See <https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/964/display/redirect>
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sha256=e0d55f5d9957b7048218a4387e3de0102023e80d9c7651e22df68ed71292855e Stored in directory: /home/jenkins/.cache/pip/wheels/e6/1f/28/9337974c607f5f016ef124646a645ebf2fb34bdd32df5f9dd8 Successfully built apache-beam Installing collected packages: sortedcontainers, pytz, pyasn1, docopt, crcmod, zstandard, wrapt, websocket-client, urllib3, tomli, threadpoolctl, tenacity, sqlparse, scipy, rsa, regex, pyyaml, python-dateutil, pyparsing, pymysql, PyJWT, pyhamcrest, pycparser, pyasn1-modules, 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, attrs, sqlalchemy, scikit-learn, requests, pymongo, pydot, pandas, hypothesis, httplib2, grpcio-status, google-resumable-media, google-auth, freezegun, cffi, botocore, s3transfer, requests_mock, pytest, oauth2client, hdfs, grpc-google-iam-v1, google-auth-httplib2, google-api-core, docker, cryptography, azure-core, testcontainers, pytest-xdist, pytest-timeout, google-cloud-core, google-apitools, boto3, azure-storage-blob, apache-beam, msal, 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, msal-extensions, google-cloud-pubsublite, azure-identity Successfully installed PyJWT-2.6.0 apache-beam-2.48.0.dev0 attrs-22.2.0 azure-core-1.26.4 azure-identity-1.12.0 azure-storage-blob-12.16.0 boto3-1.26.113 botocore-1.29.113 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 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pyasn1-0.4.8 pyasn1-modules-0.2.8 pycparser-2.21 pydot-1.4.2 pyhamcrest-1.10.1 pymongo-4.3.3 pymysql-1.0.3 pyparsing-3.0.9 pytest-7.3.0 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-2.28.2 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-0.4.3 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-0.20.0 > 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. 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INFO:apache_beam.runners.dataflow.internal.apiclient:Starting GCS upload to gs://temp-storage-for-perf-tests/smoketests/load-tests-python-dataflow-streaming-combine-1-0414150209.1681484878.406083/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-1-0414150209.1681484878.406083/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-1-0414150209.1681484878.406083/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-1-0414150209.1681484878.406083/pipeline.pb in 0 seconds. INFO:apache_beam.runners.dataflow.internal.apiclient:Create job: <Job clientRequestId: '20230414150758407150-5157' createTime: '2023-04-14T15:07:59.512196Z' currentStateTime: '1970-01-01T00:00:00Z' id: '2023-04-14_08_07_59-82375092236442943' location: 'us-central1' name: 'load-tests-python-dataflow-streaming-combine-1-0414150209' projectId: 'apache-beam-testing' stageStates: [] startTime: '2023-04-14T15:07:59.512196Z' steps: [] tempFiles: [] type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)> INFO:apache_beam.runners.dataflow.internal.apiclient:Created job with id: [2023-04-14_08_07_59-82375092236442943] INFO:apache_beam.runners.dataflow.internal.apiclient:Submitted job: 2023-04-14_08_07_59-82375092236442943 INFO:apache_beam.runners.dataflow.internal.apiclient:To access the Dataflow monitoring console, please navigate to https://console.cloud.google.com/dataflow/jobs/us-central1/2023-04-14_08_07_59-82375092236442943?project=apache-beam-testing INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-04-14_08_07_59-82375092236442943 is in state JOB_STATE_PENDING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:09.128Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-b. 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INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:15.990Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.017Z: JOB_MESSAGE_DETAILED: Fusing consumer Read synthetic/Map(<lambda at iobase.py:908>) into Read synthetic/Impulse INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.048Z: 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:2023-04-14T15:08:16.081Z: 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:2023-04-14T15:08:16.113Z: 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:2023-04-14T15:08:16.146Z: JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 0/KeyWithVoid into Measure time: Start INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.178Z: 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:2023-04-14T15:08:16.209Z: 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:2023-04-14T15:08:16.242Z: 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:2023-04-14T15:08:16.274Z: 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:2023-04-14T15:08:16.305Z: 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:2023-04-14T15:08:16.328Z: JOB_MESSAGE_DETAILED: Fusing consumer Consume 0 into Combine with Top 0/UnKey INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.360Z: JOB_MESSAGE_DETAILED: Fusing consumer Measure time: End 0 into Consume 0 INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.430Z: JOB_MESSAGE_BASIC: Running job using Streaming Engine INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.465Z: JOB_MESSAGE_DEBUG: Workflow config is missing a default resource spec. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.491Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and teardown to workflow graph. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.523Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop steps. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.545Z: JOB_MESSAGE_DEBUG: Assigning stage ids. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.708Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.730Z: JOB_MESSAGE_BASIC: Starting 5 ****s in us-central1-b... INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:16.773Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-04-14_08_07_59-82375092236442943 is in state JOB_STATE_RUNNING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:08:28.394Z: 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:2023-04-14T15:08:56.706Z: 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:2023-04-14T15:09:26.621Z: JOB_MESSAGE_DETAILED: Workers have started successfully. