Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/5717#discussion_r32802697
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/joins/SortMergeJoin.scala
---
@@ -36,46 +36,91 @@ import org.apache.spark.util.collection.CompactBuffer
case class SortMergeJoin(
leftKeys: Seq[Expression],
rightKeys: Seq[Expression],
+ joinType: JoinType,
left: SparkPlan,
- right: SparkPlan) extends BinaryNode {
+ right: SparkPlan,
+ condition: Option[Expression] = None) extends BinaryNode {
- override def output: Seq[Attribute] = left.output ++ right.output
+ val (streamed, buffered, streamedKeys, bufferedKeys) = joinType match {
+ case RightOuter => (right, left, rightKeys, leftKeys)
+ case _ => (left, right, leftKeys, rightKeys)
+ }
+
+ override def output: Seq[Attribute] = joinType match {
+ case Inner =>
+ left.output ++ right.output
+ case LeftOuter =>
+ left.output ++ right.output.map(_.withNullability(true))
+ case RightOuter =>
+ left.output.map(_.withNullability(true)) ++ right.output
+ case FullOuter =>
+ left.output.map(_.withNullability(true)) ++
right.output.map(_.withNullability(true))
+ case x =>
+ throw new IllegalStateException(s"SortMergeJoin should not take $x
as the JoinType")
+ }
- override def outputPartitioning: Partitioning = left.outputPartitioning
+ override def outputPartitioning: Partitioning = joinType match {
+ case FullOuter =>
+ // when doing Full Outer join, NULL rows from both sides are not so
partitioned.
+ UnknownPartitioning(streamed.outputPartitioning.numPartitions)
+ case _ => streamed.outputPartitioning
--- End diff --
I think @JoshRosen is right, but currently all of the existed equi-join has
the same bug which described at
https://issues.apache.org/jira/browse/SPARK-2205 , so for now, we'd better keep
it the same as it was to be (just take the streaming output partitioning).
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