number,wr_item_sk] CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] InputAdapter WholeStageCodegen (50) @@ -164,16 +164,16 @@ TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_cat BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #16 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 @@ -197,9 +197,9 @@ TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_cat BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter @@ -224,9 +224,9 @@ TakeOrderedAndProject [sales_cnt_diff,prev_year,year,i_brand_id,i_class_id,i_cat BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/explain.txt index 69427a8e2..f3b80d8bd 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/explain.txt @@ -8,23 +8,23 @@ TakeOrderedAndProject (38) : +- * BroadcastHashJoin Inner BuildRight (14) : :- * Project (9) : : +- * BroadcastHashJoin Inner BuildRight (8) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : +- BroadcastExchange (7) - : : +- * Filter (6) - : : +- * ColumnarToRow (5) + : : +- * ColumnarToRow (6) + : : +- CometFilter (5) : : +- CometScan parquet spark_catalog.default.item (4) : +- BroadcastExchange (13) - : +- * Filter (12) - : +- * ColumnarToRow (11) + : +- * ColumnarToRow (12) + : +- CometFilter (11) : +- CometScan parquet spark_catalog.default.date_dim (10) :- * Project (24) : +- * BroadcastHashJoin Inner BuildRight (23) : :- * Project (21) : : +- * BroadcastHashJoin Inner BuildRight (20) - : : :- * Filter (18) - : : : +- * ColumnarToRow (17) + : : :- * ColumnarToRow (18) + : : : +- CometFilter (17) : : : +- CometScan parquet spark_catalog.default.web_sales (16) : : +- ReusedExchange (19) : +- ReusedExchange (22) @@ -32,8 +32,8 @@ TakeOrderedAndProject (38) +- * BroadcastHashJoin Inner BuildRight (32) :- * Project (30) : +- * BroadcastHashJoin Inner BuildRight (29) - : :- * Filter (27) - : : +- * ColumnarToRow (26) + : :- * ColumnarToRow (27) + : : +- CometFilter (26) : : +- CometScan parquet spark_catalog.default.catalog_sales (25) : +- ReusedExchange (28) +- ReusedExchange (31) @@ -47,12 +47,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4)] PushedFilters: [IsNull(ss_store_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] +Condition : (isnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_sold_date_sk#4] -Condition : (isnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) (4) Scan parquet spark_catalog.default.item Output [2]: [i_item_sk#5, i_category#6] @@ -61,12 +61,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [2]: [i_item_sk#5, i_category#6] +Condition : isnotnull(i_item_sk#5) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [2]: [i_item_sk#5, i_category#6] -Condition : isnotnull(i_item_sk#5) (7) BroadcastExchange Input [2]: [i_item_sk#5, i_category#6] @@ -89,12 +89,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [3]: [d_date_sk#7, d_year#8, d_qoy#9] +Condition : isnotnull(d_date_sk#7) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [3]: [d_date_sk#7, d_year#8, d_qoy#9] -Condition : isnotnull(d_date_sk#7) (13) BroadcastExchange Input [3]: [d_date_sk#7, d_year#8, d_qoy#9] @@ -118,12 +118,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#16)] PushedFilters: [IsNull(ws_ship_customer_sk), IsNotNull(ws_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 6] +(17) CometFilter Input [4]: [ws_item_sk#13, ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16] +Condition : (isnull(ws_ship_customer_sk#14) AND isnotnull(ws_item_sk#13)) -(18) Filter [codegen id : 6] +(18) ColumnarToRow [codegen id : 6] Input [4]: [ws_item_sk#13, ws_ship_customer_sk#14, ws_ext_sales_price#15, ws_sold_date_sk#16] -Condition : (isnull(ws_ship_customer_sk#14) AND isnotnull(ws_item_sk#13)) (19) ReusedExchange [Reuses operator id: 7] Output [2]: [i_item_sk#17, i_category#18] @@ -159,12 +159,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#28)] PushedFilters: [IsNull(cs_ship_addr_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 9] +(26) CometFilter Input [4]: [cs_ship_addr_sk#25, cs_item_sk#26, cs_ext_sales_price#27, cs_sold_date_sk#28] +Condition : (isnull(cs_ship_addr_sk#25) AND isnotnull(cs_item_sk#26)) -(27) Filter [codegen id : 9] +(27) ColumnarToRow [codegen id : 9] Input [4]: [cs_ship_addr_sk#25, cs_item_sk#26, cs_ext_sales_price#27, cs_sold_date_sk#28] -Condition : (isnull(cs_ship_addr_sk#25) AND isnotnull(cs_item_sk#26)) (28) ReusedExchange [Reuses operator id: 7] Output [2]: [i_item_sk#29, i_category#30] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/simplified.txt index 074a78dd4..73e6b09af 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q76/simplified.txt @@ -12,32 +12,32 @@ TakeOrderedAndProject [channel,col_name,d_year,d_qoy,i_category,sales_cnt,sales_ BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_store_sk,ss_ext_sales_price,ss_sold_date_sk,i_category] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_store_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_sold_date_sk] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_category] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] WholeStageCodegen (6) Project [ws_ship_customer_sk,d_year,d_qoy,i_category,ws_ext_sales_price] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_ship_customer_sk,ws_ext_sales_price,ws_sold_date_sk,i_category] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_ship_customer_sk,ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_ship_customer_sk,ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ship_customer_sk,ws_ext_sales_price,ws_sold_date_sk] InputAdapter ReusedExchange [i_item_sk,i_category] #2 @@ -48,9 +48,9 @@ TakeOrderedAndProject [channel,col_name,d_year,d_qoy,i_category,sales_cnt,sales_ BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_ship_addr_sk,cs_ext_sales_price,cs_sold_date_sk,i_category] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_ship_addr_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_ship_addr_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_ship_addr_sk,cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] InputAdapter ReusedExchange [i_item_sk,i_category] #2 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/explain.txt index a228bce35..bbfa6a4c4 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/explain.txt @@ -14,13 +14,13 @@ TakeOrderedAndProject (85) : : +- * BroadcastHashJoin Inner BuildRight (11) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.store (7) : +- BroadcastExchange (28) : +- * HashAggregate (27) @@ -30,8 +30,8 @@ TakeOrderedAndProject (85) : +- * BroadcastHashJoin Inner BuildRight (23) : :- * Project (21) : : +- * BroadcastHashJoin Inner BuildRight (20) - : : :- * Filter (18) - : : : +- * ColumnarToRow (17) + : : :- * ColumnarToRow (18) + : : : +- CometFilter (17) : : : +- CometScan parquet spark_catalog.default.store_returns (16) : : +- ReusedExchange (19) : +- ReusedExchange (22) @@ -63,13 +63,13 @@ TakeOrderedAndProject (85) : +- * BroadcastHashJoin Inner BuildRight (60) : :- * Project (55) : : +- * BroadcastHashJoin Inner BuildRight (54) - : : :- * Filter (52) - : : : +- * ColumnarToRow (51) + : : :- * ColumnarToRow (52) + : : : +- CometFilter (51) : : : +- CometScan parquet spark_catalog.default.web_sales (50) : : +- ReusedExchange (53) : +- BroadcastExchange (59) - : +- * Filter (58) - : +- * ColumnarToRow (57) + : +- * ColumnarToRow (58) + : +- CometFilter (57) : +- CometScan parquet spark_catalog.default.web_page (56) +- BroadcastExchange (77) +- * HashAggregate (76) @@ -79,8 +79,8 @@ TakeOrderedAndProject (85) +- * BroadcastHashJoin Inner BuildRight (72) :- * Project (70) : +- * BroadcastHashJoin Inner BuildRight (69) - : :- * Filter (67) - : : +- * ColumnarToRow (66) + : :- * ColumnarToRow (67) + : : +- CometFilter (66) : : +- CometScan parquet spark_catalog.default.web_returns (65) : +- ReusedExchange (68) +- ReusedExchange (71) @@ -94,12 +94,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_store_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] -Condition : isnotnull(ss_store_sk#1) (4) ReusedExchange [Reuses operator id: 90] Output [1]: [d_date_sk#6] @@ -121,12 +121,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [1]: [s_store_sk#7] +Condition : isnotnull(s_store_sk#7) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [1]: [s_store_sk#7] -Condition : isnotnull(s_store_sk#7) (10) BroadcastExchange Input [1]: [s_store_sk#7] @@ -168,12 +168,12 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#19), dynamicpruningexpression(s PushedFilters: [IsNotNull(sr_store_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 6] +(17) CometFilter Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] +Condition : isnotnull(sr_store_sk#16) -(18) Filter [codegen id : 6] +(18) ColumnarToRow [codegen id : 6] Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] -Condition : isnotnull(sr_store_sk#16) (19) ReusedExchange [Reuses operator id: 90] Output [1]: [d_date_sk#21] @@ -335,12 +335,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#68), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_web_page_sk)] ReadSchema: struct -(51) ColumnarToRow [codegen id : 17] +(51) CometFilter Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] +Condition : isnotnull(ws_web_page_sk#65) -(52) Filter [codegen id : 17] +(52) ColumnarToRow [codegen id : 17] Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] -Condition : isnotnull(ws_web_page_sk#65) (53) ReusedExchange [Reuses operator id: 90] Output [1]: [d_date_sk#70] @@ -362,12 +362,12 @@ Location [not included in comparison]/{warehouse_dir}/web_page] PushedFilters: [IsNotNull(wp_web_page_sk)] ReadSchema: struct -(57) ColumnarToRow [codegen id : 16] +(57) CometFilter Input [1]: [wp_web_page_sk#71] +Condition : isnotnull(wp_web_page_sk#71) -(58) Filter [codegen id : 16] +(58) ColumnarToRow [codegen id : 16] Input [1]: [wp_web_page_sk#71] -Condition : isnotnull(wp_web_page_sk#71) (59) BroadcastExchange Input [1]: [wp_web_page_sk#71] @@ -409,12 +409,12 @@ PartitionFilters: [isnotnull(wr_returned_date_sk#83), dynamicpruningexpression(w PushedFilters: [IsNotNull(wr_web_page_sk)] ReadSchema: struct -(66) ColumnarToRow [codegen id : 20] +(66) CometFilter Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] +Condition : isnotnull(wr_web_page_sk#80) -(67) Filter [codegen id : 20] +(67) ColumnarToRow [codegen id : 20] Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] -Condition : isnotnull(wr_web_page_sk#80) (68) ReusedExchange [Reuses operator id: 90] Output [1]: [d_date_sk#85] @@ -506,9 +506,9 @@ Arguments: 100, [channel#99 ASC NULLS FIRST, id#100 ASC NULLS FIRST], [channel#9 Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 BroadcastExchange (90) -+- * Project (89) - +- * Filter (88) - +- * ColumnarToRow (87) ++- * ColumnarToRow (89) + +- CometProject (88) + +- CometFilter (87) +- CometScan parquet spark_catalog.default.date_dim (86) @@ -519,16 +519,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-08-03), LessThanOrEqual(d_date,2000-09-02), IsNotNull(d_date_sk)] ReadSchema: struct -(87) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#6, d_date#120] - -(88) Filter [codegen id : 1] +(87) CometFilter Input [2]: [d_date_sk#6, d_date#120] Condition : (((isnotnull(d_date#120) AND (d_date#120 >= 2000-08-03)) AND (d_date#120 <= 2000-09-02)) AND isnotnull(d_date_sk#6)) -(89) Project [codegen id : 1] -Output [1]: [d_date_sk#6] +(88) CometProject Input [2]: [d_date_sk#6, d_date#120] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(89) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] (90) BroadcastExchange Input [1]: [d_date_sk#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/simplified.txt index 36cb2e9f5..d6693067f 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q77/simplified.txt @@ -20,26 +20,26 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_store_sk,ss_ext_sales_price,ss_net_profit] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk] InputAdapter BroadcastExchange #5 @@ -53,9 +53,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] BroadcastHashJoin [sr_store_sk,s_store_sk] Project [sr_store_sk,sr_return_amt,sr_net_loss] BroadcastHashJoin [sr_returned_date_sk,d_date_sk] - Filter [sr_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sr_store_sk] CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -106,9 +106,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] Project [ws_web_page_sk,ws_ext_sales_price,ws_net_profit] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_web_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_web_page_sk] CometScan parquet spark_catalog.default.web_sales [ws_web_page_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -116,9 +116,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter BroadcastExchange #11 WholeStageCodegen (16) - Filter [wp_web_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [wp_web_page_sk] CometScan parquet spark_catalog.default.web_page [wp_web_page_sk] InputAdapter BroadcastExchange #12 @@ -132,9 +132,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] BroadcastHashJoin [wr_web_page_sk,wp_web_page_sk] Project [wr_web_page_sk,wr_return_amt,wr_net_loss] BroadcastHashJoin [wr_returned_date_sk,d_date_sk] - Filter [wr_web_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [wr_web_page_sk] CometScan parquet spark_catalog.default.web_returns [wr_web_page_sk,wr_return_amt,wr_net_loss,wr_returned_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/explain.txt index e2d0fc3ea..7f2688112 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/explain.txt @@ -15,14 +15,14 @@ TakeOrderedAndProject (70) : : : +- * SortMergeJoin LeftOuter (12) : : : :- * Sort (5) : : : : +- Exchange (4) - : : : : +- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : : +- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- * Sort (11) : : : +- Exchange (10) - : : : +- * Project (9) - : : : +- * Filter (8) - : : : +- * ColumnarToRow (7) + : : : +- * ColumnarToRow (9) + : : : +- CometProject (8) + : : : +- CometFilter (7) : : : +- CometScan parquet spark_catalog.default.store_returns (6) : : +- ReusedExchange (15) : +- * Sort (43) @@ -37,14 +37,14 @@ TakeOrderedAndProject (70) : : +- * SortMergeJoin LeftOuter (33) : : :- * Sort (26) : : : +- Exchange (25) - : : : +- * Filter (24) - : : : +- * ColumnarToRow (23) + : : : +- * ColumnarToRow (24) + : : : +- CometFilter (23) : : : +- CometScan parquet spark_catalog.default.web_sales (22) : : +- * Sort (32) : : +- Exchange (31) - : : +- * Project (30) - : : +- * Filter (29) - : : +- * ColumnarToRow (28) + : : +- * ColumnarToRow (30) + : : +- CometProject (29) + : : +- CometFilter (28) : : +- CometScan parquet spark_catalog.default.web_returns (27) : +- ReusedExchange (36) +- * Sort (67) @@ -59,14 +59,14 @@ TakeOrderedAndProject (70) : +- * SortMergeJoin LeftOuter (57) : :- * Sort (50) : : +- Exchange (49) - : : +- * Filter (48) - : : +- * ColumnarToRow (47) + : : +- * ColumnarToRow (48) + : : +- CometFilter (47) : : +- CometScan parquet spark_catalog.default.catalog_sales (46) : +- * Sort (56) : +- Exchange (55) - : +- * Project (54) - : +- * Filter (53) - : +- * ColumnarToRow (52) + : +- * ColumnarToRow (54) + : +- CometProject (53) + : +- CometFilter (52) : +- CometScan parquet spark_catalog.default.catalog_returns (51) +- ReusedExchange (60) @@ -79,12 +79,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] +(2) CometFilter Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_customer_sk#2)) -(3) Filter [codegen id : 1] +(3) ColumnarToRow [codegen id : 1] Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] -Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_customer_sk#2)) (4) Exchange Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] @@ -101,16 +101,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] ReadSchema: struct -(7) ColumnarToRow [codegen id : 3] -Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] - -(8) Filter [codegen id : 3] +(7) CometFilter Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] Condition : (isnotnull(sr_ticket_number#10) AND isnotnull(sr_item_sk#9)) -(9) Project [codegen id : 3] -Output [2]: [sr_item_sk#9, sr_ticket_number#10] +(8) CometProject Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Arguments: [sr_item_sk#9, sr_ticket_number#10], [sr_item_sk#9, sr_ticket_number#10] + +(9) ColumnarToRow [codegen id : 3] +Input [2]: [sr_item_sk#9, sr_ticket_number#10] (10) Exchange Input [2]: [sr_item_sk#9, sr_ticket_number#10] @@ -177,12 +177,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 8] +(23) CometFilter Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_item_sk#27) AND isnotnull(ws_bill_customer_sk#28)) -(24) Filter [codegen id : 8] +(24) ColumnarToRow [codegen id : 8] Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] -Condition : (isnotnull(ws_item_sk#27) AND isnotnull(ws_bill_customer_sk#28)) (25) Exchange Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] @@ -199,16 +199,16 @@ Location [not included in comparison]/{warehouse_dir}/web_returns] PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] ReadSchema: struct -(28) ColumnarToRow [codegen id : 10] -Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] - -(29) Filter [codegen id : 10] +(28) CometFilter Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] Condition : (isnotnull(wr_order_number#36) AND isnotnull(wr_item_sk#35)) -(30) Project [codegen id : 10] -Output [2]: [wr_item_sk#35, wr_order_number#36] +(29) CometProject Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Arguments: [wr_item_sk#35, wr_order_number#36], [wr_item_sk#35, wr_order_number#36] + +(30) ColumnarToRow [codegen id : 10] +Input [2]: [wr_item_sk#35, wr_order_number#36] (31) Exchange Input [2]: [wr_item_sk#35, wr_order_number#36] @@ -289,12 +289,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#60), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_bill_customer_sk)] ReadSchema: struct -(47) ColumnarToRow [codegen id : 16] +(47) CometFilter Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Condition : (isnotnull(cs_item_sk#55) AND isnotnull(cs_bill_customer_sk#54)) -(48) Filter [codegen id : 16] +(48) ColumnarToRow [codegen id : 16] Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] -Condition : (isnotnull(cs_item_sk#55) AND isnotnull(cs_bill_customer_sk#54)) (49) Exchange Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] @@ -311,16 +311,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] ReadSchema: struct -(52) ColumnarToRow [codegen id : 18] -Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] - -(53) Filter [codegen id : 18] +(52) CometFilter Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] Condition : (isnotnull(cr_order_number#63) AND isnotnull(cr_item_sk#62)) -(54) Project [codegen id : 18] -Output [2]: [cr_item_sk#62, cr_order_number#63] +(53) CometProject Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Arguments: [cr_item_sk#62, cr_order_number#63], [cr_item_sk#62, cr_order_number#63] + +(54) ColumnarToRow [codegen id : 18] +Input [2]: [cr_item_sk#62, cr_order_number#63] (55) Exchange Input [2]: [cr_item_sk#62, cr_order_number#63] @@ -401,8 +401,8 @@ Arguments: 100, [ratio#81 ASC NULLS FIRST, ss_qty#24 DESC NULLS LAST, ss_wc#25 D Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (74) -+- * Filter (73) - +- * ColumnarToRow (72) ++- * ColumnarToRow (73) + +- CometFilter (72) +- CometScan parquet spark_catalog.default.date_dim (71) @@ -413,12 +413,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(72) ColumnarToRow [codegen id : 1] +(72) CometFilter Input [2]: [d_date_sk#12, d_year#13] +Condition : ((isnotnull(d_year#13) AND (d_year#13 = 2000)) AND isnotnull(d_date_sk#12)) -(73) Filter [codegen id : 1] +(73) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#12, d_year#13] -Condition : ((isnotnull(d_year#13) AND (d_year#13 = 2000)) AND isnotnull(d_date_sk#12)) (74) BroadcastExchange Input [2]: [d_date_sk#12, d_year#13] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/simplified.txt index bb2d54937..280687e30 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q78/simplified.txt @@ -25,16 +25,16 @@ TakeOrderedAndProject [ratio,ss_qty,ss_wc,ss_sp,other_chan_qty,other_chan_wholes InputAdapter Exchange [ss_ticket_number,ss_item_sk] #2 WholeStageCodegen (1) - Filter [ss_item_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_wholesale_cost,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter WholeStageCodegen (4) @@ -42,10 +42,10 @@ TakeOrderedAndProject [ratio,ss_qty,ss_wc,ss_sp,other_chan_qty,other_chan_wholes InputAdapter Exchange [sr_ticket_number,sr_item_sk] #4 WholeStageCodegen (3) - Project [sr_item_sk,sr_ticket_number] - Filter [sr_ticket_number,sr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_ticket_number,sr_item_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk,d_year] #3 @@ -69,9 +69,9 @@ TakeOrderedAndProject [ratio,ss_qty,ss_wc,ss_sp,other_chan_qty,other_chan_wholes InputAdapter Exchange [ws_order_number,ws_item_sk] #6 WholeStageCodegen (8) - Filter [ws_item_sk,ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk,ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_order_number,ws_quantity,ws_wholesale_cost,ws_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -80,10 +80,10 @@ TakeOrderedAndProject [ratio,ss_qty,ss_wc,ss_sp,other_chan_qty,other_chan_wholes InputAdapter Exchange [wr_order_number,wr_item_sk] #7 WholeStageCodegen (10) - Project [wr_item_sk,wr_order_number] - Filter [wr_order_number,wr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number] + CometFilter [wr_order_number,wr_item_sk] CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk,d_year] #3 @@ -107,9 +107,9 @@ TakeOrderedAndProject [ratio,ss_qty,ss_wc,ss_sp,other_chan_qty,other_chan_wholes InputAdapter Exchange [cs_order_number,cs_item_sk] #9 WholeStageCodegen (16) - Filter [cs_item_sk,cs_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_bill_customer_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_order_number,cs_quantity,cs_wholesale_cost,cs_sales_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -118,10 +118,10 @@ TakeOrderedAndProject [ratio,ss_qty,ss_wc,ss_sp,other_chan_qty,other_chan_wholes InputAdapter Exchange [cr_order_number,cr_item_sk] #10 WholeStageCodegen (18) - Project [cr_item_sk,cr_order_number] - Filter [cr_order_number,cr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number] + CometFilter [cr_order_number,cr_item_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk,d_year] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/explain.txt index af1d4e56e..c89bad220 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/explain.txt @@ -11,23 +11,23 @@ TakeOrderedAndProject (30) : : +- * BroadcastHashJoin Inner BuildRight (12) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (11) - : : +- * Project (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.store (7) : +- BroadcastExchange (18) - : +- * Project (17) - : +- * Filter (16) - : +- * ColumnarToRow (15) + : +- * ColumnarToRow (17) + : +- CometProject (16) + : +- CometFilter (15) : +- CometScan parquet spark_catalog.default.household_demographics (14) +- BroadcastExchange (27) - +- * Filter (26) - +- * ColumnarToRow (25) + +- * ColumnarToRow (26) + +- CometFilter (25) +- CometScan parquet spark_catalog.default.customer (24) @@ -39,12 +39,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8] -Condition : ((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) (4) ReusedExchange [Reuses operator id: 35] Output [1]: [d_date_sk#10] @@ -66,16 +66,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_number_employees), GreaterThanOrEqual(s_number_employees,200), LessThanOrEqual(s_number_employees,295), IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] -Input [3]: [s_store_sk#11, s_number_employees#12, s_city#13] - -(9) Filter [codegen id : 2] +(8) CometFilter Input [3]: [s_store_sk#11, s_number_employees#12, s_city#13] Condition : (((isnotnull(s_number_employees#12) AND (s_number_employees#12 >= 200)) AND (s_number_employees#12 <= 295)) AND isnotnull(s_store_sk#11)) -(10) Project [codegen id : 2] -Output [2]: [s_store_sk#11, s_city#13] +(9) CometProject Input [3]: [s_store_sk#11, s_number_employees#12, s_city#13] +Arguments: [s_store_sk#11, s_city#13], [s_store_sk#11, s_city#13] + +(10) ColumnarToRow [codegen id : 2] +Input [2]: [s_store_sk#11, s_city#13] (11) BroadcastExchange Input [2]: [s_store_sk#11, s_city#13] @@ -98,16 +98,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [Or(EqualTo(hd_dep_count,6),GreaterThan(hd_vehicle_count,2)), IsNotNull(hd_demo_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] -Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] - -(16) Filter [codegen id : 3] +(15) CometFilter Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] Condition : (((hd_dep_count#15 = 6) OR (hd_vehicle_count#16 > 2)) AND isnotnull(hd_demo_sk#14)) -(17) Project [codegen id : 3] -Output [1]: [hd_demo_sk#14] +(16) CometProject Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16] +Arguments: [hd_demo_sk#14], [hd_demo_sk#14] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#14] (18) BroadcastExchange Input [1]: [hd_demo_sk#14] @@ -148,12 +148,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk)] ReadSchema: struct -(25) ColumnarToRow [codegen id : 5] +(25) CometFilter Input [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] +Condition : isnotnull(c_customer_sk#25) -(26) Filter [codegen id : 5] +(26) ColumnarToRow [codegen id : 5] Input [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] -Condition : isnotnull(c_customer_sk#25) (27) BroadcastExchange Input [3]: [c_customer_sk#25, c_first_name#26, c_last_name#27] @@ -177,9 +177,9 @@ Arguments: 100, [c_last_name#27 ASC NULLS FIRST, c_first_name#26 ASC NULLS FIRST Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (35) -+- * Project (34) - +- * Filter (33) - +- * ColumnarToRow (32) ++- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) +- CometScan parquet spark_catalog.default.date_dim (31) @@ -190,16 +190,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_dow), EqualTo(d_dow,1), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] ReadSchema: struct -(32) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#10, d_year#29, d_dow#30] - -(33) Filter [codegen id : 1] +(32) CometFilter Input [3]: [d_date_sk#10, d_year#29, d_dow#30] Condition : (((isnotnull(d_dow#30) AND (d_dow#30 = 1)) AND d_year#29 IN (1999,2000,2001)) AND isnotnull(d_date_sk#10)) -(34) Project [codegen id : 1] -Output [1]: [d_date_sk#10] +(33) CometProject Input [3]: [d_date_sk#10, d_year#29, d_dow#30] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(34) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] (35) BroadcastExchange Input [1]: [d_date_sk#10] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/simplified.txt index 505434600..4c05c449c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q79/simplified.txt @@ -13,40 +13,40 @@ TakeOrderedAndProject [c_last_name,c_first_name,s_city,profit,substr(s_city, 1, BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_ticket_number,ss_coupon_amt,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_dow,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dow,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dow] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [s_store_sk,s_city] - Filter [s_number_employees,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk,s_city] + CometFilter [s_number_employees,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_number_employees,s_city] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Project [hd_demo_sk] - Filter [hd_dep_count,hd_vehicle_count,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_vehicle_count,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] InputAdapter BroadcastExchange #5 WholeStageCodegen (5) - Filter [c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/explain.txt index 0a4159cd9..7d6d717c1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/explain.txt @@ -9,22 +9,22 @@ TakeOrderedAndProject (43) : +- * BroadcastHashJoin Inner BuildRight (11) : :- * Project (6) : : +- * BroadcastHashJoin Inner BuildRight (5) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : +- ReusedExchange (4) : +- BroadcastExchange (10) - : +- * Filter (9) - : +- * ColumnarToRow (8) + : +- * ColumnarToRow (9) + : +- CometFilter (8) : +- CometScan parquet spark_catalog.default.store (7) +- BroadcastExchange (37) +- * HashAggregate (36) +- Exchange (35) +- * HashAggregate (34) +- * BroadcastHashJoin LeftSemi BuildRight (33) - :- * Project (16) - : +- * Filter (15) - : +- * ColumnarToRow (14) + :- * ColumnarToRow (16) + : +- CometProject (15) + : +- CometFilter (14) : +- CometScan parquet spark_catalog.default.customer_address (13) +- BroadcastExchange (32) +- * Project (31) @@ -34,13 +34,13 @@ TakeOrderedAndProject (43) +- * HashAggregate (27) +- * Project (26) +- * BroadcastHashJoin Inner BuildRight (25) - :- * Filter (19) - : +- * ColumnarToRow (18) + :- * ColumnarToRow (19) + : +- CometFilter (18) : +- CometScan parquet spark_catalog.default.customer_address (17) +- BroadcastExchange (24) - +- * Project (23) - +- * Filter (22) - +- * ColumnarToRow (21) + +- * ColumnarToRow (23) + +- CometProject (22) + +- CometFilter (21) +- CometScan parquet spark_catalog.default.customer (20) @@ -52,12 +52,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 8] +(2) CometFilter Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) -(3) Filter [codegen id : 8] +(3) ColumnarToRow [codegen id : 8] Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] -Condition : isnotnull(ss_store_sk#1) (4) ReusedExchange [Reuses operator id: 48] Output [1]: [d_date_sk#5] @@ -79,12 +79,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_zip)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [3]: [s_store_sk#6, s_store_name#7, s_zip#8] +Condition : (isnotnull(s_store_sk#6) AND isnotnull(s_zip#8)) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [3]: [s_store_sk#6, s_store_name#7, s_zip#8] -Condition : (isnotnull(s_store_sk#6) AND isnotnull(s_zip#8)) (10) BroadcastExchange Input [3]: [s_store_sk#6, s_store_name#7, s_zip#8] @@ -106,16 +106,16 @@ Batched: true Location [not included in comparison]/{warehouse_dir}/customer_address] ReadSchema: struct -(14) ColumnarToRow [codegen id : 6] -Input [1]: [ca_zip#9] - -(15) Filter [codegen id : 6] +(14) CometFilter Input [1]: [ca_zip#9] Condition : (substr(ca_zip#9, 1, 5) INSET 10144, 10336, 10390, 10445, 10516, 10567, 11101, 11356, 11376, 11489, 11634, 11928, 12305, 13354, 13375, 13376, 13394, 13595, 13695, 13955, 14060, 14089, 14171, 14328, 14663, 14867, 14922, 15126, 15146, 15371, 15455, 15559, 15723, 15734, 15765, 15798, 15882, 16021, 16725, 16807, 17043, 17183, 17871, 17879, 17920, 18119, 18270, 18376, 18383, 18426, 18652, 18767, 18799, 18840, 18842, 18845, 18906, 19430, 19505, 19512, 19515, 19736, 19769, 19849, 20004, 20260, 20548, 21076, 21195, 21286, 21309, 21337, 21756, 22152, 22245, 22246, 22351, 22437, 22461, 22685, 22744, 22752, 22927, 23006, 23470, 23932, 23968, 24128, 24206, 24317, 24610, 24671, 24676, 24996, 25003, 25103, 25280, 25486, 25631, 25733, 25782, 25858, 25989, 26065, 26105, 26231, 26233, 26653, 26689, 26859, 27068, 27156, 27385, 27700, 28286, 28488, 28545, 28577, 28587, 28709, 28810, 28898, 28915, 29178, 29741, 29839, 30010, 30122, 30431, 30450, 30469, 30625, 30903, 31016, 31029, 31387, 31671, 31880, 32213, 32754, 33123, 33282, 33515, 33786, 34102, 34322, 34425, 35258, 35458, 35474, 35576, 35850, 35942, 36233, 36420, 36446, 36495, 36634, 37125, 37126, 37930, 38122, 38193, 38415, 38607, 38935, 39127, 39192, 39371, 39516, 39736, 39861, 39972, 40081, 40162, 40558, 40604, 41248, 41367, 41368, 41766, 41918, 42029, 42666, 42961, 43285, 43848, 43933, 44165, 44438, 45200, 45266, 45375, 45549, 45692, 45721, 45748, 46081, 46136, 46820, 47305, 47537, 47770, 48033, 48425, 48583, 49130, 49156, 49448, 50016, 50298, 50308, 50412, 51061, 51103, 51200, 51211, 51622, 51649, 51650, 51798, 51949, 52867, 53179, 53268, 53535, 53672, 54364, 54601, 54917, 55253, 55307, 55565, 56240, 56458, 56529, 56571, 56575, 56616, 56691, 56910, 57047, 57647, 57665, 57834, 57855, 58048, 58058, 58078, 58263, 58470, 58943, 59166, 59402, 60099, 60279, 60576, 61265, 61547, 61810, 61860, 62377, 62496, 62878, 62971, 63089, 63193, 63435, 63792, 63837, 63981, 64034, 64147, 64457, 64528, 64544, 65084, 65164, 66162, 66708, 66864, 67030, 67301, 67467, 67473, 67853, 67875, 67897, 68014, 68100, 68101, 68309, 68341, 68621, 68786, 68806, 68880, 68893, 68908, 69035, 69399, 69913, 69952, 70372, 70466, 70738, 71256, 71286, 71791, 71954, 72013, 72151, 72175, 72305, 72325, 72425, 72550, 72823, 73134, 73171, 73241, 73273, 73520, 73650, 74351, 75691, 76107, 76231, 76232, 76614, 76638, 76698, 77191, 77556, 77610, 77721, 78451, 78567, 78668, 78890, 79077, 79777, 79994, 81019, 81096, 81312, 81426, 82136, 82276, 82636, 83041, 83144, 83444, 83849, 83921, 83926, 83933, 84093, 84935, 85816, 86057, 86198, 86284, 86379, 87343, 87501, 87816, 88086, 88190, 88424, 88885, 89091, 89360, 90225, 90257, 90578, 91068, 91110, 91137, 91393, 92712, 94167, 94627, 94898, 94945, 94983, 96451, 96576, 96765, 96888, 96976, 97189, 97789, 98025, 98235, 98294, 98359, 98569, 99076, 99543 AND isnotnull(substr(ca_zip#9, 1, 5))) -(16) Project [codegen id : 6] -Output [1]: [substr(ca_zip#9, 1, 5) AS ca_zip#10] +(15) CometProject Input [1]: [ca_zip#9] +Arguments: [ca_zip#10], [substr(ca_zip#9, 1, 5) AS ca_zip#10] + +(16) ColumnarToRow [codegen id : 6] +Input [1]: [ca_zip#10] (17) Scan parquet spark_catalog.default.customer_address Output [2]: [ca_address_sk#11, ca_zip#12] @@ -124,12 +124,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 4] +(18) CometFilter Input [2]: [ca_address_sk#11, ca_zip#12] +Condition : isnotnull(ca_address_sk#11) -(19) Filter [codegen id : 4] +(19) ColumnarToRow [codegen id : 4] Input [2]: [ca_address_sk#11, ca_zip#12] -Condition : isnotnull(ca_address_sk#11) (20) Scan parquet spark_catalog.default.customer Output [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] @@ -138,16 +138,16 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_preferred_cust_flag), EqualTo(c_preferred_cust_flag,Y), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 3] -Input [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] - -(22) Filter [codegen id : 3] +(21) CometFilter Input [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] Condition : ((isnotnull(c_preferred_cust_flag#14) AND (c_preferred_cust_flag#14 = Y)) AND isnotnull(c_current_addr_sk#13)) -(23) Project [codegen id : 3] -Output [1]: [c_current_addr_sk#13] +(22) CometProject Input [2]: [c_current_addr_sk#13, c_preferred_cust_flag#14] +Arguments: [c_current_addr_sk#13], [c_current_addr_sk#13] + +(23) ColumnarToRow [codegen id : 3] +Input [1]: [c_current_addr_sk#13] (24) BroadcastExchange Input [1]: [c_current_addr_sk#13] @@ -257,9 +257,9 @@ Arguments: 100, [s_store_name#7 ASC NULLS FIRST], [s_store_name#7, sum(ss_net_pr Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (48) -+- * Project (47) - +- * Filter (46) - +- * ColumnarToRow (45) ++- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) +- CometScan parquet spark_catalog.default.date_dim (44) @@ -270,16 +270,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_qoy), IsNotNull(d_year), EqualTo(d_qoy,2), EqualTo(d_year,1998), IsNotNull(d_date_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#5, d_year#24, d_qoy#25] - -(46) Filter [codegen id : 1] +(45) CometFilter Input [3]: [d_date_sk#5, d_year#24, d_qoy#25] Condition : ((((isnotnull(d_qoy#25) AND isnotnull(d_year#24)) AND (d_qoy#25 = 2)) AND (d_year#24 = 1998)) AND isnotnull(d_date_sk#5)) -(47) Project [codegen id : 1] -Output [1]: [d_date_sk#5] +(46) CometProject Input [3]: [d_date_sk#5, d_year#24, d_qoy#25] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(47) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] (48) BroadcastExchange Input [1]: [d_date_sk#5] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/simplified.txt index 0cafe9244..76fa27693 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q8/simplified.txt @@ -11,26 +11,26 @@ TakeOrderedAndProject [s_store_name,sum(ss_net_profit)] BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_store_sk,ss_net_profit] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_qoy,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_qoy,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [s_store_sk,s_zip] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_zip] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_zip] InputAdapter BroadcastExchange #4 @@ -41,10 +41,10 @@ TakeOrderedAndProject [s_store_name,sum(ss_net_profit)] WholeStageCodegen (6) HashAggregate [ca_zip] BroadcastHashJoin [ca_zip,ca_zip] - Project [ca_zip] - Filter [ca_zip] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_zip] [ca_zip] + CometFilter [ca_zip] CometScan parquet spark_catalog.default.customer_address [ca_zip] InputAdapter BroadcastExchange #6 @@ -58,15 +58,15 @@ TakeOrderedAndProject [s_store_name,sum(ss_net_profit)] HashAggregate [ca_zip] [count,count] Project [ca_zip] BroadcastHashJoin [ca_address_sk,c_current_addr_sk] - Filter [ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_zip] InputAdapter BroadcastExchange #8 WholeStageCodegen (3) - Project [c_current_addr_sk] - Filter [c_preferred_cust_flag,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [c_current_addr_sk] + CometFilter [c_preferred_cust_flag,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_current_addr_sk,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/explain.txt index 6bee1df88..db2d015db 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/explain.txt @@ -20,29 +20,29 @@ TakeOrderedAndProject (107) : : : : : +- * SortMergeJoin LeftOuter (12) : : : : : :- * Sort (5) : : : : : : +- Exchange (4) - : : : : : : +- * Filter (3) - : : : : : : +- * ColumnarToRow (2) + : : : : : : +- * ColumnarToRow (3) + : : : : : : +- CometFilter (2) : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : : +- * Sort (11) : : : : : +- Exchange (10) - : : : : : +- * Project (9) - : : : : : +- * Filter (8) - : : : : : +- * ColumnarToRow (7) + : : : : : +- * ColumnarToRow (9) + : : : : : +- CometProject (8) + : : : : : +- CometFilter (7) : : : : : +- CometScan parquet spark_catalog.default.store_returns (6) : : : : +- ReusedExchange (14) : : : +- BroadcastExchange (20) - : : : +- * Filter (19) - : : : +- * ColumnarToRow (18) + : : : +- * ColumnarToRow (19) + : : : +- CometFilter (18) : : : +- CometScan parquet spark_catalog.default.store (17) : : +- BroadcastExchange (27) - : : +- * Project (26) - : : +- * Filter (25) - : : +- * ColumnarToRow (24) + : : +- * ColumnarToRow (26) + : : +- CometProject (25) + : : +- CometFilter (24) : : +- CometScan parquet spark_catalog.default.item (23) : +- BroadcastExchange (34) - : +- * Project (33) - : +- * Filter (32) - : +- * ColumnarToRow (31) + : +- * ColumnarToRow (33) + : +- CometProject (32) + : +- CometFilter (31) : +- CometScan parquet spark_catalog.default.promotion (30) :- * HashAggregate (70) : +- Exchange (69) @@ -59,19 +59,19 @@ TakeOrderedAndProject (107) : : : : : +- * SortMergeJoin LeftOuter (51) : : : : : :- * Sort (44) : : : : : : +- Exchange (43) - : : : : : : +- * Filter (42) - : : : : : : +- * ColumnarToRow (41) + : : : : : : +- * ColumnarToRow (42) + : : : : : : +- CometFilter (41) : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (40) : : : : : +- * Sort (50) : : : : : +- Exchange (49) - : : : : : +- * Project (48) - : : : : : +- * Filter (47) - : : : : : +- * ColumnarToRow (46) + : : : : : +- * ColumnarToRow (48) + : : : : : +- CometProject (47) + : : : : : +- CometFilter (46) : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (45) : : : : +- ReusedExchange (53) : : : +- BroadcastExchange (59) - : : : +- * Filter (58) - : : : +- * ColumnarToRow (57) + : : : +- * ColumnarToRow (58) + : : : +- CometFilter (57) : : : +- CometScan parquet spark_catalog.default.catalog_page (56) : : +- ReusedExchange (62) : +- ReusedExchange (65) @@ -90,19 +90,19 @@ TakeOrderedAndProject (107) : : : : +- * SortMergeJoin LeftOuter (82) : : : : :- * Sort (75) : : : : : +- Exchange (74) - : : : : : +- * Filter (73) - : : : : : +- * ColumnarToRow (72) + : : : : : +- * ColumnarToRow (73) + : : : : : +- CometFilter (72) : : : : : +- CometScan parquet spark_catalog.default.web_sales (71) : : : : +- * Sort (81) : : : : +- Exchange (80) - : : : : +- * Project (79) - : : : : +- * Filter (78) - : : : : +- * ColumnarToRow (77) + : : : : +- * ColumnarToRow (79) + : : : : +- CometProject (78) + : : : : +- CometFilter (77) : : : : +- CometScan parquet spark_catalog.default.web_returns (76) : : : +- ReusedExchange (84) : : +- BroadcastExchange (90) - : : +- * Filter (89) - : : +- * ColumnarToRow (88) + : : +- * ColumnarToRow (89) + : : +- CometFilter (88) : : +- CometScan parquet spark_catalog.default.web_site (87) : +- ReusedExchange (93) +- ReusedExchange (96) @@ -116,12 +116,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk), IsNotNull(ss_promo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] +(2) CometFilter Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Condition : ((isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) -(3) Filter [codegen id : 1] +(3) ColumnarToRow [codegen id : 1] Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] -Condition : ((isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) (4) Exchange Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] @@ -138,16 +138,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] ReadSchema: struct -(7) ColumnarToRow [codegen id : 3] -Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] - -(8) Filter [codegen id : 3] +(7) CometFilter Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] Condition : (isnotnull(sr_item_sk#9) AND isnotnull(sr_ticket_number#10)) -(9) Project [codegen id : 3] -Output [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +(8) CometProject Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Arguments: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12], [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] + +(9) ColumnarToRow [codegen id : 3] +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] (10) Exchange Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] @@ -187,12 +187,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 6] +(18) CometFilter Input [2]: [s_store_sk#15, s_store_id#16] +Condition : isnotnull(s_store_sk#15) -(19) Filter [codegen id : 6] +(19) ColumnarToRow [codegen id : 6] Input [2]: [s_store_sk#15, s_store_id#16] -Condition : isnotnull(s_store_sk#15) (20) BroadcastExchange Input [2]: [s_store_sk#15, s_store_id#16] @@ -215,16 +215,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_current_price), GreaterThan(i_current_price,50.00), IsNotNull(i_item_sk)] ReadSchema: struct -(24) ColumnarToRow [codegen id : 7] -Input [2]: [i_item_sk#17, i_current_price#18] - -(25) Filter [codegen id : 7] +(24) CometFilter Input [2]: [i_item_sk#17, i_current_price#18] Condition : ((isnotnull(i_current_price#18) AND (i_current_price#18 > 50.00)) AND isnotnull(i_item_sk#17)) -(26) Project [codegen id : 7] -Output [1]: [i_item_sk#17] +(25) CometProject Input [2]: [i_item_sk#17, i_current_price#18] +Arguments: [i_item_sk#17], [i_item_sk#17] + +(26) ColumnarToRow [codegen id : 7] +Input [1]: [i_item_sk#17] (27) BroadcastExchange Input [1]: [i_item_sk#17] @@ -247,16 +247,16 @@ Location [not included in comparison]/{warehouse_dir}/promotion] PushedFilters: [IsNotNull(p_channel_tv), EqualTo(p_channel_tv,N), IsNotNull(p_promo_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 8] -Input [2]: [p_promo_sk#19, p_channel_tv#20] - -(32) Filter [codegen id : 8] +(31) CometFilter Input [2]: [p_promo_sk#19, p_channel_tv#20] Condition : ((isnotnull(p_channel_tv#20) AND (p_channel_tv#20 = N)) AND isnotnull(p_promo_sk#19)) -(33) Project [codegen id : 8] -Output [1]: [p_promo_sk#19] +(32) CometProject Input [2]: [p_promo_sk#19, p_channel_tv#20] +Arguments: [p_promo_sk#19], [p_promo_sk#19] + +(33) ColumnarToRow [codegen id : 8] +Input [1]: [p_promo_sk#19] (34) BroadcastExchange Input [1]: [p_promo_sk#19] @@ -298,12 +298,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_catalog_page_sk), IsNotNull(cs_item_sk), IsNotNull(cs_promo_sk)] ReadSchema: struct -(41) ColumnarToRow [codegen id : 11] +(41) CometFilter Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Condition : ((isnotnull(cs_catalog_page_sk#39) AND isnotnull(cs_item_sk#40)) AND isnotnull(cs_promo_sk#41)) -(42) Filter [codegen id : 11] +(42) ColumnarToRow [codegen id : 11] Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] -Condition : ((isnotnull(cs_catalog_page_sk#39) AND isnotnull(cs_item_sk#40)) AND isnotnull(cs_promo_sk#41)) (43) Exchange Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] @@ -320,16 +320,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] ReadSchema: struct -(46) ColumnarToRow [codegen id : 13] -Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] - -(47) Filter [codegen id : 13] +(46) CometFilter Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] Condition : (isnotnull(cr_item_sk#47) AND isnotnull(cr_order_number#48)) -(48) Project [codegen id : 13] -Output [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +(47) CometProject Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Arguments: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50], [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] + +(48) ColumnarToRow [codegen id : 13] +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] (49) Exchange Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] @@ -369,12 +369,12 @@ Location [not included in comparison]/{warehouse_dir}/catalog_page] PushedFilters: [IsNotNull(cp_catalog_page_sk)] ReadSchema: struct -(57) ColumnarToRow [codegen id : 16] +(57) CometFilter Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Condition : isnotnull(cp_catalog_page_sk#53) -(58) Filter [codegen id : 16] +(58) ColumnarToRow [codegen id : 16] Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] -Condition : isnotnull(cp_catalog_page_sk#53) (59) BroadcastExchange Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] @@ -442,12 +442,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#81), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_web_site_sk), IsNotNull(ws_item_sk), IsNotNull(ws_promo_sk)] ReadSchema: struct -(72) ColumnarToRow [codegen id : 21] +(72) CometFilter Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Condition : ((isnotnull(ws_web_site_sk#76) AND isnotnull(ws_item_sk#75)) AND isnotnull(ws_promo_sk#77)) -(73) Filter [codegen id : 21] +(73) ColumnarToRow [codegen id : 21] Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] -Condition : ((isnotnull(ws_web_site_sk#76) AND isnotnull(ws_item_sk#75)) AND isnotnull(ws_promo_sk#77)) (74) Exchange Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] @@ -464,16 +464,16 @@ Location [not included in comparison]/{warehouse_dir}/web_returns] PushedFilters: [IsNotNull(wr_item_sk), IsNotNull(wr_order_number)] ReadSchema: struct -(77) ColumnarToRow [codegen id : 23] -Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] - -(78) Filter [codegen id : 23] +(77) CometFilter Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] Condition : (isnotnull(wr_item_sk#83) AND isnotnull(wr_order_number#84)) -(79) Project [codegen id : 23] -Output [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +(78) CometProject Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Arguments: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86], [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] + +(79) ColumnarToRow [codegen id : 23] +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] (80) Exchange Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] @@ -513,12 +513,12 @@ Location [not included in comparison]/{warehouse_dir}/web_site] PushedFilters: [IsNotNull(web_site_sk)] ReadSchema: struct -(88) ColumnarToRow [codegen id : 26] +(88) CometFilter Input [2]: [web_site_sk#89, web_site_id#90] +Condition : isnotnull(web_site_sk#89) -(89) Filter [codegen id : 26] +(89) ColumnarToRow [codegen id : 26] Input [2]: [web_site_sk#89, web_site_id#90] -Condition : isnotnull(web_site_sk#89) (90) BroadcastExchange Input [2]: [web_site_sk#89, web_site_id#90] @@ -610,9 +610,9 @@ Arguments: 100, [channel#111 ASC NULLS FIRST, id#112 ASC NULLS FIRST], [channel# Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (112) -+- * Project (111) - +- * Filter (110) - +- * ColumnarToRow (109) ++- * ColumnarToRow (111) + +- CometProject (110) + +- CometFilter (109) +- CometScan parquet spark_catalog.default.date_dim (108) @@ -623,16 +623,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-08-23), LessThanOrEqual(d_date,2000-09-22), IsNotNull(d_date_sk)] ReadSchema: struct -(109) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#14, d_date#132] - -(110) Filter [codegen id : 1] +(109) CometFilter Input [2]: [d_date_sk#14, d_date#132] Condition : (((isnotnull(d_date#132) AND (d_date#132 >= 2000-08-23)) AND (d_date#132 <= 2000-09-22)) AND isnotnull(d_date_sk#14)) -(111) Project [codegen id : 1] -Output [1]: [d_date_sk#14] +(110) CometProject Input [2]: [d_date_sk#14, d_date#132] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(111) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] (112) BroadcastExchange Input [1]: [d_date_sk#14] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/simplified.txt index 9b229a658..7e257bdc6 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q80/simplified.txt @@ -30,17 +30,17 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [ss_item_sk,ss_ticket_number] #3 WholeStageCodegen (1) - Filter [ss_store_sk,ss_item_sk,ss_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk,ss_promo_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter WholeStageCodegen (4) @@ -48,35 +48,35 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [sr_item_sk,sr_ticket_number] #5 WholeStageCodegen (3) - Project [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss] - Filter [sr_item_sk,sr_ticket_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss] + CometFilter [sr_item_sk,sr_ticket_number] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss,sr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #6 WholeStageCodegen (6) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] InputAdapter BroadcastExchange #7 WholeStageCodegen (7) - Project [i_item_sk] - Filter [i_current_price,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_current_price,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price] InputAdapter BroadcastExchange #8 WholeStageCodegen (8) - Project [p_promo_sk] - Filter [p_channel_tv,p_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [p_promo_sk] + CometFilter [p_channel_tv,p_promo_sk] CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_tv] WholeStageCodegen (20) HashAggregate [cp_catalog_page_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(cs_ext_sales_price)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum((cs_net_profit - coalesce(cast(cr_net_loss as decimal(12,2)), 0.00))),sales,returns,profit,channel,id,sum,sum,isEmpty,sum,isEmpty] @@ -100,9 +100,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [cs_item_sk,cs_order_number] #10 WholeStageCodegen (11) - Filter [cs_catalog_page_sk,cs_item_sk,cs_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_catalog_page_sk,cs_item_sk,cs_promo_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -111,19 +111,19 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [cr_item_sk,cr_order_number] #11 WholeStageCodegen (13) - Project [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss] - Filter [cr_item_sk,cr_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss] + CometFilter [cr_item_sk,cr_order_number] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss,cr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #12 WholeStageCodegen (16) - Filter [cp_catalog_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cp_catalog_page_sk] CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] InputAdapter ReusedExchange [i_item_sk] #7 @@ -151,9 +151,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [ws_item_sk,ws_order_number] #14 WholeStageCodegen (21) - Filter [ws_web_site_sk,ws_item_sk,ws_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_web_site_sk,ws_item_sk,ws_promo_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_order_number,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -162,19 +162,19 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [wr_item_sk,wr_order_number] #15 WholeStageCodegen (23) - Project [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss] - Filter [wr_item_sk,wr_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss] + CometFilter [wr_item_sk,wr_order_number] CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #16 WholeStageCodegen (26) - Filter [web_site_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [web_site_sk] CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] InputAdapter ReusedExchange [i_item_sk] #7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/explain.txt index dba7a3c3d..431d1453d 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/explain.txt @@ -14,13 +14,13 @@ TakeOrderedAndProject (48) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (6) : : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (1) : : : : +- ReusedExchange (4) : : : +- BroadcastExchange (10) - : : : +- * Filter (9) - : : : +- * ColumnarToRow (8) + : : : +- * ColumnarToRow (9) + : : : +- CometFilter (8) : : : +- CometScan parquet spark_catalog.default.customer_address (7) : : +- BroadcastExchange (33) : : +- * Filter (32) @@ -34,18 +34,18 @@ TakeOrderedAndProject (48) : : +- * BroadcastHashJoin Inner BuildRight (24) : : :- * Project (22) : : : +- * BroadcastHashJoin Inner BuildRight (21) - : : : :- * Filter (19) - : : : : +- * ColumnarToRow (18) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) : : : : +- CometScan parquet spark_catalog.default.catalog_returns (17) : : : +- ReusedExchange (20) : : +- ReusedExchange (23) : +- BroadcastExchange (39) - : +- * Filter (38) - : +- * ColumnarToRow (37) + : +- * ColumnarToRow (38) + : +- CometFilter (37) : +- CometScan parquet spark_catalog.default.customer (36) +- BroadcastExchange (45) - +- * Filter (44) - +- * ColumnarToRow (43) + +- * ColumnarToRow (44) + +- CometFilter (43) +- CometScan parquet spark_catalog.default.customer_address (42) @@ -57,12 +57,12 @@ PartitionFilters: [isnotnull(cr_returned_date_sk#4), dynamicpruningexpression(cr PushedFilters: [IsNotNull(cr_returning_addr_sk), IsNotNull(cr_returning_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [4]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, cr_returned_date_sk#4] +Condition : (isnotnull(cr_returning_addr_sk#2) AND isnotnull(cr_returning_customer_sk#1)) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [4]: [cr_returning_customer_sk#1, cr_returning_addr_sk#2, cr_return_amt_inc_tax#3, cr_returned_date_sk#4] -Condition : (isnotnull(cr_returning_addr_sk#2) AND isnotnull(cr_returning_customer_sk#1)) (4) ReusedExchange [Reuses operator id: 53] Output [1]: [d_date_sk#6] @@ -84,12 +84,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_state)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [2]: [ca_address_sk#7, ca_state#8] +Condition : (isnotnull(ca_address_sk#7) AND isnotnull(ca_state#8)) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [2]: [ca_address_sk#7, ca_state#8] -Condition : (isnotnull(ca_address_sk#7) AND isnotnull(ca_state#8)) (10) BroadcastExchange Input [2]: [ca_address_sk#7, ca_state#8] @@ -135,12 +135,12 @@ PartitionFilters: [isnotnull(cr_returned_date_sk#18), dynamicpruningexpression(c PushedFilters: [IsNotNull(cr_returning_addr_sk)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 6] +(18) CometFilter Input [4]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, cr_returned_date_sk#18] +Condition : isnotnull(cr_returning_addr_sk#16) -(19) Filter [codegen id : 6] +(19) ColumnarToRow [codegen id : 6] Input [4]: [cr_returning_customer_sk#15, cr_returning_addr_sk#16, cr_return_amt_inc_tax#17, cr_returned_date_sk#18] -Condition : isnotnull(cr_returning_addr_sk#16) (20) ReusedExchange [Reuses operator id: 53] Output [1]: [d_date_sk#20] @@ -229,12 +229,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(37) ColumnarToRow [codegen id : 9] +(37) CometFilter Input [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] +Condition : (isnotnull(c_customer_sk#33) AND isnotnull(c_current_addr_sk#35)) -(38) Filter [codegen id : 9] +(38) ColumnarToRow [codegen id : 9] Input [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] -Condition : (isnotnull(c_customer_sk#33) AND isnotnull(c_current_addr_sk#35)) (39) BroadcastExchange Input [6]: [c_customer_sk#33, c_customer_id#34, c_current_addr_sk#35, c_salutation#36, c_first_name#37, c_last_name#38] @@ -257,12 +257,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,GA), IsNotNull(ca_address_sk)] ReadSchema: struct -(43) ColumnarToRow [codegen id : 10] +(43) CometFilter Input [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] +Condition : ((isnotnull(ca_state#46) AND (ca_state#46 = GA)) AND isnotnull(ca_address_sk#39)) -(44) Filter [codegen id : 10] +(44) ColumnarToRow [codegen id : 10] Input [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] -Condition : ((isnotnull(ca_state#46) AND (ca_state#46 = GA)) AND isnotnull(ca_address_sk#39)) (45) BroadcastExchange Input [12]: [ca_address_sk#39, ca_street_number#40, ca_street_name#41, ca_street_type#42, ca_suite_number#43, ca_city#44, ca_county#45, ca_state#46, ca_zip#47, ca_country#48, ca_gmt_offset#49, ca_location_type#50] @@ -286,9 +286,9 @@ Arguments: 100, [c_customer_id#34 ASC NULLS FIRST, c_salutation#36 ASC NULLS FIR Subquery:1 Hosting operator id = 1 Hosting Expression = cr_returned_date_sk#4 IN dynamicpruning#5 BroadcastExchange (53) -+- * Project (52) - +- * Filter (51) - +- * ColumnarToRow (50) ++- * ColumnarToRow (52) + +- CometProject (51) + +- CometFilter (50) +- CometScan parquet spark_catalog.default.date_dim (49) @@ -299,16 +299,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(50) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#6, d_year#51] - -(51) Filter [codegen id : 1] +(50) CometFilter Input [2]: [d_date_sk#6, d_year#51] Condition : ((isnotnull(d_year#51) AND (d_year#51 = 2000)) AND isnotnull(d_date_sk#6)) -(52) Project [codegen id : 1] -Output [1]: [d_date_sk#6] +(51) CometProject Input [2]: [d_date_sk#6, d_year#51] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(52) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] (53) BroadcastExchange Input [1]: [d_date_sk#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/simplified.txt index 2b63992d3..6f042847c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q81/simplified.txt @@ -16,26 +16,26 @@ TakeOrderedAndProject [c_customer_id,c_salutation,c_first_name,c_last_name,ca_st BroadcastHashJoin [cr_returning_addr_sk,ca_address_sk] Project [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax] BroadcastHashJoin [cr_returned_date_sk,d_date_sk] - Filter [cr_returning_addr_sk,cr_returning_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cr_returning_addr_sk,cr_returning_customer_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax,cr_returned_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [ca_address_sk,ca_state] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_state] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #4 @@ -55,9 +55,9 @@ TakeOrderedAndProject [c_customer_id,c_salutation,c_first_name,c_last_name,ca_st BroadcastHashJoin [cr_returning_addr_sk,ca_address_sk] Project [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax] BroadcastHashJoin [cr_returned_date_sk,d_date_sk] - Filter [cr_returning_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cr_returning_addr_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_returning_customer_sk,cr_returning_addr_sk,cr_return_amt_inc_tax,cr_returned_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -67,14 +67,14 @@ TakeOrderedAndProject [c_customer_id,c_salutation,c_first_name,c_last_name,ca_st InputAdapter BroadcastExchange #7 WholeStageCodegen (9) - Filter [c_customer_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_current_addr_sk,c_salutation,c_first_name,c_last_name] InputAdapter BroadcastExchange #8 WholeStageCodegen (10) - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_street_number,ca_street_name,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset,ca_location_type] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/explain.txt index 348f4d58b..7609fa520 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/explain.txt @@ -10,19 +10,19 @@ TakeOrderedAndProject (25) : +- * BroadcastHashJoin Inner BuildRight (13) : :- * Project (11) : : +- * BroadcastHashJoin Inner BuildRight (10) - : : :- * Project (4) - : : : +- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.item (1) : : +- BroadcastExchange (9) - : : +- * Project (8) - : : +- * Filter (7) - : : +- * ColumnarToRow (6) + : : +- * ColumnarToRow (8) + : : +- CometProject (7) + : : +- CometFilter (6) : : +- CometScan parquet spark_catalog.default.inventory (5) : +- ReusedExchange (12) - +- * Project (19) - +- * Filter (18) - +- * ColumnarToRow (17) + +- * ColumnarToRow (19) + +- CometProject (18) + +- CometFilter (17) +- CometScan parquet spark_catalog.default.store_sales (16) @@ -33,16 +33,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,62.00), LessThanOrEqual(i_current_price,92.00), In(i_manufact_id, [129,270,423,821]), IsNotNull(i_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] -Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] - -(3) Filter [codegen id : 3] +(2) CometFilter Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] Condition : ((((isnotnull(i_current_price#4) AND (i_current_price#4 >= 62.00)) AND (i_current_price#4 <= 92.00)) AND i_manufact_id#5 IN (129,270,821,423)) AND isnotnull(i_item_sk#1)) -(4) Project [codegen id : 3] -Output [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] +(3) CometProject Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5] +Arguments: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4], [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] + +(4) ColumnarToRow [codegen id : 3] +Input [4]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4] (5) Scan parquet spark_catalog.default.inventory Output [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] @@ -52,16 +52,16 @@ PartitionFilters: [isnotnull(inv_date_sk#8), dynamicpruningexpression(inv_date_s PushedFilters: [IsNotNull(inv_quantity_on_hand), GreaterThanOrEqual(inv_quantity_on_hand,100), LessThanOrEqual(inv_quantity_on_hand,500), IsNotNull(inv_item_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] -Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] - -(7) Filter [codegen id : 1] +(6) CometFilter Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] Condition : (((isnotnull(inv_quantity_on_hand#7) AND (inv_quantity_on_hand#7 >= 100)) AND (inv_quantity_on_hand#7 <= 500)) AND isnotnull(inv_item_sk#6)) -(8) Project [codegen id : 1] -Output [2]: [inv_item_sk#6, inv_date_sk#8] +(7) CometProject Input [3]: [inv_item_sk#6, inv_quantity_on_hand#7, inv_date_sk#8] +Arguments: [inv_item_sk#6, inv_date_sk#8], [inv_item_sk#6, inv_date_sk#8] + +(8) ColumnarToRow [codegen id : 1] +Input [2]: [inv_item_sk#6, inv_date_sk#8] (9) BroadcastExchange Input [2]: [inv_item_sk#6, inv_date_sk#8] @@ -101,16 +101,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(17) ColumnarToRow -Input [2]: [ss_item_sk#11, ss_sold_date_sk#12] - -(18) Filter +(17) CometFilter Input [2]: [ss_item_sk#11, ss_sold_date_sk#12] Condition : isnotnull(ss_item_sk#11) -(19) Project -Output [1]: [ss_item_sk#11] +(18) CometProject Input [2]: [ss_item_sk#11, ss_sold_date_sk#12] +Arguments: [ss_item_sk#11], [ss_item_sk#11] + +(19) ColumnarToRow +Input [1]: [ss_item_sk#11] (20) BroadcastHashJoin [codegen id : 4] Left keys [1]: [i_item_sk#1] @@ -148,9 +148,9 @@ Arguments: 100, [i_item_id#2 ASC NULLS FIRST], [i_item_id#2, i_item_desc#3, i_cu Subquery:1 Hosting operator id = 5 Hosting Expression = inv_date_sk#8 IN dynamicpruning#9 BroadcastExchange (30) -+- * Project (29) - +- * Filter (28) - +- * ColumnarToRow (27) ++- * ColumnarToRow (29) + +- CometProject (28) + +- CometFilter (27) +- CometScan parquet spark_catalog.default.date_dim (26) @@ -161,16 +161,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-05-25), LessThanOrEqual(d_date,2000-07-24), IsNotNull(d_date_sk)] ReadSchema: struct -(27) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#10, d_date#13] - -(28) Filter [codegen id : 1] +(27) CometFilter Input [2]: [d_date_sk#10, d_date#13] Condition : (((isnotnull(d_date#13) AND (d_date#13 >= 2000-05-25)) AND (d_date#13 <= 2000-07-24)) AND isnotnull(d_date_sk#10)) -(29) Project [codegen id : 1] -Output [1]: [d_date_sk#10] +(28) CometProject Input [2]: [d_date_sk#10, d_date#13] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(29) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] (30) BroadcastExchange Input [1]: [d_date_sk#10] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/simplified.txt index 631237f50..0252eb575 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q82/simplified.txt @@ -14,31 +14,31 @@ TakeOrderedAndProject [i_item_id,i_item_desc,i_current_price] BroadcastHashJoin [inv_date_sk,d_date_sk] Project [i_item_sk,i_item_id,i_item_desc,i_current_price,inv_date_sk] BroadcastHashJoin [i_item_sk,inv_item_sk] - Project [i_item_sk,i_item_id,i_item_desc,i_current_price] - Filter [i_current_price,i_manufact_id,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_item_id,i_item_desc,i_current_price] + CometFilter [i_current_price,i_manufact_id,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_manufact_id] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [inv_item_sk,inv_date_sk] - Filter [inv_quantity_on_hand,inv_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [inv_item_sk,inv_date_sk] + CometFilter [inv_quantity_on_hand,inv_item_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_quantity_on_hand,inv_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter ReusedExchange [d_date_sk] #4 - Project [ss_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_item_sk] + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/explain.txt index 74f90aab2..5183e0275 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/explain.txt @@ -11,12 +11,12 @@ TakeOrderedAndProject (46) : : +- * BroadcastHashJoin Inner BuildRight (11) : : :- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_returns (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.item (4) : : +- ReusedExchange (10) : +- BroadcastExchange (28) @@ -27,8 +27,8 @@ TakeOrderedAndProject (46) : +- * BroadcastHashJoin Inner BuildRight (23) : :- * Project (21) : : +- * BroadcastHashJoin Inner BuildRight (20) - : : :- * Filter (18) - : : : +- * ColumnarToRow (17) + : : :- * ColumnarToRow (18) + : : : +- CometFilter (17) : : : +- CometScan parquet spark_catalog.default.catalog_returns (16) : : +- ReusedExchange (19) : +- ReusedExchange (22) @@ -40,8 +40,8 @@ TakeOrderedAndProject (46) +- * BroadcastHashJoin Inner BuildRight (38) :- * Project (36) : +- * BroadcastHashJoin Inner BuildRight (35) - : :- * Filter (33) - : : +- * ColumnarToRow (32) + : :- * ColumnarToRow (33) + : : +- CometFilter (32) : : +- CometScan parquet spark_catalog.default.web_returns (31) : +- ReusedExchange (34) +- ReusedExchange (37) @@ -55,12 +55,12 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#3), dynamicpruningexpression(sr PushedFilters: [IsNotNull(sr_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [3]: [sr_item_sk#1, sr_return_quantity#2, sr_returned_date_sk#3] +Condition : isnotnull(sr_item_sk#1) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [3]: [sr_item_sk#1, sr_return_quantity#2, sr_returned_date_sk#3] -Condition : isnotnull(sr_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [2]: [i_item_sk#5, i_item_id#6] @@ -69,12 +69,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_item_id)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [2]: [i_item_sk#5, i_item_id#6] +Condition : (isnotnull(i_item_sk#5) AND isnotnull(i_item_id#6)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [2]: [i_item_sk#5, i_item_id#6] -Condition : (isnotnull(i_item_sk#5) AND isnotnull(i_item_id#6)) (7) BroadcastExchange Input [2]: [i_item_sk#5, i_item_id#6] @@ -129,12 +129,12 @@ PartitionFilters: [isnotnull(cr_returned_date_sk#15), dynamicpruningexpression(c PushedFilters: [IsNotNull(cr_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 10] +(17) CometFilter Input [3]: [cr_item_sk#13, cr_return_quantity#14, cr_returned_date_sk#15] +Condition : isnotnull(cr_item_sk#13) -(18) Filter [codegen id : 10] +(18) ColumnarToRow [codegen id : 10] Input [3]: [cr_item_sk#13, cr_return_quantity#14, cr_returned_date_sk#15] -Condition : isnotnull(cr_item_sk#13) (19) ReusedExchange [Reuses operator id: 7] Output [2]: [i_item_sk#17, i_item_id#18] @@ -202,12 +202,12 @@ PartitionFilters: [isnotnull(wr_returned_date_sk#27), dynamicpruningexpression(w PushedFilters: [IsNotNull(wr_item_sk)] ReadSchema: struct -(32) ColumnarToRow [codegen id : 16] +(32) CometFilter Input [3]: [wr_item_sk#25, wr_return_quantity#26, wr_returned_date_sk#27] +Condition : isnotnull(wr_item_sk#25) -(33) Filter [codegen id : 16] +(33) ColumnarToRow [codegen id : 16] Input [3]: [wr_item_sk#25, wr_return_quantity#26, wr_returned_date_sk#27] -Condition : isnotnull(wr_item_sk#25) (34) ReusedExchange [Reuses operator id: 7] Output [2]: [i_item_sk#29, i_item_id#30] @@ -277,8 +277,8 @@ Subquery:1 Hosting operator id = 1 Hosting Expression = sr_returned_date_sk#3 IN BroadcastExchange (62) +- * Project (61) +- * BroadcastHashJoin LeftSemi BuildRight (60) - :- * Filter (49) - : +- * ColumnarToRow (48) + :- * ColumnarToRow (49) + : +- CometFilter (48) : +- CometScan parquet spark_catalog.default.date_dim (47) +- BroadcastExchange (59) +- * Project (58) @@ -286,9 +286,9 @@ BroadcastExchange (62) :- * ColumnarToRow (51) : +- CometScan parquet spark_catalog.default.date_dim (50) +- BroadcastExchange (56) - +- * Project (55) - +- * Filter (54) - +- * ColumnarToRow (53) + +- * ColumnarToRow (55) + +- CometProject (54) + +- CometFilter (53) +- CometScan parquet spark_catalog.default.date_dim (52) @@ -299,12 +299,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date_sk)] ReadSchema: struct -(48) ColumnarToRow [codegen id : 3] +(48) CometFilter Input [2]: [d_date_sk#7, d_date#41] +Condition : isnotnull(d_date_sk#7) -(49) Filter [codegen id : 3] +(49) ColumnarToRow [codegen id : 3] Input [2]: [d_date_sk#7, d_date#41] -Condition : isnotnull(d_date_sk#7) (50) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date#42, d_week_seq#43] @@ -322,16 +322,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [In(d_date, [2000-06-30,2000-09-27,2000-11-17])] ReadSchema: struct -(53) ColumnarToRow [codegen id : 1] -Input [2]: [d_date#44, d_week_seq#45] - -(54) Filter [codegen id : 1] +(53) CometFilter Input [2]: [d_date#44, d_week_seq#45] Condition : d_date#44 IN (2000-06-30,2000-09-27,2000-11-17) -(55) Project [codegen id : 1] -Output [1]: [d_week_seq#45] +(54) CometProject Input [2]: [d_date#44, d_week_seq#45] +Arguments: [d_week_seq#45], [d_week_seq#45] + +(55) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#45] (56) BroadcastExchange Input [1]: [d_week_seq#45] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/simplified.txt index 52f1fe4b5..a8f1ba3f1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q83.ansi/simplified.txt @@ -13,18 +13,18 @@ TakeOrderedAndProject [item_id,sr_item_qty,sr_dev,cr_item_qty,cr_dev,wr_item_qty BroadcastHashJoin [sr_returned_date_sk,d_date_sk] Project [sr_return_quantity,sr_returned_date_sk,i_item_id] BroadcastHashJoin [sr_item_sk,i_item_sk] - Filter [sr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sr_item_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_return_quantity,sr_returned_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (3) Project [d_date_sk] BroadcastHashJoin [d_date,d_date] - Filter [d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #3 @@ -37,17 +37,17 @@ TakeOrderedAndProject [item_id,sr_item_qty,sr_dev,cr_item_qty,cr_dev,wr_item_qty InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Project [d_week_seq] - Filter [d_date] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_date] CometScan parquet spark_catalog.default.date_dim [d_date,d_week_seq] InputAdapter BroadcastExchange #5 WholeStageCodegen (1) - Filter [i_item_sk,i_item_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_item_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] InputAdapter ReusedExchange [d_date_sk] #2 @@ -63,9 +63,9 @@ TakeOrderedAndProject [item_id,sr_item_qty,sr_dev,cr_item_qty,cr_dev,wr_item_qty BroadcastHashJoin [cr_returned_date_sk,d_date_sk] Project [cr_return_quantity,cr_returned_date_sk,i_item_id] BroadcastHashJoin [cr_item_sk,i_item_sk] - Filter [cr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cr_item_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_return_quantity,cr_returned_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -84,9 +84,9 @@ TakeOrderedAndProject [item_id,sr_item_qty,sr_dev,cr_item_qty,cr_dev,wr_item_qty BroadcastHashJoin [wr_returned_date_sk,d_date_sk] Project [wr_return_quantity,wr_returned_date_sk,i_item_id] BroadcastHashJoin [wr_item_sk,i_item_sk] - Filter [wr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [wr_item_sk] CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_return_quantity,wr_returned_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/explain.txt index c7e5238f1..8dc935d1d 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/explain.txt @@ -11,30 +11,30 @@ TakeOrderedAndProject (37) : : : +- * BroadcastHashJoin Inner BuildRight (15) : : : :- * Project (10) : : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : : +- BroadcastExchange (8) - : : : : +- * Project (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (7) + : : : : +- CometProject (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.customer_address (4) : : : +- BroadcastExchange (14) - : : : +- * Filter (13) - : : : +- * ColumnarToRow (12) + : : : +- * ColumnarToRow (13) + : : : +- CometFilter (12) : : : +- CometScan parquet spark_catalog.default.customer_demographics (11) : : +- BroadcastExchange (20) - : : +- * Filter (19) - : : +- * ColumnarToRow (18) + : : +- * ColumnarToRow (19) + : : +- CometFilter (18) : : +- CometScan parquet spark_catalog.default.household_demographics (17) : +- BroadcastExchange (27) - : +- * Project (26) - : +- * Filter (25) - : +- * ColumnarToRow (24) + : +- * ColumnarToRow (26) + : +- CometProject (25) + : +- CometFilter (24) : +- CometScan parquet spark_catalog.default.income_band (23) - +- * Project (34) - +- * Filter (33) - +- * ColumnarToRow (32) + +- * ColumnarToRow (34) + +- CometProject (33) + +- CometFilter (32) +- CometScan parquet spark_catalog.default.store_returns (31) @@ -45,12 +45,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [6]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_current_addr_sk#4, c_first_name#5, c_last_name#6] +Condition : ((isnotnull(c_current_addr_sk#4) AND isnotnull(c_current_cdemo_sk#2)) AND isnotnull(c_current_hdemo_sk#3)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [6]: [c_customer_id#1, c_current_cdemo_sk#2, c_current_hdemo_sk#3, c_current_addr_sk#4, c_first_name#5, c_last_name#6] -Condition : ((isnotnull(c_current_addr_sk#4) AND isnotnull(c_current_cdemo_sk#2)) AND isnotnull(c_current_hdemo_sk#3)) (4) Scan parquet spark_catalog.default.customer_address Output [2]: [ca_address_sk#7, ca_city#8] @@ -59,16 +59,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_city), EqualTo(ca_city,Edgewood), IsNotNull(ca_address_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [2]: [ca_address_sk#7, ca_city#8] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [2]: [ca_address_sk#7, ca_city#8] Condition : ((isnotnull(ca_city#8) AND (ca_city#8 = Edgewood)) AND isnotnull(ca_address_sk#7)) -(7) Project [codegen id : 1] -Output [1]: [ca_address_sk#7] +(6) CometProject Input [2]: [ca_address_sk#7, ca_city#8] +Arguments: [ca_address_sk#7], [ca_address_sk#7] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [ca_address_sk#7] (8) BroadcastExchange Input [1]: [ca_address_sk#7] @@ -91,12 +91,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] +(12) CometFilter Input [1]: [cd_demo_sk#9] +Condition : isnotnull(cd_demo_sk#9) -(13) Filter [codegen id : 2] +(13) ColumnarToRow [codegen id : 2] Input [1]: [cd_demo_sk#9] -Condition : isnotnull(cd_demo_sk#9) (14) BroadcastExchange Input [1]: [cd_demo_sk#9] @@ -119,12 +119,12 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_demo_sk), IsNotNull(hd_income_band_sk)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 3] +(18) CometFilter Input [2]: [hd_demo_sk#10, hd_income_band_sk#11] +Condition : (isnotnull(hd_demo_sk#10) AND isnotnull(hd_income_band_sk#11)) -(19) Filter [codegen id : 3] +(19) ColumnarToRow [codegen id : 3] Input [2]: [hd_demo_sk#10, hd_income_band_sk#11] -Condition : (isnotnull(hd_demo_sk#10) AND isnotnull(hd_income_band_sk#11)) (20) BroadcastExchange Input [2]: [hd_demo_sk#10, hd_income_band_sk#11] @@ -147,16 +147,16 @@ Location [not included in comparison]/{warehouse_dir}/income_band] PushedFilters: [IsNotNull(ib_lower_bound), IsNotNull(ib_upper_bound), GreaterThanOrEqual(ib_lower_bound,38128), LessThanOrEqual(ib_upper_bound,88128), IsNotNull(ib_income_band_sk)] ReadSchema: struct -(24) ColumnarToRow [codegen id : 4] -Input [3]: [ib_income_band_sk#12, ib_lower_bound#13, ib_upper_bound#14] - -(25) Filter [codegen id : 4] +(24) CometFilter Input [3]: [ib_income_band_sk#12, ib_lower_bound#13, ib_upper_bound#14] Condition : ((((isnotnull(ib_lower_bound#13) AND isnotnull(ib_upper_bound#14)) AND (ib_lower_bound#13 >= 38128)) AND (ib_upper_bound#14 <= 88128)) AND isnotnull(ib_income_band_sk#12)) -(26) Project [codegen id : 4] -Output [1]: [ib_income_band_sk#12] +(25) CometProject Input [3]: [ib_income_band_sk#12, ib_lower_bound#13, ib_upper_bound#14] +Arguments: [ib_income_band_sk#12], [ib_income_band_sk#12] + +(26) ColumnarToRow [codegen id : 4] +Input [1]: [ib_income_band_sk#12] (27) BroadcastExchange Input [1]: [ib_income_band_sk#12] @@ -183,16 +183,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_cdemo_sk)] ReadSchema: struct -(32) ColumnarToRow -Input [2]: [sr_cdemo_sk#15, sr_returned_date_sk#16] - -(33) Filter +(32) CometFilter Input [2]: [sr_cdemo_sk#15, sr_returned_date_sk#16] Condition : isnotnull(sr_cdemo_sk#15) -(34) Project -Output [1]: [sr_cdemo_sk#15] +(33) CometProject Input [2]: [sr_cdemo_sk#15, sr_returned_date_sk#16] +Arguments: [sr_cdemo_sk#15], [sr_cdemo_sk#15] + +(34) ColumnarToRow +Input [1]: [sr_cdemo_sk#15] (35) BroadcastHashJoin [codegen id : 6] Left keys [1]: [cd_demo_sk#9] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/simplified.txt index 157e471bb..be3451d29 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q84/simplified.txt @@ -13,42 +13,42 @@ TakeOrderedAndProject [c_customer_id,customer_id,customername] BroadcastHashJoin [c_current_cdemo_sk,cd_demo_sk] Project [c_customer_id,c_current_cdemo_sk,c_current_hdemo_sk,c_first_name,c_last_name] BroadcastHashJoin [c_current_addr_sk,ca_address_sk] - Filter [c_current_addr_sk,c_current_cdemo_sk,c_current_hdemo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk,c_current_hdemo_sk] CometScan parquet spark_catalog.default.customer [c_customer_id,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_name,c_last_name] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Project [ca_address_sk] - Filter [ca_city,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_city,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_city] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Filter [hd_demo_sk,hd_income_band_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [hd_demo_sk,hd_income_band_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_income_band_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Project [ib_income_band_sk] - Filter [ib_lower_bound,ib_upper_bound,ib_income_band_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ib_income_band_sk] + CometFilter [ib_lower_bound,ib_upper_bound,ib_income_band_sk] CometScan parquet spark_catalog.default.income_band [ib_income_band_sk,ib_lower_bound,ib_upper_bound] - Project [sr_cdemo_sk] - Filter [sr_cdemo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_cdemo_sk] + CometFilter [sr_cdemo_sk] CometScan parquet spark_catalog.default.store_returns [sr_cdemo_sk,sr_returned_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/explain.txt index b6a58f11d..ce1cc2262 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/explain.txt @@ -1,52 +1,51 @@ == Physical Plan == -TakeOrderedAndProject (48) -+- * HashAggregate (47) - +- Exchange (46) - +- * HashAggregate (45) - +- * Project (44) - +- * BroadcastHashJoin Inner BuildRight (43) - :- * Project (38) - : +- * BroadcastHashJoin Inner BuildRight (37) - : :- * Project (35) - : : +- * BroadcastHashJoin Inner BuildRight (34) - : : :- * Project (28) - : : : +- * BroadcastHashJoin Inner BuildRight (27) - : : : :- * Project (22) - : : : : +- * BroadcastHashJoin Inner BuildRight (21) - : : : : :- * Project (16) - : : : : : +- * BroadcastHashJoin Inner BuildRight (15) - : : : : : :- * Project (10) - : : : : : : +- * BroadcastHashJoin Inner BuildLeft (9) - : : : : : : :- BroadcastExchange (4) - : : : : : : : +- * Filter (3) - : : : : : : : +- * ColumnarToRow (2) - : : : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) - : : : : : : +- * Project (8) - : : : : : : +- * Filter (7) - : : : : : : +- * ColumnarToRow (6) - : : : : : : +- CometScan parquet spark_catalog.default.web_returns (5) - : : : : : +- BroadcastExchange (14) - : : : : : +- * Filter (13) - : : : : : +- * ColumnarToRow (12) - : : : : : +- CometScan parquet spark_catalog.default.web_page (11) - : : : : +- BroadcastExchange (20) - : : : : +- * Filter (19) - : : : : +- * ColumnarToRow (18) - : : : : +- CometScan parquet spark_catalog.default.customer_demographics (17) - : : : +- BroadcastExchange (26) - : : : +- * Filter (25) - : : : +- * ColumnarToRow (24) - : : : +- CometScan parquet spark_catalog.default.customer_demographics (23) - : : +- BroadcastExchange (33) - : : +- * Project (32) - : : +- * Filter (31) - : : +- * ColumnarToRow (30) - : : +- CometScan parquet spark_catalog.default.customer_address (29) - : +- ReusedExchange (36) - +- BroadcastExchange (42) - +- * Filter (41) - +- * ColumnarToRow (40) - +- CometScan parquet spark_catalog.default.reason (39) +TakeOrderedAndProject (47) ++- * HashAggregate (46) + +- Exchange (45) + +- * HashAggregate (44) + +- * Project (43) + +- * BroadcastHashJoin Inner BuildRight (42) + :- * Project (37) + : +- * BroadcastHashJoin Inner BuildRight (36) + : :- * Project (34) + : : +- * BroadcastHashJoin Inner BuildRight (33) + : : :- * Project (27) + : : : +- * BroadcastHashJoin Inner BuildRight (26) + : : : :- * Project (21) + : : : : +- * BroadcastHashJoin Inner BuildRight (20) + : : : : :- * Project (15) + : : : : : +- * BroadcastHashJoin Inner BuildRight (14) + : : : : : :- * ColumnarToRow (9) + : : : : : : +- CometProject (8) + : : : : : : +- CometBroadcastHashJoin (7) + : : : : : : :- CometBroadcastExchange (3) + : : : : : : : +- CometFilter (2) + : : : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : : : : : +- CometProject (6) + : : : : : : +- CometFilter (5) + : : : : : : +- CometScan parquet spark_catalog.default.web_returns (4) + : : : : : +- BroadcastExchange (13) + : : : : : +- * ColumnarToRow (12) + : : : : : +- CometFilter (11) + : : : : : +- CometScan parquet spark_catalog.default.web_page (10) + : : : : +- BroadcastExchange (19) + : : : : +- * ColumnarToRow (18) + : : : : +- CometFilter (17) + : : : : +- CometScan parquet spark_catalog.default.customer_demographics (16) + : : : +- BroadcastExchange (25) + : : : +- * ColumnarToRow (24) + : : : +- CometFilter (23) + : : : +- CometScan parquet spark_catalog.default.customer_demographics (22) + : : +- BroadcastExchange (32) + : : +- * ColumnarToRow (31) + : : +- CometProject (30) + : : +- CometFilter (29) + : : +- CometScan parquet spark_catalog.default.customer_address (28) + : +- ReusedExchange (35) + +- BroadcastExchange (41) + +- * ColumnarToRow (40) + +- CometFilter (39) + +- CometScan parquet spark_catalog.default.reason (38) (1) Scan parquet spark_catalog.default.web_sales @@ -57,254 +56,250 