See <https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/977/display/redirect>
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pyparsing, pymysql, PyJWT, pyhamcrest, pycparser, pyasn1, pyarrow, psycopg2-binary, proto-plus, portalocker, parameterized, overrides, orjson, objsize, mock, joblib, jmespath, isodate, iniconfig, idna, greenlet, googleapis-common-protos, google-crc32c, fasteners, fastavro, execnet, exceptiongroup, dnspython, dill, deprecation, cloudpickle, charset-normalizer, certifi, cachetools, sqlalchemy, scikit-learn, rsa, requests, pymongo, pydot, pyasn1-modules, pandas, httplib2, grpcio-status, google-resumable-media, freezegun, cffi, botocore, attrs, s3transfer, requests_mock, pytest, oauth2client, hypothesis, hdfs, grpc-google-iam-v1, google-auth, docker, cryptography, azure-core, testcontainers, pytest-xdist, pytest-timeout, google-auth-httplib2, google-apitools, google-api-core, boto3, azure-storage-blob, apache-beam, msal, google-cloud-core, msal-extensions, google-cloud-vision, google-cloud-videointelligence, google-cloud-spanner, google-cloud-recommendations-ai, google-cloud-pubsub, google-cloud-language, google-cloud-dlp, google-cloud-datastore, google-cloud-bigtable, google-cloud-bigquery-storage, google-cloud-bigquery, google-cloud-pubsublite, azure-identity Successfully installed PyJWT-2.6.0 apache-beam-2.48.0.dev0 attrs-23.1.0 azure-core-1.26.4 azure-identity-1.12.0 azure-storage-blob-12.16.0 boto3-1.26.121 botocore-1.29.121 cachetools-4.2.4 certifi-2022.12.7 cffi-1.15.1 charset-normalizer-3.1.0 cloudpickle-2.2.1 crcmod-1.7 cryptography-40.0.2 deprecation-2.1.0 dill-0.3.1.1 dnspython-2.3.0 docker-6.0.1 docopt-0.6.2 exceptiongroup-1.1.1 execnet-1.9.0 fastavro-1.7.3 fasteners-0.18 freezegun-1.2.2 google-api-core-2.11.0 google-apitools-0.5.31 google-auth-2.17.3 google-auth-httplib2-0.1.0 google-cloud-bigquery-3.10.0 google-cloud-bigquery-storage-2.19.1 google-cloud-bigtable-2.17.0 google-cloud-core-2.3.2 google-cloud-datastore-2.15.1 google-cloud-dlp-3.12.1 google-cloud-language-2.9.1 google-cloud-pubsub-2.16.0 google-cloud-pubsublite-1.7.0 google-cloud-recommendations-ai-0.10.3 google-cloud-spanner-3.32.0 google-cloud-videointelligence-2.11.1 google-cloud-vision-3.4.1 google-crc32c-1.5.0 google-resumable-media-2.5.0 googleapis-common-protos-1.59.0 greenlet-2.0.2 grpc-google-iam-v1-0.12.6 grpcio-status-1.54.0 hdfs-2.7.0 httplib2-0.21.0 hypothesis-6.74.0 idna-3.4 iniconfig-2.0.0 isodate-0.6.1 jmespath-1.0.1 joblib-1.2.0 mock-5.0.2 msal-1.22.0 msal-extensions-1.0.0 oauth2client-4.1.3 objsize-0.6.1 orjson-3.8.10 overrides-6.5.0 pandas-1.3.5 parameterized-0.9.0 portalocker-2.7.0 proto-plus-1.22.2 psycopg2-binary-2.9.6 pyarrow-11.0.0 pyasn1-0.5.0 pyasn1-modules-0.3.0 pycparser-2.21 pydot-1.4.2 pyhamcrest-2.0.4 pymongo-4.3.3 pymysql-1.0.3 pyparsing-3.0.9 pytest-7.3.1 pytest-timeout-2.1.0 pytest-xdist-3.2.1 python-dateutil-2.8.2 pytz-2023.3 pyyaml-6.0 regex-2022.10.31 requests-2.29.0 requests_mock-1.10.0 rsa-4.9 s3transfer-0.6.0 scikit-learn-1.0.2 scipy-1.7.3 sortedcontainers-2.4.0 sqlalchemy-1.4.47 sqlparse-0.4.4 tenacity-8.2.2 testcontainers-3.7.1 threadpoolctl-3.1.0 tomli-2.0.1 urllib3-1.26.15 websocket-client-1.5.1 wrapt-1.15.0 zstandard-0.21.0 > Task :sdks:python:apache_beam:testing:load_tests:run INFO:apache_beam.runners.portability.stager:Copying Beam SDK "<https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/ws/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:2.48.0.dev INFO:root:Using provided Python SDK container image: gcr.io/cloud-dataflow/v1beta3/beam_python3.7_sdk:beam-master-20230422 INFO:root:Python SDK container image set to "gcr.io/cloud-dataflow/v1beta3/beam_python3.7_sdk:beam-master-20230422" 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-1-0427150219.1682608085.417329/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-1-0427150219.1682608085.417329/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-1-0427150219.1682608085.417329/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-1-0427150219.1682608085.417329/pipeline.pb in 0 seconds. INFO:apache_beam.runners.dataflow.internal.apiclient:Create job: <Job clientRequestId: '20230427150805418366-9209' createTime: '2023-04-27T15:08:06.593165Z' currentStateTime: '1970-01-01T00:00:00Z' id: '2023-04-27_08_08_05-2550698046437071704' location: 'us-central1' name: 'load-tests-python-dataflow-streaming-combine-1-0427150219' projectId: 'apache-beam-testing' stageStates: [] startTime: '2023-04-27T15:08:06.593165Z' steps: [] tempFiles: [] type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)> INFO:apache_beam.runners.dataflow.internal.apiclient:Created job with id: [2023-04-27_08_08_05-2550698046437071704] INFO:apache_beam.runners.dataflow.internal.apiclient:Submitted job: 2023-04-27_08_08_05-2550698046437071704 INFO:apache_beam.runners.dataflow.internal.apiclient:To access the Dataflow monitoring console, please navigate to https://console.cloud.google.com/dataflow/jobs/us-central1/2023-04-27_08_08_05-2550698046437071704?project=apache-beam-testing INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-04-27_08_08_05-2550698046437071704 is in state JOB_STATE_PENDING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:11.056Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-b. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:15.597Z: JOB_MESSAGE_DETAILED: Expanding SplittableParDo operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:15.629Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:15.696Z: JOB_MESSAGE_DETAILED: Expanding CoGroupByKey operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:15.764Z: JOB_MESSAGE_DETAILED: Expanding SplittableProcessKeyed operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:15.794Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations into streaming Read/Write steps INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:15.842Z: JOB_MESSAGE_DETAILED: Lifting ValueCombiningMappingFns into MergeBucketsMappingFns INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:15.890Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner information. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:15.928Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:15.956Z: JOB_MESSAGE_DETAILED: Fusing consumer Read synthetic/Map(<lambda at iobase.py:908>) into Read synthetic/Impulse INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:15.992Z: 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:2023-04-27T15:08:16.034Z: 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:2023-04-27T15:08:16.069Z: 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:2023-04-27T15:08:16.090Z: JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 0/KeyWithVoid into Measure time: Start INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:16.122Z: 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:2023-04-27T15:08:16.154Z: 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:2023-04-27T15:08:16.190Z: 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:2023-04-27T15:08:16.222Z: 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:2023-04-27T15:08:16.250Z: 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:2023-04-27T15:08:16.276Z: JOB_MESSAGE_DETAILED: Fusing consumer Consume 0 into Combine with Top 0/UnKey INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:16.304Z: JOB_MESSAGE_DETAILED: Fusing consumer Measure time: End 0 into Consume 0 INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:16.386Z: JOB_MESSAGE_BASIC: Running job using Streaming Engine INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:16.411Z: JOB_MESSAGE_DEBUG: Workflow config is missing a default resource spec. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:16.430Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and teardown to workflow graph. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:16.460Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop steps. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:16.484Z: JOB_MESSAGE_DEBUG: Assigning stage ids. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:16.643Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:16.672Z: JOB_MESSAGE_BASIC: Starting 5 ****s in us-central1-b... INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:16.716Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-04-27_08_08_05-2550698046437071704 is in state JOB_STATE_RUNNING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:08:48.617Z: 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:2023-04-27T15:09:10.299Z: JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 2 so that the pipeline can catch up with its backlog and keep up with its input rate. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:09:10.330Z: JOB_MESSAGE_DETAILED: Autoscaling: Resized **** pool to 2, though goal was 5. This could be a quota issue. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:09:29.916Z: JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 3 so that the pipeline can catch up with its backlog and keep up with its input rate. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:09:29.943Z: JOB_MESSAGE_DETAILED: Autoscaling: Resized **** pool to 3, though goal was 5. This could be a quota issue. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:09:39.924Z: 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:2023-04-27T15:09:43.017Z: JOB_MESSAGE_DETAILED: Workers have started successfully. