allisonwang-db commented on code in PR #40811:
URL: https://github.com/apache/spark/pull/40811#discussion_r1170824254
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala:
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@@ -325,9 +327,22 @@ object PullupCorrelatedPredicates extends
Rule[LogicalPlan] with PredicateHelper
}
plan.transformExpressionsWithPruning(_.containsPattern(PLAN_EXPRESSION)) {
- case ScalarSubquery(sub, children, exprId, conditions, hint) if
children.nonEmpty =>
+ case ScalarSubquery(sub, children, exprId, conditions, hint,
mayHaveCountBugOld)
+ if children.nonEmpty =>
val (newPlan, newCond) = decorrelate(sub, plan)
- ScalarSubquery(newPlan, children, exprId, getJoinCondition(newCond,
conditions), hint)
+ val mayHaveCountBug = if (mayHaveCountBugOld.isEmpty) {
+ // Check whether the pre-rewrite subquery had empty
groupingExpressions. If yes, it may
+ // be subject to the COUNT bug. If it has non-empty
groupingExpressions, there is
+ // no COUNT bug.
+ val (topPart, havingNode, aggNode) = splitSubquery(sub)
Review Comment:
The new decorrelation framework also handles the count bug
`decorrelate(innerPlan, outerPlan, handleCountBug)` by inserting new joins with
the outer query. It's currently being used to handle the count bug for lateral
subqueries only since it changes the plan for scalar subqueries. We might want
to unify the way we handle the count bug in the future.
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