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#7), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_page_sk), Or(Or(And(GreaterThanOrEqual(ws_sales_price,100.00),LessThanOrEqual(ws_sales_price,150.00)),And(GreaterThanOrEqual(ws_sales_price,50.00),LessThanOrEqual(ws_sales_price,100.00))),And(GreaterThanOrEqual(ws_sales_price,150.00),LessThanOrEqual(ws_sales_price,200.00))), Or(Or(And(GreaterThanOrEqual(ws_net_profit,100.00),LessThanOrEqual(ws_net_profit,200.00)),And(GreaterThanOrEqual(ws_net_profit,150.00),LessThanOrEqual(ws_net_profit,300.00))),And(GreaterThanOrEqual(ws_net_profit,50.00),LessThanOrEqual(ws_net_profit,250.00)))] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] Condition : ((((isnotnull(ws_item_sk#1) AND isnotnull(ws_order_number#3)) AND isnotnull(ws_web_page_sk#2)) AND ((((ws_sales_price#5 >= 100.00) AND (ws_sales_price#5 <= 150.00)) OR ((ws_sales_price#5 >= 50.00) AND (ws_sales_price#5 <= 100.00))) OR ((ws_sales_price#5 >= 150.00) AND (ws_sales_price#5 <= 200.00)))) AND ((((ws_net_profit#6 >= 100.00) AND (ws_net_profit#6 <= 200.00)) OR ((ws_net_profit#6 >= 150.00) AND (ws_net_profit#6 <= 300.00))) OR ((ws_net_profit#6 >= 50.00) AND (ws_net_profit#6 <= 250.00)))) -(4) BroadcastExchange +(3) CometBroadcastExchange Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[2, int, false] as bigint) & 4294967295))),false), [plan_id=1] +Arguments: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] -(5) Scan parquet spark_catalog.default.web_returns +(4) Scan parquet spark_catalog.default.web_returns Output [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] Batched: true Location [not included in comparison]/{warehouse_dir}/web_returns] PushedFilters: [IsNotNull(wr_item_sk), IsNotNull(wr_order_number), IsNotNull(wr_refunded_cdemo_sk), IsNotNull(wr_returning_cdemo_sk), IsNotNull(wr_refunded_addr_sk), IsNotNull(wr_reason_sk)] ReadSchema: struct -(6) ColumnarToRow -Input [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] - -(7) Filter +(5) CometFilter Input [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] Condition : (((((isnotnull(wr_item_sk#9) AND isnotnull(wr_order_number#14)) AND isnotnull(wr_refunded_cdemo_sk#10)) AND isnotnull(wr_returning_cdemo_sk#12)) AND isnotnull(wr_refunded_addr_sk#11)) AND isnotnull(wr_reason_sk#13)) -(8) Project -Output [8]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16] +(6) CometProject Input [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17] +Arguments: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16], [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16] -(9) BroadcastHashJoin [codegen id : 8] -Left keys [2]: [ws_item_sk#1, ws_order_number#3] -Right keys [2]: [wr_item_sk#9, wr_order_number#14] -Join type: Inner -Join condition: None +(7) CometBroadcastHashJoin +Left output [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7] +Right output [8]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16] +Arguments: [ws_item_sk#1, ws_order_number#3], [wr_item_sk#9, wr_order_number#14], Inner -(10) Project [codegen id : 8] -Output [11]: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] +(8) CometProject Input [15]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16] +Arguments: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16], [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] + +(9) ColumnarToRow [codegen id : 7] +Input [11]: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] -(11) Scan parquet spark_catalog.default.web_page +(10) Scan parquet spark_catalog.default.web_page Output [1]: [wp_web_page_sk#18] Batched: true Location [not included in comparison]/{warehouse_dir}/web_page] PushedFilters: [IsNotNull(wp_web_page_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [1]: [wp_web_page_sk#18] +Condition : isnotnull(wp_web_page_sk#18) -(13) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 1] Input [1]: [wp_web_page_sk#18] -Condition : isnotnull(wp_web_page_sk#18) -(14) BroadcastExchange +(13) BroadcastExchange Input [1]: [wp_web_page_sk#18] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] -(15) BroadcastHashJoin [codegen id : 8] +(14) BroadcastHashJoin [codegen id : 7] Left keys [1]: [ws_web_page_sk#2] Right keys [1]: [wp_web_page_sk#18] Join type: Inner Join condition: None -(16) Project [codegen id : 8] +(15) Project [codegen id : 7] Output [10]: [ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] Input [12]: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, wp_web_page_sk#18] -(17) Scan parquet spark_catalog.default.customer_demographics +(16) Scan parquet spark_catalog.default.customer_demographics Output [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] Batched: true Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,Advanced Degree )),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College ))),And(EqualTo(cd_marital_status,W),EqualTo(cd_education_status,2 yr Degree )))] ReadSchema: struct -(18) ColumnarToRow [codegen id : 3] +(17) CometFilter Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] +Condition : (((isnotnull(cd_demo_sk#19) AND isnotnull(cd_marital_status#20)) AND isnotnull(cd_education_status#21)) AND ((((cd_marital_status#20 = M) AND (cd_education_status#21 = Advanced Degree )) OR ((cd_marital_status#20 = S) AND (cd_education_status#21 = College ))) OR ((cd_marital_status#20 = W) AND (cd_education_status#21 = 2 yr Degree )))) -(19) Filter [codegen id : 3] +(18) ColumnarToRow [codegen id : 2] Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] -Condition : (((isnotnull(cd_demo_sk#19) AND isnotnull(cd_marital_status#20)) AND isnotnull(cd_education_status#21)) AND ((((cd_marital_status#20 = M) AND (cd_education_status#21 = Advanced Degree )) OR ((cd_marital_status#20 = S) AND (cd_education_status#21 = College ))) OR ((cd_marital_status#20 = W) AND (cd_education_status#21 = 2 yr Degree )))) -(20) BroadcastExchange +(19) BroadcastExchange Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2] -(21) BroadcastHashJoin [codegen id : 8] +(20) BroadcastHashJoin [codegen id : 7] Left keys [1]: [wr_refunded_cdemo_sk#10] Right keys [1]: [cd_demo_sk#19] Join type: Inner Join condition: ((((((cd_marital_status#20 = M) AND (cd_education_status#21 = Advanced Degree )) AND (ws_sales_price#5 >= 100.00)) AND (ws_sales_price#5 <= 150.00)) OR ((((cd_marital_status#20 = S) AND (cd_education_status#21 = College )) AND (ws_sales_price#5 >= 50.00)) AND (ws_sales_price#5 <= 100.00))) OR ((((cd_marital_status#20 = W) AND (cd_education_status#21 = 2 yr Degree )) AND (ws_sales_price#5 >= 150.00)) AND (ws_sales_price#5 <= 200.00))) -(22) Project [codegen id : 8] +(21) Project [codegen id : 7] Output [10]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_marital_status#20, cd_education_status#21] Input [13]: [ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_demo_sk#19, cd_marital_status#20, cd_education_status#21] -(23) Scan parquet spark_catalog.default.customer_demographics +(22) Scan parquet spark_catalog.default.customer_demographics Output [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] Batched: true Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status), IsNotNull(cd_education_status)] ReadSchema: struct -(24) ColumnarToRow [codegen id : 4] +(23) CometFilter Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] +Condition : ((isnotnull(cd_demo_sk#22) AND isnotnull(cd_marital_status#23)) AND isnotnull(cd_education_status#24)) -(25) Filter [codegen id : 4] +(24) ColumnarToRow [codegen id : 3] Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] -Condition : ((isnotnull(cd_demo_sk#22) AND isnotnull(cd_marital_status#23)) AND isnotnull(cd_education_status#24)) -(26) BroadcastExchange +(25) BroadcastExchange Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] -Arguments: HashedRelationBroadcastMode(List(input[0, int, false], input[1, string, false], input[2, string, false]),false), [plan_id=4] +Arguments: HashedRelationBroadcastMode(List(input[0, int, false], input[1, string, false], input[2, string, false]),false), [plan_id=3] -(27) BroadcastHashJoin [codegen id : 8] +(26) BroadcastHashJoin [codegen id : 7] Left keys [3]: [wr_returning_cdemo_sk#12, cd_marital_status#20, cd_education_status#21] Right keys [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] Join type: Inner Join condition: None -(28) Project [codegen id : 8] +(27) Project [codegen id : 7] Output [7]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] Input [13]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_marital_status#20, cd_education_status#21, cd_demo_sk#22, cd_marital_status#23, cd_education_status#24] -(29) Scan parquet spark_catalog.default.customer_address +(28) Scan parquet spark_catalog.default.customer_address Output [3]: [ca_address_sk#25, ca_state#26, ca_country#27] Batched: true Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [IN,NJ,OH]),In(ca_state, [CT,KY,WI])),In(ca_state, [AR,IA,LA]))] ReadSchema: struct -(30) ColumnarToRow [codegen id : 5] -Input [3]: [ca_address_sk#25, ca_state#26, ca_country#27] - -(31) Filter [codegen id : 5] +(29) CometFilter Input [3]: [ca_address_sk#25, ca_state#26, ca_country#27] Condition : (((isnotnull(ca_country#27) AND (ca_country#27 = United States)) AND isnotnull(ca_address_sk#25)) AND ((ca_state#26 IN (IN,OH,NJ) OR ca_state#26 IN (WI,CT,KY)) OR ca_state#26 IN (LA,IA,AR))) -(32) Project [codegen id : 5] -Output [2]: [ca_address_sk#25, ca_state#26] +(30) CometProject Input [3]: [ca_address_sk#25, ca_state#26, ca_country#27] +Arguments: [ca_address_sk#25, ca_state#26], [ca_address_sk#25, ca_state#26] -(33) BroadcastExchange +(31) ColumnarToRow [codegen id : 4] Input [2]: [ca_address_sk#25, ca_state#26] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5] -(34) BroadcastHashJoin [codegen id : 8] +(32) BroadcastExchange +Input [2]: [ca_address_sk#25, ca_state#26] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4] + +(33) BroadcastHashJoin [codegen id : 7] Left keys [1]: [wr_refunded_addr_sk#11] Right keys [1]: [ca_address_sk#25] Join type: Inner Join condition: ((((ca_state#26 IN (IN,OH,NJ) AND (ws_net_profit#6 >= 100.00)) AND (ws_net_profit#6 <= 200.00)) OR ((ca_state#26 IN (WI,CT,KY) AND (ws_net_profit#6 >= 150.00)) AND (ws_net_profit#6 <= 300.00))) OR ((ca_state#26 IN (LA,IA,AR) AND (ws_net_profit#6 >= 50.00)) AND (ws_net_profit#6 <= 250.00))) -(35) Project [codegen id : 8] +(34) Project [codegen id : 7] Output [5]: [ws_quantity#4, ws_sold_date_sk#7, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] Input [9]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, ca_address_sk#25, ca_state#26] -(36) ReusedExchange [Reuses operator id: 53] +(35) ReusedExchange [Reuses operator id: 52] Output [1]: [d_date_sk#28] -(37) BroadcastHashJoin [codegen id : 8] +(36) BroadcastHashJoin [codegen id : 7] Left keys [1]: [ws_sold_date_sk#7] Right keys [1]: [d_date_sk#28] Join type: Inner Join condition: None -(38) Project [codegen id : 8] +(37) Project [codegen id : 7] Output [4]: [ws_quantity#4, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16] Input [6]: [ws_quantity#4, ws_sold_date_sk#7, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, d_date_sk#28] -(39) Scan parquet spark_catalog.default.reason +(38) Scan parquet spark_catalog.default.reason Output [2]: [r_reason_sk#29, r_reason_desc#30] Batched: true Location [not included in comparison]/{warehouse_dir}/reason] PushedFilters: [IsNotNull(r_reason_sk)] ReadSchema: struct -(40) ColumnarToRow [codegen id : 7] +(39) CometFilter Input [2]: [r_reason_sk#29, r_reason_desc#30] +Condition : isnotnull(r_reason_sk#29) -(41) Filter [codegen id : 7] +(40) ColumnarToRow [codegen id : 6] Input [2]: [r_reason_sk#29, r_reason_desc#30] -Condition : isnotnull(r_reason_sk#29) -(42) BroadcastExchange +(41) BroadcastExchange Input [2]: [r_reason_sk#29, r_reason_desc#30] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] -(43) BroadcastHashJoin [codegen id : 8] +(42) BroadcastHashJoin [codegen id : 7] Left keys [1]: [wr_reason_sk#13] Right keys [1]: [r_reason_sk#29] Join type: Inner Join condition: None -(44) Project [codegen id : 8] +(43) Project [codegen id : 7] Output [4]: [ws_quantity#4, wr_fee#15, wr_refunded_cash#16, r_reason_desc#30] Input [6]: [ws_quantity#4, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, r_reason_sk#29, r_reason_desc#30] -(45) HashAggregate [codegen id : 8] +(44) HashAggregate [codegen id : 7] Input [4]: [ws_quantity#4, wr_fee#15, wr_refunded_cash#16, r_reason_desc#30] Keys [1]: [r_reason_desc#30] Functions [3]: [partial_avg(ws_quantity#4), partial_avg(UnscaledValue(wr_refunded_cash#16)), partial_avg(UnscaledValue(wr_fee#15))] Aggregate Attributes [6]: [sum#31, count#32, sum#33, count#34, sum#35, count#36] Results [7]: [r_reason_desc#30, sum#37, count#38, sum#39, count#40, sum#41, count#42] -(46) Exchange +(45) Exchange Input [7]: [r_reason_desc#30, sum#37, count#38, sum#39, count#40, sum#41, count#42] -Arguments: hashpartitioning(r_reason_desc#30, 5), ENSURE_REQUIREMENTS, [plan_id=7] +Arguments: hashpartitioning(r_reason_desc#30, 5), ENSURE_REQUIREMENTS, [plan_id=6] -(47) HashAggregate [codegen id : 9] +(46) HashAggregate [codegen id : 8] Input [7]: [r_reason_desc#30, sum#37, count#38, sum#39, count#40, sum#41, count#42] Keys [1]: [r_reason_desc#30] Functions [3]: [avg(ws_quantity#4), avg(UnscaledValue(wr_refunded_cash#16)), avg(UnscaledValue(wr_fee#15))] Aggregate Attributes [3]: [avg(ws_quantity#4)#43, avg(UnscaledValue(wr_refunded_cash#16))#44, avg(UnscaledValue(wr_fee#15))#45] Results [4]: [substr(r_reason_desc#30, 1, 20) AS substr(r_reason_desc, 1, 20)#46, avg(ws_quantity#4)#43 AS avg(ws_quantity)#47, cast((avg(UnscaledValue(wr_refunded_cash#16))#44 / 100.0) as decimal(11,6)) AS avg(wr_refunded_cash)#48, cast((avg(UnscaledValue(wr_fee#15))#45 / 100.0) as decimal(11,6)) AS avg(wr_fee)#49] -(48) TakeOrderedAndProject +(47) TakeOrderedAndProject Input [4]: [substr(r_reason_desc, 1, 20)#46, avg(ws_quantity)#47, avg(wr_refunded_cash)#48, avg(wr_fee)#49] Arguments: 100, [substr(r_reason_desc, 1, 20)#46 ASC NULLS FIRST, avg(ws_quantity)#47 ASC NULLS FIRST, avg(wr_refunded_cash)#48 ASC NULLS FIRST, avg(wr_fee)#49 ASC NULLS FIRST], [substr(r_reason_desc, 1, 20)#46, avg(ws_quantity)#47, avg(wr_refunded_cash)#48, avg(wr_fee)#49] ===== Subqueries ===== Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#7 IN dynamicpruning#8 -BroadcastExchange (53) -+- * Project (52) - +- * Filter (51) - +- * ColumnarToRow (50) - +- CometScan parquet spark_catalog.default.date_dim (49) +BroadcastExchange (52) ++- * ColumnarToRow (51) + +- CometProject (50) + +- CometFilter (49) + +- CometScan parquet spark_catalog.default.date_dim (48) -(49) Scan parquet spark_catalog.default.date_dim +(48) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date_sk#28, d_year#50] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(50) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#28, d_year#50] - -(51) Filter [codegen id : 1] +(49) CometFilter Input [2]: [d_date_sk#28, d_year#50] Condition : ((isnotnull(d_year#50) AND (d_year#50 = 2000)) AND isnotnull(d_date_sk#28)) -(52) Project [codegen id : 1] -Output [1]: [d_date_sk#28] +(50) CometProject Input [2]: [d_date_sk#28, d_year#50] +Arguments: [d_date_sk#28], [d_date_sk#28] + +(51) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#28] -(53) BroadcastExchange +(52) BroadcastExchange Input [1]: [d_date_sk#28] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/simplified.txt index 99ca4aeaf..7c5ee727b 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q85/simplified.txt @@ -1,9 +1,9 @@ TakeOrderedAndProject [substr(r_reason_desc, 1, 20),avg(ws_quantity),avg(wr_refunded_cash),avg(wr_fee)] - WholeStageCodegen (9) + WholeStageCodegen (8) HashAggregate [r_reason_desc,sum,count,sum,count,sum,count] [avg(ws_quantity),avg(UnscaledValue(wr_refunded_cash)),avg(UnscaledValue(wr_fee)),substr(r_reason_desc, 1, 20),avg(ws_quantity),avg(wr_refunded_cash),avg(wr_fee),sum,count,sum,count,sum,count] InputAdapter Exchange [r_reason_desc] #1 - WholeStageCodegen (8) + WholeStageCodegen (7) HashAggregate [r_reason_desc,ws_quantity,wr_refunded_cash,wr_fee] [sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] Project [ws_quantity,wr_fee,wr_refunded_cash,r_reason_desc] BroadcastHashJoin [wr_reason_sk,r_reason_sk] @@ -17,63 +17,59 @@ TakeOrderedAndProject [substr(r_reason_desc, 1, 20),avg(ws_quantity),avg(wr_refu BroadcastHashJoin [wr_refunded_cdemo_sk,cd_demo_sk,cd_marital_status,cd_education_status,ws_sales_price] Project [ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_fee,wr_refunded_cash] BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] - Project [ws_web_page_sk,ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_fee,wr_refunded_cash] - BroadcastHashJoin [ws_item_sk,ws_order_number,wr_item_sk,wr_order_number] - InputAdapter - BroadcastExchange #2 - WholeStageCodegen (1) - Filter [ws_item_sk,ws_order_number,ws_web_page_sk,ws_sales_price,ws_net_profit] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_page_sk,ws_order_number,ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk] - SubqueryBroadcast [d_date_sk] #1 - BroadcastExchange #3 - WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] - Project [wr_item_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_order_number,wr_fee,wr_refunded_cash] - Filter [wr_item_sk,wr_order_number,wr_refunded_cdemo_sk,wr_returning_cdemo_sk,wr_refunded_addr_sk,wr_reason_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ws_web_page_sk,ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_fee,wr_refunded_cash] + CometBroadcastHashJoin [ws_item_sk,ws_order_number,wr_item_sk,wr_order_number] + CometBroadcastExchange #2 + CometFilter [ws_item_sk,ws_order_number,ws_web_page_sk,ws_sales_price,ws_net_profit] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_page_sk,ws_order_number,ws_quantity,ws_sales_price,ws_net_profit,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #3 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + CometProject [wr_item_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_order_number,wr_fee,wr_refunded_cash] + CometFilter [wr_item_sk,wr_order_number,wr_refunded_cdemo_sk,wr_returning_cdemo_sk,wr_refunded_addr_sk,wr_reason_sk] CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_refunded_cdemo_sk,wr_refunded_addr_sk,wr_returning_cdemo_sk,wr_reason_sk,wr_order_number,wr_fee,wr_refunded_cash,wr_returned_date_sk] InputAdapter BroadcastExchange #4 - WholeStageCodegen (2) - Filter [wp_web_page_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [wp_web_page_sk] CometScan parquet spark_catalog.default.web_page [wp_web_page_sk] InputAdapter BroadcastExchange #5 - WholeStageCodegen (3) - Filter [cd_demo_sk,cd_marital_status,cd_education_status] - ColumnarToRow - InputAdapter + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status,cd_education_status] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] InputAdapter BroadcastExchange #6 - WholeStageCodegen (4) - Filter [cd_demo_sk,cd_marital_status,cd_education_status] - ColumnarToRow - InputAdapter + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status,cd_education_status] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] InputAdapter BroadcastExchange #7 - WholeStageCodegen (5) - Project [ca_address_sk,ca_state] - Filter [ca_country,ca_address_sk,ca_state] - ColumnarToRow - InputAdapter + WholeStageCodegen (4) + ColumnarToRow + InputAdapter + CometProject [ca_address_sk,ca_state] + CometFilter [ca_country,ca_address_sk,ca_state] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #8 - WholeStageCodegen (7) - Filter [r_reason_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [r_reason_sk] CometScan parquet spark_catalog.default.reason [r_reason_sk,r_reason_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/explain.txt index 07e05a0ae..5bfd2925d 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/explain.txt @@ -12,13 +12,13 @@ TakeOrderedAndProject (21) +- * BroadcastHashJoin Inner BuildRight (11) :- * Project (6) : +- * BroadcastHashJoin Inner BuildRight (5) - : :- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.web_sales (1) : +- ReusedExchange (4) +- BroadcastExchange (10) - +- * Filter (9) - +- * ColumnarToRow (8) + +- * ColumnarToRow (9) + +- CometFilter (8) +- CometScan parquet spark_catalog.default.item (7) @@ -30,12 +30,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] -Condition : isnotnull(ws_item_sk#1) (4) ReusedExchange [Reuses operator id: 26] Output [1]: [d_date_sk#5] @@ -57,12 +57,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [3]: [i_item_sk#6, i_class#7, i_category#8] +Condition : isnotnull(i_item_sk#6) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [3]: [i_item_sk#6, i_class#7, i_category#8] -Condition : isnotnull(i_item_sk#6) (10) BroadcastExchange Input [3]: [i_item_sk#6, i_class#7, i_category#8] @@ -124,9 +124,9 @@ Arguments: 100, [lochierarchy#16 DESC NULLS LAST, CASE WHEN (lochierarchy#16 = 0 Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (26) -+- * Project (25) - +- * Filter (24) - +- * ColumnarToRow (23) ++- * ColumnarToRow (25) + +- CometProject (24) + +- CometFilter (23) +- CometScan parquet spark_catalog.default.date_dim (22) @@ -137,16 +137,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#5, d_month_seq#21] - -(24) Filter [codegen id : 1] +(23) CometFilter Input [2]: [d_date_sk#5, d_month_seq#21] Condition : (((isnotnull(d_month_seq#21) AND (d_month_seq#21 >= 1200)) AND (d_month_seq#21 <= 1211)) AND isnotnull(d_date_sk#5)) -(25) Project [codegen id : 1] -Output [1]: [d_date_sk#5] +(24) CometProject Input [2]: [d_date_sk#5, d_month_seq#21] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(25) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] (26) BroadcastExchange Input [1]: [d_date_sk#5] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/simplified.txt index a33617e7f..f9db2ce7a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q86/simplified.txt @@ -18,24 +18,24 @@ TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,total_sum,i_cl BroadcastHashJoin [ws_item_sk,i_item_sk] Project [ws_item_sk,ws_net_paid] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_net_paid,ws_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/explain.txt index bce0869c5..a4c9f13ce 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/explain.txt @@ -12,13 +12,13 @@ : : +- * BroadcastHashJoin Inner BuildRight (11) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.customer (7) : +- BroadcastExchange (28) : +- * HashAggregate (27) @@ -28,8 +28,8 @@ : +- * BroadcastHashJoin Inner BuildRight (23) : :- * Project (21) : : +- * BroadcastHashJoin Inner BuildRight (20) - : : :- * Filter (18) - : : : +- * ColumnarToRow (17) + : : :- * ColumnarToRow (18) + : : : +- CometFilter (17) : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) : : +- ReusedExchange (19) : +- ReusedExchange (22) @@ -41,8 +41,8 @@ +- * BroadcastHashJoin Inner BuildRight (37) :- * Project (35) : +- * BroadcastHashJoin Inner BuildRight (34) - : :- * Filter (32) - : : +- * ColumnarToRow (31) + : :- * ColumnarToRow (32) + : : +- CometFilter (31) : : +- CometScan parquet spark_catalog.default.web_sales (30) : +- ReusedExchange (33) +- ReusedExchange (36) @@ -56,12 +56,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#2), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] +Condition : isnotnull(ss_customer_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [2]: [ss_customer_sk#1, ss_sold_date_sk#2] -Condition : isnotnull(ss_customer_sk#1) (4) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#4, d_date#5] @@ -83,12 +83,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] +Condition : isnotnull(c_customer_sk#6) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] -Condition : isnotnull(c_customer_sk#6) (10) BroadcastExchange Input [3]: [c_customer_sk#6, c_first_name#7, c_last_name#8] @@ -130,12 +130,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#10), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_customer_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 6] +(17) CometFilter Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] +Condition : isnotnull(cs_bill_customer_sk#9) -(18) Filter [codegen id : 6] +(18) ColumnarToRow [codegen id : 6] Input [2]: [cs_bill_customer_sk#9, cs_sold_date_sk#10] -Condition : isnotnull(cs_bill_customer_sk#9) (19) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#12, d_date#13] @@ -199,12 +199,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#18), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 10] +(31) CometFilter Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] +Condition : isnotnull(ws_bill_customer_sk#17) -(32) Filter [codegen id : 10] +(32) ColumnarToRow [codegen id : 10] Input [2]: [ws_bill_customer_sk#17, ws_sold_date_sk#18] -Condition : isnotnull(ws_bill_customer_sk#17) (33) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#20, d_date#21] @@ -286,9 +286,9 @@ Results [1]: [count(1)#27 AS count(1)#28] Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#2 IN dynamicpruning#3 BroadcastExchange (52) -+- * Project (51) - +- * Filter (50) - +- * ColumnarToRow (49) ++- * ColumnarToRow (51) + +- CometProject (50) + +- CometFilter (49) +- CometScan parquet spark_catalog.default.date_dim (48) @@ -299,16 +299,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(49) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] - -(50) Filter [codegen id : 1] +(49) CometFilter Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] Condition : (((isnotnull(d_month_seq#29) AND (d_month_seq#29 >= 1200)) AND (d_month_seq#29 <= 1211)) AND isnotnull(d_date_sk#4)) -(51) Project [codegen id : 1] -Output [2]: [d_date_sk#4, d_date#5] +(50) CometProject Input [3]: [d_date_sk#4, d_date#5, d_month_seq#29] +Arguments: [d_date_sk#4, d_date#5], [d_date_sk#4, d_date#5] + +(51) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#4, d_date#5] (52) BroadcastExchange Input [2]: [d_date_sk#4, d_date#5] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/simplified.txt index 27489c0a9..315afe660 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q87/simplified.txt @@ -16,26 +16,26 @@ WholeStageCodegen (13) BroadcastHashJoin [ss_customer_sk,c_customer_sk] Project [ss_customer_sk,d_date] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk,d_date] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] InputAdapter ReusedExchange [d_date_sk,d_date] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_first_name,c_last_name] InputAdapter BroadcastExchange #5 @@ -49,9 +49,9 @@ WholeStageCodegen (13) BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] Project [cs_bill_customer_sk,d_date] BroadcastHashJoin [cs_sold_date_sk,d_date_sk] - Filter [cs_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_customer_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -70,9 +70,9 @@ WholeStageCodegen (13) BroadcastHashJoin [ws_bill_customer_sk,c_customer_sk] Project [ws_bill_customer_sk,d_date] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/explain.txt index ecd6c5498..a5f68e564 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/explain.txt @@ -15,24 +15,24 @@ : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (17) : : : : : : : : :- * Project (11) : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (10) -: : : : : : : : : :- * Project (4) -: : : : : : : : : : +- * Filter (3) -: : : : : : : : : : +- * ColumnarToRow (2) +: : : : : : : : : :- * ColumnarToRow (4) +: : : : : : : : : : +- CometProject (3) +: : : : : : : : : : +- CometFilter (2) : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : : : : : : +- BroadcastExchange (9) -: : : : : : : : : +- * Project (8) -: : : : : : : : : +- * Filter (7) -: : : : : : : : : +- * ColumnarToRow (6) +: : : : : : : : : +- * ColumnarToRow (8) +: : : : : : : : : +- CometProject (7) +: : : : : : : : : +- CometFilter (6) : : : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (5) : : : : : : : : +- BroadcastExchange (16) -: : : : : : : : +- * Project (15) -: : : : : : : : +- * Filter (14) -: : : : : : : : +- * ColumnarToRow (13) +: : : : : : : : +- * ColumnarToRow (15) +: : : : : : : : +- CometProject (14) +: : : : : : : : +- CometFilter (13) : : : : : : : : +- CometScan parquet spark_catalog.default.time_dim (12) : : : : : : : +- BroadcastExchange (23) -: : : : : : : +- * Project (22) -: : : : : : : +- * Filter (21) -: : : : : : : +- * ColumnarToRow (20) +: : : : : : : +- * ColumnarToRow (22) +: : : : : : : +- CometProject (21) +: : : : : : : +- CometFilter (20) : : : : : : : +- CometScan parquet spark_catalog.default.store (19) : : : : : : +- BroadcastExchange (49) : : : : : : +- * HashAggregate (48) @@ -44,15 +44,15 @@ : : : : : : : +- * BroadcastHashJoin Inner BuildRight (41) : : : : : : : :- * Project (35) : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (34) -: : : : : : : : :- * Project (32) -: : : : : : : : : +- * Filter (31) -: : : : : : : : : +- * ColumnarToRow (30) +: : : : : : : : :- * ColumnarToRow (32) +: : : : : : : : : +- CometProject (31) +: : : : : : : : : +- CometFilter (30) : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (29) : : : : : : : : +- ReusedExchange (33) : : : : : : : +- BroadcastExchange (40) -: : : : : : : +- * Project (39) -: : : : : : : +- * Filter (38) -: : : : : : : +- * ColumnarToRow (37) +: : : : : : : +- * ColumnarToRow (39) +: : : : : : : +- CometProject (38) +: : : : : : : +- CometFilter (37) : : : : : : : +- CometScan parquet spark_catalog.default.time_dim (36) : : : : : : +- ReusedExchange (43) : : : : : +- BroadcastExchange (71) @@ -65,15 +65,15 @@ : : : : : : +- * BroadcastHashJoin Inner BuildRight (63) : : : : : : :- * Project (57) : : : : : : : +- * BroadcastHashJoin Inner BuildRight (56) -: : : : : : : :- * Project (54) -: : : : : : : : +- * Filter (53) -: : : : : : : : +- * ColumnarToRow (52) +: : : : : : : :- * ColumnarToRow (54) +: : : : : : : : +- CometProject (53) +: : : : : : : : +- CometFilter (52) : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (51) : : : : : : : +- ReusedExchange (55) : : : : : : +- BroadcastExchange (62) -: : : : : : +- * Project (61) -: : : : : : +- * Filter (60) -: : : : : : +- * ColumnarToRow (59) +: : : : : : +- * ColumnarToRow (61) +: : : : : : +- CometProject (60) +: : : : : : +- CometFilter (59) : : : : : : +- CometScan parquet spark_catalog.default.time_dim (58) : : : : : +- ReusedExchange (65) : : : : +- BroadcastExchange (93) @@ -86,15 +86,15 @@ : : : : : +- * BroadcastHashJoin Inner BuildRight (85) : : : : : :- * Project (79) : : : : : : +- * BroadcastHashJoin Inner BuildRight (78) -: : : : : : :- * Project (76) -: : : : : : : +- * Filter (75) -: : : : : : : +- * ColumnarToRow (74) +: : : : : : :- * ColumnarToRow (76) +: : : : : : : +- CometProject (75) +: : : : : : : +- CometFilter (74) : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (73) : : : : : : +- ReusedExchange (77) : : : : : +- BroadcastExchange (84) -: : : : : +- * Project (83) -: : : : : +- * Filter (82) -: : : : : +- * ColumnarToRow (81) +: : : : : +- * ColumnarToRow (83) +: : : : : +- CometProject (82) +: : : : : +- CometFilter (81) : : : : : +- CometScan parquet spark_catalog.default.time_dim (80) : : : : +- ReusedExchange (87) : : : +- BroadcastExchange (115) @@ -107,15 +107,15 @@ : : : : +- * BroadcastHashJoin Inner BuildRight (107) : : : : :- * Project (101) : : : : : +- * BroadcastHashJoin Inner BuildRight (100) -: : : : : :- * Project (98) -: : : : : : +- * Filter (97) -: : : : : : +- * ColumnarToRow (96) +: : : : : :- * ColumnarToRow (98) +: : : : : : +- CometProject (97) +: : : : : : +- CometFilter (96) : : : : : : +- CometScan parquet spark_catalog.default.store_sales (95) : : : : : +- ReusedExchange (99) : : : : +- BroadcastExchange (106) -: : : : +- * Project (105) -: : : : +- * Filter (104) -: : : : +- * ColumnarToRow (103) +: : : : +- * ColumnarToRow (105) +: : : : +- CometProject (104) +: : : : +- CometFilter (103) : : : : +- CometScan parquet spark_catalog.default.time_dim (102) : : : +- ReusedExchange (109) : : +- BroadcastExchange (137) @@ -128,15 +128,15 @@ : : : +- * BroadcastHashJoin Inner BuildRight (129) : : : :- * Project (123) : : : : +- * BroadcastHashJoin Inner BuildRight (122) -: : : : :- * Project (120) -: : : : : +- * Filter (119) -: : : : : +- * ColumnarToRow (118) +: : : : :- * ColumnarToRow (120) +: : : : : +- CometProject (119) +: : : : : +- CometFilter (118) : : : : : +- CometScan parquet spark_catalog.default.store_sales (117) : : : : +- ReusedExchange (121) : : : +- BroadcastExchange (128) -: : : +- * Project (127) -: : : +- * Filter (126) -: : : +- * ColumnarToRow (125) +: : : +- * ColumnarToRow (127) +: : : +- CometProject (126) +: : : +- CometFilter (125) : : : +- CometScan parquet spark_catalog.default.time_dim (124) : : +- ReusedExchange (131) : +- BroadcastExchange (159) @@ -149,15 +149,15 @@ : : +- * BroadcastHashJoin Inner BuildRight (151) : : :- * Project (145) : : : +- * BroadcastHashJoin Inner BuildRight (144) -: : : :- * Project (142) -: : : : +- * Filter (141) -: : : : +- * ColumnarToRow (140) +: : : :- * ColumnarToRow (142) +: : : : +- CometProject (141) +: : : : +- CometFilter (140) : : : : +- CometScan parquet spark_catalog.default.store_sales (139) : : : +- ReusedExchange (143) : : +- BroadcastExchange (150) -: : +- * Project (149) -: : +- * Filter (148) -: : +- * ColumnarToRow (147) +: : +- * ColumnarToRow (149) +: : +- CometProject (148) +: : +- CometFilter (147) : : +- CometScan parquet spark_catalog.default.time_dim (146) : +- ReusedExchange (153) +- BroadcastExchange (181) @@ -170,15 +170,15 @@ : +- * BroadcastHashJoin Inner BuildRight (173) : :- * Project (167) : : +- * BroadcastHashJoin Inner BuildRight (166) - : : :- * Project (164) - : : : +- * Filter (163) - : : : +- * ColumnarToRow (162) + : : :- * ColumnarToRow (164) + : : : +- CometProject (163) + : : : +- CometFilter (162) : : : +- CometScan parquet spark_catalog.default.store_sales (161) : : +- ReusedExchange (165) : +- BroadcastExchange (172) - : +- * Project (171) - : +- * Filter (170) - : +- * ColumnarToRow (169) + : +- * ColumnarToRow (171) + : +- CometProject (170) + : +- CometFilter (169) : +- CometScan parquet spark_catalog.default.time_dim (168) +- ReusedExchange (175) @@ -190,16 +190,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] -Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] - -(3) Filter [codegen id : 4] +(2) CometFilter Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] Condition : ((isnotnull(ss_hdemo_sk#2) AND isnotnull(ss_sold_time_sk#1)) AND isnotnull(ss_store_sk#3)) -(4) Project [codegen id : 4] -Output [3]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] +(3) CometProject Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Arguments: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3], [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] + +(4) ColumnarToRow [codegen id : 4] +Input [3]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] (5) Scan parquet spark_catalog.default.household_demographics Output [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] @@ -208,16 +208,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [Or(Or(And(EqualTo(hd_dep_count,4),LessThanOrEqual(hd_vehicle_count,6)),And(EqualTo(hd_dep_count,2),LessThanOrEqual(hd_vehicle_count,4))),And(EqualTo(hd_dep_count,0),LessThanOrEqual(hd_vehicle_count,2))), IsNotNull(hd_demo_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] -Input [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] - -(7) Filter [codegen id : 1] +(6) CometFilter Input [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] Condition : (((((hd_dep_count#6 = 4) AND (hd_vehicle_count#7 <= 6)) OR ((hd_dep_count#6 = 2) AND (hd_vehicle_count#7 <= 4))) OR ((hd_dep_count#6 = 0) AND (hd_vehicle_count#7 <= 2))) AND isnotnull(hd_demo_sk#5)) -(8) Project [codegen id : 1] -Output [1]: [hd_demo_sk#5] +(7) CometProject Input [3]: [hd_demo_sk#5, hd_dep_count#6, hd_vehicle_count#7] +Arguments: [hd_demo_sk#5], [hd_demo_sk#5] + +(8) ColumnarToRow [codegen id : 1] +Input [1]: [hd_demo_sk#5] (9) BroadcastExchange Input [1]: [hd_demo_sk#5] @@ -240,16 +240,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,8), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] ReadSchema: struct -(13) ColumnarToRow [codegen id : 2] -Input [3]: [t_time_sk#8, t_hour#9, t_minute#10] - -(14) Filter [codegen id : 2] +(13) CometFilter Input [3]: [t_time_sk#8, t_hour#9, t_minute#10] Condition : ((((isnotnull(t_hour#9) AND isnotnull(t_minute#10)) AND (t_hour#9 = 8)) AND (t_minute#10 >= 30)) AND isnotnull(t_time_sk#8)) -(15) Project [codegen id : 2] -Output [1]: [t_time_sk#8] +(14) CometProject Input [3]: [t_time_sk#8, t_hour#9, t_minute#10] +Arguments: [t_time_sk#8], [t_time_sk#8] + +(15) ColumnarToRow [codegen id : 2] +Input [1]: [t_time_sk#8] (16) BroadcastExchange Input [1]: [t_time_sk#8] @@ -272,16 +272,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_name), EqualTo(s_store_name,ese), IsNotNull(s_store_sk)] ReadSchema: struct -(20) ColumnarToRow [codegen id : 3] -Input [2]: [s_store_sk#11, s_store_name#12] - -(21) Filter [codegen id : 3] +(20) CometFilter Input [2]: [s_store_sk#11, s_store_name#12] Condition : ((isnotnull(s_store_name#12) AND (s_store_name#12 = ese)) AND isnotnull(s_store_sk#11)) -(22) Project [codegen id : 3] -Output [1]: [s_store_sk#11] +(21) CometProject Input [2]: [s_store_sk#11, s_store_name#12] +Arguments: [s_store_sk#11], [s_store_sk#11] + +(22) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#11] (23) BroadcastExchange Input [1]: [s_store_sk#11] @@ -322,16 +322,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 8] -Input [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, ss_sold_date_sk#20] - -(31) Filter [codegen id : 8] +(30) CometFilter Input [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, ss_sold_date_sk#20] Condition : ((isnotnull(ss_hdemo_sk#18) AND isnotnull(ss_sold_time_sk#17)) AND isnotnull(ss_store_sk#19)) -(32) Project [codegen id : 8] -Output [3]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19] +(31) CometProject Input [4]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19, ss_sold_date_sk#20] +Arguments: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19], [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19] + +(32) ColumnarToRow [codegen id : 8] +Input [3]: [ss_sold_time_sk#17, ss_hdemo_sk#18, ss_store_sk#19] (33) ReusedExchange [Reuses operator id: 9] Output [1]: [hd_demo_sk#21] @@ -353,16 +353,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,9), LessThan(t_minute,30), IsNotNull(t_time_sk)] ReadSchema: struct -(37) ColumnarToRow [codegen id : 6] -Input [3]: [t_time_sk#22, t_hour#23, t_minute#24] - -(38) Filter [codegen id : 6] +(37) CometFilter Input [3]: [t_time_sk#22, t_hour#23, t_minute#24] Condition : ((((isnotnull(t_hour#23) AND isnotnull(t_minute#24)) AND (t_hour#23 = 9)) AND (t_minute#24 < 30)) AND isnotnull(t_time_sk#22)) -(39) Project [codegen id : 6] -Output [1]: [t_time_sk#22] +(38) CometProject Input [3]: [t_time_sk#22, t_hour#23, t_minute#24] +Arguments: [t_time_sk#22], [t_time_sk#22] + +(39) ColumnarToRow [codegen id : 6] +Input [1]: [t_time_sk#22] (40) BroadcastExchange Input [1]: [t_time_sk#22] @@ -424,16 +424,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(52) ColumnarToRow [codegen id : 13] -Input [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, ss_sold_date_sk#33] - -(53) Filter [codegen id : 13] +(52) CometFilter Input [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, ss_sold_date_sk#33] Condition : ((isnotnull(ss_hdemo_sk#31) AND isnotnull(ss_sold_time_sk#30)) AND isnotnull(ss_store_sk#32)) -(54) Project [codegen id : 13] -Output [3]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32] +(53) CometProject Input [4]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32, ss_sold_date_sk#33] +Arguments: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32], [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32] + +(54) ColumnarToRow [codegen id : 13] +Input [3]: [ss_sold_time_sk#30, ss_hdemo_sk#31, ss_store_sk#32] (55) ReusedExchange [Reuses operator id: 9] Output [1]: [hd_demo_sk#34] @@ -455,16 +455,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,9), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] ReadSchema: struct -(59) ColumnarToRow [codegen id : 11] -Input [3]: [t_time_sk#35, t_hour#36, t_minute#37] - -(60) Filter [codegen id : 11] +(59) CometFilter Input [3]: [t_time_sk#35, t_hour#36, t_minute#37] Condition : ((((isnotnull(t_hour#36) AND isnotnull(t_minute#37)) AND (t_hour#36 = 9)) AND (t_minute#37 >= 30)) AND isnotnull(t_time_sk#35)) -(61) Project [codegen id : 11] -Output [1]: [t_time_sk#35] +(60) CometProject Input [3]: [t_time_sk#35, t_hour#36, t_minute#37] +Arguments: [t_time_sk#35], [t_time_sk#35] + +(61) ColumnarToRow [codegen id : 11] +Input [1]: [t_time_sk#35] (62) BroadcastExchange Input [1]: [t_time_sk#35] @@ -526,16 +526,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(74) ColumnarToRow [codegen id : 18] -Input [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, ss_sold_date_sk#46] - -(75) Filter [codegen id : 18] +(74) CometFilter Input [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, ss_sold_date_sk#46] Condition : ((isnotnull(ss_hdemo_sk#44) AND isnotnull(ss_sold_time_sk#43)) AND isnotnull(ss_store_sk#45)) -(76) Project [codegen id : 18] -Output [3]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45] +(75) CometProject Input [4]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45, ss_sold_date_sk#46] +Arguments: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45], [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45] + +(76) ColumnarToRow [codegen id : 18] +Input [3]: [ss_sold_time_sk#43, ss_hdemo_sk#44, ss_store_sk#45] (77) ReusedExchange [Reuses operator id: 9] Output [1]: [hd_demo_sk#47] @@ -557,16 +557,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,10), LessThan(t_minute,30), IsNotNull(t_time_sk)] ReadSchema: struct -(81) ColumnarToRow [codegen id : 16] -Input [3]: [t_time_sk#48, t_hour#49, t_minute#50] - -(82) Filter [codegen id : 16] +(81) CometFilter Input [3]: [t_time_sk#48, t_hour#49, t_minute#50] Condition : ((((isnotnull(t_hour#49) AND isnotnull(t_minute#50)) AND (t_hour#49 = 10)) AND (t_minute#50 < 30)) AND isnotnull(t_time_sk#48)) -(83) Project [codegen id : 16] -Output [1]: [t_time_sk#48] +(82) CometProject Input [3]: [t_time_sk#48, t_hour#49, t_minute#50] +Arguments: [t_time_sk#48], [t_time_sk#48] + +(83) ColumnarToRow [codegen id : 16] +Input [1]: [t_time_sk#48] (84) BroadcastExchange Input [1]: [t_time_sk#48] @@ -628,16 +628,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(96) ColumnarToRow [codegen id : 23] -Input [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, ss_sold_date_sk#59] - -(97) Filter [codegen id : 23] +(96) CometFilter Input [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, ss_sold_date_sk#59] Condition : ((isnotnull(ss_hdemo_sk#57) AND isnotnull(ss_sold_time_sk#56)) AND isnotnull(ss_store_sk#58)) -(98) Project [codegen id : 23] -Output [3]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58] +(97) CometProject Input [4]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58, ss_sold_date_sk#59] +Arguments: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58], [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58] + +(98) ColumnarToRow [codegen id : 23] +Input [3]: [ss_sold_time_sk#56, ss_hdemo_sk#57, ss_store_sk#58] (99) ReusedExchange [Reuses operator id: 9] Output [1]: [hd_demo_sk#60] @@ -659,16 +659,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,10), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] ReadSchema: struct -(103) ColumnarToRow [codegen id : 21] -Input [3]: [t_time_sk#61, t_hour#62, t_minute#63] - -(104) Filter [codegen id : 21] +(103) CometFilter Input [3]: [t_time_sk#61, t_hour#62, t_minute#63] Condition : ((((isnotnull(t_hour#62) AND isnotnull(t_minute#63)) AND (t_hour#62 = 10)) AND (t_minute#63 >= 30)) AND isnotnull(t_time_sk#61)) -(105) Project [codegen id : 21] -Output [1]: [t_time_sk#61] +(104) CometProject Input [3]: [t_time_sk#61, t_hour#62, t_minute#63] +Arguments: [t_time_sk#61], [t_time_sk#61] + +(105) ColumnarToRow [codegen id : 21] +Input [1]: [t_time_sk#61] (106) BroadcastExchange Input [1]: [t_time_sk#61] @@ -730,16 +730,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(118) ColumnarToRow [codegen id : 28] -Input [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, ss_sold_date_sk#72] - -(119) Filter [codegen id : 28] +(118) CometFilter Input [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, ss_sold_date_sk#72] Condition : ((isnotnull(ss_hdemo_sk#70) AND isnotnull(ss_sold_time_sk#69)) AND isnotnull(ss_store_sk#71)) -(120) Project [codegen id : 28] -Output [3]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71] +(119) CometProject Input [4]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71, ss_sold_date_sk#72] +Arguments: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71], [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71] + +(120) ColumnarToRow [codegen id : 28] +Input [3]: [ss_sold_time_sk#69, ss_hdemo_sk#70, ss_store_sk#71] (121) ReusedExchange [Reuses operator id: 9] Output [1]: [hd_demo_sk#73] @@ -761,16 +761,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,11), LessThan(t_minute,30), IsNotNull(t_time_sk)] ReadSchema: struct -(125) ColumnarToRow [codegen id : 26] -Input [3]: [t_time_sk#74, t_hour#75, t_minute#76] - -(126) Filter [codegen id : 26] +(125) CometFilter Input [3]: [t_time_sk#74, t_hour#75, t_minute#76] Condition : ((((isnotnull(t_hour#75) AND isnotnull(t_minute#76)) AND (t_hour#75 = 11)) AND (t_minute#76 < 30)) AND isnotnull(t_time_sk#74)) -(127) Project [codegen id : 26] -Output [1]: [t_time_sk#74] +(126) CometProject Input [3]: [t_time_sk#74, t_hour#75, t_minute#76] +Arguments: [t_time_sk#74], [t_time_sk#74] + +(127) ColumnarToRow [codegen id : 26] +Input [1]: [t_time_sk#74] (128) BroadcastExchange Input [1]: [t_time_sk#74] @@ -832,16 +832,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(140) ColumnarToRow [codegen id : 33] -Input [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, ss_sold_date_sk#85] - -(141) Filter [codegen id : 33] +(140) CometFilter Input [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, ss_sold_date_sk#85] Condition : ((isnotnull(ss_hdemo_sk#83) AND isnotnull(ss_sold_time_sk#82)) AND isnotnull(ss_store_sk#84)) -(142) Project [codegen id : 33] -Output [3]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84] +(141) CometProject Input [4]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84, ss_sold_date_sk#85] +Arguments: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84], [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84] + +(142) ColumnarToRow [codegen id : 33] +Input [3]: [ss_sold_time_sk#82, ss_hdemo_sk#83, ss_store_sk#84] (143) ReusedExchange [Reuses operator id: 9] Output [1]: [hd_demo_sk#86] @@ -863,16 +863,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,11), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] ReadSchema: struct -(147) ColumnarToRow [codegen id : 31] -Input [3]: [t_time_sk#87, t_hour#88, t_minute#89] - -(148) Filter [codegen id : 31] +(147) CometFilter Input [3]: [t_time_sk#87, t_hour#88, t_minute#89] Condition : ((((isnotnull(t_hour#88) AND isnotnull(t_minute#89)) AND (t_hour#88 = 11)) AND (t_minute#89 >= 30)) AND isnotnull(t_time_sk#87)) -(149) Project [codegen id : 31] -Output [1]: [t_time_sk#87] +(148) CometProject Input [3]: [t_time_sk#87, t_hour#88, t_minute#89] +Arguments: [t_time_sk#87], [t_time_sk#87] + +(149) ColumnarToRow [codegen id : 31] +Input [1]: [t_time_sk#87] (150) BroadcastExchange Input [1]: [t_time_sk#87] @@ -934,16 +934,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(162) ColumnarToRow [codegen id : 38] -Input [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, ss_sold_date_sk#98] - -(163) Filter [codegen id : 38] +(162) CometFilter Input [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, ss_sold_date_sk#98] Condition : ((isnotnull(ss_hdemo_sk#96) AND isnotnull(ss_sold_time_sk#95)) AND isnotnull(ss_store_sk#97)) -(164) Project [codegen id : 38] -Output [3]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97] +(163) CometProject Input [4]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97, ss_sold_date_sk#98] +Arguments: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97], [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97] + +(164) ColumnarToRow [codegen id : 38] +Input [3]: [ss_sold_time_sk#95, ss_hdemo_sk#96, ss_store_sk#97] (165) ReusedExchange [Reuses operator id: 9] Output [1]: [hd_demo_sk#99] @@ -965,16 +965,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,12), LessThan(t_minute,30), IsNotNull(t_time_sk)] ReadSchema: struct -(169) ColumnarToRow [codegen id : 36] -Input [3]: [t_time_sk#100, t_hour#101, t_minute#102] - -(170) Filter [codegen id : 36] +(169) CometFilter Input [3]: [t_time_sk#100, t_hour#101, t_minute#102] Condition : ((((isnotnull(t_hour#101) AND isnotnull(t_minute#102)) AND (t_hour#101 = 12)) AND (t_minute#102 < 30)) AND isnotnull(t_time_sk#100)) -(171) Project [codegen id : 36] -Output [1]: [t_time_sk#100] +(170) CometProject Input [3]: [t_time_sk#100, t_hour#101, t_minute#102] +Arguments: [t_time_sk#100], [t_time_sk#100] + +(171) ColumnarToRow [codegen id : 36] +Input [1]: [t_time_sk#100] (172) BroadcastExchange Input [1]: [t_time_sk#100] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/simplified.txt index 3087d3432..b497e0bab 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q88/simplified.txt @@ -17,34 +17,34 @@ WholeStageCodegen (40) BroadcastHashJoin [ss_sold_time_sk,t_time_sk] Project [ss_sold_time_sk,ss_store_sk] BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] - Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] - Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Project [hd_demo_sk] - Filter [hd_dep_count,hd_vehicle_count,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_vehicle_count,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count,hd_vehicle_count] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [t_time_sk] - Filter [t_hour,t_minute,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Project [s_store_sk] - Filter [s_store_name,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_store_name,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name] InputAdapter BroadcastExchange #5 @@ -60,20 +60,20 @@ WholeStageCodegen (40) BroadcastHashJoin [ss_sold_time_sk,t_time_sk] Project [ss_sold_time_sk,ss_store_sk] BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] - Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] - Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] InputAdapter ReusedExchange [hd_demo_sk] #2 InputAdapter BroadcastExchange #7 WholeStageCodegen (6) - Project [t_time_sk] - Filter [t_hour,t_minute,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] InputAdapter ReusedExchange [s_store_sk] #4 @@ -91,20 +91,20 @@ WholeStageCodegen (40) BroadcastHashJoin [ss_sold_time_sk,t_time_sk] Project [ss_sold_time_sk,ss_store_sk] BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] - Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] - Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] InputAdapter ReusedExchange [hd_demo_sk] #2 InputAdapter BroadcastExchange #10 WholeStageCodegen (11) - Project [t_time_sk] - Filter [t_hour,t_minute,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] InputAdapter ReusedExchange [s_store_sk] #4 @@ -122,20 +122,20 @@ WholeStageCodegen (40) BroadcastHashJoin [ss_sold_time_sk,t_time_sk] Project [ss_sold_time_sk,ss_store_sk] BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] - Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] - Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] InputAdapter ReusedExchange [hd_demo_sk] #2 InputAdapter BroadcastExchange #13 WholeStageCodegen (16) - Project [t_time_sk] - Filter [t_hour,t_minute,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] InputAdapter ReusedExchange [s_store_sk] #4 @@ -153,20 +153,20 @@ WholeStageCodegen (40) BroadcastHashJoin [ss_sold_time_sk,t_time_sk] Project [ss_sold_time_sk,ss_store_sk] BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] - Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] - Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] InputAdapter ReusedExchange [hd_demo_sk] #2 InputAdapter BroadcastExchange #16 WholeStageCodegen (21) - Project [t_time_sk] - Filter [t_hour,t_minute,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] InputAdapter ReusedExchange [s_store_sk] #4 @@ -184,20 +184,20 @@ WholeStageCodegen (40) BroadcastHashJoin [ss_sold_time_sk,t_time_sk] Project [ss_sold_time_sk,ss_store_sk] BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] - Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] - Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] InputAdapter ReusedExchange [hd_demo_sk] #2 InputAdapter BroadcastExchange #19 WholeStageCodegen (26) - Project [t_time_sk] - Filter [t_hour,t_minute,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] InputAdapter ReusedExchange [s_store_sk] #4 @@ -215,20 +215,20 @@ WholeStageCodegen (40) BroadcastHashJoin [ss_sold_time_sk,t_time_sk] Project [ss_sold_time_sk,ss_store_sk] BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] - Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] - Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] InputAdapter ReusedExchange [hd_demo_sk] #2 InputAdapter BroadcastExchange #22 WholeStageCodegen (31) - Project [t_time_sk] - Filter [t_hour,t_minute,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] InputAdapter ReusedExchange [s_store_sk] #4 @@ -246,20 +246,20 @@ WholeStageCodegen (40) BroadcastHashJoin [ss_sold_time_sk,t_time_sk] Project [ss_sold_time_sk,ss_store_sk] BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] - Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] - Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] InputAdapter ReusedExchange [hd_demo_sk] #2 InputAdapter BroadcastExchange #25 WholeStageCodegen (36) - Project [t_time_sk] - Filter [t_hour,t_minute,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] InputAdapter ReusedExchange [s_store_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/explain.txt index bfa41701d..3657266e2 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/explain.txt @@ -14,17 +14,17 @@ TakeOrderedAndProject (27) : +- * BroadcastHashJoin Inner BuildRight (11) : :- * Project (9) : : +- * BroadcastHashJoin Inner BuildRight (8) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.item (1) : : +- BroadcastExchange (7) - : : +- * Filter (6) - : : +- * ColumnarToRow (5) + : : +- * ColumnarToRow (6) + : : +- CometFilter (5) : : +- CometScan parquet spark_catalog.default.store_sales (4) : +- ReusedExchange (10) +- BroadcastExchange (16) - +- * Filter (15) - +- * ColumnarToRow (14) + +- * ColumnarToRow (15) + +- CometFilter (14) +- CometScan parquet spark_catalog.default.store (13) @@ -35,12 +35,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [Or(And(In(i_category, [Books ,Electronics ,Sports ]),In(i_class, [computers ,football ,stereo ])),And(In(i_category, [Jewelry ,Men ,Women ]),In(i_class, [birdal ,dresses ,shirts ]))), IsNotNull(i_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4] +Condition : (((i_category#4 IN (Books ,Electronics ,Sports ) AND i_class#3 IN (computers ,stereo ,football )) OR (i_category#4 IN (Men ,Jewelry ,Women ) AND i_class#3 IN (shirts ,birdal ,dresses ))) AND isnotnull(i_item_sk#1)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4] -Condition : (((i_category#4 IN (Books ,Electronics ,Sports ) AND i_class#3 IN (computers ,stereo ,football )) OR (i_category#4 IN (Men ,Jewelry ,Women ) AND i_class#3 IN (shirts ,birdal ,dresses ))) AND isnotnull(i_item_sk#1)) (4) Scan parquet spark_catalog.default.store_sales Output [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] @@ -50,12 +50,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] +Condition : (isnotnull(ss_item_sk#5) AND isnotnull(ss_store_sk#6)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] -Condition : (isnotnull(ss_item_sk#5) AND isnotnull(ss_store_sk#6)) (7) BroadcastExchange Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8] @@ -91,12 +91,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Condition : isnotnull(s_store_sk#12) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] -Condition : isnotnull(s_store_sk#12) (16) BroadcastExchange Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] @@ -158,9 +158,9 @@ Arguments: 100, [(sum_sales#18 - avg_monthly_sales#20) ASC NULLS FIRST, s_store_ Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (32) -+- * Project (31) - +- * Filter (30) - +- * ColumnarToRow (29) ++- * ColumnarToRow (31) + +- CometProject (30) + +- CometFilter (29) +- CometScan parquet spark_catalog.default.date_dim (28) @@ -171,16 +171,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk)] ReadSchema: struct -(29) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#10, d_year#21, d_moy#11] - -(30) Filter [codegen id : 1] +(29) CometFilter Input [3]: [d_date_sk#10, d_year#21, d_moy#11] Condition : ((isnotnull(d_year#21) AND (d_year#21 = 1999)) AND isnotnull(d_date_sk#10)) -(31) Project [codegen id : 1] -Output [2]: [d_date_sk#10, d_moy#11] +(30) CometProject Input [3]: [d_date_sk#10, d_year#21, d_moy#11] +Arguments: [d_date_sk#10, d_moy#11], [d_date_sk#10, d_moy#11] + +(31) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#10, d_moy#11] (32) BroadcastExchange Input [2]: [d_date_sk#10, d_moy#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/simplified.txt index d7daa4af9..bb9e4e17e 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q89/simplified.txt @@ -20,31 +20,31 @@ TakeOrderedAndProject [sum_sales,avg_monthly_sales,s_store_name,i_category,i_cla BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [i_brand,i_class,i_category,ss_store_sk,ss_sales_price,ss_sold_date_sk] BroadcastHashJoin [i_item_sk,ss_item_sk] - Filter [i_category,i_class,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_category,i_class,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [ss_item_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk,d_moy] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_moy] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk,d_moy] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/explain.txt index 1b7aad28b..69c23211b 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/explain.txt @@ -1,7 +1,7 @@ == Physical Plan == * Project (4) -+- * Filter (3) - +- * ColumnarToRow (2) ++- * ColumnarToRow (3) + +- CometFilter (2) +- CometScan parquet spark_catalog.default.reason (1) @@ -12,12 +12,12 @@ Location [not included in comparison]/{warehouse_dir}/reason] PushedFilters: [IsNotNull(r_reason_sk), EqualTo(r_reason_sk,1)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] +(2) CometFilter Input [1]: [r_reason_sk#1] +Condition : (isnotnull(r_reason_sk#1) AND (r_reason_sk#1 = 1)) -(3) Filter [codegen id : 1] +(3) ColumnarToRow [codegen id : 1] Input [1]: [r_reason_sk#1] -Condition : (isnotnull(r_reason_sk#1) AND (r_reason_sk#1 = 1)) (4) Project [codegen id : 1] Output [5]: [CASE WHEN (Subquery scalar-subquery#2, [id=#3].count(1) > 62316685) THEN ReusedSubquery Subquery scalar-subquery#2, [id=#3].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#2, [id=#3].avg(ss_net_paid) END AS bucket1#4, CASE WHEN (Subquery scalar-subquery#5, [id=#6].count(1) > 19045798) THEN ReusedSubquery Subquery scalar-subquery#5, [id=#6].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#5, [id=#6].avg(ss_net_paid) END AS bucket2#7, CASE WHEN (Subquery scalar-subquery#8, [id=#9].count(1) > 365541424) THEN ReusedSubquery Subquery scalar-subquery#8, [id=#9].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#8, [id=#9].avg(ss_net_paid) END AS bucket3#10, CASE WHEN (Subquery scalar-subquery#11, [id=#12].count(1) > 216357808) THEN ReusedSubquery Subquery scalar-subquery#11, [id=#12].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#11, [id=#12].avg(ss_net_paid) END AS bucket4#13, CASE WHEN (Subquery scalar-subquery#14, [id=#15].count(1) > 184483884) THEN ReusedSubquery Subquery scalar-subquery#14, [id=#15].avg(ss_ext_discount_amt) ELSE ReusedSubquery Subquery scalar-subquery#14, [id=#15].avg(ss_net_paid) END AS bucket5#16] @@ -30,9 +30,9 @@ Subquery:1 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery +- * HashAggregate (11) +- Exchange (10) +- * HashAggregate (9) - +- * Project (8) - +- * Filter (7) - +- * ColumnarToRow (6) + +- * ColumnarToRow (8) + +- CometProject (7) + +- CometFilter (6) +- CometScan parquet spark_catalog.default.store_sales (5) @@ -43,16 +43,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,1), LessThanOrEqual(ss_quantity,20)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] -Input [4]: [ss_quantity#17, ss_ext_discount_amt#18, ss_net_paid#19, ss_sold_date_sk#20] - -(7) Filter [codegen id : 1] +(6) CometFilter Input [4]: [ss_quantity#17, ss_ext_discount_amt#18, ss_net_paid#19, ss_sold_date_sk#20] Condition : ((isnotnull(ss_quantity#17) AND (ss_quantity#17 >= 1)) AND (ss_quantity#17 <= 20)) -(8) Project [codegen id : 1] -Output [2]: [ss_ext_discount_amt#18, ss_net_paid#19] +(7) CometProject Input [4]: [ss_quantity#17, ss_ext_discount_amt#18, ss_net_paid#19, ss_sold_date_sk#20] +Arguments: [ss_ext_discount_amt#18, ss_net_paid#19], [ss_ext_discount_amt#18, ss_net_paid#19] + +(8) ColumnarToRow [codegen id : 1] +Input [2]: [ss_ext_discount_amt#18, ss_net_paid#19] (9) HashAggregate [codegen id : 1] Input [2]: [ss_ext_discount_amt#18, ss_net_paid#19] @@ -85,9 +85,9 @@ Subquery:4 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery +- * HashAggregate (19) +- Exchange (18) +- * HashAggregate (17) - +- * Project (16) - +- * Filter (15) - +- * ColumnarToRow (14) + +- * ColumnarToRow (16) + +- CometProject (15) + +- CometFilter (14) +- CometScan parquet spark_catalog.default.store_sales (13) @@ -98,16 +98,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,21), LessThanOrEqual(ss_quantity,40)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 1] -Input [4]: [ss_quantity#38, ss_ext_discount_amt#39, ss_net_paid#40, ss_sold_date_sk#41] - -(15) Filter [codegen id : 1] +(14) CometFilter Input [4]: [ss_quantity#38, ss_ext_discount_amt#39, ss_net_paid#40, ss_sold_date_sk#41] Condition : ((isnotnull(ss_quantity#38) AND (ss_quantity#38 >= 21)) AND (ss_quantity#38 <= 40)) -(16) Project [codegen id : 1] -Output [2]: [ss_ext_discount_amt#39, ss_net_paid#40] +(15) CometProject Input [4]: [ss_quantity#38, ss_ext_discount_amt#39, ss_net_paid#40, ss_sold_date_sk#41] +Arguments: [ss_ext_discount_amt#39, ss_net_paid#40], [ss_ext_discount_amt#39, ss_net_paid#40] + +(16) ColumnarToRow [codegen id : 1] +Input [2]: [ss_ext_discount_amt#39, ss_net_paid#40] (17) HashAggregate [codegen id : 1] Input [2]: [ss_ext_discount_amt#39, ss_net_paid#40] @@ -140,9 +140,9 @@ Subquery:7 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquery +- * HashAggregate (27) +- Exchange (26) +- * HashAggregate (25) - +- * Project (24) - +- * Filter (23) - +- * ColumnarToRow (22) + +- * ColumnarToRow (24) + +- CometProject (23) + +- CometFilter (22) +- CometScan parquet spark_catalog.default.store_sales (21) @@ -153,16 +153,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,41), LessThanOrEqual(ss_quantity,60)] ReadSchema: struct -(22) ColumnarToRow [codegen id : 1] -Input [4]: [ss_quantity#59, ss_ext_discount_amt#60, ss_net_paid#61, ss_sold_date_sk#62] - -(23) Filter [codegen id : 1] +(22) CometFilter Input [4]: [ss_quantity#59, ss_ext_discount_amt#60, ss_net_paid#61, ss_sold_date_sk#62] Condition : ((isnotnull(ss_quantity#59) AND (ss_quantity#59 >= 41)) AND (ss_quantity#59 <= 60)) -(24) Project [codegen id : 1] -Output [2]: [ss_ext_discount_amt#60, ss_net_paid#61] +(23) CometProject Input [4]: [ss_quantity#59, ss_ext_discount_amt#60, ss_net_paid#61, ss_sold_date_sk#62] +Arguments: [ss_ext_discount_amt#60, ss_net_paid#61], [ss_ext_discount_amt#60, ss_net_paid#61] + +(24) ColumnarToRow [codegen id : 1] +Input [2]: [ss_ext_discount_amt#60, ss_net_paid#61] (25) HashAggregate [codegen id : 1] Input [2]: [ss_ext_discount_amt#60, ss_net_paid#61] @@ -195,9 +195,9 @@ Subquery:10 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquer +- * HashAggregate (35) +- Exchange (34) +- * HashAggregate (33) - +- * Project (32) - +- * Filter (31) - +- * ColumnarToRow (30) + +- * ColumnarToRow (32) + +- CometProject (31) + +- CometFilter (30) +- CometScan parquet spark_catalog.default.store_sales (29) @@ -208,16 +208,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,61), LessThanOrEqual(ss_quantity,80)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 1] -Input [4]: [ss_quantity#80, ss_ext_discount_amt#81, ss_net_paid#82, ss_sold_date_sk#83] - -(31) Filter [codegen id : 1] +(30) CometFilter Input [4]: [ss_quantity#80, ss_ext_discount_amt#81, ss_net_paid#82, ss_sold_date_sk#83] Condition : ((isnotnull(ss_quantity#80) AND (ss_quantity#80 >= 61)) AND (ss_quantity#80 <= 80)) -(32) Project [codegen id : 1] -Output [2]: [ss_ext_discount_amt#81, ss_net_paid#82] +(31) CometProject Input [4]: [ss_quantity#80, ss_ext_discount_amt#81, ss_net_paid#82, ss_sold_date_sk#83] +Arguments: [ss_ext_discount_amt#81, ss_net_paid#82], [ss_ext_discount_amt#81, ss_net_paid#82] + +(32) ColumnarToRow [codegen id : 1] +Input [2]: [ss_ext_discount_amt#81, ss_net_paid#82] (33) HashAggregate [codegen id : 1] Input [2]: [ss_ext_discount_amt#81, ss_net_paid#82] @@ -250,9 +250,9 @@ Subquery:13 Hosting operator id = 4 Hosting Expression = Subquery scalar-subquer +- * HashAggregate (43) +- Exchange (42) +- * HashAggregate (41) - +- * Project (40) - +- * Filter (39) - +- * ColumnarToRow (38) + +- * ColumnarToRow (40) + +- CometProject (39) + +- CometFilter (38) +- CometScan parquet spark_catalog.default.store_sales (37) @@ -263,16 +263,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_quantity), GreaterThanOrEqual(ss_quantity,81), LessThanOrEqual(ss_quantity,100)] ReadSchema: struct -(38) ColumnarToRow [codegen id : 1] -Input [4]: [ss_quantity#101, ss_ext_discount_amt#102, ss_net_paid#103, ss_sold_date_sk#104] - -(39) Filter [codegen id : 1] +(38) CometFilter Input [4]: [ss_quantity#101, ss_ext_discount_amt#102, ss_net_paid#103, ss_sold_date_sk#104] Condition : ((isnotnull(ss_quantity#101) AND (ss_quantity#101 >= 81)) AND (ss_quantity#101 <= 100)) -(40) Project [codegen id : 1] -Output [2]: [ss_ext_discount_amt#102, ss_net_paid#103] +(39) CometProject Input [4]: [ss_quantity#101, ss_ext_discount_amt#102, ss_net_paid#103, ss_sold_date_sk#104] +Arguments: [ss_ext_discount_amt#102, ss_net_paid#103], [ss_ext_discount_amt#102, ss_net_paid#103] + +(40) ColumnarToRow [codegen id : 1] +Input [2]: [ss_ext_discount_amt#102, ss_net_paid#103] (41) HashAggregate [codegen id : 1] Input [2]: [ss_ext_discount_amt#102, ss_net_paid#103] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/simplified.txt index 9e0a4a1ab..fdd3bd293 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q9/simplified.txt @@ -8,10 +8,10 @@ WholeStageCodegen (1) Exchange #1 WholeStageCodegen (1) HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] - Project [ss_ext_discount_amt,ss_net_paid] - Filter [ss_quantity] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_ext_discount_amt,ss_net_paid] + CometFilter [ss_quantity] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] ReusedSubquery [mergedValue] #1 ReusedSubquery [mergedValue] #1 @@ -23,10 +23,10 @@ WholeStageCodegen (1) Exchange #2 WholeStageCodegen (1) HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] - Project [ss_ext_discount_amt,ss_net_paid] - Filter [ss_quantity] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_ext_discount_amt,ss_net_paid] + CometFilter [ss_quantity] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] ReusedSubquery [mergedValue] #2 ReusedSubquery [mergedValue] #2 @@ -38,10 +38,10 @@ WholeStageCodegen (1) Exchange #3 WholeStageCodegen (1) HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] - Project [ss_ext_discount_amt,ss_net_paid] - Filter [ss_quantity] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_ext_discount_amt,ss_net_paid] + CometFilter [ss_quantity] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] ReusedSubquery [mergedValue] #3 ReusedSubquery [mergedValue] #3 @@ -53,10 +53,10 @@ WholeStageCodegen (1) Exchange #4 WholeStageCodegen (1) HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] - Project [ss_ext_discount_amt,ss_net_paid] - Filter [ss_quantity] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_ext_discount_amt,ss_net_paid] + CometFilter [ss_quantity] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] ReusedSubquery [mergedValue] #4 ReusedSubquery [mergedValue] #4 @@ -68,14 +68,14 @@ WholeStageCodegen (1) Exchange #5 WholeStageCodegen (1) HashAggregate [ss_ext_discount_amt,ss_net_paid] [count,sum,count,sum,count,count,sum,count,sum,count] - Project [ss_ext_discount_amt,ss_net_paid] - Filter [ss_quantity] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_ext_discount_amt,ss_net_paid] + CometFilter [ss_quantity] CometScan parquet spark_catalog.default.store_sales [ss_quantity,ss_ext_discount_amt,ss_net_paid,ss_sold_date_sk] ReusedSubquery [mergedValue] #5 ReusedSubquery [mergedValue] #5 - Filter [r_reason_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [r_reason_sk] CometScan parquet spark_catalog.default.reason [r_reason_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/explain.txt index c6d4a3c0b..fcfbca847 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/explain.txt @@ -10,24 +10,24 @@ : : +- * BroadcastHashJoin Inner BuildRight (17) : : :- * Project (11) : : : +- * BroadcastHashJoin Inner BuildRight (10) - : : : :- * Project (4) - : : : : +- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (4) + : : : : +- CometProject (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.web_sales (1) : : : +- BroadcastExchange (9) - : : : +- * Project (8) - : : : +- * Filter (7) - : : : +- * ColumnarToRow (6) + : : : +- * ColumnarToRow (8) + : : : +- CometProject (7) + : : : +- CometFilter (6) : : : +- CometScan parquet spark_catalog.default.household_demographics (5) : : +- BroadcastExchange (16) - : : +- * Project (15) - : : +- * Filter (14) - : : +- * ColumnarToRow (13) + : : +- * ColumnarToRow (15) + : : +- CometProject (14) + : : +- CometFilter (13) : : +- CometScan parquet spark_catalog.default.time_dim (12) : +- BroadcastExchange (23) - : +- * Project (22) - : +- * Filter (21) - : +- * ColumnarToRow (20) + : +- * ColumnarToRow (22) + : +- CometProject (21) + : +- CometFilter (20) : +- CometScan parquet spark_catalog.default.web_page (19) +- BroadcastExchange (49) +- * HashAggregate (48) @@ -39,15 +39,15 @@ : +- * BroadcastHashJoin Inner BuildRight (41) : :- * Project (35) : : +- * BroadcastHashJoin Inner BuildRight (34) - : : :- * Project (32) - : : : +- * Filter (31) - : : : +- * ColumnarToRow (30) + : : :- * ColumnarToRow (32) + : : : +- CometProject (31) + : : : +- CometFilter (30) : : : +- CometScan parquet spark_catalog.default.web_sales (29) : : +- ReusedExchange (33) : +- BroadcastExchange (40) - : +- * Project (39) - : +- * Filter (38) - : +- * ColumnarToRow (37) + : +- * ColumnarToRow (39) + : +- CometProject (38) + : +- CometFilter (37) : +- CometScan parquet spark_catalog.default.time_dim (36) +- ReusedExchange (43) @@ -59,16 +59,16 @@ Location [not included in comparison]/{warehouse_dir}/web_sales] PushedFilters: [IsNotNull(ws_ship_hdemo_sk), IsNotNull(ws_sold_time_sk), IsNotNull(ws_web_page_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] -Input [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, ws_sold_date_sk#4] - -(3) Filter [codegen id : 4] +(2) CometFilter Input [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, ws_sold_date_sk#4] Condition : ((isnotnull(ws_ship_hdemo_sk#2) AND isnotnull(ws_sold_time_sk#1)) AND isnotnull(ws_web_page_sk#3)) -(4) Project [codegen id : 4] -Output [3]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3] +(3) CometProject Input [4]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3, ws_sold_date_sk#4] +Arguments: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3], [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3] + +(4) ColumnarToRow [codegen id : 4] +Input [3]: [ws_sold_time_sk#1, ws_ship_hdemo_sk#2, ws_web_page_sk#3] (5) Scan parquet spark_catalog.default.household_demographics Output [2]: [hd_demo_sk#5, hd_dep_count#6] @@ -77,16 +77,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_dep_count), EqualTo(hd_dep_count,6), IsNotNull(hd_demo_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] -Input [2]: [hd_demo_sk#5, hd_dep_count#6] - -(7) Filter [codegen id : 1] +(6) CometFilter Input [2]: [hd_demo_sk#5, hd_dep_count#6] Condition : ((isnotnull(hd_dep_count#6) AND (hd_dep_count#6 = 6)) AND isnotnull(hd_demo_sk#5)) -(8) Project [codegen id : 1] -Output [1]: [hd_demo_sk#5] +(7) CometProject Input [2]: [hd_demo_sk#5, hd_dep_count#6] +Arguments: [hd_demo_sk#5], [hd_demo_sk#5] + +(8) ColumnarToRow [codegen id : 1] +Input [1]: [hd_demo_sk#5] (9) BroadcastExchange Input [1]: [hd_demo_sk#5] @@ -109,16 +109,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), GreaterThanOrEqual(t_hour,8), LessThanOrEqual(t_hour,9), IsNotNull(t_time_sk)] ReadSchema: struct -(13) ColumnarToRow [codegen id : 2] -Input [2]: [t_time_sk#7, t_hour#8] - -(14) Filter [codegen id : 2] +(13) CometFilter Input [2]: [t_time_sk#7, t_hour#8] Condition : (((isnotnull(t_hour#8) AND (t_hour#8 >= 8)) AND (t_hour#8 <= 9)) AND isnotnull(t_time_sk#7)) -(15) Project [codegen id : 2] -Output [1]: [t_time_sk#7] +(14) CometProject Input [2]: [t_time_sk#7, t_hour#8] +Arguments: [t_time_sk#7], [t_time_sk#7] + +(15) ColumnarToRow [codegen id : 2] +Input [1]: [t_time_sk#7] (16) BroadcastExchange Input [1]: [t_time_sk#7] @@ -141,16 +141,16 @@ Location [not included in comparison]/{warehouse_dir}/web_page] PushedFilters: [IsNotNull(wp_char_count), GreaterThanOrEqual(wp_char_count,5000), LessThanOrEqual(wp_char_count,5200), IsNotNull(wp_web_page_sk)] ReadSchema: struct -(20) ColumnarToRow [codegen id : 3] -Input [2]: [wp_web_page_sk#9, wp_char_count#10] - -(21) Filter [codegen id : 3] +(20) CometFilter Input [2]: [wp_web_page_sk#9, wp_char_count#10] Condition : (((isnotnull(wp_char_count#10) AND (wp_char_count#10 >= 5000)) AND (wp_char_count#10 <= 5200)) AND isnotnull(wp_web_page_sk#9)) -(22) Project [codegen id : 3] -Output [1]: [wp_web_page_sk#9] +(21) CometProject Input [2]: [wp_web_page_sk#9, wp_char_count#10] +Arguments: [wp_web_page_sk#9], [wp_web_page_sk#9] + +(22) ColumnarToRow [codegen id : 3] +Input [1]: [wp_web_page_sk#9] (23) BroadcastExchange Input [1]: [wp_web_page_sk#9] @@ -191,16 +191,16 @@ Location [not included in comparison]/{warehouse_dir}/web_sales] PushedFilters: [IsNotNull(ws_ship_hdemo_sk), IsNotNull(ws_sold_time_sk), IsNotNull(ws_web_page_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 8] -Input [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, ws_sold_date_sk#18] - -(31) Filter [codegen id : 8] +(30) CometFilter Input [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, ws_sold_date_sk#18] Condition : ((isnotnull(ws_ship_hdemo_sk#16) AND isnotnull(ws_sold_time_sk#15)) AND isnotnull(ws_web_page_sk#17)) -(32) Project [codegen id : 8] -Output [3]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17] +(31) CometProject Input [4]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17, ws_sold_date_sk#18] +Arguments: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17], [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17] + +(32) ColumnarToRow [codegen id : 8] +Input [3]: [ws_sold_time_sk#15, ws_ship_hdemo_sk#16, ws_web_page_sk#17] (33) ReusedExchange [Reuses operator id: 9] Output [1]: [hd_demo_sk#19] @@ -222,16 +222,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), GreaterThanOrEqual(t_hour,19), LessThanOrEqual(t_hour,20), IsNotNull(t_time_sk)] ReadSchema: struct -(37) ColumnarToRow [codegen id : 6] -Input [2]: [t_time_sk#20, t_hour#21] - -(38) Filter [codegen id : 6] +(37) CometFilter Input [2]: [t_time_sk#20, t_hour#21] Condition : (((isnotnull(t_hour#21) AND (t_hour#21 >= 19)) AND (t_hour#21 <= 20)) AND isnotnull(t_time_sk#20)) -(39) Project [codegen id : 6] -Output [1]: [t_time_sk#20] +(38) CometProject Input [2]: [t_time_sk#20, t_hour#21] +Arguments: [t_time_sk#20], [t_time_sk#20] + +(39) ColumnarToRow [codegen id : 6] +Input [1]: [t_time_sk#20] (40) BroadcastExchange Input [1]: [t_time_sk#20] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/simplified.txt index 3f9582bb0..c4e04b06b 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q90/simplified.txt @@ -12,34 +12,34 @@ WholeStageCodegen (10) BroadcastHashJoin [ws_sold_time_sk,t_time_sk] Project [ws_sold_time_sk,ws_web_page_sk] BroadcastHashJoin [ws_ship_hdemo_sk,hd_demo_sk] - Project [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk] - Filter [ws_ship_hdemo_sk,ws_sold_time_sk,ws_web_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk] + CometFilter [ws_ship_hdemo_sk,ws_sold_time_sk,ws_web_page_sk] CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk,ws_sold_date_sk] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Project [hd_demo_sk] - Filter [hd_dep_count,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [t_time_sk] - Filter [t_hour,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Project [wp_web_page_sk] - Filter [wp_char_count,wp_web_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [wp_web_page_sk] + CometFilter [wp_char_count,wp_web_page_sk] CometScan parquet spark_catalog.default.web_page [wp_web_page_sk,wp_char_count] InputAdapter BroadcastExchange #5 @@ -55,20 +55,20 @@ WholeStageCodegen (10) BroadcastHashJoin [ws_sold_time_sk,t_time_sk] Project [ws_sold_time_sk,ws_web_page_sk] BroadcastHashJoin [ws_ship_hdemo_sk,hd_demo_sk] - Project [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk] - Filter [ws_ship_hdemo_sk,ws_sold_time_sk,ws_web_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk] + CometFilter [ws_ship_hdemo_sk,ws_sold_time_sk,ws_web_page_sk] CometScan parquet spark_catalog.default.web_sales [ws_sold_time_sk,ws_ship_hdemo_sk,ws_web_page_sk,ws_sold_date_sk] InputAdapter ReusedExchange [hd_demo_sk] #2 InputAdapter BroadcastExchange #7 WholeStageCodegen (6) - Project [t_time_sk] - Filter [t_hour,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour] InputAdapter ReusedExchange [wp_web_page_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/explain.txt index 521373bf7..61f35489a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/explain.txt @@ -16,31 +16,31 @@ : : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : : :- * Project (9) : : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : : :- * Filter (3) - : : : : : : +- * ColumnarToRow (2) + : : : : : :- * ColumnarToRow (3) + : : : : : : +- CometFilter (2) : : : : : : +- CometScan parquet spark_catalog.default.call_center (1) : : : : : +- BroadcastExchange (7) - : : : : : +- * Filter (6) - : : : : : +- * ColumnarToRow (5) + : : : : : +- * ColumnarToRow (6) + : : : : : +- CometFilter (5) : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (4) : : : : +- ReusedExchange (10) : : : +- BroadcastExchange (16) - : : : +- * Filter (15) - : : : +- * ColumnarToRow (14) + : : : +- * ColumnarToRow (15) + : : : +- CometFilter (14) : : : +- CometScan parquet spark_catalog.default.customer (13) : : +- BroadcastExchange (23) - : : +- * Project (22) - : : +- * Filter (21) - : : +- * ColumnarToRow (20) + : : +- * ColumnarToRow (22) + : : +- CometProject (21) + : : +- CometFilter (20) : : +- CometScan parquet spark_catalog.default.customer_address (19) : +- BroadcastExchange (29) - : +- * Filter (28) - : +- * ColumnarToRow (27) + : +- * ColumnarToRow (28) + : +- CometFilter (27) : +- CometScan parquet spark_catalog.default.customer_demographics (26) +- BroadcastExchange (36) - +- * Project (35) - +- * Filter (34) - +- * ColumnarToRow (33) + +- * ColumnarToRow (35) + +- CometProject (34) + +- CometFilter (33) +- CometScan parquet spark_catalog.default.household_demographics (32) @@ -51,12 +51,12 @@ Location [not included in comparison]/{warehouse_dir}/call_center] PushedFilters: [IsNotNull(cc_call_center_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 7] +(2) CometFilter Input [4]: [cc_call_center_sk#1, cc_call_center_id#2, cc_name#3, cc_manager#4] +Condition : isnotnull(cc_call_center_sk#1) -(3) Filter [codegen id : 7] +(3) ColumnarToRow [codegen id : 7] Input [4]: [cc_call_center_sk#1, cc_call_center_id#2, cc_name#3, cc_manager#4] -Condition : isnotnull(cc_call_center_sk#1) (4) Scan parquet spark_catalog.default.catalog_returns Output [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] @@ -66,12 +66,12 @@ PartitionFilters: [isnotnull(cr_returned_date_sk#8), dynamicpruningexpression(cr PushedFilters: [IsNotNull(cr_call_center_sk), IsNotNull(cr_returning_customer_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] +Condition : (isnotnull(cr_call_center_sk#6) AND isnotnull(cr_returning_customer_sk#5)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] -Condition : (isnotnull(cr_call_center_sk#6) AND isnotnull(cr_returning_customer_sk#5)) (7) BroadcastExchange Input [4]: [cr_returning_customer_sk#5, cr_call_center_sk#6, cr_net_loss#7, cr_returned_date_sk#8] @@ -107,12 +107,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] +Condition : (((isnotnull(c_customer_sk#11) AND isnotnull(c_current_addr_sk#14)) AND isnotnull(c_current_cdemo_sk#12)) AND isnotnull(c_current_hdemo_sk#13)) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] -Condition : (((isnotnull(c_customer_sk#11) AND isnotnull(c_current_addr_sk#14)) AND isnotnull(c_current_cdemo_sk#12)) AND isnotnull(c_current_hdemo_sk#13)) (16) BroadcastExchange Input [4]: [c_customer_sk#11, c_current_cdemo_sk#12, c_current_hdemo_sk#13, c_current_addr_sk#14] @@ -135,16 +135,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_gmt_offset), EqualTo(ca_gmt_offset,-7.00), IsNotNull(ca_address_sk)] ReadSchema: struct -(20) ColumnarToRow [codegen id : 4] -Input [2]: [ca_address_sk#15, ca_gmt_offset#16] - -(21) Filter [codegen id : 4] +(20) CometFilter Input [2]: [ca_address_sk#15, ca_gmt_offset#16] Condition : ((isnotnull(ca_gmt_offset#16) AND (ca_gmt_offset#16 = -7.00)) AND isnotnull(ca_address_sk#15)) -(22) Project [codegen id : 4] -Output [1]: [ca_address_sk#15] +(21) CometProject Input [2]: [ca_address_sk#15, ca_gmt_offset#16] +Arguments: [ca_address_sk#15], [ca_address_sk#15] + +(22) ColumnarToRow [codegen id : 4] +Input [1]: [ca_address_sk#15] (23) BroadcastExchange Input [1]: [ca_address_sk#15] @@ -167,12 +167,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,Unknown )),And(EqualTo(cd_marital_status,W),EqualTo(cd_education_status,Advanced Degree ))), IsNotNull(cd_demo_sk)] ReadSchema: struct -(27) ColumnarToRow [codegen id : 5] +(27) CometFilter Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] +Condition : ((((cd_marital_status#18 = M) AND (cd_education_status#19 = Unknown )) OR ((cd_marital_status#18 = W) AND (cd_education_status#19 = Advanced Degree ))) AND isnotnull(cd_demo_sk#17)) -(28) Filter [codegen id : 5] +(28) ColumnarToRow [codegen id : 5] Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] -Condition : ((((cd_marital_status#18 = M) AND (cd_education_status#19 = Unknown )) OR ((cd_marital_status#18 = W) AND (cd_education_status#19 = Advanced Degree ))) AND isnotnull(cd_demo_sk#17)) (29) BroadcastExchange Input [3]: [cd_demo_sk#17, cd_marital_status#18, cd_education_status#19] @@ -195,16 +195,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_buy_potential), StringStartsWith(hd_buy_potential,Unknown), IsNotNull(hd_demo_sk)] ReadSchema: struct -(33) ColumnarToRow [codegen id : 6] -Input [2]: [hd_demo_sk#20, hd_buy_potential#21] - -(34) Filter [codegen id : 6] +(33) CometFilter Input [2]: [hd_demo_sk#20, hd_buy_potential#21] Condition : ((isnotnull(hd_buy_potential#21) AND StartsWith(hd_buy_potential#21, Unknown)) AND isnotnull(hd_demo_sk#20)) -(35) Project [codegen id : 6] -Output [1]: [hd_demo_sk#20] +(34) CometProject Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Arguments: [hd_demo_sk#20], [hd_demo_sk#20] + +(35) ColumnarToRow [codegen id : 6] +Input [1]: [hd_demo_sk#20] (36) BroadcastExchange Input [1]: [hd_demo_sk#20] @@ -250,9 +250,9 @@ Arguments: [Returns_Loss#28 DESC NULLS LAST], true, 0 Subquery:1 Hosting operator id = 4 Hosting Expression = cr_returned_date_sk#8 IN dynamicpruning#9 BroadcastExchange (48) -+- * Project (47) - +- * Filter (46) - +- * ColumnarToRow (45) ++- * ColumnarToRow (47) + +- CometProject (46) + +- CometFilter (45) +- CometScan parquet spark_catalog.default.date_dim (44) @@ -263,16 +263,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,1998), EqualTo(d_moy,11), IsNotNull(d_date_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#10, d_year#29, d_moy#30] - -(46) Filter [codegen id : 1] +(45) CometFilter Input [3]: [d_date_sk#10, d_year#29, d_moy#30] Condition : ((((isnotnull(d_year#29) AND isnotnull(d_moy#30)) AND (d_year#29 = 1998)) AND (d_moy#30 = 11)) AND isnotnull(d_date_sk#10)) -(47) Project [codegen id : 1] -Output [1]: [d_date_sk#10] +(46) CometProject