[
https://issues.apache.org/jira/browse/SPARK-54480?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jungtaek Lim resolved SPARK-54480.
----------------------------------
Fix Version/s: 4.1.0
4.0.2
Resolution: Fixed
Issue resolved by pull request 53266
[https://github.com/apache/spark/pull/53266]
> Reenable test_accessing_spark_session_*
> ---------------------------------------
>
> Key: SPARK-54480
> URL: https://issues.apache.org/jira/browse/SPARK-54480
> Project: Spark
> Issue Type: Sub-task
> Components: Tests
> Affects Versions: 4.1.0, 4.0.1, 4.2.0
> Reporter: Hyukjin Kwon
> Assignee: Jungtaek Lim
> Priority: Major
> Fix For: 4.1.0, 4.0.2
>
>
> {code}
> ======================================================================
> ERROR [10.037s]: test_accessing_spark_session
> (pyspark.sql.tests.connect.streaming.test_parity_foreach_batch.StreamingForeachBatchParityTests.test_accessing_spark_session)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/home/runner/work/spark/spark-4.0/python/pyspark/sql/tests/connect/streaming/test_parity_foreach_batch.py",
> line 117, in test_accessing_spark_session
> q = df.writeStream.foreachBatch(func).start()
> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> File
> "/home/runner/work/spark/spark-4.0/python/pyspark/sql/connect/streaming/readwriter.py",
> line 656, in start
> return self._start_internal(
> ^^^^^^^^^^^^^^^^^^^^^
> File
> "/home/runner/work/spark/spark-4.0/python/pyspark/sql/connect/streaming/readwriter.py",
> line 625, in _start_internal
> (_, properties, _) = self._session.client.execute_command(cmd)
> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> File
> "/home/runner/work/spark/spark-4.0/python/pyspark/sql/connect/client/core.py",
> line 1148, in execute_command
> data, _, metrics, observed_metrics, properties = self._execute_and_fetch(
> ^^^^^^^^^^^^^^^^^^^^^^^^
> File
> "/home/runner/work/spark/spark-4.0/python/pyspark/sql/connect/client/core.py",
> line 1560, in _execute_and_fetch
> for response in self._execute_and_fetch_as_iterator(
> File
> "/home/runner/work/spark/spark-4.0/python/pyspark/sql/connect/client/core.py",
> line 1537, in _execute_and_fetch_as_iterator
> self._handle_error(error)
> File
> "/home/runner/work/spark/spark-4.0/python/pyspark/sql/connect/client/core.py",
> line 1811, in _handle_error
> self._handle_rpc_error(error)
> File
> "/home/runner/work/spark/spark-4.0/python/pyspark/sql/connect/client/core.py",
> line 1882, in _handle_rpc_error
> raise convert_exception(
> pyspark.errors.exceptions.connect.SparkException: Python worker failed to
> connect back.
> JVM stacktrace:
> org.apache.spark.SparkException
> at
> org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:281)
> at
> org.apache.spark.api.python.StreamingPythonRunner.init(StreamingPythonRunner.scala:79)
> at
> org.apache.spark.sql.connect.planner.StreamingForeachBatchHelper$.pythonForeachBatchWrapper(StreamingForeachBatchHelper.scala:154)
> at
> org.apache.spark.sql.connect.planner.SparkConnectPlanner.handleWriteStreamOperationStart(SparkConnectPlanner.scala:3497)
> at
> org.apache.spark.sql.connect.planner.SparkConnectPlanner.process(SparkConnectPlanner.scala:2844)
> at
> org.apache.spark.sql.connect.execution.SparkConnectPlanExecution.handlePlan(SparkConnectPlanExecution.scala:95)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.$anonfun$executeInternal$1(ExecuteThreadRunner.scala:225)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.$anonfun$executeInternal$1$adapted(ExecuteThreadRunner.scala:197)
> at
> org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withSession$2(SessionHolder.scala:396)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:804)
> at
> org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withSession$1(SessionHolder.scala:396)
> at
> org.apache.spark.JobArtifactSet$.withActiveJobArtifactState(JobArtifactSet.scala:94)
> at
> org.apache.spark.sql.artifact.ArtifactManager.$anonfun$withResources$1(ArtifactManager.scala:112)
> at org.apache.spark.util.Utils$.withContextClassLoader(Utils.scala:185)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withClassLoaderIfNeeded(ArtifactManager.scala:102)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withResources(ArtifactManager.scala:111)
> at
> org.apache.spark.sql.connect.service.SessionHolder.withSession(SessionHolder.scala:395)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.executeInternal(ExecuteThreadRunner.scala:197)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.org$apache$spark$sql$connect$execution$ExecuteThreadRunner$$execute(ExecuteThreadRunner.scala:126)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner$ExecutionThread.run(ExecuteThreadRunner.scala:334)
> Caused by: java.net.SocketTimeoutException: Timed out while waiting for the
> Python worker to connect back
> at
> org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:263)
> at
> org.apache.spark.api.python.StreamingPythonRunner.init(StreamingPythonRunner.scala:79)
> at
> org.apache.spark.sql.connect.planner.StreamingForeachBatchHelper$.pythonForeachBatchWrapper(StreamingForeachBatchHelper.scala:154)
> at
> org.apache.spark.sql.connect.planner.SparkConnectPlanner.handleWriteStreamOperationStart(SparkConnectPlanner.scala:3497)
> at
> org.apache.spark.sql.connect.planner.SparkConnectPlanner.process(SparkConnectPlanner.scala:2844)
> at
> org.apache.spark.sql.connect.execution.SparkConnectPlanExecution.handlePlan(SparkConnectPlanExecution.scala:95)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.$anonfun$executeInternal$1(ExecuteThreadRunner.scala:225)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.$anonfun$executeInternal$1$adapted(ExecuteThreadRunner.scala:197)
> at
> org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withSession$2(SessionHolder.scala:396)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:804)
> at
