bogao007 commented on code in PR #48838:
URL: https://github.com/apache/spark/pull/48838#discussion_r1844724391
##########
python/pyspark/sql/streaming/stateful_processor.py:
##########
@@ -420,10 +411,27 @@ def handleInputRows(
timer_values: TimerValues
Timer value for the current batch that process the input
rows.
Users can get the processing or event time timestamp
from TimerValues.
+ """
+ return iter([])
Review Comment:
Why do we change the `...` placeholder here?
##########
python/pyspark/sql/streaming/stateful_processor.py:
##########
@@ -420,10 +411,27 @@ def handleInputRows(
timer_values: TimerValues
Timer value for the current batch that process the input
rows.
Users can get the processing or event time timestamp
from TimerValues.
+ """
+ return iter([])
+
+ def handleExpiredTimer(
Review Comment:
Just double check that this method is not required for users to implement,
correct?
##########
python/pyspark/sql/pandas/group_ops.py:
##########
@@ -573,7 +568,16 @@ def transformWithStateUDF(
statefulProcessorApiClient.set_handle_state(StatefulProcessorHandleState.CLOSED)
return iter([])
- result = handle_data_with_timers(statefulProcessorApiClient, key,
inputRows)
+ if timeMode != "none":
+ batch_timestamp =
statefulProcessorApiClient.get_batch_timestamp()
+ watermark_timestamp =
statefulProcessorApiClient.get_watermark_timestamp()
+ else:
+ batch_timestamp = -1
+ watermark_timestamp = -1
Review Comment:
Can we abstract this as a separate method and share in both UDFs to reduce
redundant code?
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