[GitHub] [spark] zhengruifeng commented on a diff in pull request #39254: [SPARK-41333][SPARK-41737] Implement `GroupedData.{min, max, avg, sum}`

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

zhengruifeng commented on code in PR #39254:
URL: https://github.com/apache/spark/pull/39254#discussion_r1058084926


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connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala:
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@@ -1061,6 +1068,81 @@ class SparkConnectPlanner(session: SparkSession) {
     }
   }
 
+  private def transformNumericAggregate(agg: proto.Aggregate): LogicalPlan = {

Review Comment:
   I believe it's necessary to have a separate method for it, actually at first I attempted to implement it in existing `transformAggregate` then I found that the two paths are too different:
   1, for the regular agg, we build the logical plan;
   2, for the numeric agg, we have to use the dataframe API to avoid doing the analysis by myself.
   



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