[SPARK-19611][SQL] Introduce configurable table schema inference #16942
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| /* | ||
| * 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. | ||
| */ | ||
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| package org.apache.spark.sql.hive | ||
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| import java.io.File | ||
| import java.util.concurrent.{Executors, TimeUnit} | ||
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| import org.scalatest.BeforeAndAfterEach | ||
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| import org.apache.spark.metrics.source.HiveCatalogMetrics | ||
| import org.apache.spark.sql.catalyst.TableIdentifier | ||
| import org.apache.spark.sql.catalyst.catalog._ | ||
| import org.apache.spark.sql.execution.datasources.FileStatusCache | ||
| import org.apache.spark.sql.QueryTest | ||
| import org.apache.spark.sql.hive.client.HiveClient | ||
| import org.apache.spark.sql.hive.test.TestHiveSingleton | ||
| import org.apache.spark.sql.internal.SQLConf | ||
| import org.apache.spark.sql.test.SQLTestUtils | ||
| import org.apache.spark.sql.types._ | ||
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| class HiveSchemaInferenceSuite | ||
| extends QueryTest with TestHiveSingleton with SQLTestUtils with BeforeAndAfterEach { | ||
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| import HiveSchemaInferenceSuite._ | ||
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| // Create a CatalogTable instance modeling an external Hive table in a metastore that isn't | ||
| // controlled by Spark (i.e. has no Spark-specific table properties set). | ||
| private def hiveExternalCatalogTable( | ||
| tableName: String, | ||
| location: String, | ||
| schema: StructType, | ||
| partitionColumns: Seq[String], | ||
| properties: Map[String, String] = Map.empty): CatalogTable = { | ||
| CatalogTable( | ||
| identifier = TableIdentifier(table = tableName, database = Option("default")), | ||
| tableType = CatalogTableType.EXTERNAL, | ||
| storage = CatalogStorageFormat( | ||
| locationUri = Option(location), | ||
| inputFormat = Option("org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat"), | ||
| outputFormat = Option("org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat"), | ||
| serde = Option("org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe"), | ||
| compressed = false, | ||
| properties = Map("serialization.format" -> "1")), | ||
| schema = schema, | ||
| provider = Option("hive"), | ||
| partitionColumnNames = partitionColumns, | ||
| properties = properties) | ||
| } | ||
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| // Creates CatalogTablePartition instances for adding partitions of data to our test table. | ||
| private def hiveCatalogPartition(location: String, index: Int): CatalogTablePartition | ||
| = CatalogTablePartition( | ||
| spec = Map("partcol1" -> index.toString, "partcol2" -> index.toString), | ||
| storage = CatalogStorageFormat( | ||
| locationUri = Option(s"${location}/partCol1=$index/partCol2=$index/"), | ||
| inputFormat = Option("org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat"), | ||
| outputFormat = Option("org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat"), | ||
| serde = Option("org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe"), | ||
| compressed = false, | ||
| properties = Map("serialization.format" -> "1"))) | ||
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| // Creates a case-sensitive external Hive table for testing schema inference options. Table | ||
| // will not have Spark-specific table properties set. | ||
| private def setupCaseSensitiveTable( | ||
| tableName: String, | ||
| dir: File): Unit = { | ||
| spark.range(NUM_RECORDS) | ||
| .selectExpr("id as fieldOne", "id as partCol1", "id as partCol2") | ||
| .write | ||
| .partitionBy("partCol1", "partCol2") | ||
| .mode("overwrite") | ||
| .parquet(dir.getAbsolutePath) | ||
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| val lowercaseSchema = StructType(Seq( | ||
| StructField("fieldone", LongType), | ||
| StructField("partcol1", IntegerType), | ||
| StructField("partcol2", IntegerType))) | ||
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| val client = spark.sharedState.externalCatalog.asInstanceOf[HiveExternalCatalog].client | ||
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| val catalogTable = hiveExternalCatalogTable( | ||
| tableName, | ||
| dir.getAbsolutePath, | ||
| lowercaseSchema, | ||
| Seq("partcol1", "partcol2")) | ||
| client.createTable(catalogTable, true) | ||
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| val partitions = (0 until NUM_RECORDS).map(hiveCatalogPartition(dir.getAbsolutePath, _)).toSeq | ||
| client.createPartitions("default", tableName, partitions, true) | ||
| } | ||
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| // Create a test table used for a single unit test, with data stored in the specified directory. | ||
| private def withTestTable(dir: File)(f: File => Unit): Unit = { | ||
| setupCaseSensitiveTable(TEST_TABLE_NAME, dir) | ||
| try f(dir) finally spark.sql(s"DROP TABLE IF EXISTS $TEST_TABLE_NAME") | ||
| } | ||
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| override def beforeEach(): Unit = { | ||
| super.beforeEach() | ||
| FileStatusCache.resetForTesting() | ||
| } | ||
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| override def afterEach(): Unit = { | ||
| super.afterEach() | ||
| FileStatusCache.resetForTesting() | ||
| } | ||
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| test("Queries against case-sensitive tables with no schema in table properties should work " + | ||
| "when schema inference is enabled") { | ||
| withSQLConf("spark.sql.hive.schemaInferenceMode" -> "INFER_AND_SAVE") { | ||
|
Author
There was a problem hiding this comment. Will change this to reference the key via the constant in SQLConf rather than |
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| withTempDir { dir => | ||
| withTestTable(dir) { dir => | ||
| val expectedSchema = StructType(Seq( | ||
| StructField("fieldOne", LongType), | ||
| // Partition columns remain case-insensitive | ||
| StructField("partcol1", IntegerType), | ||
| StructField("partcol2", IntegerType))) | ||
| assert(spark.sql(FIELD_QUERY).count == NUM_RECORDS) | ||
| assert(spark.sql(PARTITION_COLUMN_QUERY).count == NUM_RECORDS) | ||
| // Test that the case-sensitive schema was storied as a table property after inference | ||
| assert(spark.sql(SELECT_ALL_QUERY).schema == expectedSchema) | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| test("Schema should be inferred but not stored when ...") { | ||
| withSQLConf("spark.sql.hive.schemaInferenceMode" -> "INFER_ONLY") { | ||
| withTempDir { dir => | ||
| withTestTable(dir) { dir => | ||
| val existingSchema = spark.sql(SELECT_ALL_QUERY).schema | ||
| assert(spark.sql(FIELD_QUERY).count == NUM_RECORDS) | ||
| assert(spark.sql(PARTITION_COLUMN_QUERY).count == NUM_RECORDS) | ||
| assert(spark.sql(SELECT_ALL_QUERY).schema == existingSchema) | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| object HiveSchemaInferenceSuite { | ||
| private val NUM_RECORDS = 10 | ||
| private val TEST_TABLE_NAME = "test_table" | ||
| private val FIELD_QUERY = s"SELECT * FROM $TEST_TABLE_NAME WHERE fieldOne >= 0" | ||
| private val PARTITION_COLUMN_QUERY = s"SELECT * FROM $TEST_TABLE_NAME WHERE partCol1 >= 0" | ||
| private val SELECT_ALL_QUERY = s"SELECT * FROM $TEST_TABLE_NAME" | ||
| } | ||
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As mentioned in the PR, I'm looking for a good place to store these values as constants or an enum.