Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/1147#discussion_r15679602
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/joins.scala ---
@@ -37,6 +37,135 @@ case object BuildLeft extends BuildSide
@DeveloperApi
case object BuildRight extends BuildSide
+/**
+ * Constant Value for Binary Join Node
+ */
+object BinaryJoinNode {
+ val SINGLE_NULL_LIST = Seq[Row](null)
+ val EMPTY_NULL_LIST = Seq[Row]()
+}
+
+// TODO If join key was null should be considered as equal? In Hive this
is configurable.
+
+/**
+ * Output the tuples for the matched (with the same join key) join group,
base on the join types,
+ * Both input iterators should be repeatable.
+ */
+trait BinaryRepeatableIteratorNode extends BinaryNode {
+ self: Product =>
+
+ val leftNullRow = new GenericRow(left.output.length)
+ val rightNullRow = new GenericRow(right.output.length)
+
+ val joinedRow = new JoinedRow()
+
+ val boundCondition = InterpretedPredicate(
+ condition
+ .map(c => BindReferences.bindReference(c, left.output ++
right.output))
+ .getOrElse(Literal(true)))
+
+ def condition: Option[Expression]
+ def joinType: JoinType
+
+ // TODO we need to rewrite all of the iterators with our own
implementation instead of the scala
+ // iterator for performance / memory usage reason.
+
+ def leftOuterIterator(key: Row, leftIter: Iterable[Row], rightIter:
Iterable[Row])
+ : Iterator[Row] = {
+ leftIter.iterator.flatMap { l =>
+ joinedRow.withLeft(l)
+ var matched = false
+ (if (!key.anyNull) rightIter else
BinaryJoinNode.EMPTY_NULL_LIST).collect {
+ case r if (boundCondition(joinedRow.withRight(r))) => {
+ matched = true
+ joinedRow.copy
+ }
+ } ++ BinaryJoinNode.SINGLE_NULL_LIST.collect {
--- End diff --
Yeah, that's pretty cool implementation, I will update it.
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