c21 commented on a change in pull request #29130:
URL: https://github.com/apache/spark/pull/29130#discussion_r456502678
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File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/joins/ShuffledHashJoinExec.scala
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@@ -47,6 +47,18 @@ case class ShuffledHashJoinExec(
"buildDataSize" -> SQLMetrics.createSizeMetric(sparkContext, "data size of
build side"),
"buildTime" -> SQLMetrics.createTimingMetric(sparkContext, "time to build
hash map"))
+ override def outputPartitioning: Partitioning = joinType match {
Review comment:
> Why does shuffle hash join not support FullOuter?
@cloud-fan sorry if I miss anything, but [isn't this true
now](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashJoin.scala#L196-L210)?
Given current spark implementation for hash join, stream side looks up in
build side hash map, it can handle non-matching keys from stream side if
there's no match in build side hash map. But it cannot handle non-matching keys
from build side, as there's no info persisted from stream side.
I feel an interesting followup could be to handle full outer join in
shuffled hash join, where when looking up stream side keys from build side
`HashedRelation`. Mark this info inside build side `HashedRelation`, and after
reading all rows from stream side, output all non-matching rows from build side
based on modified `HashedRelation`.
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