Kimahriman commented on a change in pull request #32448: URL: https://github.com/apache/spark/pull/32448#discussion_r633698385
########## File path: sql/core/src/test/scala/org/apache/spark/sql/DataFrameSetOperationsSuite.scala ########## @@ -743,17 +777,59 @@ class DataFrameSetOperationsSuite extends QueryTest with SharedSparkSession { StructField("a", StringType))) val nestedStructValues2 = Row("b", "a") - val df1: DataFrame = spark.createDataFrame( + val df1 = spark.createDataFrame( sparkContext.parallelize(Row(nestedStructValues1) :: Nil), StructType(Seq(StructField("topLevelCol", nestedStructType1)))) - val df2: DataFrame = spark.createDataFrame( + val df2 = spark.createDataFrame( sparkContext.parallelize(Row(nestedStructValues2) :: Nil), StructType(Seq(StructField("topLevelCol", nestedStructType2)))) val union = df1.unionByName(df2, allowMissingColumns = true) - checkAnswer(union, Row(Row(null, "b")) :: Row(Row("a", "b")) :: Nil) - assert(union.schema.toDDL == "`topLevelCol` STRUCT<`a`: STRING, `b`: STRING>") + assert(union.schema.toDDL == "`topLevelCol` STRUCT<`b`: STRING, `a`: STRING>") + checkAnswer(union, Row(Row("b", null)) :: Row(Row("b", "a")) :: Nil) + } + + test("SPARK-35290: Make unionByName null-filling behavior work with struct columns" + + " - sorting edge case") { + val nestedStructType1 = StructType(Seq( + StructField("b", StructType(Seq( + StructField("ba", StringType) + ))) + )) + val nestedStructValues1 = Row(Row("ba")) + + val nestedStructType2 = StructType(Seq( + StructField("a", StructType(Seq( + StructField("aa", StringType) + ))), + StructField("b", StructType(Seq( + StructField("bb", StringType) + ))) + )) + val nestedStructValues2 = Row(Row("aa"), Row("bb")) + + val df1 = spark.createDataFrame( + sparkContext.parallelize(Row(nestedStructValues1) :: Nil), + StructType(Seq(StructField("topLevelCol", nestedStructType1)))) + + val df2 = spark.createDataFrame( + sparkContext.parallelize(Row(nestedStructValues2) :: Nil), + StructType(Seq(StructField("topLevelCol", nestedStructType2)))) + + var unionDf = df1.unionByName(df2, true) + assert(unionDf.schema.toDDL == "`topLevelCol` " + + "STRUCT<`b`: STRUCT<`ba`: STRING, `bb`: STRING>, `a`: STRUCT<`aa`: STRING>>") + checkAnswer(unionDf, + Row(Row(Row("ba", null), null)) :: + Row(Row(Row(null, "bb"), Row("aa"))) :: Nil) + + unionDf = df2.unionByName(df1, true) + assert(unionDf.schema.toDDL == "`topLevelCol` STRUCT<`a`: STRUCT<`aa`: STRING>, " + + "`b`: STRUCT<`bb`: STRING, `ba`: STRING>>") + checkAnswer(unionDf, + Row(Row(null, Row(null, "ba"))) :: + Row(Row(Row("aa"), Row("bb", null))) :: Nil) Review comment: The union throws an analysis exception because the right side gets corrupted. It's the same example I have in the issue: https://issues.apache.org/jira/browse/SPARK-35290 -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org