Github user icexelloss commented on a diff in the pull request: https://github.com/apache/spark/pull/22620#discussion_r222456993 --- Diff: python/pyspark/sql/udf.py --- @@ -310,9 +319,11 @@ def register(self, name, f, returnType=None): "Invalid returnType: data type can not be specified when f is" "a user-defined function, but got %s." % returnType) if f.evalType not in [PythonEvalType.SQL_BATCHED_UDF, - PythonEvalType.SQL_SCALAR_PANDAS_UDF]: + PythonEvalType.SQL_SCALAR_PANDAS_UDF, + PythonEvalType.SQL_GROUPED_AGG_PANDAS_UDF]: --- End diff -- We don't need it here: Users specify GROUPED_AGG only. GROUPED_AGG is turned to WINDOW_AGG eval type in WindowInPandasExec. Admittedly, there is a bit confusion here we can improve. We just haven't got a user specified udf type that maps to multiple evalType before WINDOW_AGG.
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