jingz-db commented on code in PR #48005:
URL: https://github.com/apache/spark/pull/48005#discussion_r1799926038
##########
python/pyspark/sql/pandas/group_ops.py:
##########
@@ -505,22 +514,75 @@ def transformWithStateUDF(
return result
- if isinstance(outputStructType, str):
- outputStructType = cast(StructType,
_parse_datatype_string(outputStructType))
+ def transformWithStateWithInitStateUDF(
+ statefulProcessorApiClient: StatefulProcessorApiClient,
+ key: Any,
+ inputRows: Iterator["PandasDataFrameLike"],
+ # for non first batch, initialStates will be None
Review Comment:
Added the above in the comments with other input combinations.
##########
python/pyspark/sql/pandas/group_ops.py:
##########
@@ -505,22 +514,75 @@ def transformWithStateUDF(
return result
- if isinstance(outputStructType, str):
- outputStructType = cast(StructType,
_parse_datatype_string(outputStructType))
+ def transformWithStateWithInitStateUDF(
+ statefulProcessorApiClient: StatefulProcessorApiClient,
+ key: Any,
+ inputRows: Iterator["PandasDataFrameLike"],
+ # for non first batch, initialStates will be None
+ initialStates: Iterator["PandasDataFrameLike"] = None
+ ) -> Iterator["PandasDataFrameLike"]:
+ handle = StatefulProcessorHandle(statefulProcessorApiClient)
+
+ if statefulProcessorApiClient.handle_state ==
StatefulProcessorHandleState.CREATED:
Review Comment:
You are correct. I also moved out the code block and run a local test with
partition number as "1" to confirm the implementation is correct.
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