maropu commented on a change in pull request #28830:
URL: https://github.com/apache/spark/pull/28830#discussion_r439904040
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File path: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
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@@ -2541,7 +2542,20 @@ class Dataset[T] private[sql](
def dropDuplicates(colNames: Seq[String]): Dataset[T] = withTypedPlan {
val resolver = sparkSession.sessionState.analyzer.resolver
val allColumns = queryExecution.analyzed.output
- val groupCols = colNames.distinct.flatMap { (colName: String) =>
+ // SPARK-31990: We must preserve the input order of `colNames` because of
the compatibility
+ // issue (the Streaming's state store depends on the `groupCols` order).
+ val orderPreservingDistinctColNames = {
+ val nameSeen = mutable.Set[String]()
Review comment:
Ah, I see and it looks the same:
https://github.com/scala/scala/blob/2.12.x/src/library/scala/collection/SeqLike.scala#L504-L523
But, (I'm not a Scala compiler expert though), the `distinct` scala API makes
sure an input order is preserved? I read [the @HeartSaVioR comment
](https://issues.apache.org/jira/browse/SPARK-31990?focusedCommentId=17135286&page=com.atlassian.jira.plugin.system.issuetabpanels%3Acomment-tabpanel#comment-17135286)
in the Jira, then I'm not sure about that. So, I wrote this method to preserve
the order explicitly for safeguard.
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