> org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withSession$1(SessionHolder.scala:396)
> at
> org.apache.spark.JobArtifactSet$.withActiveJobArtifactState(JobArtifactSet.scala:94)
> at
> org.apache.spark.sql.artifact.ArtifactManager.$anonfun$withResources$1(ArtifactManager.scala:112)
> at org.apache.spark.util.Utils$.withContextClassLoader(Utils.scala:185)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withClassLoaderIfNeeded(ArtifactManager.scala:102)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withResources(ArtifactManager.scala:111)
> at
> org.apache.spark.sql.connect.service.SessionHolder.withSession(SessionHolder.scala:395)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.executeInternal(ExecuteThreadRunner.scala:197)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.org$apache$spark$sql$connect$execution$ExecuteThreadRunner$$execute(ExecuteThreadRunner.scala:126)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner$ExecutionThread.run(ExecuteThreadRunner.scala:334)
> During handling of the above exception, another exception occurred:
> Traceback (most recent call last):
> File
> "/home/runner/work/spark/spark-4.0/python/pyspark/sql/tests/connect/streaming/test_parity_foreach_batch.py",
> line 121, in test_accessing_spark_session
> if q:
> ^
> UnboundLocalError: cannot access local variable 'q' where it is not
> associated with a value
> ======================================================================
> ERROR [10.027s]: test_accessing_spark_session_through_df
> (pyspark.sql.tests.connect.streaming.test_parity_foreach_batch.StreamingForeachBatchParityTests.test_accessing_spark_session_through_df)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/home/runner/work/spark/spark-4.0/python/pyspark/sql/tests/connect/streaming/test_parity_foreach_batch.py",
> line 132, in test_accessing_spark_session_through_df
> q = df.writeStream.foreachBatch(func).start()
> at
> org.apache.spark.sql.connect.planner.SparkConnectPlanner.process(SparkConnectPlanner.scala:2844)
> at
> org.apache.spark.sql.connect.execution.SparkConnectPlanExecution.handlePlan(SparkConnectPlanExecution.scala:95)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.$anonfun$executeInternal$1(ExecuteThreadRunner.scala:225)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.$anonfun$executeInternal$1$adapted(ExecuteThreadRunner.scala:197)
> at
> org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withSession$2(SessionHolder.scala:396)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:804)
> at
> org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withSession$1(SessionHolder.scala:396)
> at
> org.apache.spark.JobArtifactSet$.withActiveJobArtifactState(JobArtifactSet.scala:94)
> at
> org.apache.spark.sql.artifact.ArtifactManager.$anonfun$withResources$1(ArtifactManager.scala:112)
> at org.apache.spark.util.Utils$.withContextClassLoader(Utils.scala:185)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withClassLoaderIfNeeded(ArtifactManager.scala:102)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withResources(ArtifactManager.scala:111)
> at
> org.apache.spark.sql.connect.service.SessionHolder.withSession(SessionHolder.scala:395)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.executeInternal(ExecuteThreadRunner.scala:197)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.org$apache$spark$sql$connect$execution$ExecuteThreadRunner$$execute(ExecuteThreadRunner.scala:126)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner$ExecutionThread.run(ExecuteThreadRunner.scala:334)
> Caused by: java.net.SocketTimeoutException: Timed out while waiting for the
> Python worker to connect back
> at
> org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:263)
> at
> org.apache.spark.api.python.StreamingPythonRunner.init(StreamingPythonRunner.scala:79)
> at
> org.apache.spark.sql.connect.planner.StreamingForeachBatchHelper$.pythonForeachBatchWrapper(StreamingForeachBatchHelper.scala:154)
> at
> org.apache.spark.sql.connect.planner.SparkConnectPlanner.handleWriteStreamOperationStart(SparkConnectPlanner.scala:3497)
> at
> org.apache.spark.sql.connect.planner.SparkConnectPlanner.process(SparkConnectPlanner.scala:2844)
> at
> org.apache.spark.sql.connect.execution.SparkConnectPlanExecution.handlePlan(SparkConnectPlanExecution.scala:95)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.$anonfun$executeInternal$1(ExecuteThreadRunner.scala:225)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.$anonfun$executeInternal$1$adapted(ExecuteThreadRunner.scala:197)
> at
> org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withSession$2(SessionHolder.scala:396)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:804)
> at
> org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withSession$1(SessionHolder.scala:396)
> at
> org.apache.spark.JobArtifactSet$.withActiveJobArtifactState(JobArtifactSet.scala:94)
> at
> org.apache.spark.sql.artifact.ArtifactManager.$anonfun$withResources$1(ArtifactManager.scala:112)
> at org.apache.spark.util.Utils$.withContextClassLoader(Utils.scala:185)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withClassLoaderIfNeeded(ArtifactManager.scala:102)
> at
> org.apache.spark.sql.artifact.ArtifactManager.withResources(ArtifactManager.scala:111)
> at
> org.apache.spark.sql.connect.service.SessionHolder.withSession(SessionHolder.scala:395)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.executeInternal(ExecuteThreadRunner.scala:197)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner.org$apache$spark$sql$connect$execution$ExecuteThreadRunner$$execute(ExecuteThreadRunner.scala:126)
> at
> org.apache.spark.sql.connect.execution.ExecuteThreadRunner$ExecutionThread.run(ExecuteThreadRunner.scala:334)
> ----------------------------------------------------------------------
> {code}
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