Input [3]: [d_date_sk#10, d_year#29, d_moy#30] +Arguments: [d_date_sk#10], [d_date_sk#10] + +(47) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#10] (48) BroadcastExchange Input [1]: [d_date_sk#10] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/simplified.txt index d40b04b59..e5d62e3c0 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q91/simplified.txt @@ -20,54 +20,54 @@ WholeStageCodegen (9) BroadcastHashJoin [cr_returned_date_sk,d_date_sk] Project [cc_call_center_id,cc_name,cc_manager,cr_returning_customer_sk,cr_net_loss,cr_returned_date_sk] BroadcastHashJoin [cc_call_center_sk,cr_call_center_sk] - Filter [cc_call_center_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cc_call_center_sk] CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_call_center_id,cc_name,cc_manager] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [cr_call_center_sk,cr_returning_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cr_call_center_sk,cr_returning_customer_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_returning_customer_sk,cr_call_center_sk,cr_net_loss,cr_returned_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [c_customer_sk,c_current_addr_sk,c_current_cdemo_sk,c_current_hdemo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk,c_current_cdemo_sk,c_current_hdemo_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] InputAdapter BroadcastExchange #6 WholeStageCodegen (4) - Project [ca_address_sk] - Filter [ca_gmt_offset,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_gmt_offset,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_gmt_offset] InputAdapter BroadcastExchange #7 WholeStageCodegen (5) - Filter [cd_marital_status,cd_education_status,cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_marital_status,cd_education_status,cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status,cd_education_status] InputAdapter BroadcastExchange #8 WholeStageCodegen (6) - Project [hd_demo_sk] - Filter [hd_buy_potential,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_buy_potential,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/explain.txt index 204b23130..5f1f96168 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/explain.txt @@ -8,13 +8,13 @@ : +- * BroadcastHashJoin Inner BuildRight (22) : :- * Project (10) : : +- * BroadcastHashJoin Inner BuildRight (9) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.web_sales (1) : : +- BroadcastExchange (8) - : : +- * Project (7) - : : +- * Filter (6) - : : +- * ColumnarToRow (5) + : : +- * ColumnarToRow (7) + : : +- CometProject (6) + : : +- CometFilter (5) : : +- CometScan parquet spark_catalog.default.item (4) : +- BroadcastExchange (21) : +- * Filter (20) @@ -23,8 +23,8 @@ : +- * HashAggregate (17) : +- * Project (16) : +- * BroadcastHashJoin Inner BuildRight (15) - : :- * Filter (13) - : : +- * ColumnarToRow (12) + : :- * ColumnarToRow (13) + : : +- CometFilter (12) : : +- CometScan parquet spark_catalog.default.web_sales (11) : +- ReusedExchange (14) +- ReusedExchange (24) @@ -38,12 +38,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_ext_discount_amt)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 6] +(2) CometFilter Input [3]: [ws_item_sk#1, ws_ext_discount_amt#2, ws_sold_date_sk#3] +Condition : (isnotnull(ws_item_sk#1) AND isnotnull(ws_ext_discount_amt#2)) -(3) Filter [codegen id : 6] +(3) ColumnarToRow [codegen id : 6] Input [3]: [ws_item_sk#1, ws_ext_discount_amt#2, ws_sold_date_sk#3] -Condition : (isnotnull(ws_item_sk#1) AND isnotnull(ws_ext_discount_amt#2)) (4) Scan parquet spark_catalog.default.item Output [2]: [i_item_sk#5, i_manufact_id#6] @@ -52,16 +52,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_manufact_id), EqualTo(i_manufact_id,350), IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [2]: [i_item_sk#5, i_manufact_id#6] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [2]: [i_item_sk#5, i_manufact_id#6] Condition : ((isnotnull(i_manufact_id#6) AND (i_manufact_id#6 = 350)) AND isnotnull(i_item_sk#5)) -(7) Project [codegen id : 1] -Output [1]: [i_item_sk#5] +(6) CometProject Input [2]: [i_item_sk#5, i_manufact_id#6] +Arguments: [i_item_sk#5], [i_item_sk#5] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [i_item_sk#5] (8) BroadcastExchange Input [1]: [i_item_sk#5] @@ -85,12 +85,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#9), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 3] +(12) CometFilter Input [3]: [ws_item_sk#7, ws_ext_discount_amt#8, ws_sold_date_sk#9] +Condition : isnotnull(ws_item_sk#7) -(13) Filter [codegen id : 3] +(13) ColumnarToRow [codegen id : 3] Input [3]: [ws_item_sk#7, ws_ext_discount_amt#8, ws_sold_date_sk#9] -Condition : isnotnull(ws_item_sk#7) (14) ReusedExchange [Reuses operator id: 34] Output [1]: [d_date_sk#11] @@ -176,9 +176,9 @@ Results [1]: [MakeDecimal(sum(UnscaledValue(ws_ext_discount_amt#2))#21,17,2) AS Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (34) -+- * Project (33) - +- * Filter (32) - +- * ColumnarToRow (31) ++- * ColumnarToRow (33) + +- CometProject (32) + +- CometFilter (31) +- CometScan parquet spark_catalog.default.date_dim (30) @@ -189,16 +189,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-01-27), LessThanOrEqual(d_date,2000-04-26), IsNotNull(d_date_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#18, d_date#23] - -(32) Filter [codegen id : 1] +(31) CometFilter Input [2]: [d_date_sk#18, d_date#23] Condition : (((isnotnull(d_date#23) AND (d_date#23 >= 2000-01-27)) AND (d_date#23 <= 2000-04-26)) AND isnotnull(d_date_sk#18)) -(33) Project [codegen id : 1] -Output [1]: [d_date_sk#18] +(32) CometProject Input [2]: [d_date_sk#18, d_date#23] +Arguments: [d_date_sk#18], [d_date_sk#18] + +(33) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#18] (34) BroadcastExchange Input [1]: [d_date_sk#18] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/simplified.txt index 33d262f07..a5e724c1f 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q92/simplified.txt @@ -10,25 +10,25 @@ WholeStageCodegen (7) BroadcastHashJoin [i_item_sk,ws_item_sk,ws_ext_discount_amt,(1.3 * avg(ws_ext_discount_amt))] Project [ws_ext_discount_amt,ws_sold_date_sk,i_item_sk] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk,ws_ext_discount_amt] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk,ws_ext_discount_amt] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_discount_amt,ws_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [i_item_sk] - Filter [i_manufact_id,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_manufact_id,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_manufact_id] InputAdapter BroadcastExchange #4 @@ -41,9 +41,9 @@ WholeStageCodegen (7) HashAggregate [ws_item_sk,ws_ext_discount_amt] [sum,count,sum,count] Project [ws_item_sk,ws_ext_discount_amt] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_discount_amt,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/explain.txt index 121f25701..00ed822f2 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/explain.txt @@ -9,19 +9,19 @@ TakeOrderedAndProject (24) : +- * SortMergeJoin Inner (12) : :- * Sort (5) : : +- Exchange (4) - : : +- * Project (3) - : : +- * ColumnarToRow (2) + : : +- * ColumnarToRow (3) + : : +- CometProject (2) : : +- CometScan parquet spark_catalog.default.store_sales (1) : +- * Sort (11) : +- Exchange (10) - : +- * Project (9) - : +- * Filter (8) - : +- * ColumnarToRow (7) + : +- * ColumnarToRow (9) + : +- CometProject (8) + : +- CometFilter (7) : +- CometScan parquet spark_catalog.default.store_returns (6) +- BroadcastExchange (18) - +- * Project (17) - +- * Filter (16) - +- * ColumnarToRow (15) + +- * ColumnarToRow (17) + +- CometProject (16) + +- CometFilter (15) +- CometScan parquet spark_catalog.default.reason (14) @@ -31,12 +31,12 @@ Batched: true Location [not included in comparison]/{warehouse_dir}/store_sales] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] +(2) CometProject Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5, ss_sold_date_sk#6] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5], [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] -(3) Project [codegen id : 1] -Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] -Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5, ss_sold_date_sk#6] +(3) ColumnarToRow [codegen id : 1] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] (4) Exchange Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_sales_price#5] @@ -53,16 +53,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number), IsNotNull(sr_reason_sk)] ReadSchema: struct -(7) ColumnarToRow [codegen id : 3] -Input [5]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11] - -(8) Filter [codegen id : 3] +(7) CometFilter Input [5]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11] Condition : ((isnotnull(sr_item_sk#7) AND isnotnull(sr_ticket_number#9)) AND isnotnull(sr_reason_sk#8)) -(9) Project [codegen id : 3] -Output [4]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] +(8) CometProject Input [5]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11] +Arguments: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10], [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] + +(9) ColumnarToRow [codegen id : 3] +Input [4]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] (10) Exchange Input [4]: [sr_item_sk#7, sr_reason_sk#8, sr_ticket_number#9, sr_return_quantity#10] @@ -89,16 +89,16 @@ Location [not included in comparison]/{warehouse_dir}/reason] PushedFilters: [IsNotNull(r_reason_desc), EqualTo(r_reason_desc,reason 28 ), IsNotNull(r_reason_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 5] -Input [2]: [r_reason_sk#12, r_reason_desc#13] - -(16) Filter [codegen id : 5] +(15) CometFilter Input [2]: [r_reason_sk#12, r_reason_desc#13] Condition : ((isnotnull(r_reason_desc#13) AND (r_reason_desc#13 = reason 28 )) AND isnotnull(r_reason_sk#12)) -(17) Project [codegen id : 5] -Output [1]: [r_reason_sk#12] +(16) CometProject Input [2]: [r_reason_sk#12, r_reason_desc#13] +Arguments: [r_reason_sk#12], [r_reason_sk#12] + +(17) ColumnarToRow [codegen id : 5] +Input [1]: [r_reason_sk#12] (18) BroadcastExchange Input [1]: [r_reason_sk#12] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/simplified.txt index 775e14725..3ec7ac7b6 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q93/simplified.txt @@ -15,9 +15,9 @@ TakeOrderedAndProject [sumsales,ss_customer_sk] InputAdapter Exchange [ss_item_sk,ss_ticket_number] #2 WholeStageCodegen (1) - Project [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_sales_price] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_sales_price] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_sales_price,ss_sold_date_sk] InputAdapter WholeStageCodegen (4) @@ -25,16 +25,16 @@ TakeOrderedAndProject [sumsales,ss_customer_sk] InputAdapter Exchange [sr_item_sk,sr_ticket_number] #3 WholeStageCodegen (3) - Project [sr_item_sk,sr_reason_sk,sr_ticket_number,sr_return_quantity] - Filter [sr_item_sk,sr_ticket_number,sr_reason_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_reason_sk,sr_ticket_number,sr_return_quantity] + CometFilter [sr_item_sk,sr_ticket_number,sr_reason_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_reason_sk,sr_ticket_number,sr_return_quantity,sr_returned_date_sk] InputAdapter BroadcastExchange #4 WholeStageCodegen (5) - Project [r_reason_sk] - Filter [r_reason_desc,r_reason_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [r_reason_sk] + CometFilter [r_reason_desc,r_reason_sk] CometScan parquet spark_catalog.default.reason [r_reason_sk,r_reason_desc] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/explain.txt index 180e7e033..d71f96e15 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/explain.txt @@ -15,34 +15,34 @@ : : : : +- * SortMergeJoin LeftSemi (12) : : : : :- * Sort (6) : : : : : +- Exchange (5) - : : : : : +- * Project (4) - : : : : : +- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) : : : : +- * Sort (11) : : : : +- Exchange (10) - : : : : +- * Project (9) - : : : : +- * ColumnarToRow (8) + : : : : +- * ColumnarToRow (9) + : : : : +- CometProject (8) : : : : +- CometScan parquet spark_catalog.default.web_sales (7) : : : +- * Sort (18) : : : +- Exchange (17) - : : : +- * Project (16) - : : : +- * ColumnarToRow (15) + : : : +- * ColumnarToRow (16) + : : : +- CometProject (15) : : : +- CometScan parquet spark_catalog.default.web_returns (14) : : +- BroadcastExchange (24) - : : +- * Project (23) - : : +- * Filter (22) - : : +- * ColumnarToRow (21) + : : +- * ColumnarToRow (23) + : : +- CometProject (22) + : : +- CometFilter (21) : : +- CometScan parquet spark_catalog.default.date_dim (20) : +- BroadcastExchange (31) - : +- * Project (30) - : +- * Filter (29) - : +- * ColumnarToRow (28) + : +- * ColumnarToRow (30) + : +- CometProject (29) + : +- CometFilter (28) : +- CometScan parquet spark_catalog.default.customer_address (27) +- BroadcastExchange (38) - +- * Project (37) - +- * Filter (36) - +- * ColumnarToRow (35) + +- * ColumnarToRow (37) + +- CometProject (36) + +- CometFilter (35) +- CometScan parquet spark_catalog.default.web_site (34) @@ -53,16 +53,16 @@ Location [not included in comparison]/{warehouse_dir}/web_sales] PushedFilters: [IsNotNull(ws_ship_date_sk), IsNotNull(ws_ship_addr_sk), IsNotNull(ws_web_site_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [8]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ws_sold_date_sk#8] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [8]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ws_sold_date_sk#8] Condition : ((isnotnull(ws_ship_date_sk#1) AND isnotnull(ws_ship_addr_sk#2)) AND isnotnull(ws_web_site_sk#3)) -(4) Project [codegen id : 1] -Output [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] +(3) CometProject Input [8]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7, ws_sold_date_sk#8] +Arguments: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7], [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] + +(4) ColumnarToRow [codegen id : 1] +Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] (5) Exchange Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_warehouse_sk#4, ws_order_number#5, ws_ext_ship_cost#6, ws_net_profit#7] @@ -78,12 +78,12 @@ Batched: true Location [not included in comparison]/{warehouse_dir}/web_sales] ReadSchema: struct -(8) ColumnarToRow [codegen id : 3] +(8) CometProject Input [3]: [ws_warehouse_sk#9, ws_order_number#10, ws_sold_date_sk#11] +Arguments: [ws_warehouse_sk#9, ws_order_number#10], [ws_warehouse_sk#9, ws_order_number#10] -(9) Project [codegen id : 3] -Output [2]: [ws_warehouse_sk#9, ws_order_number#10] -Input [3]: [ws_warehouse_sk#9, ws_order_number#10, ws_sold_date_sk#11] +(9) ColumnarToRow [codegen id : 3] +Input [2]: [ws_warehouse_sk#9, ws_order_number#10] (10) Exchange Input [2]: [ws_warehouse_sk#9, ws_order_number#10] @@ -109,12 +109,12 @@ Batched: true Location [not included in comparison]/{warehouse_dir}/web_returns] ReadSchema: struct -(15) ColumnarToRow [codegen id : 6] +(15) CometProject Input [2]: [wr_order_number#12, wr_returned_date_sk#13] +Arguments: [wr_order_number#12], [wr_order_number#12] -(16) Project [codegen id : 6] -Output [1]: [wr_order_number#12] -Input [2]: [wr_order_number#12, wr_returned_date_sk#13] +(16) ColumnarToRow [codegen id : 6] +Input [1]: [wr_order_number#12] (17) Exchange Input [1]: [wr_order_number#12] @@ -137,16 +137,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-01), LessThanOrEqual(d_date,1999-04-02), IsNotNull(d_date_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 8] -Input [2]: [d_date_sk#14, d_date#15] - -(22) Filter [codegen id : 8] +(21) CometFilter Input [2]: [d_date_sk#14, d_date#15] Condition : (((isnotnull(d_date#15) AND (d_date#15 >= 1999-02-01)) AND (d_date#15 <= 1999-04-02)) AND isnotnull(d_date_sk#14)) -(23) Project [codegen id : 8] -Output [1]: [d_date_sk#14] +(22) CometProject Input [2]: [d_date_sk#14, d_date#15] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(23) ColumnarToRow [codegen id : 8] +Input [1]: [d_date_sk#14] (24) BroadcastExchange Input [1]: [d_date_sk#14] @@ -169,16 +169,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,IL), IsNotNull(ca_address_sk)] ReadSchema: struct -(28) ColumnarToRow [codegen id : 9] -Input [2]: [ca_address_sk#16, ca_state#17] - -(29) Filter [codegen id : 9] +(28) CometFilter Input [2]: [ca_address_sk#16, ca_state#17] Condition : ((isnotnull(ca_state#17) AND (ca_state#17 = IL)) AND isnotnull(ca_address_sk#16)) -(30) Project [codegen id : 9] -Output [1]: [ca_address_sk#16] +(29) CometProject Input [2]: [ca_address_sk#16, ca_state#17] +Arguments: [ca_address_sk#16], [ca_address_sk#16] + +(30) ColumnarToRow [codegen id : 9] +Input [1]: [ca_address_sk#16] (31) BroadcastExchange Input [1]: [ca_address_sk#16] @@ -201,16 +201,16 @@ Location [not included in comparison]/{warehouse_dir}/web_site] PushedFilters: [IsNotNull(web_company_name), EqualTo(web_company_name,pri ), IsNotNull(web_site_sk)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 10] -Input [2]: [web_site_sk#18, web_company_name#19] - -(36) Filter [codegen id : 10] +(35) CometFilter Input [2]: [web_site_sk#18, web_company_name#19] Condition : ((isnotnull(web_company_name#19) AND (web_company_name#19 = pri )) AND isnotnull(web_site_sk#18)) -(37) Project [codegen id : 10] -Output [1]: [web_site_sk#18] +(36) CometProject Input [2]: [web_site_sk#18, web_company_name#19] +Arguments: [web_site_sk#18], [web_site_sk#18] + +(37) ColumnarToRow [codegen id : 10] +Input [1]: [web_site_sk#18] (38) BroadcastExchange Input [1]: [web_site_sk#18] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/simplified.txt index 1aa3b4dc1..34ddde768 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q94/simplified.txt @@ -23,10 +23,10 @@ WholeStageCodegen (12) InputAdapter Exchange [ws_order_number] #2 WholeStageCodegen (1) - Project [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_warehouse_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] - Filter [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_warehouse_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + CometFilter [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk] CometScan parquet spark_catalog.default.web_sales [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_warehouse_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit,ws_sold_date_sk] InputAdapter WholeStageCodegen (4) @@ -34,9 +34,9 @@ WholeStageCodegen (12) InputAdapter Exchange [ws_order_number] #3 WholeStageCodegen (3) - Project [ws_warehouse_sk,ws_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ws_warehouse_sk,ws_order_number] CometScan parquet spark_catalog.default.web_sales [ws_warehouse_sk,ws_order_number,ws_sold_date_sk] InputAdapter WholeStageCodegen (7) @@ -44,31 +44,31 @@ WholeStageCodegen (12) InputAdapter Exchange [wr_order_number] #4 WholeStageCodegen (6) - Project [wr_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [wr_order_number] CometScan parquet spark_catalog.default.web_returns [wr_order_number,wr_returned_date_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (8) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #6 WholeStageCodegen (9) - Project [ca_address_sk] - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #7 WholeStageCodegen (10) - Project [web_site_sk] - Filter [web_company_name,web_site_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [web_site_sk] + CometFilter [web_company_name,web_site_sk] CometScan parquet spark_catalog.default.web_site [web_site_sk,web_company_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/explain.txt index f8ee8ccb8..c8cdce055 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/explain.txt @@ -14,17 +14,17 @@ : : : :- * SortMergeJoin LeftSemi (17) : : : : :- * Sort (6) : : : : : +- Exchange (5) - : : : : : +- * Project (4) - : : : : : +- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.web_sales (1) : : : : +- * Project (16) : : : : +- * SortMergeJoin Inner (15) : : : : :- * Sort (12) : : : : : +- Exchange (11) - : : : : : +- * Project (10) - : : : : : +- * Filter (9) - : : : : : +- * ColumnarToRow (8) + : : : : : +- * ColumnarToRow (10) + : : : : : +- CometProject (9) + : : : : : +- CometFilter (8) : : : : : +- CometScan parquet spark_catalog.default.web_sales (7) : : : : +- * Sort (14) : : : : +- ReusedExchange (13) @@ -32,9 +32,9 @@ : : : +- * SortMergeJoin Inner (30) : : : :- * Sort (23) : : : : +- Exchange (22) - : : : : +- * Project (21) - : : : : +- * Filter (20) - : : : : +- * ColumnarToRow (19) + : : : : +- * ColumnarToRow (21) + : : : : +- CometProject (20) + : : : : +- CometFilter (19) : : : : +- CometScan parquet spark_catalog.default.web_returns (18) : : : +- * Project (29) : : : +- * SortMergeJoin Inner (28) @@ -43,19 +43,19 @@ : : : +- * Sort (27) : : : +- ReusedExchange (26) : : +- BroadcastExchange (37) - : : +- * Project (36) - : : +- * Filter (35) - : : +- * ColumnarToRow (34) + : : +- * ColumnarToRow (36) + : : +- CometProject (35) + : : +- CometFilter (34) : : +- CometScan parquet spark_catalog.default.date_dim (33) : +- BroadcastExchange (44) - : +- * Project (43) - : +- * Filter (42) - : +- * ColumnarToRow (41) + : +- * ColumnarToRow (43) + : +- CometProject (42) + : +- CometFilter (41) : +- CometScan parquet spark_catalog.default.customer_address (40) +- BroadcastExchange (51) - +- * Project (50) - +- * Filter (49) - +- * ColumnarToRow (48) + +- * ColumnarToRow (50) + +- CometProject (49) + +- CometFilter (48) +- CometScan parquet spark_catalog.default.web_site (47) @@ -66,16 +66,16 @@ Location [not included in comparison]/{warehouse_dir}/web_sales] PushedFilters: [IsNotNull(ws_ship_date_sk), IsNotNull(ws_ship_addr_sk), IsNotNull(ws_web_site_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ws_sold_date_sk#7] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ws_sold_date_sk#7] Condition : ((isnotnull(ws_ship_date_sk#1) AND isnotnull(ws_ship_addr_sk#2)) AND isnotnull(ws_web_site_sk#3)) -(4) Project [codegen id : 1] -Output [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] +(3) CometProject Input [7]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6, ws_sold_date_sk#7] +Arguments: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6], [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] + +(4) ColumnarToRow [codegen id : 1] +Input [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] (5) Exchange Input [6]: [ws_ship_date_sk#1, ws_ship_addr_sk#2, ws_web_site_sk#3, ws_order_number#4, ws_ext_ship_cost#5, ws_net_profit#6] @@ -92,16 +92,16 @@ Location [not included in comparison]/{warehouse_dir}/web_sales] PushedFilters: [IsNotNull(ws_order_number), IsNotNull(ws_warehouse_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 3] -Input [3]: [ws_warehouse_sk#8, ws_order_number#9, ws_sold_date_sk#10] - -(9) Filter [codegen id : 3] +(8) CometFilter Input [3]: [ws_warehouse_sk#8, ws_order_number#9, ws_sold_date_sk#10] Condition : (isnotnull(ws_order_number#9) AND isnotnull(ws_warehouse_sk#8)) -(10) Project [codegen id : 3] -Output [2]: [ws_warehouse_sk#8, ws_order_number#9] +(9) CometProject Input [3]: [ws_warehouse_sk#8, ws_order_number#9, ws_sold_date_sk#10] +Arguments: [ws_warehouse_sk#8, ws_order_number#9], [ws_warehouse_sk#8, ws_order_number#9] + +(10) ColumnarToRow [codegen id : 3] +Input [2]: [ws_warehouse_sk#8, ws_order_number#9] (11) Exchange Input [2]: [ws_warehouse_sk#8, ws_order_number#9] @@ -141,16 +141,16 @@ Location [not included in comparison]/{warehouse_dir}/web_returns] PushedFilters: [IsNotNull(wr_order_number)] ReadSchema: struct -(19) ColumnarToRow [codegen id : 9] -Input [2]: [wr_order_number#13, wr_returned_date_sk#14] - -(20) Filter [codegen id : 9] +(19) CometFilter Input [2]: [wr_order_number#13, wr_returned_date_sk#14] Condition : isnotnull(wr_order_number#13) -(21) Project [codegen id : 9] -Output [1]: [wr_order_number#13] +(20) CometProject Input [2]: [wr_order_number#13, wr_returned_date_sk#14] +Arguments: [wr_order_number#13], [wr_order_number#13] + +(21) ColumnarToRow [codegen id : 9] +Input [1]: [wr_order_number#13] (22) Exchange Input [1]: [wr_order_number#13] @@ -207,16 +207,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-01), LessThanOrEqual(d_date,1999-04-02), IsNotNull(d_date_sk)] ReadSchema: struct -(34) ColumnarToRow [codegen id : 17] -Input [2]: [d_date_sk#19, d_date#20] - -(35) Filter [codegen id : 17] +(34) CometFilter Input [2]: [d_date_sk#19, d_date#20] Condition : (((isnotnull(d_date#20) AND (d_date#20 >= 1999-02-01)) AND (d_date#20 <= 1999-04-02)) AND isnotnull(d_date_sk#19)) -(36) Project [codegen id : 17] -Output [1]: [d_date_sk#19] +(35) CometProject Input [2]: [d_date_sk#19, d_date#20] +Arguments: [d_date_sk#19], [d_date_sk#19] + +(36) ColumnarToRow [codegen id : 17] +Input [1]: [d_date_sk#19] (37) BroadcastExchange Input [1]: [d_date_sk#19] @@ -239,16 +239,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_state), EqualTo(ca_state,IL), IsNotNull(ca_address_sk)] ReadSchema: struct -(41) ColumnarToRow [codegen id : 18] -Input [2]: [ca_address_sk#21, ca_state#22] - -(42) Filter [codegen id : 18] +(41) CometFilter Input [2]: [ca_address_sk#21, ca_state#22] Condition : ((isnotnull(ca_state#22) AND (ca_state#22 = IL)) AND isnotnull(ca_address_sk#21)) -(43) Project [codegen id : 18] -Output [1]: [ca_address_sk#21] +(42) CometProject Input [2]: [ca_address_sk#21, ca_state#22] +Arguments: [ca_address_sk#21], [ca_address_sk#21] + +(43) ColumnarToRow [codegen id : 18] +Input [1]: [ca_address_sk#21] (44) BroadcastExchange Input [1]: [ca_address_sk#21] @@ -271,16 +271,16 @@ Location [not included in comparison]/{warehouse_dir}/web_site] PushedFilters: [IsNotNull(web_company_name), EqualTo(web_company_name,pri ), IsNotNull(web_site_sk)] ReadSchema: struct -(48) ColumnarToRow [codegen id : 19] -Input [2]: [web_site_sk#23, web_company_name#24] - -(49) Filter [codegen id : 19] +(48) CometFilter Input [2]: [web_site_sk#23, web_company_name#24] Condition : ((isnotnull(web_company_name#24) AND (web_company_name#24 = pri )) AND isnotnull(web_site_sk#23)) -(50) Project [codegen id : 19] -Output [1]: [web_site_sk#23] +(49) CometProject Input [2]: [web_site_sk#23, web_company_name#24] +Arguments: [web_site_sk#23], [web_site_sk#23] + +(50) ColumnarToRow [codegen id : 19] +Input [1]: [web_site_sk#23] (51) BroadcastExchange Input [1]: [web_site_sk#23] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/simplified.txt index 389d74d39..5b699890c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q95/simplified.txt @@ -22,10 +22,10 @@ WholeStageCodegen (21) InputAdapter Exchange [ws_order_number] #2 WholeStageCodegen (1) - Project [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] - Filter [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit] + CometFilter [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk] CometScan parquet spark_catalog.default.web_sales [ws_ship_date_sk,ws_ship_addr_sk,ws_web_site_sk,ws_order_number,ws_ext_ship_cost,ws_net_profit,ws_sold_date_sk] InputAdapter WholeStageCodegen (7) @@ -37,10 +37,10 @@ WholeStageCodegen (21) InputAdapter Exchange [ws_order_number] #3 WholeStageCodegen (3) - Project [ws_warehouse_sk,ws_order_number] - Filter [ws_order_number,ws_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ws_warehouse_sk,ws_order_number] + CometFilter [ws_order_number,ws_warehouse_sk] CometScan parquet spark_catalog.default.web_sales [ws_warehouse_sk,ws_order_number,ws_sold_date_sk] InputAdapter WholeStageCodegen (6) @@ -57,10 +57,10 @@ WholeStageCodegen (21) InputAdapter Exchange [wr_order_number] #4 WholeStageCodegen (9) - Project [wr_order_number] - Filter [wr_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [wr_order_number] + CometFilter [wr_order_number] CometScan parquet spark_catalog.default.web_returns [wr_order_number,wr_returned_date_sk] InputAdapter WholeStageCodegen (15) @@ -79,24 +79,24 @@ WholeStageCodegen (21) InputAdapter BroadcastExchange #5 WholeStageCodegen (17) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #6 WholeStageCodegen (18) - Project [ca_address_sk] - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #7 WholeStageCodegen (19) - Project [web_site_sk] - Filter [web_company_name,web_site_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [web_site_sk] + CometFilter [web_company_name,web_site_sk] CometScan parquet spark_catalog.default.web_site [web_site_sk,web_company_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/explain.txt index e0ce29b43..60c262e9c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/explain.txt @@ -8,24 +8,24 @@ : +- * BroadcastHashJoin Inner BuildRight (17) : :- * Project (11) : : +- * BroadcastHashJoin Inner BuildRight (10) - : : :- * Project (4) - : : : +- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : +- BroadcastExchange (9) - : : +- * Project (8) - : : +- * Filter (7) - : : +- * ColumnarToRow (6) + : : +- * ColumnarToRow (8) + : : +- CometProject (7) + : : +- CometFilter (6) : : +- CometScan parquet spark_catalog.default.household_demographics (5) : +- BroadcastExchange (16) - : +- * Project (15) - : +- * Filter (14) - : +- * ColumnarToRow (13) + : +- * ColumnarToRow (15) + : +- CometProject (14) + : +- CometFilter (13) : +- CometScan parquet spark_catalog.default.time_dim (12) +- BroadcastExchange (23) - +- * Project (22) - +- * Filter (21) - +- * ColumnarToRow (20) + +- * ColumnarToRow (22) + +- CometProject (21) + +- CometFilter (20) +- CometScan parquet spark_catalog.default.store (19) @@ -36,16 +36,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_hdemo_sk), IsNotNull(ss_sold_time_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] -Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] - -(3) Filter [codegen id : 4] +(2) CometFilter Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] Condition : ((isnotnull(ss_hdemo_sk#2) AND isnotnull(ss_sold_time_sk#1)) AND isnotnull(ss_store_sk#3)) -(4) Project [codegen id : 4] -Output [3]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] +(3) CometProject Input [4]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_sold_date_sk#4] +Arguments: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3], [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] + +(4) ColumnarToRow [codegen id : 4] +Input [3]: [ss_sold_time_sk#1, ss_hdemo_sk#2, ss_store_sk#3] (5) Scan parquet spark_catalog.default.household_demographics Output [2]: [hd_demo_sk#5, hd_dep_count#6] @@ -54,16 +54,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_dep_count), EqualTo(hd_dep_count,7), IsNotNull(hd_demo_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 1] -Input [2]: [hd_demo_sk#5, hd_dep_count#6] - -(7) Filter [codegen id : 1] +(6) CometFilter Input [2]: [hd_demo_sk#5, hd_dep_count#6] Condition : ((isnotnull(hd_dep_count#6) AND (hd_dep_count#6 = 7)) AND isnotnull(hd_demo_sk#5)) -(8) Project [codegen id : 1] -Output [1]: [hd_demo_sk#5] +(7) CometProject Input [2]: [hd_demo_sk#5, hd_dep_count#6] +Arguments: [hd_demo_sk#5], [hd_demo_sk#5] + +(8) ColumnarToRow [codegen id : 1] +Input [1]: [hd_demo_sk#5] (9) BroadcastExchange Input [1]: [hd_demo_sk#5] @@ -86,16 +86,16 @@ Location [not included in comparison]/{warehouse_dir}/time_dim] PushedFilters: [IsNotNull(t_hour), IsNotNull(t_minute), EqualTo(t_hour,20), GreaterThanOrEqual(t_minute,30), IsNotNull(t_time_sk)] ReadSchema: struct -(13) ColumnarToRow [codegen id : 2] -Input [3]: [t_time_sk#7, t_hour#8, t_minute#9] - -(14) Filter [codegen id : 2] +(13) CometFilter Input [3]: [t_time_sk#7, t_hour#8, t_minute#9] Condition : ((((isnotnull(t_hour#8) AND isnotnull(t_minute#9)) AND (t_hour#8 = 20)) AND (t_minute#9 >= 30)) AND isnotnull(t_time_sk#7)) -(15) Project [codegen id : 2] -Output [1]: [t_time_sk#7] +(14) CometProject Input [3]: [t_time_sk#7, t_hour#8, t_minute#9] +Arguments: [t_time_sk#7], [t_time_sk#7] + +(15) ColumnarToRow [codegen id : 2] +Input [1]: [t_time_sk#7] (16) BroadcastExchange Input [1]: [t_time_sk#7] @@ -118,16 +118,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_name), EqualTo(s_store_name,ese), IsNotNull(s_store_sk)] ReadSchema: struct -(20) ColumnarToRow [codegen id : 3] -Input [2]: [s_store_sk#10, s_store_name#11] - -(21) Filter [codegen id : 3] +(20) CometFilter Input [2]: [s_store_sk#10, s_store_name#11] Condition : ((isnotnull(s_store_name#11) AND (s_store_name#11 = ese)) AND isnotnull(s_store_sk#10)) -(22) Project [codegen id : 3] -Output [1]: [s_store_sk#10] +(21) CometProject Input [2]: [s_store_sk#10, s_store_name#11] +Arguments: [s_store_sk#10], [s_store_sk#10] + +(22) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#10] (23) BroadcastExchange Input [1]: [s_store_sk#10] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/simplified.txt index fe9cd8bc8..d1438f48e 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q96/simplified.txt @@ -10,32 +10,32 @@ WholeStageCodegen (5) BroadcastHashJoin [ss_sold_time_sk,t_time_sk] Project [ss_sold_time_sk,ss_store_sk] BroadcastHashJoin [ss_hdemo_sk,hd_demo_sk] - Project [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] - Filter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk] + CometFilter [ss_hdemo_sk,ss_sold_time_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_sold_time_sk,ss_hdemo_sk,ss_store_sk,ss_sold_date_sk] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Project [hd_demo_sk] - Filter [hd_dep_count,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_dep_count,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_dep_count] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Project [t_time_sk] - Filter [t_hour,t_minute,t_time_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [t_time_sk] + CometFilter [t_hour,t_minute,t_time_sk] CometScan parquet spark_catalog.default.time_dim [t_time_sk,t_hour,t_minute] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Project [s_store_sk] - Filter [s_store_name,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_store_name,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/explain.txt index 6d54b23d8..66ccf4f22 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/explain.txt @@ -146,9 +146,9 @@ Results [3]: [sum(CASE WHEN (isnotnull(customer_sk#6) AND isnull(customer_sk#13) Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (28) -+- * Project (27) - +- * Filter (26) - +- * ColumnarToRow (25) ++- * ColumnarToRow (27) + +- CometProject (26) + +- CometFilter (25) +- CometScan parquet spark_catalog.default.date_dim (24) @@ -159,16 +159,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(25) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#5, d_month_seq#27] - -(26) Filter [codegen id : 1] +(25) CometFilter Input [2]: [d_date_sk#5, d_month_seq#27] Condition : (((isnotnull(d_month_seq#27) AND (d_month_seq#27 >= 1200)) AND (d_month_seq#27 <= 1211)) AND isnotnull(d_date_sk#5)) -(27) Project [codegen id : 1] -Output [1]: [d_date_sk#5] +(26) CometProject Input [2]: [d_date_sk#5, d_month_seq#27] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(27) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] (28) BroadcastExchange Input [1]: [d_date_sk#5] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/simplified.txt index ba918e146..be9c20a56 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q97/simplified.txt @@ -22,10 +22,10 @@ WholeStageCodegen (8) SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] InputAdapter ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/explain.txt index d4202b01d..3d66a07d0 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/explain.txt @@ -13,12 +13,12 @@ +- * BroadcastHashJoin Inner BuildRight (11) :- * Project (9) : +- * BroadcastHashJoin Inner BuildRight (8) - : :- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.store_sales (1) : +- BroadcastExchange (7) - : +- * Filter (6) - : +- * ColumnarToRow (5) + : +- * ColumnarToRow (6) + : +- CometFilter (5) : +- CometScan parquet spark_catalog.default.item (4) +- ReusedExchange (10) @@ -31,12 +31,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_item_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] -Condition : isnotnull(ss_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -45,12 +45,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] -Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) (7) BroadcastExchange Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -129,9 +129,9 @@ Input [7]: [i_item_desc#7, i_category#10, i_class#9, i_current_price#8, itemreve Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (27) -+- * Project (26) - +- * Filter (25) - +- * ColumnarToRow (24) ++- * ColumnarToRow (26) + +- CometProject (25) + +- CometFilter (24) +- CometScan parquet spark_catalog.default.date_dim (23) @@ -142,16 +142,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] ReadSchema: struct -(24) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#11, d_date#19] - -(25) Filter [codegen id : 1] +(24) CometFilter Input [2]: [d_date_sk#11, d_date#19] Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) -(26) Project [codegen id : 1] -Output [1]: [d_date_sk#11] +(25) CometProject Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(26) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] (27) BroadcastExchange Input [1]: [d_date_sk#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/simplified.txt index d3b1f3fe6..9eabb9977 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q98/simplified.txt @@ -21,24 +21,24 @@ WholeStageCodegen (7) BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_ext_sales_price,ss_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #5 WholeStageCodegen (1) - Filter [i_category,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] InputAdapter ReusedExchange [d_date_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/explain.txt index f8cf6b243..936555026 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/explain.txt @@ -11,25 +11,25 @@ TakeOrderedAndProject (32) : : +- * BroadcastHashJoin Inner BuildRight (14) : : :- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.warehouse (4) : : +- BroadcastExchange (13) - : : +- * Filter (12) - : : +- * ColumnarToRow (11) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) : : +- CometScan parquet spark_catalog.default.ship_mode (10) : +- BroadcastExchange (19) - : +- * Filter (18) - : +- * ColumnarToRow (17) + : +- * ColumnarToRow (18) + : +- CometFilter (17) : +- CometScan parquet spark_catalog.default.call_center (16) +- BroadcastExchange (26) - +- * Project (25) - +- * Filter (24) - +- * ColumnarToRow (23) + +- * ColumnarToRow (25) + +- CometProject (24) + +- CometFilter (23) +- CometScan parquet spark_catalog.default.date_dim (22) @@ -40,12 +40,12 @@ Location [not included in comparison]/{warehouse_dir}/catalog_sales] PushedFilters: [IsNotNull(cs_warehouse_sk), IsNotNull(cs_ship_mode_sk), IsNotNull(cs_call_center_sk), IsNotNull(cs_ship_date_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_warehouse_sk#4, cs_sold_date_sk#5] +Condition : (((isnotnull(cs_warehouse_sk#4) AND isnotnull(cs_ship_mode_sk#3)) AND isnotnull(cs_call_center_sk#2)) AND isnotnull(cs_ship_date_sk#1)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [5]: [cs_ship_date_sk#1, cs_call_center_sk#2, cs_ship_mode_sk#3, cs_warehouse_sk#4, cs_sold_date_sk#5] -Condition : (((isnotnull(cs_warehouse_sk#4) AND isnotnull(cs_ship_mode_sk#3)) AND isnotnull(cs_call_center_sk#2)) AND isnotnull(cs_ship_date_sk#1)) (4) Scan parquet spark_catalog.default.warehouse Output [2]: [w_warehouse_sk#6, w_warehouse_name#7] @@ -54,12 +54,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] +Condition : isnotnull(w_warehouse_sk#6) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] -Condition : isnotnull(w_warehouse_sk#6) (7) BroadcastExchange Input [2]: [w_warehouse_sk#6, w_warehouse_name#7] @@ -82,12 +82,12 @@ Location [not included in comparison]/{warehouse_dir}/ship_mode] PushedFilters: [IsNotNull(sm_ship_mode_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [2]: [sm_ship_mode_sk#8, sm_type#9] +Condition : isnotnull(sm_ship_mode_sk#8) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [2]: [sm_ship_mode_sk#8, sm_type#9] -Condition : isnotnull(sm_ship_mode_sk#8) (13) BroadcastExchange Input [2]: [sm_ship_mode_sk#8, sm_type#9] @@ -110,12 +110,12 @@ Location [not included in comparison]/{warehouse_dir}/call_center] PushedFilters: [IsNotNull(cc_call_center_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 3] +(17) CometFilter Input [2]: [cc_call_center_sk#10, cc_name#11] +Condition : isnotnull(cc_call_center_sk#10) -(18) Filter [codegen id : 3] +(18) ColumnarToRow [codegen id : 3] Input [2]: [cc_call_center_sk#10, cc_name#11] -Condition : isnotnull(cc_call_center_sk#10) (19) BroadcastExchange Input [2]: [cc_call_center_sk#10, cc_name#11] @@ -138,16 +138,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 4] -Input [2]: [d_date_sk#12, d_month_seq#13] - -(24) Filter [codegen id : 4] +(23) CometFilter Input [2]: [d_date_sk#12, d_month_seq#13] Condition : (((isnotnull(d_month_seq#13) AND (d_month_seq#13 >= 1200)) AND (d_month_seq#13 <= 1211)) AND isnotnull(d_date_sk#12)) -(25) Project [codegen id : 4] -Output [1]: [d_date_sk#12] +(24) CometProject Input [2]: [d_date_sk#12, d_month_seq#13] +Arguments: [d_date_sk#12], [d_date_sk#12] + +(25) ColumnarToRow [codegen id : 4] +Input [1]: [d_date_sk#12] (26) BroadcastExchange Input [1]: [d_date_sk#12] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/simplified.txt index c165c1fc1..c5f25f079 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark4_0/q99/simplified.txt @@ -13,36 +13,36 @@ TakeOrderedAndProject [substr(w_warehouse_name, 1, 20),sm_type,cc_name,30 days , BroadcastHashJoin [cs_ship_mode_sk,sm_ship_mode_sk] Project [cs_ship_date_sk,cs_call_center_sk,cs_ship_mode_sk,cs_sold_date_sk,w_warehouse_name] BroadcastHashJoin [cs_warehouse_sk,w_warehouse_sk] - Filter [cs_warehouse_sk,cs_ship_mode_sk,cs_call_center_sk,cs_ship_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_warehouse_sk,cs_ship_mode_sk,cs_call_center_sk,cs_ship_date_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_call_center_sk,cs_ship_mode_sk,cs_warehouse_sk,cs_sold_date_sk] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [sm_ship_mode_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sm_ship_mode_sk] CometScan parquet spark_catalog.default.ship_mode [sm_ship_mode_sk,sm_type] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Filter [cc_call_center_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cc_call_center_sk] CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_name] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/explain.txt index a0259dcc2..be0e98db2 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/explain.txt @@ -10,8 +10,8 @@ TakeOrderedAndProject (41) : :- * Project (24) : : +- * BroadcastHashJoin LeftSemi BuildRight (23) : : :- * BroadcastHashJoin LeftSemi BuildRight (10) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : +- BroadcastExchange (9) : : : +- * Project (8) @@ -32,13 +32,13 @@ TakeOrderedAndProject (41) : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) : : +- ReusedExchange (18) : +- BroadcastExchange (29) - : +- * Project (28) - : +- * Filter (27) - : +- * ColumnarToRow (26) + : +- * ColumnarToRow (28) + : +- CometProject (27) + : +- CometFilter (26) : +- CometScan parquet spark_catalog.default.customer_address (25) +- BroadcastExchange (35) - +- * Filter (34) - +- * ColumnarToRow (33) + +- * ColumnarToRow (34) + +- CometFilter (33) +- CometScan parquet spark_catalog.default.customer_demographics (32) @@ -49,12 +49,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 9] +(2) CometFilter Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) -(3) Filter [codegen id : 9] +(3) ColumnarToRow [codegen id : 9] Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] -Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) (4) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_customer_sk#4, ss_sold_date_sk#5] @@ -158,16 +158,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [In(ca_county, [Dona Ana County,Douglas County,Gaines County,Richland County,Walker County]), IsNotNull(ca_address_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 7] -Input [2]: [ca_address_sk#18, ca_county#19] - -(27) Filter [codegen id : 7] +(26) CometFilter Input [2]: [ca_address_sk#18, ca_county#19] Condition : (ca_county#19 IN (Walker County,Richland County,Gaines County,Douglas County,Dona Ana County) AND isnotnull(ca_address_sk#18)) -(28) Project [codegen id : 7] -Output [1]: [ca_address_sk#18] +(27) CometProject Input [2]: [ca_address_sk#18, ca_county#19] +Arguments: [ca_address_sk#18], [ca_address_sk#18] + +(28) ColumnarToRow [codegen id : 7] +Input [1]: [ca_address_sk#18] (29) BroadcastExchange Input [1]: [ca_address_sk#18] @@ -190,12 +190,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk)] ReadSchema: struct -(33) ColumnarToRow [codegen id : 8] +(33) CometFilter Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] +Condition : isnotnull(cd_demo_sk#20) -(34) Filter [codegen id : 8] +(34) ColumnarToRow [codegen id : 8] Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] -Condition : isnotnull(cd_demo_sk#20) (35) BroadcastExchange Input [9]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_education_status#23, cd_purchase_estimate#24, cd_credit_rating#25, cd_dep_count#26, cd_dep_employed_count#27, cd_dep_college_count#28] @@ -237,9 +237,9 @@ Arguments: 100, [cd_gender#21 ASC NULLS FIRST, cd_marital_status#22 ASC NULLS FI Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (46) -+- * Project (45) - +- * Filter (44) - +- * ColumnarToRow (43) ++- * ColumnarToRow (45) + +- CometProject (44) + +- CometFilter (43) +- CometScan parquet spark_catalog.default.date_dim (42) @@ -250,16 +250,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2002), GreaterThanOrEqual(d_moy,4), LessThanOrEqual(d_moy,7), IsNotNull(d_date_sk)] ReadSchema: struct -(43) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#7, d_year#38, d_moy#39] - -(44) Filter [codegen id : 1] +(43) CometFilter Input [3]: [d_date_sk#7, d_year#38, d_moy#39] Condition : (((((isnotnull(d_year#38) AND isnotnull(d_moy#39)) AND (d_year#38 = 2002)) AND (d_moy#39 >= 4)) AND (d_moy#39 <= 7)) AND isnotnull(d_date_sk#7)) -(45) Project [codegen id : 1] -Output [1]: [d_date_sk#7] +(44) CometProject Input [3]: [d_date_sk#7, d_year#38, d_moy#39] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(45) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] (46) BroadcastExchange Input [1]: [d_date_sk#7] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/simplified.txt index 668cec531..3eb2210a6 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q10a/simplified.txt @@ -12,9 +12,9 @@ TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purcha Project [c_current_cdemo_sk,c_current_addr_sk] BroadcastHashJoin [c_customer_sk,customer_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_current_addr_sk,c_current_cdemo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] InputAdapter BroadcastExchange #2 @@ -27,10 +27,10 @@ TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purcha SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk] #3 @@ -58,15 +58,15 @@ TakeOrderedAndProject [cd_gender,cd_marital_status,cd_education_status,cd_purcha InputAdapter BroadcastExchange #5 WholeStageCodegen (7) - Project [ca_address_sk] - Filter [ca_county,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_county,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county] InputAdapter BroadcastExchange #6 WholeStageCodegen (8) - Filter [cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status,cd_purchase_estimate,cd_credit_rating,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/explain.txt index 2c9f35aea..daa1f5243 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/explain.txt @@ -13,12 +13,12 @@ TakeOrderedAndProject (71) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.store_sales (4) : : : +- ReusedExchange (10) : : +- BroadcastExchange (32) @@ -29,12 +29,12 @@ TakeOrderedAndProject (71) : : +- * BroadcastHashJoin Inner BuildRight (27) : : :- * Project (25) : : : +- * BroadcastHashJoin Inner BuildRight (24) - : : : :- * Filter (19) - : : : : +- * ColumnarToRow (18) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) : : : : +- CometScan parquet spark_catalog.default.customer (17) : : : +- BroadcastExchange (23) - : : : +- * Filter (22) - : : : +- * ColumnarToRow (21) + : : : +- * ColumnarToRow (22) + : : : +- CometFilter (21) : : : +- CometScan parquet spark_catalog.default.store_sales (20) : : +- ReusedExchange (26) : +- BroadcastExchange (50) @@ -46,12 +46,12 @@ TakeOrderedAndProject (71) : +- * BroadcastHashJoin Inner BuildRight (44) : :- * Project (42) : : +- * BroadcastHashJoin Inner BuildRight (41) - : : :- * Filter (36) - : : : +- * ColumnarToRow (35) + : : :- * ColumnarToRow (36) + : : : +- CometFilter (35) : : : +- CometScan parquet spark_catalog.default.customer (34) : : +- BroadcastExchange (40) - : : +- * Filter (39) - : : +- * ColumnarToRow (38) + : : +- * ColumnarToRow (39) + : : +- CometFilter (38) : : +- CometScan parquet spark_catalog.default.web_sales (37) : +- ReusedExchange (43) +- BroadcastExchange (68) @@ -62,12 +62,12 @@ TakeOrderedAndProject (71) +- * BroadcastHashJoin Inner BuildRight (63) :- * Project (61) : +- * BroadcastHashJoin Inner BuildRight (60) - : :- * Filter (55) - : : +- * ColumnarToRow (54) + : :- * ColumnarToRow (55) + : : +- CometFilter (54) : : +- CometScan parquet spark_catalog.default.customer (53) : +- BroadcastExchange (59) - : +- * Filter (58) - : +- * ColumnarToRow (57) + : +- * ColumnarToRow (58) + : +- CometFilter (57) : +- CometScan parquet spark_catalog.default.web_sales (56) +- ReusedExchange (62) @@ -79,12 +79,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [8]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4, c_preferred_cust_flag#5, c_birth_country#6, c_login#7, c_email_address#8] -Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) (4) Scan parquet spark_catalog.default.store_sales Output [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] @@ -94,12 +94,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] +Condition : isnotnull(ss_customer_sk#9) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] -Condition : isnotnull(ss_customer_sk#9) (7) BroadcastExchange Input [4]: [ss_customer_sk#9, ss_ext_discount_amt#10, ss_ext_list_price#11, ss_sold_date_sk#12] @@ -157,12 +157,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 6] +(18) CometFilter Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] +Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_customer_id#22)) -(19) Filter [codegen id : 6] +(19) ColumnarToRow [codegen id : 6] Input [8]: [c_customer_sk#21, c_customer_id#22, c_first_name#23, c_last_name#24, c_preferred_cust_flag#25, c_birth_country#26, c_login#27, c_email_address#28] -Condition : (isnotnull(c_customer_sk#21) AND isnotnull(c_customer_id#22)) (20) Scan parquet spark_catalog.default.store_sales Output [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] @@ -172,12 +172,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#32), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] +(21) CometFilter Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] +Condition : isnotnull(ss_customer_sk#29) -(22) Filter [codegen id : 4] +(22) ColumnarToRow [codegen id : 4] Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] -Condition : isnotnull(ss_customer_sk#29) (23) BroadcastExchange Input [4]: [ss_customer_sk#29, ss_ext_discount_amt#30, ss_ext_list_price#31, ss_sold_date_sk#32] @@ -241,12 +241,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 10] +(35) CometFilter Input [8]: [c_customer_sk#43, c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50] +Condition : (isnotnull(c_customer_sk#43) AND isnotnull(c_customer_id#44)) -(36) Filter [codegen id : 10] +(36) ColumnarToRow [codegen id : 10] Input [8]: [c_customer_sk#43, c_customer_id#44, c_first_name#45, c_last_name#46, c_preferred_cust_flag#47, c_birth_country#48, c_login#49, c_email_address#50] -Condition : (isnotnull(c_customer_sk#43) AND isnotnull(c_customer_id#44)) (37) Scan parquet spark_catalog.default.web_sales Output [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] @@ -256,12 +256,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#54), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(38) ColumnarToRow [codegen id : 8] +(38) CometFilter Input [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] +Condition : isnotnull(ws_bill_customer_sk#51) -(39) Filter [codegen id : 8] +(39) ColumnarToRow [codegen id : 8] Input [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] -Condition : isnotnull(ws_bill_customer_sk#51) (40) BroadcastExchange Input [4]: [ws_bill_customer_sk#51, ws_ext_discount_amt#52, ws_ext_list_price#53, ws_sold_date_sk#54] @@ -333,12 +333,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(54) ColumnarToRow [codegen id : 14] +(54) CometFilter Input [8]: [c_customer_sk#63, c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70] +Condition : (isnotnull(c_customer_sk#63) AND isnotnull(c_customer_id#64)) -(55) Filter [codegen id : 14] +(55) ColumnarToRow [codegen id : 14] Input [8]: [c_customer_sk#63, c_customer_id#64, c_first_name#65, c_last_name#66, c_preferred_cust_flag#67, c_birth_country#68, c_login#69, c_email_address#70] -Condition : (isnotnull(c_customer_sk#63) AND isnotnull(c_customer_id#64)) (56) Scan parquet spark_catalog.default.web_sales Output [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] @@ -348,12 +348,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#74), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(57) ColumnarToRow [codegen id : 12] +(57) CometFilter Input [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] +Condition : isnotnull(ws_bill_customer_sk#71) -(58) Filter [codegen id : 12] +(58) ColumnarToRow [codegen id : 12] Input [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] -Condition : isnotnull(ws_bill_customer_sk#71) (59) BroadcastExchange Input [4]: [ws_bill_customer_sk#71, ws_ext_discount_amt#72, ws_ext_list_price#73, ws_sold_date_sk#74] @@ -422,8 +422,8 @@ Arguments: 100, [customer_id#38 ASC NULLS FIRST, customer_first_name#39 ASC NULL Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 BroadcastExchange (75) -+- * Filter (74) - +- * ColumnarToRow (73) ++- * ColumnarToRow (74) + +- CometFilter (73) +- CometScan parquet spark_catalog.default.date_dim (72) @@ -434,12 +434,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(73) ColumnarToRow [codegen id : 1] +(73) CometFilter Input [2]: [d_date_sk#14, d_year#15] +Condition : ((isnotnull(d_year#15) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#14)) -(74) Filter [codegen id : 1] +(74) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#14, d_year#15] -Condition : ((isnotnull(d_year#15) AND (d_year#15 = 2001)) AND isnotnull(d_date_sk#14)) (75) BroadcastExchange Input [2]: [d_date_sk#14, d_year#15] @@ -447,8 +447,8 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint) Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#32 IN dynamicpruning#33 BroadcastExchange (79) -+- * Filter (78) - +- * ColumnarToRow (77) ++- * ColumnarToRow (78) + +- CometFilter (77) +- CometScan parquet spark_catalog.default.date_dim (76) @@ -459,12 +459,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] ReadSchema: struct -(77) ColumnarToRow [codegen id : 1] +(77) CometFilter Input [2]: [d_date_sk#34, d_year#35] +Condition : ((isnotnull(d_year#35) AND (d_year#35 = 2002)) AND isnotnull(d_date_sk#34)) -(78) Filter [codegen id : 1] +(78) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#34, d_year#35] -Condition : ((isnotnull(d_year#35) AND (d_year#35 = 2002)) AND isnotnull(d_date_sk#34)) (79) BroadcastExchange Input [2]: [d_date_sk#34, d_year#35] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/simplified.txt index 172da54ae..0a30aba05 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q11/simplified.txt @@ -15,23 +15,23 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,custom BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #3 @@ -47,23 +47,23 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,custom BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #6 WholeStageCodegen (4) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_ext_discount_amt,ss_ext_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #7 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #7 @@ -80,16 +80,16 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,custom BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #10 WholeStageCodegen (8) - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -106,16 +106,16 @@ TakeOrderedAndProject [customer_id,customer_first_name,customer_last_name,custom BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name,c_preferred_cust_flag,c_birth_country,c_login,c_email_address] InputAdapter BroadcastExchange #13 WholeStageCodegen (12) - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_ext_discount_amt,ws_ext_list_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/explain.txt index 233ef7cb0..c39a71879 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/explain.txt @@ -11,12 +11,12 @@ TakeOrderedAndProject (20) +- * BroadcastHashJoin Inner BuildRight (11) :- * Project (9) : +- * BroadcastHashJoin Inner BuildRight (8) - : :- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.web_sales (1) : +- BroadcastExchange (7) - : +- * Filter (6) - : +- * ColumnarToRow (5) + : +- * ColumnarToRow (6) + : +- CometFilter (5) : +- CometScan parquet spark_catalog.default.item (4) +- ReusedExchange (10) @@ -29,12 +29,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [3]: [ws_item_sk#1, ws_ext_sales_price#2, ws_sold_date_sk#3] -Condition : isnotnull(ws_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -43,12 +43,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] -Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) (7) BroadcastExchange Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -119,9 +119,9 @@ Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_ite Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (25) -+- * Project (24) - +- * Filter (23) - +- * ColumnarToRow (22) ++- * ColumnarToRow (24) + +- CometProject (23) + +- CometFilter (22) +- CometScan parquet spark_catalog.default.date_dim (21) @@ -132,16 +132,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] ReadSchema: struct -(22) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#11, d_date#19] - -(23) Filter [codegen id : 1] +(22) CometFilter Input [2]: [d_date_sk#11, d_date#19] Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) -(24) Project [codegen id : 1] -Output [1]: [d_date_sk#11] +(23) CometProject Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(24) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] (25) BroadcastExchange Input [1]: [d_date_sk#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/simplified.txt index 689e8ae67..1bc2538b4 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q12/simplified.txt @@ -17,24 +17,24 @@ TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_c BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_ext_sales_price,ws_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_ext_sales_price,ws_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Filter [i_category,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] InputAdapter ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/explain.txt index 04118281e..ec52cea9f 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/explain.txt @@ -10,14 +10,14 @@ TakeOrderedAndProject (84) : :- * Project (59) : : +- * BroadcastHashJoin Inner BuildRight (58) : : :- * BroadcastHashJoin LeftSemi BuildRight (51) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- BroadcastExchange (50) : : : +- * Project (49) : : : +- * BroadcastHashJoin Inner BuildRight (48) - : : : :- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : :- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.item (4) : : : +- BroadcastExchange (47) : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) @@ -28,25 +28,25 @@ TakeOrderedAndProject (84) : : : : +- * BroadcastHashJoin Inner BuildRight (31) : : : : :- * Project (29) : : : : : +- * BroadcastHashJoin Inner BuildRight (28) - : : : : : :- * Filter (9) - : : : : : : +- * ColumnarToRow (8) + : : : : : :- * ColumnarToRow (9) + : : : : : : +- CometFilter (8) : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) : : : : : +- BroadcastExchange (27) : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) - : : : : : :- * Filter (12) - : : : : : : +- * ColumnarToRow (11) + : : : : : :- * ColumnarToRow (12) + : : : : : : +- CometFilter (11) : : : : : : +- CometScan parquet spark_catalog.default.item (10) : : : : : +- BroadcastExchange (25) : : : : : +- * Project (24) : : : : : +- * BroadcastHashJoin Inner BuildRight (23) : : : : : :- * Project (21) : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) - : : : : : : :- * Filter (15) - : : : : : : : +- * ColumnarToRow (14) + : : : : : : :- * ColumnarToRow (15) + : : : : : : : +- CometFilter (14) : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) : : : : : : +- BroadcastExchange (19) - : : : : : : +- * Filter (18) - : : : : : : +- * ColumnarToRow (17) + : : : : : : +- * ColumnarToRow (18) + : : : : : : +- CometFilter (17) : : : : : : +- CometScan parquet spark_catalog.default.item (16) : : : : : +- ReusedExchange (22) : : : : +- ReusedExchange (30) @@ -55,15 +55,15 @@ TakeOrderedAndProject (84) : : : +- * BroadcastHashJoin Inner BuildRight (43) : : : :- * Project (41) : : : : +- * BroadcastHashJoin Inner BuildRight (40) - : : : : :- * Filter (38) - : : : : : +- * ColumnarToRow (37) + : : : : :- * ColumnarToRow (38) + : : : : : +- CometFilter (37) : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) : : : : +- ReusedExchange (39) : : : +- ReusedExchange (42) : : +- BroadcastExchange (57) : : +- * BroadcastHashJoin LeftSemi BuildRight (56) - : : :- * Filter (54) - : : : +- * ColumnarToRow (53) + : : :- * ColumnarToRow (54) + : : : +- CometFilter (53) : : : +- CometScan parquet spark_catalog.default.item (52) : : +- ReusedExchange (55) : +- ReusedExchange (60) @@ -77,8 +77,8 @@ TakeOrderedAndProject (84) :- * Project (74) : +- * BroadcastHashJoin Inner BuildRight (73) : :- * BroadcastHashJoin LeftSemi BuildRight (71) - : : :- * Filter (69) - : : : +- * ColumnarToRow (68) + : : :- * ColumnarToRow (69) + : : : +- CometFilter (68) : : : +- CometScan parquet spark_catalog.default.store_sales (67) : : +- ReusedExchange (70) : +- ReusedExchange (72) @@ -93,12 +93,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 25] +(2) CometFilter Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) -(3) Filter [codegen id : 25] +(3) ColumnarToRow [codegen id : 25] Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] -Condition : isnotnull(ss_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] @@ -107,12 +107,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 11] +(5) CometFilter Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) -(6) Filter [codegen id : 11] +(6) ColumnarToRow [codegen id : 11] Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] -Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) (7) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] @@ -122,12 +122,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 6] +(8) CometFilter Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) -(9) Filter [codegen id : 6] +(9) ColumnarToRow [codegen id : 6] Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] -Condition : isnotnull(ss_item_sk#10) (10) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] @@ -136,12 +136,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 4] +(11) CometFilter Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) -(12) Filter [codegen id : 4] +(12) ColumnarToRow [codegen id : 4] Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] -Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) (13) Scan parquet spark_catalog.default.catalog_sales Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] @@ -151,12 +151,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] -Condition : isnotnull(cs_item_sk#17) (16) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] @@ -165,12 +165,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 1] +(17) CometFilter Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) -(18) Filter [codegen id : 1] +(18) ColumnarToRow [codegen id : 1] Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] -Condition : isnotnull(i_item_sk#20) (19) BroadcastExchange Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] @@ -262,12 +262,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(37) ColumnarToRow [codegen id : 9] +(37) CometFilter Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) -(38) Filter [codegen id : 9] +(38) ColumnarToRow [codegen id : 9] Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] -Condition : isnotnull(ws_item_sk#29) (39) ReusedExchange [Reuses operator id: 19] Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] @@ -336,12 +336,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] ReadSchema: struct -(53) ColumnarToRow [codegen id : 23] +(53) CometFilter Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : (((isnotnull(i_item_sk#38) AND isnotnull(i_brand_id#39)) AND isnotnull(i_class_id#40)) AND isnotnull(i_category_id#41)) -(54) Filter [codegen id : 23] +(54) ColumnarToRow [codegen id : 23] Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] -Condition : (((isnotnull(i_item_sk#38) AND isnotnull(i_brand_id#39)) AND isnotnull(i_class_id#40)) AND isnotnull(i_category_id#41)) (55) ReusedExchange [Reuses operator id: 50] Output [1]: [ss_item_sk#37] @@ -409,12 +409,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#59), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(68) ColumnarToRow [codegen id : 50] +(68) CometFilter Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] +Condition : isnotnull(ss_item_sk#56) -(69) Filter [codegen id : 50] +(69) ColumnarToRow [codegen id : 50] Input [4]: [ss_item_sk#56, ss_quantity#57, ss_list_price#58, ss_sold_date_sk#59] -Condition : isnotnull(ss_item_sk#56) (70) ReusedExchange [Reuses operator id: 50] Output [1]: [ss_item_sk#61] @@ -608,9 +608,9 @@ Subquery:4 Hosting operator id = 95 Hosting Expression = ws_sold_date_sk#94 IN d Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 BroadcastExchange (108) -+- * Project (107) - +- * Filter (106) - +- * ColumnarToRow (105) ++- * ColumnarToRow (107) + +- CometProject (106) + +- CometFilter (105) +- CometScan parquet spark_catalog.default.date_dim (104) @@ -621,27 +621,27 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#106), IsNotNull(d_date_sk)] ReadSchema: struct -(105) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#42, d_week_seq#105] - -(106) Filter [codegen id : 1] +(105) CometFilter Input [2]: [d_date_sk#42, d_week_seq#105] Condition : ((isnotnull(d_week_seq#105) AND (d_week_seq#105 = ReusedSubquery Subquery scalar-subquery#106, [id=#107])) AND isnotnull(d_date_sk#42)) -(107) Project [codegen id : 1] -Output [1]: [d_date_sk#42] +(106) CometProject Input [2]: [d_date_sk#42, d_week_seq#105] +Arguments: [d_date_sk#42], [d_date_sk#42] + +(107) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#42] (108) BroadcastExchange Input [1]: [d_date_sk#42] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] -Subquery:6 Hosting operator id = 106 Hosting Expression = ReusedSubquery Subquery scalar-subquery#106, [id=#107] +Subquery:6 Hosting operator id = 105 Hosting Expression = ReusedSubquery Subquery scalar-subquery#106, [id=#107] Subquery:7 Hosting operator id = 104 Hosting Expression = Subquery scalar-subquery#106, [id=#107] -* Project (112) -+- * Filter (111) - +- * ColumnarToRow (110) +* ColumnarToRow (112) ++- CometProject (111) + +- CometFilter (110) +- CometScan parquet spark_catalog.default.date_dim (109) @@ -652,22 +652,22 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1999), EqualTo(d_moy,12), EqualTo(d_dom,16)] ReadSchema: struct -(110) ColumnarToRow [codegen id : 1] -Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] - -(111) Filter [codegen id : 1] +(110) CometFilter Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] Condition : (((((isnotnull(d_year#109) AND isnotnull(d_moy#110)) AND isnotnull(d_dom#111)) AND (d_year#109 = 1999)) AND (d_moy#110 = 12)) AND (d_dom#111 = 16)) -(112) Project [codegen id : 1] -Output [1]: [d_week_seq#108] +(111) CometProject Input [4]: [d_week_seq#108, d_year#109, d_moy#110, d_dom#111] +Arguments: [d_week_seq#108], [d_week_seq#108] + +(112) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#108] Subquery:8 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 BroadcastExchange (117) -+- * Project (116) - +- * Filter (115) - +- * ColumnarToRow (114) ++- * ColumnarToRow (116) + +- CometProject (115) + +- CometFilter (114) +- CometScan parquet spark_catalog.default.date_dim (113) @@ -678,16 +678,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1998), LessThanOrEqual(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(114) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#25, d_year#112] - -(115) Filter [codegen id : 1] +(114) CometFilter Input [2]: [d_date_sk#25, d_year#112] Condition : (((isnotnull(d_year#112) AND (d_year#112 >= 1998)) AND (d_year#112 <= 2000)) AND isnotnull(d_date_sk#25)) -(116) Project [codegen id : 1] -Output [1]: [d_date_sk#25] +(115) CometProject Input [2]: [d_date_sk#25, d_year#112] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(116) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] (117) BroadcastExchange Input [1]: [d_date_sk#25] @@ -701,9 +701,9 @@ Subquery:11 Hosting operator id = 81 Hosting Expression = ReusedSubquery Subquer Subquery:12 Hosting operator id = 67 Hosting Expression = ss_sold_date_sk#59 IN dynamicpruning#60 BroadcastExchange (122) -+- * Project (121) - +- * Filter (120) - +- * ColumnarToRow (119) ++- * ColumnarToRow (121) + +- CometProject (120) + +- CometFilter (119) +- CometScan parquet spark_catalog.default.date_dim (118) @@ -714,27 +714,27 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_week_seq), EqualTo(d_week_seq,ScalarSubquery#114), IsNotNull(d_date_sk)] ReadSchema: struct -(119) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#66, d_week_seq#113] - -(120) Filter [codegen id : 1] +(119) CometFilter Input [2]: [d_date_sk#66, d_week_seq#113] Condition : ((isnotnull(d_week_seq#113) AND (d_week_seq#113 = ReusedSubquery Subquery scalar-subquery#114, [id=#115])) AND isnotnull(d_date_sk#66)) -(121) Project [codegen id : 1] -Output [1]: [d_date_sk#66] +(120) CometProject Input [2]: [d_date_sk#66, d_week_seq#113] +Arguments: [d_date_sk#66], [d_date_sk#66] + +(121) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#66] (122) BroadcastExchange Input [1]: [d_date_sk#66] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15] -Subquery:13 Hosting operator id = 120 Hosting Expression = ReusedSubquery Subquery scalar-subquery#114, [id=#115] +Subquery:13 Hosting operator id = 119 Hosting Expression = ReusedSubquery Subquery scalar-subquery#114, [id=#115] Subquery:14 Hosting operator id = 118 Hosting Expression = Subquery scalar-subquery#114, [id=#115] -* Project (126) -+- * Filter (125) - +- * ColumnarToRow (124) +* ColumnarToRow (126) ++- CometProject (125) + +- CometFilter (124) +- CometScan parquet spark_catalog.default.date_dim (123) @@ -745,15 +745,15 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1998), EqualTo(d_moy,12), EqualTo(d_dom,16)] ReadSchema: struct -(124) ColumnarToRow [codegen id : 1] -Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] - -(125) Filter [codegen id : 1] +(124) CometFilter Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] Condition : (((((isnotnull(d_year#117) AND isnotnull(d_moy#118)) AND isnotnull(d_dom#119)) AND (d_year#117 = 1998)) AND (d_moy#118 = 12)) AND (d_dom#119 = 16)) -(126) Project [codegen id : 1] -Output [1]: [d_week_seq#116] +(125) CometProject Input [4]: [d_week_seq#116, d_year#117, d_moy#118, d_dom#119] +Arguments: [d_week_seq#116], [d_week_seq#116] + +(126) ColumnarToRow [codegen id : 1] +Input [1]: [d_week_seq#116] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/simplified.txt index 64646b717..55aa823ab 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14/simplified.txt @@ -48,34 +48,34 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ss_item_sk,i_item_sk] BroadcastHashJoin [ss_item_sk,ss_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_week_seq,d_date_sk] - ReusedSubquery [d_week_seq] #2 - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #2 CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] Subquery #2 WholeStageCodegen (1) - Project [d_week_seq] - Filter [d_year,d_moy,d_dom] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_moy,d_dom] CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] InputAdapter BroadcastExchange #3 WholeStageCodegen (11) Project [i_item_sk] BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] - Filter [i_brand_id,i_class_id,i_category_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_brand_id,i_class_id,i_category_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter BroadcastExchange #4 @@ -90,25 +90,25 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #3 BroadcastExchange #6 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #7 WholeStageCodegen (4) BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] - Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter BroadcastExchange #8 @@ -117,17 +117,17 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] ReusedSubquery [d_date_sk] #3 InputAdapter BroadcastExchange #9 WholeStageCodegen (1) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter ReusedExchange [d_date_sk] #6 @@ -140,9 +140,9 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] ReusedSubquery [d_date_sk] #3 InputAdapter @@ -153,9 +153,9 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ BroadcastExchange #11 WholeStageCodegen (23) BroadcastHashJoin [i_item_sk,ss_item_sk] - Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter ReusedExchange [ss_item_sk] #3 @@ -176,25 +176,25 @@ TakeOrderedAndProject [i_brand_id,i_class_id,i_category_id,channel,sales,number_ Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ss_item_sk,i_item_sk] BroadcastHashJoin [ss_item_sk,ss_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #5 BroadcastExchange #15 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_week_seq,d_date_sk] - ReusedSubquery [d_week_seq] #6 - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_week_seq,d_date_sk] + ReusedSubquery [d_week_seq] #6 CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] Subquery #6 WholeStageCodegen (1) - Project [d_week_seq] - Filter [d_year,d_moy,d_dom] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_week_seq] + CometFilter [d_year,d_moy,d_dom] CometScan parquet spark_catalog.default.date_dim [d_week_seq,d_year,d_moy,d_dom] InputAdapter ReusedExchange [ss_item_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/explain.txt index 4dd70ec51..d76059e01 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/explain.txt @@ -17,14 +17,14 @@ TakeOrderedAndProject (125) : : :- * Project (59) : : : +- * BroadcastHashJoin Inner BuildRight (58) : : : :- * BroadcastHashJoin LeftSemi BuildRight (51) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : +- BroadcastExchange (50) : : : : +- * Project (49) : : : : +- * BroadcastHashJoin Inner BuildRight (48) - : : : : :- * Filter (6) - : : : : : +- * ColumnarToRow (5) + : : : : :- * ColumnarToRow (6) + : : : : : +- CometFilter (5) : : : : : +- CometScan parquet spark_catalog.default.item (4) : : : : +- BroadcastExchange (47) : : : : +- * BroadcastHashJoin LeftSemi BuildRight (46) @@ -35,25 +35,25 @@ TakeOrderedAndProject (125) : : : : : +- * BroadcastHashJoin Inner BuildRight (31) : : : : : :- * Project (29) : : : : : : +- * BroadcastHashJoin Inner BuildRight (28) - : : : : : : :- * Filter (9) - : : : : : : : +- * ColumnarToRow (8) + : : : : : : :- * ColumnarToRow (9) + : : : : : : : +- CometFilter (8) : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (7) : : : : : : +- BroadcastExchange (27) : : : : : : +- * BroadcastHashJoin LeftSemi BuildRight (26) - : : : : : : :- * Filter (12) - : : : : : : : +- * ColumnarToRow (11) + : : : : : : :- * ColumnarToRow (12) + : : : : : : : +- CometFilter (11) : : : : : : : +- CometScan parquet spark_catalog.default.item (10) : : : : : : +- BroadcastExchange (25) : : : : : : +- * Project (24) : : : : : : +- * BroadcastHashJoin Inner BuildRight (23) : : : : : : :- * Project (21) : : : : : : : +- * BroadcastHashJoin Inner BuildRight (20) - : : : : : : : :- * Filter (15) - : : : : : : : : +- * ColumnarToRow (14) + : : : : : : : :- * ColumnarToRow (15) + : : : : : : : : +- CometFilter (14) : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) : : : : : : : +- BroadcastExchange (19) - : : : : : : : +- * Filter (18) - : : : : : : : +- * ColumnarToRow (17) + : : : : : : : +- * ColumnarToRow (18) + : : : : : : : +- CometFilter (17) : : : : : : : +- CometScan parquet spark_catalog.default.item (16) : : : : : : +- ReusedExchange (22) : : : : : +- ReusedExchange (30) @@ -62,15 +62,15 @@ TakeOrderedAndProject (125) : : : : +- * BroadcastHashJoin Inner BuildRight (43) : : : : :- * Project (41) : : : : : +- * BroadcastHashJoin Inner BuildRight (40) - : : : : : :- * Filter (38) - : : : : : : +- * ColumnarToRow (37) + : : : : : :- * ColumnarToRow (38) + : : : : : : +- CometFilter (37) : : : : : : +- CometScan parquet spark_catalog.default.web_sales (36) : : : : : +- ReusedExchange (39) : : : : +- ReusedExchange (42) : : : +- BroadcastExchange (57) : : : +- * BroadcastHashJoin LeftSemi BuildRight (56) - : : : :- * Filter (54) - : : : : +- * ColumnarToRow (53) + : : : :- * ColumnarToRow (54) + : : : : +- CometFilter (53) : : : : +- CometScan parquet spark_catalog.default.item (52) : : : +- ReusedExchange (55) : : +- ReusedExchange (60) @@ -83,8 +83,8 @@ TakeOrderedAndProject (125) : : :- * Project (74) : : : +- * BroadcastHashJoin Inner BuildRight (73) : : : :- * BroadcastHashJoin LeftSemi BuildRight (71) - : : : : :- * Filter (69) - : : : : : +- * ColumnarToRow (68) + : : : : :- * ColumnarToRow (69) + : : : : : +- CometFilter (68) : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (67) : : : : +- ReusedExchange (70) : : : +- ReusedExchange (72) @@ -98,8 +98,8 @@ TakeOrderedAndProject (125) : :- * Project (89) : : +- * BroadcastHashJoin Inner BuildRight (88) : : :- * BroadcastHashJoin LeftSemi BuildRight (86) - : : : :- * Filter (84) - : : : : +- * ColumnarToRow (83) + : : : :- * ColumnarToRow (84) + : : : : +- CometFilter (83) : : : : +- CometScan parquet spark_catalog.default.web_sales (82) : : : +- ReusedExchange (85) : : +- ReusedExchange (87) @@ -134,12 +134,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 25] +(2) CometFilter Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_item_sk#1) -(3) Filter [codegen id : 25] +(3) ColumnarToRow [codegen id : 25] Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4] -Condition : isnotnull(ss_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] @@ -148,12 +148,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 11] +(5) CometFilter Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] +Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) -(6) Filter [codegen id : 11] +(6) ColumnarToRow [codegen id : 11] Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9] -Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9)) (7) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_item_sk#10, ss_sold_date_sk#11] @@ -163,12 +163,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 6] +(8) CometFilter Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_item_sk#10) -(9) Filter [codegen id : 6] +(9) ColumnarToRow [codegen id : 6] Input [2]: [ss_item_sk#10, ss_sold_date_sk#11] -Condition : isnotnull(ss_item_sk#10) (10) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] @@ -177,12 +177,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 4] +(11) CometFilter Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] +Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) -(12) Filter [codegen id : 4] +(12) ColumnarToRow [codegen id : 4] Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16] -Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16)) (13) Scan parquet spark_catalog.default.catalog_sales Output [2]: [cs_item_sk#17, cs_sold_date_sk#18] @@ -192,12 +192,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] +Condition : isnotnull(cs_item_sk#17) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [2]: [cs_item_sk#17, cs_sold_date_sk#18] -Condition : isnotnull(cs_item_sk#17) (16) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] @@ -206,12 +206,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 1] +(17) CometFilter Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] +Condition : isnotnull(i_item_sk#20) -(18) Filter [codegen id : 1] +(18) ColumnarToRow [codegen id : 1] Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] -Condition : isnotnull(i_item_sk#20) (19) BroadcastExchange Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23] @@ -303,12 +303,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#30), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(37) ColumnarToRow [codegen id : 9] +(37) CometFilter Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] +Condition : isnotnull(ws_item_sk#29) -(38) Filter [codegen id : 9] +(38) ColumnarToRow [codegen id : 9] Input [2]: [ws_item_sk#29, ws_sold_date_sk#30] -Condition : isnotnull(ws_item_sk#29) (39) ReusedExchange [Reuses operator id: 19] Output [4]: [i_item_sk#32, i_brand_id#33, i_class_id#34, i_category_id#35] @@ -377,12 +377,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(53) ColumnarToRow [codegen id : 23] +(53) CometFilter Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] +Condition : isnotnull(i_item_sk#38) -(54) Filter [codegen id : 23] +(54) ColumnarToRow [codegen id : 23] Input [4]: [i_item_sk#38, i_brand_id#39, i_class_id#40, i_category_id#41] -Condition : isnotnull(i_item_sk#38) (55) ReusedExchange [Reuses operator id: 50] Output [1]: [ss_item_sk#37] @@ -450,12 +450,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#59), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(68) ColumnarToRow [codegen id : 51] +(68) CometFilter Input [4]: [cs_item_sk#56, cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59] +Condition : isnotnull(cs_item_sk#56) -(69) Filter [codegen id : 51] +(69) ColumnarToRow [codegen id : 51] Input [4]: [cs_item_sk#56, cs_quantity#57, cs_list_price#58, cs_sold_date_sk#59] -Condition : isnotnull(cs_item_sk#56) (70) ReusedExchange [Reuses operator id: 50] Output [1]: [ss_item_sk#61] @@ -522,12 +522,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#81), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(83) ColumnarToRow [codegen id : 77] +(83) CometFilter Input [4]: [ws_item_sk#78, ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81] +Condition : isnotnull(ws_item_sk#78) -(84) Filter [codegen id : 77] +(84) ColumnarToRow [codegen id : 77] Input [4]: [ws_item_sk#78, ws_quantity#79, ws_list_price#80, ws_sold_date_sk#81] -Condition : isnotnull(ws_item_sk#78) (85) ReusedExchange [Reuses operator id: 50] Output [1]: [ss_item_sk#83] @@ -859,9 +859,9 @@ Subquery:2 Hosting operator id = 126 Hosting Expression = ss_sold_date_sk#206 IN Subquery:3 Hosting operator id = 131 Hosting Expression = cs_sold_date_sk#213 IN dynamicpruning#214 BroadcastExchange (149) -+- * Project (148) - +- * Filter (147) - +- * ColumnarToRow (146) ++- * ColumnarToRow (148) + +- CometProject (147) + +- CometFilter (146) +- CometScan parquet spark_catalog.default.date_dim (145) @@ -872,16 +872,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1998), LessThanOrEqual(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(146) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#215, d_year#231] - -(147) Filter [codegen id : 1] +(146) CometFilter Input [2]: [d_date_sk#215, d_year#231] Condition : (((isnotnull(d_year#231) AND (d_year#231 >= 1998)) AND (d_year#231 <= 2000)) AND isnotnull(d_date_sk#215)) -(148) Project [codegen id : 1] -Output [1]: [d_date_sk#215] +(147) CometProject Input [2]: [d_date_sk#215, d_year#231] +Arguments: [d_date_sk#215], [d_date_sk#215] + +(148) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#215] (149) BroadcastExchange Input [1]: [d_date_sk#215] @@ -891,9 +891,9 @@ Subquery:4 Hosting operator id = 136 Hosting Expression = ws_sold_date_sk#220 IN Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 BroadcastExchange (154) -+- * Project (153) - +- * Filter (152) - +- * ColumnarToRow (151) ++- * ColumnarToRow (153) + +- CometProject (152) + +- CometFilter (151) +- CometScan parquet spark_catalog.default.date_dim (150) @@ -904,16 +904,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,11), IsNotNull(d_date_sk)] ReadSchema: struct -(151) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#42, d_year#232, d_moy#233] - -(152) Filter [codegen id : 1] +(151) CometFilter Input [3]: [d_date_sk#42, d_year#232, d_moy#233] Condition : ((((isnotnull(d_year#232) AND isnotnull(d_moy#233)) AND (d_year#232 = 2000)) AND (d_moy#233 = 11)) AND isnotnull(d_date_sk#42)) -(153) Project [codegen id : 1] -Output [1]: [d_date_sk#42] +(152) CometProject Input [3]: [d_date_sk#42, d_year#232, d_moy#233] +Arguments: [d_date_sk#42], [d_date_sk#42] + +(153) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#42] (154) BroadcastExchange Input [1]: [d_date_sk#42] @@ -921,9 +921,9 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)) Subquery:6 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12 BroadcastExchange (159) -+- * Project (158) - +- * Filter (157) - +- * ColumnarToRow (156) ++- * ColumnarToRow (158) + +- CometProject (157) + +- CometFilter (156) +- CometScan parquet spark_catalog.default.date_dim (155) @@ -934,16 +934,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(156) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#25, d_year#234] - -(157) Filter [codegen id : 1] +(156) CometFilter Input [2]: [d_date_sk#25, d_year#234] Condition : (((isnotnull(d_year#234) AND (d_year#234 >= 1999)) AND (d_year#234 <= 2001)) AND isnotnull(d_date_sk#25)) -(158) Project [codegen id : 1] -Output [1]: [d_date_sk#25] +(157) CometProject Input [2]: [d_date_sk#25, d_year#234] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(158) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] (159) BroadcastExchange Input [1]: [d_date_sk#25] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/simplified.txt index 7284dab53..a203f9620 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q14a/simplified.txt @@ -44,10 +44,10 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum_sales,num SubqueryBroadcast [d_date_sk] #4 BroadcastExchange #15 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk] #15 @@ -70,26 +70,26 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum_sales,num Project [ss_quantity,ss_list_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ss_item_sk,i_item_sk] BroadcastHashJoin [ss_item_sk,ss_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_quantity,ss_list_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter BroadcastExchange #5 WholeStageCodegen (11) Project [i_item_sk] BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,brand_id,class_id,category_id] - Filter [i_brand_id,i_class_id,i_category_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_brand_id,i_class_id,i_category_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter BroadcastExchange #6 @@ -104,25 +104,25 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum_sales,num BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #8 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #9 WholeStageCodegen (4) BroadcastHashJoin [i_brand_id,i_class_id,i_category_id,i_brand_id,i_class_id,i_category_id] - Filter [i_item_sk,i_brand_id,i_class_id,i_category_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_brand_id,i_class_id,i_category_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter BroadcastExchange #10 @@ -131,17 +131,17 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum_sales,num BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter BroadcastExchange #11 WholeStageCodegen (1) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter ReusedExchange [d_date_sk] #8 @@ -154,9 +154,9 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum_sales,num BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter @@ -167,9 +167,9 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum_sales,num BroadcastExchange #13 WholeStageCodegen (23) BroadcastHashJoin [i_item_sk,ss_item_sk] - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id] InputAdapter ReusedExchange [ss_item_sk] #5 @@ -188,9 +188,9 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum_sales,num Project [cs_quantity,cs_list_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [cs_item_sk,i_item_sk] BroadcastHashJoin [cs_item_sk,ss_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_quantity,cs_list_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -212,9 +212,9 @@ TakeOrderedAndProject [channel,i_brand_id,i_class_id,i_category_id,sum_sales,num Project [ws_quantity,ws_list_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id] BroadcastHashJoin [ws_item_sk,i_item_sk] BroadcastHashJoin [ws_item_sk,ss_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_quantity,ws_list_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/explain.txt index 908089cc5..8bcc0c6ba 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/explain.txt @@ -16,31 +16,31 @@ TakeOrderedAndProject (153) : : : : : +- * BroadcastHashJoin Inner BuildRight (16) : : : : : :- * Project (10) : : : : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : : : : :- * Filter (3) - : : : : : : : +- * ColumnarToRow (2) + : : : : : : :- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : : : : +- BroadcastExchange (8) - : : : : : : +- * Project (7) - : : : : : : +- * Filter (6) - : : : : : : +- * ColumnarToRow (5) + : : : : : : +- * ColumnarToRow (7) + : : : : : : +- CometProject (6) + : : : : : : +- CometFilter (5) : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) : : : : : +- BroadcastExchange (15) - : : : : : +- * Project (14) - : : : : : +- * Filter (13) - : : : : : +- * ColumnarToRow (12) + : : : : : +- * ColumnarToRow (14) + : : : : : +- CometProject (13) + : : : : : +- CometFilter (12) : : : : : +- CometScan parquet spark_catalog.default.customer (11) : : : : +- BroadcastExchange (21) - : : : : +- * Filter (20) - : : : : +- * ColumnarToRow (19) + : : : : +- * ColumnarToRow (20) + : : : : +- CometFilter (19) : : : : +- CometScan parquet spark_catalog.default.customer_demographics (18) : : : +- BroadcastExchange (27) - : : : +- * Filter (26) - : : : +- * ColumnarToRow (25) + : : : +- * ColumnarToRow (26) + : : : +- CometFilter (25) : : : +- CometScan parquet spark_catalog.default.customer_address (24) : : +- ReusedExchange (30) : +- BroadcastExchange (36) - : +- * Filter (35) - : +- * ColumnarToRow (34) + : +- * ColumnarToRow (35) + : +- CometFilter (34) : +- CometScan parquet spark_catalog.default.item (33) :- * HashAggregate (68) : +- Exchange (67) @@ -57,15 +57,15 @@ TakeOrderedAndProject (153) : : : : : +- * BroadcastHashJoin Inner BuildRight (49) : : : : : :- * Project (47) : : : : : : +- * BroadcastHashJoin Inner BuildRight (46) - : : : : : : :- * Filter (44) - : : : : : : : +- * ColumnarToRow (43) + : : : : : : :- * ColumnarToRow (44) + : : : : : : : +- CometFilter (43) : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (42) : : : : : : +- ReusedExchange (45) : : : : : +- ReusedExchange (48) : : : : +- ReusedExchange (51) : : : +- BroadcastExchange (57) - : : : +- * Filter (56) - : : : +- * ColumnarToRow (55) + : : : +- * ColumnarToRow (56) + : : : +- CometFilter (55) : : : +- CometScan parquet spark_catalog.default.customer_address (54) : : +- ReusedExchange (60) : +- ReusedExchange (63) @@ -84,16 +84,16 @@ TakeOrderedAndProject (153) : : : : : +- * BroadcastHashJoin Inner BuildRight (76) : : : : : :- * Project (74) : : : : : : +- * BroadcastHashJoin Inner BuildRight (73) - : : : : : : :- * Filter (71) - : : : : : : : +- * ColumnarToRow (70) + : : : : : : :- * ColumnarToRow (71) + : : : : : : : +- CometFilter (70) : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (69) : : : : : : +- ReusedExchange (72) : : : : : +- ReusedExchange (75) : : : : +- ReusedExchange (78) : : : +- BroadcastExchange (85) - : : : +- * Project (84) - : : : +- * Filter (83) - : : : +- * ColumnarToRow (82) + : : : +- * ColumnarToRow (84) + : : : +- CometProject (83) + : : : +- CometFilter (82) : : : +- CometScan parquet spark_catalog.default.customer_address (81) : : +- ReusedExchange (88) : +- ReusedExchange (91) @@ -112,16 +112,16 @@ TakeOrderedAndProject (153) : : : : : +- * BroadcastHashJoin Inner BuildRight (104) : : : : : :- * Project (102) : : : : : : +- * BroadcastHashJoin Inner BuildRight (101) - : : : : : : :- * Filter (99) - : : : : : : : +- * ColumnarToRow (98) + : : : : : : :- * ColumnarToRow (99) + : : : : : : : +- CometFilter (98) : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (97) : : : : : : +- ReusedExchange (100) : : : : : +- ReusedExchange (103) : : : : +- ReusedExchange (106) : : : +- BroadcastExchange (113) - : : : +- * Project (112) - : : : +- * Filter (111) - : : : +- * ColumnarToRow (110) + : : : +- * ColumnarToRow (112) + : : : +- CometProject (111) + : : : +- CometFilter (110) : : : +- CometScan parquet spark_catalog.default.customer_address (109) : : +- ReusedExchange (116) : +- ReusedExchange (119) @@ -140,8 +140,8 @@ TakeOrderedAndProject (153) : : : : +- * BroadcastHashJoin Inner BuildRight (132) : : : : :- * Project (130) : : : : : +- * BroadcastHashJoin Inner BuildRight (129) - : : : : : :- * Filter (127) - : : : : : : +- * ColumnarToRow (126) + : : : : : :- * ColumnarToRow (127) + : : : : : : +- CometFilter (126) : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (125) : : : : : +- ReusedExchange (128) : : : : +- ReusedExchange (131) @@ -149,8 +149,8 @@ TakeOrderedAndProject (153) : : +- ReusedExchange (137) : +- ReusedExchange (140) +- BroadcastExchange (146) - +- * Filter (145) - +- * ColumnarToRow (144) + +- * ColumnarToRow (145) + +- CometFilter (144) +- CometScan parquet spark_catalog.default.item (143) @@ -162,12 +162,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#9), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 7] +(2) CometFilter Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] +Condition : ((isnotnull(cs_bill_cdemo_sk#2) AND isnotnull(cs_bill_customer_sk#1)) AND isnotnull(cs_item_sk#3)) -(3) Filter [codegen id : 7] +(3) ColumnarToRow [codegen id : 7] Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9] -Condition : ((isnotnull(cs_bill_cdemo_sk#2) AND isnotnull(cs_bill_customer_sk#1)) AND isnotnull(cs_item_sk#3)) (4) Scan parquet spark_catalog.default.customer_demographics Output [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] @@ -176,16 +176,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_education_status,College ), IsNotNull(cd_demo_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] Condition : ((((isnotnull(cd_gender#12) AND isnotnull(cd_education_status#13)) AND (cd_gender#12 = M)) AND (cd_education_status#13 = College )) AND isnotnull(cd_demo_sk#11)) -(7) Project [codegen id : 1] -Output [2]: [cd_demo_sk#11, cd_dep_count#14] +(6) CometProject Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14] +Arguments: [cd_demo_sk#11, cd_dep_count#14], [cd_demo_sk#11, cd_dep_count#14] + +(7) ColumnarToRow [codegen id : 1] +Input [2]: [cd_demo_sk#11, cd_dep_count#14] (8) BroadcastExchange Input [2]: [cd_demo_sk#11, cd_dep_count#14] @@ -208,16 +208,16 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [In(c_birth_month, [1,10,12,4,5,9]), IsNotNull(c_customer_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(12) ColumnarToRow [codegen id : 2] -Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] - -(13) Filter [codegen id : 2] +(12) CometFilter Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] Condition : (((c_birth_month#18 IN (9,5,12,4,1,10) AND isnotnull(c_customer_sk#15)) AND isnotnull(c_current_cdemo_sk#16)) AND isnotnull(c_current_addr_sk#17)) -(14) Project [codegen id : 2] -Output [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] +(13) CometProject Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19] +Arguments: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19], [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] + +(14) ColumnarToRow [codegen id : 2] +Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] (15) BroadcastExchange Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19] @@ -240,12 +240,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk)] ReadSchema: struct -(19) ColumnarToRow [codegen id : 3] +(19) CometFilter Input [1]: [cd_demo_sk#20] +Condition : isnotnull(cd_demo_sk#20) -(20) Filter [codegen id : 3] +(20) ColumnarToRow [codegen id : 3] Input [1]: [cd_demo_sk#20] -Condition : isnotnull(cd_demo_sk#20) (21) BroadcastExchange Input [1]: [cd_demo_sk#20] @@ -268,12 +268,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] ReadSchema: struct -(25) ColumnarToRow [codegen id : 4] +(25) CometFilter Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] +Condition : (ca_state#23 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#21)) -(26) Filter [codegen id : 4] +(26) ColumnarToRow [codegen id : 4] Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] -Condition : (ca_state#23 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#21)) (27) BroadcastExchange Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24] @@ -309,12 +309,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(34) ColumnarToRow [codegen id : 6] +(34) CometFilter Input [2]: [i_item_sk#26, i_item_id#27] +Condition : isnotnull(i_item_sk#26) -(35) Filter [codegen id : 6] +(35) ColumnarToRow [codegen id : 6] Input [2]: [i_item_sk#26, i_item_id#27] -Condition : isnotnull(i_item_sk#26) (36) BroadcastExchange Input [2]: [i_item_sk#26, i_item_id#27] @@ -356,12 +356,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#85), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(43) ColumnarToRow [codegen id : 15] +(43) CometFilter Input [9]: [cs_bill_customer_sk#77, cs_bill_cdemo_sk#78, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85] +Condition : ((isnotnull(cs_bill_cdemo_sk#78) AND isnotnull(cs_bill_customer_sk#77)) AND isnotnull(cs_item_sk#79)) -(44) Filter [codegen id : 15] +(44) ColumnarToRow [codegen id : 15] Input [9]: [cs_bill_customer_sk#77, cs_bill_cdemo_sk#78, cs_item_sk#79, cs_quantity#80, cs_list_price#81, cs_sales_price#82, cs_coupon_amt#83, cs_net_profit#84, cs_sold_date_sk#85] -Condition : ((isnotnull(cs_bill_cdemo_sk#78) AND isnotnull(cs_bill_customer_sk#77)) AND isnotnull(cs_item_sk#79)) (45) ReusedExchange [Reuses operator id: 8] Output [2]: [cd_demo_sk#87, cd_dep_count#88] @@ -409,12 +409,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] ReadSchema: struct -(55) ColumnarToRow [codegen id : 12] +(55) CometFilter Input [3]: [ca_address_sk#94, ca_state#95, ca_country#96] +Condition : (ca_state#95 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#94)) -(56) Filter [codegen id : 12] +(56) ColumnarToRow [codegen id : 12] Input [3]: [ca_address_sk#94, ca_state#95, ca_country#96] -Condition : (ca_state#95 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#94)) (57) BroadcastExchange Input [3]: [ca_address_sk#94, ca_state#95, ca_country#96] @@ -482,12 +482,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#158), dynamicpruningexpression(cs_s PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(70) ColumnarToRow [codegen id : 23] +(70) CometFilter Input [9]: [cs_bill_customer_sk#150, cs_bill_cdemo_sk#151, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158] +Condition : ((isnotnull(cs_bill_cdemo_sk#151) AND isnotnull(cs_bill_customer_sk#150)) AND isnotnull(cs_item_sk#152)) -(71) Filter [codegen id : 23] +(71) ColumnarToRow [codegen id : 23] Input [9]: [cs_bill_customer_sk#150, cs_bill_cdemo_sk#151, cs_item_sk#152, cs_quantity#153, cs_list_price#154, cs_sales_price#155, cs_coupon_amt#156, cs_net_profit#157, cs_sold_date_sk#158] -Condition : ((isnotnull(cs_bill_cdemo_sk#151) AND isnotnull(cs_bill_customer_sk#150)) AND isnotnull(cs_item_sk#152)) (72) ReusedExchange [Reuses operator id: 8] Output [2]: [cd_demo_sk#160, cd_dep_count#161] @@ -535,16 +535,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] ReadSchema: struct -(82) ColumnarToRow [codegen id : 20] -Input [3]: [ca_address_sk#167, ca_state#168, ca_country#169] - -(83) Filter [codegen id : 20] +(82) CometFilter Input [3]: [ca_address_sk#167, ca_state#168, ca_country#169] Condition : (ca_state#168 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#167)) -(84) Project [codegen id : 20] -Output [2]: [ca_address_sk#167, ca_country#169] +(83) CometProject Input [3]: [ca_address_sk#167, ca_state#168, ca_country#169] +Arguments: [ca_address_sk#167, ca_country#169], [ca_address_sk#167, ca_country#169] + +(84) ColumnarToRow [codegen id : 20] +Input [2]: [ca_address_sk#167, ca_country#169] (85) BroadcastExchange Input [2]: [ca_address_sk#167, ca_country#169] @@ -612,12 +612,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#232), dynamicpruningexpression(cs_s PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(98) ColumnarToRow [codegen id : 31] +(98) CometFilter Input [9]: [cs_bill_customer_sk#224, cs_bill_cdemo_sk#225, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232] +Condition : ((isnotnull(cs_bill_cdemo_sk#225) AND isnotnull(cs_bill_customer_sk#224)) AND isnotnull(cs_item_sk#226)) -(99) Filter [codegen id : 31] +(99) ColumnarToRow [codegen id : 31] Input [9]: [cs_bill_customer_sk#224, cs_bill_cdemo_sk#225, cs_item_sk#226, cs_quantity#227, cs_list_price#228, cs_sales_price#229, cs_coupon_amt#230, cs_net_profit#231, cs_sold_date_sk#232] -Condition : ((isnotnull(cs_bill_cdemo_sk#225) AND isnotnull(cs_bill_customer_sk#224)) AND isnotnull(cs_item_sk#226)) (100) ReusedExchange [Reuses operator id: 8] Output [2]: [cd_demo_sk#234, cd_dep_count#235] @@ -665,16 +665,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [In(ca_state, [AL,MS,NC,ND,OK,TN,WI]), IsNotNull(ca_address_sk)] ReadSchema: struct -(110) ColumnarToRow [codegen id : 28] -Input [2]: [ca_address_sk#241, ca_state#242] - -(111) Filter [codegen id : 28] +(110) CometFilter Input [2]: [ca_address_sk#241, ca_state#242] Condition : (ca_state#242 IN (ND,WI,AL,NC,OK,MS,TN) AND isnotnull(ca_address_sk#241)) -(112) Project [codegen id : 28] -Output [1]: [ca_address_sk#241] +(111) CometProject Input [2]: [ca_address_sk#241, ca_state#242] +Arguments: [ca_address_sk#241], [ca_address_sk#241] + +(112) ColumnarToRow [codegen id : 28] +Input [1]: [ca_address_sk#241] (113) BroadcastExchange Input [1]: [ca_address_sk#241] @@ -742,12 +742,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#306), dynamicpruningexpression(cs_s PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)] ReadSchema: struct -(126) ColumnarToRow [codegen id : 39] +(126) CometFilter Input [9]: [cs_bill_customer_sk#298, cs_bill_cdemo_sk#299, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306] +Condition : ((isnotnull(cs_bill_cdemo_sk#299) AND isnotnull(cs_bill_customer_sk#298)) AND isnotnull(cs_item_sk#300)) -(127) Filter [codegen id : 39] +(127) ColumnarToRow [codegen id : 39] Input [9]: [cs_bill_customer_sk#298, cs_bill_cdemo_sk#299, cs_item_sk#300, cs_quantity#301, cs_list_price#302, cs_sales_price#303, cs_coupon_amt#304, cs_net_profit#305, cs_sold_date_sk#306] -Condition : ((isnotnull(cs_bill_cdemo_sk#299) AND isnotnull(cs_bill_customer_sk#298)) AND isnotnull(cs_item_sk#300)) (128) ReusedExchange [Reuses operator id: 8] Output [2]: [cd_demo_sk#308, cd_dep_count#309] @@ -821,12 +821,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(144) ColumnarToRow [codegen id : 38] +(144) CometFilter Input [1]: [i_item_sk#317] +Condition : isnotnull(i_item_sk#317) -(145) Filter [codegen id : 38] +(145) ColumnarToRow [codegen id : 38] Input [1]: [i_item_sk#317] -Condition : isnotnull(i_item_sk#317) (146) BroadcastExchange Input [1]: [i_item_sk#317] @@ -870,9 +870,9 @@ Arguments: 100, [ca_country#24 ASC NULLS FIRST, ca_state#23 ASC NULLS FIRST, ca_ Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#9 IN dynamicpruning#10 BroadcastExchange (158) -+- * Project (157) - +- * Filter (156) - +- * ColumnarToRow (155) ++- * ColumnarToRow (157) + +- CometProject (156) + +- CometFilter (155) +- CometScan parquet spark_catalog.default.date_dim (154) @@ -883,16 +883,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(155) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#25, d_year#371] - -(156) Filter [codegen id : 1] +(155) CometFilter Input [2]: [d_date_sk#25, d_year#371] Condition : ((isnotnull(d_year#371) AND (d_year#371 = 2001)) AND isnotnull(d_date_sk#25)) -(157) Project [codegen id : 1] -Output [1]: [d_date_sk#25] +(156) CometProject Input [2]: [d_date_sk#25, d_year#371] +Arguments: [d_date_sk#25], [d_date_sk#25] + +(157) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#25] (158) BroadcastExchange Input [1]: [d_date_sk#25] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/simplified.txt index 369a6d222..f02809572 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q18a/simplified.txt @@ -18,56 +18,56 @@ TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,ag BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] - Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [cd_demo_sk,cd_dep_count] - Filter [cd_gender,cd_education_status,cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk,cd_dep_count] + CometFilter [cd_gender,cd_education_status,cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_education_status,cd_dep_count] InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] - Filter [c_birth_month,c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_year] + CometFilter [c_birth_month,c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk,c_birth_month,c_birth_year] InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk] InputAdapter BroadcastExchange #6 WholeStageCodegen (4) - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_county,ca_state,ca_country] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #7 WholeStageCodegen (6) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] WholeStageCodegen (16) HashAggregate [i_item_id,ca_country,ca_state,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(agg2),avg(agg3),avg(agg4),avg(agg5),avg(agg6),avg(agg7),county,agg1,agg2,agg3,agg4,agg5,agg6,agg7,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count,sum,count] @@ -87,9 +87,9 @@ TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,ag BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] - Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -101,9 +101,9 @@ TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,ag InputAdapter BroadcastExchange #9 WholeStageCodegen (12) - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] InputAdapter ReusedExchange [d_date_sk] #2 @@ -127,9 +127,9 @@ TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,ag BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] - Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -141,10 +141,10 @@ TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,ag InputAdapter BroadcastExchange #11 WholeStageCodegen (20) - Project [ca_address_sk,ca_country] - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk,ca_country] + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_country] InputAdapter ReusedExchange [d_date_sk] #2 @@ -168,9 +168,9 @@ TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,ag BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] - Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -182,10 +182,10 @@ TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,ag InputAdapter BroadcastExchange #13 WholeStageCodegen (28) - Project [ca_address_sk] - Filter [ca_state,ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ca_address_sk] + CometFilter [ca_state,ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter ReusedExchange [d_date_sk] #2 @@ -209,9 +209,9 @@ TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,ag BroadcastHashJoin [cs_bill_customer_sk,c_customer_sk] Project [cs_bill_customer_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk,cd_dep_count] BroadcastHashJoin [cs_bill_cdemo_sk,cd_demo_sk] - Filter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_bill_cdemo_sk,cs_bill_customer_sk,cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_bill_cdemo_sk,cs_item_sk,cs_quantity,cs_list_price,cs_sales_price,cs_coupon_amt,cs_net_profit,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -227,7 +227,7 @@ TakeOrderedAndProject [ca_country,ca_state,ca_county,i_item_id,agg1,agg2,agg3,ag InputAdapter BroadcastExchange #15 WholeStageCodegen (38) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/explain.txt index 5c6c60771..1304af2e1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/explain.txt @@ -11,12 +11,12 @@ TakeOrderedAndProject (20) +- * BroadcastHashJoin Inner BuildRight (11) :- * Project (9) : +- * BroadcastHashJoin Inner BuildRight (8) - : :- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : +- BroadcastExchange (7) - : +- * Filter (6) - : +- * ColumnarToRow (5) + : +- * ColumnarToRow (6) + : +- CometFilter (5) : +- CometScan parquet spark_catalog.default.item (4) +- ReusedExchange (10) @@ -29,12 +29,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#3), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] +Condition : isnotnull(cs_item_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [3]: [cs_item_sk#1, cs_ext_sales_price#2, cs_sold_date_sk#3] -Condition : isnotnull(cs_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -43,12 +43,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] -Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) (7) BroadcastExchange Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -119,9 +119,9 @@ Arguments: 100, [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_ite Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (25) -+- * Project (24) - +- * Filter (23) - +- * ColumnarToRow (22) ++- * ColumnarToRow (24) + +- CometProject (23) + +- CometFilter (22) +- CometScan parquet spark_catalog.default.date_dim (21) @@ -132,16 +132,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] ReadSchema: struct -(22) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#11, d_date#19] - -(23) Filter [codegen id : 1] +(22) CometFilter Input [2]: [d_date_sk#11, d_date#19] Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) -(24) Project [codegen id : 1] -Output [1]: [d_date_sk#11] +(23) CometProject Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(24) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] (25) BroadcastExchange Input [1]: [d_date_sk#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/simplified.txt index b5d7b5cc8..2a2a392cd 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q20/simplified.txt @@ -17,24 +17,24 @@ TakeOrderedAndProject [i_category,i_class,i_item_id,i_item_desc,revenueratio,i_c BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_ext_sales_price,cs_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_ext_sales_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Filter [i_category,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] InputAdapter ReusedExchange [d_date_sk] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/explain.txt index 5085b8ed3..fdebdc8a4 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/explain.txt @@ -10,13 +10,13 @@ TakeOrderedAndProject (22) : +- * BroadcastHashJoin Inner BuildRight (11) : :- * Project (6) : : +- * BroadcastHashJoin Inner BuildRight (5) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.inventory (1) : : +- ReusedExchange (4) : +- BroadcastExchange (10) - : +- * Filter (9) - : +- * ColumnarToRow (8) + : +- * ColumnarToRow (9) + : +- CometFilter (8) : +- CometScan parquet spark_catalog.default.item (7) +- BroadcastExchange (15) +- * ColumnarToRow (14) @@ -31,12 +31,12 @@ PartitionFilters: [isnotnull(inv_date_sk#3), dynamicpruningexpression(inv_date_s PushedFilters: [IsNotNull(inv_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [3]: [inv_item_sk#1, inv_quantity_on_hand#2, inv_date_sk#3] +Condition : isnotnull(inv_item_sk#1) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [3]: [inv_item_sk#1, inv_quantity_on_hand#2, inv_date_sk#3] -Condition : isnotnull(inv_item_sk#1) (4) ReusedExchange [Reuses operator id: 27] Output [1]: [d_date_sk#5] @@ -58,12 +58,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] +Condition : isnotnull(i_item_sk#6) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] -Condition : isnotnull(i_item_sk#6) (10) BroadcastExchange Input [5]: [i_item_sk#6, i_brand#7, i_class#8, i_category#9, i_product_name#10] @@ -130,9 +130,9 @@ Arguments: 100, [qoh#21 ASC NULLS FIRST, i_product_name#11 ASC NULLS FIRST, i_br Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#3 IN dynamicpruning#4 BroadcastExchange (27) -+- * Project (26) - +- * Filter (25) - +- * ColumnarToRow (24) ++- * ColumnarToRow (26) + +- CometProject (25) + +- CometFilter (24) +- CometScan parquet spark_catalog.default.date_dim (23) @@ -143,16 +143,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)] ReadSchema: struct -(24) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#5, d_month_seq#22] - -(25) Filter [codegen id : 1] +(24) CometFilter Input [2]: [d_date_sk#5, d_month_seq#22] Condition : (((isnotnull(d_month_seq#22) AND (d_month_seq#22 >= 1200)) AND (d_month_seq#22 <= 1211)) AND isnotnull(d_date_sk#5)) -(26) Project [codegen id : 1] -Output [1]: [d_date_sk#5] +(25) CometProject Input [2]: [d_date_sk#5, d_month_seq#22] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(26) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] (27) BroadcastExchange Input [1]: [d_date_sk#5] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/simplified.txt index 853aad173..63a428d4e 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22/simplified.txt @@ -12,26 +12,26 @@ TakeOrderedAndProject [qoh,i_product_name,i_brand,i_class,i_category] BroadcastHashJoin [inv_item_sk,i_item_sk] Project [inv_item_sk,inv_quantity_on_hand] BroadcastHashJoin [inv_date_sk,d_date_sk] - Filter [inv_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_quantity_on_hand,inv_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] InputAdapter BroadcastExchange #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/explain.txt index 4f067d199..1e5f5c2f7 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/explain.txt @@ -12,17 +12,17 @@ TakeOrderedAndProject (45) : : +- * BroadcastHashJoin Inner BuildRight (11) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.inventory (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.item (7) : +- BroadcastExchange (16) - : +- * Filter (15) - : +- * ColumnarToRow (14) + : +- * ColumnarToRow (15) + : +- CometFilter (14) : +- CometScan parquet spark_catalog.default.warehouse (13) :- * HashAggregate (28) : +- Exchange (27) @@ -54,12 +54,12 @@ PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_s PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] +Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4] -Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2)) (4) ReusedExchange [Reuses operator id: 50] Output [1]: [d_date_sk#6] @@ -81,12 +81,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] +Condition : isnotnull(i_item_sk#7) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] -Condition : isnotnull(i_item_sk#7) (10) BroadcastExchange Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11] @@ -109,12 +109,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [1]: [w_warehouse_sk#12] +Condition : isnotnull(w_warehouse_sk#12) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [1]: [w_warehouse_sk#12] -Condition : isnotnull(w_warehouse_sk#12) (16) BroadcastExchange Input [1]: [w_warehouse_sk#12] @@ -284,9 +284,9 @@ Arguments: 100, [qoh#28 ASC NULLS FIRST, i_product_name#24 ASC NULLS FIRST, i_br Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5 BroadcastExchange (50) -+- * Project (49) - +- * Filter (48) - +- * ColumnarToRow (47) ++- * ColumnarToRow (49) + +- CometProject (48) + +- CometFilter (47) +- CometScan parquet spark_catalog.default.date_dim (46) @@ -297,16 +297,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] ReadSchema: struct -(47) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#6, d_month_seq#95] - -(48) Filter [codegen id : 1] +(47) CometFilter Input [2]: [d_date_sk#6, d_month_seq#95] Condition : (((isnotnull(d_month_seq#95) AND (d_month_seq#95 >= 1212)) AND (d_month_seq#95 <= 1223)) AND isnotnull(d_date_sk#6)) -(49) Project [codegen id : 1] -Output [1]: [d_date_sk#6] +(48) CometProject Input [2]: [d_date_sk#6, d_month_seq#95] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] (50) BroadcastExchange Input [1]: [d_date_sk#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/simplified.txt index 0819dc055..3aa0745ad 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q22a/simplified.txt @@ -14,33 +14,33 @@ TakeOrderedAndProject [qoh,i_product_name,i_brand,i_class,i_category] BroadcastHashJoin [inv_item_sk,i_item_sk] Project [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand] BroadcastHashJoin [inv_date_sk,d_date_sk] - Filter [inv_item_sk,inv_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [inv_item_sk,inv_warehouse_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk] WholeStageCodegen (11) HashAggregate [i_product_name,i_brand,i_class,sum,count] [avg(qoh),i_category,qoh,sum,count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/explain.txt index f2d354a2d..0cba9b059 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/explain.txt @@ -20,32 +20,32 @@ : : : : +- * SortMergeJoin Inner (13) : : : : :- * Sort (6) : : : : : +- Exchange (5) - : : : : : +- * Project (4) - : : : : : +- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : : +- * ColumnarToRow (4) + : : : : : +- CometProject (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : +- * Sort (12) : : : : +- Exchange (11) - : : : : +- * Project (10) - : : : : +- * Filter (9) - : : : : +- * ColumnarToRow (8) + : : : : +- * ColumnarToRow (10) + : : : : +- CometProject (9) + : : : : +- CometFilter (8) : : : : +- CometScan parquet spark_catalog.default.store_returns (7) : : : +- BroadcastExchange (19) - : : : +- * Project (18) - : : : +- * Filter (17) - : : : +- * ColumnarToRow (16) + : : : +- * ColumnarToRow (18) + : : : +- CometProject (17) + : : : +- CometFilter (16) : : : +- CometScan parquet spark_catalog.default.store (15) : : +- BroadcastExchange (25) - : : +- * Filter (24) - : : +- * ColumnarToRow (23) + : : +- * ColumnarToRow (24) + : : +- CometFilter (23) : : +- CometScan parquet spark_catalog.default.item (22) : +- BroadcastExchange (31) - : +- * Filter (30) - : +- * ColumnarToRow (29) + : +- * ColumnarToRow (30) + : +- CometFilter (29) : +- CometScan parquet spark_catalog.default.customer (28) +- BroadcastExchange (37) - +- * Filter (36) - +- * ColumnarToRow (35) + +- * ColumnarToRow (36) + +- CometFilter (35) +- CometScan parquet spark_catalog.default.customer_address (34) @@ -56,16 +56,16 @@ Location [not included in comparison]/{warehouse_dir}/store_sales] PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_customer_sk#2)) -(4) Project [codegen id : 1] -Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] +(3) CometProject Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5, ss_sold_date_sk#6] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5], [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] + +(4) ColumnarToRow [codegen id : 1] +Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] (5) Exchange Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_net_paid#5] @@ -82,16 +82,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 3] -Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] - -(9) Filter [codegen id : 3] +(8) CometFilter Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] Condition : (isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#7)) -(10) Project [codegen id : 3] -Output [2]: [sr_item_sk#7, sr_ticket_number#8] +(9) CometProject Input [3]: [sr_item_sk#7, sr_ticket_number#8, sr_returned_date_sk#9] +Arguments: [sr_item_sk#7, sr_ticket_number#8], [sr_item_sk#7, sr_ticket_number#8] + +(10) ColumnarToRow [codegen id : 3] +Input [2]: [sr_item_sk#7, sr_ticket_number#8] (11) Exchange Input [2]: [sr_item_sk#7, sr_ticket_number#8] @@ -118,16 +118,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_market_id), EqualTo(s_market_id,8), IsNotNull(s_store_sk), IsNotNull(s_zip)] ReadSchema: struct -(16) ColumnarToRow [codegen id : 5] -Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] - -(17) Filter [codegen id : 5] +(16) CometFilter Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] Condition : (((isnotnull(s_market_id#12) AND (s_market_id#12 = 8)) AND isnotnull(s_store_sk#10)) AND isnotnull(s_zip#14)) -(18) Project [codegen id : 5] -Output [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] +(17) CometProject Input [5]: [s_store_sk#10, s_store_name#11, s_market_id#12, s_state#13, s_zip#14] +Arguments: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14], [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] + +(18) ColumnarToRow [codegen id : 5] +Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] (19) BroadcastExchange Input [4]: [s_store_sk#10, s_store_name#11, s_state#13, s_zip#14] @@ -150,12 +150,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_color), EqualTo(i_color,pale ), IsNotNull(i_item_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 6] +(23) CometFilter Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] +Condition : ((isnotnull(i_color#18) AND (i_color#18 = pale )) AND isnotnull(i_item_sk#15)) -(24) Filter [codegen id : 6] +(24) ColumnarToRow [codegen id : 6] Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] -Condition : ((isnotnull(i_color#18) AND (i_color#18 = pale )) AND isnotnull(i_item_sk#15)) (25) BroadcastExchange Input [6]: [i_item_sk#15, i_current_price#16, i_size#17, i_color#18, i_units#19, i_manager_id#20] @@ -178,12 +178,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk), IsNotNull(c_birth_country)] ReadSchema: struct -(29) ColumnarToRow [codegen id : 7] +(29) CometFilter Input [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] +Condition : ((isnotnull(c_customer_sk#21) AND isnotnull(c_current_addr_sk#22)) AND isnotnull(c_birth_country#25)) -(30) Filter [codegen id : 7] +(30) ColumnarToRow [codegen id : 7] Input [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] -Condition : ((isnotnull(c_customer_sk#21) AND isnotnull(c_current_addr_sk#22)) AND isnotnull(c_birth_country#25)) (31) BroadcastExchange Input [5]: [c_customer_sk#21, c_current_addr_sk#22, c_first_name#23, c_last_name#24, c_birth_country#25] @@ -206,12 +206,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_country), IsNotNull(ca_zip)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 8] +(35) CometFilter Input [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] +Condition : ((isnotnull(ca_address_sk#26) AND isnotnull(ca_country#29)) AND isnotnull(ca_zip#28)) -(36) Filter [codegen id : 8] +(36) ColumnarToRow [codegen id : 8] Input [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] -Condition : ((isnotnull(ca_address_sk#26) AND isnotnull(ca_country#29)) AND isnotnull(ca_zip#28)) (37) BroadcastExchange Input [4]: [ca_address_sk#26, ca_state#27, ca_zip#28, ca_country#29] @@ -300,8 +300,8 @@ Subquery:1 Hosting operator id = 46 Hosting Expression = Subquery scalar-subquer : : : : +- ReusedExchange (51) : : : +- ReusedExchange (55) : : +- BroadcastExchange (61) - : : +- * Filter (60) - : : +- * ColumnarToRow (59) + : : +- * ColumnarToRow (60) + : : +- CometFilter (59) : : +- CometScan parquet spark_catalog.default.item (58) : +- ReusedExchange (64) +- ReusedExchange (67) @@ -351,12 +351,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(59) ColumnarToRow [codegen id : 6] +(59) CometFilter Input [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] +Condition : isnotnull(i_item_sk#53) -(60) Filter [codegen id : 6] +(60) ColumnarToRow [codegen id : 6] Input [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] -Condition : isnotnull(i_item_sk#53) (61) BroadcastExchange Input [6]: [i_item_sk#53, i_current_price#54, i_size#55, i_color#56, i_units#57, i_manager_id#58] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/simplified.txt index 02c50e74d..7024f439f 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q24/simplified.txt @@ -41,9 +41,9 @@ WholeStageCodegen (12) InputAdapter BroadcastExchange #12 WholeStageCodegen (6) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] InputAdapter ReusedExchange [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name,c_birth_country] #8 @@ -75,10 +75,10 @@ WholeStageCodegen (12) InputAdapter Exchange [ss_ticket_number,ss_item_sk] #4 WholeStageCodegen (1) - Project [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] - Filter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid] + CometFilter [ss_ticket_number,ss_item_sk,ss_store_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_store_sk,ss_ticket_number,ss_net_paid,ss_sold_date_sk] InputAdapter WholeStageCodegen (4) @@ -86,37 +86,37 @@ WholeStageCodegen (12) InputAdapter Exchange [sr_ticket_number,sr_item_sk] #5 WholeStageCodegen (3) - Project [sr_item_sk,sr_ticket_number] - Filter [sr_ticket_number,sr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_ticket_number,sr_item_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] InputAdapter BroadcastExchange #6 WholeStageCodegen (5) - Project [s_store_sk,s_store_name,s_state,s_zip] - Filter [s_market_id,s_store_sk,s_zip] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk,s_store_name,s_state,s_zip] + CometFilter [s_market_id,s_store_sk,s_zip] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_market_id,s_state,s_zip] InputAdapter BroadcastExchange #7 WholeStageCodegen (6) - Filter [i_color,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_color,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_size,i_color,i_units,i_manager_id] InputAdapter BroadcastExchange #8 WholeStageCodegen (7) - Filter [c_customer_sk,c_current_addr_sk,c_birth_country] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_current_addr_sk,c_birth_country] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk,c_first_name,c_last_name,c_birth_country] InputAdapter BroadcastExchange #9 WholeStageCodegen (8) - Filter [ca_address_sk,ca_country,ca_zip] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk,ca_country,ca_zip] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state,ca_zip,ca_country] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/explain.txt index 803b7f919..fc43e7271 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/explain.txt @@ -12,22 +12,22 @@ TakeOrderedAndProject (73) : : : +- * BroadcastHashJoin Inner BuildRight (12) : : : :- * Project (10) : : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : +- BroadcastExchange (8) - : : : : +- * Project (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (7) + : : : : +- CometProject (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.customer_demographics (4) : : : +- ReusedExchange (11) : : +- BroadcastExchange (17) - : : +- * Filter (16) - : : +- * ColumnarToRow (15) + : : +- * ColumnarToRow (16) + : : +- CometFilter (15) : : +- CometScan parquet spark_catalog.default.store (14) : +- BroadcastExchange (23) - : +- * Filter (22) - : +- * ColumnarToRow (21) + : +- * ColumnarToRow (22) + : +- CometFilter (21) : +- CometScan parquet spark_catalog.default.item (20) :- * HashAggregate (50) : +- Exchange (49) @@ -40,15 +40,15 @@ TakeOrderedAndProject (73) : : : +- * BroadcastHashJoin Inner BuildRight (36) : : : :- * Project (34) : : : : +- * BroadcastHashJoin Inner BuildRight (33) - : : : : :- * Filter (31) - : : : : : +- * ColumnarToRow (30) + : : : : :- * ColumnarToRow (31) + : : : : : +- CometFilter (30) : : : : : +- CometScan parquet spark_catalog.default.store_sales (29) : : : : +- ReusedExchange (32) : : : +- ReusedExchange (35) : : +- BroadcastExchange (42) - : : +- * Project (41) - : : +- * Filter (40) - : : +- * ColumnarToRow (39) + : : +- * ColumnarToRow (41) + : : +- CometProject (40) + : : +- CometFilter (39) : : +- CometScan parquet spark_catalog.default.store (38) : +- ReusedExchange (45) +- * HashAggregate (71) @@ -62,15 +62,15 @@ TakeOrderedAndProject (73) : : +- * BroadcastHashJoin Inner BuildRight (58) : : :- * Project (56) : : : +- * BroadcastHashJoin Inner BuildRight (55) - : : : :- * Filter (53) - : : : : +- * ColumnarToRow (52) + : : : :- * ColumnarToRow (53) + : : : : +- CometFilter (52) : : : : +- CometScan parquet spark_catalog.default.store_sales (51) : : : +- ReusedExchange (54) : : +- ReusedExchange (57) : +- ReusedExchange (60) +- BroadcastExchange (66) - +- * Filter (65) - +- * ColumnarToRow (64) + +- * ColumnarToRow (65) + +- CometFilter (64) +- CometScan parquet spark_catalog.default.item (63) @@ -82,12 +82,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 5] +(2) CometFilter Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] +Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_item_sk#1)) -(3) Filter [codegen id : 5] +(3) ColumnarToRow [codegen id : 5] Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8] -Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_item_sk#1)) (4) Scan parquet spark_catalog.default.customer_demographics Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] @@ -96,16 +96,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,F), EqualTo(cd_marital_status,W), EqualTo(cd_education_status,Primary ), IsNotNull(cd_demo_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = F)) AND (cd_marital_status#12 = W)) AND (cd_education_status#13 = Primary )) AND isnotnull(cd_demo_sk#10)) -(7) Project [codegen id : 1] -Output [1]: [cd_demo_sk#10] +(6) CometProject Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13] +Arguments: [cd_demo_sk#10], [cd_demo_sk#10] + +(7) ColumnarToRow [codegen id : 1] +Input [1]: [cd_demo_sk#10] (8) BroadcastExchange Input [1]: [cd_demo_sk#10] @@ -141,12 +141,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] +(15) CometFilter Input [2]: [s_store_sk#15, s_state#16] +Condition : ((isnotnull(s_state#16) AND (s_state#16 = TN)) AND isnotnull(s_store_sk#15)) -(16) Filter [codegen id : 3] +(16) ColumnarToRow [codegen id : 3] Input [2]: [s_store_sk#15, s_state#16] -Condition : ((isnotnull(s_state#16) AND (s_state#16 = TN)) AND isnotnull(s_store_sk#15)) (17) BroadcastExchange Input [2]: [s_store_sk#15, s_state#16] @@ -169,12 +169,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] +(21) CometFilter Input [2]: [i_item_sk#17, i_item_id#18] +Condition : isnotnull(i_item_sk#17) -(22) Filter [codegen id : 4] +(22) ColumnarToRow [codegen id : 4] Input [2]: [i_item_sk#17, i_item_id#18] -Condition : isnotnull(i_item_sk#17) (23) BroadcastExchange Input [2]: [i_item_sk#17, i_item_id#18] @@ -216,12 +216,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#55), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 11] +(30) CometFilter Input [8]: [ss_item_sk#48, ss_cdemo_sk#49, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55] +Condition : ((isnotnull(ss_cdemo_sk#49) AND isnotnull(ss_store_sk#50)) AND isnotnull(ss_item_sk#48)) -(31) Filter [codegen id : 11] +(31) ColumnarToRow [codegen id : 11] Input [8]: [ss_item_sk#48, ss_cdemo_sk#49, ss_store_sk#50, ss_quantity#51, ss_list_price#52, ss_sales_price#53, ss_coupon_amt#54, ss_sold_date_sk#55] -Condition : ((isnotnull(ss_cdemo_sk#49) AND isnotnull(ss_store_sk#50)) AND isnotnull(ss_item_sk#48)) (32) ReusedExchange [Reuses operator id: 8] Output [1]: [cd_demo_sk#57] @@ -256,16 +256,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] ReadSchema: struct -(39) ColumnarToRow [codegen id : 9] -Input [2]: [s_store_sk#59, s_state#60] - -(40) Filter [codegen id : 9] +(39) CometFilter Input [2]: [s_store_sk#59, s_state#60] Condition : ((isnotnull(s_state#60) AND (s_state#60 = TN)) AND isnotnull(s_store_sk#59)) -(41) Project [codegen id : 9] -Output [1]: [s_store_sk#59] +(40) CometProject Input [2]: [s_store_sk#59, s_state#60] +Arguments: [s_store_sk#59], [s_store_sk#59] + +(41) ColumnarToRow [codegen id : 9] +Input [1]: [s_store_sk#59] (42) BroadcastExchange Input [1]: [s_store_sk#59] @@ -320,12 +320,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#100), dynamicpruningexpression(ss_s PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(52) ColumnarToRow [codegen id : 17] +(52) CometFilter Input [8]: [ss_item_sk#93, ss_cdemo_sk#94, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100] +Condition : ((isnotnull(ss_cdemo_sk#94) AND isnotnull(ss_store_sk#95)) AND isnotnull(ss_item_sk#93)) -(53) Filter [codegen id : 17] +(53) ColumnarToRow [codegen id : 17] Input [8]: [ss_item_sk#93, ss_cdemo_sk#94, ss_store_sk#95, ss_quantity#96, ss_list_price#97, ss_sales_price#98, ss_coupon_amt#99, ss_sold_date_sk#100] -Condition : ((isnotnull(ss_cdemo_sk#94) AND isnotnull(ss_store_sk#95)) AND isnotnull(ss_item_sk#93)) (54) ReusedExchange [Reuses operator id: 8] Output [1]: [cd_demo_sk#102] @@ -373,12 +373,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(64) ColumnarToRow [codegen id : 16] +(64) CometFilter Input [1]: [i_item_sk#105] +Condition : isnotnull(i_item_sk#105) -(65) Filter [codegen id : 16] +(65) ColumnarToRow [codegen id : 16] Input [1]: [i_item_sk#105] -Condition : isnotnull(i_item_sk#105) (66) BroadcastExchange Input [1]: [i_item_sk#105] @@ -422,9 +422,9 @@ Arguments: 100, [i_item_id#18 ASC NULLS FIRST, s_state#16 ASC NULLS FIRST], [i_i Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (78) -+- * Project (77) - +- * Filter (76) - +- * ColumnarToRow (75) ++- * ColumnarToRow (77) + +- CometProject (76) + +- CometFilter (75) +- CometScan parquet spark_catalog.default.date_dim (74) @@ -435,16 +435,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1998), IsNotNull(d_date_sk)] ReadSchema: struct -(75) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#14, d_year#137] - -(76) Filter [codegen id : 1] +(75) CometFilter Input [2]: [d_date_sk#14, d_year#137] Condition : ((isnotnull(d_year#137) AND (d_year#137 = 1998)) AND isnotnull(d_date_sk#14)) -(77) Project [codegen id : 1] -Output [1]: [d_date_sk#14] +(76) CometProject Input [2]: [d_date_sk#14, d_year#137] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(77) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] (78) BroadcastExchange Input [1]: [d_date_sk#14] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/simplified.txt index a05c3e288..32f003798 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q27a/simplified.txt @@ -14,41 +14,41 @@ TakeOrderedAndProject [i_item_id,s_state,g_state,agg1,agg2,agg3,agg4] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] - Filter [ss_cdemo_sk,ss_store_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_cdemo_sk,ss_store_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #2 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Project [cd_demo_sk] - Filter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_gender,cd_marital_status,cd_education_status,cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_education_status] InputAdapter ReusedExchange [d_date_sk] #2 InputAdapter BroadcastExchange #4 WholeStageCodegen (3) - Filter [s_state,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_state,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_state] InputAdapter BroadcastExchange #5 WholeStageCodegen (4) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id] WholeStageCodegen (12) HashAggregate [i_item_id,sum,count,sum,count,sum,count,sum,count] [avg(agg1),avg(UnscaledValue(agg2)),avg(UnscaledValue(agg3)),avg(UnscaledValue(agg4)),s_state,g_state,agg1,agg2,agg3,agg4,sum,count,sum,count,sum,count,sum,count] @@ -64,9 +64,9 @@ TakeOrderedAndProject [i_item_id,s_state,g_state,agg1,agg2,agg3,agg4] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] - Filter [ss_cdemo_sk,ss_store_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_cdemo_sk,ss_store_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -76,10 +76,10 @@ TakeOrderedAndProject [i_item_id,s_state,g_state,agg1,agg2,agg3,agg4] InputAdapter BroadcastExchange #7 WholeStageCodegen (9) - Project [s_store_sk] - Filter [s_state,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_state,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_state] InputAdapter ReusedExchange [i_item_sk,i_item_id] #5 @@ -97,9 +97,9 @@ TakeOrderedAndProject [i_item_id,s_state,g_state,agg1,agg2,agg3,agg4] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_item_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] BroadcastHashJoin [ss_cdemo_sk,cd_demo_sk] - Filter [ss_cdemo_sk,ss_store_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_cdemo_sk,ss_store_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_cdemo_sk,ss_store_sk,ss_quantity,ss_list_price,ss_sales_price,ss_coupon_amt,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -111,7 +111,7 @@ TakeOrderedAndProject [i_item_id,s_state,g_state,agg1,agg2,agg3,agg4] InputAdapter BroadcastExchange #9 WholeStageCodegen (16) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/explain.txt index a42f101d7..387fa47f9 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/explain.txt @@ -13,23 +13,23 @@ : : +- * BroadcastHashJoin Inner BuildRight (12) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (11) - : : +- * Project (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.store (7) : +- BroadcastExchange (18) - : +- * Project (17) - : +- * Filter (16) - : +- * ColumnarToRow (15) + : +- * ColumnarToRow (17) + : +- CometProject (16) + : +- CometFilter (15) : +- CometScan parquet spark_catalog.default.household_demographics (14) +- BroadcastExchange (28) - +- * Filter (27) - +- * ColumnarToRow (26) + +- * ColumnarToRow (27) + +- CometFilter (26) +- CometScan parquet spark_catalog.default.customer (25) @@ -41,12 +41,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] +Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5] -Condition : ((isnotnull(ss_store_sk#3) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_customer_sk#1)) (4) ReusedExchange [Reuses operator id: 37] Output [1]: [d_date_sk#7] @@ -68,16 +68,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_county), EqualTo(s_county,Williamson County), IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] -Input [2]: [s_store_sk#8, s_county#9] - -(9) Filter [codegen id : 2] +(8) CometFilter Input [2]: [s_store_sk#8, s_county#9] Condition : ((isnotnull(s_county#9) AND (s_county#9 = Williamson County)) AND isnotnull(s_store_sk#8)) -(10) Project [codegen id : 2] -Output [1]: [s_store_sk#8] +(9) CometProject Input [2]: [s_store_sk#8, s_county#9] +Arguments: [s_store_sk#8], [s_store_sk#8] + +(10) ColumnarToRow [codegen id : 2] +Input [1]: [s_store_sk#8] (11) BroadcastExchange Input [1]: [s_store_sk#8] @@ -100,16 +100,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_vehicle_count), Or(EqualTo(hd_buy_potential,>10000 ),EqualTo(hd_buy_potential,unknown )), GreaterThan(hd_vehicle_count,0), IsNotNull(hd_demo_sk)] ReadSchema: struct -(15) ColumnarToRow [codegen id : 3] -Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] - -(16) Filter [codegen id : 3] +(15) CometFilter Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] Condition : ((((isnotnull(hd_vehicle_count#13) AND ((hd_buy_potential#11 = >10000 ) OR (hd_buy_potential#11 = unknown ))) AND (hd_vehicle_count#13 > 0)) AND CASE WHEN (hd_vehicle_count#13 > 0) THEN ((cast(hd_dep_count#12 as double) / cast(hd_vehicle_count#13 as double)) > 1.2) END) AND isnotnull(hd_demo_sk#10)) -(17) Project [codegen id : 3] -Output [1]: [hd_demo_sk#10] +(16) CometProject Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13] +Arguments: [hd_demo_sk#10], [hd_demo_sk#10] + +(17) ColumnarToRow [codegen id : 3] +Input [1]: [hd_demo_sk#10] (18) BroadcastExchange Input [1]: [hd_demo_sk#10] @@ -154,12 +154,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 5] +(26) CometFilter Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] +Condition : isnotnull(c_customer_sk#18) -(27) Filter [codegen id : 5] +(27) ColumnarToRow [codegen id : 5] Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] -Condition : isnotnull(c_customer_sk#18) (28) BroadcastExchange Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22] @@ -187,9 +187,9 @@ Arguments: [c_last_name#21 ASC NULLS FIRST, c_first_name#20 ASC NULLS FIRST, c_s Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (37) -+- * Project (36) - +- * Filter (35) - +- * ColumnarToRow (34) ++- * ColumnarToRow (36) + +- CometProject (35) + +- CometFilter (34) +- CometScan parquet spark_catalog.default.date_dim (33) @@ -200,16 +200,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [Or(And(GreaterThanOrEqual(d_dom,1),LessThanOrEqual(d_dom,3)),And(GreaterThanOrEqual(d_dom,25),LessThanOrEqual(d_dom,28))), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)] ReadSchema: struct -(34) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#7, d_year#23, d_dom#24] - -(35) Filter [codegen id : 1] +(34) CometFilter Input [3]: [d_date_sk#7, d_year#23, d_dom#24] Condition : (((((d_dom#24 >= 1) AND (d_dom#24 <= 3)) OR ((d_dom#24 >= 25) AND (d_dom#24 <= 28))) AND d_year#23 IN (1999,2000,2001)) AND isnotnull(d_date_sk#7)) -(36) Project [codegen id : 1] -Output [1]: [d_date_sk#7] +(35) CometProject Input [3]: [d_date_sk#7, d_year#23, d_dom#24] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(36) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] (37) BroadcastExchange Input [1]: [d_date_sk#7] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/simplified.txt index cb7ac8dc8..b473e4892 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q34/simplified.txt @@ -17,40 +17,40 @@ WholeStageCodegen (7) BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_hdemo_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_hdemo_sk,ss_store_sk,ss_ticket_number,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_dom,d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_dom,d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_dom] InputAdapter ReusedExchange [d_date_sk] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Project [s_store_sk] - Filter [s_county,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_county,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_county] InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Project [hd_demo_sk] - Filter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_vehicle_count,hd_buy_potential,hd_dep_count,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential,hd_dep_count,hd_vehicle_count] InputAdapter BroadcastExchange #6 WholeStageCodegen (5) - Filter [c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/explain.txt index 03d608ad6..ce8753277 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/explain.txt @@ -12,8 +12,8 @@ TakeOrderedAndProject (42) : : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (24) : : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (17) : : : :- * BroadcastHashJoin LeftSemi BuildRight (10) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : : +- BroadcastExchange (9) : : : : +- * Project (8) @@ -34,12 +34,12 @@ TakeOrderedAndProject (42) : : : +- CometScan parquet spark_catalog.default.catalog_sales (18) : : +- ReusedExchange (20) : +- BroadcastExchange (30) - : +- * Filter (29) - : +- * ColumnarToRow (28) + : +- * ColumnarToRow (29) + : +- CometFilter (28) : +- CometScan parquet spark_catalog.default.customer_address (27) +- BroadcastExchange (36) - +- * Filter (35) - +- * ColumnarToRow (34) + +- * ColumnarToRow (35) + +- CometFilter (34) +- CometScan parquet spark_catalog.default.customer_demographics (33) @@ -50,12 +50,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 9] +(2) CometFilter Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] +Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) -(3) Filter [codegen id : 9] +(3) ColumnarToRow [codegen id : 9] Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5] -Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4)) (4) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_customer_sk#6, ss_sold_date_sk#7] @@ -171,12 +171,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk)] ReadSchema: struct -(28) ColumnarToRow [codegen id : 7] +(28) CometFilter Input [2]: [ca_address_sk#18, ca_state#19] +Condition : isnotnull(ca_address_sk#18) -(29) Filter [codegen id : 7] +(29) ColumnarToRow [codegen id : 7] Input [2]: [ca_address_sk#18, ca_state#19] -Condition : isnotnull(ca_address_sk#18) (30) BroadcastExchange Input [2]: [ca_address_sk#18, ca_state#19] @@ -199,12 +199,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk)] ReadSchema: struct -(34) ColumnarToRow [codegen id : 8] +(34) CometFilter Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Condition : isnotnull(cd_demo_sk#20) -(35) Filter [codegen id : 8] +(35) ColumnarToRow [codegen id : 8] Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] -Condition : isnotnull(cd_demo_sk#20) (36) BroadcastExchange Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] @@ -246,9 +246,9 @@ Arguments: 100, [ca_state#19 ASC NULLS FIRST, cd_gender#21 ASC NULLS FIRST, cd_m Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (47) -+- * Project (46) - +- * Filter (45) - +- * ColumnarToRow (44) ++- * ColumnarToRow (46) + +- CometProject (45) + +- CometFilter (44) +- CometScan parquet spark_catalog.default.date_dim (43) @@ -259,16 +259,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,2002), LessThan(d_qoy,4), IsNotNull(d_date_sk)] ReadSchema: struct -(44) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] - -(45) Filter [codegen id : 1] +(44) CometFilter Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] Condition : ((((isnotnull(d_year#74) AND isnotnull(d_qoy#75)) AND (d_year#74 = 2002)) AND (d_qoy#75 < 4)) AND isnotnull(d_date_sk#9)) -(46) Project [codegen id : 1] -Output [1]: [d_date_sk#9] +(45) CometProject Input [3]: [d_date_sk#9, d_year#74, d_qoy#75] +Arguments: [d_date_sk#9], [d_date_sk#9] + +(46) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#9] (47) BroadcastExchange Input [1]: [d_date_sk#9] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/simplified.txt index 6b81822e4..dc724ca91 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35/simplified.txt @@ -14,9 +14,9 @@ TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_ BroadcastHashJoin [c_customer_sk,cs_ship_customer_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_current_addr_sk,c_current_cdemo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] InputAdapter BroadcastExchange #2 @@ -29,10 +29,10 @@ TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_ SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_qoy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_qoy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] InputAdapter ReusedExchange [d_date_sk] #3 @@ -61,14 +61,14 @@ TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_ InputAdapter BroadcastExchange #6 WholeStageCodegen (7) - Filter [ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #7 WholeStageCodegen (8) - Filter [cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/explain.txt index 11ca8c0c8..648b19933 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/explain.txt @@ -10,8 +10,8 @@ TakeOrderedAndProject (40) : :- * Project (24) : : +- * BroadcastHashJoin LeftSemi BuildRight (23) : : :- * BroadcastHashJoin LeftSemi BuildRight (10) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : +- BroadcastExchange (9) : : : +- * Project (8) @@ -32,12 +32,12 @@ TakeOrderedAndProject (40) : : : +- CometScan parquet spark_catalog.default.catalog_sales (16) : : +- ReusedExchange (18) : +- BroadcastExchange (28) - : +- * Filter (27) - : +- * ColumnarToRow (26) + : +- * ColumnarToRow (27) + : +- CometFilter (26) : +- CometScan parquet spark_catalog.default.customer_address (25) +- BroadcastExchange (34) - +- * Filter (33) - +- * ColumnarToRow (32) + +- * ColumnarToRow (33) + +- CometFilter (32) +- CometScan parquet spark_catalog.default.customer_demographics (31) @@ -48,12 +48,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 9] +(2) CometFilter Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] +Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) -(3) Filter [codegen id : 9] +(3) ColumnarToRow [codegen id : 9] Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3] -Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2)) (4) Scan parquet spark_catalog.default.store_sales Output [2]: [ss_customer_sk#4, ss_sold_date_sk#5] @@ -157,12 +157,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 7] +(26) CometFilter Input [2]: [ca_address_sk#18, ca_state#19] +Condition : isnotnull(ca_address_sk#18) -(27) Filter [codegen id : 7] +(27) ColumnarToRow [codegen id : 7] Input [2]: [ca_address_sk#18, ca_state#19] -Condition : isnotnull(ca_address_sk#18) (28) BroadcastExchange Input [2]: [ca_address_sk#18, ca_state#19] @@ -185,12 +185,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk)] ReadSchema: struct -(32) ColumnarToRow [codegen id : 8] +(32) CometFilter Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] +Condition : isnotnull(cd_demo_sk#20) -(33) Filter [codegen id : 8] +(33) ColumnarToRow [codegen id : 8] Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] -Condition : isnotnull(cd_demo_sk#20) (34) BroadcastExchange Input [6]: [cd_demo_sk#20, cd_gender#21, cd_marital_status#22, cd_dep_count#23, cd_dep_employed_count#24, cd_dep_college_count#25] @@ -232,9 +232,9 @@ Arguments: 100, [ca_state#19 ASC NULLS FIRST, cd_gender#21 ASC NULLS FIRST, cd_m Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (45) -+- * Project (44) - +- * Filter (43) - +- * ColumnarToRow (42) ++- * ColumnarToRow (44) + +- CometProject (43) + +- CometFilter (42) +- CometScan parquet spark_catalog.default.date_dim (41) @@ -245,16 +245,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,1999), LessThan(d_qoy,4), IsNotNull(d_date_sk)] ReadSchema: struct -(42) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#7, d_year#74, d_qoy#75] - -(43) Filter [codegen id : 1] +(42) CometFilter Input [3]: [d_date_sk#7, d_year#74, d_qoy#75] Condition : ((((isnotnull(d_year#74) AND isnotnull(d_qoy#75)) AND (d_year#74 = 1999)) AND (d_qoy#75 < 4)) AND isnotnull(d_date_sk#7)) -(44) Project [codegen id : 1] -Output [1]: [d_date_sk#7] +(43) CometProject Input [3]: [d_date_sk#7, d_year#74, d_qoy#75] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(44) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] (45) BroadcastExchange Input [1]: [d_date_sk#7] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/simplified.txt index 2cf44995a..e5cb94055 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q35a/simplified.txt @@ -12,9 +12,9 @@ TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_ Project [c_current_cdemo_sk,c_current_addr_sk] BroadcastHashJoin [c_customer_sk,customsk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_current_addr_sk,c_current_cdemo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_current_cdemo_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_addr_sk] InputAdapter BroadcastExchange #2 @@ -27,10 +27,10 @@ TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_ SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_qoy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_qoy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_qoy] InputAdapter ReusedExchange [d_date_sk] #3 @@ -58,14 +58,14 @@ TakeOrderedAndProject [ca_state,cd_gender,cd_marital_status,cd_dep_count,cd_dep_ InputAdapter BroadcastExchange #5 WholeStageCodegen (7) - Filter [ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #6 WholeStageCodegen (8) - Filter [cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_gender,cd_marital_status,cd_dep_count,cd_dep_employed_count,cd_dep_college_count] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/explain.txt index 5a7efec07..2610a698c 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/explain.txt @@ -17,18 +17,18 @@ TakeOrderedAndProject (41) : : +- * BroadcastHashJoin Inner BuildRight (11) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.item (7) : +- BroadcastExchange (17) - : +- * Project (16) - : +- * Filter (15) - : +- * ColumnarToRow (14) + : +- * ColumnarToRow (16) + : +- CometProject (15) + : +- CometFilter (14) : +- CometScan parquet spark_catalog.default.store (13) :- * HashAggregate (27) : +- Exchange (26) @@ -50,12 +50,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_store_sk#2)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5] -Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_store_sk#2)) (4) ReusedExchange [Reuses operator id: 46] Output [1]: [d_date_sk#7] @@ -77,12 +77,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [3]: [i_item_sk#8, i_class#9, i_category#10] +Condition : isnotnull(i_item_sk#8) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [3]: [i_item_sk#8, i_class#9, i_category#10] -Condition : isnotnull(i_item_sk#8) (10) BroadcastExchange Input [3]: [i_item_sk#8, i_class#9, i_category#10] @@ -105,16 +105,16 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] -Input [2]: [s_store_sk#11, s_state#12] - -(15) Filter [codegen id : 3] +(14) CometFilter Input [2]: [s_store_sk#11, s_state#12] Condition : ((isnotnull(s_state#12) AND (s_state#12 = TN)) AND isnotnull(s_store_sk#11)) -(16) Project [codegen id : 3] -Output [1]: [s_store_sk#11] +(15) CometProject Input [2]: [s_store_sk#11, s_state#12] +Arguments: [s_store_sk#11], [s_store_sk#11] + +(16) ColumnarToRow [codegen id : 3] +Input [1]: [s_store_sk#11] (17) BroadcastExchange Input [1]: [s_store_sk#11] @@ -248,9 +248,9 @@ Arguments: 100, [lochierarchy#22 DESC NULLS LAST, CASE WHEN (lochierarchy#22 = 0 Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (46) -+- * Project (45) - +- * Filter (44) - +- * ColumnarToRow (43) ++- * ColumnarToRow (45) + +- CometProject (44) + +- CometFilter (43) +- CometScan parquet spark_catalog.default.date_dim (42) @@ -261,16 +261,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(43) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#7, d_year#74] - -(44) Filter [codegen id : 1] +(43) CometFilter Input [2]: [d_date_sk#7, d_year#74] Condition : ((isnotnull(d_year#74) AND (d_year#74 = 2001)) AND isnotnull(d_date_sk#7)) -(45) Project [codegen id : 1] -Output [1]: [d_date_sk#7] +(44) CometProject Input [2]: [d_date_sk#7, d_year#74] +Arguments: [d_date_sk#7], [d_date_sk#7] + +(45) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#7] (46) BroadcastExchange Input [1]: [d_date_sk#7] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/simplified.txt index 9d07011c7..f265d2099 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q36a/simplified.txt @@ -27,34 +27,34 @@ TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,gross_margin,i BroadcastHashJoin [ss_item_sk,i_item_sk] Project [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_item_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (2) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] InputAdapter BroadcastExchange #6 WholeStageCodegen (3) - Project [s_store_sk] - Filter [s_state,s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [s_store_sk] + CometFilter [s_state,s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_state] WholeStageCodegen (11) HashAggregate [i_category,sum,isEmpty,sum,isEmpty] [sum(ss_net_profit),sum(ss_ext_sales_price),gross_margin,i_class,t_category,t_class,lochierarchy,sum,isEmpty,sum,isEmpty] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/explain.txt index 95dc7f0cd..9cb7b35cb 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/explain.txt @@ -20,17 +20,17 @@ TakeOrderedAndProject (45) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.item (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.store_sales (4) : : : +- ReusedExchange (10) : : +- BroadcastExchange (16) - : : +- * Filter (15) - : : +- * ColumnarToRow (14) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) : : +- CometScan parquet spark_catalog.default.store (13) : +- BroadcastExchange (35) : +- * Project (34) @@ -53,12 +53,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [3]: [i_item_sk#1, i_brand#2, i_category#3] -Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) (4) Scan parquet spark_catalog.default.store_sales Output [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] @@ -68,12 +68,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#4) AND isnotnull(ss_store_sk#5)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] -Condition : (isnotnull(ss_item_sk#4) AND isnotnull(ss_store_sk#5)) (7) BroadcastExchange Input [4]: [ss_item_sk#4, ss_store_sk#5, ss_sales_price#6, ss_sold_date_sk#7] @@ -109,12 +109,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_company_name)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] +Condition : ((isnotnull(s_store_sk#12) AND isnotnull(s_store_name#13)) AND isnotnull(s_company_name#14)) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] -Condition : ((isnotnull(s_store_sk#12) AND isnotnull(s_store_name#13)) AND isnotnull(s_company_name#14)) (16) BroadcastExchange Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14] @@ -253,8 +253,8 @@ Arguments: 100, [(sum_sales#18 - avg_monthly_sales#21) ASC NULLS FIRST, d_moy#11 Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (49) -+- * Filter (48) - +- * ColumnarToRow (47) ++- * ColumnarToRow (48) + +- CometFilter (47) +- CometScan parquet spark_catalog.default.date_dim (46) @@ -265,12 +265,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] ReadSchema: struct -(47) ColumnarToRow [codegen id : 1] +(47) CometFilter Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) -(48) Filter [codegen id : 1] +(48) ColumnarToRow [codegen id : 1] Input [3]: [d_date_sk#9, d_year#10, d_moy#11] -Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) (49) BroadcastExchange Input [3]: [d_date_sk#9, d_year#10, d_moy#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/simplified.txt index 1a45368ff..a54895305 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q47/simplified.txt @@ -28,32 +28,32 @@ TakeOrderedAndProject [sum_sales,avg_monthly_sales,d_moy,i_category,d_year,psum, BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [i_brand,i_category,ss_store_sk,ss_sales_price,ss_sold_date_sk] BroadcastHashJoin [i_item_sk,ss_item_sk] - Filter [i_item_sk,i_category,i_brand] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_category,i_brand] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [ss_item_sk,ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk,d_year,d_moy] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [s_store_sk,s_store_name,s_company_name] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_name,s_company_name] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_company_name] InputAdapter BroadcastExchange #6 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/explain.txt index 2a8889da9..6591c8b8a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/explain.txt @@ -1,81 +1,78 @@ == Physical Plan == -TakeOrderedAndProject (77) -+- * HashAggregate (76) - +- Exchange (75) - +- * HashAggregate (74) - +- Union (73) - :- * Project (24) - : +- * Filter (23) - : +- Window (22) - : +- * Sort (21) - : +- Window (20) - : +- * Sort (19) - : +- Exchange (18) - : +- * HashAggregate (17) - : +- Exchange (16) - : +- * HashAggregate (15) - : +- * Project (14) - : +- * BroadcastHashJoin Inner BuildRight (13) - : :- * Project (11) - : : +- * BroadcastHashJoin Inner BuildLeft (10) - : : :- BroadcastExchange (5) - : : : +- * Project (4) - : : : +- * Filter (3) - : : : +- * ColumnarToRow (2) - : : : +- CometScan parquet spark_catalog.default.web_sales (1) - : : +- * Project (9) - : : +- * Filter (8) - : : +- * ColumnarToRow (7) - : : +- CometScan parquet spark_catalog.default.web_returns (6) - : +- ReusedExchange (12) - :- * Project (48) - : +- * Filter (47) - : +- Window (46) - : +- * Sort (45) - : +- Window (44) - : +- * Sort (43) - : +- Exchange (42) - : +- * HashAggregate (41) - : +- Exchange (40) - : +- * HashAggregate (39) - : +- * Project (38) - : +- * BroadcastHashJoin Inner BuildRight (37) - : :- * Project (35) - : : +- * BroadcastHashJoin Inner BuildLeft (34) - : : :- BroadcastExchange (29) - : : : +- * Project (28) - : : : +- * Filter (27) - : : : +- * ColumnarToRow (26) - : : : +- CometScan parquet spark_catalog.default.catalog_sales (25) - : : +- * Project (33) - : : +- * Filter (32) - : : +- * ColumnarToRow (31) - : : +- CometScan parquet spark_catalog.default.catalog_returns (30) - : +- ReusedExchange (36) - +- * Project (72) - +- * Filter (71) - +- Window (70) - +- * Sort (69) - +- Window (68) - +- * Sort (67) - +- Exchange (66) - +- * HashAggregate (65) - +- Exchange (64) - +- * HashAggregate (63) - +- * Project (62) - +- * BroadcastHashJoin Inner BuildRight (61) - :- * Project (59) - : +- * BroadcastHashJoin Inner BuildLeft (58) - : :- BroadcastExchange (53) - : : +- * Project (52) - : : +- * Filter (51) - : : +- * ColumnarToRow (50) - : : +- CometScan parquet spark_catalog.default.store_sales (49) - : +- * Project (57) - : +- * Filter (56) - : +- * ColumnarToRow (55) - : +- CometScan parquet spark_catalog.default.store_returns (54) - +- ReusedExchange (60) +TakeOrderedAndProject (74) ++- * HashAggregate (73) + +- Exchange (72) + +- * HashAggregate (71) + +- Union (70) + :- * Project (23) + : +- * Filter (22) + : +- Window (21) + : +- * Sort (20) + : +- Window (19) + : +- * Sort (18) + : +- Exchange (17) + : +- * HashAggregate (16) + : +- Exchange (15) + : +- * HashAggregate (14) + : +- * Project (13) + : +- * BroadcastHashJoin Inner BuildRight (12) + : :- * ColumnarToRow (10) + : : +- CometProject (9) + : : +- CometBroadcastHashJoin (8) + : : :- CometBroadcastExchange (4) + : : : +- CometProject (3) + : : : +- CometFilter (2) + : : : +- CometScan parquet spark_catalog.default.web_sales (1) + : : +- CometProject (7) + : : +- CometFilter (6) + : : +- CometScan parquet spark_catalog.default.web_returns (5) + : +- ReusedExchange (11) + :- * Project (46) + : +- * Filter (45) + : +- Window (44) + : +- * Sort (43) + : +- Window (42) + : +- * Sort (41) + : +- Exchange (40) + : +- * HashAggregate (39) + : +- Exchange (38) + : +- * HashAggregate (37) + : +- * Project (36) + : +- * BroadcastHashJoin Inner BuildRight (35) + : :- * ColumnarToRow (33) + : : +- CometProject (32) + : : +- CometBroadcastHashJoin (31) + : : :- CometBroadcastExchange (27) + : : : +- CometProject (26) + : : : +- CometFilter (25) + : : : +- CometScan parquet spark_catalog.default.catalog_sales (24) + : : +- CometProject (30) + : : +- CometFilter (29) + : : +- CometScan parquet spark_catalog.default.catalog_returns (28) + : +- ReusedExchange (34) + +- * Project (69) + +- * Filter (68) + +- Window (67) + +- * Sort (66) + +- Window (65) + +- * Sort (64) + +- Exchange (63) + +- * HashAggregate (62) + +- Exchange (61) + +- * HashAggregate (60) + +- * Project (59) + +- * BroadcastHashJoin Inner BuildRight (58) + :- * ColumnarToRow (56) + : +- CometProject (55) + : +- CometBroadcastHashJoin (54) + : :- CometBroadcastExchange (50) + : : +- CometProject (49) + : : +- CometFilter (48) + : : +- CometScan parquet spark_catalog.default.store_sales (47) + : +- CometProject (53) + : +- CometFilter (52) + : +- CometScan parquet spark_catalog.default.store_returns (51) + +- ReusedExchange (57) (1) Scan parquet spark_catalog.default.web_sales @@ -86,109 +83,105 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#6), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_net_profit), IsNotNull(ws_net_paid), IsNotNull(ws_quantity), GreaterThan(ws_net_profit,1.00), GreaterThan(ws_net_paid,0.00), GreaterThan(ws_quantity,0), IsNotNull(ws_order_number), IsNotNull(ws_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] Condition : (((((((isnotnull(ws_net_profit#5) AND isnotnull(ws_net_paid#4)) AND isnotnull(ws_quantity#3)) AND (ws_net_profit#5 > 1.00)) AND (ws_net_paid#4 > 0.00)) AND (ws_quantity#3 > 0)) AND isnotnull(ws_order_number#2)) AND isnotnull(ws_item_sk#1)) -(4) Project [codegen id : 1] -Output [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +(3) CometProject Input [6]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_net_profit#5, ws_sold_date_sk#6] +Arguments: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6], [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] -(5) BroadcastExchange +(4) CometBroadcastExchange Input [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=1] +Arguments: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] -(6) Scan parquet spark_catalog.default.web_returns +(5) Scan parquet spark_catalog.default.web_returns Output [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] Batched: true Location [not included in comparison]/{warehouse_dir}/web_returns] PushedFilters: [IsNotNull(wr_return_amt), GreaterThan(wr_return_amt,10000.00), IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] ReadSchema: struct -(7) ColumnarToRow -Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] - -(8) Filter +(6) CometFilter Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] Condition : (((isnotnull(wr_return_amt#11) AND (wr_return_amt#11 > 10000.00)) AND isnotnull(wr_order_number#9)) AND isnotnull(wr_item_sk#8)) -(9) Project -Output [4]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +(7) CometProject Input [5]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11, wr_returned_date_sk#12] +Arguments: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11], [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] -(10) BroadcastHashJoin [codegen id : 3] -Left keys [2]: [ws_order_number#2, ws_item_sk#1] -Right keys [2]: [wr_order_number#9, wr_item_sk#8] -Join type: Inner -Join condition: None +(8) CometBroadcastHashJoin +Left output [5]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6] +Right output [4]: [wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +Arguments: [ws_order_number#2, ws_item_sk#1], [wr_order_number#9, wr_item_sk#8], Inner -(11) Project [codegen id : 3] -Output [6]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] +(9) CometProject Input [9]: [ws_item_sk#1, ws_order_number#2, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_item_sk#8, wr_order_number#9, wr_return_quantity#10, wr_return_amt#11] +Arguments: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11], [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] -(12) ReusedExchange [Reuses operator id: 82] +(10) ColumnarToRow [codegen id : 2] +Input [6]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11] + +(11) ReusedExchange [Reuses operator id: 79] Output [1]: [d_date_sk#13] -(13) BroadcastHashJoin [codegen id : 3] +(12) BroadcastHashJoin [codegen id : 2] Left keys [1]: [ws_sold_date_sk#6] Right keys [1]: [d_date_sk#13] Join type: Inner Join condition: None -(14) Project [codegen id : 3] +(13) Project [codegen id : 2] Output [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] Input [7]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, ws_sold_date_sk#6, wr_return_quantity#10, wr_return_amt#11, d_date_sk#13] -(15) HashAggregate [codegen id : 3] +(14) HashAggregate [codegen id : 2] Input [5]: [ws_item_sk#1, ws_quantity#3, ws_net_paid#4, wr_return_quantity#10, wr_return_amt#11] Keys [1]: [ws_item_sk#1] Functions [4]: [partial_sum(coalesce(wr_return_quantity#10, 0)), partial_sum(coalesce(ws_quantity#3, 0)), partial_sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] Aggregate Attributes [6]: [sum#14, sum#15, sum#16, isEmpty#17, sum#18, isEmpty#19] Results [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] -(16) Exchange +(15) Exchange Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] -Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] +Arguments: hashpartitioning(ws_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] -(17) HashAggregate [codegen id : 4] +(16) HashAggregate [codegen id : 3] Input [7]: [ws_item_sk#1, sum#20, sum#21, sum#22, isEmpty#23, sum#24, isEmpty#25] Keys [1]: [ws_item_sk#1] Functions [4]: [sum(coalesce(wr_return_quantity#10, 0)), sum(coalesce(ws_quantity#3, 0)), sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00)), sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))] Aggregate Attributes [4]: [sum(coalesce(wr_return_quantity#10, 0))#26, sum(coalesce(ws_quantity#3, 0))#27, sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28, sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29] Results [3]: [ws_item_sk#1 AS item#30, (cast(sum(coalesce(wr_return_quantity#10, 0))#26 as decimal(15,4)) / cast(sum(coalesce(ws_quantity#3, 0))#27 as decimal(15,4))) AS return_ratio#31, (cast(sum(coalesce(cast(wr_return_amt#11 as decimal(12,2)), 0.00))#28 as decimal(15,4)) / cast(sum(coalesce(cast(ws_net_paid#4 as decimal(12,2)), 0.00))#29 as decimal(15,4))) AS currency_ratio#32] -(18) Exchange +(17) Exchange Input [3]: [item#30, return_ratio#31, currency_ratio#32] -Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=3] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=2] -(19) Sort [codegen id : 5] +(18) Sort [codegen id : 4] Input [3]: [item#30, return_ratio#31, currency_ratio#32] Arguments: [return_ratio#31 ASC NULLS FIRST], false, 0 -(20) Window +(19) Window Input [3]: [item#30, return_ratio#31, currency_ratio#32] Arguments: [rank(return_ratio#31) windowspecdefinition(return_ratio#31 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#33], [return_ratio#31 ASC NULLS FIRST] -(21) Sort [codegen id : 6] +(20) Sort [codegen id : 5] Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] Arguments: [currency_ratio#32 ASC NULLS FIRST], false, 0 -(22) Window +(21) Window Input [4]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33] Arguments: [rank(currency_ratio#32) windowspecdefinition(currency_ratio#32 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#34], [currency_ratio#32 ASC NULLS FIRST] -(23) Filter [codegen id : 7] +(22) Filter [codegen id : 6] Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] Condition : ((return_rank#33 <= 10) OR (currency_rank#34 <= 10)) -(24) Project [codegen id : 7] +(23) Project [codegen id : 6] Output [5]: [web AS channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Input [5]: [item#30, return_ratio#31, currency_ratio#32, return_rank#33, currency_rank#34] -(25) Scan parquet spark_catalog.default.catalog_sales +(24) Scan parquet spark_catalog.default.catalog_sales Output [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] Batched: true Location: InMemoryFileIndex [] @@ -196,109 +189,105 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#41), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_net_profit), IsNotNull(cs_net_paid), IsNotNull(cs_quantity), GreaterThan(cs_net_profit,1.00), GreaterThan(cs_net_paid,0.00), GreaterThan(cs_quantity,0), IsNotNull(cs_order_number), IsNotNull(cs_item_sk)] ReadSchema: struct -(26) ColumnarToRow [codegen id : 8] -Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] - -(27) Filter [codegen id : 8] +(25) CometFilter Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] Condition : (((((((isnotnull(cs_net_profit#40) AND isnotnull(cs_net_paid#39)) AND isnotnull(cs_quantity#38)) AND (cs_net_profit#40 > 1.00)) AND (cs_net_paid#39 > 0.00)) AND (cs_quantity#38 > 0)) AND isnotnull(cs_order_number#37)) AND isnotnull(cs_item_sk#36)) -(28) Project [codegen id : 8] -Output [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +(26) CometProject Input [6]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_net_profit#40, cs_sold_date_sk#41] +Arguments: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41], [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] -(29) BroadcastExchange +(27) CometBroadcastExchange Input [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=4] +Arguments: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] -(30) Scan parquet spark_catalog.default.catalog_returns +(28) Scan parquet spark_catalog.default.catalog_returns Output [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] Batched: true Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_return_amount), GreaterThan(cr_return_amount,10000.00), IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] ReadSchema: struct -(31) ColumnarToRow -Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] - -(32) Filter +(29) CometFilter Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] Condition : (((isnotnull(cr_return_amount#46) AND (cr_return_amount#46 > 10000.00)) AND isnotnull(cr_order_number#44)) AND isnotnull(cr_item_sk#43)) -(33) Project -Output [4]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +(30) CometProject Input [5]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46, cr_returned_date_sk#47] +Arguments: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46], [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] -(34) BroadcastHashJoin [codegen id : 10] -Left keys [2]: [cs_order_number#37, cs_item_sk#36] -Right keys [2]: [cr_order_number#44, cr_item_sk#43] -Join type: Inner -Join condition: None +(31) CometBroadcastHashJoin +Left output [5]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41] +Right output [4]: [cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +Arguments: [cs_order_number#37, cs_item_sk#36], [cr_order_number#44, cr_item_sk#43], Inner -(35) Project [codegen id : 10] -Output [6]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] +(32) CometProject Input [9]: [cs_item_sk#36, cs_order_number#37, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_item_sk#43, cr_order_number#44, cr_return_quantity#45, cr_return_amount#46] +Arguments: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46], [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] + +(33) ColumnarToRow [codegen id : 8] +Input [6]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46] -(36) ReusedExchange [Reuses operator id: 82] +(34) ReusedExchange [Reuses operator id: 79] Output [1]: [d_date_sk#48] -(37) BroadcastHashJoin [codegen id : 10] +(35) BroadcastHashJoin [codegen id : 8] Left keys [1]: [cs_sold_date_sk#41] Right keys [1]: [d_date_sk#48] Join type: Inner Join condition: None -(38) Project [codegen id : 10] +(36) Project [codegen id : 8] Output [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] Input [7]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cs_sold_date_sk#41, cr_return_quantity#45, cr_return_amount#46, d_date_sk#48] -(39) HashAggregate [codegen id : 10] +(37) HashAggregate [codegen id : 8] Input [5]: [cs_item_sk#36, cs_quantity#38, cs_net_paid#39, cr_return_quantity#45, cr_return_amount#46] Keys [1]: [cs_item_sk#36] Functions [4]: [partial_sum(coalesce(cr_return_quantity#45, 0)), partial_sum(coalesce(cs_quantity#38, 0)), partial_sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] Aggregate Attributes [6]: [sum#49, sum#50, sum#51, isEmpty#52, sum#53, isEmpty#54] Results [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] -(40) Exchange +(38) Exchange Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] -Arguments: hashpartitioning(cs_item_sk#36, 5), ENSURE_REQUIREMENTS, [plan_id=5] +Arguments: hashpartitioning(cs_item_sk#36, 5), ENSURE_REQUIREMENTS, [plan_id=3] -(41) HashAggregate [codegen id : 11] +(39) HashAggregate [codegen id : 9] Input [7]: [cs_item_sk#36, sum#55, sum#56, sum#57, isEmpty#58, sum#59, isEmpty#60] Keys [1]: [cs_item_sk#36] Functions [4]: [sum(coalesce(cr_return_quantity#45, 0)), sum(coalesce(cs_quantity#38, 0)), sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00)), sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))] Aggregate Attributes [4]: [sum(coalesce(cr_return_quantity#45, 0))#61, sum(coalesce(cs_quantity#38, 0))#62, sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63, sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64] Results [3]: [cs_item_sk#36 AS item#65, (cast(sum(coalesce(cr_return_quantity#45, 0))#61 as decimal(15,4)) / cast(sum(coalesce(cs_quantity#38, 0))#62 as decimal(15,4))) AS return_ratio#66, (cast(sum(coalesce(cast(cr_return_amount#46 as decimal(12,2)), 0.00))#63 as decimal(15,4)) / cast(sum(coalesce(cast(cs_net_paid#39 as decimal(12,2)), 0.00))#64 as decimal(15,4))) AS currency_ratio#67] -(42) Exchange +(40) Exchange Input [3]: [item#65, return_ratio#66, currency_ratio#67] -Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4] -(43) Sort [codegen id : 12] +(41) Sort [codegen id : 10] Input [3]: [item#65, return_ratio#66, currency_ratio#67] Arguments: [return_ratio#66 ASC NULLS FIRST], false, 0 -(44) Window +(42) Window Input [3]: [item#65, return_ratio#66, currency_ratio#67] Arguments: [rank(return_ratio#66) windowspecdefinition(return_ratio#66 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#68], [return_ratio#66 ASC NULLS FIRST] -(45) Sort [codegen id : 13] +(43) Sort [codegen id : 11] Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] Arguments: [currency_ratio#67 ASC NULLS FIRST], false, 0 -(46) Window +(44) Window Input [4]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68] Arguments: [rank(currency_ratio#67) windowspecdefinition(currency_ratio#67 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#69], [currency_ratio#67 ASC NULLS FIRST] -(47) Filter [codegen id : 14] +(45) Filter [codegen id : 12] Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] Condition : ((return_rank#68 <= 10) OR (currency_rank#69 <= 10)) -(48) Project [codegen id : 14] +(46) Project [codegen id : 12] Output [5]: [catalog AS channel#70, item#65, return_ratio#66, return_rank#68, currency_rank#69] Input [5]: [item#65, return_ratio#66, currency_ratio#67, return_rank#68, currency_rank#69] -(49) Scan parquet spark_catalog.default.store_sales +(47) Scan parquet spark_catalog.default.store_sales Output [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] Batched: true Location: InMemoryFileIndex [] @@ -306,166 +295,162 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#76), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_net_profit), IsNotNull(ss_net_paid), IsNotNull(ss_quantity), GreaterThan(ss_net_profit,1.00), GreaterThan(ss_net_paid,0.00), GreaterThan(ss_quantity,0), IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk)] ReadSchema: struct -(50) ColumnarToRow [codegen id : 15] -Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] - -(51) Filter [codegen id : 15] +(48) CometFilter Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] Condition : (((((((isnotnull(ss_net_profit#75) AND isnotnull(ss_net_paid#74)) AND isnotnull(ss_quantity#73)) AND (ss_net_profit#75 > 1.00)) AND (ss_net_paid#74 > 0.00)) AND (ss_quantity#73 > 0)) AND isnotnull(ss_ticket_number#72)) AND isnotnull(ss_item_sk#71)) -(52) Project [codegen id : 15] -Output [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +(49) CometProject Input [6]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_net_profit#75, ss_sold_date_sk#76] +Arguments: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76], [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] -(53) BroadcastExchange +(50) CometBroadcastExchange Input [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=7] +Arguments: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] -(54) Scan parquet spark_catalog.default.store_returns +(51) Scan parquet spark_catalog.default.store_returns Output [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] Batched: true Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_return_amt), GreaterThan(sr_return_amt,10000.00), IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] ReadSchema: struct -(55) ColumnarToRow -Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] - -(56) Filter +(52) CometFilter Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] Condition : (((isnotnull(sr_return_amt#81) AND (sr_return_amt#81 > 10000.00)) AND isnotnull(sr_ticket_number#79)) AND isnotnull(sr_item_sk#78)) -(57) Project -Output [4]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +(53) CometProject Input [5]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81, sr_returned_date_sk#82] +Arguments: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81], [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] -(58) BroadcastHashJoin [codegen id : 17] -Left keys [2]: [ss_ticket_number#72, ss_item_sk#71] -Right keys [2]: [sr_ticket_number#79, sr_item_sk#78] -Join type: Inner -Join condition: None +(54) CometBroadcastHashJoin +Left output [5]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76] +Right output [4]: [sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +Arguments: [ss_ticket_number#72, ss_item_sk#71], [sr_ticket_number#79, sr_item_sk#78], Inner -(59) Project [codegen id : 17] -Output [6]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] +(55) CometProject Input [9]: [ss_item_sk#71, ss_ticket_number#72, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_item_sk#78, sr_ticket_number#79, sr_return_quantity#80, sr_return_amt#81] +Arguments: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81], [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] + +(56) ColumnarToRow [codegen id : 14] +Input [6]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81] -(60) ReusedExchange [Reuses operator id: 82] +(57) ReusedExchange [Reuses operator id: 79] Output [1]: [d_date_sk#83] -(61) BroadcastHashJoin [codegen id : 17] +(58) BroadcastHashJoin [codegen id : 14] Left keys [1]: [ss_sold_date_sk#76] Right keys [1]: [d_date_sk#83] Join type: Inner Join condition: None -(62) Project [codegen id : 17] +(59) Project [codegen id : 14] Output [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] Input [7]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, ss_sold_date_sk#76, sr_return_quantity#80, sr_return_amt#81, d_date_sk#83] -(63) HashAggregate [codegen id : 17] +(60) HashAggregate [codegen id : 14] Input [5]: [ss_item_sk#71, ss_quantity#73, ss_net_paid#74, sr_return_quantity#80, sr_return_amt#81] Keys [1]: [ss_item_sk#71] Functions [4]: [partial_sum(coalesce(sr_return_quantity#80, 0)), partial_sum(coalesce(ss_quantity#73, 0)), partial_sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), partial_sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] Aggregate Attributes [6]: [sum#84, sum#85, sum#86, isEmpty#87, sum#88, isEmpty#89] Results [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] -(64) Exchange +(61) Exchange Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] -Arguments: hashpartitioning(ss_item_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=8] +Arguments: hashpartitioning(ss_item_sk#71, 5), ENSURE_REQUIREMENTS, [plan_id=5] -(65) HashAggregate [codegen id : 18] +(62) HashAggregate [codegen id : 15] Input [7]: [ss_item_sk#71, sum#90, sum#91, sum#92, isEmpty#93, sum#94, isEmpty#95] Keys [1]: [ss_item_sk#71] Functions [4]: [sum(coalesce(sr_return_quantity#80, 0)), sum(coalesce(ss_quantity#73, 0)), sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00)), sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))] Aggregate Attributes [4]: [sum(coalesce(sr_return_quantity#80, 0))#96, sum(coalesce(ss_quantity#73, 0))#97, sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98, sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99] Results [3]: [ss_item_sk#71 AS item#100, (cast(sum(coalesce(sr_return_quantity#80, 0))#96 as decimal(15,4)) / cast(sum(coalesce(ss_quantity#73, 0))#97 as decimal(15,4))) AS return_ratio#101, (cast(sum(coalesce(cast(sr_return_amt#81 as decimal(12,2)), 0.00))#98 as decimal(15,4)) / cast(sum(coalesce(cast(ss_net_paid#74 as decimal(12,2)), 0.00))#99 as decimal(15,4))) AS currency_ratio#102] -(66) Exchange +(63) Exchange Input [3]: [item#100, return_ratio#101, currency_ratio#102] -Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=9] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=6] -(67) Sort [codegen id : 19] +(64) Sort [codegen id : 16] Input [3]: [item#100, return_ratio#101, currency_ratio#102] Arguments: [return_ratio#101 ASC NULLS FIRST], false, 0 -(68) Window +(65) Window Input [3]: [item#100, return_ratio#101, currency_ratio#102] Arguments: [rank(return_ratio#101) windowspecdefinition(return_ratio#101 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS return_rank#103], [return_ratio#101 ASC NULLS FIRST] -(69) Sort [codegen id : 20] +(66) Sort [codegen id : 17] Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] Arguments: [currency_ratio#102 ASC NULLS FIRST], false, 0 -(70) Window +(67) Window Input [4]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103] Arguments: [rank(currency_ratio#102) windowspecdefinition(currency_ratio#102 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS currency_rank#104], [currency_ratio#102 ASC NULLS FIRST] -(71) Filter [codegen id : 21] +(68) Filter [codegen id : 18] Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] Condition : ((return_rank#103 <= 10) OR (currency_rank#104 <= 10)) -(72) Project [codegen id : 21] +(69) Project [codegen id : 18] Output [5]: [store AS channel#105, item#100, return_ratio#101, return_rank#103, currency_rank#104] Input [5]: [item#100, return_ratio#101, currency_ratio#102, return_rank#103, currency_rank#104] -(73) Union +(70) Union -(74) HashAggregate [codegen id : 22] +(71) HashAggregate [codegen id : 19] Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Functions: [] Aggregate Attributes: [] Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] -(75) Exchange +(72) Exchange Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] -Arguments: hashpartitioning(channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34, 5), ENSURE_REQUIREMENTS, [plan_id=10] +Arguments: hashpartitioning(channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34, 5), ENSURE_REQUIREMENTS, [plan_id=7] -(76) HashAggregate [codegen id : 23] +(73) HashAggregate [codegen id : 20] Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Keys [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Functions: [] Aggregate Attributes: [] Results [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] -(77) TakeOrderedAndProject +(74) TakeOrderedAndProject Input [5]: [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] Arguments: 100, [channel#35 ASC NULLS FIRST, return_rank#33 ASC NULLS FIRST, currency_rank#34 ASC NULLS FIRST, item#30 ASC NULLS FIRST], [channel#35, item#30, return_ratio#31, return_rank#33, currency_rank#34] ===== Subqueries ===== Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#6 IN dynamicpruning#7 -BroadcastExchange (82) -+- * Project (81) - +- * Filter (80) - +- * ColumnarToRow (79) - +- CometScan parquet spark_catalog.default.date_dim (78) +BroadcastExchange (79) ++- * ColumnarToRow (78) + +- CometProject (77) + +- CometFilter (76) + +- CometScan parquet spark_catalog.default.date_dim (75) -(78) Scan parquet spark_catalog.default.date_dim +(75) Scan parquet spark_catalog.default.date_dim Output [3]: [d_date_sk#13, d_year#106, d_moy#107] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,12), IsNotNull(d_date_sk)] ReadSchema: struct -(79) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#13, d_year#106, d_moy#107] - -(80) Filter [codegen id : 1] +(76) CometFilter Input [3]: [d_date_sk#13, d_year#106, d_moy#107] Condition : ((((isnotnull(d_year#106) AND isnotnull(d_moy#107)) AND (d_year#106 = 2001)) AND (d_moy#107 = 12)) AND isnotnull(d_date_sk#13)) -(81) Project [codegen id : 1] -Output [1]: [d_date_sk#13] +(77) CometProject Input [3]: [d_date_sk#13, d_year#106, d_moy#107] +Arguments: [d_date_sk#13], [d_date_sk#13] + +(78) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#13] -(82) BroadcastExchange +(79) BroadcastExchange Input [1]: [d_date_sk#13] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8] -Subquery:2 Hosting operator id = 25 Hosting Expression = cs_sold_date_sk#41 IN dynamicpruning#7 +Subquery:2 Hosting operator id = 24 Hosting Expression = cs_sold_date_sk#41 IN dynamicpruning#7 -Subquery:3 Hosting operator id = 49 Hosting Expression = ss_sold_date_sk#76 IN dynamicpruning#7 +Subquery:3 Hosting operator id = 47 Hosting Expression = ss_sold_date_sk#76 IN dynamicpruning#7 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/simplified.txt index b707750da..43ebf34cc 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q49/simplified.txt @@ -1,133 +1,121 @@ TakeOrderedAndProject [channel,return_rank,currency_rank,item,return_ratio] - WholeStageCodegen (23) + WholeStageCodegen (20) HashAggregate [channel,item,return_ratio,return_rank,currency_rank] InputAdapter Exchange [channel,item,return_ratio,return_rank,currency_rank] #1 - WholeStageCodegen (22) + WholeStageCodegen (19) HashAggregate [channel,item,return_ratio,return_rank,currency_rank] InputAdapter Union - WholeStageCodegen (7) + WholeStageCodegen (6) Project [item,return_ratio,return_rank,currency_rank] Filter [return_rank,currency_rank] InputAdapter Window [currency_ratio] - WholeStageCodegen (6) + WholeStageCodegen (5) Sort [currency_ratio] InputAdapter Window [return_ratio] - WholeStageCodegen (5) + WholeStageCodegen (4) Sort [return_ratio] InputAdapter Exchange #2 - WholeStageCodegen (4) + WholeStageCodegen (3) HashAggregate [ws_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(wr_return_quantity, 0)),sum(coalesce(ws_quantity, 0)),sum(coalesce(cast(wr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ws_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] InputAdapter Exchange [ws_item_sk] #3 - WholeStageCodegen (3) + WholeStageCodegen (2) HashAggregate [ws_item_sk,wr_return_quantity,ws_quantity,wr_return_amt,ws_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] Project [ws_item_sk,ws_quantity,ws_net_paid,wr_return_quantity,wr_return_amt] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Project [ws_item_sk,ws_quantity,ws_net_paid,ws_sold_date_sk,wr_return_quantity,wr_return_amt] - BroadcastHashJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] - InputAdapter - BroadcastExchange #4 - WholeStageCodegen (1) - Project [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_sold_date_sk] - Filter [ws_net_profit,ws_net_paid,ws_quantity,ws_order_number,ws_item_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_net_profit,ws_sold_date_sk] - SubqueryBroadcast [d_date_sk] #1 - BroadcastExchange #5 - WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] - Project [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] - Filter [wr_return_amt,wr_order_number,wr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ws_item_sk,ws_quantity,ws_net_paid,ws_sold_date_sk,wr_return_quantity,wr_return_amt] + CometBroadcastHashJoin [ws_order_number,ws_item_sk,wr_order_number,wr_item_sk] + CometBroadcastExchange #4 + CometProject [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_sold_date_sk] + CometFilter [ws_net_profit,ws_net_paid,ws_quantity,ws_order_number,ws_item_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_net_paid,ws_net_profit,ws_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_year,d_moy,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] + CometProject [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + CometFilter [wr_return_amt,wr_order_number,wr_item_sk] CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #5 - WholeStageCodegen (14) + WholeStageCodegen (12) Project [item,return_ratio,return_rank,currency_rank] Filter [return_rank,currency_rank] InputAdapter Window [currency_ratio] - WholeStageCodegen (13) + WholeStageCodegen (11) Sort [currency_ratio] InputAdapter Window [return_ratio] - WholeStageCodegen (12) + WholeStageCodegen (10) Sort [return_ratio] InputAdapter Exchange #6 - WholeStageCodegen (11) + WholeStageCodegen (9) HashAggregate [cs_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(cr_return_quantity, 0)),sum(coalesce(cs_quantity, 0)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum(coalesce(cast(cs_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] InputAdapter Exchange [cs_item_sk] #7 - WholeStageCodegen (10) + WholeStageCodegen (8) HashAggregate [cs_item_sk,cr_return_quantity,cs_quantity,cr_return_amount,cs_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] Project [cs_item_sk,cs_quantity,cs_net_paid,cr_return_quantity,cr_return_amount] BroadcastHashJoin [cs_sold_date_sk,d_date_sk] - Project [cs_item_sk,cs_quantity,cs_net_paid,cs_sold_date_sk,cr_return_quantity,cr_return_amount] - BroadcastHashJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] - InputAdapter - BroadcastExchange #8 - WholeStageCodegen (8) - Project [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_sold_date_sk] - Filter [cs_net_profit,cs_net_paid,cs_quantity,cs_order_number,cs_item_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_net_profit,cs_sold_date_sk] - ReusedSubquery [d_date_sk] #1 - Project [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] - Filter [cr_return_amount,cr_order_number,cr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cs_item_sk,cs_quantity,cs_net_paid,cs_sold_date_sk,cr_return_quantity,cr_return_amount] + CometBroadcastHashJoin [cs_order_number,cs_item_sk,cr_order_number,cr_item_sk] + CometBroadcastExchange #8 + CometProject [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_sold_date_sk] + CometFilter [cs_net_profit,cs_net_paid,cs_quantity,cs_order_number,cs_item_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_net_paid,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + CometFilter [cr_return_amount,cr_order_number,cr_item_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #5 - WholeStageCodegen (21) + WholeStageCodegen (18) Project [item,return_ratio,return_rank,currency_rank] Filter [return_rank,currency_rank] InputAdapter Window [currency_ratio] - WholeStageCodegen (20) + WholeStageCodegen (17) Sort [currency_ratio] InputAdapter Window [return_ratio] - WholeStageCodegen (19) + WholeStageCodegen (16) Sort [return_ratio] InputAdapter Exchange #9 - WholeStageCodegen (18) + WholeStageCodegen (15) HashAggregate [ss_item_sk,sum,sum,sum,isEmpty,sum,isEmpty] [sum(coalesce(sr_return_quantity, 0)),sum(coalesce(ss_quantity, 0)),sum(coalesce(cast(sr_return_amt as decimal(12,2)), 0.00)),sum(coalesce(cast(ss_net_paid as decimal(12,2)), 0.00)),item,return_ratio,currency_ratio,sum,sum,sum,isEmpty,sum,isEmpty] InputAdapter Exchange [ss_item_sk] #10 - WholeStageCodegen (17) + WholeStageCodegen (14) HashAggregate [ss_item_sk,sr_return_quantity,ss_quantity,sr_return_amt,ss_net_paid] [sum,sum,sum,isEmpty,sum,isEmpty,sum,sum,sum,isEmpty,sum,isEmpty] Project [ss_item_sk,ss_quantity,ss_net_paid,sr_return_quantity,sr_return_amt] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Project [ss_item_sk,ss_quantity,ss_net_paid,ss_sold_date_sk,sr_return_quantity,sr_return_amt] - BroadcastHashJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] - InputAdapter - BroadcastExchange #11 - WholeStageCodegen (15) - Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_sold_date_sk] - Filter [ss_net_profit,ss_net_paid,ss_quantity,ss_ticket_number,ss_item_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_net_profit,ss_sold_date_sk] - ReusedSubquery [d_date_sk] #1 - Project [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] - Filter [sr_return_amt,sr_ticket_number,sr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_quantity,ss_net_paid,ss_sold_date_sk,sr_return_quantity,sr_return_amt] + CometBroadcastHashJoin [ss_ticket_number,ss_item_sk,sr_ticket_number,sr_item_sk] + CometBroadcastExchange #11 + CometProject [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_sold_date_sk] + CometFilter [ss_net_profit,ss_net_paid,ss_quantity,ss_ticket_number,ss_item_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_net_paid,ss_net_profit,ss_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + CometFilter [sr_return_amt,sr_ticket_number,sr_item_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/explain.txt index cb9e772c9..3892f250a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/explain.txt @@ -27,8 +27,8 @@ TakeOrderedAndProject (67) : : : +- * HashAggregate (7) : : : +- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.web_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (18) @@ -52,8 +52,8 @@ TakeOrderedAndProject (67) : : +- * HashAggregate (32) : : +- * Project (31) : : +- * BroadcastHashJoin Inner BuildRight (30) - : : :- * Filter (28) - : : : +- * ColumnarToRow (27) + : : :- * ColumnarToRow (28) + : : : +- CometFilter (27) : : : +- CometScan parquet spark_catalog.default.store_sales (26) : : +- ReusedExchange (29) : +- BroadcastExchange (43) @@ -76,12 +76,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 2] +(2) CometFilter Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) -(3) Filter [codegen id : 2] +(3) ColumnarToRow [codegen id : 2] Input [3]: [ws_item_sk#1, ws_sales_price#2, ws_sold_date_sk#3] -Condition : isnotnull(ws_item_sk#1) (4) ReusedExchange [Reuses operator id: 72] Output [2]: [d_date_sk#5, d_date#6] @@ -193,12 +193,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(27) ColumnarToRow [codegen id : 14] +(27) CometFilter Input [3]: [ss_item_sk#24, ss_sales_price#25, ss_sold_date_sk#26] +Condition : isnotnull(ss_item_sk#24) -(28) Filter [codegen id : 14] +(28) ColumnarToRow [codegen id : 14] Input [3]: [ss_item_sk#24, ss_sales_price#25, ss_sold_date_sk#26] -Condition : isnotnull(ss_item_sk#24) (29) ReusedExchange [Reuses operator id: 72] Output [2]: [d_date_sk#28, d_date#29] @@ -383,9 +383,9 @@ Arguments: 100, [item_sk#47 ASC NULLS FIRST, d_date#48 ASC NULLS FIRST], [item_s Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (72) -+- * Project (71) - +- * Filter (70) - +- * ColumnarToRow (69) ++- * ColumnarToRow (71) + +- CometProject (70) + +- CometFilter (69) +- CometScan parquet spark_catalog.default.date_dim (68) @@ -396,16 +396,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] ReadSchema: struct -(69) ColumnarToRow [codegen id : 1] -Input [3]: [d_date_sk#5, d_date#6, d_month_seq#65] - -(70) Filter [codegen id : 1] +(69) CometFilter Input [3]: [d_date_sk#5, d_date#6, d_month_seq#65] Condition : (((isnotnull(d_month_seq#65) AND (d_month_seq#65 >= 1212)) AND (d_month_seq#65 <= 1223)) AND isnotnull(d_date_sk#5)) -(71) Project [codegen id : 1] -Output [2]: [d_date_sk#5, d_date#6] +(70) CometProject Input [3]: [d_date_sk#5, d_date#6, d_month_seq#65] +Arguments: [d_date_sk#5, d_date#6], [d_date_sk#5, d_date#6] + +(71) ColumnarToRow [codegen id : 1] +Input [2]: [d_date_sk#5, d_date#6] (72) BroadcastExchange Input [2]: [d_date_sk#5, d_date#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/simplified.txt index 252bc7f69..3109290dc 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q51a/simplified.txt @@ -43,17 +43,17 @@ TakeOrderedAndProject [item_sk,d_date,web_sales,store_sales,web_cumulative,store HashAggregate [ws_item_sk,d_date,ws_sales_price] [sum,sum] Project [ws_item_sk,ws_sales_price,d_date] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_sales_price,ws_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #6 WholeStageCodegen (1) - Project [d_date_sk,d_date] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_month_seq] InputAdapter ReusedExchange [d_date_sk,d_date] #6 @@ -95,9 +95,9 @@ TakeOrderedAndProject [item_sk,d_date,web_sales,store_sales,web_cumulative,store HashAggregate [ss_item_sk,d_date,ss_sales_price] [sum,sum] Project [ss_item_sk,ss_sales_price,d_date] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_sales_price,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/explain.txt index ef343f0e7..dd64cc7bc 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/explain.txt @@ -20,17 +20,17 @@ TakeOrderedAndProject (45) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.item (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (4) : : : +- ReusedExchange (10) : : +- BroadcastExchange (16) - : : +- * Filter (15) - : : +- * ColumnarToRow (14) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) : : +- CometScan parquet spark_catalog.default.call_center (13) : +- BroadcastExchange (35) : +- * Project (34) @@ -53,12 +53,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_category), IsNotNull(i_brand)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [3]: [i_item_sk#1, i_brand#2, i_category#3] +Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [3]: [i_item_sk#1, i_brand#2, i_category#3] -Condition : ((isnotnull(i_item_sk#1) AND isnotnull(i_category#3)) AND isnotnull(i_brand#2)) (4) Scan parquet spark_catalog.default.catalog_sales Output [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] @@ -68,12 +68,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#7), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_call_center_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] +Condition : (isnotnull(cs_item_sk#5) AND isnotnull(cs_call_center_sk#4)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] -Condition : (isnotnull(cs_item_sk#5) AND isnotnull(cs_call_center_sk#4)) (7) BroadcastExchange Input [4]: [cs_call_center_sk#4, cs_item_sk#5, cs_sales_price#6, cs_sold_date_sk#7] @@ -109,12 +109,12 @@ Location [not included in comparison]/{warehouse_dir}/call_center] PushedFilters: [IsNotNull(cc_call_center_sk), IsNotNull(cc_name)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [2]: [cc_call_center_sk#12, cc_name#13] +Condition : (isnotnull(cc_call_center_sk#12) AND isnotnull(cc_name#13)) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [2]: [cc_call_center_sk#12, cc_name#13] -Condition : (isnotnull(cc_call_center_sk#12) AND isnotnull(cc_name#13)) (16) BroadcastExchange Input [2]: [cc_call_center_sk#12, cc_name#13] @@ -253,8 +253,8 @@ Arguments: 100, [(sum_sales#17 - avg_monthly_sales#20) ASC NULLS FIRST, d_year#1 Subquery:1 Hosting operator id = 4 Hosting Expression = cs_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (49) -+- * Filter (48) - +- * ColumnarToRow (47) ++- * ColumnarToRow (48) + +- CometFilter (47) +- CometScan parquet spark_catalog.default.date_dim (46) @@ -265,12 +265,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [Or(Or(EqualTo(d_year,1999),And(EqualTo(d_year,1998),EqualTo(d_moy,12))),And(EqualTo(d_year,2000),EqualTo(d_moy,1))), IsNotNull(d_date_sk)] ReadSchema: struct -(47) ColumnarToRow [codegen id : 1] +(47) CometFilter Input [3]: [d_date_sk#9, d_year#10, d_moy#11] +Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) -(48) Filter [codegen id : 1] +(48) ColumnarToRow [codegen id : 1] Input [3]: [d_date_sk#9, d_year#10, d_moy#11] -Condition : ((((d_year#10 = 1999) OR ((d_year#10 = 1998) AND (d_moy#11 = 12))) OR ((d_year#10 = 2000) AND (d_moy#11 = 1))) AND isnotnull(d_date_sk#9)) (49) BroadcastExchange Input [3]: [d_date_sk#9, d_year#10, d_moy#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/simplified.txt index 8e259bf7f..56e33be9e 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q57/simplified.txt @@ -28,32 +28,32 @@ TakeOrderedAndProject [sum_sales,avg_monthly_sales,d_year,i_category,i_brand,d_m BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [i_brand,i_category,cs_call_center_sk,cs_sales_price,cs_sold_date_sk] BroadcastHashJoin [i_item_sk,cs_item_sk] - Filter [i_item_sk,i_category,i_brand] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk,i_category,i_brand] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_category] InputAdapter BroadcastExchange #3 WholeStageCodegen (1) - Filter [cs_item_sk,cs_call_center_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_call_center_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_call_center_sk,cs_item_sk,cs_sales_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Filter [d_year,d_moy,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_moy,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk,d_year,d_moy] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [cc_call_center_sk,cc_name] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cc_call_center_sk,cc_name] CometScan parquet spark_catalog.default.call_center [cc_call_center_sk,cc_name] InputAdapter BroadcastExchange #6 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/explain.txt index 8489cf66d..2769e772a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/explain.txt @@ -1,91 +1,87 @@ == Physical Plan == -TakeOrderedAndProject (87) -+- * HashAggregate (86) - +- Exchange (85) - +- * HashAggregate (84) - +- Union (83) - :- * HashAggregate (72) - : +- Exchange (71) - : +- * HashAggregate (70) - : +- Union (69) - : :- * HashAggregate (21) - : : +- Exchange (20) - : : +- * HashAggregate (19) - : : +- * Project (18) - : : +- * BroadcastHashJoin Inner BuildRight (17) - : : :- * Project (12) - : : : +- * BroadcastHashJoin Inner BuildRight (11) - : : : :- Union (9) - : : : : :- * Project (4) - : : : : : +- * Filter (3) - : : : : : +- * ColumnarToRow (2) - : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) - : : : : +- * Project (8) - : : : : +- * Filter (7) - : : : : +- * ColumnarToRow (6) - : : : : +- CometScan parquet spark_catalog.default.store_returns (5) - : : : +- ReusedExchange (10) - : : +- BroadcastExchange (16) - : : +- * Filter (15) - : : +- * ColumnarToRow (14) - : : +- CometScan parquet spark_catalog.default.store (13) - : :- * HashAggregate (42) - : : +- Exchange (41) - : : +- * HashAggregate (40) - : : +- * Project (39) - : : +- * BroadcastHashJoin Inner BuildRight (38) - : : :- * Project (33) - : : : +- * BroadcastHashJoin Inner BuildRight (32) - : : : :- Union (30) - : : : : :- * Project (25) - : : : : : +- * Filter (24) - : : : : : +- * ColumnarToRow (23) - : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (22) - : : : : +- * Project (29) - : : : : +- * Filter (28) - : : : : +- * ColumnarToRow (27) - : : : : +- CometScan parquet spark_catalog.default.catalog_returns (26) - : : : +- ReusedExchange (31) - : : +- BroadcastExchange (37) - : : +- * Filter (36) - : : +- * ColumnarToRow (35) - : : +- CometScan parquet spark_catalog.default.catalog_page (34) - : +- * HashAggregate (68) - : +- Exchange (67) - : +- * HashAggregate (66) - : +- * Project (65) - : +- * BroadcastHashJoin Inner BuildRight (64) - : :- * Project (59) - : : +- * BroadcastHashJoin Inner BuildRight (58) - : : :- Union (56) - : : : :- * Project (46) - : : : : +- * Filter (45) - : : : : +- * ColumnarToRow (44) - : : : : +- CometScan parquet spark_catalog.default.web_sales (43) - : : : +- * Project (55) - : : : +- * BroadcastHashJoin Inner BuildLeft (54) - : : : :- BroadcastExchange (49) - : : : : +- * ColumnarToRow (48) - : : : : +- CometScan parquet spark_catalog.default.web_returns (47) - : : : +- * Project (53) - : : : +- * Filter (52) - : : : +- * ColumnarToRow (51) - : : : +- CometScan parquet spark_catalog.default.web_sales (50) - : : +- ReusedExchange (57) - : +- BroadcastExchange (63) - : +- * Filter (62) - : +- * ColumnarToRow (61) - : +- CometScan parquet spark_catalog.default.web_site (60) - :- * HashAggregate (77) - : +- Exchange (76) - : +- * HashAggregate (75) - : +- * HashAggregate (74) - : +- ReusedExchange (73) - +- * HashAggregate (82) - +- Exchange (81) - +- * HashAggregate (80) - +- * HashAggregate (79) - +- ReusedExchange (78) +TakeOrderedAndProject (83) ++- * HashAggregate (82) + +- Exchange (81) + +- * HashAggregate (80) + +- Union (79) + :- * HashAggregate (68) + : +- Exchange (67) + : +- * HashAggregate (66) + : +- Union (65) + : :- * HashAggregate (20) + : : +- Exchange (19) + : : +- * HashAggregate (18) + : : +- * Project (17) + : : +- * BroadcastHashJoin Inner BuildRight (16) + : : :- * Project (11) + : : : +- * BroadcastHashJoin Inner BuildRight (10) + : : : :- * ColumnarToRow (8) + : : : : +- CometUnion (7) + : : : : :- CometProject (3) + : : : : : +- CometFilter (2) + : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : +- CometProject (6) + : : : : +- CometFilter (5) + : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : +- ReusedExchange (9) + : : +- BroadcastExchange (15) + : : +- * ColumnarToRow (14) + : : +- CometFilter (13) + : : +- CometScan parquet spark_catalog.default.store (12) + : :- * HashAggregate (40) + : : +- Exchange (39) + : : +- * HashAggregate (38) + : : +- * Project (37) + : : +- * BroadcastHashJoin Inner BuildRight (36) + : : :- * Project (31) + : : : +- * BroadcastHashJoin Inner BuildRight (30) + : : : :- * ColumnarToRow (28) + : : : : +- CometUnion (27) + : : : : :- CometProject (23) + : : : : : +- CometFilter (22) + : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (21) + : : : : +- CometProject (26) + : : : : +- CometFilter (25) + : : : : +- CometScan parquet spark_catalog.default.catalog_returns (24) + : : : +- ReusedExchange (29) + : : +- BroadcastExchange (35) + : : +- * ColumnarToRow (34) + : : +- CometFilter (33) + : : +- CometScan parquet spark_catalog.default.catalog_page (32) + : +- * HashAggregate (64) + : +- Exchange (63) + : +- * HashAggregate (62) + : +- * Project (61) + : +- * BroadcastHashJoin Inner BuildRight (60) + : :- * Project (55) + : : +- * BroadcastHashJoin Inner BuildRight (54) + : : :- * ColumnarToRow (52) + : : : +- CometUnion (51) + : : : :- CometProject (43) + : : : : +- CometFilter (42) + : : : : +- CometScan parquet spark_catalog.default.web_sales (41) + : : : +- CometProject (50) + : : : +- CometBroadcastHashJoin (49) + : : : :- CometBroadcastExchange (45) + : : : : +- CometScan parquet spark_catalog.default.web_returns (44) + : : : +- CometProject (48) + : : : +- CometFilter (47) + : : : +- CometScan parquet spark_catalog.default.web_sales (46) + : : +- ReusedExchange (53) + : +- BroadcastExchange (59) + : +- * ColumnarToRow (58) + : +- CometFilter (57) + : +- CometScan parquet spark_catalog.default.web_site (56) + :- * HashAggregate (73) + : +- Exchange (72) + : +- * HashAggregate (71) + : +- * HashAggregate (70) + : +- ReusedExchange (69) + +- * HashAggregate (78) + +- Exchange (77) + +- * HashAggregate (76) + +- * HashAggregate (75) + +- ReusedExchange (74) (1) Scan parquet spark_catalog.default.store_sales @@ -96,18 +92,15 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] Condition : isnotnull(ss_store_sk#1) -(4) Project [codegen id : 1] -Output [6]: [ss_store_sk#1 AS store_sk#6, ss_sold_date_sk#4 AS date_sk#7, ss_ext_sales_price#2 AS sales_price#8, ss_net_profit#3 AS profit#9, 0.00 AS return_amt#10, 0.00 AS net_loss#11] +(3) CometProject Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Arguments: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11], [ss_store_sk#1 AS store_sk#6, ss_sold_date_sk#4 AS date_sk#7, ss_ext_sales_price#2 AS sales_price#8, ss_net_profit#3 AS profit#9, 0.00 AS return_amt#10, 0.00 AS net_loss#11] -(5) Scan parquet spark_catalog.default.store_returns +(4) Scan parquet spark_catalog.default.store_returns Output [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] Batched: true Location: InMemoryFileIndex [] @@ -115,79 +108,81 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#15), dynamicpruningexpression(s PushedFilters: [IsNotNull(sr_store_sk)] ReadSchema: struct -(6) ColumnarToRow [codegen id : 2] -Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] - -(7) Filter [codegen id : 2] +(5) CometFilter Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] Condition : isnotnull(sr_store_sk#12) -(8) Project [codegen id : 2] -Output [6]: [sr_store_sk#12 AS store_sk#16, sr_returned_date_sk#15 AS date_sk#17, 0.00 AS sales_price#18, 0.00 AS profit#19, sr_return_amt#13 AS return_amt#20, sr_net_loss#14 AS net_loss#21] +(6) CometProject Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15] +Arguments: [store_sk#16, date_sk#17, sales_price#18, profit#19, return_amt#20, net_loss#21], [sr_store_sk#12 AS store_sk#16, sr_returned_date_sk#15 AS date_sk#17, 0.00 AS sales_price#18, 0.00 AS profit#19, sr_return_amt#13 AS return_amt#20, sr_net_loss#14 AS net_loss#21] + +(7) CometUnion +Child 0 Input [6]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11] +Child 1 Input [6]: [store_sk#16, date_sk#17, sales_price#18, profit#19, return_amt#20, net_loss#21] -(9) Union +(8) ColumnarToRow [codegen id : 3] +Input [6]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11] -(10) ReusedExchange [Reuses operator id: 92] +(9) ReusedExchange [Reuses operator id: 88] Output [1]: [d_date_sk#22] -(11) BroadcastHashJoin [codegen id : 5] +(10) BroadcastHashJoin [codegen id : 3] Left keys [1]: [date_sk#7] Right keys [1]: [d_date_sk#22] Join type: Inner Join condition: None -(12) Project [codegen id : 5] +(11) Project [codegen id : 3] Output [5]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11] Input [7]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11, d_date_sk#22] -(13) Scan parquet spark_catalog.default.store +(12) Scan parquet spark_catalog.default.store Output [2]: [s_store_sk#23, s_store_id#24] Batched: true Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 4] +(13) CometFilter Input [2]: [s_store_sk#23, s_store_id#24] +Condition : isnotnull(s_store_sk#23) -(15) Filter [codegen id : 4] +(14) ColumnarToRow [codegen id : 2] Input [2]: [s_store_sk#23, s_store_id#24] -Condition : isnotnull(s_store_sk#23) -(16) BroadcastExchange +(15) BroadcastExchange Input [2]: [s_store_sk#23, s_store_id#24] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1] -(17) BroadcastHashJoin [codegen id : 5] +(16) BroadcastHashJoin [codegen id : 3] Left keys [1]: [store_sk#6] Right keys [1]: [s_store_sk#23] Join type: Inner Join condition: None -(18) Project [codegen id : 5] +(17) Project [codegen id : 3] Output [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] Input [7]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_sk#23, s_store_id#24] -(19) HashAggregate [codegen id : 5] +(18) HashAggregate [codegen id : 3] Input [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#24] Keys [1]: [s_store_id#24] Functions [4]: [partial_sum(UnscaledValue(sales_price#8)), partial_sum(UnscaledValue(return_amt#10)), partial_sum(UnscaledValue(profit#9)), partial_sum(UnscaledValue(net_loss#11))] Aggregate Attributes [4]: [sum#25, sum#26, sum#27, sum#28] Results [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] -(20) Exchange +(19) Exchange Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] Arguments: hashpartitioning(s_store_id#24, 5), ENSURE_REQUIREMENTS, [plan_id=2] -(21) HashAggregate [codegen id : 6] +(20) HashAggregate [codegen id : 4] Input [5]: [s_store_id#24, sum#29, sum#30, sum#31, sum#32] Keys [1]: [s_store_id#24] Functions [4]: [sum(UnscaledValue(sales_price#8)), sum(UnscaledValue(return_amt#10)), sum(UnscaledValue(profit#9)), sum(UnscaledValue(net_loss#11))] Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#8))#33, sum(UnscaledValue(return_amt#10))#34, sum(UnscaledValue(profit#9))#35, sum(UnscaledValue(net_loss#11))#36] Results [5]: [store channel AS channel#37, concat(store, s_store_id#24) AS id#38, MakeDecimal(sum(UnscaledValue(sales_price#8))#33,17,2) AS sales#39, MakeDecimal(sum(UnscaledValue(return_amt#10))#34,17,2) AS returns#40, (MakeDecimal(sum(UnscaledValue(profit#9))#35,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#11))#36,17,2)) AS profit#41] -(22) Scan parquet spark_catalog.default.catalog_sales +(21) Scan parquet spark_catalog.default.catalog_sales Output [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] Batched: true Location: InMemoryFileIndex [] @@ -195,18 +190,15 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_catalog_page_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 7] -Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] - -(24) Filter [codegen id : 7] +(22) CometFilter Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] Condition : isnotnull(cs_catalog_page_sk#42) -(25) Project [codegen id : 7] -Output [6]: [cs_catalog_page_sk#42 AS page_sk#47, cs_sold_date_sk#45 AS date_sk#48, cs_ext_sales_price#43 AS sales_price#49, cs_net_profit#44 AS profit#50, 0.00 AS return_amt#51, 0.00 AS net_loss#52] +(23) CometProject Input [4]: [cs_catalog_page_sk#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Arguments: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52], [cs_catalog_page_sk#42 AS page_sk#47, cs_sold_date_sk#45 AS date_sk#48, cs_ext_sales_price#43 AS sales_price#49, cs_net_profit#44 AS profit#50, 0.00 AS return_amt#51, 0.00 AS net_loss#52] -(26) Scan parquet spark_catalog.default.catalog_returns +(24) Scan parquet spark_catalog.default.catalog_returns Output [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] Batched: true Location: InMemoryFileIndex [] @@ -214,79 +206,81 @@ PartitionFilters: [isnotnull(cr_returned_date_sk#56), dynamicpruningexpression(c PushedFilters: [IsNotNull(cr_catalog_page_sk)] ReadSchema: struct -(27) ColumnarToRow [codegen id : 8] -Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] - -(28) Filter [codegen id : 8] +(25) CometFilter Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] Condition : isnotnull(cr_catalog_page_sk#53) -(29) Project [codegen id : 8] -Output [6]: [cr_catalog_page_sk#53 AS page_sk#57, cr_returned_date_sk#56 AS date_sk#58, 0.00 AS sales_price#59, 0.00 AS profit#60, cr_return_amount#54 AS return_amt#61, cr_net_loss#55 AS net_loss#62] +(26) CometProject Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56] +Arguments: [page_sk#57, date_sk#58, sales_price#59, profit#60, return_amt#61, net_loss#62], [cr_catalog_page_sk#53 AS page_sk#57, cr_returned_date_sk#56 AS date_sk#58, 0.00 AS sales_price#59, 0.00 AS profit#60, cr_return_amount#54 AS return_amt#61, cr_net_loss#55 AS net_loss#62] -(30) Union +(27) CometUnion +Child 0 Input [6]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52] +Child 1 Input [6]: [page_sk#57, date_sk#58, sales_price#59, profit#60, return_amt#61, net_loss#62] -(31) ReusedExchange [Reuses operator id: 92] +(28) ColumnarToRow [codegen id : 7] +Input [6]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52] + +(29) ReusedExchange [Reuses operator id: 88] Output [1]: [d_date_sk#63] -(32) BroadcastHashJoin [codegen id : 11] +(30) BroadcastHashJoin [codegen id : 7] Left keys [1]: [date_sk#48] Right keys [1]: [d_date_sk#63] Join type: Inner Join condition: None -(33) Project [codegen id : 11] +(31) Project [codegen id : 7] Output [5]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52] Input [7]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52, d_date_sk#63] -(34) Scan parquet spark_catalog.default.catalog_page +(32) Scan parquet spark_catalog.default.catalog_page Output [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] Batched: true Location [not included in comparison]/{warehouse_dir}/catalog_page] PushedFilters: [IsNotNull(cp_catalog_page_sk)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 10] +(33) CometFilter Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] +Condition : isnotnull(cp_catalog_page_sk#64) -(36) Filter [codegen id : 10] +(34) ColumnarToRow [codegen id : 6] Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] -Condition : isnotnull(cp_catalog_page_sk#64) -(37) BroadcastExchange +(35) BroadcastExchange Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3] -(38) BroadcastHashJoin [codegen id : 11] +(36) BroadcastHashJoin [codegen id : 7] Left keys [1]: [page_sk#47] Right keys [1]: [cp_catalog_page_sk#64] Join type: Inner Join condition: None -(39) Project [codegen id : 11] +(37) Project [codegen id : 7] Output [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] Input [7]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_sk#64, cp_catalog_page_id#65] -(40) HashAggregate [codegen id : 11] +(38) HashAggregate [codegen id : 7] Input [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#65] Keys [1]: [cp_catalog_page_id#65] Functions [4]: [partial_sum(UnscaledValue(sales_price#49)), partial_sum(UnscaledValue(return_amt#51)), partial_sum(UnscaledValue(profit#50)), partial_sum(UnscaledValue(net_loss#52))] Aggregate Attributes [4]: [sum#66, sum#67, sum#68, sum#69] Results [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] -(41) Exchange +(39) Exchange Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] Arguments: hashpartitioning(cp_catalog_page_id#65, 5), ENSURE_REQUIREMENTS, [plan_id=4] -(42) HashAggregate [codegen id : 12] +(40) HashAggregate [codegen id : 8] Input [5]: [cp_catalog_page_id#65, sum#70, sum#71, sum#72, sum#73] Keys [1]: [cp_catalog_page_id#65] Functions [4]: [sum(UnscaledValue(sales_price#49)), sum(UnscaledValue(return_amt#51)), sum(UnscaledValue(profit#50)), sum(UnscaledValue(net_loss#52))] Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#49))#74, sum(UnscaledValue(return_amt#51))#75, sum(UnscaledValue(profit#50))#76, sum(UnscaledValue(net_loss#52))#77] Results [5]: [catalog channel AS channel#78, concat(catalog_page, cp_catalog_page_id#65) AS id#79, MakeDecimal(sum(UnscaledValue(sales_price#49))#74,17,2) AS sales#80, MakeDecimal(sum(UnscaledValue(return_amt#51))#75,17,2) AS returns#81, (MakeDecimal(sum(UnscaledValue(profit#50))#76,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#52))#77,17,2)) AS profit#82] -(43) Scan parquet spark_catalog.default.web_sales +(41) Scan parquet spark_catalog.default.web_sales Output [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] Batched: true Location: InMemoryFileIndex [] @@ -294,260 +288,255 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#86), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_web_site_sk)] ReadSchema: struct -(44) ColumnarToRow [codegen id : 13] -Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] - -(45) Filter [codegen id : 13] +(42) CometFilter Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] Condition : isnotnull(ws_web_site_sk#83) -(46) Project [codegen id : 13] -Output [6]: [ws_web_site_sk#83 AS wsr_web_site_sk#88, ws_sold_date_sk#86 AS date_sk#89, ws_ext_sales_price#84 AS sales_price#90, ws_net_profit#85 AS profit#91, 0.00 AS return_amt#92, 0.00 AS net_loss#93] +(43) CometProject Input [4]: [ws_web_site_sk#83, ws_ext_sales_price#84, ws_net_profit#85, ws_sold_date_sk#86] +Arguments: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93], [ws_web_site_sk#83 AS wsr_web_site_sk#88, ws_sold_date_sk#86 AS date_sk#89, ws_ext_sales_price#84 AS sales_price#90, ws_net_profit#85 AS profit#91, 0.00 AS return_amt#92, 0.00 AS net_loss#93] -(47) Scan parquet spark_catalog.default.web_returns +(44) Scan parquet spark_catalog.default.web_returns Output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] Batched: true Location: InMemoryFileIndex [] PartitionFilters: [isnotnull(wr_returned_date_sk#98), dynamicpruningexpression(wr_returned_date_sk#98 IN dynamicpruning#87)] ReadSchema: struct -(48) ColumnarToRow [codegen id : 14] -Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] - -(49) BroadcastExchange +(45) CometBroadcastExchange Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, true] as bigint), 32) | (cast(input[1, int, true] as bigint) & 4294967295))),false), [plan_id=5] +Arguments: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] -(50) Scan parquet spark_catalog.default.web_sales +(46) Scan parquet spark_catalog.default.web_sales Output [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] Batched: true Location [not included in comparison]/{warehouse_dir}/web_sales] PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_site_sk)] ReadSchema: struct -(51) ColumnarToRow -Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] - -(52) Filter +(47) CometFilter Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] Condition : ((isnotnull(ws_item_sk#99) AND isnotnull(ws_order_number#101)) AND isnotnull(ws_web_site_sk#100)) -(53) Project -Output [3]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +(48) CometProject Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102] +Arguments: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101], [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] -(54) BroadcastHashJoin [codegen id : 15] -Left keys [2]: [wr_item_sk#94, wr_order_number#95] -Right keys [2]: [ws_item_sk#99, ws_order_number#101] -Join type: Inner -Join condition: None +(49) CometBroadcastHashJoin +Left output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98] +Right output [3]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +Arguments: [wr_item_sk#94, wr_order_number#95], [ws_item_sk#99, ws_order_number#101], Inner -(55) Project [codegen id : 15] -Output [6]: [ws_web_site_sk#100 AS wsr_web_site_sk#103, wr_returned_date_sk#98 AS date_sk#104, 0.00 AS sales_price#105, 0.00 AS profit#106, wr_return_amt#96 AS return_amt#107, wr_net_loss#97 AS net_loss#108] +(50) CometProject Input [8]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98, ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101] +Arguments: [wsr_web_site_sk#103, date_sk#104, sales_price#105, profit#106, return_amt#107, net_loss#108], [ws_web_site_sk#100 AS wsr_web_site_sk#103, wr_returned_date_sk#98 AS date_sk#104, 0.00 AS sales_price#105, 0.00 AS profit#106, wr_return_amt#96 AS return_amt#107, wr_net_loss#97 AS net_loss#108] -(56) Union +(51) CometUnion +Child 0 Input [6]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93] +Child 1 Input [6]: [wsr_web_site_sk#103, date_sk#104, sales_price#105, profit#106, return_amt#107, net_loss#108] -(57) ReusedExchange [Reuses operator id: 92] +(52) ColumnarToRow [codegen id : 11] +Input [6]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93] + +(53) ReusedExchange [Reuses operator id: 88] Output [1]: [d_date_sk#109] -(58) BroadcastHashJoin [codegen id : 18] +(54) BroadcastHashJoin [codegen id : 11] Left keys [1]: [date_sk#89] Right keys [1]: [d_date_sk#109] Join type: Inner Join condition: None -(59) Project [codegen id : 18] +(55) Project [codegen id : 11] Output [5]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93] Input [7]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93, d_date_sk#109] -(60) Scan parquet spark_catalog.default.web_site +(56) Scan parquet spark_catalog.default.web_site Output [2]: [web_site_sk#110, web_site_id#111] Batched: true Location [not included in comparison]/{warehouse_dir}/web_site] PushedFilters: [IsNotNull(web_site_sk)] ReadSchema: struct -(61) ColumnarToRow [codegen id : 17] +(57) CometFilter Input [2]: [web_site_sk#110, web_site_id#111] +Condition : isnotnull(web_site_sk#110) -(62) Filter [codegen id : 17] +(58) ColumnarToRow [codegen id : 10] Input [2]: [web_site_sk#110, web_site_id#111] -Condition : isnotnull(web_site_sk#110) -(63) BroadcastExchange +(59) BroadcastExchange Input [2]: [web_site_sk#110, web_site_id#111] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] -(64) BroadcastHashJoin [codegen id : 18] +(60) BroadcastHashJoin [codegen id : 11] Left keys [1]: [wsr_web_site_sk#88] Right keys [1]: [web_site_sk#110] Join type: Inner Join condition: None -(65) Project [codegen id : 18] +(61) Project [codegen id : 11] Output [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] Input [7]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_sk#110, web_site_id#111] -(66) HashAggregate [codegen id : 18] +(62) HashAggregate [codegen id : 11] Input [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#111] Keys [1]: [web_site_id#111] Functions [4]: [partial_sum(UnscaledValue(sales_price#90)), partial_sum(UnscaledValue(return_amt#92)), partial_sum(UnscaledValue(profit#91)), partial_sum(UnscaledValue(net_loss#93))] Aggregate Attributes [4]: [sum#112, sum#113, sum#114, sum#115] Results [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] -(67) Exchange +(63) Exchange Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] -Arguments: hashpartitioning(web_site_id#111, 5), ENSURE_REQUIREMENTS, [plan_id=7] +Arguments: hashpartitioning(web_site_id#111, 5), ENSURE_REQUIREMENTS, [plan_id=6] -(68) HashAggregate [codegen id : 19] +(64) HashAggregate [codegen id : 12] Input [5]: [web_site_id#111, sum#116, sum#117, sum#118, sum#119] Keys [1]: [web_site_id#111] Functions [4]: [sum(UnscaledValue(sales_price#90)), sum(UnscaledValue(return_amt#92)), sum(UnscaledValue(profit#91)), sum(UnscaledValue(net_loss#93))] Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#90))#120, sum(UnscaledValue(return_amt#92))#121, sum(UnscaledValue(profit#91))#122, sum(UnscaledValue(net_loss#93))#123] Results [5]: [web channel AS channel#124, concat(web_site, web_site_id#111) AS id#125, MakeDecimal(sum(UnscaledValue(sales_price#90))#120,17,2) AS sales#126, MakeDecimal(sum(UnscaledValue(return_amt#92))#121,17,2) AS returns#127, (MakeDecimal(sum(UnscaledValue(profit#91))#122,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#93))#123,17,2)) AS profit#128] -(69) Union +(65) Union -(70) HashAggregate [codegen id : 20] +(66) HashAggregate [codegen id : 13] Input [5]: [channel#37, id#38, sales#39, returns#40, profit#41] Keys [2]: [channel#37, id#38] Functions [3]: [partial_sum(sales#39), partial_sum(returns#40), partial_sum(profit#41)] Aggregate Attributes [6]: [sum#129, isEmpty#130, sum#131, isEmpty#132, sum#133, isEmpty#134] Results [8]: [channel#37, id#38, sum#135, isEmpty#136, sum#137, isEmpty#138, sum#139, isEmpty#140] -(71) Exchange +(67) Exchange Input [8]: [channel#37, id#38, sum#135, isEmpty#136, sum#137, isEmpty#138, sum#139, isEmpty#140] -Arguments: hashpartitioning(channel#37, id#38, 5), ENSURE_REQUIREMENTS, [plan_id=8] +Arguments: hashpartitioning(channel#37, id#38, 5), ENSURE_REQUIREMENTS, [plan_id=7] -(72) HashAggregate [codegen id : 21] +(68) HashAggregate [codegen id : 14] Input [8]: [channel#37, id#38, sum#135, isEmpty#136, sum#137, isEmpty#138, sum#139, isEmpty#140] Keys [2]: [channel#37, id#38] Functions [3]: [sum(sales#39), sum(returns#40), sum(profit#41)] Aggregate Attributes [3]: [sum(sales#39)#141, sum(returns#40)#142, sum(profit#41)#143] Results [5]: [channel#37, id#38, cast(sum(sales#39)#141 as decimal(37,2)) AS sales#144, cast(sum(returns#40)#142 as decimal(37,2)) AS returns#145, cast(sum(profit#41)#143 as decimal(38,2)) AS profit#146] -(73) ReusedExchange [Reuses operator id: 71] +(69) ReusedExchange [Reuses operator id: 67] Output [8]: [channel#147, id#148, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] -(74) HashAggregate [codegen id : 42] +(70) HashAggregate [codegen id : 28] Input [8]: [channel#147, id#148, sum#149, isEmpty#150, sum#151, isEmpty#152, sum#153, isEmpty#154] Keys [2]: [channel#147, id#148] Functions [3]: [sum(sales#155), sum(returns#156), sum(profit#157)] Aggregate Attributes [3]: [sum(sales#155)#141, sum(returns#156)#142, sum(profit#157)#143] Results [4]: [channel#147, sum(sales#155)#141 AS sales#158, sum(returns#156)#142 AS returns#159, sum(profit#157)#143 AS profit#160] -(75) HashAggregate [codegen id : 42] +(71) HashAggregate [codegen id : 28] Input [4]: [channel#147, sales#158, returns#159, profit#160] Keys [1]: [channel#147] Functions [3]: [partial_sum(sales#158), partial_sum(returns#159), partial_sum(profit#160)] Aggregate Attributes [6]: [sum#161, isEmpty#162, sum#163, isEmpty#164, sum#165, isEmpty#166] Results [7]: [channel#147, sum#167, isEmpty#168, sum#169, isEmpty#170, sum#171, isEmpty#172] -(76) Exchange +(72) Exchange Input [7]: [channel#147, sum#167, isEmpty#168, sum#169, isEmpty#170, sum#171, isEmpty#172] -Arguments: hashpartitioning(channel#147, 5), ENSURE_REQUIREMENTS, [plan_id=9] +Arguments: hashpartitioning(channel#147, 5), ENSURE_REQUIREMENTS, [plan_id=8] -(77) HashAggregate [codegen id : 43] +(73) HashAggregate [codegen id : 29] Input [7]: [channel#147, sum#167, isEmpty#168, sum#169, isEmpty#170, sum#171, isEmpty#172] Keys [1]: [channel#147] Functions [3]: [sum(sales#158), sum(returns#159), sum(profit#160)] Aggregate Attributes [3]: [sum(sales#158)#173, sum(returns#159)#174, sum(profit#160)#175] Results [5]: [channel#147, null AS id#176, sum(sales#158)#173 AS sum(sales)#177, sum(returns#159)#174 AS sum(returns)#178, sum(profit#160)#175 AS sum(profit)#179] -(78) ReusedExchange [Reuses operator id: 71] +(74) ReusedExchange [Reuses operator id: 67] Output [8]: [channel#180, id#181, sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] -(79) HashAggregate [codegen id : 64] +(75) HashAggregate [codegen id : 43] Input [8]: [channel#180, id#181, sum#182, isEmpty#183, sum#184, isEmpty#185, sum#186, isEmpty#187] Keys [2]: [channel#180, id#181] Functions [3]: [sum(sales#188), sum(returns#189), sum(profit#190)] Aggregate Attributes [3]: [sum(sales#188)#141, sum(returns#189)#142, sum(profit#190)#143] Results [3]: [sum(sales#188)#141 AS sales#191, sum(returns#189)#142 AS returns#192, sum(profit#190)#143 AS profit#193] -(80) HashAggregate [codegen id : 64] +(76) HashAggregate [codegen id : 43] Input [3]: [sales#191, returns#192, profit#193] Keys: [] Functions [3]: [partial_sum(sales#191), partial_sum(returns#192), partial_sum(profit#193)] Aggregate Attributes [6]: [sum#194, isEmpty#195, sum#196, isEmpty#197, sum#198, isEmpty#199] Results [6]: [sum#200, isEmpty#201, sum#202, isEmpty#203, sum#204, isEmpty#205] -(81) Exchange +(77) Exchange Input [6]: [sum#200, isEmpty#201, sum#202, isEmpty#203, sum#204, isEmpty#205] -Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=10] +Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=9] -(82) HashAggregate [codegen id : 65] +(78) HashAggregate [codegen id : 44] Input [6]: [sum#200, isEmpty#201, sum#202, isEmpty#203, sum#204, isEmpty#205] Keys: [] Functions [3]: [sum(sales#191), sum(returns#192), sum(profit#193)] Aggregate Attributes [3]: [sum(sales#191)#206, sum(returns#192)#207, sum(profit#193)#208] Results [5]: [null AS channel#209, null AS id#210, sum(sales#191)#206 AS sum(sales)#211, sum(returns#192)#207 AS sum(returns)#212, sum(profit#193)#208 AS sum(profit)#213] -(83) Union +(79) Union -(84) HashAggregate [codegen id : 66] +(80) HashAggregate [codegen id : 45] Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] Keys [5]: [channel#37, id#38, sales#144, returns#145, profit#146] Functions: [] Aggregate Attributes: [] Results [5]: [channel#37, id#38, sales#144, returns#145, profit#146] -(85) Exchange +(81) Exchange Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] -Arguments: hashpartitioning(channel#37, id#38, sales#144, returns#145, profit#146, 5), ENSURE_REQUIREMENTS, [plan_id=11] +Arguments: hashpartitioning(channel#37, id#38, sales#144, returns#145, profit#146, 5), ENSURE_REQUIREMENTS, [plan_id=10] -(86) HashAggregate [codegen id : 67] +(82) HashAggregate [codegen id : 46] Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] Keys [5]: [channel#37, id#38, sales#144, returns#145, profit#146] Functions: [] Aggregate Attributes: [] Results [5]: [channel#37, id#38, sales#144, returns#145, profit#146] -(87) TakeOrderedAndProject +(83) TakeOrderedAndProject Input [5]: [channel#37, id#38, sales#144, returns#145, profit#146] Arguments: 100, [channel#37 ASC NULLS FIRST, id#38 ASC NULLS FIRST], [channel#37, id#38, sales#144, returns#145, profit#146] ===== Subqueries ===== Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 -BroadcastExchange (92) -+- * Project (91) - +- * Filter (90) - +- * ColumnarToRow (89) - +- CometScan parquet spark_catalog.default.date_dim (88) +BroadcastExchange (88) ++- * ColumnarToRow (87) + +- CometProject (86) + +- CometFilter (85) + +- CometScan parquet spark_catalog.default.date_dim (84) -(88) Scan parquet spark_catalog.default.date_dim +(84) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date_sk#22, d_date#214] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1998-08-04), LessThanOrEqual(d_date,1998-08-18), IsNotNull(d_date_sk)] ReadSchema: struct -(89) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#22, d_date#214] - -(90) Filter [codegen id : 1] +(85) CometFilter Input [2]: [d_date_sk#22, d_date#214] Condition : (((isnotnull(d_date#214) AND (d_date#214 >= 1998-08-04)) AND (d_date#214 <= 1998-08-18)) AND isnotnull(d_date_sk#22)) -(91) Project [codegen id : 1] -Output [1]: [d_date_sk#22] +(86) CometProject Input [2]: [d_date_sk#22, d_date#214] +Arguments: [d_date_sk#22], [d_date_sk#22] + +(87) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#22] -(92) BroadcastExchange +(88) BroadcastExchange Input [1]: [d_date_sk#22] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=11] -Subquery:2 Hosting operator id = 5 Hosting Expression = sr_returned_date_sk#15 IN dynamicpruning#5 +Subquery:2 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#15 IN dynamicpruning#5 -Subquery:3 Hosting operator id = 22 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#5 +Subquery:3 Hosting operator id = 21 Hosting Expression = cs_sold_date_sk#45 IN dynamicpruning#5 -Subquery:4 Hosting operator id = 26 Hosting Expression = cr_returned_date_sk#56 IN dynamicpruning#5 +Subquery:4 Hosting operator id = 24 Hosting Expression = cr_returned_date_sk#56 IN dynamicpruning#5 -Subquery:5 Hosting operator id = 43 Hosting Expression = ws_sold_date_sk#86 IN dynamicpruning#5 +Subquery:5 Hosting operator id = 41 Hosting Expression = ws_sold_date_sk#86 IN dynamicpruning#5 -Subquery:6 Hosting operator id = 47 Hosting Expression = wr_returned_date_sk#98 IN dynamicpruning#5 +Subquery:6 Hosting operator id = 44 Hosting Expression = wr_returned_date_sk#98 IN dynamicpruning#5 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/simplified.txt index f132fec3b..aaec304fd 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q5a/simplified.txt @@ -1,154 +1,135 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] - WholeStageCodegen (67) + WholeStageCodegen (46) HashAggregate [channel,id,sales,returns,profit] InputAdapter Exchange [channel,id,sales,returns,profit] #1 - WholeStageCodegen (66) + WholeStageCodegen (45) HashAggregate [channel,id,sales,returns,profit] InputAdapter Union - WholeStageCodegen (21) + WholeStageCodegen (14) HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] InputAdapter Exchange [channel,id] #2 - WholeStageCodegen (20) + WholeStageCodegen (13) HashAggregate [channel,id,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] InputAdapter Union - WholeStageCodegen (6) + WholeStageCodegen (4) HashAggregate [s_store_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),channel,id,sales,returns,profit,sum,sum,sum,sum] InputAdapter Exchange [s_store_id] #3 - WholeStageCodegen (5) + WholeStageCodegen (3) HashAggregate [s_store_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] Project [sales_price,profit,return_amt,net_loss,s_store_id] BroadcastHashJoin [store_sk,s_store_sk] Project [store_sk,sales_price,profit,return_amt,net_loss] BroadcastHashJoin [date_sk,d_date_sk] - InputAdapter - Union - WholeStageCodegen (1) - Project [ss_store_sk,ss_sold_date_sk,ss_ext_sales_price,ss_net_profit] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] - SubqueryBroadcast [d_date_sk] #1 - BroadcastExchange #4 - WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] - WholeStageCodegen (2) - Project [sr_store_sk,sr_returned_date_sk,sr_return_amt,sr_net_loss] - Filter [sr_store_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] - ReusedSubquery [d_date_sk] #1 + ColumnarToRow + InputAdapter + CometUnion + CometProject [ss_store_sk,ss_sold_date_sk,ss_ext_sales_price,ss_net_profit] [store_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [ss_store_sk] + CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #4 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] + CometProject [sr_store_sk,sr_returned_date_sk,sr_return_amt,sr_net_loss] [store_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [sr_store_sk] + CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #5 - WholeStageCodegen (4) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (2) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] - WholeStageCodegen (12) + WholeStageCodegen (8) HashAggregate [cp_catalog_page_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),channel,id,sales,returns,profit,sum,sum,sum,sum] InputAdapter Exchange [cp_catalog_page_id] #6 - WholeStageCodegen (11) + WholeStageCodegen (7) HashAggregate [cp_catalog_page_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] Project [sales_price,profit,return_amt,net_loss,cp_catalog_page_id] BroadcastHashJoin [page_sk,cp_catalog_page_sk] Project [page_sk,sales_price,profit,return_amt,net_loss] BroadcastHashJoin [date_sk,d_date_sk] - InputAdapter - Union - WholeStageCodegen (7) - Project [cs_catalog_page_sk,cs_sold_date_sk,cs_ext_sales_price,cs_net_profit] - Filter [cs_catalog_page_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] - ReusedSubquery [d_date_sk] #1 - WholeStageCodegen (8) - Project [cr_catalog_page_sk,cr_returned_date_sk,cr_return_amount,cr_net_loss] - Filter [cr_catalog_page_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.catalog_returns [cr_catalog_page_sk,cr_return_amount,cr_net_loss,cr_returned_date_sk] - ReusedSubquery [d_date_sk] #1 + ColumnarToRow + InputAdapter + CometUnion + CometProject [cs_catalog_page_sk,cs_sold_date_sk,cs_ext_sales_price,cs_net_profit] [page_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [cs_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [cr_catalog_page_sk,cr_returned_date_sk,cr_return_amount,cr_net_loss] [page_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [cr_catalog_page_sk] + CometScan parquet spark_catalog.default.catalog_returns [cr_catalog_page_sk,cr_return_amount,cr_net_loss,cr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #7 - WholeStageCodegen (10) - Filter [cp_catalog_page_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (6) + ColumnarToRow + InputAdapter + CometFilter [cp_catalog_page_sk] CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] - WholeStageCodegen (19) + WholeStageCodegen (12) HashAggregate [web_site_id,sum,sum,sum,sum] [sum(UnscaledValue(sales_price)),sum(UnscaledValue(return_amt)),sum(UnscaledValue(profit)),sum(UnscaledValue(net_loss)),channel,id,sales,returns,profit,sum,sum,sum,sum] InputAdapter Exchange [web_site_id] #8 - WholeStageCodegen (18) + WholeStageCodegen (11) HashAggregate [web_site_id,sales_price,return_amt,profit,net_loss] [sum,sum,sum,sum,sum,sum,sum,sum] Project [sales_price,profit,return_amt,net_loss,web_site_id] BroadcastHashJoin [wsr_web_site_sk,web_site_sk] Project [wsr_web_site_sk,sales_price,profit,return_amt,net_loss] BroadcastHashJoin [date_sk,d_date_sk] - InputAdapter - Union - WholeStageCodegen (13) - Project [ws_web_site_sk,ws_sold_date_sk,ws_ext_sales_price,ws_net_profit] - Filter [ws_web_site_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_sales [ws_web_site_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] - ReusedSubquery [d_date_sk] #1 - WholeStageCodegen (15) - Project [ws_web_site_sk,wr_returned_date_sk,wr_return_amt,wr_net_loss] - BroadcastHashJoin [wr_item_sk,wr_order_number,ws_item_sk,ws_order_number] - InputAdapter - BroadcastExchange #9 - WholeStageCodegen (14) - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] - ReusedSubquery [d_date_sk] #1 - Project [ws_item_sk,ws_web_site_sk,ws_order_number] - Filter [ws_item_sk,ws_order_number,ws_web_site_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_order_number,ws_sold_date_sk] + ColumnarToRow + InputAdapter + CometUnion + CometProject [ws_web_site_sk,ws_sold_date_sk,ws_ext_sales_price,ws_net_profit] [wsr_web_site_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometFilter [ws_web_site_sk] + CometScan parquet spark_catalog.default.web_sales [ws_web_site_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [ws_web_site_sk,wr_returned_date_sk,wr_return_amt,wr_net_loss] [wsr_web_site_sk,date_sk,sales_price,profit,return_amt,net_loss] + CometBroadcastHashJoin [wr_item_sk,wr_order_number,ws_item_sk,ws_order_number] + CometBroadcastExchange #9 + CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] + ReusedSubquery [d_date_sk] #1 + CometProject [ws_item_sk,ws_web_site_sk,ws_order_number] + CometFilter [ws_item_sk,ws_order_number,ws_web_site_sk] + CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_order_number,ws_sold_date_sk] InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #10 - WholeStageCodegen (17) - Filter [web_site_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometFilter [web_site_sk] CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] - WholeStageCodegen (43) + WholeStageCodegen (29) HashAggregate [channel,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),id,sum(sales),sum(returns),sum(profit),sum,isEmpty,sum,isEmpty,sum,isEmpty] InputAdapter Exchange [channel] #11 - WholeStageCodegen (42) + WholeStageCodegen (28) HashAggregate [channel,sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] InputAdapter ReusedExchange [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] #2 - WholeStageCodegen (65) + WholeStageCodegen (44) HashAggregate [sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),channel,id,sum(sales),sum(returns),sum(profit),sum,isEmpty,sum,isEmpty,sum,isEmpty] InputAdapter Exchange #12 - WholeStageCodegen (64) + WholeStageCodegen (43) HashAggregate [sales,returns,profit] [sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty,sum,isEmpty] HashAggregate [channel,id,sum,isEmpty,sum,isEmpty,sum,isEmpty] [sum(sales),sum(returns),sum(profit),sales,returns,profit,sum,isEmpty,sum,isEmpty,sum,isEmpty] InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/explain.txt index 7e0bfdaf7..a71a3a875 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/explain.txt @@ -12,31 +12,31 @@ TakeOrderedAndProject (39) : : +- * BroadcastHashJoin Inner BuildRight (14) : : :- * Project (9) : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.customer_address (1) : : : +- BroadcastExchange (7) - : : : +- * Filter (6) - : : : +- * ColumnarToRow (5) + : : : +- * ColumnarToRow (6) + : : : +- CometFilter (5) : : : +- CometScan parquet spark_catalog.default.customer (4) : : +- BroadcastExchange (13) - : : +- * Filter (12) - : : +- * ColumnarToRow (11) + : : +- * ColumnarToRow (12) + : : +- CometFilter (11) : : +- CometScan parquet spark_catalog.default.store_sales (10) : +- ReusedExchange (16) +- BroadcastExchange (32) +- * Project (31) +- * BroadcastHashJoin Inner BuildRight (30) - :- * Filter (21) - : +- * ColumnarToRow (20) + :- * ColumnarToRow (21) + : +- CometFilter (20) : +- CometScan parquet spark_catalog.default.item (19) +- BroadcastExchange (29) +- * Filter (28) +- * HashAggregate (27) +- Exchange (26) +- * HashAggregate (25) - +- * Filter (24) - +- * ColumnarToRow (23) + +- * ColumnarToRow (24) + +- CometFilter (23) +- CometScan parquet spark_catalog.default.item (22) @@ -47,12 +47,12 @@ Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 7] +(2) CometFilter Input [2]: [ca_address_sk#1, ca_state#2] +Condition : isnotnull(ca_address_sk#1) -(3) Filter [codegen id : 7] +(3) ColumnarToRow [codegen id : 7] Input [2]: [ca_address_sk#1, ca_state#2] -Condition : isnotnull(ca_address_sk#1) (4) Scan parquet spark_catalog.default.customer Output [2]: [c_customer_sk#3, c_current_addr_sk#4] @@ -61,12 +61,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_customer_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [2]: [c_customer_sk#3, c_current_addr_sk#4] +Condition : (isnotnull(c_current_addr_sk#4) AND isnotnull(c_customer_sk#3)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [2]: [c_customer_sk#3, c_current_addr_sk#4] -Condition : (isnotnull(c_current_addr_sk#4) AND isnotnull(c_customer_sk#3)) (7) BroadcastExchange Input [2]: [c_customer_sk#3, c_current_addr_sk#4] @@ -90,12 +90,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_customer_sk#6) AND isnotnull(ss_item_sk#5)) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] -Condition : (isnotnull(ss_customer_sk#6) AND isnotnull(ss_item_sk#5)) (13) BroadcastExchange Input [3]: [ss_item_sk#5, ss_customer_sk#6, ss_sold_date_sk#7] @@ -131,12 +131,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_current_price), IsNotNull(i_category), IsNotNull(i_item_sk)] ReadSchema: struct -(20) ColumnarToRow [codegen id : 6] +(20) CometFilter Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] +Condition : ((isnotnull(i_current_price#11) AND isnotnull(i_category#12)) AND isnotnull(i_item_sk#10)) -(21) Filter [codegen id : 6] +(21) ColumnarToRow [codegen id : 6] Input [3]: [i_item_sk#10, i_current_price#11, i_category#12] -Condition : ((isnotnull(i_current_price#11) AND isnotnull(i_category#12)) AND isnotnull(i_item_sk#10)) (22) Scan parquet spark_catalog.default.item Output [2]: [i_current_price#13, i_category#14] @@ -145,12 +145,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_category)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 4] +(23) CometFilter Input [2]: [i_current_price#13, i_category#14] +Condition : isnotnull(i_category#14) -(24) Filter [codegen id : 4] +(24) ColumnarToRow [codegen id : 4] Input [2]: [i_current_price#13, i_category#14] -Condition : isnotnull(i_category#14) (25) HashAggregate [codegen id : 4] Input [2]: [i_current_price#13, i_category#14] @@ -232,9 +232,9 @@ Arguments: 100, [cnt#25 ASC NULLS FIRST, state#24 ASC NULLS FIRST], [state#24, c Subquery:1 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (44) -+- * Project (43) - +- * Filter (42) - +- * ColumnarToRow (41) ++- * ColumnarToRow (43) + +- CometProject (42) + +- CometFilter (41) +- CometScan parquet spark_catalog.default.date_dim (40) @@ -245,30 +245,30 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), EqualTo(d_month_seq,ScalarSubquery#27), IsNotNull(d_date_sk)] ReadSchema: struct -(41) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#9, d_month_seq#26] - -(42) Filter [codegen id : 1] +(41) CometFilter Input [2]: [d_date_sk#9, d_month_seq#26] Condition : ((isnotnull(d_month_seq#26) AND (d_month_seq#26 = ReusedSubquery Subquery scalar-subquery#27, [id=#28])) AND isnotnull(d_date_sk#9)) -(43) Project [codegen id : 1] -Output [1]: [d_date_sk#9] +(42) CometProject Input [2]: [d_date_sk#9, d_month_seq#26] +Arguments: [d_date_sk#9], [d_date_sk#9] + +(43) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#9] (44) BroadcastExchange Input [1]: [d_date_sk#9] Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7] -Subquery:2 Hosting operator id = 42 Hosting Expression = ReusedSubquery Subquery scalar-subquery#27, [id=#28] +Subquery:2 Hosting operator id = 41 Hosting Expression = ReusedSubquery Subquery scalar-subquery#27, [id=#28] Subquery:3 Hosting operator id = 40 Hosting Expression = Subquery scalar-subquery#27, [id=#28] * HashAggregate (51) +- Exchange (50) - +- * HashAggregate (49) - +- * Project (48) - +- * Filter (47) - +- * ColumnarToRow (46) + +- * ColumnarToRow (49) + +- CometHashAggregate (48) + +- CometProject (47) + +- CometFilter (46) +- CometScan parquet spark_catalog.default.date_dim (45) @@ -279,23 +279,21 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,1)] ReadSchema: struct -(46) ColumnarToRow [codegen id : 1] -Input [3]: [d_month_seq#29, d_year#30, d_moy#31] - -(47) Filter [codegen id : 1] +(46) CometFilter Input [3]: [d_month_seq#29, d_year#30, d_moy#31] Condition : (((isnotnull(d_year#30) AND isnotnull(d_moy#31)) AND (d_year#30 = 2000)) AND (d_moy#31 = 1)) -(48) Project [codegen id : 1] -Output [1]: [d_month_seq#29] +(47) CometProject Input [3]: [d_month_seq#29, d_year#30, d_moy#31] +Arguments: [d_month_seq#29], [d_month_seq#29] -(49) HashAggregate [codegen id : 1] +(48) CometHashAggregate Input [1]: [d_month_seq#29] Keys [1]: [d_month_seq#29] Functions: [] -Aggregate Attributes: [] -Results [1]: [d_month_seq#29] + +(49) ColumnarToRow [codegen id : 1] +Input [1]: [d_month_seq#29] (50) Exchange Input [1]: [d_month_seq#29] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/simplified.txt index 7078a77e4..c2d5a6ce8 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q6/simplified.txt @@ -14,32 +14,32 @@ TakeOrderedAndProject [cnt,state] BroadcastHashJoin [c_customer_sk,ss_customer_sk] Project [ca_state,c_customer_sk] BroadcastHashJoin [ca_address_sk,c_current_addr_sk] - Filter [ca_address_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_state] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [c_current_addr_sk,c_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_current_addr_sk,c_customer_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_addr_sk] InputAdapter BroadcastExchange #3 WholeStageCodegen (2) - Filter [ss_customer_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ReusedSubquery [d_month_seq] #2 - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] + ReusedSubquery [d_month_seq] #2 CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] Subquery #2 WholeStageCodegen (2) @@ -47,11 +47,11 @@ TakeOrderedAndProject [cnt,state] InputAdapter Exchange [d_month_seq] #5 WholeStageCodegen (1) - HashAggregate [d_month_seq] - Project [d_month_seq] - Filter [d_year,d_moy] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometHashAggregate [d_month_seq] + CometProject [d_month_seq] + CometFilter [d_year,d_moy] CometScan parquet spark_catalog.default.date_dim [d_month_seq,d_year,d_moy] InputAdapter ReusedExchange [d_date_sk] #4 @@ -60,9 +60,9 @@ TakeOrderedAndProject [cnt,state] WholeStageCodegen (6) Project [i_item_sk] BroadcastHashJoin [i_category,i_category,i_current_price,avg(i_current_price)] - Filter [i_current_price,i_category,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_current_price,i_category,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_category] InputAdapter BroadcastExchange #7 @@ -73,7 +73,7 @@ TakeOrderedAndProject [cnt,state] Exchange [i_category] #8 WholeStageCodegen (4) HashAggregate [i_category,i_current_price] [sum,count,sum,count] - Filter [i_category] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_category] CometScan parquet spark_catalog.default.item [i_current_price,i_category] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/explain.txt index d2d493a6d..e50a522b8 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/explain.txt @@ -1,187 +1,185 @@ == Physical Plan == -* Sort (183) -+- Exchange (182) - +- * Project (181) - +- * SortMergeJoin Inner (180) - :- * Sort (111) - : +- Exchange (110) - : +- * HashAggregate (109) - : +- * HashAggregate (108) - : +- * Project (107) - : +- * BroadcastHashJoin Inner BuildRight (106) - : :- * Project (100) - : : +- * BroadcastHashJoin Inner BuildRight (99) - : : :- * Project (97) - : : : +- * BroadcastHashJoin Inner BuildRight (96) - : : : :- * Project (91) - : : : : +- * BroadcastHashJoin Inner BuildRight (90) - : : : : :- * Project (88) - : : : : : +- * BroadcastHashJoin Inner BuildRight (87) - : : : : : :- * Project (82) - : : : : : : +- * BroadcastHashJoin Inner BuildRight (81) - : : : : : : :- * Project (79) - : : : : : : : +- * BroadcastHashJoin Inner BuildRight (78) - : : : : : : : :- * Project (73) - : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (72) - : : : : : : : : :- * Project (67) - : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (66) - : : : : : : : : : :- * Project (64) - : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (63) - : : : : : : : : : : :- * Project (58) - : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (57) - : : : : : : : : : : : :- * Project (55) - : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (54) - : : : : : : : : : : : : :- * Project (49) - : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (48) - : : : : : : : : : : : : : :- * Project (43) - : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (42) - : : : : : : : : : : : : : : :- * Project (37) - : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (36) - : : : : : : : : : : : : : : : :- * Project (34) - : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (33) - : : : : : : : : : : : : : : : : :- * Sort (12) - : : : : : : : : : : : : : : : : : +- Exchange (11) - : : : : : : : : : : : : : : : : : +- * Project (10) - : : : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildLeft (9) - : : : : : : : : : : : : : : : : : :- BroadcastExchange (4) - : : : : : : : : : : : : : : : : : : +- * Filter (3) - : : : : : : : : : : : : : : : : : : +- * ColumnarToRow (2) - : : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) - : : : : : : : : : : : : : : : : : +- * Project (8) - : : : : : : : : : : : : : : : : : +- * Filter (7) - : : : : : : : : : : : : : : : : : +- * ColumnarToRow (6) - : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (5) - : : : : : : : : : : : : : : : : +- * Sort (32) - : : : : : : : : : : : : : : : : +- * Project (31) - : : : : : : : : : : : : : : : : +- * Filter (30) - : : : : : : : : : : : : : : : : +- * HashAggregate (29) - : : : : : : : : : : : : : : : : +- Exchange (28) - : : : : : : : : : : : : : : : : +- * HashAggregate (27) - : : : : : : : : : : : : : : : : +- * Project (26) - : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (25) - : : : : : : : : : : : : : : : : :- * Sort (18) - : : : : : : : : : : : : : : : : : +- Exchange (17) - : : : : : : : : : : : : : : : : : +- * Project (16) - : : : : : : : : : : : : : : : : : +- * Filter (15) - : : : : : : : : : : : : : : : : : +- * ColumnarToRow (14) - : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (13) - : : : : : : : : : : : : : : : : +- * Sort (24) - : : : : : : : : : : : : : : : : +- Exchange (23) - : : : : : : : : : : : : : : : : +- * Project (22) - : : : : : : : : : : : : : : : : +- * Filter (21) - : : : : : : : : : : : : : : : : +- * ColumnarToRow (20) - : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (19) - : : : : : : : : : : : : : : : +- ReusedExchange (35) - : : : : : : : : : : : : : : +- BroadcastExchange (41) - : : : : : : : : : : : : : : +- * Filter (40) - : : : : : : : : : : : : : : +- * ColumnarToRow (39) - : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store (38) - : : : : : : : : : : : : : +- BroadcastExchange (47) - : : : : : : : : : : : : : +- * Filter (46) - : : : : : : : : : : : : : +- * ColumnarToRow (45) - : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer (44) - : : : : : : : : : : : : +- BroadcastExchange (53) - : : : : : : : : : : : : +- * Filter (52) - : : : : : : : : : : : : +- * ColumnarToRow (51) - : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.date_dim (50) - : : : : : : : : : : : +- ReusedExchange (56) - : : : : : : : : : : +- BroadcastExchange (62) - : : : : : : : : : : +- * Filter (61) - : : : : : : : : : : +- * ColumnarToRow (60) - : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (59) - : : : : : : : : : +- ReusedExchange (65) - : : : : : : : : +- BroadcastExchange (71) - : : : : : : : : +- * Filter (70) - : : : : : : : : +- * ColumnarToRow (69) - : : : : : : : : +- CometScan parquet spark_catalog.default.promotion (68) - : : : : : : : +- BroadcastExchange (77) - : : : : : : : +- * Filter (76) - : : : : : : : +- * ColumnarToRow (75) - : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (74) - : : : : : : +- ReusedExchange (80) - : : : : : +- BroadcastExchange (86) - : : : : : +- * Filter (85) - : : : : : +- * ColumnarToRow (84) - : : : : : +- CometScan parquet spark_catalog.default.customer_address (83) - : : : : +- ReusedExchange (89) - : : : +- BroadcastExchange (95) - : : : +- * Filter (94) - : : : +- * ColumnarToRow (93) - : : : +- CometScan parquet spark_catalog.default.income_band (92) - : : +- ReusedExchange (98) - : +- BroadcastExchange (105) - : +- * Project (104) - : +- * Filter (103) - : +- * ColumnarToRow (102) - : +- CometScan parquet spark_catalog.default.item (101) - +- * Sort (179) - +- Exchange (178) - +- * HashAggregate (177) - +- * HashAggregate (176) - +- * Project (175) - +- * BroadcastHashJoin Inner BuildRight (174) - :- * Project (172) - : +- * BroadcastHashJoin Inner BuildRight (171) - : :- * Project (169) - : : +- * BroadcastHashJoin Inner BuildRight (168) - : : :- * Project (166) - : : : +- * BroadcastHashJoin Inner BuildRight (165) - : : : :- * Project (163) - : : : : +- * BroadcastHashJoin Inner BuildRight (162) - : : : : :- * Project (160) - : : : : : +- * BroadcastHashJoin Inner BuildRight (159) - : : : : : :- * Project (157) - : : : : : : +- * BroadcastHashJoin Inner BuildRight (156) - : : : : : : :- * Project (154) - : : : : : : : +- * BroadcastHashJoin Inner BuildRight (153) - : : : : : : : :- * Project (151) - : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (150) - : : : : : : : : :- * Project (148) - : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (147) - : : : : : : : : : :- * Project (145) - : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (144) - : : : : : : : : : : :- * Project (142) - : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (141) - : : : : : : : : : : : :- * Project (139) - : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (138) - : : : : : : : : : : : : :- * Project (136) - : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (135) - : : : : : : : : : : : : : :- * Project (133) - : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (132) - : : : : : : : : : : : : : : :- * Project (130) - : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (129) - : : : : : : : : : : : : : : : :- * Sort (123) - : : : : : : : : : : : : : : : : +- Exchange (122) - : : : : : : : : : : : : : : : : +- * Project (121) - : : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildLeft (120) - : : : : : : : : : : : : : : : : :- BroadcastExchange (115) - : : : : : : : : : : : : : : : : : +- * Filter (114) - : : : : : : : : : : : : : : : : : +- * ColumnarToRow (113) - : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (112) - : : : : : : : : : : : : : : : : +- * Project (119) - : : : : : : : : : : : : : : : : +- * Filter (118) - : : : : : : : : : : : : : : : : +- * ColumnarToRow (117) - : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (116) - : : : : : : : : : : : : : : : +- * Sort (128) - : : : : : : : : : : : : : : : +- * Project (127) - : : : : : : : : : : : : : : : +- * Filter (126) - : : : : : : : : : : : : : : : +- * HashAggregate (125) - : : : : : : : : : : : : : : : +- ReusedExchange (124) - : : : : : : : : : : : : : : +- ReusedExchange (131) - : : : : : : : : : : : : : +- ReusedExchange (134) - : : : : : : : : : : : : +- ReusedExchange (137) - : : : : : : : : : : : +- ReusedExchange (140) - : : : : : : : : : : +- ReusedExchange (143) - : : : : : : : : : +- ReusedExchange (146) - : : : : : : : : +- ReusedExchange (149) - : : : : : : : +- ReusedExchange (152) - : : : : : : +- ReusedExchange (155) - : : : : : +- ReusedExchange (158) - : : : : +- ReusedExchange (161) - : : : +- ReusedExchange (164) - : : +- ReusedExchange (167) - : +- ReusedExchange (170) - +- ReusedExchange (173) +* Sort (181) ++- Exchange (180) + +- * Project (179) + +- * SortMergeJoin Inner (178) + :- * Sort (110) + : +- Exchange (109) + : +- * HashAggregate (108) + : +- * HashAggregate (107) + : +- * Project (106) + : +- * BroadcastHashJoin Inner BuildRight (105) + : :- * Project (99) + : : +- * BroadcastHashJoin Inner BuildRight (98) + : : :- * Project (96) + : : : +- * BroadcastHashJoin Inner BuildRight (95) + : : : :- * Project (90) + : : : : +- * BroadcastHashJoin Inner BuildRight (89) + : : : : :- * Project (87) + : : : : : +- * BroadcastHashJoin Inner BuildRight (86) + : : : : : :- * Project (81) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (80) + : : : : : : :- * Project (78) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (77) + : : : : : : : :- * Project (72) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (71) + : : : : : : : : :- * Project (66) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (65) + : : : : : : : : : :- * Project (63) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (62) + : : : : : : : : : : :- * Project (57) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (56) + : : : : : : : : : : : :- * Project (54) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (53) + : : : : : : : : : : : : :- * Project (48) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (47) + : : : : : : : : : : : : : :- * Project (42) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (41) + : : : : : : : : : : : : : : :- * Project (36) + : : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (35) + : : : : : : : : : : : : : : : :- * Project (33) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (32) + : : : : : : : : : : : : : : : : :- * Sort (11) + : : : : : : : : : : : : : : : : : +- Exchange (10) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (9) + : : : : : : : : : : : : : : : : : +- CometProject (8) + : : : : : : : : : : : : : : : : : +- CometBroadcastHashJoin (7) + : : : : : : : : : : : : : : : : : :- CometBroadcastExchange (3) + : : : : : : : : : : : : : : : : : : +- CometFilter (2) + : : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) + : : : : : : : : : : : : : : : : : +- CometProject (6) + : : : : : : : : : : : : : : : : : +- CometFilter (5) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (4) + : : : : : : : : : : : : : : : : +- * Sort (31) + : : : : : : : : : : : : : : : : +- * Project (30) + : : : : : : : : : : : : : : : : +- * Filter (29) + : : : : : : : : : : : : : : : : +- * HashAggregate (28) + : : : : : : : : : : : : : : : : +- Exchange (27) + : : : : : : : : : : : : : : : : +- * HashAggregate (26) + : : : : : : : : : : : : : : : : +- * Project (25) + : : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (24) + : : : : : : : : : : : : : : : : :- * Sort (17) + : : : : : : : : : : : : : : : : : +- Exchange (16) + : : : : : : : : : : : : : : : : : +- * ColumnarToRow (15) + : : : : : : : : : : : : : : : : : +- CometProject (14) + : : : : : : : : : : : : : : : : : +- CometFilter (13) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (12) + : : : : : : : : : : : : : : : : +- * Sort (23) + : : : : : : : : : : : : : : : : +- Exchange (22) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (21) + : : : : : : : : : : : : : : : : +- CometProject (20) + : : : : : : : : : : : : : : : : +- CometFilter (19) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (18) + : : : : : : : : : : : : : : : +- ReusedExchange (34) + : : : : : : : : : : : : : : +- BroadcastExchange (40) + : : : : : : : : : : : : : : +- * ColumnarToRow (39) + : : : : : : : : : : : : : : +- CometFilter (38) + : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store (37) + : : : : : : : : : : : : : +- BroadcastExchange (46) + : : : : : : : : : : : : : +- * ColumnarToRow (45) + : : : : : : : : : : : : : +- CometFilter (44) + : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer (43) + : : : : : : : : : : : : +- BroadcastExchange (52) + : : : : : : : : : : : : +- * ColumnarToRow (51) + : : : : : : : : : : : : +- CometFilter (50) + : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.date_dim (49) + : : : : : : : : : : : +- ReusedExchange (55) + : : : : : : : : : : +- BroadcastExchange (61) + : : : : : : : : : : +- * ColumnarToRow (60) + : : : : : : : : : : +- CometFilter (59) + : : : : : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (58) + : : : : : : : : : +- ReusedExchange (64) + : : : : : : : : +- BroadcastExchange (70) + : : : : : : : : +- * ColumnarToRow (69) + : : : : : : : : +- CometFilter (68) + : : : : : : : : +- CometScan parquet spark_catalog.default.promotion (67) + : : : : : : : +- BroadcastExchange (76) + : : : : : : : +- * ColumnarToRow (75) + : : : : : : : +- CometFilter (74) + : : : : : : : +- CometScan parquet spark_catalog.default.household_demographics (73) + : : : : : : +- ReusedExchange (79) + : : : : : +- BroadcastExchange (85) + : : : : : +- * ColumnarToRow (84) + : : : : : +- CometFilter (83) + : : : : : +- CometScan parquet spark_catalog.default.customer_address (82) + : : : : +- ReusedExchange (88) + : : : +- BroadcastExchange (94) + : : : +- * ColumnarToRow (93) + : : : +- CometFilter (92) + : : : +- CometScan parquet spark_catalog.default.income_band (91) + : : +- ReusedExchange (97) + : +- BroadcastExchange (104) + : +- * ColumnarToRow (103) + : +- CometProject (102) + : +- CometFilter (101) + : +- CometScan parquet spark_catalog.default.item (100) + +- * Sort (177) + +- Exchange (176) + +- * HashAggregate (175) + +- * HashAggregate (174) + +- * Project (173) + +- * BroadcastHashJoin Inner BuildRight (172) + :- * Project (170) + : +- * BroadcastHashJoin Inner BuildRight (169) + : :- * Project (167) + : : +- * BroadcastHashJoin Inner BuildRight (166) + : : :- * Project (164) + : : : +- * BroadcastHashJoin Inner BuildRight (163) + : : : :- * Project (161) + : : : : +- * BroadcastHashJoin Inner BuildRight (160) + : : : : :- * Project (158) + : : : : : +- * BroadcastHashJoin Inner BuildRight (157) + : : : : : :- * Project (155) + : : : : : : +- * BroadcastHashJoin Inner BuildRight (154) + : : : : : : :- * Project (152) + : : : : : : : +- * BroadcastHashJoin Inner BuildRight (151) + : : : : : : : :- * Project (149) + : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (148) + : : : : : : : : :- * Project (146) + : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (145) + : : : : : : : : : :- * Project (143) + : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (142) + : : : : : : : : : : :- * Project (140) + : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (139) + : : : : : : : : : : : :- * Project (137) + : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (136) + : : : : : : : : : : : : :- * Project (134) + : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (133) + : : : : : : : : : : : : : :- * Project (131) + : : : : : : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (130) + : : : : : : : : : : : : : : :- * Project (128) + : : : : : : : : : : : : : : : +- * SortMergeJoin Inner (127) + : : : : : : : : : : : : : : : :- * Sort (121) + : : : : : : : : : : : : : : : : +- Exchange (120) + : : : : : : : : : : : : : : : : +- * ColumnarToRow (119) + : : : : : : : : : : : : : : : : +- CometProject (118) + : : : : : : : : : : : : : : : : +- CometBroadcastHashJoin (117) + : : : : : : : : : : : : : : : : :- CometBroadcastExchange (113) + : : : : : : : : : : : : : : : : : +- CometFilter (112) + : : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (111) + : : : : : : : : : : : : : : : : +- CometProject (116) + : : : : : : : : : : : : : : : : +- CometFilter (115) + : : : : : : : : : : : : : : : : +- CometScan parquet spark_catalog.default.store_returns (114) + : : : : : : : : : : : : : : : +- * Sort (126) + : : : : : : : : : : : : : : : +- * Project (125) + : : : : : : : : : : : : : : : +- * Filter (124) + : : : : : : : : : : : : : : : +- * HashAggregate (123) + : : : : : : : : : : : : : : : +- ReusedExchange (122) + : : : : : : : : : : : : : : +- ReusedExchange (129) + : : : : : : : : : : : : : +- ReusedExchange (132) + : : : : : : : : : : : : +- ReusedExchange (135) + : : : : : : : : : : : +- ReusedExchange (138) + : : : : : : : : : : +- ReusedExchange (141) + : : : : : : : : : +- ReusedExchange (144) + : : : : : : : : +- ReusedExchange (147) + : : : : : : : +- ReusedExchange (150) + : : : : : : +- ReusedExchange (153) + : : : : : +- ReusedExchange (156) + : : : : +- ReusedExchange (159) + : : : +- ReusedExchange (162) + : : +- ReusedExchange (165) + : +- ReusedExchange (168) + +- ReusedExchange (171) (1) Scan parquet spark_catalog.default.store_sales @@ -192,512 +190,508 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#12), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] -Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] - -(3) Filter [codegen id : 1] +(2) CometFilter Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] Condition : (((((((isnotnull(ss_item_sk#1) AND isnotnull(ss_ticket_number#8)) AND isnotnull(ss_store_sk#6)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_cdemo_sk#3)) AND isnotnull(ss_promo_sk#7)) AND isnotnull(ss_hdemo_sk#4)) AND isnotnull(ss_addr_sk#5)) -(4) BroadcastExchange +(3) CometBroadcastExchange Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[7, int, false] as bigint) & 4294967295))),false), [plan_id=1] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] -(5) Scan parquet spark_catalog.default.store_returns +(4) Scan parquet spark_catalog.default.store_returns Output [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] Batched: true Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] ReadSchema: struct -(6) ColumnarToRow -Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] - -(7) Filter +(5) CometFilter Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] Condition : (isnotnull(sr_item_sk#14) AND isnotnull(sr_ticket_number#15)) -(8) Project -Output [2]: [sr_item_sk#14, sr_ticket_number#15] +(6) CometProject Input [3]: [sr_item_sk#14, sr_ticket_number#15, sr_returned_date_sk#16] +Arguments: [sr_item_sk#14, sr_ticket_number#15], [sr_item_sk#14, sr_ticket_number#15] -(9) BroadcastHashJoin [codegen id : 2] -Left keys [2]: [ss_item_sk#1, ss_ticket_number#8] -Right keys [2]: [sr_item_sk#14, sr_ticket_number#15] -Join type: Inner -Join condition: None +(7) CometBroadcastHashJoin +Left output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +Right output [2]: [sr_item_sk#14, sr_ticket_number#15] +Arguments: [ss_item_sk#1, ss_ticket_number#8], [sr_item_sk#14, sr_ticket_number#15], Inner -(10) Project [codegen id : 2] -Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] +(8) CometProject Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_ticket_number#8, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, sr_item_sk#14, sr_ticket_number#15] +Arguments: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12], [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] + +(9) ColumnarToRow [codegen id : 1] +Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] -(11) Exchange +(10) Exchange Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] -Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2] +Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=1] -(12) Sort [codegen id : 3] +(11) Sort [codegen id : 2] Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] Arguments: [ss_item_sk#1 ASC NULLS FIRST], false, 0 -(13) Scan parquet spark_catalog.default.catalog_sales +(12) Scan parquet spark_catalog.default.catalog_sales Output [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] Batched: true Location [not included in comparison]/{warehouse_dir}/catalog_sales] PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_order_number)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 4] -Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] - -(15) Filter [codegen id : 4] +(13) CometFilter Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] Condition : (isnotnull(cs_item_sk#17) AND isnotnull(cs_order_number#18)) -(16) Project [codegen id : 4] -Output [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] +(14) CometProject Input [4]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cs_sold_date_sk#20] +Arguments: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19], [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] + +(15) ColumnarToRow [codegen id : 3] +Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] -(17) Exchange +(16) Exchange Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] -Arguments: hashpartitioning(cs_item_sk#17, cs_order_number#18, 5), ENSURE_REQUIREMENTS, [plan_id=3] +Arguments: hashpartitioning(cs_item_sk#17, cs_order_number#18, 5), ENSURE_REQUIREMENTS, [plan_id=2] -(18) Sort [codegen id : 5] +(17) Sort [codegen id : 4] Input [3]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19] Arguments: [cs_item_sk#17 ASC NULLS FIRST, cs_order_number#18 ASC NULLS FIRST], false, 0 -(19) Scan parquet spark_catalog.default.catalog_returns +(18) Scan parquet spark_catalog.default.catalog_returns Output [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] Batched: true Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] ReadSchema: struct -(20) ColumnarToRow [codegen id : 6] -Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] - -(21) Filter [codegen id : 6] +(19) CometFilter Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] Condition : (isnotnull(cr_item_sk#21) AND isnotnull(cr_order_number#22)) -(22) Project [codegen id : 6] -Output [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] +(20) CometProject Input [6]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25, cr_returned_date_sk#26] +Arguments: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25], [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] + +(21) ColumnarToRow [codegen id : 5] +Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] -(23) Exchange +(22) Exchange Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] -Arguments: hashpartitioning(cr_item_sk#21, cr_order_number#22, 5), ENSURE_REQUIREMENTS, [plan_id=4] +Arguments: hashpartitioning(cr_item_sk#21, cr_order_number#22, 5), ENSURE_REQUIREMENTS, [plan_id=3] -(24) Sort [codegen id : 7] +(23) Sort [codegen id : 6] Input [5]: [cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] Arguments: [cr_item_sk#21 ASC NULLS FIRST, cr_order_number#22 ASC NULLS FIRST], false, 0 -(25) SortMergeJoin [codegen id : 8] +(24) SortMergeJoin [codegen id : 7] Left keys [2]: [cs_item_sk#17, cs_order_number#18] Right keys [2]: [cr_item_sk#21, cr_order_number#22] Join type: Inner Join condition: None -(26) Project [codegen id : 8] +(25) Project [codegen id : 7] Output [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] Input [8]: [cs_item_sk#17, cs_order_number#18, cs_ext_list_price#19, cr_item_sk#21, cr_order_number#22, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] -(27) HashAggregate [codegen id : 8] +(26) HashAggregate [codegen id : 7] Input [5]: [cs_item_sk#17, cs_ext_list_price#19, cr_refunded_cash#23, cr_reversed_charge#24, cr_store_credit#25] Keys [1]: [cs_item_sk#17] Functions [2]: [partial_sum(UnscaledValue(cs_ext_list_price#19)), partial_sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] Aggregate Attributes [3]: [sum#27, sum#28, isEmpty#29] Results [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] -(28) Exchange +(27) Exchange Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] -Arguments: hashpartitioning(cs_item_sk#17, 5), ENSURE_REQUIREMENTS, [plan_id=5] +Arguments: hashpartitioning(cs_item_sk#17, 5), ENSURE_REQUIREMENTS, [plan_id=4] -(29) HashAggregate [codegen id : 9] +(28) HashAggregate [codegen id : 8] Input [4]: [cs_item_sk#17, sum#30, sum#31, isEmpty#32] Keys [1]: [cs_item_sk#17] Functions [2]: [sum(UnscaledValue(cs_ext_list_price#19)), sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))] Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#19))#33, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34] Results [3]: [cs_item_sk#17, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#19))#33,17,2) AS sale#35, sum(((cr_refunded_cash#23 + cr_reversed_charge#24) + cr_store_credit#25))#34 AS refund#36] -(30) Filter [codegen id : 9] +(29) Filter [codegen id : 8] Input [3]: [cs_item_sk#17, sale#35, refund#36] Condition : ((isnotnull(sale#35) AND isnotnull(refund#36)) AND (cast(sale#35 as decimal(21,2)) > (2 * refund#36))) -(31) Project [codegen id : 9] +(30) Project [codegen id : 8] Output [1]: [cs_item_sk#17] Input [3]: [cs_item_sk#17, sale#35, refund#36] -(32) Sort [codegen id : 9] +(31) Sort [codegen id : 8] Input [1]: [cs_item_sk#17] Arguments: [cs_item_sk#17 ASC NULLS FIRST], false, 0 -(33) SortMergeJoin [codegen id : 25] +(32) SortMergeJoin [codegen id : 24] Left keys [1]: [ss_item_sk#1] Right keys [1]: [cs_item_sk#17] Join type: Inner Join condition: None -(34) Project [codegen id : 25] +(33) Project [codegen id : 24] Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12] Input [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, cs_item_sk#17] -(35) ReusedExchange [Reuses operator id: 187] +(34) ReusedExchange [Reuses operator id: 185] Output [2]: [d_date_sk#37, d_year#38] -(36) BroadcastHashJoin [codegen id : 25] +(35) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_sold_date_sk#12] Right keys [1]: [d_date_sk#37] Join type: Inner Join condition: None -(37) Project [codegen id : 25] +(36) Project [codegen id : 24] Output [11]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38] Input [13]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, ss_sold_date_sk#12, d_date_sk#37, d_year#38] -(38) Scan parquet spark_catalog.default.store +(37) Scan parquet spark_catalog.default.store Output [3]: [s_store_sk#39, s_store_name#40, s_zip#41] Batched: true Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_name), IsNotNull(s_zip)] ReadSchema: struct -(39) ColumnarToRow [codegen id : 11] +(38) CometFilter Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] +Condition : ((isnotnull(s_store_sk#39) AND isnotnull(s_store_name#40)) AND isnotnull(s_zip#41)) -(40) Filter [codegen id : 11] +(39) ColumnarToRow [codegen id : 10] Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] -Condition : ((isnotnull(s_store_sk#39) AND isnotnull(s_store_name#40)) AND isnotnull(s_zip#41)) -(41) BroadcastExchange +(40) BroadcastExchange Input [3]: [s_store_sk#39, s_store_name#40, s_zip#41] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5] -(42) BroadcastHashJoin [codegen id : 25] +(41) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_store_sk#6] Right keys [1]: [s_store_sk#39] Join type: Inner Join condition: None -(43) Project [codegen id : 25] +(42) Project [codegen id : 24] Output [12]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41] Input [14]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_store_sk#6, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_sk#39, s_store_name#40, s_zip#41] -(44) Scan parquet spark_catalog.default.customer +(43) Scan parquet spark_catalog.default.customer Output [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] Batched: true Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_first_sales_date_sk), IsNotNull(c_first_shipto_date_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_hdemo_sk), IsNotNull(c_current_addr_sk)] ReadSchema: struct -(45) ColumnarToRow [codegen id : 12] +(44) CometFilter Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] +Condition : (((((isnotnull(c_customer_sk#42) AND isnotnull(c_first_sales_date_sk#47)) AND isnotnull(c_first_shipto_date_sk#46)) AND isnotnull(c_current_cdemo_sk#43)) AND isnotnull(c_current_hdemo_sk#44)) AND isnotnull(c_current_addr_sk#45)) -(46) Filter [codegen id : 12] +(45) ColumnarToRow [codegen id : 11] Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] -Condition : (((((isnotnull(c_customer_sk#42) AND isnotnull(c_first_sales_date_sk#47)) AND isnotnull(c_first_shipto_date_sk#46)) AND isnotnull(c_current_cdemo_sk#43)) AND isnotnull(c_current_hdemo_sk#44)) AND isnotnull(c_current_addr_sk#45)) -(47) BroadcastExchange +(46) BroadcastExchange Input [6]: [c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6] -(48) BroadcastHashJoin [codegen id : 25] +(47) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_customer_sk#2] Right keys [1]: [c_customer_sk#42] Join type: Inner Join condition: None -(49) Project [codegen id : 25] +(48) Project [codegen id : 24] Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] Input [18]: [ss_item_sk#1, ss_customer_sk#2, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_customer_sk#42, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47] -(50) Scan parquet spark_catalog.default.date_dim +(49) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date_sk#48, d_year#49] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date_sk)] ReadSchema: struct -(51) ColumnarToRow [codegen id : 13] +(50) CometFilter Input [2]: [d_date_sk#48, d_year#49] +Condition : isnotnull(d_date_sk#48) -(52) Filter [codegen id : 13] +(51) ColumnarToRow [codegen id : 12] Input [2]: [d_date_sk#48, d_year#49] -Condition : isnotnull(d_date_sk#48) -(53) BroadcastExchange +(52) BroadcastExchange Input [2]: [d_date_sk#48, d_year#49] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7] -(54) BroadcastHashJoin [codegen id : 25] +(53) BroadcastHashJoin [codegen id : 24] Left keys [1]: [c_first_sales_date_sk#47] Right keys [1]: [d_date_sk#48] Join type: Inner Join condition: None -(55) Project [codegen id : 25] +(54) Project [codegen id : 24] Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49] Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, c_first_sales_date_sk#47, d_date_sk#48, d_year#49] -(56) ReusedExchange [Reuses operator id: 53] +(55) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#50, d_year#51] -(57) BroadcastHashJoin [codegen id : 25] +(56) BroadcastHashJoin [codegen id : 24] Left keys [1]: [c_first_shipto_date_sk#46] Right keys [1]: [d_date_sk#50] Join type: Inner Join condition: None -(58) Project [codegen id : 25] +(57) Project [codegen id : 24] Output [16]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, c_first_shipto_date_sk#46, d_year#49, d_date_sk#50, d_year#51] -(59) Scan parquet spark_catalog.default.customer_demographics +(58) Scan parquet spark_catalog.default.customer_demographics Output [2]: [cd_demo_sk#52, cd_marital_status#53] Batched: true Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status)] ReadSchema: struct -(60) ColumnarToRow [codegen id : 15] +(59) CometFilter Input [2]: [cd_demo_sk#52, cd_marital_status#53] +Condition : (isnotnull(cd_demo_sk#52) AND isnotnull(cd_marital_status#53)) -(61) Filter [codegen id : 15] +(60) ColumnarToRow [codegen id : 14] Input [2]: [cd_demo_sk#52, cd_marital_status#53] -Condition : (isnotnull(cd_demo_sk#52) AND isnotnull(cd_marital_status#53)) -(62) BroadcastExchange +(61) BroadcastExchange Input [2]: [cd_demo_sk#52, cd_marital_status#53] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8] -(63) BroadcastHashJoin [codegen id : 25] +(62) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_cdemo_sk#3] Right keys [1]: [cd_demo_sk#52] Join type: Inner Join condition: None -(64) Project [codegen id : 25] +(63) Project [codegen id : 24] Output [16]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53] Input [18]: [ss_item_sk#1, ss_cdemo_sk#3, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_demo_sk#52, cd_marital_status#53] -(65) ReusedExchange [Reuses operator id: 62] +(64) ReusedExchange [Reuses operator id: 61] Output [2]: [cd_demo_sk#54, cd_marital_status#55] -(66) BroadcastHashJoin [codegen id : 25] +(65) BroadcastHashJoin [codegen id : 24] Left keys [1]: [c_current_cdemo_sk#43] Right keys [1]: [cd_demo_sk#54] Join type: Inner Join condition: NOT (cd_marital_status#53 = cd_marital_status#55) -(67) Project [codegen id : 25] +(66) Project [codegen id : 24] Output [14]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] Input [18]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_cdemo_sk#43, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, cd_marital_status#53, cd_demo_sk#54, cd_marital_status#55] -(68) Scan parquet spark_catalog.default.promotion +(67) Scan parquet spark_catalog.default.promotion Output [1]: [p_promo_sk#56] Batched: true Location [not included in comparison]/{warehouse_dir}/promotion] PushedFilters: [IsNotNull(p_promo_sk)] ReadSchema: struct -(69) ColumnarToRow [codegen id : 17] +(68) CometFilter Input [1]: [p_promo_sk#56] +Condition : isnotnull(p_promo_sk#56) -(70) Filter [codegen id : 17] +(69) ColumnarToRow [codegen id : 16] Input [1]: [p_promo_sk#56] -Condition : isnotnull(p_promo_sk#56) -(71) BroadcastExchange +(70) BroadcastExchange Input [1]: [p_promo_sk#56] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=9] -(72) BroadcastHashJoin [codegen id : 25] +(71) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_promo_sk#7] Right keys [1]: [p_promo_sk#56] Join type: Inner Join condition: None -(73) Project [codegen id : 25] +(72) Project [codegen id : 24] Output [13]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51] Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_promo_sk#7, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, p_promo_sk#56] -(74) Scan parquet spark_catalog.default.household_demographics +(73) Scan parquet spark_catalog.default.household_demographics Output [2]: [hd_demo_sk#57, hd_income_band_sk#58] Batched: true Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_demo_sk), IsNotNull(hd_income_band_sk)] ReadSchema: struct -(75) ColumnarToRow [codegen id : 18] +(74) CometFilter Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] +Condition : (isnotnull(hd_demo_sk#57) AND isnotnull(hd_income_band_sk#58)) -(76) Filter [codegen id : 18] +(75) ColumnarToRow [codegen id : 17] Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] -Condition : (isnotnull(hd_demo_sk#57) AND isnotnull(hd_income_band_sk#58)) -(77) BroadcastExchange +(76) BroadcastExchange Input [2]: [hd_demo_sk#57, hd_income_band_sk#58] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=11] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=10] -(78) BroadcastHashJoin [codegen id : 25] +(77) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_hdemo_sk#4] Right keys [1]: [hd_demo_sk#57] Join type: Inner Join condition: None -(79) Project [codegen id : 25] +(78) Project [codegen id : 24] Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58] Input [15]: [ss_item_sk#1, ss_hdemo_sk#4, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_demo_sk#57, hd_income_band_sk#58] -(80) ReusedExchange [Reuses operator id: 77] +(79) ReusedExchange [Reuses operator id: 76] Output [2]: [hd_demo_sk#59, hd_income_band_sk#60] -(81) BroadcastHashJoin [codegen id : 25] +(80) BroadcastHashJoin [codegen id : 24] Left keys [1]: [c_current_hdemo_sk#44] Right keys [1]: [hd_demo_sk#59] Join type: Inner Join condition: None -(82) Project [codegen id : 25] +(81) Project [codegen id : 24] Output [13]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60] Input [15]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_hdemo_sk#44, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_demo_sk#59, hd_income_band_sk#60] -(83) Scan parquet spark_catalog.default.customer_address +(82) Scan parquet spark_catalog.default.customer_address Output [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] Batched: true Location [not included in comparison]/{warehouse_dir}/customer_address] PushedFilters: [IsNotNull(ca_address_sk)] ReadSchema: struct -(84) ColumnarToRow [codegen id : 20] +(83) CometFilter Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] +Condition : isnotnull(ca_address_sk#61) -(85) Filter [codegen id : 20] +(84) ColumnarToRow [codegen id : 19] Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] -Condition : isnotnull(ca_address_sk#61) -(86) BroadcastExchange +(85) BroadcastExchange Input [5]: [ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=11] -(87) BroadcastHashJoin [codegen id : 25] +(86) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_addr_sk#5] Right keys [1]: [ca_address_sk#61] Join type: Inner Join condition: None -(88) Project [codegen id : 25] +(87) Project [codegen id : 24] Output [16]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] Input [18]: [ss_item_sk#1, ss_addr_sk#5, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_address_sk#61, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65] -(89) ReusedExchange [Reuses operator id: 86] +(88) ReusedExchange [Reuses operator id: 85] Output [5]: [ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] -(90) BroadcastHashJoin [codegen id : 25] +(89) BroadcastHashJoin [codegen id : 24] Left keys [1]: [c_current_addr_sk#45] Right keys [1]: [ca_address_sk#66] Join type: Inner Join condition: None -(91) Project [codegen id : 25] +(90) Project [codegen id : 24] Output [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] Input [21]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, c_current_addr_sk#45, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_address_sk#66, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] -(92) Scan parquet spark_catalog.default.income_band +(91) Scan parquet spark_catalog.default.income_band Output [1]: [ib_income_band_sk#71] Batched: true Location [not included in comparison]/{warehouse_dir}/income_band] PushedFilters: [IsNotNull(ib_income_band_sk)] ReadSchema: struct -(93) ColumnarToRow [codegen id : 22] +(92) CometFilter Input [1]: [ib_income_band_sk#71] +Condition : isnotnull(ib_income_band_sk#71) -(94) Filter [codegen id : 22] +(93) ColumnarToRow [codegen id : 21] Input [1]: [ib_income_band_sk#71] -Condition : isnotnull(ib_income_band_sk#71) -(95) BroadcastExchange +(94) BroadcastExchange Input [1]: [ib_income_band_sk#71] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=13] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=12] -(96) BroadcastHashJoin [codegen id : 25] +(95) BroadcastHashJoin [codegen id : 24] Left keys [1]: [hd_income_band_sk#58] Right keys [1]: [ib_income_band_sk#71] Join type: Inner Join condition: None -(97) Project [codegen id : 25] +(96) Project [codegen id : 24] Output [18]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] Input [20]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#58, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#71] -(98) ReusedExchange [Reuses operator id: 95] +(97) ReusedExchange [Reuses operator id: 94] Output [1]: [ib_income_band_sk#72] -(99) BroadcastHashJoin [codegen id : 25] +(98) BroadcastHashJoin [codegen id : 24] Left keys [1]: [hd_income_band_sk#60] Right keys [1]: [ib_income_band_sk#72] Join type: Inner Join condition: None -(100) Project [codegen id : 25] +(99) Project [codegen id : 24] Output [17]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70] Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, hd_income_band_sk#60, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, ib_income_band_sk#72] -(101) Scan parquet spark_catalog.default.item +(100) Scan parquet spark_catalog.default.item Output [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] Batched: true Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_current_price), In(i_color, [burlywood ,floral ,indian ,medium ,purple ,spring ]), GreaterThanOrEqual(i_current_price,64.00), LessThanOrEqual(i_current_price,74.00), GreaterThanOrEqual(i_current_price,65.00), LessThanOrEqual(i_current_price,79.00), IsNotNull(i_item_sk)] ReadSchema: struct -(102) ColumnarToRow [codegen id : 24] -Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] - -(103) Filter [codegen id : 24] +(101) CometFilter Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] Condition : ((((((isnotnull(i_current_price#74) AND i_color#75 IN (purple ,burlywood ,indian ,spring ,floral ,medium )) AND (i_current_price#74 >= 64.00)) AND (i_current_price#74 <= 74.00)) AND (i_current_price#74 >= 65.00)) AND (i_current_price#74 <= 79.00)) AND isnotnull(i_item_sk#73)) -(104) Project [codegen id : 24] -Output [2]: [i_item_sk#73, i_product_name#76] +(102) CometProject Input [4]: [i_item_sk#73, i_current_price#74, i_color#75, i_product_name#76] +Arguments: [i_item_sk#73, i_product_name#76], [i_item_sk#73, i_product_name#76] + +(103) ColumnarToRow [codegen id : 23] +Input [2]: [i_item_sk#73, i_product_name#76] -(105) BroadcastExchange +(104) BroadcastExchange Input [2]: [i_item_sk#73, i_product_name#76] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13] -(106) BroadcastHashJoin [codegen id : 25] +(105) BroadcastHashJoin [codegen id : 24] Left keys [1]: [ss_item_sk#1] Right keys [1]: [i_item_sk#73] Join type: Inner Join condition: None -(107) Project [codegen id : 25] +(106) Project [codegen id : 24] Output [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] Input [19]: [ss_item_sk#1, ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, s_store_name#40, s_zip#41, d_year#49, d_year#51, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] -(108) HashAggregate [codegen id : 25] +(107) HashAggregate [codegen id : 24] Input [18]: [ss_wholesale_cost#9, ss_list_price#10, ss_coupon_amt#11, d_year#38, d_year#49, d_year#51, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, i_item_sk#73, i_product_name#76] Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#9)), partial_sum(UnscaledValue(ss_list_price#10)), partial_sum(UnscaledValue(ss_coupon_amt#11))] Aggregate Attributes [4]: [count#77, sum#78, sum#79, sum#80] Results [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] -(109) HashAggregate [codegen id : 25] +(108) HashAggregate [codegen id : 24] Input [19]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51, count#81, sum#82, sum#83, sum#84] Keys [15]: [i_product_name#76, i_item_sk#73, s_store_name#40, s_zip#41, ca_street_number#62, ca_street_name#63, ca_city#64, ca_zip#65, ca_street_number#67, ca_street_name#68, ca_city#69, ca_zip#70, d_year#38, d_year#49, d_year#51] Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#9)), sum(UnscaledValue(ss_list_price#10)), sum(UnscaledValue(ss_coupon_amt#11))] Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#9))#86, sum(UnscaledValue(ss_list_price#10))#87, sum(UnscaledValue(ss_coupon_amt#11))#88] Results [17]: [i_product_name#76 AS product_name#89, i_item_sk#73 AS item_sk#90, s_store_name#40 AS store_name#91, s_zip#41 AS store_zip#92, ca_street_number#62 AS b_street_number#93, ca_street_name#63 AS b_streen_name#94, ca_city#64 AS b_city#95, ca_zip#65 AS b_zip#96, ca_street_number#67 AS c_street_number#97, ca_street_name#68 AS c_street_name#98, ca_city#69 AS c_city#99, ca_zip#70 AS c_zip#100, d_year#38 AS syear#101, count(1)#85 AS cnt#102, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#9))#86,17,2) AS s1#103, MakeDecimal(sum(UnscaledValue(ss_list_price#10))#87,17,2) AS s2#104, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#11))#88,17,2) AS s3#105] -(110) Exchange +(109) Exchange Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] -Arguments: hashpartitioning(item_sk#90, store_name#91, store_zip#92, 5), ENSURE_REQUIREMENTS, [plan_id=15] +Arguments: hashpartitioning(item_sk#90, store_name#91, store_zip#92, 5), ENSURE_REQUIREMENTS, [plan_id=14] -(111) Sort [codegen id : 26] +(110) Sort [codegen id : 25] Input [17]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105] Arguments: [item_sk#90 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, store_zip#92 ASC NULLS FIRST], false, 0 -(112) Scan parquet spark_catalog.default.store_sales +(111) Scan parquet spark_catalog.default.store_sales Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] Batched: true Location: InMemoryFileIndex [] @@ -705,370 +699,366 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#117), dynamicpruningexpression(ss_s PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_promo_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk)] ReadSchema: struct -(113) ColumnarToRow [codegen id : 27] -Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] - -(114) Filter [codegen id : 27] +(112) CometFilter Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] Condition : (((((((isnotnull(ss_item_sk#106) AND isnotnull(ss_ticket_number#113)) AND isnotnull(ss_store_sk#111)) AND isnotnull(ss_customer_sk#107)) AND isnotnull(ss_cdemo_sk#108)) AND isnotnull(ss_promo_sk#112)) AND isnotnull(ss_hdemo_sk#109)) AND isnotnull(ss_addr_sk#110)) -(115) BroadcastExchange +(113) CometBroadcastExchange Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] -Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[7, int, false] as bigint) & 4294967295))),false), [plan_id=16] +Arguments: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] -(116) Scan parquet spark_catalog.default.store_returns +(114) Scan parquet spark_catalog.default.store_returns Output [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] Batched: true Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] ReadSchema: struct -(117) ColumnarToRow -Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] - -(118) Filter +(115) CometFilter Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] Condition : (isnotnull(sr_item_sk#119) AND isnotnull(sr_ticket_number#120)) -(119) Project -Output [2]: [sr_item_sk#119, sr_ticket_number#120] +(116) CometProject Input [3]: [sr_item_sk#119, sr_ticket_number#120, sr_returned_date_sk#121] +Arguments: [sr_item_sk#119, sr_ticket_number#120], [sr_item_sk#119, sr_ticket_number#120] -(120) BroadcastHashJoin [codegen id : 28] -Left keys [2]: [ss_item_sk#106, ss_ticket_number#113] -Right keys [2]: [sr_item_sk#119, sr_ticket_number#120] -Join type: Inner -Join condition: None +(117) CometBroadcastHashJoin +Left output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +Right output [2]: [sr_item_sk#119, sr_ticket_number#120] +Arguments: [ss_item_sk#106, ss_ticket_number#113], [sr_item_sk#119, sr_ticket_number#120], Inner -(121) Project [codegen id : 28] -Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] +(118) CometProject Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_ticket_number#113, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, sr_item_sk#119, sr_ticket_number#120] +Arguments: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117], [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] + +(119) ColumnarToRow [codegen id : 26] +Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] -(122) Exchange +(120) Exchange Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] -Arguments: hashpartitioning(ss_item_sk#106, 5), ENSURE_REQUIREMENTS, [plan_id=17] +Arguments: hashpartitioning(ss_item_sk#106, 5), ENSURE_REQUIREMENTS, [plan_id=15] -(123) Sort [codegen id : 29] +(121) Sort [codegen id : 27] Input [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] Arguments: [ss_item_sk#106 ASC NULLS FIRST], false, 0 -(124) ReusedExchange [Reuses operator id: 28] +(122) ReusedExchange [Reuses operator id: 27] Output [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] -(125) HashAggregate [codegen id : 35] +(123) HashAggregate [codegen id : 33] Input [4]: [cs_item_sk#122, sum#123, sum#124, isEmpty#125] Keys [1]: [cs_item_sk#122] Functions [2]: [sum(UnscaledValue(cs_ext_list_price#126)), sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))] Aggregate Attributes [2]: [sum(UnscaledValue(cs_ext_list_price#126))#33, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34] Results [3]: [cs_item_sk#122, MakeDecimal(sum(UnscaledValue(cs_ext_list_price#126))#33,17,2) AS sale#130, sum(((cr_refunded_cash#127 + cr_reversed_charge#128) + cr_store_credit#129))#34 AS refund#131] -(126) Filter [codegen id : 35] +(124) Filter [codegen id : 33] Input [3]: [cs_item_sk#122, sale#130, refund#131] Condition : ((isnotnull(sale#130) AND isnotnull(refund#131)) AND (cast(sale#130 as decimal(21,2)) > (2 * refund#131))) -(127) Project [codegen id : 35] +(125) Project [codegen id : 33] Output [1]: [cs_item_sk#122] Input [3]: [cs_item_sk#122, sale#130, refund#131] -(128) Sort [codegen id : 35] +(126) Sort [codegen id : 33] Input [1]: [cs_item_sk#122] Arguments: [cs_item_sk#122 ASC NULLS FIRST], false, 0 -(129) SortMergeJoin [codegen id : 51] +(127) SortMergeJoin [codegen id : 49] Left keys [1]: [ss_item_sk#106] Right keys [1]: [cs_item_sk#122] Join type: Inner Join condition: None -(130) Project [codegen id : 51] +(128) Project [codegen id : 49] Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117] Input [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, cs_item_sk#122] -(131) ReusedExchange [Reuses operator id: 191] +(129) ReusedExchange [Reuses operator id: 189] Output [2]: [d_date_sk#132, d_year#133] -(132) BroadcastHashJoin [codegen id : 51] +(130) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_sold_date_sk#117] Right keys [1]: [d_date_sk#132] Join type: Inner Join condition: None -(133) Project [codegen id : 51] +(131) Project [codegen id : 49] Output [11]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133] Input [13]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, ss_sold_date_sk#117, d_date_sk#132, d_year#133] -(134) ReusedExchange [Reuses operator id: 41] +(132) ReusedExchange [Reuses operator id: 40] Output [3]: [s_store_sk#134, s_store_name#135, s_zip#136] -(135) BroadcastHashJoin [codegen id : 51] +(133) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_store_sk#111] Right keys [1]: [s_store_sk#134] Join type: Inner Join condition: None -(136) Project [codegen id : 51] +(134) Project [codegen id : 49] Output [12]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136] Input [14]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_store_sk#111, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_sk#134, s_store_name#135, s_zip#136] -(137) ReusedExchange [Reuses operator id: 47] +(135) ReusedExchange [Reuses operator id: 46] Output [6]: [c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] -(138) BroadcastHashJoin [codegen id : 51] +(136) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_customer_sk#107] Right keys [1]: [c_customer_sk#137] Join type: Inner Join condition: None -(139) Project [codegen id : 51] +(137) Project [codegen id : 49] Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] Input [18]: [ss_item_sk#106, ss_customer_sk#107, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_customer_sk#137, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142] -(140) ReusedExchange [Reuses operator id: 53] +(138) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#143, d_year#144] -(141) BroadcastHashJoin [codegen id : 51] +(139) BroadcastHashJoin [codegen id : 49] Left keys [1]: [c_first_sales_date_sk#142] Right keys [1]: [d_date_sk#143] Join type: Inner Join condition: None -(142) Project [codegen id : 51] +(140) Project [codegen id : 49] Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144] Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, c_first_sales_date_sk#142, d_date_sk#143, d_year#144] -(143) ReusedExchange [Reuses operator id: 53] +(141) ReusedExchange [Reuses operator id: 52] Output [2]: [d_date_sk#145, d_year#146] -(144) BroadcastHashJoin [codegen id : 51] +(142) BroadcastHashJoin [codegen id : 49] Left keys [1]: [c_first_shipto_date_sk#141] Right keys [1]: [d_date_sk#145] Join type: Inner Join condition: None -(145) Project [codegen id : 51] +(143) Project [codegen id : 49] Output [16]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, c_first_shipto_date_sk#141, d_year#144, d_date_sk#145, d_year#146] -(146) ReusedExchange [Reuses operator id: 62] +(144) ReusedExchange [Reuses operator id: 61] Output [2]: [cd_demo_sk#147, cd_marital_status#148] -(147) BroadcastHashJoin [codegen id : 51] +(145) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_cdemo_sk#108] Right keys [1]: [cd_demo_sk#147] Join type: Inner Join condition: None -(148) Project [codegen id : 51] +(146) Project [codegen id : 49] Output [16]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148] Input [18]: [ss_item_sk#106, ss_cdemo_sk#108, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_demo_sk#147, cd_marital_status#148] -(149) ReusedExchange [Reuses operator id: 62] +(147) ReusedExchange [Reuses operator id: 61] Output [2]: [cd_demo_sk#149, cd_marital_status#150] -(150) BroadcastHashJoin [codegen id : 51] +(148) BroadcastHashJoin [codegen id : 49] Left keys [1]: [c_current_cdemo_sk#138] Right keys [1]: [cd_demo_sk#149] Join type: Inner Join condition: NOT (cd_marital_status#148 = cd_marital_status#150) -(151) Project [codegen id : 51] +(149) Project [codegen id : 49] Output [14]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] Input [18]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_cdemo_sk#138, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, cd_marital_status#148, cd_demo_sk#149, cd_marital_status#150] -(152) ReusedExchange [Reuses operator id: 71] +(150) ReusedExchange [Reuses operator id: 70] Output [1]: [p_promo_sk#151] -(153) BroadcastHashJoin [codegen id : 51] +(151) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_promo_sk#112] Right keys [1]: [p_promo_sk#151] Join type: Inner Join condition: None -(154) Project [codegen id : 51] +(152) Project [codegen id : 49] Output [13]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146] Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_promo_sk#112, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, p_promo_sk#151] -(155) ReusedExchange [Reuses operator id: 77] +(153) ReusedExchange [Reuses operator id: 76] Output [2]: [hd_demo_sk#152, hd_income_band_sk#153] -(156) BroadcastHashJoin [codegen id : 51] +(154) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_hdemo_sk#109] Right keys [1]: [hd_demo_sk#152] Join type: Inner Join condition: None -(157) Project [codegen id : 51] +(155) Project [codegen id : 49] Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153] Input [15]: [ss_item_sk#106, ss_hdemo_sk#109, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_demo_sk#152, hd_income_band_sk#153] -(158) ReusedExchange [Reuses operator id: 77] +(156) ReusedExchange [Reuses operator id: 76] Output [2]: [hd_demo_sk#154, hd_income_band_sk#155] -(159) BroadcastHashJoin [codegen id : 51] +(157) BroadcastHashJoin [codegen id : 49] Left keys [1]: [c_current_hdemo_sk#139] Right keys [1]: [hd_demo_sk#154] Join type: Inner Join condition: None -(160) Project [codegen id : 51] +(158) Project [codegen id : 49] Output [13]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155] Input [15]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_hdemo_sk#139, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_demo_sk#154, hd_income_band_sk#155] -(161) ReusedExchange [Reuses operator id: 86] +(159) ReusedExchange [Reuses operator id: 85] Output [5]: [ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] -(162) BroadcastHashJoin [codegen id : 51] +(160) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_addr_sk#110] Right keys [1]: [ca_address_sk#156] Join type: Inner Join condition: None -(163) Project [codegen id : 51] +(161) Project [codegen id : 49] Output [16]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] Input [18]: [ss_item_sk#106, ss_addr_sk#110, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_address_sk#156, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160] -(164) ReusedExchange [Reuses operator id: 86] +(162) ReusedExchange [Reuses operator id: 85] Output [5]: [ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] -(165) BroadcastHashJoin [codegen id : 51] +(163) BroadcastHashJoin [codegen id : 49] Left keys [1]: [c_current_addr_sk#140] Right keys [1]: [ca_address_sk#161] Join type: Inner Join condition: None -(166) Project [codegen id : 51] +(164) Project [codegen id : 49] Output [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] Input [21]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, c_current_addr_sk#140, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_address_sk#161, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] -(167) ReusedExchange [Reuses operator id: 95] +(165) ReusedExchange [Reuses operator id: 94] Output [1]: [ib_income_band_sk#166] -(168) BroadcastHashJoin [codegen id : 51] +(166) BroadcastHashJoin [codegen id : 49] Left keys [1]: [hd_income_band_sk#153] Right keys [1]: [ib_income_band_sk#166] Join type: Inner Join condition: None -(169) Project [codegen id : 51] +(167) Project [codegen id : 49] Output [18]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] Input [20]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#153, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#166] -(170) ReusedExchange [Reuses operator id: 95] +(168) ReusedExchange [Reuses operator id: 94] Output [1]: [ib_income_band_sk#167] -(171) BroadcastHashJoin [codegen id : 51] +(169) BroadcastHashJoin [codegen id : 49] Left keys [1]: [hd_income_band_sk#155] Right keys [1]: [ib_income_band_sk#167] Join type: Inner Join condition: None -(172) Project [codegen id : 51] +(170) Project [codegen id : 49] Output [17]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165] Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, hd_income_band_sk#155, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, ib_income_band_sk#167] -(173) ReusedExchange [Reuses operator id: 105] +(171) ReusedExchange [Reuses operator id: 104] Output [2]: [i_item_sk#168, i_product_name#169] -(174) BroadcastHashJoin [codegen id : 51] +(172) BroadcastHashJoin [codegen id : 49] Left keys [1]: [ss_item_sk#106] Right keys [1]: [i_item_sk#168] Join type: Inner Join condition: None -(175) Project [codegen id : 51] +(173) Project [codegen id : 49] Output [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] Input [19]: [ss_item_sk#106, ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, s_store_name#135, s_zip#136, d_year#144, d_year#146, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] -(176) HashAggregate [codegen id : 51] +(174) HashAggregate [codegen id : 49] Input [18]: [ss_wholesale_cost#114, ss_list_price#115, ss_coupon_amt#116, d_year#133, d_year#144, d_year#146, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, i_item_sk#168, i_product_name#169] Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] Functions [4]: [partial_count(1), partial_sum(UnscaledValue(ss_wholesale_cost#114)), partial_sum(UnscaledValue(ss_list_price#115)), partial_sum(UnscaledValue(ss_coupon_amt#116))] Aggregate Attributes [4]: [count#77, sum#170, sum#171, sum#172] Results [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] -(177) HashAggregate [codegen id : 51] +(175) HashAggregate [codegen id : 49] Input [19]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146, count#81, sum#173, sum#174, sum#175] Keys [15]: [i_product_name#169, i_item_sk#168, s_store_name#135, s_zip#136, ca_street_number#157, ca_street_name#158, ca_city#159, ca_zip#160, ca_street_number#162, ca_street_name#163, ca_city#164, ca_zip#165, d_year#133, d_year#144, d_year#146] Functions [4]: [count(1), sum(UnscaledValue(ss_wholesale_cost#114)), sum(UnscaledValue(ss_list_price#115)), sum(UnscaledValue(ss_coupon_amt#116))] Aggregate Attributes [4]: [count(1)#85, sum(UnscaledValue(ss_wholesale_cost#114))#86, sum(UnscaledValue(ss_list_price#115))#87, sum(UnscaledValue(ss_coupon_amt#116))#88] Results [8]: [i_item_sk#168 AS item_sk#176, s_store_name#135 AS store_name#177, s_zip#136 AS store_zip#178, d_year#133 AS syear#179, count(1)#85 AS cnt#180, MakeDecimal(sum(UnscaledValue(ss_wholesale_cost#114))#86,17,2) AS s1#181, MakeDecimal(sum(UnscaledValue(ss_list_price#115))#87,17,2) AS s2#182, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#116))#88,17,2) AS s3#183] -(178) Exchange +(176) Exchange Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] -Arguments: hashpartitioning(item_sk#176, store_name#177, store_zip#178, 5), ENSURE_REQUIREMENTS, [plan_id=18] +Arguments: hashpartitioning(item_sk#176, store_name#177, store_zip#178, 5), ENSURE_REQUIREMENTS, [plan_id=16] -(179) Sort [codegen id : 52] +(177) Sort [codegen id : 50] Input [8]: [item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] Arguments: [item_sk#176 ASC NULLS FIRST, store_name#177 ASC NULLS FIRST, store_zip#178 ASC NULLS FIRST], false, 0 -(180) SortMergeJoin [codegen id : 53] +(178) SortMergeJoin [codegen id : 51] Left keys [3]: [item_sk#90, store_name#91, store_zip#92] Right keys [3]: [item_sk#176, store_name#177, store_zip#178] Join type: Inner Join condition: (cnt#180 <= cnt#102) -(181) Project [codegen id : 53] +(179) Project [codegen id : 51] Output [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] Input [25]: [product_name#89, item_sk#90, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, item_sk#176, store_name#177, store_zip#178, syear#179, cnt#180, s1#181, s2#182, s3#183] -(182) Exchange +(180) Exchange Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] -Arguments: rangepartitioning(product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, s1#103 ASC NULLS FIRST, s1#181 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=19] +Arguments: rangepartitioning(product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, s1#103 ASC NULLS FIRST, s1#181 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, [plan_id=17] -(183) Sort [codegen id : 54] +(181) Sort [codegen id : 52] Input [21]: [product_name#89, store_name#91, store_zip#92, b_street_number#93, b_streen_name#94, b_city#95, b_zip#96, c_street_number#97, c_street_name#98, c_city#99, c_zip#100, syear#101, cnt#102, s1#103, s2#104, s3#105, s1#181, s2#182, s3#183, syear#179, cnt#180] Arguments: [product_name#89 ASC NULLS FIRST, store_name#91 ASC NULLS FIRST, cnt#180 ASC NULLS FIRST, s1#103 ASC NULLS FIRST, s1#181 ASC NULLS FIRST], true, 0 ===== Subqueries ===== Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#12 IN dynamicpruning#13 -BroadcastExchange (187) -+- * Filter (186) - +- * ColumnarToRow (185) - +- CometScan parquet spark_catalog.default.date_dim (184) +BroadcastExchange (185) ++- * ColumnarToRow (184) + +- CometFilter (183) + +- CometScan parquet spark_catalog.default.date_dim (182) -(184) Scan parquet spark_catalog.default.date_dim +(182) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date_sk#37, d_year#38] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk)] ReadSchema: struct -(185) ColumnarToRow [codegen id : 1] +(183) CometFilter Input [2]: [d_date_sk#37, d_year#38] +Condition : ((isnotnull(d_year#38) AND (d_year#38 = 1999)) AND isnotnull(d_date_sk#37)) -(186) Filter [codegen id : 1] +(184) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#37, d_year#38] -Condition : ((isnotnull(d_year#38) AND (d_year#38 = 1999)) AND isnotnull(d_date_sk#37)) -(187) BroadcastExchange +(185) BroadcastExchange Input [2]: [d_date_sk#37, d_year#38] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=20] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=18] -Subquery:2 Hosting operator id = 112 Hosting Expression = ss_sold_date_sk#117 IN dynamicpruning#118 -BroadcastExchange (191) -+- * Filter (190) - +- * ColumnarToRow (189) - +- CometScan parquet spark_catalog.default.date_dim (188) +Subquery:2 Hosting operator id = 111 Hosting Expression = ss_sold_date_sk#117 IN dynamicpruning#118 +BroadcastExchange (189) ++- * ColumnarToRow (188) + +- CometFilter (187) + +- CometScan parquet spark_catalog.default.date_dim (186) -(188) Scan parquet spark_catalog.default.date_dim +(186) Scan parquet spark_catalog.default.date_dim Output [2]: [d_date_sk#132, d_year#133] Batched: true Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(189) ColumnarToRow [codegen id : 1] +(187) CometFilter Input [2]: [d_date_sk#132, d_year#133] +Condition : ((isnotnull(d_year#133) AND (d_year#133 = 2000)) AND isnotnull(d_date_sk#132)) -(190) Filter [codegen id : 1] +(188) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#132, d_year#133] -Condition : ((isnotnull(d_year#133) AND (d_year#133 = 2000)) AND isnotnull(d_date_sk#132)) -(191) BroadcastExchange +(189) BroadcastExchange Input [2]: [d_date_sk#132, d_year#133] -Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=21] +Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=19] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/simplified.txt index 410352945..2a0bc5bce 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q64/simplified.txt @@ -1,16 +1,16 @@ -WholeStageCodegen (54) +WholeStageCodegen (52) Sort [product_name,store_name,cnt,s1,s1] InputAdapter Exchange [product_name,store_name,cnt,s1,s1] #1 - WholeStageCodegen (53) + WholeStageCodegen (51) Project [product_name,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,s1,s2,s3,syear,cnt] SortMergeJoin [item_sk,store_name,store_zip,item_sk,store_name,store_zip,cnt,cnt] InputAdapter - WholeStageCodegen (26) + WholeStageCodegen (25) Sort [item_sk,store_name,store_zip] InputAdapter Exchange [item_sk,store_name,store_zip] #2 - WholeStageCodegen (25) + WholeStageCodegen (24) HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),product_name,item_sk,store_name,store_zip,b_street_number,b_streen_name,b_city,b_zip,c_street_number,c_street_name,c_city,c_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] @@ -46,148 +46,144 @@ WholeStageCodegen (54) Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] SortMergeJoin [ss_item_sk,cs_item_sk] InputAdapter - WholeStageCodegen (3) + WholeStageCodegen (2) Sort [ss_item_sk] InputAdapter Exchange [ss_item_sk] #3 - WholeStageCodegen (2) - Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] - BroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] - InputAdapter - BroadcastExchange #4 - WholeStageCodegen (1) - Filter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] - SubqueryBroadcast [d_date_sk] #1 - BroadcastExchange #5 - WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] - Project [sr_item_sk,sr_ticket_number] - Filter [sr_item_sk,sr_ticket_number] - ColumnarToRow - InputAdapter + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + CometBroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + CometBroadcastExchange #4 + CometFilter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #1 + BroadcastExchange #5 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_item_sk,sr_ticket_number] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] InputAdapter - WholeStageCodegen (9) + WholeStageCodegen (8) Sort [cs_item_sk] Project [cs_item_sk] Filter [sale,refund] HashAggregate [cs_item_sk,sum,sum,isEmpty] [sum(UnscaledValue(cs_ext_list_price)),sum(((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)),sale,refund,sum,sum,isEmpty] InputAdapter Exchange [cs_item_sk] #6 - WholeStageCodegen (8) + WholeStageCodegen (7) HashAggregate [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] [sum,sum,isEmpty,sum,sum,isEmpty] Project [cs_item_sk,cs_ext_list_price,cr_refunded_cash,cr_reversed_charge,cr_store_credit] SortMergeJoin [cs_item_sk,cs_order_number,cr_item_sk,cr_order_number] InputAdapter - WholeStageCodegen (5) + WholeStageCodegen (4) Sort [cs_item_sk,cs_order_number] InputAdapter Exchange [cs_item_sk,cs_order_number] #7 - WholeStageCodegen (4) - Project [cs_item_sk,cs_order_number,cs_ext_list_price] - Filter [cs_item_sk,cs_order_number] - ColumnarToRow - InputAdapter + WholeStageCodegen (3) + ColumnarToRow + InputAdapter + CometProject [cs_item_sk,cs_order_number,cs_ext_list_price] + CometFilter [cs_item_sk,cs_order_number] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_ext_list_price,cs_sold_date_sk] InputAdapter - WholeStageCodegen (7) + WholeStageCodegen (6) Sort [cr_item_sk,cr_order_number] InputAdapter Exchange [cr_item_sk,cr_order_number] #8 - WholeStageCodegen (6) - Project [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit] - Filter [cr_item_sk,cr_order_number] - ColumnarToRow - InputAdapter + WholeStageCodegen (5) + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit] + CometFilter [cr_item_sk,cr_order_number] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_refunded_cash,cr_reversed_charge,cr_store_credit,cr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk,d_year] #5 InputAdapter BroadcastExchange #9 - WholeStageCodegen (11) - Filter [s_store_sk,s_store_name,s_zip] - ColumnarToRow - InputAdapter + WholeStageCodegen (10) + ColumnarToRow + InputAdapter + CometFilter [s_store_sk,s_store_name,s_zip] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_name,s_zip] InputAdapter BroadcastExchange #10 - WholeStageCodegen (12) - Filter [c_customer_sk,c_first_sales_date_sk,c_first_shipto_date_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (11) + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_first_sales_date_sk,c_first_shipto_date_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_current_cdemo_sk,c_current_hdemo_sk,c_current_addr_sk,c_first_shipto_date_sk,c_first_sales_date_sk] InputAdapter BroadcastExchange #11 - WholeStageCodegen (13) - Filter [d_date_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (12) + ColumnarToRow + InputAdapter + CometFilter [d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #11 InputAdapter BroadcastExchange #12 - WholeStageCodegen (15) - Filter [cd_demo_sk,cd_marital_status] - ColumnarToRow - InputAdapter + WholeStageCodegen (14) + ColumnarToRow + InputAdapter + CometFilter [cd_demo_sk,cd_marital_status] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] InputAdapter ReusedExchange [cd_demo_sk,cd_marital_status] #12 InputAdapter BroadcastExchange #13 - WholeStageCodegen (17) - Filter [p_promo_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (16) + ColumnarToRow + InputAdapter + CometFilter [p_promo_sk] CometScan parquet spark_catalog.default.promotion [p_promo_sk] InputAdapter BroadcastExchange #14 - WholeStageCodegen (18) - Filter [hd_demo_sk,hd_income_band_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (17) + ColumnarToRow + InputAdapter + CometFilter [hd_demo_sk,hd_income_band_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_income_band_sk] InputAdapter ReusedExchange [hd_demo_sk,hd_income_band_sk] #14 InputAdapter BroadcastExchange #15 - WholeStageCodegen (20) - Filter [ca_address_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (19) + ColumnarToRow + InputAdapter + CometFilter [ca_address_sk] CometScan parquet spark_catalog.default.customer_address [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] InputAdapter ReusedExchange [ca_address_sk,ca_street_number,ca_street_name,ca_city,ca_zip] #15 InputAdapter BroadcastExchange #16 - WholeStageCodegen (22) - Filter [ib_income_band_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (21) + ColumnarToRow + InputAdapter + CometFilter [ib_income_band_sk] CometScan parquet spark_catalog.default.income_band [ib_income_band_sk] InputAdapter ReusedExchange [ib_income_band_sk] #16 InputAdapter BroadcastExchange #17 - WholeStageCodegen (24) - Project [i_item_sk,i_product_name] - Filter [i_current_price,i_color,i_item_sk] - ColumnarToRow - InputAdapter + WholeStageCodegen (23) + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_product_name] + CometFilter [i_current_price,i_color,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price,i_color,i_product_name] InputAdapter - WholeStageCodegen (52) + WholeStageCodegen (50) Sort [item_sk,store_name,store_zip] InputAdapter Exchange [item_sk,store_name,store_zip] #18 - WholeStageCodegen (51) + WholeStageCodegen (49) HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,count,sum,sum,sum] [count(1),sum(UnscaledValue(ss_wholesale_cost)),sum(UnscaledValue(ss_list_price)),sum(UnscaledValue(ss_coupon_amt)),item_sk,store_name,store_zip,syear,cnt,s1,s2,s3,count,sum,sum,sum] HashAggregate [i_product_name,i_item_sk,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,d_year,d_year,d_year,ss_wholesale_cost,ss_list_price,ss_coupon_amt] [count,sum,sum,sum,count,sum,sum,sum] Project [ss_wholesale_cost,ss_list_price,ss_coupon_amt,d_year,d_year,d_year,s_store_name,s_zip,ca_street_number,ca_street_name,ca_city,ca_zip,ca_street_number,ca_street_name,ca_city,ca_zip,i_item_sk,i_product_name] @@ -223,34 +219,30 @@ WholeStageCodegen (54) Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] SortMergeJoin [ss_item_sk,cs_item_sk] InputAdapter - WholeStageCodegen (29) + WholeStageCodegen (27) Sort [ss_item_sk] InputAdapter Exchange [ss_item_sk] #19 - WholeStageCodegen (28) - Project [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] - BroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] - InputAdapter - BroadcastExchange #20 - WholeStageCodegen (27) - Filter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] - SubqueryBroadcast [d_date_sk] #2 - BroadcastExchange #21 - WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter - CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] - Project [sr_item_sk,sr_ticket_number] - Filter [sr_item_sk,sr_ticket_number] - ColumnarToRow - InputAdapter + WholeStageCodegen (26) + ColumnarToRow + InputAdapter + CometProject [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + CometBroadcastHashJoin [ss_item_sk,ss_ticket_number,sr_item_sk,sr_ticket_number] + CometBroadcastExchange #20 + CometFilter [ss_item_sk,ss_ticket_number,ss_store_sk,ss_customer_sk,ss_cdemo_sk,ss_promo_sk,ss_hdemo_sk,ss_addr_sk] + CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_cdemo_sk,ss_hdemo_sk,ss_addr_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_wholesale_cost,ss_list_price,ss_coupon_amt,ss_sold_date_sk] + SubqueryBroadcast [d_date_sk] #2 + BroadcastExchange #21 + WholeStageCodegen (1) + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] + CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_item_sk,sr_ticket_number] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] InputAdapter - WholeStageCodegen (35) + WholeStageCodegen (33) Sort [cs_item_sk] Project [cs_item_sk] Filter [sale,refund] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/explain.txt index 5c6c416ce..6ca27323a 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/explain.txt @@ -17,17 +17,17 @@ TakeOrderedAndProject (70) : : +- * BroadcastHashJoin Inner BuildRight (11) : : :- * Project (6) : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : :- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : :- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- ReusedExchange (4) : : +- BroadcastExchange (10) - : : +- * Filter (9) - : : +- * ColumnarToRow (8) + : : +- * ColumnarToRow (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.store (7) : +- BroadcastExchange (16) - : +- * Filter (15) - : +- * ColumnarToRow (14) + : +- * ColumnarToRow (15) + : +- CometFilter (14) : +- CometScan parquet spark_catalog.default.item (13) :- * HashAggregate (26) : +- Exchange (25) @@ -79,12 +79,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 4] +(2) CometFilter Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] +Condition : (isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) -(3) Filter [codegen id : 4] +(3) ColumnarToRow [codegen id : 4] Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5] -Condition : (isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) (4) ReusedExchange [Reuses operator id: 75] Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] @@ -106,12 +106,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [2]: [s_store_sk#11, s_store_id#12] +Condition : isnotnull(s_store_sk#11) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [2]: [s_store_sk#11, s_store_id#12] -Condition : isnotnull(s_store_sk#11) (10) BroadcastExchange Input [2]: [s_store_sk#11, s_store_id#12] @@ -134,12 +134,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 3] +(14) CometFilter Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] +Condition : isnotnull(i_item_sk#13) -(15) Filter [codegen id : 3] +(15) ColumnarToRow [codegen id : 3] Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] -Condition : isnotnull(i_item_sk#13) (16) BroadcastExchange Input [5]: [i_item_sk#13, i_brand#14, i_class#15, i_category#16, i_product_name#17] @@ -435,9 +435,9 @@ Arguments: 100, [i_category#23 ASC NULLS FIRST, i_class#24 ASC NULLS FIRST, i_br Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (75) -+- * Project (74) - +- * Filter (73) - +- * ColumnarToRow (72) ++- * ColumnarToRow (74) + +- CometProject (73) + +- CometFilter (72) +- CometScan parquet spark_catalog.default.date_dim (71) @@ -448,16 +448,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] ReadSchema: struct -(72) ColumnarToRow [codegen id : 1] -Input [5]: [d_date_sk#7, d_month_seq#221, d_year#8, d_moy#9, d_qoy#10] - -(73) Filter [codegen id : 1] +(72) CometFilter Input [5]: [d_date_sk#7, d_month_seq#221, d_year#8, d_moy#9, d_qoy#10] Condition : (((isnotnull(d_month_seq#221) AND (d_month_seq#221 >= 1212)) AND (d_month_seq#221 <= 1223)) AND isnotnull(d_date_sk#7)) -(74) Project [codegen id : 1] -Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] +(73) CometProject Input [5]: [d_date_sk#7, d_month_seq#221, d_year#8, d_moy#9, d_qoy#10] +Arguments: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10], [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] + +(74) ColumnarToRow [codegen id : 1] +Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] (75) BroadcastExchange Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/simplified.txt index aed12f8ec..4d2d3972d 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q67a/simplified.txt @@ -25,33 +25,33 @@ TakeOrderedAndProject [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_ BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,d_year,d_moy,d_qoy] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk,ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_quantity,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk,d_year,d_moy,d_qoy] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_year,d_moy,d_qoy] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq,d_year,d_moy,d_qoy] InputAdapter ReusedExchange [d_date_sk,d_year,d_moy,d_qoy] #3 InputAdapter BroadcastExchange #4 WholeStageCodegen (2) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] InputAdapter BroadcastExchange #5 WholeStageCodegen (3) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand,i_class,i_category,i_product_name] WholeStageCodegen (11) HashAggregate [i_category,i_class,i_brand,i_product_name,d_year,d_qoy,d_moy,sum,isEmpty] [sum(sumsales),s_store_id,sumsales,sum,isEmpty] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/explain.txt index 189cbfd42..6a81a2ec1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/explain.txt @@ -15,14 +15,14 @@ TakeOrderedAndProject (56) : +- * BroadcastHashJoin Inner BuildRight (33) : :- * Project (6) : : +- * BroadcastHashJoin Inner BuildRight (5) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : +- ReusedExchange (4) : +- BroadcastExchange (32) : +- * BroadcastHashJoin LeftSemi BuildRight (31) - : :- * Filter (9) - : : +- * ColumnarToRow (8) + : :- * ColumnarToRow (9) + : : +- CometFilter (8) : : +- CometScan parquet spark_catalog.default.store (7) : +- BroadcastExchange (30) : +- * Project (29) @@ -37,12 +37,12 @@ TakeOrderedAndProject (56) : +- * BroadcastHashJoin Inner BuildRight (20) : :- * Project (18) : : +- * BroadcastHashJoin Inner BuildRight (17) - : : :- * Filter (12) - : : : +- * ColumnarToRow (11) + : : :- * ColumnarToRow (12) + : : : +- CometFilter (11) : : : +- CometScan parquet spark_catalog.default.store_sales (10) : : +- BroadcastExchange (16) - : : +- * Filter (15) - : : +- * ColumnarToRow (14) + : : +- * ColumnarToRow (15) + : : +- CometFilter (14) : : +- CometScan parquet spark_catalog.default.store (13) : +- ReusedExchange (19) :- * HashAggregate (42) @@ -65,12 +65,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 8] +(2) CometFilter Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_store_sk#1) -(3) Filter [codegen id : 8] +(3) ColumnarToRow [codegen id : 8] Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3] -Condition : isnotnull(ss_store_sk#1) (4) ReusedExchange [Reuses operator id: 61] Output [1]: [d_date_sk#5] @@ -92,12 +92,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 7] +(8) CometFilter Input [3]: [s_store_sk#6, s_county#7, s_state#8] +Condition : isnotnull(s_store_sk#6) -(9) Filter [codegen id : 7] +(9) ColumnarToRow [codegen id : 7] Input [3]: [s_store_sk#6, s_county#7, s_state#8] -Condition : isnotnull(s_store_sk#6) (10) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] @@ -107,12 +107,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 4] +(11) CometFilter Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] +Condition : isnotnull(ss_store_sk#9) -(12) Filter [codegen id : 4] +(12) ColumnarToRow [codegen id : 4] Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11] -Condition : isnotnull(ss_store_sk#9) (13) Scan parquet spark_catalog.default.store Output [2]: [s_store_sk#13, s_state#14] @@ -121,12 +121,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(14) ColumnarToRow [codegen id : 2] +(14) CometFilter Input [2]: [s_store_sk#13, s_state#14] +Condition : isnotnull(s_store_sk#13) -(15) Filter [codegen id : 2] +(15) ColumnarToRow [codegen id : 2] Input [2]: [s_store_sk#13, s_state#14] -Condition : isnotnull(s_store_sk#13) (16) BroadcastExchange Input [2]: [s_store_sk#13, s_state#14] @@ -335,9 +335,9 @@ Arguments: 100, [lochierarchy#27 DESC NULLS LAST, CASE WHEN (lochierarchy#27 = 0 Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (61) -+- * Project (60) - +- * Filter (59) - +- * ColumnarToRow (58) ++- * ColumnarToRow (60) + +- CometProject (59) + +- CometFilter (58) +- CometScan parquet spark_catalog.default.date_dim (57) @@ -348,16 +348,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] ReadSchema: struct -(58) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#5, d_month_seq#61] - -(59) Filter [codegen id : 1] +(58) CometFilter Input [2]: [d_date_sk#5, d_month_seq#61] Condition : (((isnotnull(d_month_seq#61) AND (d_month_seq#61 >= 1212)) AND (d_month_seq#61 <= 1223)) AND isnotnull(d_date_sk#5)) -(60) Project [codegen id : 1] -Output [1]: [d_date_sk#5] +(59) CometProject Input [2]: [d_date_sk#5, d_month_seq#61] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(60) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] (61) BroadcastExchange Input [1]: [d_date_sk#5] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/simplified.txt index 4155cfa24..2fd04badf 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q70a/simplified.txt @@ -25,17 +25,17 @@ TakeOrderedAndProject [lochierarchy,s_state,rank_within_parent,total_sum,s_count BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_store_sk,ss_net_profit] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] InputAdapter ReusedExchange [d_date_sk] #4 @@ -43,9 +43,9 @@ TakeOrderedAndProject [lochierarchy,s_state,rank_within_parent,total_sum,s_count BroadcastExchange #5 WholeStageCodegen (7) BroadcastHashJoin [s_state,s_state] - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_county,s_state] InputAdapter BroadcastExchange #6 @@ -66,17 +66,17 @@ TakeOrderedAndProject [lochierarchy,s_state,rank_within_parent,total_sum,s_count BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_net_profit,ss_sold_date_sk,s_state] BroadcastHashJoin [ss_store_sk,s_store_sk] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_net_profit,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter BroadcastExchange #8 WholeStageCodegen (2) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_state] InputAdapter ReusedExchange [d_date_sk] #4 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/explain.txt index 68229396a..c88573838 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/explain.txt @@ -25,49 +25,49 @@ TakeOrderedAndProject (70) : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (14) : : : : : : : : :- * Project (9) : : : : : : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : : : : : : :- * Filter (3) - : : : : : : : : : : +- * ColumnarToRow (2) + : : : : : : : : : :- * ColumnarToRow (3) + : : : : : : : : : : +- CometFilter (2) : : : : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : : : : : : : +- BroadcastExchange (7) - : : : : : : : : : +- * Filter (6) - : : : : : : : : : +- * ColumnarToRow (5) + : : : : : : : : : +- * ColumnarToRow (6) + : : : : : : : : : +- CometFilter (5) : : : : : : : : : +- CometScan parquet spark_catalog.default.inventory (4) : : : : : : : : +- BroadcastExchange (13) - : : : : : : : : +- * Filter (12) - : : : : : : : : +- * ColumnarToRow (11) + : : : : : : : : +- * ColumnarToRow (12) + : : : : : : : : +- CometFilter (11) : : : : : : : : +- CometScan parquet spark_catalog.default.warehouse (10) : : : : : : : +- BroadcastExchange (19) - : : : : : : : +- * Filter (18) - : : : : : : : +- * ColumnarToRow (17) + : : : : : : : +- * ColumnarToRow (18) + : : : : : : : +- CometFilter (17) : : : : : : : +- CometScan parquet spark_catalog.default.item (16) : : : : : : +- BroadcastExchange (26) - : : : : : : +- * Project (25) - : : : : : : +- * Filter (24) - : : : : : : +- * ColumnarToRow (23) + : : : : : : +- * ColumnarToRow (25) + : : : : : : +- CometProject (24) + : : : : : : +- CometFilter (23) : : : : : : +- CometScan parquet spark_catalog.default.customer_demographics (22) : : : : : +- BroadcastExchange (33) - : : : : : +- * Project (32) - : : : : : +- * Filter (31) - : : : : : +- * ColumnarToRow (30) + : : : : : +- * ColumnarToRow (32) + : : : : : +- CometProject (31) + : : : : : +- CometFilter (30) : : : : : +- CometScan parquet spark_catalog.default.household_demographics (29) : : : : +- ReusedExchange (36) : : : +- BroadcastExchange (42) - : : : +- * Filter (41) - : : : +- * ColumnarToRow (40) + : : : +- * ColumnarToRow (41) + : : : +- CometFilter (40) : : : +- CometScan parquet spark_catalog.default.date_dim (39) : : +- BroadcastExchange (48) - : : +- * Filter (47) - : : +- * ColumnarToRow (46) + : : +- * ColumnarToRow (47) + : : +- CometFilter (46) : : +- CometScan parquet spark_catalog.default.date_dim (45) : +- BroadcastExchange (54) - : +- * Filter (53) - : +- * ColumnarToRow (52) + : +- * ColumnarToRow (53) + : +- CometFilter (52) : +- CometScan parquet spark_catalog.default.promotion (51) +- * Sort (64) +- Exchange (63) - +- * Project (62) - +- * Filter (61) - +- * ColumnarToRow (60) + +- * ColumnarToRow (62) + +- CometProject (61) + +- CometFilter (60) +- CometScan parquet spark_catalog.default.catalog_returns (59) @@ -79,12 +79,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#8), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_quantity), IsNotNull(cs_item_sk), IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_hdemo_sk), IsNotNull(cs_ship_date_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 10] +(2) CometFilter Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] +Condition : ((((isnotnull(cs_quantity#7) AND isnotnull(cs_item_sk#4)) AND isnotnull(cs_bill_cdemo_sk#2)) AND isnotnull(cs_bill_hdemo_sk#3)) AND isnotnull(cs_ship_date_sk#1)) -(3) Filter [codegen id : 10] +(3) ColumnarToRow [codegen id : 10] Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8] -Condition : ((((isnotnull(cs_quantity#7) AND isnotnull(cs_item_sk#4)) AND isnotnull(cs_bill_cdemo_sk#2)) AND isnotnull(cs_bill_hdemo_sk#3)) AND isnotnull(cs_ship_date_sk#1)) (4) Scan parquet spark_catalog.default.inventory Output [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] @@ -94,12 +94,12 @@ PartitionFilters: [isnotnull(inv_date_sk#13)] PushedFilters: [IsNotNull(inv_quantity_on_hand), IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] +Condition : ((isnotnull(inv_quantity_on_hand#12) AND isnotnull(inv_item_sk#10)) AND isnotnull(inv_warehouse_sk#11)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] -Condition : ((isnotnull(inv_quantity_on_hand#12) AND isnotnull(inv_item_sk#10)) AND isnotnull(inv_warehouse_sk#11)) (7) BroadcastExchange Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13] @@ -122,12 +122,12 @@ Location [not included in comparison]/{warehouse_dir}/warehouse] PushedFilters: [IsNotNull(w_warehouse_sk)] ReadSchema: struct -(11) ColumnarToRow [codegen id : 2] +(11) CometFilter Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] +Condition : isnotnull(w_warehouse_sk#14) -(12) Filter [codegen id : 2] +(12) ColumnarToRow [codegen id : 2] Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] -Condition : isnotnull(w_warehouse_sk#14) (13) BroadcastExchange Input [2]: [w_warehouse_sk#14, w_warehouse_name#15] @@ -150,12 +150,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 3] +(17) CometFilter Input [2]: [i_item_sk#16, i_item_desc#17] +Condition : isnotnull(i_item_sk#16) -(18) Filter [codegen id : 3] +(18) ColumnarToRow [codegen id : 3] Input [2]: [i_item_sk#16, i_item_desc#17] -Condition : isnotnull(i_item_sk#16) (19) BroadcastExchange Input [2]: [i_item_sk#16, i_item_desc#17] @@ -178,16 +178,16 @@ Location [not included in comparison]/{warehouse_dir}/customer_demographics] PushedFilters: [IsNotNull(cd_marital_status), EqualTo(cd_marital_status,M), IsNotNull(cd_demo_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 4] -Input [2]: [cd_demo_sk#18, cd_marital_status#19] - -(24) Filter [codegen id : 4] +(23) CometFilter Input [2]: [cd_demo_sk#18, cd_marital_status#19] Condition : ((isnotnull(cd_marital_status#19) AND (cd_marital_status#19 = M)) AND isnotnull(cd_demo_sk#18)) -(25) Project [codegen id : 4] -Output [1]: [cd_demo_sk#18] +(24) CometProject Input [2]: [cd_demo_sk#18, cd_marital_status#19] +Arguments: [cd_demo_sk#18], [cd_demo_sk#18] + +(25) ColumnarToRow [codegen id : 4] +Input [1]: [cd_demo_sk#18] (26) BroadcastExchange Input [1]: [cd_demo_sk#18] @@ -210,16 +210,16 @@ Location [not included in comparison]/{warehouse_dir}/household_demographics] PushedFilters: [IsNotNull(hd_buy_potential), EqualTo(hd_buy_potential,1001-5000 ), IsNotNull(hd_demo_sk)] ReadSchema: struct -(30) ColumnarToRow [codegen id : 5] -Input [2]: [hd_demo_sk#20, hd_buy_potential#21] - -(31) Filter [codegen id : 5] +(30) CometFilter Input [2]: [hd_demo_sk#20, hd_buy_potential#21] Condition : ((isnotnull(hd_buy_potential#21) AND (hd_buy_potential#21 = 1001-5000 )) AND isnotnull(hd_demo_sk#20)) -(32) Project [codegen id : 5] -Output [1]: [hd_demo_sk#20] +(31) CometProject Input [2]: [hd_demo_sk#20, hd_buy_potential#21] +Arguments: [hd_demo_sk#20], [hd_demo_sk#20] + +(32) ColumnarToRow [codegen id : 5] +Input [1]: [hd_demo_sk#20] (33) BroadcastExchange Input [1]: [hd_demo_sk#20] @@ -255,12 +255,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_week_seq), IsNotNull(d_date_sk)] ReadSchema: struct -(40) ColumnarToRow [codegen id : 7] +(40) CometFilter Input [2]: [d_date_sk#25, d_week_seq#26] +Condition : (isnotnull(d_week_seq#26) AND isnotnull(d_date_sk#25)) -(41) Filter [codegen id : 7] +(41) ColumnarToRow [codegen id : 7] Input [2]: [d_date_sk#25, d_week_seq#26] -Condition : (isnotnull(d_week_seq#26) AND isnotnull(d_date_sk#25)) (42) BroadcastExchange Input [2]: [d_date_sk#25, d_week_seq#26] @@ -283,12 +283,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), IsNotNull(d_date_sk)] ReadSchema: struct -(46) ColumnarToRow [codegen id : 8] +(46) CometFilter Input [2]: [d_date_sk#27, d_date#28] +Condition : (isnotnull(d_date#28) AND isnotnull(d_date_sk#27)) -(47) Filter [codegen id : 8] +(47) ColumnarToRow [codegen id : 8] Input [2]: [d_date_sk#27, d_date#28] -Condition : (isnotnull(d_date#28) AND isnotnull(d_date_sk#27)) (48) BroadcastExchange Input [2]: [d_date_sk#27, d_date#28] @@ -311,12 +311,12 @@ Location [not included in comparison]/{warehouse_dir}/promotion] PushedFilters: [IsNotNull(p_promo_sk)] ReadSchema: struct -(52) ColumnarToRow [codegen id : 9] +(52) CometFilter Input [1]: [p_promo_sk#29] +Condition : isnotnull(p_promo_sk#29) -(53) Filter [codegen id : 9] +(53) ColumnarToRow [codegen id : 9] Input [1]: [p_promo_sk#29] -Condition : isnotnull(p_promo_sk#29) (54) BroadcastExchange Input [1]: [p_promo_sk#29] @@ -347,16 +347,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] ReadSchema: struct -(60) ColumnarToRow [codegen id : 12] -Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] - -(61) Filter [codegen id : 12] +(60) CometFilter Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] Condition : (isnotnull(cr_item_sk#30) AND isnotnull(cr_order_number#31)) -(62) Project [codegen id : 12] -Output [2]: [cr_item_sk#30, cr_order_number#31] +(61) CometProject Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32] +Arguments: [cr_item_sk#30, cr_order_number#31], [cr_item_sk#30, cr_order_number#31] + +(62) ColumnarToRow [codegen id : 12] +Input [2]: [cr_item_sk#30, cr_order_number#31] (63) Exchange Input [2]: [cr_item_sk#30, cr_order_number#31] @@ -402,9 +402,9 @@ Arguments: 100, [total_cnt#38 DESC NULLS LAST, i_item_desc#17 ASC NULLS FIRST, w Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9 BroadcastExchange (75) -+- * Project (74) - +- * Filter (73) - +- * ColumnarToRow (72) ++- * ColumnarToRow (74) + +- CometProject (73) + +- CometFilter (72) +- CometScan parquet spark_catalog.default.date_dim (71) @@ -415,16 +415,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk), IsNotNull(d_week_seq), IsNotNull(d_date)] ReadSchema: struct -(72) ColumnarToRow [codegen id : 1] -Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] - -(73) Filter [codegen id : 1] +(72) CometFilter Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] Condition : ((((isnotnull(d_year#39) AND (d_year#39 = 2001)) AND isnotnull(d_date_sk#22)) AND isnotnull(d_week_seq#24)) AND isnotnull(d_date#23)) -(74) Project [codegen id : 1] -Output [3]: [d_date_sk#22, d_date#23, d_week_seq#24] +(73) CometProject Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39] +Arguments: [d_date_sk#22, d_date#23, d_week_seq#24], [d_date_sk#22, d_date#23, d_week_seq#24] + +(74) ColumnarToRow [codegen id : 1] +Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24] (75) BroadcastExchange Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt index 59e1279ae..17fc9dee7 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q72/simplified.txt @@ -31,77 +31,77 @@ TakeOrderedAndProject [total_cnt,i_item_desc,w_warehouse_name,d_week_seq,no_prom BroadcastHashJoin [inv_warehouse_sk,w_warehouse_sk] Project [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_sold_date_sk,inv_warehouse_sk,inv_date_sk] BroadcastHashJoin [cs_item_sk,inv_item_sk,inv_quantity_on_hand,cs_quantity] - Filter [cs_quantity,cs_item_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_ship_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_quantity,cs_item_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_ship_date_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_ship_date_sk,cs_bill_cdemo_sk,cs_bill_hdemo_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_quantity,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Project [d_date_sk,d_date,d_week_seq] - Filter [d_year,d_date_sk,d_week_seq,d_date] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk,d_date,d_week_seq] + CometFilter [d_year,d_date_sk,d_week_seq,d_date] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date,d_week_seq,d_year] InputAdapter BroadcastExchange #4 WholeStageCodegen (1) - Filter [inv_quantity_on_hand,inv_item_sk,inv_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [inv_quantity_on_hand,inv_item_sk,inv_warehouse_sk] CometScan parquet spark_catalog.default.inventory [inv_item_sk,inv_warehouse_sk,inv_quantity_on_hand,inv_date_sk] InputAdapter BroadcastExchange #5 WholeStageCodegen (2) - Filter [w_warehouse_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [w_warehouse_sk] CometScan parquet spark_catalog.default.warehouse [w_warehouse_sk,w_warehouse_name] InputAdapter BroadcastExchange #6 WholeStageCodegen (3) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_desc] InputAdapter BroadcastExchange #7 WholeStageCodegen (4) - Project [cd_demo_sk] - Filter [cd_marital_status,cd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cd_demo_sk] + CometFilter [cd_marital_status,cd_demo_sk] CometScan parquet spark_catalog.default.customer_demographics [cd_demo_sk,cd_marital_status] InputAdapter BroadcastExchange #8 WholeStageCodegen (5) - Project [hd_demo_sk] - Filter [hd_buy_potential,hd_demo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [hd_demo_sk] + CometFilter [hd_buy_potential,hd_demo_sk] CometScan parquet spark_catalog.default.household_demographics [hd_demo_sk,hd_buy_potential] InputAdapter ReusedExchange [d_date_sk,d_date,d_week_seq] #3 InputAdapter BroadcastExchange #9 WholeStageCodegen (7) - Filter [d_week_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_week_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_week_seq] InputAdapter BroadcastExchange #10 WholeStageCodegen (8) - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #11 WholeStageCodegen (9) - Filter [p_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [p_promo_sk] CometScan parquet spark_catalog.default.promotion [p_promo_sk] InputAdapter WholeStageCodegen (13) @@ -109,8 +109,8 @@ TakeOrderedAndProject [total_cnt,i_item_desc,w_warehouse_name,d_week_seq,no_prom InputAdapter Exchange [cr_item_sk,cr_order_number] #12 WholeStageCodegen (12) - Project [cr_item_sk,cr_order_number] - Filter [cr_item_sk,cr_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number] + CometFilter [cr_item_sk,cr_order_number] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt index a2f00f500..ad8c33ca1 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/explain.txt @@ -13,12 +13,12 @@ TakeOrderedAndProject (71) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (9) : : : : +- * BroadcastHashJoin Inner BuildRight (8) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.customer (1) : : : : +- BroadcastExchange (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.store_sales (4) : : : +- ReusedExchange (10) : : +- BroadcastExchange (32) @@ -29,12 +29,12 @@ TakeOrderedAndProject (71) : : +- * BroadcastHashJoin Inner BuildRight (27) : : :- * Project (25) : : : +- * BroadcastHashJoin Inner BuildRight (24) - : : : :- * Filter (19) - : : : : +- * ColumnarToRow (18) + : : : :- * ColumnarToRow (19) + : : : : +- CometFilter (18) : : : : +- CometScan parquet spark_catalog.default.customer (17) : : : +- BroadcastExchange (23) - : : : +- * Filter (22) - : : : +- * ColumnarToRow (21) + : : : +- * ColumnarToRow (22) + : : : +- CometFilter (21) : : : +- CometScan parquet spark_catalog.default.store_sales (20) : : +- ReusedExchange (26) : +- BroadcastExchange (50) @@ -46,12 +46,12 @@ TakeOrderedAndProject (71) : +- * BroadcastHashJoin Inner BuildRight (44) : :- * Project (42) : : +- * BroadcastHashJoin Inner BuildRight (41) - : : :- * Filter (36) - : : : +- * ColumnarToRow (35) + : : :- * ColumnarToRow (36) + : : : +- CometFilter (35) : : : +- CometScan parquet spark_catalog.default.customer (34) : : +- BroadcastExchange (40) - : : +- * Filter (39) - : : +- * ColumnarToRow (38) + : : +- * ColumnarToRow (39) + : : +- CometFilter (38) : : +- CometScan parquet spark_catalog.default.web_sales (37) : +- ReusedExchange (43) +- BroadcastExchange (68) @@ -62,12 +62,12 @@ TakeOrderedAndProject (71) +- * BroadcastHashJoin Inner BuildRight (63) :- * Project (61) : +- * BroadcastHashJoin Inner BuildRight (60) - : :- * Filter (55) - : : +- * ColumnarToRow (54) + : :- * ColumnarToRow (55) + : : +- CometFilter (54) : : +- CometScan parquet spark_catalog.default.customer (53) : +- BroadcastExchange (59) - : +- * Filter (58) - : +- * ColumnarToRow (57) + : +- * ColumnarToRow (58) + : +- CometFilter (57) : +- CometScan parquet spark_catalog.default.web_sales (56) +- ReusedExchange (62) @@ -79,12 +79,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] +Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [4]: [c_customer_sk#1, c_customer_id#2, c_first_name#3, c_last_name#4] -Condition : (isnotnull(c_customer_sk#1) AND isnotnull(c_customer_id#2)) (4) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] @@ -94,12 +94,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] +Condition : isnotnull(ss_customer_sk#5) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] -Condition : isnotnull(ss_customer_sk#5) (7) BroadcastExchange Input [3]: [ss_customer_sk#5, ss_net_paid#6, ss_sold_date_sk#7] @@ -157,12 +157,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 6] +(18) CometFilter Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] +Condition : (isnotnull(c_customer_sk#16) AND isnotnull(c_customer_id#17)) -(19) Filter [codegen id : 6] +(19) ColumnarToRow [codegen id : 6] Input [4]: [c_customer_sk#16, c_customer_id#17, c_first_name#18, c_last_name#19] -Condition : (isnotnull(c_customer_sk#16) AND isnotnull(c_customer_id#17)) (20) Scan parquet spark_catalog.default.store_sales Output [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] @@ -172,12 +172,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#22), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_customer_sk)] ReadSchema: struct -(21) ColumnarToRow [codegen id : 4] +(21) CometFilter Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] +Condition : isnotnull(ss_customer_sk#20) -(22) Filter [codegen id : 4] +(22) ColumnarToRow [codegen id : 4] Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] -Condition : isnotnull(ss_customer_sk#20) (23) BroadcastExchange Input [3]: [ss_customer_sk#20, ss_net_paid#21, ss_sold_date_sk#22] @@ -241,12 +241,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(35) ColumnarToRow [codegen id : 10] +(35) CometFilter Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] +Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_customer_id#33)) -(36) Filter [codegen id : 10] +(36) ColumnarToRow [codegen id : 10] Input [4]: [c_customer_sk#32, c_customer_id#33, c_first_name#34, c_last_name#35] -Condition : (isnotnull(c_customer_sk#32) AND isnotnull(c_customer_id#33)) (37) Scan parquet spark_catalog.default.web_sales Output [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] @@ -256,12 +256,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#38), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(38) ColumnarToRow [codegen id : 8] +(38) CometFilter Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] +Condition : isnotnull(ws_bill_customer_sk#36) -(39) Filter [codegen id : 8] +(39) ColumnarToRow [codegen id : 8] Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] -Condition : isnotnull(ws_bill_customer_sk#36) (40) BroadcastExchange Input [3]: [ws_bill_customer_sk#36, ws_net_paid#37, ws_sold_date_sk#38] @@ -333,12 +333,12 @@ Location [not included in comparison]/{warehouse_dir}/customer] PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_customer_id)] ReadSchema: struct -(54) ColumnarToRow [codegen id : 14] +(54) CometFilter Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] +Condition : (isnotnull(c_customer_sk#47) AND isnotnull(c_customer_id#48)) -(55) Filter [codegen id : 14] +(55) ColumnarToRow [codegen id : 14] Input [4]: [c_customer_sk#47, c_customer_id#48, c_first_name#49, c_last_name#50] -Condition : (isnotnull(c_customer_sk#47) AND isnotnull(c_customer_id#48)) (56) Scan parquet spark_catalog.default.web_sales Output [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] @@ -348,12 +348,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#53), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(57) ColumnarToRow [codegen id : 12] +(57) CometFilter Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] +Condition : isnotnull(ws_bill_customer_sk#51) -(58) Filter [codegen id : 12] +(58) ColumnarToRow [codegen id : 12] Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] -Condition : isnotnull(ws_bill_customer_sk#51) (59) BroadcastExchange Input [3]: [ws_bill_customer_sk#51, ws_net_paid#52, ws_sold_date_sk#53] @@ -422,8 +422,8 @@ Arguments: 100, [customer_first_name#29 ASC NULLS FIRST, customer_id#28 ASC NULL Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (75) -+- * Filter (74) - +- * ColumnarToRow (73) ++- * ColumnarToRow (74) + +- CometFilter (73) +- CometScan parquet spark_catalog.default.date_dim (72) @@ -434,12 +434,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] ReadSchema: struct -(73) ColumnarToRow [codegen id : 1] +(73) CometFilter Input [2]: [d_date_sk#9, d_year#10] +Condition : (((isnotnull(d_year#10) AND (d_year#10 = 2001)) AND d_year#10 IN (2001,2002)) AND isnotnull(d_date_sk#9)) -(74) Filter [codegen id : 1] +(74) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#9, d_year#10] -Condition : (((isnotnull(d_year#10) AND (d_year#10 = 2001)) AND d_year#10 IN (2001,2002)) AND isnotnull(d_date_sk#9)) (75) BroadcastExchange Input [2]: [d_date_sk#9, d_year#10] @@ -447,8 +447,8 @@ Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint) Subquery:2 Hosting operator id = 20 Hosting Expression = ss_sold_date_sk#22 IN dynamicpruning#23 BroadcastExchange (79) -+- * Filter (78) - +- * ColumnarToRow (77) ++- * ColumnarToRow (78) + +- CometFilter (77) +- CometScan parquet spark_catalog.default.date_dim (76) @@ -459,12 +459,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), In(d_year, [2001,2002]), IsNotNull(d_date_sk)] ReadSchema: struct -(77) ColumnarToRow [codegen id : 1] +(77) CometFilter Input [2]: [d_date_sk#24, d_year#25] +Condition : (((isnotnull(d_year#25) AND (d_year#25 = 2002)) AND d_year#25 IN (2001,2002)) AND isnotnull(d_date_sk#24)) -(78) Filter [codegen id : 1] +(78) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#24, d_year#25] -Condition : (((isnotnull(d_year#25) AND (d_year#25 = 2002)) AND d_year#25 IN (2001,2002)) AND isnotnull(d_date_sk#24)) (79) BroadcastExchange Input [2]: [d_date_sk#24, d_year#25] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt index 9d6161f56..26989b0c0 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q74/simplified.txt @@ -15,23 +15,23 @@ TakeOrderedAndProject [customer_first_name,customer_id,customer_last_name] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] InputAdapter BroadcastExchange #2 WholeStageCodegen (1) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #3 @@ -47,23 +47,23 @@ TakeOrderedAndProject [customer_first_name,customer_id,customer_last_name] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,ss_net_paid,ss_sold_date_sk] BroadcastHashJoin [c_customer_sk,ss_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] InputAdapter BroadcastExchange #6 WholeStageCodegen (4) - Filter [ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_customer_sk,ss_net_paid,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #7 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [d_date_sk,d_year] #7 @@ -80,16 +80,16 @@ TakeOrderedAndProject [customer_first_name,customer_id,customer_last_name] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] InputAdapter BroadcastExchange #10 WholeStageCodegen (8) - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -106,16 +106,16 @@ TakeOrderedAndProject [customer_first_name,customer_id,customer_last_name] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [c_customer_id,c_first_name,c_last_name,ws_net_paid,ws_sold_date_sk] BroadcastHashJoin [c_customer_sk,ws_bill_customer_sk] - Filter [c_customer_sk,c_customer_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [c_customer_sk,c_customer_id] CometScan parquet spark_catalog.default.customer [c_customer_sk,c_customer_id,c_first_name,c_last_name] InputAdapter BroadcastExchange #13 WholeStageCodegen (12) - Filter [ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_bill_customer_sk,ws_net_paid,ws_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt index e52462afa..5c8480a96 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/explain.txt @@ -20,20 +20,20 @@ TakeOrderedAndProject (129) : : : +- * BroadcastHashJoin Inner BuildRight (12) : : : :- * Project (10) : : : : +- * BroadcastHashJoin Inner BuildRight (9) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (1) : : : : +- BroadcastExchange (8) - : : : : +- * Project (7) - : : : : +- * Filter (6) - : : : : +- * ColumnarToRow (5) + : : : : +- * ColumnarToRow (7) + : : : : +- CometProject (6) + : : : : +- CometFilter (5) : : : : +- CometScan parquet spark_catalog.default.item (4) : : : +- ReusedExchange (11) : : +- * Sort (21) : : +- Exchange (20) - : : +- * Project (19) - : : +- * Filter (18) - : : +- * ColumnarToRow (17) + : : +- * ColumnarToRow (19) + : : +- CometProject (18) + : : +- CometFilter (17) : : +- CometScan parquet spark_catalog.default.catalog_returns (16) : :- * Project (42) : : +- * SortMergeJoin LeftOuter (41) @@ -43,16 +43,16 @@ TakeOrderedAndProject (129) : : : +- * BroadcastHashJoin Inner BuildRight (31) : : : :- * Project (29) : : : : +- * BroadcastHashJoin Inner BuildRight (28) - : : : : :- * Filter (26) - : : : : : +- * ColumnarToRow (25) + : : : : :- * ColumnarToRow (26) + : : : : : +- CometFilter (25) : : : : : +- CometScan parquet spark_catalog.default.store_sales (24) : : : : +- ReusedExchange (27) : : : +- ReusedExchange (30) : : +- * Sort (40) : : +- Exchange (39) - : : +- * Project (38) - : : +- * Filter (37) - : : +- * ColumnarToRow (36) + : : +- * ColumnarToRow (38) + : : +- CometProject (37) + : : +- CometFilter (36) : : +- CometScan parquet spark_catalog.default.store_returns (35) : +- * Project (61) : +- * SortMergeJoin LeftOuter (60) @@ -62,16 +62,16 @@ TakeOrderedAndProject (129) : : +- * BroadcastHashJoin Inner BuildRight (50) : : :- * Project (48) : : : +- * BroadcastHashJoin Inner BuildRight (47) - : : : :- * Filter (45) - : : : : +- * ColumnarToRow (44) + : : : :- * ColumnarToRow (45) + : : : : +- CometFilter (44) : : : : +- CometScan parquet spark_catalog.default.web_sales (43) : : : +- ReusedExchange (46) : : +- ReusedExchange (49) : +- * Sort (59) : +- Exchange (58) - : +- * Project (57) - : +- * Filter (56) - : +- * ColumnarToRow (55) + : +- * ColumnarToRow (57) + : +- CometProject (56) + : +- CometFilter (55) : +- CometScan parquet spark_catalog.default.web_returns (54) +- * Sort (126) +- Exchange (125) @@ -91,8 +91,8 @@ TakeOrderedAndProject (129) : : +- * BroadcastHashJoin Inner BuildRight (79) : : :- * Project (77) : : : +- * BroadcastHashJoin Inner BuildRight (76) - : : : :- * Filter (74) - : : : : +- * ColumnarToRow (73) + : : : :- * ColumnarToRow (74) + : : : : +- CometFilter (73) : : : : +- CometScan parquet spark_catalog.default.catalog_sales (72) : : : +- ReusedExchange (75) : : +- ReusedExchange (78) @@ -106,8 +106,8 @@ TakeOrderedAndProject (129) : : +- * BroadcastHashJoin Inner BuildRight (94) : : :- * Project (92) : : : +- * BroadcastHashJoin Inner BuildRight (91) - : : : :- * Filter (89) - : : : : +- * ColumnarToRow (88) + : : : :- * ColumnarToRow (89) + : : : : +- CometFilter (88) : : : : +- CometScan parquet spark_catalog.default.store_sales (87) : : : +- ReusedExchange (90) : : +- ReusedExchange (93) @@ -121,8 +121,8 @@ TakeOrderedAndProject (129) : +- * BroadcastHashJoin Inner BuildRight (109) : :- * Project (107) : : +- * BroadcastHashJoin Inner BuildRight (106) - : : :- * Filter (104) - : : : +- * ColumnarToRow (103) + : : :- * ColumnarToRow (104) + : : : +- CometFilter (103) : : : +- CometScan parquet spark_catalog.default.web_sales (102) : : +- ReusedExchange (105) : +- ReusedExchange (108) @@ -138,12 +138,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#5), dynamicpruningexpression(cs_sol PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] +Condition : isnotnull(cs_item_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [5]: [cs_item_sk#1, cs_order_number#2, cs_quantity#3, cs_ext_sales_price#4, cs_sold_date_sk#5] -Condition : isnotnull(cs_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] @@ -152,16 +152,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_category), EqualTo(i_category,Books ), IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id), IsNotNull(i_manufact_id)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] -Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] - -(6) Filter [codegen id : 1] +(5) CometFilter Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] Condition : ((((((isnotnull(i_category#11) AND (i_category#11 = Books )) AND isnotnull(i_item_sk#7)) AND isnotnull(i_brand_id#8)) AND isnotnull(i_class_id#9)) AND isnotnull(i_category_id#10)) AND isnotnull(i_manufact_id#12)) -(7) Project [codegen id : 1] -Output [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] +(6) CometProject Input [6]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_category#11, i_manufact_id#12] +Arguments: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12], [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] + +(7) ColumnarToRow [codegen id : 1] +Input [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] (8) BroadcastExchange Input [5]: [i_item_sk#7, i_brand_id#8, i_class_id#9, i_category_id#10, i_manufact_id#12] @@ -205,16 +205,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 5] -Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] - -(18) Filter [codegen id : 5] +(17) CometFilter Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] Condition : (isnotnull(cr_order_number#16) AND isnotnull(cr_item_sk#15)) -(19) Project [codegen id : 5] -Output [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] +(18) CometProject Input [5]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18, cr_returned_date_sk#19] +Arguments: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18], [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] + +(19) ColumnarToRow [codegen id : 5] +Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] (20) Exchange Input [4]: [cr_item_sk#15, cr_order_number#16, cr_return_quantity#17, cr_return_amount#18] @@ -242,12 +242,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#26), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(25) ColumnarToRow [codegen id : 10] +(25) CometFilter Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] +Condition : isnotnull(ss_item_sk#22) -(26) Filter [codegen id : 10] +(26) ColumnarToRow [codegen id : 10] Input [5]: [ss_item_sk#22, ss_ticket_number#23, ss_quantity#24, ss_ext_sales_price#25, ss_sold_date_sk#26] -Condition : isnotnull(ss_item_sk#22) (27) ReusedExchange [Reuses operator id: 8] Output [5]: [i_item_sk#28, i_brand_id#29, i_class_id#30, i_category_id#31, i_manufact_id#32] @@ -290,16 +290,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] ReadSchema: struct -(36) ColumnarToRow [codegen id : 12] -Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] - -(37) Filter [codegen id : 12] +(36) CometFilter Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] Condition : (isnotnull(sr_ticket_number#36) AND isnotnull(sr_item_sk#35)) -(38) Project [codegen id : 12] -Output [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] +(37) CometProject Input [5]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38, sr_returned_date_sk#39] +Arguments: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38], [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] + +(38) ColumnarToRow [codegen id : 12] +Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] (39) Exchange Input [4]: [sr_item_sk#35, sr_ticket_number#36, sr_return_quantity#37, sr_return_amt#38] @@ -327,12 +327,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#46), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(44) ColumnarToRow [codegen id : 17] +(44) CometFilter Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] +Condition : isnotnull(ws_item_sk#42) -(45) Filter [codegen id : 17] +(45) ColumnarToRow [codegen id : 17] Input [5]: [ws_item_sk#42, ws_order_number#43, ws_quantity#44, ws_ext_sales_price#45, ws_sold_date_sk#46] -Condition : isnotnull(ws_item_sk#42) (46) ReusedExchange [Reuses operator id: 8] Output [5]: [i_item_sk#48, i_brand_id#49, i_class_id#50, i_category_id#51, i_manufact_id#52] @@ -375,16 +375,16 @@ Location [not included in comparison]/{warehouse_dir}/web_returns] PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] ReadSchema: struct -(55) ColumnarToRow [codegen id : 19] -Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] - -(56) Filter [codegen id : 19] +(55) CometFilter Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] Condition : (isnotnull(wr_order_number#56) AND isnotnull(wr_item_sk#55)) -(57) Project [codegen id : 19] -Output [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] +(56) CometProject Input [5]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58, wr_returned_date_sk#59] +Arguments: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58], [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] + +(57) ColumnarToRow [codegen id : 19] +Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] (58) Exchange Input [4]: [wr_item_sk#55, wr_order_number#56, wr_return_quantity#57, wr_return_amt#58] @@ -462,12 +462,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#74), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk)] ReadSchema: struct -(73) ColumnarToRow [codegen id : 28] +(73) CometFilter Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] +Condition : isnotnull(cs_item_sk#70) -(74) Filter [codegen id : 28] +(74) ColumnarToRow [codegen id : 28] Input [5]: [cs_item_sk#70, cs_order_number#71, cs_quantity#72, cs_ext_sales_price#73, cs_sold_date_sk#74] -Condition : isnotnull(cs_item_sk#70) (75) ReusedExchange [Reuses operator id: 8] Output [5]: [i_item_sk#76, i_brand_id#77, i_class_id#78, i_category_id#79, i_manufact_id#80] @@ -528,12 +528,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#93), dynamicpruningexpression(ss_so PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(88) ColumnarToRow [codegen id : 35] +(88) CometFilter Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] +Condition : isnotnull(ss_item_sk#89) -(89) Filter [codegen id : 35] +(89) ColumnarToRow [codegen id : 35] Input [5]: [ss_item_sk#89, ss_ticket_number#90, ss_quantity#91, ss_ext_sales_price#92, ss_sold_date_sk#93] -Condition : isnotnull(ss_item_sk#89) (90) ReusedExchange [Reuses operator id: 8] Output [5]: [i_item_sk#95, i_brand_id#96, i_class_id#97, i_category_id#98, i_manufact_id#99] @@ -594,12 +594,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#112), dynamicpruningexpression(ws_s PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(103) ColumnarToRow [codegen id : 42] +(103) CometFilter Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] +Condition : isnotnull(ws_item_sk#108) -(104) Filter [codegen id : 42] +(104) ColumnarToRow [codegen id : 42] Input [5]: [ws_item_sk#108, ws_order_number#109, ws_quantity#110, ws_ext_sales_price#111, ws_sold_date_sk#112] -Condition : isnotnull(ws_item_sk#108) (105) ReusedExchange [Reuses operator id: 8] Output [5]: [i_item_sk#114, i_brand_id#115, i_class_id#116, i_category_id#117, i_manufact_id#118] @@ -720,8 +720,8 @@ Arguments: 100, [sales_cnt_diff#137 ASC NULLS FIRST, sales_amt_diff#138 ASC NULL Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#5 IN dynamicpruning#6 BroadcastExchange (133) -+- * Filter (132) - +- * ColumnarToRow (131) ++- * ColumnarToRow (132) + +- CometFilter (131) +- CometScan parquet spark_catalog.default.date_dim (130) @@ -732,12 +732,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)] ReadSchema: struct -(131) ColumnarToRow [codegen id : 1] +(131) CometFilter Input [2]: [d_date_sk#13, d_year#14] +Condition : ((isnotnull(d_year#14) AND (d_year#14 = 2002)) AND isnotnull(d_date_sk#13)) -(132) Filter [codegen id : 1] +(132) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#13, d_year#14] -Condition : ((isnotnull(d_year#14) AND (d_year#14 = 2002)) AND isnotnull(d_date_sk#13)) (133) BroadcastExchange Input [2]: [d_date_sk#13, d_year#14] @@ -749,8 +749,8 @@ Subquery:3 Hosting operator id = 43 Hosting Expression = ws_sold_date_sk#46 IN d Subquery:4 Hosting operator id = 72 Hosting Expression = cs_sold_date_sk#74 IN dynamicpruning#75 BroadcastExchange (137) -+- * Filter (136) - +- * ColumnarToRow (135) ++- * ColumnarToRow (136) + +- CometFilter (135) +- CometScan parquet spark_catalog.default.date_dim (134) @@ -761,12 +761,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)] ReadSchema: struct -(135) ColumnarToRow [codegen id : 1] +(135) CometFilter Input [2]: [d_date_sk#81, d_year#82] +Condition : ((isnotnull(d_year#82) AND (d_year#82 = 2001)) AND isnotnull(d_date_sk#81)) -(136) Filter [codegen id : 1] +(136) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#81, d_year#82] -Condition : ((isnotnull(d_year#82) AND (d_year#82 = 2001)) AND isnotnull(d_date_sk#81)) (137) BroadcastExchange Input [2]: [d_date_sk#81, d_year#82] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt index 3a7ec65a0..9939b2fe2 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q75/simplified.txt @@ -34,24 +34,24 @@ TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #5 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter BroadcastExchange #6 WholeStageCodegen (1) - Project [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] - Filter [i_category,i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] + CometFilter [i_category,i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] CometScan parquet spark_catalog.default.item [i_item_sk,i_brand_id,i_class_id,i_category_id,i_category,i_manufact_id] InputAdapter ReusedExchange [d_date_sk,d_year] #5 @@ -61,10 +61,10 @@ TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i InputAdapter Exchange [cr_order_number,cr_item_sk] #7 WholeStageCodegen (5) - Project [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] - Filter [cr_order_number,cr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount] + CometFilter [cr_order_number,cr_item_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_quantity,cr_return_amount,cr_returned_date_sk] WholeStageCodegen (14) Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ss_quantity,sr_return_quantity,ss_ext_sales_price,sr_return_amt] @@ -79,9 +79,9 @@ TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -94,10 +94,10 @@ TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i InputAdapter Exchange [sr_ticket_number,sr_item_sk] #9 WholeStageCodegen (12) - Project [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] - Filter [sr_ticket_number,sr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt] + CometFilter [sr_ticket_number,sr_item_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_quantity,sr_return_amt,sr_returned_date_sk] WholeStageCodegen (21) Project [d_year,i_brand_id,i_class_id,i_category_id,i_manufact_id,ws_quantity,wr_return_quantity,ws_ext_sales_price,wr_return_amt] @@ -112,9 +112,9 @@ TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -127,10 +127,10 @@ TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i InputAdapter Exchange [wr_order_number,wr_item_sk] #11 WholeStageCodegen (19) - Project [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] - Filter [wr_order_number,wr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt] + CometFilter [wr_order_number,wr_item_sk] CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_quantity,wr_return_amt,wr_returned_date_sk] InputAdapter WholeStageCodegen (50) @@ -164,16 +164,16 @@ TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i BroadcastHashJoin [cs_sold_date_sk,d_date_sk] Project [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [cs_item_sk,i_item_sk] - Filter [cs_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_item_sk,cs_order_number,cs_quantity,cs_ext_sales_price,cs_sold_date_sk] SubqueryBroadcast [d_date_sk] #2 BroadcastExchange #16 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter ReusedExchange [i_item_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] #6 @@ -197,9 +197,9 @@ TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ticket_number,ss_quantity,ss_ext_sales_price,ss_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter @@ -224,9 +224,9 @@ TakeOrderedAndProject [sales_cnt_diff,sales_amt_diff,prev_year,year,i_brand_id,i BroadcastHashJoin [ws_sold_date_sk,d_date_sk] Project [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk,i_brand_id,i_class_id,i_category_id,i_manufact_id] BroadcastHashJoin [ws_item_sk,i_item_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_order_number,ws_quantity,ws_ext_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #2 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt index ec9c0ac47..5c1865267 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/explain.txt @@ -17,13 +17,13 @@ TakeOrderedAndProject (98) : : : +- * BroadcastHashJoin Inner BuildRight (11) : : : :- * Project (6) : : : : +- * BroadcastHashJoin Inner BuildRight (5) - : : : : :- * Filter (3) - : : : : : +- * ColumnarToRow (2) + : : : : :- * ColumnarToRow (3) + : : : : : +- CometFilter (2) : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : +- ReusedExchange (4) : : : +- BroadcastExchange (10) - : : : +- * Filter (9) - : : : +- * ColumnarToRow (8) + : : : +- * ColumnarToRow (9) + : : : +- CometFilter (8) : : : +- CometScan parquet spark_catalog.default.store (7) : : +- BroadcastExchange (28) : : +- * HashAggregate (27) @@ -33,8 +33,8 @@ TakeOrderedAndProject (98) : : +- * BroadcastHashJoin Inner BuildRight (23) : : :- * Project (21) : : : +- * BroadcastHashJoin Inner BuildRight (20) - : : : :- * Filter (18) - : : : : +- * ColumnarToRow (17) + : : : :- * ColumnarToRow (18) + : : : : +- CometFilter (17) : : : : +- CometScan parquet spark_catalog.default.store_returns (16) : : : +- ReusedExchange (19) : : +- ReusedExchange (22) @@ -66,13 +66,13 @@ TakeOrderedAndProject (98) : : +- * BroadcastHashJoin Inner BuildRight (60) : : :- * Project (55) : : : +- * BroadcastHashJoin Inner BuildRight (54) - : : : :- * Filter (52) - : : : : +- * ColumnarToRow (51) + : : : :- * ColumnarToRow (52) + : : : : +- CometFilter (51) : : : : +- CometScan parquet spark_catalog.default.web_sales (50) : : : +- ReusedExchange (53) : : +- BroadcastExchange (59) - : : +- * Filter (58) - : : +- * ColumnarToRow (57) + : : +- * ColumnarToRow (58) + : : +- CometFilter (57) : : +- CometScan parquet spark_catalog.default.web_page (56) : +- BroadcastExchange (77) : +- * HashAggregate (76) @@ -82,8 +82,8 @@ TakeOrderedAndProject (98) : +- * BroadcastHashJoin Inner BuildRight (72) : :- * Project (70) : : +- * BroadcastHashJoin Inner BuildRight (69) - : : :- * Filter (67) - : : : +- * ColumnarToRow (66) + : : :- * ColumnarToRow (67) + : : : +- CometFilter (66) : : : +- CometScan parquet spark_catalog.default.web_returns (65) : : +- ReusedExchange (68) : +- ReusedExchange (71) @@ -107,12 +107,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] +Condition : isnotnull(ss_store_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4] -Condition : isnotnull(ss_store_sk#1) (4) ReusedExchange [Reuses operator id: 103] Output [1]: [d_date_sk#6] @@ -134,12 +134,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [1]: [s_store_sk#7] +Condition : isnotnull(s_store_sk#7) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [1]: [s_store_sk#7] -Condition : isnotnull(s_store_sk#7) (10) BroadcastExchange Input [1]: [s_store_sk#7] @@ -181,12 +181,12 @@ PartitionFilters: [isnotnull(sr_returned_date_sk#19), dynamicpruningexpression(s PushedFilters: [IsNotNull(sr_store_sk)] ReadSchema: struct -(17) ColumnarToRow [codegen id : 6] +(17) CometFilter Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] +Condition : isnotnull(sr_store_sk#16) -(18) Filter [codegen id : 6] +(18) ColumnarToRow [codegen id : 6] Input [4]: [sr_store_sk#16, sr_return_amt#17, sr_net_loss#18, sr_returned_date_sk#19] -Condition : isnotnull(sr_store_sk#16) (19) ReusedExchange [Reuses operator id: 103] Output [1]: [d_date_sk#21] @@ -348,12 +348,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#68), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_web_page_sk)] ReadSchema: struct -(51) ColumnarToRow [codegen id : 17] +(51) CometFilter Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] +Condition : isnotnull(ws_web_page_sk#65) -(52) Filter [codegen id : 17] +(52) ColumnarToRow [codegen id : 17] Input [4]: [ws_web_page_sk#65, ws_ext_sales_price#66, ws_net_profit#67, ws_sold_date_sk#68] -Condition : isnotnull(ws_web_page_sk#65) (53) ReusedExchange [Reuses operator id: 103] Output [1]: [d_date_sk#70] @@ -375,12 +375,12 @@ Location [not included in comparison]/{warehouse_dir}/web_page] PushedFilters: [IsNotNull(wp_web_page_sk)] ReadSchema: struct -(57) ColumnarToRow [codegen id : 16] +(57) CometFilter Input [1]: [wp_web_page_sk#71] +Condition : isnotnull(wp_web_page_sk#71) -(58) Filter [codegen id : 16] +(58) ColumnarToRow [codegen id : 16] Input [1]: [wp_web_page_sk#71] -Condition : isnotnull(wp_web_page_sk#71) (59) BroadcastExchange Input [1]: [wp_web_page_sk#71] @@ -422,12 +422,12 @@ PartitionFilters: [isnotnull(wr_returned_date_sk#83), dynamicpruningexpression(w PushedFilters: [IsNotNull(wr_web_page_sk)] ReadSchema: struct -(66) ColumnarToRow [codegen id : 20] +(66) CometFilter Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] +Condition : isnotnull(wr_web_page_sk#80) -(67) Filter [codegen id : 20] +(67) ColumnarToRow [codegen id : 20] Input [4]: [wr_web_page_sk#80, wr_return_amt#81, wr_net_loss#82, wr_returned_date_sk#83] -Condition : isnotnull(wr_web_page_sk#80) (68) ReusedExchange [Reuses operator id: 103] Output [1]: [d_date_sk#85] @@ -591,9 +591,9 @@ Arguments: 100, [channel#31 ASC NULLS FIRST, id#32 ASC NULLS FIRST], [channel#31 Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5 BroadcastExchange (103) -+- * Project (102) - +- * Filter (101) - +- * ColumnarToRow (100) ++- * ColumnarToRow (102) + +- CometProject (101) + +- CometFilter (100) +- CometScan parquet spark_catalog.default.date_dim (99) @@ -604,16 +604,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1998-08-04), LessThanOrEqual(d_date,1998-09-03), IsNotNull(d_date_sk)] ReadSchema: struct -(100) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#6, d_date#184] - -(101) Filter [codegen id : 1] +(100) CometFilter Input [2]: [d_date_sk#6, d_date#184] Condition : (((isnotnull(d_date#184) AND (d_date#184 >= 1998-08-04)) AND (d_date#184 <= 1998-09-03)) AND isnotnull(d_date_sk#6)) -(102) Project [codegen id : 1] -Output [1]: [d_date_sk#6] +(101) CometProject Input [2]: [d_date_sk#6, d_date#184] +Arguments: [d_date_sk#6], [d_date_sk#6] + +(102) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#6] (103) BroadcastExchange Input [1]: [d_date_sk#6] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt index 9b7a2b9ef..670a7e6c3 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q77a/simplified.txt @@ -27,26 +27,26 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] BroadcastHashJoin [ss_store_sk,s_store_sk] Project [ss_store_sk,ss_ext_sales_price,ss_net_profit] BroadcastHashJoin [ss_sold_date_sk,d_date_sk] - Filter [ss_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk] CometScan parquet spark_catalog.default.store_sales [ss_store_sk,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (2) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk] InputAdapter BroadcastExchange #6 @@ -60,9 +60,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] BroadcastHashJoin [sr_store_sk,s_store_sk] Project [sr_store_sk,sr_return_amt,sr_net_loss] BroadcastHashJoin [sr_returned_date_sk,d_date_sk] - Filter [sr_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [sr_store_sk] CometScan parquet spark_catalog.default.store_returns [sr_store_sk,sr_return_amt,sr_net_loss,sr_returned_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -113,9 +113,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] BroadcastHashJoin [ws_web_page_sk,wp_web_page_sk] Project [ws_web_page_sk,ws_ext_sales_price,ws_net_profit] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_web_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_web_page_sk] CometScan parquet spark_catalog.default.web_sales [ws_web_page_sk,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -123,9 +123,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter BroadcastExchange #12 WholeStageCodegen (16) - Filter [wp_web_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [wp_web_page_sk] CometScan parquet spark_catalog.default.web_page [wp_web_page_sk] InputAdapter BroadcastExchange #13 @@ -139,9 +139,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] BroadcastHashJoin [wr_web_page_sk,wp_web_page_sk] Project [wr_web_page_sk,wr_return_amt,wr_net_loss] BroadcastHashJoin [wr_returned_date_sk,d_date_sk] - Filter [wr_web_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [wr_web_page_sk] CometScan parquet spark_catalog.default.web_returns [wr_web_page_sk,wr_return_amt,wr_net_loss,wr_returned_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt index 76c968e91..c7ee5b1c9 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/explain.txt @@ -15,14 +15,14 @@ TakeOrderedAndProject (70) : : : +- * SortMergeJoin LeftOuter (12) : : : :- * Sort (5) : : : : +- Exchange (4) - : : : : +- * Filter (3) - : : : : +- * ColumnarToRow (2) + : : : : +- * ColumnarToRow (3) + : : : : +- CometFilter (2) : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : +- * Sort (11) : : : +- Exchange (10) - : : : +- * Project (9) - : : : +- * Filter (8) - : : : +- * ColumnarToRow (7) + : : : +- * ColumnarToRow (9) + : : : +- CometProject (8) + : : : +- CometFilter (7) : : : +- CometScan parquet spark_catalog.default.store_returns (6) : : +- ReusedExchange (15) : +- * Sort (43) @@ -37,14 +37,14 @@ TakeOrderedAndProject (70) : : +- * SortMergeJoin LeftOuter (33) : : :- * Sort (26) : : : +- Exchange (25) - : : : +- * Filter (24) - : : : +- * ColumnarToRow (23) + : : : +- * ColumnarToRow (24) + : : : +- CometFilter (23) : : : +- CometScan parquet spark_catalog.default.web_sales (22) : : +- * Sort (32) : : +- Exchange (31) - : : +- * Project (30) - : : +- * Filter (29) - : : +- * ColumnarToRow (28) + : : +- * ColumnarToRow (30) + : : +- CometProject (29) + : : +- CometFilter (28) : : +- CometScan parquet spark_catalog.default.web_returns (27) : +- ReusedExchange (36) +- * Sort (67) @@ -59,14 +59,14 @@ TakeOrderedAndProject (70) : +- * SortMergeJoin LeftOuter (57) : :- * Sort (50) : : +- Exchange (49) - : : +- * Filter (48) - : : +- * ColumnarToRow (47) + : : +- * ColumnarToRow (48) + : : +- CometFilter (47) : : +- CometScan parquet spark_catalog.default.catalog_sales (46) : +- * Sort (56) : +- Exchange (55) - : +- * Project (54) - : +- * Filter (53) - : +- * ColumnarToRow (52) + : +- * ColumnarToRow (54) + : +- CometProject (53) + : +- CometFilter (52) : +- CometScan parquet spark_catalog.default.catalog_returns (51) +- ReusedExchange (60) @@ -79,12 +79,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] +(2) CometFilter Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] +Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_customer_sk#2)) -(3) Filter [codegen id : 1] +(3) ColumnarToRow [codegen id : 1] Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] -Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_customer_sk#2)) (4) Exchange Input [7]: [ss_item_sk#1, ss_customer_sk#2, ss_ticket_number#3, ss_quantity#4, ss_wholesale_cost#5, ss_sales_price#6, ss_sold_date_sk#7] @@ -101,16 +101,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk)] ReadSchema: struct -(7) ColumnarToRow [codegen id : 3] -Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] - -(8) Filter [codegen id : 3] +(7) CometFilter Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] Condition : (isnotnull(sr_ticket_number#10) AND isnotnull(sr_item_sk#9)) -(9) Project [codegen id : 3] -Output [2]: [sr_item_sk#9, sr_ticket_number#10] +(8) CometProject Input [3]: [sr_item_sk#9, sr_ticket_number#10, sr_returned_date_sk#11] +Arguments: [sr_item_sk#9, sr_ticket_number#10], [sr_item_sk#9, sr_ticket_number#10] + +(9) ColumnarToRow [codegen id : 3] +Input [2]: [sr_item_sk#9, sr_ticket_number#10] (10) Exchange Input [2]: [sr_item_sk#9, sr_ticket_number#10] @@ -177,12 +177,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#33), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_bill_customer_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 8] +(23) CometFilter Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] +Condition : (isnotnull(ws_item_sk#27) AND isnotnull(ws_bill_customer_sk#28)) -(24) Filter [codegen id : 8] +(24) ColumnarToRow [codegen id : 8] Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] -Condition : (isnotnull(ws_item_sk#27) AND isnotnull(ws_bill_customer_sk#28)) (25) Exchange Input [7]: [ws_item_sk#27, ws_bill_customer_sk#28, ws_order_number#29, ws_quantity#30, ws_wholesale_cost#31, ws_sales_price#32, ws_sold_date_sk#33] @@ -199,16 +199,16 @@ Location [not included in comparison]/{warehouse_dir}/web_returns] PushedFilters: [IsNotNull(wr_order_number), IsNotNull(wr_item_sk)] ReadSchema: struct -(28) ColumnarToRow [codegen id : 10] -Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] - -(29) Filter [codegen id : 10] +(28) CometFilter Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] Condition : (isnotnull(wr_order_number#36) AND isnotnull(wr_item_sk#35)) -(30) Project [codegen id : 10] -Output [2]: [wr_item_sk#35, wr_order_number#36] +(29) CometProject Input [3]: [wr_item_sk#35, wr_order_number#36, wr_returned_date_sk#37] +Arguments: [wr_item_sk#35, wr_order_number#36], [wr_item_sk#35, wr_order_number#36] + +(30) ColumnarToRow [codegen id : 10] +Input [2]: [wr_item_sk#35, wr_order_number#36] (31) Exchange Input [2]: [wr_item_sk#35, wr_order_number#36] @@ -289,12 +289,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#60), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_item_sk), IsNotNull(cs_bill_customer_sk)] ReadSchema: struct -(47) ColumnarToRow [codegen id : 16] +(47) CometFilter Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] +Condition : (isnotnull(cs_item_sk#55) AND isnotnull(cs_bill_customer_sk#54)) -(48) Filter [codegen id : 16] +(48) ColumnarToRow [codegen id : 16] Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] -Condition : (isnotnull(cs_item_sk#55) AND isnotnull(cs_bill_customer_sk#54)) (49) Exchange Input [7]: [cs_bill_customer_sk#54, cs_item_sk#55, cs_order_number#56, cs_quantity#57, cs_wholesale_cost#58, cs_sales_price#59, cs_sold_date_sk#60] @@ -311,16 +311,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_order_number), IsNotNull(cr_item_sk)] ReadSchema: struct -(52) ColumnarToRow [codegen id : 18] -Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] - -(53) Filter [codegen id : 18] +(52) CometFilter Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] Condition : (isnotnull(cr_order_number#63) AND isnotnull(cr_item_sk#62)) -(54) Project [codegen id : 18] -Output [2]: [cr_item_sk#62, cr_order_number#63] +(53) CometProject Input [3]: [cr_item_sk#62, cr_order_number#63, cr_returned_date_sk#64] +Arguments: [cr_item_sk#62, cr_order_number#63], [cr_item_sk#62, cr_order_number#63] + +(54) ColumnarToRow [codegen id : 18] +Input [2]: [cr_item_sk#62, cr_order_number#63] (55) Exchange Input [2]: [cr_item_sk#62, cr_order_number#63] @@ -401,8 +401,8 @@ Arguments: 100, [ss_sold_year#23 ASC NULLS FIRST, ss_item_sk#1 ASC NULLS FIRST, Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (74) -+- * Filter (73) - +- * ColumnarToRow (72) ++- * ColumnarToRow (73) + +- CometFilter (72) +- CometScan parquet spark_catalog.default.date_dim (71) @@ -413,12 +413,12 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)] ReadSchema: struct -(72) ColumnarToRow [codegen id : 1] +(72) CometFilter Input [2]: [d_date_sk#12, d_year#13] +Condition : ((isnotnull(d_year#13) AND (d_year#13 = 2000)) AND isnotnull(d_date_sk#12)) -(73) Filter [codegen id : 1] +(73) ColumnarToRow [codegen id : 1] Input [2]: [d_date_sk#12, d_year#13] -Condition : ((isnotnull(d_year#13) AND (d_year#13 = 2000)) AND isnotnull(d_date_sk#12)) (74) BroadcastExchange Input [2]: [d_date_sk#12, d_year#13] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt index f962e8fb8..49bd173f6 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q78/simplified.txt @@ -25,16 +25,16 @@ TakeOrderedAndProject [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp InputAdapter Exchange [ss_ticket_number,ss_item_sk] #2 WholeStageCodegen (1) - Filter [ss_item_sk,ss_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk,ss_customer_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_customer_sk,ss_ticket_number,ss_quantity,ss_wholesale_cost,ss_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #3 WholeStageCodegen (1) - Filter [d_year,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [d_year,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_year] InputAdapter WholeStageCodegen (4) @@ -42,10 +42,10 @@ TakeOrderedAndProject [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp InputAdapter Exchange [sr_ticket_number,sr_item_sk] #4 WholeStageCodegen (3) - Project [sr_item_sk,sr_ticket_number] - Filter [sr_ticket_number,sr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number] + CometFilter [sr_ticket_number,sr_item_sk] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk,d_year] #3 @@ -69,9 +69,9 @@ TakeOrderedAndProject [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp InputAdapter Exchange [ws_order_number,ws_item_sk] #6 WholeStageCodegen (8) - Filter [ws_item_sk,ws_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk,ws_bill_customer_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_bill_customer_sk,ws_order_number,ws_quantity,ws_wholesale_cost,ws_sales_price,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -80,10 +80,10 @@ TakeOrderedAndProject [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp InputAdapter Exchange [wr_order_number,wr_item_sk] #7 WholeStageCodegen (10) - Project [wr_item_sk,wr_order_number] - Filter [wr_order_number,wr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number] + CometFilter [wr_order_number,wr_item_sk] CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk,d_year] #3 @@ -107,9 +107,9 @@ TakeOrderedAndProject [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp InputAdapter Exchange [cs_order_number,cs_item_sk] #9 WholeStageCodegen (16) - Filter [cs_item_sk,cs_bill_customer_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_item_sk,cs_bill_customer_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_bill_customer_sk,cs_item_sk,cs_order_number,cs_quantity,cs_wholesale_cost,cs_sales_price,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -118,10 +118,10 @@ TakeOrderedAndProject [ss_sold_year,ss_item_sk,ss_customer_sk,ss_qty,ss_wc,ss_sp InputAdapter Exchange [cr_order_number,cr_item_sk] #10 WholeStageCodegen (18) - Project [cr_item_sk,cr_order_number] - Filter [cr_order_number,cr_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number] + CometFilter [cr_order_number,cr_item_sk] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk,d_year] #3 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt index d01fc085a..8f47f4f0e 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/explain.txt @@ -23,29 +23,29 @@ TakeOrderedAndProject (120) : : : : : : +- * SortMergeJoin LeftOuter (12) : : : : : : :- * Sort (5) : : : : : : : +- Exchange (4) - : : : : : : : +- * Filter (3) - : : : : : : : +- * ColumnarToRow (2) + : : : : : : : +- * ColumnarToRow (3) + : : : : : : : +- CometFilter (2) : : : : : : : +- CometScan parquet spark_catalog.default.store_sales (1) : : : : : : +- * Sort (11) : : : : : : +- Exchange (10) - : : : : : : +- * Project (9) - : : : : : : +- * Filter (8) - : : : : : : +- * ColumnarToRow (7) + : : : : : : +- * ColumnarToRow (9) + : : : : : : +- CometProject (8) + : : : : : : +- CometFilter (7) : : : : : : +- CometScan parquet spark_catalog.default.store_returns (6) : : : : : +- ReusedExchange (14) : : : : +- BroadcastExchange (20) - : : : : +- * Filter (19) - : : : : +- * ColumnarToRow (18) + : : : : +- * ColumnarToRow (19) + : : : : +- CometFilter (18) : : : : +- CometScan parquet spark_catalog.default.store (17) : : : +- BroadcastExchange (27) - : : : +- * Project (26) - : : : +- * Filter (25) - : : : +- * ColumnarToRow (24) + : : : +- * ColumnarToRow (26) + : : : +- CometProject (25) + : : : +- CometFilter (24) : : : +- CometScan parquet spark_catalog.default.item (23) : : +- BroadcastExchange (34) - : : +- * Project (33) - : : +- * Filter (32) - : : +- * ColumnarToRow (31) + : : +- * ColumnarToRow (33) + : : +- CometProject (32) + : : +- CometFilter (31) : : +- CometScan parquet spark_catalog.default.promotion (30) : :- * HashAggregate (70) : : +- Exchange (69) @@ -62,19 +62,19 @@ TakeOrderedAndProject (120) : : : : : : +- * SortMergeJoin LeftOuter (51) : : : : : : :- * Sort (44) : : : : : : : +- Exchange (43) - : : : : : : : +- * Filter (42) - : : : : : : : +- * ColumnarToRow (41) + : : : : : : : +- * ColumnarToRow (42) + : : : : : : : +- CometFilter (41) : : : : : : : +- CometScan parquet spark_catalog.default.catalog_sales (40) : : : : : : +- * Sort (50) : : : : : : +- Exchange (49) - : : : : : : +- * Project (48) - : : : : : : +- * Filter (47) - : : : : : : +- * ColumnarToRow (46) + : : : : : : +- * ColumnarToRow (48) + : : : : : : +- CometProject (47) + : : : : : : +- CometFilter (46) : : : : : : +- CometScan parquet spark_catalog.default.catalog_returns (45) : : : : : +- ReusedExchange (53) : : : : +- BroadcastExchange (59) - : : : : +- * Filter (58) - : : : : +- * ColumnarToRow (57) + : : : : +- * ColumnarToRow (58) + : : : : +- CometFilter (57) : : : : +- CometScan parquet spark_catalog.default.catalog_page (56) : : : +- ReusedExchange (62) : : +- ReusedExchange (65) @@ -93,19 +93,19 @@ TakeOrderedAndProject (120) : : : : : +- * SortMergeJoin LeftOuter (82) : : : : : :- * Sort (75) : : : : : : +- Exchange (74) - : : : : : : +- * Filter (73) - : : : : : : +- * ColumnarToRow (72) + : : : : : : +- * ColumnarToRow (73) + : : : : : : +- CometFilter (72) : : : : : : +- CometScan parquet spark_catalog.default.web_sales (71) : : : : : +- * Sort (81) : : : : : +- Exchange (80) - : : : : : +- * Project (79) - : : : : : +- * Filter (78) - : : : : : +- * ColumnarToRow (77) + : : : : : +- * ColumnarToRow (79) + : : : : : +- CometProject (78) + : : : : : +- CometFilter (77) : : : : : +- CometScan parquet spark_catalog.default.web_returns (76) : : : : +- ReusedExchange (84) : : : +- BroadcastExchange (90) - : : : +- * Filter (89) - : : : +- * ColumnarToRow (88) + : : : +- * ColumnarToRow (89) + : : : +- CometFilter (88) : : : +- CometScan parquet spark_catalog.default.web_site (87) : : +- ReusedExchange (93) : +- ReusedExchange (96) @@ -129,12 +129,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_item_sk), IsNotNull(ss_promo_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 1] +(2) CometFilter Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] +Condition : ((isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) -(3) Filter [codegen id : 1] +(3) ColumnarToRow [codegen id : 1] Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] -Condition : ((isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3)) (4) Exchange Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_promo_sk#3, ss_ticket_number#4, ss_ext_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7] @@ -151,16 +151,16 @@ Location [not included in comparison]/{warehouse_dir}/store_returns] PushedFilters: [IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)] ReadSchema: struct -(7) ColumnarToRow [codegen id : 3] -Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] - -(8) Filter [codegen id : 3] +(7) CometFilter Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] Condition : (isnotnull(sr_item_sk#9) AND isnotnull(sr_ticket_number#10)) -(9) Project [codegen id : 3] -Output [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] +(8) CometProject Input [5]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12, sr_returned_date_sk#13] +Arguments: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12], [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] + +(9) ColumnarToRow [codegen id : 3] +Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] (10) Exchange Input [4]: [sr_item_sk#9, sr_ticket_number#10, sr_return_amt#11, sr_net_loss#12] @@ -200,12 +200,12 @@ Location [not included in comparison]/{warehouse_dir}/store] PushedFilters: [IsNotNull(s_store_sk)] ReadSchema: struct -(18) ColumnarToRow [codegen id : 6] +(18) CometFilter Input [2]: [s_store_sk#15, s_store_id#16] +Condition : isnotnull(s_store_sk#15) -(19) Filter [codegen id : 6] +(19) ColumnarToRow [codegen id : 6] Input [2]: [s_store_sk#15, s_store_id#16] -Condition : isnotnull(s_store_sk#15) (20) BroadcastExchange Input [2]: [s_store_sk#15, s_store_id#16] @@ -228,16 +228,16 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_current_price), GreaterThan(i_current_price,50.00), IsNotNull(i_item_sk)] ReadSchema: struct -(24) ColumnarToRow [codegen id : 7] -Input [2]: [i_item_sk#17, i_current_price#18] - -(25) Filter [codegen id : 7] +(24) CometFilter Input [2]: [i_item_sk#17, i_current_price#18] Condition : ((isnotnull(i_current_price#18) AND (i_current_price#18 > 50.00)) AND isnotnull(i_item_sk#17)) -(26) Project [codegen id : 7] -Output [1]: [i_item_sk#17] +(25) CometProject Input [2]: [i_item_sk#17, i_current_price#18] +Arguments: [i_item_sk#17], [i_item_sk#17] + +(26) ColumnarToRow [codegen id : 7] +Input [1]: [i_item_sk#17] (27) BroadcastExchange Input [1]: [i_item_sk#17] @@ -260,16 +260,16 @@ Location [not included in comparison]/{warehouse_dir}/promotion] PushedFilters: [IsNotNull(p_channel_tv), EqualTo(p_channel_tv,N), IsNotNull(p_promo_sk)] ReadSchema: struct -(31) ColumnarToRow [codegen id : 8] -Input [2]: [p_promo_sk#19, p_channel_tv#20] - -(32) Filter [codegen id : 8] +(31) CometFilter Input [2]: [p_promo_sk#19, p_channel_tv#20] Condition : ((isnotnull(p_channel_tv#20) AND (p_channel_tv#20 = N)) AND isnotnull(p_promo_sk#19)) -(33) Project [codegen id : 8] -Output [1]: [p_promo_sk#19] +(32) CometProject Input [2]: [p_promo_sk#19, p_channel_tv#20] +Arguments: [p_promo_sk#19], [p_promo_sk#19] + +(33) ColumnarToRow [codegen id : 8] +Input [1]: [p_promo_sk#19] (34) BroadcastExchange Input [1]: [p_promo_sk#19] @@ -311,12 +311,12 @@ PartitionFilters: [isnotnull(cs_sold_date_sk#45), dynamicpruningexpression(cs_so PushedFilters: [IsNotNull(cs_catalog_page_sk), IsNotNull(cs_item_sk), IsNotNull(cs_promo_sk)] ReadSchema: struct -(41) ColumnarToRow [codegen id : 11] +(41) CometFilter Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] +Condition : ((isnotnull(cs_catalog_page_sk#39) AND isnotnull(cs_item_sk#40)) AND isnotnull(cs_promo_sk#41)) -(42) Filter [codegen id : 11] +(42) ColumnarToRow [codegen id : 11] Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] -Condition : ((isnotnull(cs_catalog_page_sk#39) AND isnotnull(cs_item_sk#40)) AND isnotnull(cs_promo_sk#41)) (43) Exchange Input [7]: [cs_catalog_page_sk#39, cs_item_sk#40, cs_promo_sk#41, cs_order_number#42, cs_ext_sales_price#43, cs_net_profit#44, cs_sold_date_sk#45] @@ -333,16 +333,16 @@ Location [not included in comparison]/{warehouse_dir}/catalog_returns] PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)] ReadSchema: struct -(46) ColumnarToRow [codegen id : 13] -Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] - -(47) Filter [codegen id : 13] +(46) CometFilter Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] Condition : (isnotnull(cr_item_sk#47) AND isnotnull(cr_order_number#48)) -(48) Project [codegen id : 13] -Output [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] +(47) CometProject Input [5]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50, cr_returned_date_sk#51] +Arguments: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50], [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] + +(48) ColumnarToRow [codegen id : 13] +Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] (49) Exchange Input [4]: [cr_item_sk#47, cr_order_number#48, cr_return_amount#49, cr_net_loss#50] @@ -382,12 +382,12 @@ Location [not included in comparison]/{warehouse_dir}/catalog_page] PushedFilters: [IsNotNull(cp_catalog_page_sk)] ReadSchema: struct -(57) ColumnarToRow [codegen id : 16] +(57) CometFilter Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] +Condition : isnotnull(cp_catalog_page_sk#53) -(58) Filter [codegen id : 16] +(58) ColumnarToRow [codegen id : 16] Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] -Condition : isnotnull(cp_catalog_page_sk#53) (59) BroadcastExchange Input [2]: [cp_catalog_page_sk#53, cp_catalog_page_id#54] @@ -455,12 +455,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#81), dynamicpruningexpression(ws_so PushedFilters: [IsNotNull(ws_web_site_sk), IsNotNull(ws_item_sk), IsNotNull(ws_promo_sk)] ReadSchema: struct -(72) ColumnarToRow [codegen id : 21] +(72) CometFilter Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] +Condition : ((isnotnull(ws_web_site_sk#76) AND isnotnull(ws_item_sk#75)) AND isnotnull(ws_promo_sk#77)) -(73) Filter [codegen id : 21] +(73) ColumnarToRow [codegen id : 21] Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] -Condition : ((isnotnull(ws_web_site_sk#76) AND isnotnull(ws_item_sk#75)) AND isnotnull(ws_promo_sk#77)) (74) Exchange Input [7]: [ws_item_sk#75, ws_web_site_sk#76, ws_promo_sk#77, ws_order_number#78, ws_ext_sales_price#79, ws_net_profit#80, ws_sold_date_sk#81] @@ -477,16 +477,16 @@ Location [not included in comparison]/{warehouse_dir}/web_returns] PushedFilters: [IsNotNull(wr_item_sk), IsNotNull(wr_order_number)] ReadSchema: struct -(77) ColumnarToRow [codegen id : 23] -Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] - -(78) Filter [codegen id : 23] +(77) CometFilter Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] Condition : (isnotnull(wr_item_sk#83) AND isnotnull(wr_order_number#84)) -(79) Project [codegen id : 23] -Output [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] +(78) CometProject Input [5]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86, wr_returned_date_sk#87] +Arguments: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86], [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] + +(79) ColumnarToRow [codegen id : 23] +Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] (80) Exchange Input [4]: [wr_item_sk#83, wr_order_number#84, wr_return_amt#85, wr_net_loss#86] @@ -526,12 +526,12 @@ Location [not included in comparison]/{warehouse_dir}/web_site] PushedFilters: [IsNotNull(web_site_sk)] ReadSchema: struct -(88) ColumnarToRow [codegen id : 26] +(88) CometFilter Input [2]: [web_site_sk#89, web_site_id#90] +Condition : isnotnull(web_site_sk#89) -(89) Filter [codegen id : 26] +(89) ColumnarToRow [codegen id : 26] Input [2]: [web_site_sk#89, web_site_id#90] -Condition : isnotnull(web_site_sk#89) (90) BroadcastExchange Input [2]: [web_site_sk#89, web_site_id#90] @@ -695,9 +695,9 @@ Arguments: 100, [channel#34 ASC NULLS FIRST, id#35 ASC NULLS FIRST], [channel#34 Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8 BroadcastExchange (125) -+- * Project (124) - +- * Filter (123) - +- * ColumnarToRow (122) ++- * ColumnarToRow (124) + +- CometProject (123) + +- CometFilter (122) +- CometScan parquet spark_catalog.default.date_dim (121) @@ -708,16 +708,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1998-08-04), LessThanOrEqual(d_date,1998-09-03), IsNotNull(d_date_sk)] ReadSchema: struct -(122) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#14, d_date#196] - -(123) Filter [codegen id : 1] +(122) CometFilter Input [2]: [d_date_sk#14, d_date#196] Condition : (((isnotnull(d_date#196) AND (d_date#196 >= 1998-08-04)) AND (d_date#196 <= 1998-09-03)) AND isnotnull(d_date_sk#14)) -(124) Project [codegen id : 1] -Output [1]: [d_date_sk#14] +(123) CometProject Input [2]: [d_date_sk#14, d_date#196] +Arguments: [d_date_sk#14], [d_date_sk#14] + +(124) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#14] (125) BroadcastExchange Input [1]: [d_date_sk#14] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt index 047ac07a6..34e47dcba 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q80a/simplified.txt @@ -37,17 +37,17 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [ss_item_sk,ss_ticket_number] #4 WholeStageCodegen (1) - Filter [ss_store_sk,ss_item_sk,ss_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_store_sk,ss_item_sk,ss_promo_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_store_sk,ss_promo_sk,ss_ticket_number,ss_ext_sales_price,ss_net_profit,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #5 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter WholeStageCodegen (4) @@ -55,35 +55,35 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [sr_item_sk,sr_ticket_number] #6 WholeStageCodegen (3) - Project [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss] - Filter [sr_item_sk,sr_ticket_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss] + CometFilter [sr_item_sk,sr_ticket_number] CometScan parquet spark_catalog.default.store_returns [sr_item_sk,sr_ticket_number,sr_return_amt,sr_net_loss,sr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #5 InputAdapter BroadcastExchange #7 WholeStageCodegen (6) - Filter [s_store_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [s_store_sk] CometScan parquet spark_catalog.default.store [s_store_sk,s_store_id] InputAdapter BroadcastExchange #8 WholeStageCodegen (7) - Project [i_item_sk] - Filter [i_current_price,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [i_item_sk] + CometFilter [i_current_price,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_current_price] InputAdapter BroadcastExchange #9 WholeStageCodegen (8) - Project [p_promo_sk] - Filter [p_channel_tv,p_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [p_promo_sk] + CometFilter [p_channel_tv,p_promo_sk] CometScan parquet spark_catalog.default.promotion [p_promo_sk,p_channel_tv] WholeStageCodegen (20) HashAggregate [cp_catalog_page_id,sum,sum,isEmpty,sum,isEmpty] [sum(UnscaledValue(cs_ext_sales_price)),sum(coalesce(cast(cr_return_amount as decimal(12,2)), 0.00)),sum((cs_net_profit - coalesce(cast(cr_net_loss as decimal(12,2)), 0.00))),channel,id,sales,returns,profit,sum,sum,isEmpty,sum,isEmpty] @@ -107,9 +107,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [cs_item_sk,cs_order_number] #11 WholeStageCodegen (11) - Filter [cs_catalog_page_sk,cs_item_sk,cs_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cs_catalog_page_sk,cs_item_sk,cs_promo_sk] CometScan parquet spark_catalog.default.catalog_sales [cs_catalog_page_sk,cs_item_sk,cs_promo_sk,cs_order_number,cs_ext_sales_price,cs_net_profit,cs_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -118,19 +118,19 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [cr_item_sk,cr_order_number] #12 WholeStageCodegen (13) - Project [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss] - Filter [cr_item_sk,cr_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss] + CometFilter [cr_item_sk,cr_order_number] CometScan parquet spark_catalog.default.catalog_returns [cr_item_sk,cr_order_number,cr_return_amount,cr_net_loss,cr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #5 InputAdapter BroadcastExchange #13 WholeStageCodegen (16) - Filter [cp_catalog_page_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [cp_catalog_page_sk] CometScan parquet spark_catalog.default.catalog_page [cp_catalog_page_sk,cp_catalog_page_id] InputAdapter ReusedExchange [i_item_sk] #8 @@ -158,9 +158,9 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [ws_item_sk,ws_order_number] #15 WholeStageCodegen (21) - Filter [ws_web_site_sk,ws_item_sk,ws_promo_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_web_site_sk,ws_item_sk,ws_promo_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_web_site_sk,ws_promo_sk,ws_order_number,ws_ext_sales_price,ws_net_profit,ws_sold_date_sk] ReusedSubquery [d_date_sk] #1 InputAdapter @@ -169,19 +169,19 @@ TakeOrderedAndProject [channel,id,sales,returns,profit] InputAdapter Exchange [wr_item_sk,wr_order_number] #16 WholeStageCodegen (23) - Project [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss] - Filter [wr_item_sk,wr_order_number] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss] + CometFilter [wr_item_sk,wr_order_number] CometScan parquet spark_catalog.default.web_returns [wr_item_sk,wr_order_number,wr_return_amt,wr_net_loss,wr_returned_date_sk] InputAdapter ReusedExchange [d_date_sk] #5 InputAdapter BroadcastExchange #17 WholeStageCodegen (26) - Filter [web_site_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [web_site_sk] CometScan parquet spark_catalog.default.web_site [web_site_sk,web_site_id] InputAdapter ReusedExchange [i_item_sk] #8 diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt index 7aac30e5f..58e7f5825 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/explain.txt @@ -15,13 +15,13 @@ TakeOrderedAndProject (34) : +- * BroadcastHashJoin Inner BuildRight (11) : :- * Project (6) : : +- * BroadcastHashJoin Inner BuildRight (5) - : : :- * Filter (3) - : : : +- * ColumnarToRow (2) + : : :- * ColumnarToRow (3) + : : : +- CometFilter (2) : : : +- CometScan parquet spark_catalog.default.web_sales (1) : : +- ReusedExchange (4) : +- BroadcastExchange (10) - : +- * Filter (9) - : +- * ColumnarToRow (8) + : +- * ColumnarToRow (9) + : +- CometFilter (8) : +- CometScan parquet spark_catalog.default.item (7) :- * HashAggregate (20) : +- Exchange (19) @@ -43,12 +43,12 @@ PartitionFilters: [isnotnull(ws_sold_date_sk#3), dynamicpruningexpression(ws_sol PushedFilters: [IsNotNull(ws_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] +Condition : isnotnull(ws_item_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [3]: [ws_item_sk#1, ws_net_paid#2, ws_sold_date_sk#3] -Condition : isnotnull(ws_item_sk#1) (4) ReusedExchange [Reuses operator id: 39] Output [1]: [d_date_sk#5] @@ -70,12 +70,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [IsNotNull(i_item_sk)] ReadSchema: struct -(8) ColumnarToRow [codegen id : 2] +(8) CometFilter Input [3]: [i_item_sk#6, i_class#7, i_category#8] +Condition : isnotnull(i_item_sk#6) -(9) Filter [codegen id : 2] +(9) ColumnarToRow [codegen id : 2] Input [3]: [i_item_sk#6, i_class#7, i_category#8] -Condition : isnotnull(i_item_sk#6) (10) BroadcastExchange Input [3]: [i_item_sk#6, i_class#7, i_category#8] @@ -209,9 +209,9 @@ Arguments: 100, [lochierarchy#15 DESC NULLS LAST, CASE WHEN (lochierarchy#15 = 0 Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (39) -+- * Project (38) - +- * Filter (37) - +- * ColumnarToRow (36) ++- * ColumnarToRow (38) + +- CometProject (37) + +- CometFilter (36) +- CometScan parquet spark_catalog.default.date_dim (35) @@ -222,16 +222,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)] ReadSchema: struct -(36) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#5, d_month_seq#49] - -(37) Filter [codegen id : 1] +(36) CometFilter Input [2]: [d_date_sk#5, d_month_seq#49] Condition : (((isnotnull(d_month_seq#49) AND (d_month_seq#49 >= 1212)) AND (d_month_seq#49 <= 1223)) AND isnotnull(d_date_sk#5)) -(38) Project [codegen id : 1] -Output [1]: [d_date_sk#5] +(37) CometProject Input [2]: [d_date_sk#5, d_month_seq#49] +Arguments: [d_date_sk#5], [d_date_sk#5] + +(38) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#5] (39) BroadcastExchange Input [1]: [d_date_sk#5] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt index 5146ee0d2..5c5e08885 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q86a/simplified.txt @@ -25,26 +25,26 @@ TakeOrderedAndProject [lochierarchy,i_category,rank_within_parent,total_sum,i_cl BroadcastHashJoin [ws_item_sk,i_item_sk] Project [ws_item_sk,ws_net_paid] BroadcastHashJoin [ws_sold_date_sk,d_date_sk] - Filter [ws_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ws_item_sk] CometScan parquet spark_catalog.default.web_sales [ws_item_sk,ws_net_paid,ws_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_month_seq,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_month_seq,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_month_seq] InputAdapter ReusedExchange [d_date_sk] #4 InputAdapter BroadcastExchange #5 WholeStageCodegen (2) - Filter [i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_class,i_category] WholeStageCodegen (9) HashAggregate [i_category,sum,isEmpty] [sum(total_sum),total_sum,i_class,g_category,g_class,lochierarchy,sum,isEmpty] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt index a2f3cffb6..f77b7ec93 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/explain.txt @@ -12,12 +12,12 @@ +- * BroadcastHashJoin Inner BuildRight (11) :- * Project (9) : +- * BroadcastHashJoin Inner BuildRight (8) - : :- * Filter (3) - : : +- * ColumnarToRow (2) + : :- * ColumnarToRow (3) + : : +- CometFilter (2) : : +- CometScan parquet spark_catalog.default.store_sales (1) : +- BroadcastExchange (7) - : +- * Filter (6) - : +- * ColumnarToRow (5) + : +- * ColumnarToRow (6) + : +- CometFilter (5) : +- CometScan parquet spark_catalog.default.item (4) +- ReusedExchange (10) @@ -30,12 +30,12 @@ PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sol PushedFilters: [IsNotNull(ss_item_sk)] ReadSchema: struct -(2) ColumnarToRow [codegen id : 3] +(2) CometFilter Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] +Condition : isnotnull(ss_item_sk#1) -(3) Filter [codegen id : 3] +(3) ColumnarToRow [codegen id : 3] Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3] -Condition : isnotnull(ss_item_sk#1) (4) Scan parquet spark_catalog.default.item Output [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -44,12 +44,12 @@ Location [not included in comparison]/{warehouse_dir}/item] PushedFilters: [In(i_category, [Books ,Home ,Sports ]), IsNotNull(i_item_sk)] ReadSchema: struct -(5) ColumnarToRow [codegen id : 1] +(5) CometFilter Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] +Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) -(6) Filter [codegen id : 1] +(6) ColumnarToRow [codegen id : 1] Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] -Condition : (i_category#10 IN (Sports ,Books ,Home ) AND isnotnull(i_item_sk#5)) (7) BroadcastExchange Input [6]: [i_item_sk#5, i_item_id#6, i_item_desc#7, i_current_price#8, i_class#9, i_category#10] @@ -124,9 +124,9 @@ Arguments: [i_category#10 ASC NULLS FIRST, i_class#9 ASC NULLS FIRST, i_item_id# Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4 BroadcastExchange (26) -+- * Project (25) - +- * Filter (24) - +- * ColumnarToRow (23) ++- * ColumnarToRow (25) + +- CometProject (24) + +- CometFilter (23) +- CometScan parquet spark_catalog.default.date_dim (22) @@ -137,16 +137,16 @@ Location [not included in comparison]/{warehouse_dir}/date_dim] PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1999-02-22), LessThanOrEqual(d_date,1999-03-24), IsNotNull(d_date_sk)] ReadSchema: struct -(23) ColumnarToRow [codegen id : 1] -Input [2]: [d_date_sk#11, d_date#19] - -(24) Filter [codegen id : 1] +(23) CometFilter Input [2]: [d_date_sk#11, d_date#19] Condition : (((isnotnull(d_date#19) AND (d_date#19 >= 1999-02-22)) AND (d_date#19 <= 1999-03-24)) AND isnotnull(d_date_sk#11)) -(25) Project [codegen id : 1] -Output [1]: [d_date_sk#11] +(24) CometProject Input [2]: [d_date_sk#11, d_date#19] +Arguments: [d_date_sk#11], [d_date_sk#11] + +(25) ColumnarToRow [codegen id : 1] +Input [1]: [d_date_sk#11] (26) BroadcastExchange Input [1]: [d_date_sk#11] diff --git a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt index 5aa7c17f1..b7489a0af 100644 --- a/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt +++ b/spark/src/test/resources/tpcds-plan-stability/approved-plans-v2_7-spark4_0/q98/simplified.txt @@ -20,24 +20,24 @@ WholeStageCodegen (7) BroadcastHashJoin [ss_sold_date_sk,d_date_sk] Project [ss_ext_sales_price,ss_sold_date_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] BroadcastHashJoin [ss_item_sk,i_item_sk] - Filter [ss_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [ss_item_sk] CometScan parquet spark_catalog.default.store_sales [ss_item_sk,ss_ext_sales_price,ss_sold_date_sk] SubqueryBroadcast [d_date_sk] #1 BroadcastExchange #4 WholeStageCodegen (1) - Project [d_date_sk] - Filter [d_date,d_date_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometProject [d_date_sk] + CometFilter [d_date,d_date_sk] CometScan parquet spark_catalog.default.date_dim [d_date_sk,d_date] InputAdapter BroadcastExchange #5 WholeStageCodegen (1) - Filter [i_category,i_item_sk] - ColumnarToRow - InputAdapter + ColumnarToRow + InputAdapter + CometFilter [i_category,i_item_sk] CometScan parquet spark_catalog.default.item [i_item_sk,i_item_id,i_item_desc,i_current_price,i_class,i_category] InputAdapter ReusedExchange [d_date_sk] #4 diff --git a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala index 4d73596a7..fd2218965 100644 --- a/spark/src/test/scala/org/apache/comet/CometCastSuite.scala +++ b/spark/src/test/scala/org/apache/comet/CometCastSuite.scala @@ -990,12 +990,9 @@ class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper { if (CometSparkSessionExtensions.isSpark40Plus) { // for Spark 4 we expect to sparkException carries the message assert( - cometMessage == sparkException.getMessage - .split("\n") - .head + sparkException.getMessage .replace(".WITH_SUGGESTION] ", "]") - .replace(" SQLSTATE: 22003", "") - .replace(" SQLSTATE: 22018", "")) + .startsWith(cometMessage)) } else if (CometSparkSessionExtensions.isSpark34Plus) { // for Spark 3.4 we expect to reproduce the error message exactly assert(cometMessage == sparkMessage) diff --git a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala index 22d016c66..691d2cd63 100644 --- a/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala +++ b/spark/src/test/scala/org/apache/spark/sql/comet/CometPlanStabilitySuite.scala @@ -298,7 +298,6 @@ trait CometPlanStabilitySuite extends DisableAdaptiveExecutionSuite with TPCDSBa } class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { - // TODO: remove the Spark 4.0 golden file once ANSI is fully supported private val planName = if (isSpark40Plus) "approved-plans-v1_4-spark4_0" else "approved-plans-v1_4" override val goldenFilePath: String = @@ -312,7 +311,6 @@ class CometTPCDSV1_4_PlanStabilitySuite extends CometPlanStabilitySuite { } class CometTPCDSV2_7_PlanStabilitySuite extends CometPlanStabilitySuite { - // TODO: remove the Spark 4.0 golden file once ANSI is fully supported private val planName = if (isSpark40Plus) "approved-plans-v2_7-spark4_0" else "approved-plans-v2_7" override val goldenFilePath: String = From 77fcaf1dbca0120336c9698de73358aedc6ee79a Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Fri, 24 May 2024 18:50:26 -0700 Subject: [PATCH 42/68] wip --- .../spark/sql/comet/CometScanExec.scala | 90 +------------------ .../sql/comet/shims/ShimCometScanExec.scala | 89 +++++++++++++++++- .../sql/comet/shims/ShimCometScanExec.scala | 13 ++- 3 files changed, 99 insertions(+), 93 deletions(-) diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala b/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala index 9a5b55d65..873efca3a 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala @@ -61,8 +61,7 @@ case class CometScanExec( tableIdentifier: Option[TableIdentifier], disableBucketedScan: Boolean = false, wrapped: FileSourceScanExec) - extends DataSourceScanExec - with ShimCometScanExec + extends ShimCometScanExec with CometPlan { // FIXME: ideally we should reuse wrapped.supportsColumnar, however that fails many tests @@ -89,48 +88,6 @@ case class CometScanExec( private def isDynamicPruningFilter(e: Expression): Boolean = e.find(_.isInstanceOf[PlanExpression[_]]).isDefined - @transient lazy val selectedPartitions: Array[PartitionDirectory] = { - val optimizerMetadataTimeNs = relation.location.metadataOpsTimeNs.getOrElse(0L) - val startTime = System.nanoTime() - val ret = - relation.location.listFiles(partitionFilters.filterNot(isDynamicPruningFilter), dataFilters) - setFilesNumAndSizeMetric(ret, true) - val timeTakenMs = - NANOSECONDS.toMillis((System.nanoTime() - startTime) + optimizerMetadataTimeNs) - driverMetrics("metadataTime") = timeTakenMs - ret - }.toArray - - // We can only determine the actual partitions at runtime when a dynamic partition filter is - // present. This is because such a filter relies on information that is only available at run - // time (for instance the keys used in the other side of a join). - @transient private lazy val dynamicallySelectedPartitions: Array[PartitionDirectory] = { - val dynamicPartitionFilters = partitionFilters.filter(isDynamicPruningFilter) - - if (dynamicPartitionFilters.nonEmpty) { - val startTime = System.nanoTime() - // call the file index for the files matching all filters except dynamic partition filters - val predicate = dynamicPartitionFilters.reduce(And) - val partitionColumns = relation.partitionSchema - val boundPredicate = Predicate.create( - predicate.transform { case a: AttributeReference => - val index = partitionColumns.indexWhere(a.name == _.name) - BoundReference(index, partitionColumns(index).dataType, nullable = true) - }, - Nil) - val ret = selectedPartitions.filter(p => boundPredicate.eval(p.values)) - setFilesNumAndSizeMetric(ret, false) - val timeTakenMs = (System.nanoTime() - startTime) / 1000 / 1000 - driverMetrics("pruningTime") = timeTakenMs - ret - } else { - selectedPartitions - } - } - - // exposed for testing - lazy val bucketedScan: Boolean = wrapped.bucketedScan - override lazy val (outputPartitioning, outputOrdering): (Partitioning, Seq[SortOrder]) = (wrapped.outputPartitioning, wrapped.outputOrdering) @@ -148,55 +105,10 @@ case class CometScanExec( wrapped.verboseStringWithOperatorId() } - lazy val inputRDD: RDD[InternalRow] = { - val options = relation.options + - (ShimFileFormat.OPTION_RETURNING_BATCH -> supportsColumnar.toString) - val readFile: (PartitionedFile) => Iterator[InternalRow] = - relation.fileFormat.buildReaderWithPartitionValues( - sparkSession = relation.sparkSession, - dataSchema = relation.dataSchema, - partitionSchema = relation.partitionSchema, - requiredSchema = requiredSchema, - filters = pushedDownFilters, - options = options, - hadoopConf = - relation.sparkSession.sessionState.newHadoopConfWithOptions(relation.options)) - - val readRDD = if (bucketedScan) { - createBucketedReadRDD( - relation.bucketSpec.get, - readFile, - dynamicallySelectedPartitions, - relation) - } else { - createReadRDD(readFile, dynamicallySelectedPartitions, relation) - } - sendDriverMetrics() - readRDD - } - override def inputRDDs(): Seq[RDD[InternalRow]] = { inputRDD :: Nil } - /** Helper for computing total number and size of files in selected partitions. */ - private def setFilesNumAndSizeMetric( - partitions: Seq[PartitionDirectory], - static: Boolean): Unit = { - val filesNum = partitions.map(_.files.size.toLong).sum - val filesSize = partitions.map(_.files.map(_.getLen).sum).sum - if (!static || !partitionFilters.exists(isDynamicPruningFilter)) { - driverMetrics("numFiles") = filesNum - driverMetrics("filesSize") = filesSize - } else { - driverMetrics("staticFilesNum") = filesNum - driverMetrics("staticFilesSize") = filesSize - } - if (relation.partitionSchema.nonEmpty) { - driverMetrics("numPartitions") = partitions.length - } - } - override lazy val metrics: Map[String, SQLMetric] = wrapped.metrics ++ { // Tracking scan time has overhead, we can't afford to do it for each row, and can only do // it for each batch. diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala index 02b97f9fb..f3e2b65da 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala @@ -37,7 +37,7 @@ import org.apache.spark.sql.execution.datasources.v2.DataSourceRDD import org.apache.spark.sql.execution.metric.SQLMetric import org.apache.spark.sql.types.