cloud-fan commented on a change in pull request #25121: [SPARK-28356][SQL] Do
not reduce the number of partitions for repartition in adaptive execution
URL: https://github.com/apache/spark/pull/25121#discussion_r313691232
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/ReduceNumShufflePartitions.scala
##########
@@ -76,12 +82,7 @@ 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)
- // We may get different pre-shuffle partition number if user calls
repartition manually.
- // We don't reduce shuffle partition number in that case.
- val distinctNumPreShufflePartitions =
- validMetrics.map(stats => stats.bytesByPartitionId.length).distinct
-
- if (validMetrics.nonEmpty && distinctNumPreShufflePartitions.length ==
1) {
+ if (validMetrics.nonEmpty) {
Review comment:
ah `SinglePartition` is an exception. So it's still possible to hit
`distinctNumPreShufflePartitions.length > 1` here. Let's add back this check
@carsonwang @maryannxue
thanks for reporting it!
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