HeartSaVioR commented on a change in pull request #28830:
URL: https://github.com/apache/spark/pull/28830#discussion_r439965525
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File path: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
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@@ -2541,7 +2541,9 @@ 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 keep `toSet.toSeq` here because of the backward
compatibility issue
+ // (the Streaming's state store depends on the `groupCols` order).
+ val groupCols = colNames.toSet.toSeq.flatMap { (colName: String) =>
Review comment:
Worth noting that we need to have "concrete" solution eventually - if
columns are all having same type neither #28830 nor #24173 catch the change and
the result becomes silently incorrect. I roughly remember the similar issue on
pyspark, which was trying to fix the issue on order vs name, don't remember how
it ended up. cc. @HyukjinKwon
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