Kimahriman commented on a change in pull request #32448:
URL: https://github.com/apache/spark/pull/32448#discussion_r634518604
##########
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:
It's just weird because it's different behavior than every other part of
spark. `withColumn` and `withField` both append to the end. And currently
before this PR and if the I applied the tweak `df1.unionByname(df2, True)`
would not always have the same schema as `df2.unionByName(df1, True)`. It only
sorts nested struct fields, not the top level attributes.
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