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




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