leanken commented on a change in pull request #29104:
URL: https://github.com/apache/spark/pull/29104#discussion_r457473120
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File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoinExec.scala
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@@ -64,10 +65,32 @@ case class BroadcastHashJoinExec(
val numOutputRows = longMetric("numOutputRows")
val broadcastRelation = buildPlan.executeBroadcast[HashedRelation]()
- streamedPlan.execute().mapPartitions { streamedIter =>
- val hashed = broadcastRelation.value.asReadOnlyCopy()
-
TaskContext.get().taskMetrics().incPeakExecutionMemory(hashed.estimatedSize)
- join(streamedIter, hashed, numOutputRows)
+ if (isNullAwareAntiJoin) {
+ streamedPlan.execute().mapPartitionsInternal { streamedIter =>
+ if (broadcastRelation.value.inputEmpty) {
+ streamedIter
+ } else if (broadcastRelation.value.anyNullKeyExists) {
Review comment:
As for my option, I think we should not use BroadcastHashJoinExec to
deal with this special case, because its specialization break the hypothesis of
normal join.
normally join case is consist of
joinKeys and condition
but Or(EqualTo(a=b), IsNull(EqualTo(a=b)) can't trans into such pattern.
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