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new 7879634 [SPARK-35639][SQL] Make hasCoalescedPartition return true if
something was actually coalesced
7879634 is described below
commit 78796349d9246d36a248e645ea303270cace14ee
Author: Eugene Koifman <eugene.koif...@workday.com>
AuthorDate: Wed Jul 14 15:48:02 2021 +0800
[SPARK-35639][SQL] Make hasCoalescedPartition return true if something was
actually coalesced
### What changes were proposed in this pull request?
Fix `CustomShuffleReaderExec.hasCoalescedPartition` so that it returns true
only if some original partitions got combined
### Why are the changes needed?
W/o this change `CustomShuffleReaderExec` description can report
`coalesced` even though partitions are unchanged
### Does this PR introduce _any_ user-facing change?
Yes, the `Arguments` in the node description is now accurate:
```
(16) CustomShuffleReader
Input [3]: [registration#4, sum#85, count#86L]
Arguments: coalesced
```
### How was this patch tested?
Existing tests
Closes #32872 from ekoifman/PRISM-77023-fix-hasCoalescedPartition.
Authored-by: Eugene Koifman <eugene.koif...@workday.com>
Signed-off-by: Wenchen Fan <wenc...@databricks.com>
(cherry picked from commit 4033b2a3f4faa48bfdc0802d5637b7ec726b06e7)
Signed-off-by: Wenchen Fan <wenc...@databricks.com>
---
.../adaptive/CustomShuffleReaderExec.scala | 11 +++++++++--
.../execution/CoalesceShufflePartitionsSuite.scala | 21 +++++++++++++++++----
.../execution/adaptive/AdaptiveQueryExecSuite.scala | 8 ++++----
3 files changed, 30 insertions(+), 10 deletions(-)
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/CustomShuffleReaderExec.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/CustomShuffleReaderExec.scala
index 176fff6..61318a7 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/CustomShuffleReaderExec.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/CustomShuffleReaderExec.scala
@@ -87,8 +87,15 @@ case class CustomShuffleReaderExec private(
Iterator(desc)
}
- def hasCoalescedPartition: Boolean =
- partitionSpecs.exists(_.isInstanceOf[CoalescedPartitionSpec])
+ /**
+ * Returns true iff some non-empty partitions were combined
+ */
+ def hasCoalescedPartition: Boolean = {
+ partitionSpecs.exists {
+ case s: CoalescedPartitionSpec => s.endReducerIndex -
s.startReducerIndex > 1
+ case _ => false
+ }
+ }
def hasSkewedPartition: Boolean =
partitionSpecs.exists(_.isInstanceOf[PartialReducerPartitionSpec])
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/execution/CoalesceShufflePartitionsSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/execution/CoalesceShufflePartitionsSuite.scala
index e368868..fbae929 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/execution/CoalesceShufflePartitionsSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/execution/CoalesceShufflePartitionsSuite.scala
@@ -315,7 +315,7 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite
with BeforeAndAfterAl
test("SPARK-24705 adaptive query execution works correctly when exchange
reuse enabled") {
val test: SparkSession => Unit = { spark: SparkSession =>
spark.sql("SET spark.sql.exchange.reuse=true")
- val df = spark.range(1).selectExpr("id AS key", "id AS value")
+ val df = spark.range(0, 6, 1).selectExpr("id AS key", "id AS value")
// test case 1: a query stage has 3 child stages but they are the same
stage.
// Final Stage 1
@@ -323,7 +323,7 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite
with BeforeAndAfterAl
// ReusedQueryStage 0
// ReusedQueryStage 0
val resultDf = df.join(df, "key").join(df, "key")
- QueryTest.checkAnswer(resultDf, Row(0, 0, 0, 0) :: Nil)
+ QueryTest.checkAnswer(resultDf, (0 to 5).map(i => Row(i, i, i, i)))
val finalPlan = resultDf.queryExecution.executedPlan
.asInstanceOf[AdaptiveSparkPlanExec].executedPlan
assert(finalPlan.collect {
@@ -344,7 +344,9 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite
with BeforeAndAfterAl
val grouped = df.groupBy("key").agg(max("value").as("value"))
val resultDf2 = grouped.groupBy(col("key") + 1).max("value")
.union(grouped.groupBy(col("key") + 2).max("value"))
- QueryTest.checkAnswer(resultDf2, Row(1, 0) :: Row(2, 0) :: Nil)
+ QueryTest.checkAnswer(resultDf2, Row(1, 0) :: Row(2, 0) :: Row(2, 1) ::
Row(3, 1) ::
+ Row(3, 2) :: Row(4, 2) :: Row(4, 3) :: Row(5, 3) :: Row(5, 4) ::
Row(6, 4) :: Row(6, 5) ::
+ Row(7, 5) :: Nil)
val finalPlan2 = resultDf2.queryExecution.executedPlan
.asInstanceOf[AdaptiveSparkPlanExec].executedPlan
@@ -353,6 +355,17 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite
with BeforeAndAfterAl
val level1Stages = finalPlan2.collect { case q: QueryStageExec => q }
assert(level1Stages.length == 2)
+ assert(
+ finalPlan2.collect {
+ case r @ CoalescedShuffleReader() => r
+ }.length == 2, "finalPlan2")
+
+ level1Stages.foreach(qs =>
+ assert(qs.plan.collect {
+ case r @ CoalescedShuffleReader() => r
+ }.length == 1,
+ "Wrong CoalescedShuffleReader below " + qs.simpleString(3)))
+
val leafStages = level1Stages.flatMap { stage =>
// All of the child stages of result stage have only one child stage.
val children = stage.plan.collect { case q: QueryStageExec => q }
@@ -368,7 +381,7 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite
with BeforeAndAfterAl
}
assert(reusedStages.length == 1)
}
- withSparkSession(test, 4, None)
+ withSparkSession(test, 400, None)
}
test("Do not reduce the number of shuffle partition for repartition") {
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala
index 000cdfb..5000abc 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala
@@ -953,7 +953,7 @@ class AdaptiveQueryExecSuite
SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "-1",
SQLConf.SHUFFLE_PARTITIONS.key -> "100",
SQLConf.SKEW_JOIN_SKEWED_PARTITION_THRESHOLD.key -> "800",
- SQLConf.ADVISORY_PARTITION_SIZE_IN_BYTES.key -> "800") {
+ SQLConf.ADVISORY_PARTITION_SIZE_IN_BYTES.key -> "1000") {
withTempView("skewData1", "skewData2") {
spark
.range(0, 1000, 1, 10)
@@ -982,9 +982,9 @@ class AdaptiveQueryExecSuite
assert(reader.metrics.contains("numSkewedPartitions"))
}
assert(readers(0).metrics("numSkewedPartitions").value == 2)
- assert(readers(0).metrics("numSkewedSplits").value == 15)
+ assert(readers(0).metrics("numSkewedSplits").value == 11)
assert(readers(1).metrics("numSkewedPartitions").value == 1)
- assert(readers(1).metrics("numSkewedSplits").value == 12)
+ assert(readers(1).metrics("numSkewedSplits").value == 9)
}
}
}
@@ -1582,7 +1582,7 @@ class AdaptiveQueryExecSuite
// Skew join can apply as the repartition is not optimized out.
assert(smjWithNum.head.isSkewJoin)
val customReadersWithNum = collect(smjWithNum.head) {
- case c: CustomShuffleReaderExec if c.hasCoalescedPartition => c
+ case c: CustomShuffleReaderExec => c
}
assert(customReadersWithNum.nonEmpty)
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