SaurabhChawla100 commented on pull request #32972:
URL: https://github.com/apache/spark/pull/32972#issuecomment-864455597
> I think it works in current master, no?
>
> ```
> scala> val df1 = Seq((1, Struct1(1, 2))).toDF("a", "b")
> df1: org.apache.spark.sql.DataFrame = [a: int, b: struct<c1: int, c2: int>]
>
> scala> val df2 = Seq((1, Struct2(1, 2))).toDF("a", "b")
> df2: org.apache.spark.sql.DataFrame = [a: int, b: struct<c2: int, c1: int>]
>
> scala> val unionDF = df1.unionByName(df2, true)
> unionDF: org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = [a: int,
b: struct<c1: int, c2: int>]
>
> scala> unionDF.show
> +---+------+
> | a| b|
> +---+------+
> | 1|{1, 2}|
> | 1|{2, 1}|
> +---+------+
> ```
yes this is ` val unionDF = df1.unionByName(df2, true)` working in the
current master but this is giving exception `val unionDF =
df1.unionByName(df2)` , So the change is done to make this scenario working.
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