{LongType, StructField, StructType} -trait ShimCometScanExec { +trait ShimCometScanExec extends DataSourceScanExec { def wrapped: FileSourceScanExec // TODO: remove after dropping Spark 3.2 support and directly call wrapped.metadataColumns @@ -138,4 +138,91 @@ trait ShimCometScanExec { maxSplitBytes: Long, partitionValues: InternalRow): Seq[PartitionedFile] = PartitionedFileUtil.splitFiles(sparkSession, file, filePath, isSplitable, maxSplitBytes, partitionValues) + + @transient lazy val selectedPartitions: Array[PartitionDirectory] = { + val optimizerMetadataTimeNs = relation.location.metadataOpsTimeNs.getOrElse(0L) + val startTime = System.nanoTime() + val ret = + relation.location.listFiles(partitionFilters.filterNot(isDynamicPruningFilter), dataFilters) + setFilesNumAndSizeMetric(ret, true) + val timeTakenMs = + NANOSECONDS.toMillis((System.nanoTime() - startTime) + optimizerMetadataTimeNs) + driverMetrics("metadataTime") = timeTakenMs + ret + }.toArray + + // We can only determine the actual partitions at runtime when a dynamic partition filter is + // present. This is because such a filter relies on information that is only available at run + // time (for instance the keys used in the other side of a join). + @transient private lazy val dynamicallySelectedPartitions: Array[PartitionDirectory] = { + val dynamicPartitionFilters = partitionFilters.filter(isDynamicPruningFilter) + + if (dynamicPartitionFilters.nonEmpty) { + val startTime = System.nanoTime() + // call the file index for the files matching all filters except dynamic partition filters + val predicate = dynamicPartitionFilters.reduce(And) + val partitionColumns = relation.partitionSchema + val boundPredicate = Predicate.create( + predicate.transform { case a: AttributeReference => + val index = partitionColumns.indexWhere(a.name == _.name) + BoundReference(index, partitionColumns(index).dataType, nullable = true) + }, + Nil) + val ret = selectedPartitions.filter(p => boundPredicate.eval(p.values)) + setFilesNumAndSizeMetric(ret, false) + val timeTakenMs = (System.nanoTime() - startTime) / 1000 / 1000 + driverMetrics("pruningTime") = timeTakenMs + ret + } else { + selectedPartitions + } + } + + // exposed for testing + lazy val bucketedScan: Boolean = wrapped.bucketedScan + + lazy val inputRDD: RDD[InternalRow] = { + val options = relation.options + + (ShimFileFormat.OPTION_RETURNING_BATCH -> supportsColumnar.toString) + val readFile: (PartitionedFile) => Iterator[InternalRow] = + relation.fileFormat.buildReaderWithPartitionValues( + sparkSession = relation.sparkSession, + dataSchema = relation.dataSchema, + partitionSchema = relation.partitionSchema, + requiredSchema = requiredSchema, + filters = pushedDownFilters, + options = options, + hadoopConf = + relation.sparkSession.sessionState.newHadoopConfWithOptions(relation.options)) + + val readRDD = if (bucketedScan) { + createBucketedReadRDD( + relation.bucketSpec.get, + readFile, + dynamicallySelectedPartitions, + relation) + } else { + createReadRDD(readFile, dynamicallySelectedPartitions, relation) + } + sendDriverMetrics() + readRDD + } + + /** Helper for computing total number and size of files in selected partitions. */ + private def setFilesNumAndSizeMetric( + partitions: Seq[PartitionDirectory], + static: Boolean): Unit = { + val filesNum = partitions.map(_.files.size.toLong).sum + val filesSize = partitions.map(_.files.map(_.getLen).sum).sum + if (!static || !partitionFilters.exists(isDynamicPruningFilter)) { + driverMetrics("numFiles") = filesNum + driverMetrics("filesSize") = filesSize + } else { + driverMetrics("staticFilesNum") = filesNum + driverMetrics("staticFilesSize") = filesSize + } + if (relation.partitionSchema.nonEmpty) { + driverMetrics("numPartitions") = partitions.length + } + } } diff --git a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala index 543116c10..70712e2dc 100644 --- a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala @@ -30,14 +30,14 @@ import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.datasources.v2.DataSourceRDD import org.apache.spark.sql.execution.datasources._ import org.apache.spark.sql.execution.metric.SQLMetric -import org.apache.spark.sql.execution.{FileSourceScanExec, PartitionedFileUtil} +import org.apache.spark.sql.execution.{FileSourceScanExec, FileSourceScanLike, PartitionedFileUtil, ScanFileListing} import org.apache.spark.sql.types.StructType import org.apache.spark.SparkContext -trait ShimCometScanExec { +trait ShimCometScanExec extends FileSourceScanLike { def wrapped: FileSourceScanExec - lazy val fileConstantMetadataColumns: Seq[AttributeReference] = + override lazy val fileConstantMetadataColumns: Seq[AttributeReference] = wrapped.fileConstantMetadataColumns protected def newDataSourceRDD( @@ -80,4 +80,11 @@ trait ShimCometScanExec { maxSplitBytes: Long, partitionValues: InternalRow): Seq[PartitionedFile] = PartitionedFileUtil.splitFiles(file, isSplitable, maxSplitBytes, partitionValues) + + @transient override lazy val selectedPartitions: ScanFileListing = wrapped.selectedPartitions + + // exposed for testing + override lazy val bucketedScan: Boolean = wrapped.bucketedScan + + lazy val inputRDD = wrapped.inputRDD } From 6b398da9a81ecf8aeda7bbf773c9d709cf867e78 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Sat, 25 May 2024 01:49:12 -0700 Subject: [PATCH 43/68] Revert "wip" This reverts commit 77fcaf1dbca0120336c9698de73358aedc6ee79a. --- .../spark/sql/comet/CometScanExec.scala | 90 ++++++++++++++++++- .../sql/comet/shims/ShimCometScanExec.scala | 89 +----------------- .../sql/comet/shims/ShimCometScanExec.scala | 13 +-- 3 files changed, 93 insertions(+), 99 deletions(-) diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala b/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala index 873efca3a..9a5b55d65 100644 --- a/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala +++ b/spark/src/main/scala/org/apache/spark/sql/comet/CometScanExec.scala @@ -61,7 +61,8 @@ case class CometScanExec( tableIdentifier: Option[TableIdentifier], disableBucketedScan: Boolean = false, wrapped: FileSourceScanExec) - extends ShimCometScanExec + extends DataSourceScanExec + with ShimCometScanExec with CometPlan { // FIXME: ideally we should reuse wrapped.supportsColumnar, however that fails many tests @@ -88,6 +89,48 @@ case class CometScanExec( private def isDynamicPruningFilter(e: Expression): Boolean = e.find(_.isInstanceOf[PlanExpression[_]]).isDefined + @transient lazy val selectedPartitions: Array[PartitionDirectory] = { + val optimizerMetadataTimeNs = relation.location.metadataOpsTimeNs.getOrElse(0L) + val startTime = System.nanoTime() + val ret = + relation.location.listFiles(partitionFilters.filterNot(isDynamicPruningFilter), dataFilters) + setFilesNumAndSizeMetric(ret, true) + val timeTakenMs = + NANOSECONDS.toMillis((System.nanoTime() - startTime) + optimizerMetadataTimeNs) + driverMetrics("metadataTime") = timeTakenMs + ret + }.toArray + + // We can only determine the actual partitions at runtime when a dynamic partition filter is + // present. This is because such a filter relies on information that is only available at run + // time (for instance the keys used in the other side of a join). + @transient private lazy val dynamicallySelectedPartitions: Array[PartitionDirectory] = { + val dynamicPartitionFilters = partitionFilters.filter(isDynamicPruningFilter) + + if (dynamicPartitionFilters.nonEmpty) { + val startTime = System.nanoTime() + // call the file index for the files matching all filters except dynamic partition filters + val predicate = dynamicPartitionFilters.reduce(And) + val partitionColumns = relation.partitionSchema + val boundPredicate = Predicate.create( + predicate.transform { case a: AttributeReference => + val index = partitionColumns.indexWhere(a.name == _.name) + BoundReference(index, partitionColumns(index).dataType, nullable = true) + }, + Nil) + val ret = selectedPartitions.filter(p => boundPredicate.eval(p.values)) + setFilesNumAndSizeMetric(ret, false) + val timeTakenMs = (System.nanoTime() - startTime) / 1000 / 1000 + driverMetrics("pruningTime") = timeTakenMs + ret + } else { + selectedPartitions + } + } + + // exposed for testing + lazy val bucketedScan: Boolean = wrapped.bucketedScan + override lazy val (outputPartitioning, outputOrdering): (Partitioning, Seq[SortOrder]) = (wrapped.outputPartitioning, wrapped.outputOrdering) @@ -105,10 +148,55 @@ case class CometScanExec( wrapped.verboseStringWithOperatorId() } + lazy val inputRDD: RDD[InternalRow] = { + val options = relation.options + + (ShimFileFormat.OPTION_RETURNING_BATCH -> supportsColumnar.toString) + val readFile: (PartitionedFile) => Iterator[InternalRow] = + relation.fileFormat.buildReaderWithPartitionValues( + sparkSession = relation.sparkSession, + dataSchema = relation.dataSchema, + partitionSchema = relation.partitionSchema, + requiredSchema = requiredSchema, + filters = pushedDownFilters, + options = options, + hadoopConf = + relation.sparkSession.sessionState.newHadoopConfWithOptions(relation.options)) + + val readRDD = if (bucketedScan) { + createBucketedReadRDD( + relation.bucketSpec.get, + readFile, + dynamicallySelectedPartitions, + relation) + } else { + createReadRDD(readFile, dynamicallySelectedPartitions, relation) + } + sendDriverMetrics() + readRDD + } + override def inputRDDs(): Seq[RDD[InternalRow]] = { inputRDD :: Nil } + /** Helper for computing total number and size of files in selected partitions. */ + private def setFilesNumAndSizeMetric( + partitions: Seq[PartitionDirectory], + static: Boolean): Unit = { + val filesNum = partitions.map(_.files.size.toLong).sum + val filesSize = partitions.map(_.files.map(_.getLen).sum).sum + if (!static || !partitionFilters.exists(isDynamicPruningFilter)) { + driverMetrics("numFiles") = filesNum + driverMetrics("filesSize") = filesSize + } else { + driverMetrics("staticFilesNum") = filesNum + driverMetrics("staticFilesSize") = filesSize + } + if (relation.partitionSchema.nonEmpty) { + driverMetrics("numPartitions") = partitions.length + } + } + override lazy val metrics: Map[String, SQLMetric] = wrapped.metrics ++ { // Tracking scan time has overhead, we can't afford to do it for each row, and can only do // it for each batch. diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala index f3e2b65da..02b97f9fb 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala @@ -37,7 +37,7 @@ import org.apache.spark.sql.execution.datasources.v2.DataSourceRDD import org.apache.spark.sql.execution.metric.SQLMetric import org.apache.spark.sql.types.{LongType, StructField, StructType} -trait ShimCometScanExec extends DataSourceScanExec { +trait ShimCometScanExec { def wrapped: FileSourceScanExec // TODO: remove after dropping Spark 3.2 support and directly call wrapped.metadataColumns @@ -138,91 +138,4 @@ trait ShimCometScanExec extends DataSourceScanExec { maxSplitBytes: Long, partitionValues: InternalRow): Seq[PartitionedFile] = PartitionedFileUtil.splitFiles(sparkSession, file, filePath, isSplitable, maxSplitBytes, partitionValues) - - @transient lazy val selectedPartitions: Array[PartitionDirectory] = { - val optimizerMetadataTimeNs = relation.location.metadataOpsTimeNs.getOrElse(0L) - val startTime = System.nanoTime() - val ret = - relation.location.listFiles(partitionFilters.filterNot(isDynamicPruningFilter), dataFilters) - setFilesNumAndSizeMetric(ret, true) - val timeTakenMs = - NANOSECONDS.toMillis((System.nanoTime() - startTime) + optimizerMetadataTimeNs) - driverMetrics("metadataTime") = timeTakenMs - ret - }.toArray - - // We can only determine the actual partitions at runtime when a dynamic partition filter is - // present. This is because such a filter relies on information that is only available at run - // time (for instance the keys used in the other side of a join). - @transient private lazy val dynamicallySelectedPartitions: Array[PartitionDirectory] = { - val dynamicPartitionFilters = partitionFilters.filter(isDynamicPruningFilter) - - if (dynamicPartitionFilters.nonEmpty) { - val startTime = System.nanoTime() - // call the file index for the files matching all filters except dynamic partition filters - val predicate = dynamicPartitionFilters.reduce(And) - val partitionColumns = relation.partitionSchema - val boundPredicate = Predicate.create( - predicate.transform { case a: AttributeReference => - val index = partitionColumns.indexWhere(a.name == _.name) - BoundReference(index, partitionColumns(index).dataType, nullable = true) - }, - Nil) - val ret = selectedPartitions.filter(p => boundPredicate.eval(p.values)) - setFilesNumAndSizeMetric(ret, false) - val timeTakenMs = (System.nanoTime() - startTime) / 1000 / 1000 - driverMetrics("pruningTime") = timeTakenMs - ret - } else { - selectedPartitions - } - } - - // exposed for testing - lazy val bucketedScan: Boolean = wrapped.bucketedScan - - lazy val inputRDD: RDD[InternalRow] = { - val options = relation.options + - (ShimFileFormat.OPTION_RETURNING_BATCH -> supportsColumnar.toString) - val readFile: (PartitionedFile) => Iterator[InternalRow] = - relation.fileFormat.buildReaderWithPartitionValues( - sparkSession = relation.sparkSession, - dataSchema = relation.dataSchema, - partitionSchema = relation.partitionSchema, - requiredSchema = requiredSchema, - filters = pushedDownFilters, - options = options, - hadoopConf = - relation.sparkSession.sessionState.newHadoopConfWithOptions(relation.options)) - - val readRDD = if (bucketedScan) { - createBucketedReadRDD( - relation.bucketSpec.get, - readFile, - dynamicallySelectedPartitions, - relation) - } else { - createReadRDD(readFile, dynamicallySelectedPartitions, relation) - } - sendDriverMetrics() - readRDD - } - - /** Helper for computing total number and size of files in selected partitions. */ - private def setFilesNumAndSizeMetric( - partitions: Seq[PartitionDirectory], - static: Boolean): Unit = { - val filesNum = partitions.map(_.files.size.toLong).sum - val filesSize = partitions.map(_.files.map(_.getLen).sum).sum - if (!static || !partitionFilters.exists(isDynamicPruningFilter)) { - driverMetrics("numFiles") = filesNum - driverMetrics("filesSize") = filesSize - } else { - driverMetrics("staticFilesNum") = filesNum - driverMetrics("staticFilesSize") = filesSize - } - if (relation.partitionSchema.nonEmpty) { - driverMetrics("numPartitions") = partitions.length - } - } } diff --git a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala index 70712e2dc..543116c10 100644 --- a/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-4.0/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala @@ -30,14 +30,14 @@ import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.datasources.v2.DataSourceRDD import org.apache.spark.sql.execution.datasources._ import org.apache.spark.sql.execution.metric.SQLMetric -import org.apache.spark.sql.execution.{FileSourceScanExec, FileSourceScanLike, PartitionedFileUtil, ScanFileListing} +import org.apache.spark.sql.execution.{FileSourceScanExec, PartitionedFileUtil} import org.apache.spark.sql.types.StructType import org.apache.spark.SparkContext -trait ShimCometScanExec extends FileSourceScanLike { +trait ShimCometScanExec { def wrapped: FileSourceScanExec - override lazy val fileConstantMetadataColumns: Seq[AttributeReference] = + lazy val fileConstantMetadataColumns: Seq[AttributeReference] = wrapped.fileConstantMetadataColumns protected def newDataSourceRDD( @@ -80,11 +80,4 @@ trait ShimCometScanExec extends FileSourceScanLike { maxSplitBytes: Long, partitionValues: InternalRow): Seq[PartitionedFile] = PartitionedFileUtil.splitFiles(file, isSplitable, maxSplitBytes, partitionValues) - - @transient override lazy val selectedPartitions: ScanFileListing = wrapped.selectedPartitions - - // exposed for testing - override lazy val bucketedScan: Boolean = wrapped.bucketedScan - - lazy val inputRDD = wrapped.inputRDD } From b6662a2d0acd44641af5aafc07fdee4b465ec13d Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 28 May 2024 17:39:50 -0700 Subject: [PATCH 44/68] build: Enable spark-4.0 Spark tests --- dev/diffs/4.0.0.diff | 579 +++++++++++++++++++++---------------------- 1 file changed, 282 insertions(+), 297 deletions(-) diff --git a/dev/diffs/4.0.0.diff b/dev/diffs/4.0.0.diff index 19bf6dd41..e61d36d91 100644 --- a/dev/diffs/4.0.0.diff +++ b/dev/diffs/4.0.0.diff @@ -1,17 +1,17 @@ diff --git a/pom.xml b/pom.xml -index fab98342498..f2156d790d1 100644 +index 6bbcf05b59e..59300f94bef 100644 --- a/pom.xml +++ b/pom.xml -@@ -148,6 +148,8 @@ +@@ -147,6 +147,8 @@ 0.10.0 - 2.5.1 + 2.5.2 2.0.8 -+ 3.4 ++ 4.0 + 0.1.0-SNAPSHOT + + org.apache.datasketches diff --git a/sql/core/pom.xml b/sql/core/pom.xml -index 5b6cc8cb7af..5ce708adc38 100644 +index 59d798e6e62..270768842c9 100644 --- a/sql/core/pom.xml +++ b/sql/core/pom.xml @@ -77,6 +77,10 @@ @@ -53,28 +53,10 @@ index 5b6cc8cb7af..5ce708adc38 100644 - 2.13.13 + 2.13.14 2.13 4.0.0-preview1 4.0 From 2db760d83b7deb1589fd441af93f482423a368ff Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 6 Jun 2024 13:03:35 -0700 Subject: [PATCH 54/68] build: Enable spark-4.0 Spark tests --- .github/workflows/spark_sql_test_ansi.yml | 1 + pom.xml | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/spark_sql_test_ansi.yml b/.github/workflows/spark_sql_test_ansi.yml index e312807fd..85c63b58b 100644 --- a/.github/workflows/spark_sql_test_ansi.yml +++ b/.github/workflows/spark_sql_test_ansi.yml @@ -75,6 +75,7 @@ jobs: - name: Run Spark tests run: | cd apache-spark + build/sbt clean package ENABLE_COMET=true ENABLE_COMET_ANSI_MODE=true build/sbt ${{ matrix.module.args1 }} "${{ matrix.module.args2 }}" env: LC_ALL: "C.UTF-8" diff --git a/pom.xml b/pom.xml index 0b0a69360..87a21b244 100644 --- a/pom.xml +++ b/pom.xml @@ -626,7 +626,7 @@ under the License. org.scalameta semanticdb-scalac_${scala.version} - 4.8.8 + 4.8.15 From d82a2330e9d280a56e47e5d33407282e50a16536 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 6 Jun 2024 13:21:14 -0700 Subject: [PATCH 55/68] build: Enable spark-4.0 Spark tests --- .github/workflows/spark_sql_test_ansi.yml | 2 +- pom.xml | 4 +++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/.github/workflows/spark_sql_test_ansi.yml b/.github/workflows/spark_sql_test_ansi.yml index 85c63b58b..caf93fe9e 100644 --- a/.github/workflows/spark_sql_test_ansi.yml +++ b/.github/workflows/spark_sql_test_ansi.yml @@ -75,7 +75,7 @@ jobs: - name: Run Spark tests run: | cd apache-spark - build/sbt clean package + rm -rf /root/.m2/repository/org/apache/parquet ENABLE_COMET=true ENABLE_COMET_ANSI_MODE=true build/sbt ${{ matrix.module.args1 }} "${{ matrix.module.args2 }}" env: LC_ALL: "C.UTF-8" diff --git a/pom.xml b/pom.xml index 87a21b244..837dd959b 100644 --- a/pom.xml +++ b/pom.xml @@ -57,6 +57,7 @@ under the License. 1.9.13 2.43.0 0.8.11 + 4.8.8 ${project.basedir}/../core/target/debug darwin x86_64 @@ -542,6 +543,7 @@ under the License. 4.0.0-preview1 4.0 1.13.1 + 4.9.5 spark-4.0 not-needed-yet @@ -626,7 +628,7 @@ under the License. org.scalameta semanticdb-scalac_${scala.version} - 4.8.15 + ${semanticdb.version} From 0d0b22b66f13069b9d48b9d86ba7b7ebfc4408c6 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 6 Jun 2024 15:08:45 -0700 Subject: [PATCH 56/68] build: Enable spark-4.0 Spark tests --- .github/workflows/spark_sql_test_ansi.yml | 1 - pom.xml | 24 +++++++++++++++++++++++ 2 files changed, 24 insertions(+), 1 deletion(-) diff --git a/.github/workflows/spark_sql_test_ansi.yml b/.github/workflows/spark_sql_test_ansi.yml index caf93fe9e..e312807fd 100644 --- a/.github/workflows/spark_sql_test_ansi.yml +++ b/.github/workflows/spark_sql_test_ansi.yml @@ -75,7 +75,6 @@ jobs: - name: Run Spark tests run: | cd apache-spark - rm -rf /root/.m2/repository/org/apache/parquet ENABLE_COMET=true ENABLE_COMET_ANSI_MODE=true build/sbt ${{ matrix.module.args1 }} "${{ matrix.module.args2 }}" env: LC_ALL: "C.UTF-8" diff --git a/pom.xml b/pom.xml index 837dd959b..8ee7e09c3 100644 --- a/pom.xml +++ b/pom.xml @@ -167,6 +167,10 @@ under the License. com.google.code.findbugs jsr305 + + org.slf4j + slf4j-api + @@ -178,6 +182,12 @@ under the License. org.apache.arrow arrow-c-data ${arrow.version} + + + org.slf4j + slf4j-api + + @@ -186,6 +196,12 @@ under the License. parquet-column ${parquet.version} ${parquet.maven.scope} + + + org.slf4j + slf4j-api + + org.apache.parquet @@ -198,6 +214,10 @@ under the License. javax.annotation javax.annotation-api + + org.slf4j + slf4j-api + @@ -218,6 +238,10 @@ under the License. javax.annotation javax.annotation-api + + org.slf4j + slf4j-api + From 5988fffd597deb80ae690807b781f8739be6f0c2 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Thu, 6 Jun 2024 15:26:36 -0700 Subject: [PATCH 57/68] build: Enable spark-4.0 Spark tests --- .github/workflows/spark_sql_test_ansi.yml | 1 + pom.xml | 34 +++++++---------------- 2 files changed, 11 insertions(+), 24 deletions(-) diff --git a/.github/workflows/spark_sql_test_ansi.yml b/.github/workflows/spark_sql_test_ansi.yml index e312807fd..b2f93861a 100644 --- a/.github/workflows/spark_sql_test_ansi.yml +++ b/.github/workflows/spark_sql_test_ansi.yml @@ -75,6 +75,7 @@ jobs: - name: Run Spark tests run: | cd apache-spark + rm -rf /root/.m2/repository/org/apache/parquet # somehow parquet cache requires cleanups ENABLE_COMET=true ENABLE_COMET_ANSI_MODE=true build/sbt ${{ matrix.module.args1 }} "${{ matrix.module.args2 }}" env: LC_ALL: "C.UTF-8" diff --git a/pom.xml b/pom.xml index 8ee7e09c3..c89b05884 100644 --- a/pom.xml +++ b/pom.xml @@ -58,6 +58,7 @@ under the License. 2.43.0 0.8.11 4.8.8 + 2.0.6 ${project.basedir}/../core/target/debug darwin x86_64 @@ -167,10 +168,6 @@ under the License. com.google.code.findbugs jsr305 - - org.slf4j - slf4j-api - @@ -182,12 +179,6 @@ under the License. org.apache.arrow arrow-c-data ${arrow.version} - - - org.slf4j - slf4j-api - - @@ -196,12 +187,6 @@ under the License. parquet-column ${parquet.version} ${parquet.maven.scope} - - - org.slf4j - slf4j-api - - org.apache.parquet @@ -214,10 +199,6 @@ under the License. javax.annotation javax.annotation-api - - org.slf4j - slf4j-api - @@ -238,10 +219,6 @@ under the License. javax.annotation javax.annotation-api - - org.slf4j - slf4j-api - @@ -256,6 +233,12 @@ under the License. protobuf-java ${protobuf.version} + + org.slf4j + slf4j-api + ${slf4j.version} + ${spark.maven.scope} + not-needed-yet not-needed-yet @@ -544,6 +528,7 @@ under the License. 3.3.2 3.3 1.12.0 + 1.7.32 not-needed-yet spark-3.3 @@ -568,6 +553,7 @@ under the License. 4.0 1.13.1 4.9.5 + 2.0.13 spark-4.0 not-needed-yet From c1d90aabbd655e2fa9235da8a10100f7bcbda8e6 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Fri, 7 Jun 2024 01:02:13 -0700 Subject: [PATCH 58/68] build: Enable spark-4.0 Spark tests --- .github/workflows/spark_sql_test_ansi.yml | 2 +- .../scala/org/apache/comet/serde/QueryPlanSerde.scala | 8 +++++--- .../spark-3.2/org/apache/comet/shims/CometExprShim.scala | 7 +++++++ .../spark-3.3/org/apache/comet/shims/CometExprShim.scala | 6 ++++++ .../spark-3.4/org/apache/comet/shims/CometExprShim.scala | 6 ++++++ .../spark-4.0/org/apache/comet/shims/CometExprShim.scala | 6 ++++++ 6 files changed, 31 insertions(+), 4 deletions(-) diff --git a/.github/workflows/spark_sql_test_ansi.yml b/.github/workflows/spark_sql_test_ansi.yml index b2f93861a..c7d5ad7e3 100644 --- a/.github/workflows/spark_sql_test_ansi.yml +++ b/.github/workflows/spark_sql_test_ansi.yml @@ -76,7 +76,7 @@ jobs: run: | cd apache-spark rm -rf /root/.m2/repository/org/apache/parquet # somehow parquet cache requires cleanups - ENABLE_COMET=true ENABLE_COMET_ANSI_MODE=true build/sbt ${{ matrix.module.args1 }} "${{ matrix.module.args2 }}" + RUST_BACKTRACE=1 ENABLE_COMET=true ENABLE_COMET_ANSI_MODE=true build/sbt ${{ matrix.module.args1 }} "${{ matrix.module.args2 }}" env: LC_ALL: "C.UTF-8" diff --git a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala index 8d81b57c4..7dfe52dc1 100644 --- a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala +++ b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala @@ -66,7 +66,7 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde with CometExprShim _: DateType | _: BooleanType | _: NullType => true // `TimestampNTZType` is private in Spark 3.2. - case dt if dt.typeName == "timestamp_ntz" => true + case dt if isTimestampNTZType(dt) => true case dt => emitWarning(s"unsupported Spark data type: $dt") false @@ -90,7 +90,7 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde with CometExprShim case _: BinaryType => 8 case _: TimestampType => 9 case _: DecimalType => 10 - case dt if dt.typeName == "timestamp_ntz" => 11 + case dt if isTimestampNTZType(dt) => 11 case _: DateType => 12 case _: NullType => 13 case _: ArrayType => 14 @@ -1047,6 +1047,8 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde with CometExprShim com.google.protobuf.ByteString.copyFrom(value.asInstanceOf[Array[Byte]]) exprBuilder.setBytesVal(byteStr) case _: DateType => exprBuilder.setIntVal(value.asInstanceOf[Int]) + case dt if isTimestampNTZType(dt) => + exprBuilder.setLongVal(value.asInstanceOf[Long]) case dt => logWarning(s"Unexpected date type '$dt' for literal value '$value'") } @@ -2258,7 +2260,7 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde with CometExprShim _: DoubleType | _: StringType | _: DateType | _: DecimalType | _: BooleanType => true // `TimestampNTZType` is private in Spark 3.2/3.3. - case dt if dt.typeName == "timestamp_ntz" => true + case dt if isTimestampNTZType(dt) => true case _ => false } diff --git a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala index f5a578f82..b2d8566eb 100644 --- a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala @@ -19,6 +19,7 @@ package org.apache.comet.shims import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.types.DataType /** * `CometExprShim` acts as a shim for for parsing expressions from different Spark versions. @@ -30,4 +31,10 @@ trait CometExprShim { def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(false)) } + + protected def isTimestampNTZType(dt: DataType): Boolean = dt match { + // `TimestampNTZType` is private in Spark 3.2. + case dt if dt.typeName == "timestamp_ntz" => true + case _ => false + } } diff --git a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala index f5a578f82..5a89e16fb 100644 --- a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala @@ -19,6 +19,7 @@ package org.apache.comet.shims import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.types.{DataType, TimestampNTZType} /** * `CometExprShim` acts as a shim for for parsing expressions from different Spark versions. @@ -30,4 +31,9 @@ trait CometExprShim { def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(false)) } + + protected def isTimestampNTZType(dt: DataType): Boolean = dt match { + case _: TimestampNTZType => true + case _ => false + } } diff --git a/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala index 3f2301f0a..14d228248 100644 --- a/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.4/org/apache/comet/shims/CometExprShim.scala @@ -19,6 +19,7 @@ package org.apache.comet.shims import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.types.{DataType, TimestampNTZType} /** * `CometExprShim` acts as a shim for for parsing expressions from different Spark versions. @@ -30,4 +31,9 @@ trait CometExprShim { def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(unhex.failOnError)) } + + protected def isTimestampNTZType(dt: DataType): Boolean = dt match { + case _: TimestampNTZType => true + case _ => false + } } diff --git a/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala index 01f923206..1f2b50bf6 100644 --- a/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-4.0/org/apache/comet/shims/CometExprShim.scala @@ -19,6 +19,7 @@ package org.apache.comet.shims import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.types.{DataType, TimestampNTZType} /** * `CometExprShim` acts as a shim for for parsing expressions from different Spark versions. @@ -30,4 +31,9 @@ trait CometExprShim { protected def unhexSerde(unhex: Unhex): (Expression, Expression) = { (unhex.child, Literal(unhex.failOnError)) } + + protected def isTimestampNTZType(dt: DataType): Boolean = dt match { + case _: TimestampNTZType => true + case _ => false + } } From b980c0e97684b315d90703b661822d4cc242af96 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Fri, 7 Jun 2024 04:12:07 -0700 Subject: [PATCH 59/68] build: Enable spark-4.0 Spark tests --- .../org/apache/comet/parquet/BatchReader.java | 1 + .../apache/comet/shims/ShimFileFormat.scala | 18 ++++++++++++++++ .../apache/comet/shims/ShimFileFormat.scala | 5 +++++ .../apache/comet/shims/CometExprShim.scala | 2 +- .../apache/comet/shims/CometExprShim.scala | 5 +++-- .../sql/comet/shims/ShimCometScanExec.scala | 21 +++---------------- 6 files changed, 31 insertions(+), 21 deletions(-) diff --git a/common/src/main/java/org/apache/comet/parquet/BatchReader.java b/common/src/main/java/org/apache/comet/parquet/BatchReader.java index bf8e6e550..4b63f84ef 100644 --- a/common/src/main/java/org/apache/comet/parquet/BatchReader.java +++ b/common/src/main/java/org/apache/comet/parquet/BatchReader.java @@ -285,6 +285,7 @@ public void init() throws URISyntaxException, IOException { missingColumns = new boolean[columns.size()]; List paths = requestedSchema.getPaths(); StructField[] nonPartitionFields = sparkSchema.fields(); + ShimFileFormat.findRowIndexColumnIndexInSchema(sparkSchema); for (int i = 0; i < requestedSchema.getFieldCount(); i++) { Type t = requestedSchema.getFields().get(i); Preconditions.checkState( diff --git a/common/src/main/spark-3.x/org/apache/comet/shims/ShimFileFormat.scala b/common/src/main/spark-3.x/org/apache/comet/shims/ShimFileFormat.scala index 5ab7eaf4f..a5c541e96 100644 --- a/common/src/main/spark-3.x/org/apache/comet/shims/ShimFileFormat.scala +++ b/common/src/main/spark-3.x/org/apache/comet/shims/ShimFileFormat.scala @@ -19,6 +19,8 @@ package org.apache.comet.shims +import org.apache.spark.sql.types.{LongType, StructField, StructType} + object ShimFileFormat { // TODO: remove after dropping Spark 3.2 & 3.3 support and directly use FileFormat.ROW_INDEX @@ -32,4 +34,20 @@ object ShimFileFormat { // TODO: remove after dropping Spark 3.2 support and use FileFormat.OPTION_RETURNING_BATCH val OPTION_RETURNING_BATCH = "returning_batch" + + // TODO: remove after dropping Spark 3.2 & 3.3 support and directly use + // RowIndexUtil.findRowIndexColumnIndexInSchema + def findRowIndexColumnIndexInSchema(sparkSchema: StructType): Int = { + sparkSchema.fields.zipWithIndex.find { case (field: StructField, _: Int) => + field.name == ShimFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME + } match { + case Some((field: StructField, idx: Int)) => + if (field.dataType != LongType) { + throw new RuntimeException( + s"${ShimFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME} must be of LongType") + } + idx + case _ => -1 + } + } } diff --git a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala index 2f386869a..840b43fec 100644 --- a/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala +++ b/common/src/main/spark-4.0/org/apache/comet/shims/ShimFileFormat.scala @@ -21,6 +21,8 @@ package org.apache.comet.shims import org.apache.spark.sql.execution.datasources.FileFormat import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat +import org.apache.spark.sql.execution.datasources.parquet.ParquetRowIndexUtil +import org.apache.spark.sql.types.StructType object ShimFileFormat { // A name for a temporary column that holds row indexes computed by the file format reader @@ -28,4 +30,7 @@ object ShimFileFormat { val ROW_INDEX_TEMPORARY_COLUMN_NAME = ParquetFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME val OPTION_RETURNING_BATCH = FileFormat.OPTION_RETURNING_BATCH + + def findRowIndexColumnIndexInSchema(sparkSchema: StructType): Int = + ParquetRowIndexUtil.findRowIndexColumnIndexInSchema(sparkSchema) } diff --git a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala index b2d8566eb..a4cc9b44c 100644 --- a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala @@ -33,7 +33,7 @@ trait CometExprShim { } protected def isTimestampNTZType(dt: DataType): Boolean = dt match { - // `TimestampNTZType` is private in Spark 3.2. + // `TimestampNTZType` is private case dt if dt.typeName == "timestamp_ntz" => true case _ => false } diff --git a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala index 5a89e16fb..a4cc9b44c 100644 --- a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala @@ -19,7 +19,7 @@ package org.apache.comet.shims import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.types.{DataType, TimestampNTZType} +import org.apache.spark.sql.types.DataType /** * `CometExprShim` acts as a shim for for parsing expressions from different Spark versions. @@ -33,7 +33,8 @@ trait CometExprShim { } protected def isTimestampNTZType(dt: DataType): Boolean = dt match { - case _: TimestampNTZType => true + // `TimestampNTZType` is private + case dt if dt.typeName == "timestamp_ntz" => true case _ => false } } diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala index 02b97f9fb..818f03719 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala @@ -35,7 +35,7 @@ import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, H import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.datasources.v2.DataSourceRDD import org.apache.spark.sql.execution.metric.SQLMetric -import org.apache.spark.sql.types.{LongType, StructField, StructType} +import org.apache.spark.sql.types.StructType trait ShimCometScanExec { def wrapped: FileSourceScanExec @@ -108,24 +108,9 @@ trait ShimCometScanExec { } } - // Copied from Spark 3.4 RowIndexUtil due to PARQUET-2161 (tracked in SPARK-39634) - // TODO: remove after PARQUET-2161 becomes available in Parquet - private def findRowIndexColumnIndexInSchema(sparkSchema: StructType): Int = { - sparkSchema.fields.zipWithIndex.find { case (field: StructField, _: Int) => - field.name == ShimFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME - } match { - case Some((field: StructField, idx: Int)) => - if (field.dataType != LongType) { - throw new RuntimeException( - s"${ShimFileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME} must be of LongType") - } - idx - case _ => -1 - } - } - protected def isNeededForSchema(sparkSchema: StructType): Boolean = { - findRowIndexColumnIndexInSchema(sparkSchema) >= 0 + // TODO: remove after PARQUET-2161 becomes available in Parquet (tracked in SPARK-39634) + ShimFileFormat.findRowIndexColumnIndexInSchema(sparkSchema) >= 0 } protected def getPartitionedFile(f: FileStatus, p: PartitionDirectory): PartitionedFile = From 1a386bc56158d7addf954e170b3821978b7a11fb Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Fri, 7 Jun 2024 23:41:20 -0700 Subject: [PATCH 60/68] build: Enable spark-4.0 Spark tests --- .../src/main/java/org/apache/comet/parquet/TypeUtil.java | 9 ++++++++- .../scala/org/apache/comet/serde/QueryPlanSerde.scala | 2 -- 2 files changed, 8 insertions(+), 3 deletions(-) diff --git a/common/src/main/java/org/apache/comet/parquet/TypeUtil.java b/common/src/main/java/org/apache/comet/parquet/TypeUtil.java index b8b7ff525..5bd5896d1 100644 --- a/common/src/main/java/org/apache/comet/parquet/TypeUtil.java +++ b/common/src/main/java/org/apache/comet/parquet/TypeUtil.java @@ -27,6 +27,7 @@ import org.apache.parquet.schema.PrimitiveType; import org.apache.parquet.schema.Type; import org.apache.parquet.schema.Types; +import org.apache.spark.package$; import org.apache.spark.sql.execution.datasources.SchemaColumnConvertNotSupportedException; import org.apache.spark.sql.types.*; @@ -169,6 +170,7 @@ && isUnsignedIntTypeMatched(logicalTypeAnnotation, 64)) { break; case INT96: if (sparkType == TimestampNTZType$.MODULE$) { + if (isSpark40Plus()) return; convertErrorForTimestampNTZ(typeName.name()); } else if (sparkType == DataTypes.TimestampType) { return; @@ -218,7 +220,8 @@ private static void validateTimestampType( // Throw an exception if the Parquet type is TimestampLTZ and the Catalyst type is TimestampNTZ. // This is to avoid mistakes in reading the timestamp values. if (((TimestampLogicalTypeAnnotation) logicalTypeAnnotation).isAdjustedToUTC() - && sparkType == TimestampNTZType$.MODULE$) { + && sparkType == TimestampNTZType$.MODULE$ + && !isSpark40Plus()) { convertErrorForTimestampNTZ("int64 time(" + logicalTypeAnnotation + ")"); } } @@ -278,4 +281,8 @@ private static boolean isUnsignedIntTypeMatched( && !((IntLogicalTypeAnnotation) logicalTypeAnnotation).isSigned() && ((IntLogicalTypeAnnotation) logicalTypeAnnotation).getBitWidth() == bitWidth; } + + private static boolean isSpark40Plus() { + return package$.MODULE$.SPARK_VERSION().compareTo("4.0") >= 0; + } } diff --git a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala index 24c7e1452..079db0306 100644 --- a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala +++ b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala @@ -63,7 +63,6 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde with CometExprShim _: DoubleType | _: StringType | _: BinaryType | _: TimestampType | _: DecimalType | _: DateType | _: BooleanType | _: NullType => true - // `TimestampNTZType` is private in Spark 3.2. case dt if isTimestampNTZType(dt) => true case dt => emitWarning(s"unsupported Spark data type: $dt") @@ -2246,7 +2245,6 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde with CometExprShim case _: ByteType | _: ShortType | _: IntegerType | _: LongType | _: FloatType | _: DoubleType | _: StringType | _: DateType | _: DecimalType | _: BooleanType => true - // `TimestampNTZType` is private in Spark 3.2/3.3. case dt if isTimestampNTZType(dt) => true case _ => false } From 9cf702d156b3366d18d89b181c79c6f1d170351b Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Mon, 10 Jun 2024 17:34:21 -0700 Subject: [PATCH 61/68] build: Enable spark-4.0 Spark tests --- dev/diffs/4.0.0-preview1.diff | 214 ++++++++++++++++++++++++++++++++-- pom.xml | 1 + 2 files changed, 207 insertions(+), 8 deletions(-) diff --git a/dev/diffs/4.0.0-preview1.diff b/dev/diffs/4.0.0-preview1.diff index 2621fe243..089e5fbb3 100644 --- a/dev/diffs/4.0.0-preview1.diff +++ b/dev/diffs/4.0.0-preview1.diff @@ -101,6 +101,19 @@ index 7c45b02ee84..9f2b608c9f5 100644 case _ => Map[String, String]() } new SparkPlanInfo( +diff --git a/sql/core/src/test/resources/sql-tests/inputs/collations.sql b/sql/core/src/test/resources/sql-tests/inputs/collations.sql +index 619eb4470e9..8465382a007 100644 +--- a/sql/core/src/test/resources/sql-tests/inputs/collations.sql ++++ b/sql/core/src/test/resources/sql-tests/inputs/collations.sql +@@ -1,5 +1,8 @@ + -- test cases for collation support + ++-- TODO: https://github.com/apache/datafusion-comet/issues/551 ++--SET spark.comet.enabled = false ++ + -- Create a test table with data + create table t1(utf8_binary string collate utf8_binary, utf8_binary_lcase string collate utf8_binary_lcase) using parquet; + insert into t1 values('aaa', 'aaa'); diff --git a/sql/core/src/test/resources/sql-tests/inputs/explain-aqe.sql b/sql/core/src/test/resources/sql-tests/inputs/explain-aqe.sql index 7aef901da4f..f3d6e18926d 100644 --- a/sql/core/src/test/resources/sql-tests/inputs/explain-aqe.sql @@ -161,6 +174,48 @@ index 41fd4de2a09..44cd244d3b0 100644 -- Test aggregate operator with codegen on and off. --CONFIG_DIM1 spark.sql.codegen.wholeStage=true --CONFIG_DIM1 spark.sql.codegen.wholeStage=false,spark.sql.codegen.factoryMode=CODEGEN_ONLY +diff --git a/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/float8.sql b/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/float8.sql +index 932cdb95fcf..bbafaadb960 100644 +--- a/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/float8.sql ++++ b/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/float8.sql +@@ -5,6 +5,9 @@ + -- FLOAT8 + -- https://github.com/postgres/postgres/blob/REL_12_BETA2/src/test/regress/sql/float8.sql + ++-- TODO: https://github.com/apache/datafusion-comet/issues/551 ++--SET spark.comet.enabled = false ++ + CREATE TABLE FLOAT8_TBL(f1 double) USING parquet; + + -- PostgreSQL implicitly casts string literals to data with floating point types, but +diff --git a/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/groupingsets.sql b/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/groupingsets.sql +index f06b0276b00..1f39a1b3da8 100644 +--- a/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/groupingsets.sql ++++ b/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/groupingsets.sql +@@ -5,6 +5,9 @@ + + -- test data sources + ++-- TODO: https://github.com/apache/datafusion-comet/issues/551 ++--SET spark.comet.enabled = false ++ + create temp view gstest1(a,b,v) + as values (1,1,10),(1,1,11),(1,2,12),(1,2,13),(1,3,14), + (2,3,15), +diff --git a/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/int4.sql b/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/int4.sql +index 3a409eea348..26e9aaf215c 100644 +--- a/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/int4.sql ++++ b/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/int4.sql +@@ -6,6 +6,9 @@ + -- https://github.com/postgres/postgres/blob/REL_12_BETA2/src/test/regress/sql/int4.sql + -- + ++-- TODO: https://github.com/apache/datafusion-comet/issues/551 ++--SET spark.comet.enabled = false ++ + CREATE TABLE INT4_TBL(f1 int) USING parquet; + + -- [SPARK-28023] Trim the string when cast string type to other types diff --git a/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/int8.sql b/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/int8.sql index fac23b4a26f..2b73732c33f 100644 --- a/sql/core/src/test/resources/sql-tests/inputs/postgreSQL/int8.sql @@ -191,6 +246,33 @@ index 0efe0877e9b..423d3b3d76d 100644 -- -- SELECT_HAVING -- https://github.com/postgres/postgres/blob/REL_12_BETA2/src/test/regress/sql/select_having.sql +diff --git a/sql/core/src/test/resources/sql-tests/inputs/view-schema-binding-config.sql b/sql/core/src/test/resources/sql-tests/inputs/view-schema-binding-config.sql +index e803254ea64..74db78aee38 100644 +--- a/sql/core/src/test/resources/sql-tests/inputs/view-schema-binding-config.sql ++++ b/sql/core/src/test/resources/sql-tests/inputs/view-schema-binding-config.sql +@@ -1,6 +1,9 @@ + -- This test suits check the spark.sql.viewSchemaBindingMode configuration. + -- It can be DISABLED and COMPENSATION + ++-- TODO: https://github.com/apache/datafusion-comet/issues/551 ++--SET spark.comet.enabled = false ++ + -- Verify the default binding is true + SET spark.sql.legacy.viewSchemaBindingMode; + +diff --git a/sql/core/src/test/resources/sql-tests/inputs/view-schema-compensation.sql b/sql/core/src/test/resources/sql-tests/inputs/view-schema-compensation.sql +index 21a3ce1e122..316788b2989 100644 +--- a/sql/core/src/test/resources/sql-tests/inputs/view-schema-compensation.sql ++++ b/sql/core/src/test/resources/sql-tests/inputs/view-schema-compensation.sql +@@ -1,4 +1,8 @@ + -- This test suite checks the WITH SCHEMA COMPENSATION clause ++ ++-- TODO: https://github.com/apache/datafusion-comet/issues/551 ++--SET spark.comet.enabled = false ++ + -- Disable ANSI mode to ensure we are forcing it explicitly in the CASTS + SET spark.sql.ansi.enabled = false; + diff --git a/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala index d023fb82185..3774fa99148 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala @@ -684,7 +766,7 @@ index 34c6c49bc49..f5dea07a213 100644 protected val baseResourcePath = { // use the same way as `SQLQueryTestSuite` to get the resource path diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala -index 56c364e2084..a00a50e020a 100644 +index 56c364e2084..11779ee3b4b 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala @@ -1510,7 +1510,8 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark @@ -697,8 +779,48 @@ index 56c364e2084..a00a50e020a 100644 AccumulatorSuite.verifyPeakExecutionMemorySet(sparkContext, "external sort") { sql("SELECT * FROM testData2 ORDER BY a ASC, b ASC").collect() } +@@ -4454,7 +4455,8 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark + } + + test("SPARK-39166: Query context of binary arithmetic should be serialized to executors" + +- " when WSCG is off") { ++ " when WSCG is off", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withSQLConf(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key -> "false", + SQLConf.ANSI_ENABLED.key -> "true") { + withTable("t") { +@@ -4475,7 +4477,8 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark + } + + test("SPARK-39175: Query context of Cast should be serialized to executors" + +- " when WSCG is off") { ++ " when WSCG is off", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withSQLConf(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key -> "false", + SQLConf.ANSI_ENABLED.key -> "true") { + withTable("t") { +@@ -4502,7 +4505,8 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark + } + + test("SPARK-39190,SPARK-39208,SPARK-39210: Query context of decimal overflow error should " + +- "be serialized to executors when WSCG is off") { ++ "be serialized to executors when WSCG is off", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withSQLConf(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key -> "false", + SQLConf.ANSI_ENABLED.key -> "true") { + withTable("t") { +@@ -4639,7 +4643,8 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark + Row(1, 2, 3, 1, 2, 3, 1, 1)) + } + +- test("SPARK-40389: Don't eliminate a cast which can cause overflow") { ++ test("SPARK-40389: Don't eliminate a cast which can cause overflow", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withSQLConf(SQLConf.ANSI_ENABLED.key -> "true") { + withTable("dt") { + sql("create table dt using parquet as select 9000000000BD as d") diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SubquerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SubquerySuite.scala -index 68f14f13bbd..c76f9213946 100644 +index 68f14f13bbd..4b8e967102f 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/SubquerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/SubquerySuite.scala @@ -22,10 +22,11 @@ import scala.collection.mutable.ArrayBuffer @@ -736,6 +858,16 @@ index 68f14f13bbd..c76f9213946 100644 } assert(exchanges.size === 1) } +@@ -2668,7 +2675,8 @@ class SubquerySuite extends QueryTest + } + } + +- test("SPARK-43402: FileSourceScanExec supports push down data filter with scalar subquery") { ++ test("SPARK-43402: FileSourceScanExec supports push down data filter with scalar subquery", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + def checkFileSourceScan(query: String, answer: Seq[Row]): Unit = { + val df = sql(query) + checkAnswer(df, answer) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2Suite.scala b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2Suite.scala index 1de535df246..cc7ffc4eeb3 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2Suite.scala @@ -1444,6 +1576,29 @@ index a7efd0aa75e..fa65bda2051 100644 } assert(shuffles2.size == 4) val smj2 = findTopLevelSortMergeJoin(adaptive2) +diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileSourceCustomMetadataStructSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileSourceCustomMetadataStructSuite.scala +index 05872d41131..0dd83608bbd 100644 +--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileSourceCustomMetadataStructSuite.scala ++++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileSourceCustomMetadataStructSuite.scala +@@ -21,7 +21,7 @@ import java.io.File + + import org.apache.hadoop.fs.{FileStatus, Path} + +-import org.apache.spark.sql.{DataFrame, Dataset, QueryTest, Row} ++import org.apache.spark.sql.{DataFrame, Dataset, IgnoreComet, QueryTest, Row} + import org.apache.spark.sql.catalyst.InternalRow + import org.apache.spark.sql.catalyst.expressions.{Expression, FileSourceConstantMetadataStructField, FileSourceGeneratedMetadataStructField, Literal} + import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat +@@ -134,7 +134,8 @@ class FileSourceCustomMetadataStructSuite extends QueryTest with SharedSparkSess + } + } + +- test("[SPARK-43226] extra constant metadata fields with extractors") { ++ test("[SPARK-43226] extra constant metadata fields with extractors", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withTempData("parquet", FILE_SCHEMA) { (_, f0, f1) => + val format = new TestFileFormat(extraConstantMetadataFields) { + val extractPartitionNumber = { pf: PartitionedFile => diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/SchemaPruningSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/SchemaPruningSuite.scala index 0a0b23d1e60..5685926250f 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/SchemaPruningSuite.scala @@ -1535,7 +1690,7 @@ index cd6f41b4ef4..4b6a17344bc 100644 ParquetOutputFormat.WRITER_VERSION -> ParquetProperties.WriterVersion.PARQUET_2_0.toString ) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala -index 795e9f46a8d..5306c94a686 100644 +index 795e9f46a8d..6285a1e388b 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala @@ -1100,7 +1100,11 @@ abstract class ParquetFilterSuite extends QueryTest with ParquetTest with Shared @@ -1597,7 +1752,17 @@ index 795e9f46a8d..5306c94a686 100644 // block 1: // null count min max // page-0 0 0 99 -@@ -2301,7 +2315,11 @@ class ParquetV1FilterSuite extends ParquetFilterSuite { +@@ -2211,7 +2225,8 @@ abstract class ParquetFilterSuite extends QueryTest with ParquetTest with Shared + } + } + +- test("SPARK-47120: subquery literal filter pushdown") { ++ test("SPARK-47120: subquery literal filter pushdown", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withTable("t1", "t2") { + sql("create table t1(d date) using parquet") + sql("create table t2(d date) using parquet") +@@ -2301,7 +2316,11 @@ class ParquetV1FilterSuite extends ParquetFilterSuite { assert(pushedParquetFilters.exists(_.getClass === filterClass), s"${pushedParquetFilters.map(_.getClass).toList} did not contain ${filterClass}.") @@ -1610,7 +1775,7 @@ index 795e9f46a8d..5306c94a686 100644 } else { assert(selectedFilters.isEmpty, "There is filter pushed down") } -@@ -2362,7 +2380,11 @@ class ParquetV2FilterSuite extends ParquetFilterSuite { +@@ -2362,7 +2381,11 @@ class ParquetV2FilterSuite extends ParquetFilterSuite { assert(pushedParquetFilters.exists(_.getClass === filterClass), s"${pushedParquetFilters.map(_.getClass).toList} did not contain ${filterClass}.") @@ -1638,10 +1803,20 @@ index 4fb8faa43a3..984fd1a9892 100644 checkAnswer( // "fruit" column in this file is encoded using DELTA_LENGTH_BYTE_ARRAY. diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala -index a329d3fdc3c..d29523a41f7 100644 +index a329d3fdc3c..437cf699887 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala -@@ -1042,7 +1042,8 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS +@@ -1024,7 +1024,8 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS + testMigration(fromTsType = "TIMESTAMP_MICROS", toTsType = "INT96") + } + +- test("SPARK-34212 Parquet should read decimals correctly") { ++ test("SPARK-34212 Parquet should read decimals correctly", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + def readParquet(schema: String, path: File): DataFrame = { + spark.read.schema(schema).parquet(path.toString) + } +@@ -1042,7 +1043,8 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS checkAnswer(readParquet(schema2, path), df) } @@ -1651,7 +1826,7 @@ index a329d3fdc3c..d29523a41f7 100644 val schema1 = "a DECIMAL(3, 2), b DECIMAL(18, 3), c DECIMAL(37, 3)" checkAnswer(readParquet(schema1, path), df) val schema2 = "a DECIMAL(3, 0), b DECIMAL(18, 1), c DECIMAL(37, 1)" -@@ -1066,7 +1067,8 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS +@@ -1066,7 +1068,8 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS val df = sql(s"SELECT 1 a, 123456 b, ${Int.MaxValue.toLong * 10} c, CAST('1.2' AS BINARY) d") df.write.parquet(path.toString) @@ -1754,6 +1929,29 @@ index 25f6af1cc33..37b40cb5524 100644 withTempPath { dir => val e = testSchemaMismatch(dir.getCanonicalPath, vectorizedReaderEnabled = false) val expectedMessage = "Encountered error while reading file" +diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetTypeWideningSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetTypeWideningSuite.scala +index 4bd35e0789b..6bfedb65078 100644 +--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetTypeWideningSuite.scala ++++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetTypeWideningSuite.scala +@@ -24,7 +24,7 @@ import org.apache.parquet.format.converter.ParquetMetadataConverter + import org.apache.parquet.hadoop.{ParquetFileReader, ParquetOutputFormat} + + import org.apache.spark.SparkException +-import org.apache.spark.sql.{DataFrame, QueryTest, Row} ++import org.apache.spark.sql.{DataFrame, IgnoreCometSuite, QueryTest, Row} + import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper + import org.apache.spark.sql.execution.datasources.SchemaColumnConvertNotSupportedException + import org.apache.spark.sql.functions.col +@@ -38,7 +38,8 @@ class ParquetTypeWideningSuite + extends QueryTest + with ParquetTest + with SharedSparkSession +- with AdaptiveSparkPlanHelper { ++ with AdaptiveSparkPlanHelper ++ with IgnoreCometSuite { // TODO: https://github.com/apache/datafusion-comet/issues/551 + + import testImplicits._ + diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/debug/DebuggingSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/debug/DebuggingSuite.scala index b8f3ea3c6f3..bbd44221288 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/debug/DebuggingSuite.scala diff --git a/pom.xml b/pom.xml index e162c2541..a88ae7bd4 100644 --- a/pom.xml +++ b/pom.xml @@ -563,6 +563,7 @@ under the License. + spark-4.0 From 8ce4344319baddd7b8beeeebae3de55e2dc00e1d Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Mon, 10 Jun 2024 22:16:16 -0700 Subject: [PATCH 62/68] build: Enable spark-4.0 Spark tests --- dev/diffs/4.0.0-preview1.diff | 108 +++++++++++++++++++++++++++++++--- 1 file changed, 100 insertions(+), 8 deletions(-) diff --git a/dev/diffs/4.0.0-preview1.diff b/dev/diffs/4.0.0-preview1.diff index 089e5fbb3..c9a80d074 100644 --- a/dev/diffs/4.0.0-preview1.diff +++ b/dev/diffs/4.0.0-preview1.diff @@ -415,7 +415,7 @@ index 16a493b5290..3f0b70e2d59 100644 assert(exchanges.size == 2) } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala -index 2c24cc7d570..d9564511e2d 100644 +index 2c24cc7d570..50a2ce86117 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala @@ -22,6 +22,7 @@ import org.scalatest.GivenWhenThen @@ -436,7 +436,37 @@ index 2c24cc7d570..d9564511e2d 100644 case _ => Nil } } -@@ -1187,7 +1191,8 @@ abstract class DynamicPartitionPruningSuiteBase +@@ -665,7 +669,8 @@ abstract class DynamicPartitionPruningSuiteBase + } + } + +- test("partition pruning in broadcast hash joins with aliases") { ++ test("partition pruning in broadcast hash joins with aliases", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + Given("alias with simple join condition, using attribute names only") + withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_REUSE_BROADCAST_ONLY.key -> "true") { + val df = sql( +@@ -755,7 +760,8 @@ abstract class DynamicPartitionPruningSuiteBase + } + } + +- test("partition pruning in broadcast hash joins") { ++ test("partition pruning in broadcast hash joins", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + Given("disable broadcast pruning and disable subquery duplication") + withSQLConf( + SQLConf.DYNAMIC_PARTITION_PRUNING_REUSE_BROADCAST_ONLY.key -> "true", +@@ -990,7 +996,8 @@ abstract class DynamicPartitionPruningSuiteBase + } + } + +- test("different broadcast subqueries with identical children") { ++ test("different broadcast subqueries with identical children", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_REUSE_BROADCAST_ONLY.key -> "true") { + withTable("fact", "dim") { + spark.range(100).select( +@@ -1187,7 +1194,8 @@ abstract class DynamicPartitionPruningSuiteBase } } @@ -446,7 +476,7 @@ index 2c24cc7d570..d9564511e2d 100644 withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_REUSE_BROADCAST_ONLY.key -> "true") { val df = sql( """ -@@ -1238,7 +1243,8 @@ abstract class DynamicPartitionPruningSuiteBase +@@ -1238,7 +1246,8 @@ abstract class DynamicPartitionPruningSuiteBase } } @@ -456,7 +486,27 @@ index 2c24cc7d570..d9564511e2d 100644 Given("dynamic pruning filter on the build side") withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_REUSE_BROADCAST_ONLY.key -> "true") { val df = sql( -@@ -1486,7 +1492,7 @@ abstract class DynamicPartitionPruningSuiteBase +@@ -1311,7 +1320,8 @@ abstract class DynamicPartitionPruningSuiteBase + } + } + +- test("SPARK-32817: DPP throws error when the broadcast side is empty") { ++ test("SPARK-32817: DPP throws error when the broadcast side is empty", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withSQLConf( + SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true", + SQLConf.DYNAMIC_PARTITION_PRUNING_REUSE_BROADCAST_ONLY.key -> "true", +@@ -1471,7 +1481,8 @@ abstract class DynamicPartitionPruningSuiteBase + checkAnswer(df, Row(3, 2) :: Row(3, 2) :: Row(3, 2) :: Row(3, 2) :: Nil) + } + +- test("SPARK-36444: Remove OptimizeSubqueries from batch of PartitionPruning") { ++ test("SPARK-36444: Remove OptimizeSubqueries from batch of PartitionPruning", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true") { + val df = sql( + """ +@@ -1486,7 +1497,7 @@ abstract class DynamicPartitionPruningSuiteBase } test("SPARK-38148: Do not add dynamic partition pruning if there exists static partition " + @@ -465,7 +515,37 @@ index 2c24cc7d570..d9564511e2d 100644 withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true") { Seq( "f.store_id = 1" -> false, -@@ -1730,6 +1736,8 @@ abstract class DynamicPartitionPruningV1Suite extends DynamicPartitionPruningDat +@@ -1558,7 +1569,8 @@ abstract class DynamicPartitionPruningSuiteBase + } + } + +- test("SPARK-38674: Remove useless deduplicate in SubqueryBroadcastExec") { ++ test("SPARK-38674: Remove useless deduplicate in SubqueryBroadcastExec", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withTable("duplicate_keys") { + withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true") { + Seq[(Int, String)]((1, "NL"), (1, "NL"), (3, "US"), (3, "US"), (3, "US")) +@@ -1589,7 +1601,8 @@ abstract class DynamicPartitionPruningSuiteBase + } + } + +- test("SPARK-39338: Remove dynamic pruning subquery if pruningKey's references is empty") { ++ test("SPARK-39338: Remove dynamic pruning subquery if pruningKey's references is empty", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true") { + val df = sql( + """ +@@ -1618,7 +1631,8 @@ abstract class DynamicPartitionPruningSuiteBase + } + } + +- test("SPARK-39217: Makes DPP support the pruning side has Union") { ++ test("SPARK-39217: Makes DPP support the pruning side has Union", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true") { + val df = sql( + """ +@@ -1730,6 +1744,8 @@ abstract class DynamicPartitionPruningV1Suite extends DynamicPartitionPruningDat case s: BatchScanExec => // we use f1 col for v2 tables due to schema pruning s.output.exists(_.exists(_.argString(maxFields = 100).contains("f1"))) @@ -1079,13 +1159,15 @@ index 15de4c5cc5b..6a85dfb6883 100644 setupTestData() diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantProjectsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantProjectsSuite.scala -index b5bac8079c4..bf54af24a30 100644 +index b5bac8079c4..544c1ddc697 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantProjectsSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantProjectsSuite.scala -@@ -18,6 +18,7 @@ +@@ -17,7 +17,8 @@ + package org.apache.spark.sql.execution - import org.apache.spark.sql.{DataFrame, QueryTest, Row} +-import org.apache.spark.sql.{DataFrame, QueryTest, Row} ++import org.apache.spark.sql.{DataFrame, IgnoreComet, QueryTest, Row} +import org.apache.spark.sql.comet.CometProjectExec import org.apache.spark.sql.connector.SimpleWritableDataSource import org.apache.spark.sql.execution.adaptive.{AdaptiveSparkPlanHelper, DisableAdaptiveExecutionSuite, EnableAdaptiveExecutionSuite} @@ -1102,6 +1184,16 @@ index b5bac8079c4..bf54af24a30 100644 assert(actual == expected) } } +@@ -112,7 +116,8 @@ abstract class RemoveRedundantProjectsSuiteBase + assertProjectExec(query, 1, 3) + } + +- test("join with ordering requirement") { ++ test("join with ordering requirement", ++ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { + val query = "select * from (select key, a, c, b from testView) as t1 join " + + "(select key, a, b, c from testView) as t2 on t1.key = t2.key where t2.a > 50" + assertProjectExec(query, 2, 2) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantSortsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantSortsSuite.scala index 005e764cc30..92ec088efab 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantSortsSuite.scala From f028425f8c949e063a12c3f9e0ad47691bb066e6 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 11 Jun 2024 12:30:40 -0700 Subject: [PATCH 63/68] address review comments --- .github/workflows/spark_sql_test_ansi.yml | 2 -- .../src/main/java/org/apache/comet/parquet/TypeUtil.java | 2 +- .../spark-3.2/org/apache/comet/shims/CometExprShim.scala | 7 ++----- .../spark-3.3/org/apache/comet/shims/CometExprShim.scala | 7 ++----- 4 files changed, 5 insertions(+), 13 deletions(-) diff --git a/.github/workflows/spark_sql_test_ansi.yml b/.github/workflows/spark_sql_test_ansi.yml index c7d5ad7e3..34a393115 100644 --- a/.github/workflows/spark_sql_test_ansi.yml +++ b/.github/workflows/spark_sql_test_ansi.yml @@ -24,12 +24,10 @@ concurrency: on: push: paths-ignore: - - "doc/**" - "docs/**" - "**.md" pull_request: paths-ignore: - - "doc/**" - "docs/**" - "**.md" # manual trigger diff --git a/common/src/main/java/org/apache/comet/parquet/TypeUtil.java b/common/src/main/java/org/apache/comet/parquet/TypeUtil.java index 5bd5896d1..be0f2e022 100644 --- a/common/src/main/java/org/apache/comet/parquet/TypeUtil.java +++ b/common/src/main/java/org/apache/comet/parquet/TypeUtil.java @@ -170,7 +170,7 @@ && isUnsignedIntTypeMatched(logicalTypeAnnotation, 64)) { break; case INT96: if (sparkType == TimestampNTZType$.MODULE$) { - if (isSpark40Plus()) return; + if (isSpark40Plus()) return; // Spark 4.0+ supports Timestamp NTZ with INT96 convertErrorForTimestampNTZ(typeName.name()); } else if (sparkType == DataTypes.TimestampType) { return; diff --git a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala index b371e3ffe..d29a5bcf0 100644 --- a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala @@ -33,11 +33,8 @@ trait CometExprShim { (unhex.child, Literal(false)) } - protected def isTimestampNTZType(dt: DataType): Boolean = dt match { - // `TimestampNTZType` is private - case dt if dt.typeName == "timestamp_ntz" => true - case _ => false - } + protected def isTimestampNTZType(dt: DataType): Boolean = + dt.typeName == "timestamp_ntz" => true // `TimestampNTZType` is private protected def evalMode(c: Cast): CometEvalMode.Value = CometEvalMode.fromBoolean(c.ansiEnabled) } diff --git a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala index 30c9a37f9..d3a21acdb 100644 --- a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala @@ -33,11 +33,8 @@ trait CometExprShim { (unhex.child, Literal(false)) } - protected def isTimestampNTZType(dt: DataType): Boolean = dt match { - // `TimestampNTZType` is private - case dt if dt.typeName == "timestamp_ntz" => true - case _ => false - } + protected def isTimestampNTZType(dt: DataType): Boolean = + dt.typeName == "timestamp_ntz" => true // `TimestampNTZType` is private protected def evalMode(c: Cast): CometEvalMode.Value = CometEvalMode.fromBoolean(c.ansiEnabled) } From 024a4222fe25043faf619d8064c794955115cff4 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 11 Jun 2024 12:48:31 -0700 Subject: [PATCH 64/68] address review comments --- .../main/spark-3.2/org/apache/comet/shims/CometExprShim.scala | 2 +- .../main/spark-3.3/org/apache/comet/shims/CometExprShim.scala | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala index d29a5bcf0..44c1ceb69 100644 --- a/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.2/org/apache/comet/shims/CometExprShim.scala @@ -34,7 +34,7 @@ trait CometExprShim { } protected def isTimestampNTZType(dt: DataType): Boolean = - dt.typeName == "timestamp_ntz" => true // `TimestampNTZType` is private + dt.typeName == "timestamp_ntz" // `TimestampNTZType` is private protected def evalMode(c: Cast): CometEvalMode.Value = CometEvalMode.fromBoolean(c.ansiEnabled) } diff --git a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala index d3a21acdb..aa6db06d8 100644 --- a/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala +++ b/spark/src/main/spark-3.3/org/apache/comet/shims/CometExprShim.scala @@ -34,7 +34,7 @@ trait CometExprShim { } protected def isTimestampNTZType(dt: DataType): Boolean = - dt.typeName == "timestamp_ntz" => true // `TimestampNTZType` is private + dt.typeName == "timestamp_ntz" // `TimestampNTZType` is private protected def evalMode(c: Cast): CometEvalMode.Value = CometEvalMode.fromBoolean(c.ansiEnabled) } From f5972c2fce24adb271d102a160115675b6be6fa3 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 12 Jun 2024 12:15:38 -0700 Subject: [PATCH 65/68] address review comments --- .../org/apache/comet/CometSparkSessionExtensions.scala | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala b/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala index 5ecb2bf17..3146105fc 100644 --- a/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala +++ b/spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala @@ -45,7 +45,7 @@ import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.types._ import org.apache.comet.CometConf._ -import org.apache.comet.CometSparkSessionExtensions.{createMessage, getCometShuffleNotEnabledReason, isANSIEnabled, isCometBroadCastForceEnabled, isCometEnabled, isCometExecEnabled, isCometJVMShuffleMode, isCometNativeShuffleMode, isCometOperatorEnabled, isCometScan, isCometScanEnabled, isCometShuffleEnabled, isSchemaSupported, isSpark34Plus, shouldApplyRowToColumnar, withInfo, withInfos} +import org.apache.comet.CometSparkSessionExtensions.{createMessage, getCometShuffleNotEnabledReason, isANSIEnabled, isCometBroadCastForceEnabled, isCometEnabled, isCometExecEnabled, isCometJVMShuffleMode, isCometNativeShuffleMode, isCometOperatorEnabled, isCometScan, isCometScanEnabled, isCometShuffleEnabled, isSchemaSupported, isSpark34Plus, isSpark40Plus, shouldApplyRowToColumnar, withInfo, withInfos} import org.apache.comet.parquet.{CometParquetScan, SupportsComet} import org.apache.comet.serde.OperatorOuterClass.Operator import org.apache.comet.serde.QueryPlanSerde @@ -716,7 +716,9 @@ class CometSparkSessionExtensions // enabled. if (isANSIEnabled(conf)) { if (COMET_ANSI_MODE_ENABLED.get()) { - logInfo("Using Comet's experimental support for ANSI mode.") + if (!isSpark40Plus) { + logWarning("Using Comet's experimental support for ANSI mode.") + } } else { logInfo("Comet extension disabled for ANSI mode") return plan From d2aaeaaa9a9bc1f7f32ccbf47d08eb82c2a37901 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Wed, 12 Jun 2024 11:24:03 -0700 Subject: [PATCH 66/68] build: Enable spark-4.0 Spark tests --- .../java/org/apache/comet/parquet/Native.java | 1 + .../org/apache/comet/parquet/TypeUtil.java | 10 ++++-- .../java/org/apache/comet/parquet/Utils.java | 11 ++++-- core/benches/parquet_read.rs | 2 +- core/src/parquet/mod.rs | 4 ++- core/src/parquet/read/column.rs | 34 ++++++++++++++----- core/src/parquet/read/values.rs | 16 +++++++++ core/src/parquet/util/jni.rs | 7 ++-- dev/diffs/4.0.0-preview1.diff | 16 ++------- 9 files changed, 71 insertions(+), 30 deletions(-) diff --git a/common/src/main/java/org/apache/comet/parquet/Native.java b/common/src/main/java/org/apache/comet/parquet/Native.java index 0887ae12f..b40e27e73 100644 --- a/common/src/main/java/org/apache/comet/parquet/Native.java +++ b/common/src/main/java/org/apache/comet/parquet/Native.java @@ -75,6 +75,7 @@ public static native long initColumnReader( int precision, int expectedPrecision, int scale, + int expectedScale, int tu, boolean isAdjustedUtc, int batchSize, diff --git a/common/src/main/java/org/apache/comet/parquet/TypeUtil.java b/common/src/main/java/org/apache/comet/parquet/TypeUtil.java index be0f2e022..bfbb7d0d2 100644 --- a/common/src/main/java/org/apache/comet/parquet/TypeUtil.java +++ b/common/src/main/java/org/apache/comet/parquet/TypeUtil.java @@ -235,12 +235,14 @@ private static void convertErrorForTimestampNTZ(String parquetType) { } private static boolean canReadAsIntDecimal(ColumnDescriptor descriptor, DataType dt) { - if (!DecimalType.is32BitDecimalType(dt)) return false; + if (!DecimalType.is32BitDecimalType(dt) && !(isSpark40Plus() && dt instanceof DecimalType)) + return false; return isDecimalTypeMatched(descriptor, dt); } private static boolean canReadAsLongDecimal(ColumnDescriptor descriptor, DataType dt) { - if (!DecimalType.is64BitDecimalType(dt)) return false; + if (!DecimalType.is64BitDecimalType(dt) && !(isSpark40Plus() && dt instanceof DecimalType)) + return false; return isDecimalTypeMatched(descriptor, dt); } @@ -264,7 +266,9 @@ private static boolean isDecimalTypeMatched(ColumnDescriptor descriptor, DataTyp DecimalLogicalTypeAnnotation decimalType = (DecimalLogicalTypeAnnotation) typeAnnotation; // It's OK if the required decimal precision is larger than or equal to the physical decimal // precision in the Parquet metadata, as long as the decimal scale is the same. - return decimalType.getPrecision() <= d.precision() && decimalType.getScale() == d.scale(); + return decimalType.getPrecision() <= d.precision() + && (decimalType.getScale() == d.scale() + || (isSpark40Plus() && decimalType.getScale() <= d.scale())); } return false; } diff --git a/common/src/main/java/org/apache/comet/parquet/Utils.java b/common/src/main/java/org/apache/comet/parquet/Utils.java index 99f3a4edd..2d4b83a67 100644 --- a/common/src/main/java/org/apache/comet/parquet/Utils.java +++ b/common/src/main/java/org/apache/comet/parquet/Utils.java @@ -115,7 +115,7 @@ public static long initColumnReader( promotionInfo = new TypePromotionInfo(readType); } else { // If type promotion is not enable, we'll just use the Parquet primitive type and precision. - promotionInfo = new TypePromotionInfo(primitiveTypeId, precision); + promotionInfo = new TypePromotionInfo(primitiveTypeId, precision, scale); } return Native.initColumnReader( @@ -131,6 +131,7 @@ public static long initColumnReader( precision, promotionInfo.precision, scale, + promotionInfo.scale, tu, isAdjustedUtc, batchSize, @@ -144,10 +145,13 @@ static class TypePromotionInfo { int physicalTypeId; // Decimal precision from the Spark read schema, or -1 if it's not decimal type. int precision; + // Decimal scale from the Spark read schema, or -1 if it's not decimal type. + int scale; - TypePromotionInfo(int physicalTypeId, int precision) { + TypePromotionInfo(int physicalTypeId, int precision, int scale) { this.physicalTypeId = physicalTypeId; this.precision = precision; + this.scale = scale; } TypePromotionInfo(DataType sparkReadType) { @@ -159,13 +163,16 @@ static class TypePromotionInfo { int physicalTypeId = getPhysicalTypeId(primitiveType.getPrimitiveTypeName()); LogicalTypeAnnotation annotation = primitiveType.getLogicalTypeAnnotation(); int precision = -1; + int scale = -1; if (annotation instanceof LogicalTypeAnnotation.DecimalLogicalTypeAnnotation) { LogicalTypeAnnotation.DecimalLogicalTypeAnnotation decimalAnnotation = (LogicalTypeAnnotation.DecimalLogicalTypeAnnotation) annotation; precision = decimalAnnotation.getPrecision(); + scale = decimalAnnotation.getScale(); } this.physicalTypeId = physicalTypeId; this.precision = precision; + this.scale = scale; } } diff --git a/core/benches/parquet_read.rs b/core/benches/parquet_read.rs index 612d081c7..32463c077 100644 --- a/core/benches/parquet_read.rs +++ b/core/benches/parquet_read.rs @@ -54,7 +54,7 @@ fn bench(c: &mut Criterion) { ); b.iter(|| { let cd = ColumnDescriptor::new(t.clone(), 0, 0, ColumnPath::from(Vec::new())); - let promition_info = TypePromotionInfo::new(PhysicalType::INT32, -1); + let promition_info = TypePromotionInfo::new(PhysicalType::INT32, -1, -1); let mut column_reader = TestColumnReader::new( cd, promition_info, diff --git a/core/src/parquet/mod.rs b/core/src/parquet/mod.rs index 4f87d15de..e6acaa26b 100644 --- a/core/src/parquet/mod.rs +++ b/core/src/parquet/mod.rs @@ -72,6 +72,7 @@ pub extern "system" fn Java_org_apache_comet_parquet_Native_initColumnReader( precision: jint, read_precision: jint, scale: jint, + read_scale: jint, time_unit: jint, is_adjusted_utc: jboolean, batch_size: jint, @@ -94,7 +95,8 @@ pub extern "system" fn Java_org_apache_comet_parquet_Native_initColumnReader( is_adjusted_utc, jni_path, )?; - let promotion_info = TypePromotionInfo::new_from_jni(read_primitive_type, read_precision); + let promotion_info = + TypePromotionInfo::new_from_jni(read_primitive_type, read_precision, read_scale); let ctx = Context { column_reader: ColumnReader::get( desc, diff --git a/core/src/parquet/read/column.rs b/core/src/parquet/read/column.rs index 6fc73f93f..22bade6b3 100644 --- a/core/src/parquet/read/column.rs +++ b/core/src/parquet/read/column.rs @@ -132,11 +132,17 @@ impl ColumnReader { (32, false) => typed_reader!(UInt32ColumnReader, Int64), _ => unimplemented!("Unsupported INT32 annotation: {:?}", lt), }, - LogicalType::Decimal { scale, precision } => { - if use_decimal_128 { + LogicalType::Decimal { + scale, + precision: _, + } => { + if use_decimal_128 || scale < &promotion_info.scale { typed_reader!( Int32DecimalColumnReader, - ArrowDataType::Decimal128(*precision as u8, *scale as i8) + ArrowDataType::Decimal128( + promotion_info.precision as u8, + promotion_info.scale as i8 + ) ) } else { typed_reader!(Int32ColumnReader, Int32) @@ -168,11 +174,17 @@ impl ColumnReader { ), _ => panic!("Unsupported INT64 annotation: {:?}", lt), }, - LogicalType::Decimal { scale, precision } => { - if use_decimal_128 { + LogicalType::Decimal { + scale, + precision: _, + } => { + if use_decimal_128 || scale < &promotion_info.scale { typed_reader!( Int64DecimalColumnReader, - ArrowDataType::Decimal128(*precision as u8, *scale as i8) + ArrowDataType::Decimal128( + promotion_info.precision as u8, + promotion_info.scale as i8 + ) ) } else { typed_reader!(Int64ColumnReader, Int64) @@ -248,7 +260,10 @@ impl ColumnReader { PhysicalType::FIXED_LEN_BYTE_ARRAY => { if let Some(logical_type) = desc.logical_type() { match logical_type { - LogicalType::Decimal { precision, scale } => { + LogicalType::Decimal { + precision, + scale: _, + } => { if !use_decimal_128 && precision <= DECIMAL_MAX_INT_DIGITS { typed_reader!(FLBADecimal32ColumnReader, Int32) } else if !use_decimal_128 && precision <= DECIMAL_MAX_LONG_DIGITS { @@ -256,7 +271,10 @@ impl ColumnReader { } else { typed_reader!( FLBADecimalColumnReader, - ArrowDataType::Decimal128(precision as u8, scale as i8) + ArrowDataType::Decimal128( + promotion_info.precision as u8, + promotion_info.scale as i8 + ) ) } } diff --git a/core/src/parquet/read/values.rs b/core/src/parquet/read/values.rs index 9d9bbb3c9..d18ebbfc2 100644 --- a/core/src/parquet/read/values.rs +++ b/core/src/parquet/read/values.rs @@ -28,6 +28,7 @@ use crate::{ parquet::{data_type::*, read::DECIMAL_BYTE_WIDTH, ParquetMutableVector}, unlikely, }; +use arrow::datatypes::DataType as ArrowDataType; pub fn get_decoder( value_data: Buffer, @@ -647,6 +648,12 @@ macro_rules! make_plain_decimal_impl { debug_assert!(byte_width <= DECIMAL_BYTE_WIDTH); + let src_scale = src.desc.type_scale() as u32; + let dst_scale = match dst.arrow_type { + ArrowDataType::Decimal128(_percision, scale) => scale as u32, + _ => unreachable!() + }; + for _ in 0..num { let s = &mut dst_data[dst_offset..]; @@ -670,6 +677,15 @@ macro_rules! make_plain_decimal_impl { } } + if dst_scale > src_scale { + let exp = dst_scale - src_scale; + let mul = 10_i128.pow(exp); + let v = s.as_mut_ptr() as *mut i128; + unsafe { + v.write_unaligned(v.read_unaligned() * mul); + } + } + src_offset += byte_width; dst_offset += DECIMAL_BYTE_WIDTH; } diff --git a/core/src/parquet/util/jni.rs b/core/src/parquet/util/jni.rs index 62787213f..cde9fff0f 100644 --- a/core/src/parquet/util/jni.rs +++ b/core/src/parquet/util/jni.rs @@ -96,21 +96,24 @@ pub fn convert_encoding(ordinal: jint) -> Encoding { pub struct TypePromotionInfo { pub(crate) physical_type: PhysicalType, pub(crate) precision: i32, + pub(crate) scale: i32, } impl TypePromotionInfo { - pub fn new_from_jni(physical_type_id: jint, precision: jint) -> Self { + pub fn new_from_jni(physical_type_id: jint, precision: jint, scale: jint) -> Self { let physical_type = convert_physical_type(physical_type_id); Self { physical_type, precision, + scale, } } - pub fn new(physical_type: PhysicalType, precision: i32) -> Self { + pub fn new(physical_type: PhysicalType, precision: i32, scale: i32) -> Self { Self { physical_type, precision, + scale, } } } diff --git a/dev/diffs/4.0.0-preview1.diff b/dev/diffs/4.0.0-preview1.diff index c9a80d074..4031015df 100644 --- a/dev/diffs/4.0.0-preview1.diff +++ b/dev/diffs/4.0.0-preview1.diff @@ -1895,20 +1895,10 @@ index 4fb8faa43a3..984fd1a9892 100644 checkAnswer( // "fruit" column in this file is encoded using DELTA_LENGTH_BYTE_ARRAY. diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala -index a329d3fdc3c..437cf699887 100644 +index a329d3fdc3c..d29523a41f7 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala -@@ -1024,7 +1024,8 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS - testMigration(fromTsType = "TIMESTAMP_MICROS", toTsType = "INT96") - } - -- test("SPARK-34212 Parquet should read decimals correctly") { -+ test("SPARK-34212 Parquet should read decimals correctly", -+ IgnoreComet("TODO: https://github.com/apache/datafusion-comet/issues/551")) { - def readParquet(schema: String, path: File): DataFrame = { - spark.read.schema(schema).parquet(path.toString) - } -@@ -1042,7 +1043,8 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS +@@ -1042,7 +1042,8 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS checkAnswer(readParquet(schema2, path), df) } @@ -1918,7 +1908,7 @@ index a329d3fdc3c..437cf699887 100644 val schema1 = "a DECIMAL(3, 2), b DECIMAL(18, 3), c DECIMAL(37, 3)" checkAnswer(readParquet(schema1, path), df) val schema2 = "a DECIMAL(3, 0), b DECIMAL(18, 1), c DECIMAL(37, 1)" -@@ -1066,7 +1068,8 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS +@@ -1066,7 +1067,8 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS val df = sql(s"SELECT 1 a, 123456 b, ${Int.MaxValue.toLong * 10} c, CAST('1.2' AS BINARY) d") df.write.parquet(path.toString) From 23b1d3c38af4598694f0157db95984cda8877ab5 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 18 Jun 2024 16:39:58 -0700 Subject: [PATCH 67/68] address review comments --- .../org/apache/spark/sql/comet/shims/ShimCometScanExec.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala index 9c5305afb..263ef2506 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala @@ -30,7 +30,7 @@ import org.apache.spark.sql.catalyst.expressions.AttributeReference import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.{FileSourceScanExec, PartitionedFileUtil} import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, HadoopFsRelation, PartitionDirectory, PartitionedFile} -import org.apache.spark.sql.types.{LongType, StructField, StructType} +import org.apache.spark.sql.types.StructField trait ShimCometScanExec { def wrapped: FileSourceScanExec From 2b0b08cc80ee27f667fbd1cca54282b8ae20ba97 Mon Sep 17 00:00:00 2001 From: Kazuyuki Tanimura Date: Tue, 18 Jun 2024 16:56:34 -0700 Subject: [PATCH 68/68] address review comments --- .../org/apache/spark/sql/comet/shims/ShimCometScanExec.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala index 263ef2506..900b19895 100644 --- a/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala +++ b/spark/src/main/spark-3.x/org/apache/spark/sql/comet/shims/ShimCometScanExec.scala @@ -30,7 +30,7 @@ import org.apache.spark.sql.catalyst.expressions.AttributeReference import org.apache.spark.sql.execution.datasources.parquet.ParquetOptions import org.apache.spark.sql.execution.{FileSourceScanExec, PartitionedFileUtil} import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, HadoopFsRelation, PartitionDirectory, PartitionedFile} -import org.apache.spark.sql.types.StructField +import org.apache.spark.sql.types.StructType trait ShimCometScanExec { def wrapped: FileSourceScanExec