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[SPARK-16818] Exchange reuse incorrectly reuses scans over different sets of partitions #14425

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[SPARK-16818] Exchange reuse incorrectly reuses scans over different sets of partitions #14425

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e7e545f
Sat Jul 30 15:02:48 PDT 2016
ericl Jul 30, 2016
a254540
Sat Jul 30 15:06:12 PDT 2016
ericl Jul 30, 2016
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2 changes: 2 additions & 0 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -130,7 +130,9 @@ private[sql] object FileSourceStrategy extends Strategy with Logging {
createNonBucketedReadRDD(readFile, selectedPartitions, fsRelation)
}

// These metadata values make scan plans uniquely identifiable for equality checking.
val meta = Map(
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@rxin rxin Jul 30, 2016

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not related to this pr - i think we should remove the concept of metadata entirely from physical plans. It is something added as a hack to propagate the following information, which really should just be a named field in those case classes.

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@ericl ericl Jul 30, 2016

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Agreed

"PartitionFilters" -> partitionKeyFilters.mkString("[", ", ", "]"),
"Format" -> fsRelation.fileFormat.toString,
"ReadSchema" -> prunedDataSchema.simpleString,
PUSHED_FILTERS -> pushedDownFilters.mkString("[", ", ", "]"),
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35 changes: 34 additions & 1 deletion ...e/src/test/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategySuite.scala
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Expand Up @@ -30,7 +30,7 @@ import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.catalog.BucketSpec
import org.apache.spark.sql.catalyst.expressions.{Expression, ExpressionSet, PredicateHelper}
import org.apache.spark.sql.catalyst.util
import org.apache.spark.sql.execution.DataSourceScanExec
import org.apache.spark.sql.execution.{DataSourceScanExec, SparkPlan}
import org.apache.spark.sql.functions._
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.sources._
Expand Down Expand Up @@ -408,6 +408,39 @@ class FileSourceStrategySuite extends QueryTest with SharedSQLContext with Predi
}
}

test("[SPARK-16818] partition pruned file scans implement sameResult correctly") {
withTempPath { path =>
val tempDir = path.getCanonicalPath
spark.range(100)
.selectExpr("id", "id as b")
.write
.partitionBy("id")
.parquet(tempDir)
val df = spark.read.parquet(tempDir)
def getPlan(df: DataFrame): SparkPlan = {
df.queryExecution.executedPlan
}
assert(getPlan(df.where("id = 2")).sameResult(getPlan(df.where("id = 2"))))
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@rxin rxin Jul 30, 2016

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did you verify this would fail without your patch?

assert(!getPlan(df.where("id = 2")).sameResult(getPlan(df.where("id = 3"))))
}
}

test("[SPARK-16818] exchange reuse respects differences in partition pruning") {
spark.conf.set("spark.sql.exchange.reuse", true)
withTempPath { path =>
val tempDir = path.getCanonicalPath
spark.range(10)
.selectExpr("id % 2 as a", "id % 3 as b", "id as c")
.write
.partitionBy("a")
.parquet(tempDir)
val df = spark.read.parquet(tempDir)
val df1 = df.where("a = 0").groupBy("b").agg("c" -> "sum")
val df2 = df.where("a = 1").groupBy("b").agg("c" -> "sum")
checkAnswer(df1.join(df2, "b"), Row(0, 6, 12) :: Row(1, 4, 8) :: Row(2, 10, 5) :: Nil)
}
}

// Helpers for checking the arguments passed to the FileFormat.

protected val checkPartitionSchema =
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