WweiL commented on code in PR #40736:
URL: https://github.com/apache/spark/pull/40736#discussion_r1163209147
##########
python/pyspark/sql/connect/group.py:
##########
@@ -262,8 +264,44 @@ def applyInPandas(
applyInPandas.__doc__ = PySparkGroupedData.applyInPandas.__doc__
- def applyInPandasWithState(self, *args: Any, **kwargs: Any) -> None:
- raise NotImplementedError("applyInPandasWithState() is not
implemented.")
+ def applyInPandasWithState(
+ self,
+ func: "PandasGroupedMapFunctionWithState",
+ outputStructType: Union[StructType, str],
+ stateStructType: Union[StructType, str],
+ outputMode: str,
+ timeoutConf: str
+ ) -> "DataFrame":
+ from pyspark.sql.connect.udf import UserDefinedFunction
+ from pyspark.sql.connect.dataframe import DataFrame
+
+ udf_obj = UserDefinedFunction(
+ func,
+ returnType=outputStructType,
+ evalType=PythonEvalType.SQL_GROUPED_MAP_PANDAS_UDF_WITH_STATE,
+ )
+
+ output_schema: str = outputStructType.json() if
isinstance(outputStructType, StructType)\
Review Comment:
I'm not very sure if we could do like this? Above in `UserDefinedFunction`,
it takes the same `outputStructType `, but handles it differently
https://github.com/apache/spark/blob/007a42b8511b005aabdf45955e504d1f71eb1d25/python/pyspark/sql/connect/udf.py#L101
and then
https://github.com/apache/spark/blob/007a42b8511b005aabdf45955e504d1f71eb1d25/python/pyspark/sql/connect/expressions.py#L595-L598
Should we also follow this pattern?
Maybe @ueshin has more context?
##########
python/pyspark/sql/connect/group.py:
##########
@@ -262,8 +264,44 @@ def applyInPandas(
applyInPandas.__doc__ = PySparkGroupedData.applyInPandas.__doc__
- def applyInPandasWithState(self, *args: Any, **kwargs: Any) -> None:
- raise NotImplementedError("applyInPandasWithState() is not
implemented.")
+ def applyInPandasWithState(
+ self,
+ func: "PandasGroupedMapFunctionWithState",
+ outputStructType: Union[StructType, str],
+ stateStructType: Union[StructType, str],
+ outputMode: str,
+ timeoutConf: str
+ ) -> "DataFrame":
+ from pyspark.sql.connect.udf import UserDefinedFunction
+ from pyspark.sql.connect.dataframe import DataFrame
+
+ udf_obj = UserDefinedFunction(
+ func,
+ returnType=outputStructType,
+ evalType=PythonEvalType.SQL_GROUPED_MAP_PANDAS_UDF_WITH_STATE,
+ )
+
+ output_schema: str = outputStructType.json() if
isinstance(outputStructType, StructType)\
Review Comment:
I'm not very sure if we could do like this? Above in `UserDefinedFunction`,
it takes the same `outputStructType`, but handles it differently
https://github.com/apache/spark/blob/007a42b8511b005aabdf45955e504d1f71eb1d25/python/pyspark/sql/connect/udf.py#L101
and then
https://github.com/apache/spark/blob/007a42b8511b005aabdf45955e504d1f71eb1d25/python/pyspark/sql/connect/expressions.py#L595-L598
Should we also follow this pattern?
Maybe @ueshin has more context?
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