viirya commented on code in PR #43729:
URL: https://github.com/apache/spark/pull/43729#discussion_r1388441032
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala:
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@@ -661,6 +690,26 @@ case class HashShuffleSpec(
override def numPartitions: Int = partitioning.numPartitions
}
+case class CoalescedHashShuffleSpec(
+ from: ShuffleSpec,
+ partitions: Seq[CoalescedBoundary]) extends ShuffleSpec {
+
+ override def isCompatibleWith(other: ShuffleSpec): Boolean = other match {
+ case SinglePartitionShuffleSpec =>
+ numPartitions == 1
+ case CoalescedHashShuffleSpec(otherParent, otherPartitions) =>
+ partitions == otherPartitions && from.isCompatibleWith(otherParent)
Review Comment:
Hmm, if first hash partitioning is 5 partitions, second is 4 partitions. How
can we get same coalesced partitions with that?
For example:
[[0, 3], [3, 5]] != [[0, 3], [3, 4]]
[[0, 2], [2, 3], [3, 5]] != [[0, 2], [2, 3], [3, 4]]
The end reducer index of last coalesced partition should be different
always, no?
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