HyukjinKwon commented on a change in pull request #25215:
[SPARK-28445][SQL][Python] Fix error when PythonUDF is used in both group by
and aggregate expression
URL: https://github.com/apache/spark/pull/25215#discussion_r305661269
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
##########
@@ -2189,4 +2189,50 @@ class DataFrameSuite extends QueryTest with
SharedSQLContext {
|*(1) Range (0, 10, step=1, splits=2)""".stripMargin))
}
}
+
+ test("SPARK-28445: PythonUDF in grouping key and aggregate expressions") {
+ import IntegratedUDFTestUtils._
+
+ val scalaTestUDF = TestScalaUDF(name = "scalaUDF")
+ val pythonTestUDF = TestPythonUDF(name = "pyUDF")
+ assume(shouldTestPythonUDFs)
+
+ withTempView("testData") {
+ sql(
+ """CREATE OR REPLACE TEMPORARY VIEW testData AS
+ |SELECT * FROM VALUES
+ |(1, 1), (1, 2), (2, 1), (2, 2), (3, 1), (3, 2), (null, 1), (3,
null), (null, null)
+ |AS testData(a, b)""".stripMargin)
+
+ val base = spark.table("testData")
Review comment:
Ah, I would just use DSL here too although it's a bit ugly to handle `null`s.
```scala
val base = Seq(
(Some(1), Some(1)), (Some(1), Some(2)), (Some(2), Some(1)),
(Some(2), Some(2)), (Some(3), Some(1)), (Some(3), Some(2)),
(None, Some(1)), (Some(3), None), (None, None)).toDF("a", "b")
```
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