[GitHub] [spark] cloud-fan commented on a change in pull request #35490: [SPARK-38185][SQL] Fix data incorrect if aggregate function is empty

[GitBox <gi...@apache.org>]

cloud-fan commented on a change in pull request #35490:
URL: https://github.com/apache/spark/pull/35490#discussion_r804410010



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File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
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@@ -984,7 +984,8 @@ case class Aggregate(
 
   // Whether this Aggregate operator is group only. For example: SELECT a, a FROM t GROUP BY a
   private[sql] def groupOnly: Boolean = {
-    aggregateExpressions.map {
+    // aggregateExpressions can be empty through Dateset.agg
+    aggregateExpressions.nonEmpty && aggregateExpressions.map {

Review comment:
       is it more explicit to check `groupingExpressions.nonEmpty`? Logically, an aggregate operator without output columns is still group only if it has group columns.




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