zhenlineo commented on code in PR #40796:
URL: https://github.com/apache/spark/pull/40796#discussion_r1184078816
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sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala:
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@@ -700,6 +684,34 @@ private[sql] object RelationalGroupedDataset {
new RelationalGroupedDataset(df, groupingExprs, groupType: GroupType)
}
+ private[sql] def handleGroupingExpression(
+ logicalPlan: LogicalPlan,
+ sparkSession: SparkSession,
+ groupingExprs: Seq[Expression]): (QueryExecution, Seq[Attribute]) = {
+ // Resolves grouping expressions.
+ val dummyPlan = Project(groupingExprs.map(alias),
LocalRelation(logicalPlan.output))
+ val analyzedPlan = sparkSession.sessionState.analyzer.execute(dummyPlan)
+ .asInstanceOf[Project]
+ sparkSession.sessionState.analyzer.checkAnalysis(analyzedPlan)
+ val aliasedGroupings = analyzedPlan.projectList
+
+ // Adds the grouping expressions that are not in base DataFrame into
outputs.
+ val addedCols = aliasedGroupings.filter(g =>
!logicalPlan.outputSet.contains(g.toAttribute))
+ val qe = Dataset.ofRows(
+ sparkSession,
+ Project(logicalPlan.output ++ addedCols, logicalPlan)).queryExecution
+
+ (qe, aliasedGroupings.map(_.toAttribute))
+ }
+
+ private def alias(expr: Expression): NamedExpression = expr match {
Review Comment:
This adds `case u: UnresolvedFunction => UnresolvedAlias(expr, None)`
mostly. Not sure why this is a special case here.
Regarding `TypedAggregate` logic, we can move it out around each
groupingExprs (a few places, a bit out of the scope of this PR) and aggExprs
(easy).
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