[GitHub] [spark] maropu commented on pull request #31404: [SPARK-34283][SQL] Combines all adjacent 'Union' operators into a single 'Union' when using 'Dataset.union.distinct.union.distinct'

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

maropu commented on pull request #31404:
URL: https://github.com/apache/spark/pull/31404#issuecomment-770518381


   How about the case where `dropDuplicates` has different `keys` in each operations like this?
   ```
   val df1 = Seq((1, 2, 3)).toDF("a", "b", "c")
   val df2 = Seq((1, 2, 5)).toDF("a", "b", "c")
   val df3 = Seq((2, 4, 3)).toDF("a", "b", "c")
   val df4 = Seq((1, 4, 5)).toDF("a", "b", "c")
   df1.union(df2).dropDuplicates(Seq("a")).union(df3).dropDuplicates("c").union(df4).dropDuplicates("b")
   ```


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