peter-toth commented on a change in pull request #25479:
[SPARK-28356][SHUFFLE][FOLLOWUP] Fix case with different pre-shuffle partition
numbers
URL: https://github.com/apache/spark/pull/25479#discussion_r314940517
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/ReduceNumShufflePartitions.scala
##########
@@ -82,7 +82,12 @@ case class ReduceNumShufflePartitions(conf: SQLConf)
extends Rule[SparkPlan] {
// `ShuffleQueryStageExec` gives null mapOutputStatistics when the input
RDD has 0 partitions,
// we should skip it when calculating the `partitionStartIndices`.
val validMetrics = shuffleMetrics.filter(_ != null)
- if (validMetrics.nonEmpty) {
+ // We may have different pre-shuffle partition numbers, don't reduce
shuffle partition number
+ // in that case. For example when we union fully aggregated data (data
is arranged to a single
+ // partition) and a result of a SortMergeJoin (multiple partitions).
+ val distinctNumPreShufflePartitions =
+ validMetrics.map(stats => stats.bytesByPartitionId.length).distinct
+ if (validMetrics.nonEmpty && distinctNumPreShufflePartitions.length ==
1) {
Review comment:
Yes, we could remove it, but this assert has been there since the original
version of `ReduceNumShufflePartitions` where the
`distinctNumPreShufflePartitions.length == 1` check was also included. I'm not
sure what is the plan with `ReduceNumShufflePartitions`. @carsonwang,
@maryannxue do you want to improve `Union`/`SinglePartition` handling in it?
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