Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/17491#discussion_r110858303
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
---
@@ -498,3 +498,32 @@ object RewriteCorrelatedScalarSubquery extends
Rule[LogicalPlan] {
}
}
}
+
+/**
+ * This rule rewrites a EXISTS predicate sub-queries into an Aggregate
with count.
+ * So it doesn't be converted to a JOIN later.
+ */
+object RewriteEmptyExists extends Rule[LogicalPlan] with PredicateHelper {
+ private def containsAgg(plan: LogicalPlan): Boolean = {
+ plan.collect {
+ case a: Aggregate => a
+ }.nonEmpty
+ }
+
+ def apply(plan: LogicalPlan): LogicalPlan = plan transform {
+ case Filter(condition, child) =>
+ val (withSubquery, withoutSubquery) =
+
splitConjunctivePredicates(condition).partition(SubqueryExpression.hasInOrExistsSubquery)
+ val newWithSubquery = withSubquery.map(_.transform {
+ case e @ Exists(sub, conditions, exprId) if conditions.isEmpty &&
!containsAgg(sub) =>
+ val countExpr = Alias(Count(Literal(1)).toAggregateExpression(),
"count")()
+ val expr = Alias(GreaterThan(countExpr.toAttribute, Literal(0)),
e.toString)()
+ ScalarSubquery(
+ Project(Seq(expr),
+ Aggregate(Nil, Seq(countExpr), LocalLimit(Literal(1), sub))),
--- End diff --
I think it is a special case. Then I will remove this optimization and
minimize this pr's change.
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