Hyukjin Kwon created SPARK-50908:
------------------------------------
Summary: Fix flay
pyspark.sql.tests.pandas.test_pandas_transform_with_state.TransformWithStateInPandasTests
Key: SPARK-50908
URL: https://issues.apache.org/jira/browse/SPARK-50908
Project: Spark
Issue Type: Sub-task
Components: PySpark, Structured Streaming
Affects Versions: 4.0.0
Reporter: Hyukjin Kwon
https://github.com/apache/spark/actions/runs/12883552117/job/35918143550
{code}
======================================================================
ERROR [10.759s]: test_value_state_ttl_expiration
(pyspark.sql.tests.pandas.test_pandas_transform_with_state.TransformWithStateInPandasTests)
----------------------------------------------------------------------
Traceback (most recent call last):
File
"/__w/spark/spark/python/pyspark/sql/tests/pandas/test_pandas_transform_with_state.py",
line 422, in test_value_state_ttl_expiration
q.processAllAvailable()
File "/__w/spark/spark/python/pyspark/sql/streaming/query.py", line 351, in
processAllAvailable
return self._jsq.processAllAvailable()
File
"/__w/spark/spark/python/lib/py4j-0.10.9.9-src.zip/py4j/java_gateway.py", line
1362, in __call__
return_value = get_return_value(
File "/__w/spark/spark/python/pyspark/errors/exceptions/captured.py", line
253, in deco
raise converted from None
pyspark.errors.exceptions.captured.StreamingQueryException: [STREAM_FAILED]
Query [id = 8e860141-b4c1-445b-be17-7f46f4a8e1dc, runId =
8b11487b-67b9-4cfb-9176-a421032ff236] terminated with exception:
[FOREACH_BATCH_USER_FUNCTION_ERROR] An error occurred in the user provided
function in foreach batch sink. Reason: An exception was raised by the Python
Proxy. Return Message: Traceback (most recent call last):
File
"/__w/spark/spark/python/lib/py4j-0.10.9.9-src.zip/py4j/clientserver.py", line
644, in _call_proxy
return_value = getattr(self.pool[obj_id], method)(*params)
File "/__w/spark/spark/python/pyspark/sql/utils.py", line 165, in call
raise e
File "/__w/spark/spark/python/pyspark/sql/utils.py", line 162, in call
self.func(DataFrame(jdf, wrapped_session_jdf), batch_id)
File
"/__w/spark/spark/python/pyspark/sql/tests/pandas/test_pandas_transform_with_state.py",
line 374, in check_results
assertDataFrameEqual(
File "/__w/spark/spark/python/pyspark/testing/utils.py", line 1039, in
assertDataFrameEqual
assert_rows_equal(actual_list, expected_list, maxErrors=maxErrors,
showOnlyDiff=showOnlyDiff)
File "/__w/spark/spark/python/pyspark/testing/utils.py", line 995, in
assert_rows_equal
raise PySparkAssertionError(
pyspark.errors.exceptions.base.PySparkAssertionError: [DIFFERENT_ROWS] Results
do not match: ( 37.50000 % )
*** actual ***
Row(id='count-0', count=3)
Row(id='count-1', count=3)
! Row(id='ttl-count-0', count=2)
Row(id='ttl-count-1', count=3)
! Row(id='ttl-list-state-count-0', count=3)
Row(id='ttl-list-state-count-1', count=7)
! Row(id='ttl-map-state-count-0', count=2)
Row(id='ttl-map-state-count-1', count=3)
*** expected ***
Row(id='count-0', count=3)
Row(id='count-1', count=3)
! Row(id='ttl-count-0', count=1)
Row(id='ttl-count-1', count=3)
! Row(id='ttl-list-state-count-0', count=1)
Row(id='ttl-list-state-count-1', count=7)
! Row(id='ttl-map-state-count-0', count=1)
Row(id='ttl-map-state-count-1', count=3)
SQLSTATE: 39000 SQLSTATE: XXKST
=== Streaming Query ===
Identifier: [id = 8e860141-b4c1-445b-be17-7f46f4a8e1dc, runId =
8b11487b-67b9-4cfb-9176-a421032ff236]
Current Committed Offsets:
{FileStreamSource[file:/__w/spark/spark/python/target/c80337ee-345b-4c00-b9b5-bfaf49d18854/tmpg_utvcka]:
{"logOffset":1}}
Current Available Offsets:
{FileStreamSource[file:/__w/spark/spark/python/target/c80337ee-345b-4c00-b9b5-bfaf49d18854/tmpg_utvcka]:
{"logOffset":2}}
Current State: ACTIVE
Thread State: RUNNABLE
Logical Plan:
~WriteToMicroBatchDataSourceV1 ForeachBatchSink,
8e860141-b4c1-445b-be17-7f46f4a8e1dc, Update
+- ~TransformWithStateInPandas transformWithStateUDF(id#15428,
temperature#15429)#15430, 1, [id#15431, count#15432], Update, ProcessingTime,
false, 0
:- ~Project [id#15428, id#15428, temperature#15429]
: +- ~Project [cast(split_values#15425[0] as string) AS id#15428,
cast(split_values#15425[1] as int) AS temperature#15429]
: +- ~Project [value#15423, split(value#15423, ,, -1) AS
split_values#15425]
: +- ~StreamingExecutionRelation
FileStreamSource[file:/__w/spark/spark/python/target/c80337ee-345b-4c00-b9b5-bfaf49d18854/tmpg_utvcka],
[value#15423]
+- LocalRelation <empty>
JVM stacktrace:
org.apache.spark.sql.streaming.StreamingQueryException: An exception was raised
by the Python Proxy. Return Message: Traceback (most recent call last):
File
"/__w/spark/spark/python/lib/py4j-0.10.9.9-src.zip/py4j/clientserver.py", line
644, in _call_proxy
at
org.apache.spark.sql.artifact.ArtifactManager.withClassLoaderIfNeeded(ArtifactManager.scala:105)
at
org.apache.spark.sql.artifact.ArtifactManager.withResources(ArtifactManager.scala:110)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$6(SQLExecution.scala:124)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:291)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$1(SQLExecution.scala:123)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:791)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId0(SQLExecution.scala:77)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:233)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$16(MicroBatchExecution.scala:875)
at
org.apache.spark.sql.execution.streaming.ProgressContext.reportTimeTaken(ProgressReporter.scala:185)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:875)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$executeOneBatch$2(MicroBatchExecution.scala:393)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.scala:18)
at
org.apache.spark.sql.execution.streaming.ProgressContext.reportTimeTaken(ProgressReporter.scala:185)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.executeOneBatch(MicroBatchExecution.scala:363)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:343)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1$adapted(MicroBatchExecution.scala:343)
at
org.apache.spark.sql.execution.streaming.TriggerExecutor.runOneBatch(TriggerExecutor.scala:39)
at
org.apache.spark.sql.execution.streaming.TriggerExecutor.runOneBatch$(TriggerExecutor.scala:37)
at
org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.runOneBatch(TriggerExecutor.scala:70)
at
org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:82)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:343)
at
org.apache.spark.sql.execution.streaming.StreamExecution.$anonfun$runStream$1(StreamExecution.scala:337)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.scala:18)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:791)
at
org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:311)
... 1 more
{code}
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