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:09:55.521Z: JOB_MESSAGE_DETAILED: All ****s have finished the startup processes and began to receive work requests. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T15:33:53.571Z: JOB_MESSAGE_WARNING: The ****s of given job are going to be updated. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T16:13:13.195Z: 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:2023-04-27T16:16:14.560Z: 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:2023-04-27T16:45:15.644Z: 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:2023-04-27T16:46:20.929Z: 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:2023-04-27T16:47:21.896Z: 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:2023-04-27T17:13:44.303Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-b. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-27T17:13:49.792Z: 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:2023-04-27T17:21:06.812Z: 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:2023-04-27T17:22:11.632Z: 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:2023-04-27T17:56:09.321Z: 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:2023-04-27T17:57:13.968Z: 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:2023-04-27T18:00:11.281Z: 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:2023-04-27T18:30:16.141Z: 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:2023-04-27T18:32:17.227Z: 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:2023-04-27T19:05:14.330Z: 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:2023-04-27T19:10:15.733Z: 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. Build timed out (after 720 minutes). Marking the build as aborted. FATAL: command execution failed hudson.remoting.ChannelClosedException: Channel "hudson.remoting.Channel@3e483a4d:apache-beam-jenkins-4": Remote call on apache-beam-jenkins-4 failed. The channel is closing down or has closed down at hudson.remoting.Channel.call(Channel.java:993) at hudson.remoting.RemoteInvocationHandler.invoke(RemoteInvocationHandler.java:285) at com.sun.proxy.$Proxy135.isAlive(Unknown Source) at hudson.Launcher$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:321) 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 at hudson.remoting.Channel.close(Channel.java:1470) at hudson.remoting.Channel.close(Channel.java:1447) at hudson.slaves.SlaveComputer.closeChannel(SlaveComputer.java:902) at hudson.slaves.SlaveComputer.access$100(SlaveComputer.java:111) at hudson.slaves.SlaveComputer$2.run(SlaveComputer.java:782) at jenkins.util.ContextResettingExecutorService$1.run(ContextResettingExecutorService.java:28) at jenkins.security.ImpersonatingExecutorService$1.run(ImpersonatingExecutorService.java:68) at java.base/java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:515) at java.base/java.util.concurrent.FutureTask.run(FutureTask.java:264) at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) at java.base/java.lang.Thread.run(Thread.java:829) Build step 'Invoke Gradle script' changed build result to FAILURE Build step 'Invoke Gradle script' marked build as failure FATAL: Channel "hudson.remoting.Channel@3e483a4d:apache-beam-jenkins-4": Remote call on apache-beam-jenkins-4 failed. The channel is closing down or has closed down java.io.IOException at hudson.remoting.Channel.close(Channel.java:1470) at hudson.remoting.Channel.close(Channel.java:1447) at hudson.slaves.SlaveComputer.closeChannel(SlaveComputer.java:902) at hudson.slaves.SlaveComputer.access$100(SlaveComputer.java:111) at hudson.slaves.SlaveComputer$2.run(SlaveComputer.java:782) at jenkins.util.ContextResettingExecutorService$1.run(ContextResettingExecutorService.java:28) at jenkins.security.ImpersonatingExecutorService$1.run(ImpersonatingExecutorService.java:68) at java.base/java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:515) at java.base/java.util.concurrent.FutureTask.run(FutureTask.java:264) at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) at java.base/java.lang.Thread.run(Thread.java:829) Caused: hudson.remoting.ChannelClosedException: Channel "hudson.remoting.Channel@3e483a4d:apache-beam-jenkins-4": Remote call on apache-beam-jenkins-4 failed. The channel is closing down or has closed down at hudson.remoting.Channel.call(Channel.java:993) at hudson.Launcher$RemoteLauncher.kill(Launcher.java:1150) at hudson.model.AbstractBuild$AbstractBuildExecution.run(AbstractBuild.java:534) 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) --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
