See 
<https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/869/display/redirect?page=changes>

Changes:

[noreply] update Beam GCP BOM (#24929)

[noreply] [#24931][Go SDK] Make element checkpoints independant (#24932)

[noreply] Update Kafka watermark based on policy when records poll empty 
(#24205)

[noreply] Grafana dashboard - Github actions postcommit workflows mapping 
(#24176)

[noreply] Shard Python PreCommit (#24866)

[noreply] reapply single executor to storage write API writes (#24950)

[noreply] [#21368] Clean-up and use the FixedExecutorProvider (#24952)

[noreply] Add doLast on Playground integration tests (#24954) (#24955)


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> Task :sdks:python:apache_beam:testing:load_tests:run
INFO:apache_beam.runners.portability.stager:Copying Beam SDK 
"/home/jenkins/jenkins-slave/workspace/beam_LoadTests_Python_Combine_Dataflow_Streaming/src/sdks/python/build/apache-beam.tar.gz"
 to staging location.
INFO:apache_beam.runners.dataflow.dataflow_runner:Pipeline has additional 
dependencies to be installed in SDK **** container, consider using the SDK 
container image pre-building workflow to avoid repetitive installations. Learn 
more on 
https://cloud.google.com/dataflow/docs/guides/using-custom-containers#prebuild
INFO:root:Default Python SDK image for environment is 
apache/beam_python3.7_sdk:2.45.0.dev
INFO:root:Using provided Python SDK container image: 
gcr.io/cloud-dataflow/v1beta3/python37-fnapi:beam-master-20221205
INFO:root:Python SDK container image set to 
"gcr.io/cloud-dataflow/v1beta3/python37-fnapi:beam-master-20221205" for Docker 
environment
INFO:apache_beam.runners.dataflow.internal.apiclient:Defaulting to the 
temp_location as staging_location: gs://temp-storage-for-perf-tests/smoketests
INFO:apache_beam.internal.gcp.auth:Setting socket default timeout to 60 seconds.
INFO:apache_beam.internal.gcp.auth:socket default timeout is 60.0 seconds.
INFO:apache_beam.runners.dataflow.internal.apiclient:Starting GCS upload to 
gs://temp-storage-for-perf-tests/smoketests/load-tests-python-dataflow-streaming-combine-1-0110150204.1673363280.933072/dataflow_python_sdk.tar...
INFO:apache_beam.runners.dataflow.internal.apiclient:Completed GCS upload to 
gs://temp-storage-for-perf-tests/smoketests/load-tests-python-dataflow-streaming-combine-1-0110150204.1673363280.933072/dataflow_python_sdk.tar
 in 0 seconds.
INFO:apache_beam.runners.dataflow.internal.apiclient:Starting GCS upload to 
gs://temp-storage-for-perf-tests/smoketests/load-tests-python-dataflow-streaming-combine-1-0110150204.1673363280.933072/pipeline.pb...
INFO:apache_beam.runners.dataflow.internal.apiclient:Completed GCS upload to 
gs://temp-storage-for-perf-tests/smoketests/load-tests-python-dataflow-streaming-combine-1-0110150204.1673363280.933072/pipeline.pb
 in 0 seconds.
INFO:apache_beam.runners.dataflow.internal.apiclient:Create job: <Job
 clientRequestId: '20230110150800934746-7337'
 createTime: '2023-01-10T15:08:02.108653Z'
 currentStateTime: '1970-01-01T00:00:00Z'
 id: '2023-01-10_07_08_01-15559840179980843572'
 location: 'us-central1'
 name: 'load-tests-python-dataflow-streaming-combine-1-0110150204'
 projectId: 'apache-beam-testing'
 stageStates: []
 startTime: '2023-01-10T15:08:02.108653Z'
 steps: []
 tempFiles: []
 type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)>
INFO:apache_beam.runners.dataflow.internal.apiclient:Created job with id: 
[2023-01-10_07_08_01-15559840179980843572]
INFO:apache_beam.runners.dataflow.internal.apiclient:Submitted job: 
2023-01-10_07_08_01-15559840179980843572
INFO:apache_beam.runners.dataflow.internal.apiclient:To access the Dataflow 
monitoring console, please navigate to 
https://console.cloud.google.com/dataflow/jobs/us-central1/2023-01-10_07_08_01-15559840179980843572?project=apache-beam-testing
INFO:apache_beam.runners.dataflow.dataflow_runner:Job 
2023-01-10_07_08_01-15559840179980843572 is in state JOB_STATE_PENDING
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:06.752Z: 
JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-b.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.336Z: 
JOB_MESSAGE_DETAILED: Expanding SplittableParDo operations into optimizable 
parts.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.377Z: 
JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton operations into 
optimizable parts.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.458Z: 
JOB_MESSAGE_DETAILED: Expanding CoGroupByKey operations into optimizable parts.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.556Z: 
JOB_MESSAGE_DETAILED: Expanding SplittableProcessKeyed operations into 
optimizable parts.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.584Z: 
JOB_MESSAGE_DETAILED: Expanding GroupByKey operations into streaming Read/Write 
steps
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.653Z: 
JOB_MESSAGE_DETAILED: Lifting ValueCombiningMappingFns into 
MergeBucketsMappingFns
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.712Z: 
JOB_MESSAGE_DEBUG: Annotating graph with Autotuner information.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.779Z: 
JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.816Z: 
JOB_MESSAGE_DETAILED: Fusing consumer Read synthetic/Map(<lambda at 
iobase.py:908>) into Read synthetic/Impulse
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.845Z: 
JOB_MESSAGE_DETAILED: Fusing consumer 
ref_AppliedPTransform_Read-synthetic-SDFBoundedSourceReader-ParDo-SDFBoundedSourceDoFn-_6/PairWithRestriction
 into Read synthetic/Map(<lambda at iobase.py:908>)
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.881Z: 
JOB_MESSAGE_DETAILED: Fusing consumer 
ref_AppliedPTransform_Read-synthetic-SDFBoundedSourceReader-ParDo-SDFBoundedSourceDoFn-_6/SplitWithSizing
 into 
ref_AppliedPTransform_Read-synthetic-SDFBoundedSourceReader-ParDo-SDFBoundedSourceDoFn-_6/PairWithRestriction
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.902Z: 
JOB_MESSAGE_DETAILED: Fusing consumer Measure time: Start into 
ref_AppliedPTransform_Read-synthetic-SDFBoundedSourceReader-ParDo-SDFBoundedSourceDoFn-_6/ProcessElementAndRestrictionWithSizing
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.935Z: 
JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 0/KeyWithVoid into 
Measure time: Start
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:08.967Z: 
JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 
0/CombinePerKey/Combine/ConvertToAccumulators into Combine with Top 
0/KeyWithVoid
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.004Z: 
JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 
0/CombinePerKey/GroupByKey/WriteStream into Combine with Top 
0/CombinePerKey/Combine/ConvertToAccumulators
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.029Z: 
JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 0/CombinePerKey/Combine 
into Combine with Top 0/CombinePerKey/GroupByKey/ReadStream
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.060Z: 
JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 
0/CombinePerKey/Combine/Extract into Combine with Top 0/CombinePerKey/Combine
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.099Z: 
JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 0/UnKey into Combine 
with Top 0/CombinePerKey/Combine/Extract
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.134Z: 
JOB_MESSAGE_DETAILED: Fusing consumer Consume 0 into Combine with Top 0/UnKey
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.206Z: 
JOB_MESSAGE_DETAILED: Fusing consumer Measure time: End 0 into Consume 0
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.346Z: 
JOB_MESSAGE_BASIC: Running job using Streaming Engine
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.407Z: 
JOB_MESSAGE_DEBUG: Workflow config is missing a default resource spec.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.458Z: 
JOB_MESSAGE_DEBUG: Adding StepResource setup and teardown to workflow graph.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.497Z: 
JOB_MESSAGE_DEBUG: Adding workflow start and stop steps.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:09.536Z: 
JOB_MESSAGE_DEBUG: Assigning stage ids.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:10.667Z: 
JOB_MESSAGE_DEBUG: Starting **** pool setup.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:10.709Z: 
JOB_MESSAGE_BASIC: Starting 5 ****s in us-central1-b...
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:10.769Z: 
JOB_MESSAGE_DEBUG: Starting **** pool setup.
INFO:apache_beam.runners.dataflow.dataflow_runner:Job 
