cloud-fan commented on a change in pull request #28490:
URL: https://github.com/apache/spark/pull/28490#discussion_r470635433
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
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@@ -1479,6 +1479,33 @@ class Analyzer(
// Skip the having clause here, this will be handled in
ResolveAggregateFunctions.
case h: UnresolvedHaving => h
+ case agg @ (_: Aggregate | _: GroupingSets) =>
+ val resolved = agg.mapExpressions(resolveExpressionTopDown(_, agg))
+ val hasStructField = resolved.expressions.exists {
+ _.collectFirst { case gsf: GetStructField => gsf }.isDefined
+ }
+ if (hasStructField) {
+ // For struct field, it will be resolve as Alias(GetStructField,
name),
+ // In Aggregate/GroupingSets this behavior will cause same struct
field
+ // in aggExprs/groupExprs/selectedGroupByExprs will be resolved
divided
+ // with different ExprId of Alias and replace failed when construct
+ // Aggregate in ResolveGroupingAnalytics, so we resolve duplicated
struct
+ // field here with same ExprId
+ val structFieldMap = mutable.Map[String, Alias]()
+ resolved.transformExpressionsDown {
Review comment:
another concern: for `SELECT a.b, a.b FROM t GROUP BY a.b`, will we end
up with an `Aggregate` operator whose output has duplicated ExprId? It's
probably not an issue as the two output columns always have the same value.
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