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:09:34.505Z: JOB_MESSAGE_DETAILED: All ****s have finished the startup processes and began to receive work requests. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T15:26:29.739Z: JOB_MESSAGE_WARNING: The ****s of given job are going to be updated. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T16:02:10.250Z: 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:2023-04-14T16:04:13.994Z: 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:2023-04-14T16:05:15.352Z: 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:2023-04-14T16:13:12.134Z: 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:2023-04-14T16:29:18.036Z: 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:2023-04-14T16:33:15.792Z: 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:2023-04-14T16:40:16.598Z: 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:2023-04-14T16:44:29.021Z: 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:2023-04-14T17:00:20.383Z: 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:2023-04-14T17:09:21.486Z: 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:2023-04-14T17:13:32.364Z: 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:2023-04-14T17:21:33.092Z: 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:2023-04-14T17:26:25.196Z: 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:2023-04-14T17:38:29.902Z: 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:2023-04-14T17:41:30.947Z: 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:2023-04-14T17:54:28.051Z: 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:2023-04-14T18:01:40.048Z: 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:2023-04-14T18:12:31.716Z: 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:2023-04-14T18:20:36.275Z: 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:2023-04-14T18:21:37.307Z: 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:2023-04-14T18:28:54.321Z: 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:2023-04-14T18:45:35.762Z: 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:2023-04-14T18:53:46.505Z: 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:2023-04-14T19:00:37.288Z: 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:2023-04-14T19:04:38.424Z: 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:2023-04-14T19:18:39.907Z: 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:2023-04-14T19:20:51.067Z: 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:2023-04-14T19:33:52.747Z: 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:2023-04-14T19:40:43.759Z: 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:2023-04-14T19:49:45.038Z: 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:2023-04-14T20:00:41.798Z: JOB_MESSAGE_BASIC: Cancel request is committed for workflow job: 2023-04-14_08_07_59-82375092236442943. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T20:00:41.851Z: JOB_MESSAGE_DETAILED: Cleaning up. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T20:00:41.890Z: JOB_MESSAGE_DEBUG: Starting **** pool teardown. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T20:00:41.914Z: JOB_MESSAGE_BASIC: Stopping **** pool... INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T20:00:41.966Z: JOB_MESSAGE_DEBUG: Starting **** pool teardown. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-04-14T20:00:42.012Z: JOB_MESSAGE_BASIC: Stopping **** pool... INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-04-14_08_07_59-82375092236442943 is in state JOB_STATE_CANCELLING Traceback (most recent call last): File "/usr/lib/python3.7/runpy.py", line 193, in _run_module_as_main "__main__", mod_spec) File "/usr/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "<https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/ws/src/sdks/python/apache_beam/testing/load_tests/combine_test.py";,> line 129, in <module> CombineTest().run() File "<https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/ws/src/sdks/python/apache_beam/testing/load_tests/load_test.py";,> line 152, in run state = self.result.wait_until_finish(duration=self.timeout_ms) File "<https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/ws/src/sdks/python/apache_beam/runners/dataflow/dataflow_runner.py";,> line 1547, in wait_until_finish '{}'.format(consoleUrl)) AssertionError: Job did not reach to a terminal state after waiting indefinitely. Console URL: https://console.cloud.google.com/dataflow/jobs/<RegionId>/2023-04-14_08_07_59-82375092236442943?project=<ProjectId> > Task :sdks:python:apache_beam:testing:load_tests:run FAILED FAILURE: Build failed with an exception. * Where: Build file '<https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/ws/src/sdks/python/apache_beam/testing/load_tests/build.gradle'> line: 63 * What went wrong: Execution failed for task ':sdks:python:apache_beam:testing:load_tests:run'. > error occurred * Try: > Run with --stacktrace option to get the stack trace. > Run with --info or --debug option to get more log output. * Get more help at https://help.gradle.org Deprecated Gradle features were used in this build, making it incompatible with Gradle 8.0. You can use '--warning-mode all' to show the individual deprecation warnings and determine if they come from your own scripts or plugins. See https://docs.gradle.org/7.5.1/userguide/command_line_interface.html#sec:command_line_warnings BUILD FAILED in 4h 55m 5s 15 actionable tasks: 9 executed, 4 from cache, 2 up-to-date Publishing build scan... https://gradle.com/s/er3arrhjfbwjm Build step 'Invoke Gradle script' changed build result to FAILURE Build step 'Invoke Gradle script' marked build as failure --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
