peter-toth commented on code in PR #52067:
URL: https://github.com/apache/spark/pull/52067#discussion_r2289092207
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/joins/ShuffledHashJoinExec.scala:
##########
@@ -67,12 +67,7 @@ case class ShuffledHashJoinExec(
// Exposed for testing
@transient lazy val ignoreDuplicatedKey = joinType match {
- case LeftExistence(_) =>
- // For building hash relation, ignore duplicated rows with same join
keys if:
- // 1. Join condition is empty, or
- // 2. Join condition only references streamed attributes and build join
keys.
- val streamedOutputAndBuildKeys = AttributeSet(streamedOutput ++
buildKeys)
- condition.forall(_.references.subsetOf(streamedOutputAndBuildKeys))
+ case LeftExistence(_) if condition.isEmpty => true
Review Comment:
Yes, exactly. We can write a recursive function if that's easier to grasp.
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/joins/ShuffledHashJoinExec.scala:
##########
@@ -67,12 +67,7 @@ case class ShuffledHashJoinExec(
// Exposed for testing
@transient lazy val ignoreDuplicatedKey = joinType match {
- case LeftExistence(_) =>
- // For building hash relation, ignore duplicated rows with same join
keys if:
- // 1. Join condition is empty, or
- // 2. Join condition only references streamed attributes and build join
keys.
- val streamedOutputAndBuildKeys = AttributeSet(streamedOutput ++
buildKeys)
- condition.forall(_.references.subsetOf(streamedOutputAndBuildKeys))
+ case LeftExistence(_) if condition.isEmpty => true
Review Comment:
Yes, exactly. But we can write a recursive function if that's easier to
grasp.
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