zhengruifeng commented on code in PR #46397:
URL: https://github.com/apache/spark/pull/46397#discussion_r1590766241
##########
python/pyspark/sql/connect/group.py:
##########
@@ -398,11 +398,18 @@ def applyInPandas(
) -> "DataFrame":
from pyspark.sql.connect.udf import UserDefinedFunction
from pyspark.sql.connect.dataframe import DataFrame
+ from pyspark.sql.pandas.functions import _validate_pandas_udf # type:
ignore[attr-defined]
+
+ evalType = _validate_pandas_udf(
+ func,
+ schema,
+ PythonEvalType.SQL_COGROUPED_MAP_PANDAS_UDF,
+ )
udf_obj = UserDefinedFunction(
Review Comment:
PySpark Classic directly uses the `pandas_udf` method which include this
check
https://github.com/apache/spark/blob/c74f584481d9bcefda7e8ac2a37feb2d61891fe4/python/pyspark/sql/pandas/group_ops.py#L617-L620
while in Spark Connect, it cannot use the output of `pandas_udf` method here
and requires a `UserDefinedFunction` object.
So I factor the check to a separate method and invoke it here.
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