2023-01-10_07_08_01-15559840179980843572 is in state JOB_STATE_RUNNING
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:40.422Z: 
JOB_MESSAGE_BASIC: Your project already contains 100 Dataflow-created metric 
descriptors, so new user metrics of the form custom.googleapis.com/* will not 
be created. However, all user metrics are also available in the metric 
dataflow.googleapis.com/job/user_counter. If you rely on the custom metrics, 
you can delete old / unused metric descriptors. See 
https://developers.google.com/apis-explorer/#p/monitoring/v3/monitoring.projects.metricDescriptors.list
 and 
https://developers.google.com/apis-explorer/#p/monitoring/v3/monitoring.projects.metricDescriptors.delete
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:08:55.803Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:09:28.109Z: 
JOB_MESSAGE_DETAILED: Workers have started successfully.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:09:40.431Z: 
JOB_MESSAGE_DETAILED: All ****s have finished the startup processes and began 
to receive work requests.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:50:13.611Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:54:20Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:55:15.719Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T15:56:17.337Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T16:20:22.547Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T16:24:23.924Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T16:39:24.766Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T16:40:26.366Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T16:52:27.488Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
INFO:apache_beam.runners.dataflow.dataflow_runner:2023-01-10T17:00:37.479Z: 
JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 5 so that the 
pipeline can catch up with its backlog and keep up with its input rate.
FATAL: command execution failed
java.io.IOException: Backing channel 'apache-beam-jenkins-5' is disconnected.
        at 
hudson.remoting.RemoteInvocationHandler.channelOrFail(RemoteInvocationHandler.java:215)
        at 
hudson.remoting.RemoteInvocationHandler.invoke(RemoteInvocationHandler.java:285)
        at com.sun.proxy.$Proxy147.isAlive(Unknown Source)
        at hudson.Launcher$RemoteLauncher$ProcImpl.isAlive(Launcher.java:1215)
        at hudson.Launcher$RemoteLauncher$ProcImpl.join(Launcher.java:1207)
        at hudson.Launcher$ProcStarter.join(Launcher.java:524)
        at hudson.plugins.gradle.Gradle.perform(Gradle.java:317)
        at hudson.tasks.BuildStepMonitor$1.perform(BuildStepMonitor.java:20)
        at 
hudson.model.AbstractBuild$AbstractBuildExecution.perform(AbstractBuild.java:814)
        at hudson.model.Build$BuildExecution.build(Build.java:199)
        at hudson.model.Build$BuildExecution.doRun(Build.java:164)
        at 
hudson.model.AbstractBuild$AbstractBuildExecution.run(AbstractBuild.java:522)
        at hudson.model.Run.execute(Run.java:1896)
        at hudson.model.FreeStyleBuild.run(FreeStyleBuild.java:44)
        at hudson.model.ResourceController.execute(ResourceController.java:101)
        at hudson.model.Executor.run(Executor.java:442)
Caused by: java.io.IOException: Pipe closed after 0 cycles
        at 
org.apache.sshd.common.channel.ChannelPipedInputStream.read(ChannelPipedInputStream.java:126)
        at 
org.apache.sshd.common.channel.ChannelPipedInputStream.read(ChannelPipedInputStream.java:105)
        at 
hudson.remoting.FlightRecorderInputStream.read(FlightRecorderInputStream.java:94)
        at 
hudson.remoting.ChunkedInputStream.readHeader(ChunkedInputStream.java:75)
        at 
hudson.remoting.ChunkedInputStream.readUntilBreak(ChunkedInputStream.java:105)
        at 
hudson.remoting.ChunkedCommandTransport.readBlock(ChunkedCommandTransport.java:39)
        at 
hudson.remoting.AbstractSynchronousByteArrayCommandTransport.read(AbstractSynchronousByteArrayCommandTransport.java:34)
        at 
hudson.remoting.SynchronousCommandTransport$ReaderThread.run(SynchronousCommandTransport.java:61)
Build step 'Invoke Gradle script' changed build result to FAILURE
Build step 'Invoke Gradle script' marked build as failure
ERROR: apache-beam-jenkins-5 is offline; cannot locate jdk_1.8_latest

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