See <https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/1027/display/redirect>
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pyhamcrest, pycparser, pyasn1, pyarrow, psycopg2-binary, proto-plus, portalocker, parameterized, overrides, orjson, objsize, mock, joblib, jmespath, iniconfig, idna, greenlet, googleapis-common-protos, google-crc32c, fasteners, fastavro, execnet, exceptiongroup, dnspython, dill, deprecation, cloudpickle, charset-normalizer, certifi, sqlalchemy, scikit-learn, rsa, requests, python-dateutil, pymongo, pydot, pyasn1-modules, isodate, httplib2, grpcio-status, google-resumable-media, cffi, attrs, requests_mock, pytest, pandas, oauth2client, hypothesis, hdfs, grpc-google-iam-v1, google-auth, freezegun, docker, cryptography, botocore, azure-core, testcontainers, s3transfer, pytest-xdist, pytest-timeout, google-auth-httplib2, google-apitools, google-api-core, azure-storage-blob, apache-beam, msal, google-cloud-core, boto3, 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-2.7.0 apache-beam-2.49.0.dev0 attrs-23.1.0 azure-core-1.27.1 azure-identity-1.13.0 azure-storage-blob-12.16.0 boto3-1.26.154 botocore-1.29.154 certifi-2023.5.7 cffi-1.15.1 charset-normalizer-3.1.0 cloudpickle-2.2.1 crcmod-1.7 cryptography-41.0.1 deprecation-2.1.0 dill-0.3.1.1 dnspython-2.3.0 docker-6.1.3 docopt-0.6.2 exceptiongroup-1.1.1 execnet-1.9.0 fastavro-1.7.4 fasteners-0.18 freezegun-1.2.2 google-api-core-2.11.1 google-apitools-0.5.31 google-auth-2.20.0 google-auth-httplib2-0.1.0 google-cloud-bigquery-3.11.1 google-cloud-bigquery-storage-2.20.0 google-cloud-bigtable-2.19.0 google-cloud-core-2.3.2 google-cloud-datastore-2.15.2 google-cloud-dlp-3.12.1 google-cloud-language-2.10.0 google-cloud-pubsub-2.17.1 google-cloud-pubsublite-1.7.0 google-cloud-recommendations-ai-0.10.3 google-cloud-spanner-3.36.0 google-cloud-videointelligence-2.11.2 google-cloud-vision-3.4.2 google-crc32c-1.5.0 google-resumable-media-2.5.0 googleapis-common-protos-1.59.1 greenlet-2.0.2 grpc-google-iam-v1-0.12.6 grpcio-status-1.54.2 hdfs-2.7.0 httplib2-0.22.0 hypothesis-6.78.3 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-3.9.1 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-7.3.2 pytest-timeout-2.1.0 pytest-xdist-3.3.1 python-dateutil-2.8.2 pytz-2023.3 pyyaml-6.0 regex-2023.6.3 requests-2.31.0 requests_mock-1.11.0 rsa-4.9 s3transfer-0.6.1 scikit-learn-1.0.2 scipy-1.7.3 six-1.16.0 sortedcontainers-2.4.0 sqlalchemy-1.4.48 sqlparse-0.4.4 tenacity-8.2.2 testcontainers-3.7.1 threadpoolctl-3.1.0 urllib3-1.26.16 websocket-client-1.5.3 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: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-1-0616125346.1686928081.231336/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-1-0616125346.1686928081.231336/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-1-0616125346.1686928081.231336/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-1-0616125346.1686928081.231336/pipeline.pb in 0 seconds. INFO:apache_beam.runners.dataflow.internal.apiclient:Create job: <Job clientRequestId: '20230616150801234469-8006' createTime: '2023-06-16T15:08:02.511523Z' currentStateTime: '1970-01-01T00:00:00Z' id: '2023-06-16_08_08_02-15928940161055252249' location: 'us-central1' name: 'load-tests-python-dataflow-streaming-combine-1-0616125346' projectId: 'apache-beam-testing' stageStates: [] startTime: '2023-06-16T15:08:02.511523Z' steps: [] tempFiles: [] type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)> INFO:apache_beam.runners.dataflow.internal.apiclient:Created job with id: [2023-06-16_08_08_02-15928940161055252249] INFO:apache_beam.runners.dataflow.internal.apiclient:Submitted job: 2023-06-16_08_08_02-15928940161055252249 INFO:apache_beam.runners.dataflow.internal.apiclient:To access the Dataflow monitoring console, please navigate to https://console.cloud.google.com/dataflow/jobs/us-central1/2023-06-16_08_08_02-15928940161055252249?project=apache-beam-testing INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-06-16_08_08_02-15928940161055252249 is in state JOB_STATE_PENDING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:07.171Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-a. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:08.769Z: JOB_MESSAGE_DETAILED: Expanding SplittableParDo operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:08.797Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:08.858Z: JOB_MESSAGE_DETAILED: Expanding CoGroupByKey operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:08.913Z: JOB_MESSAGE_DETAILED: Expanding SplittableProcessKeyed operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:08.935Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations into streaming Read/Write steps INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:08.993Z: JOB_MESSAGE_DETAILED: Lifting ValueCombiningMappingFns into MergeBucketsMappingFns INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.056Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner information. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.095Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.125Z: JOB_MESSAGE_DETAILED: Fusing consumer Read synthetic/Map(<lambda at iobase.py:908>) into Read synthetic/Impulse INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.159Z: 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:2023-06-16T15:08:09.195Z: 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:2023-06-16T15:08:09.220Z: 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:2023-06-16T15:08:09.244Z: JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 0/KeyWithVoid into Measure time: Start INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.270Z: 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:2023-06-16T15:08:09.293Z: 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:2023-06-16T15:08:09.315Z: 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:2023-06-16T15:08:09.346Z: 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:2023-06-16T15:08:09.392Z: 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:2023-06-16T15:08:09.425Z: JOB_MESSAGE_DETAILED: Fusing consumer Consume 0 into Combine with Top 0/UnKey INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.450Z: JOB_MESSAGE_DETAILED: Fusing consumer Measure time: End 0 into Consume 0 INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.548Z: JOB_MESSAGE_DEBUG: Workflow config is missing a default resource spec. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.568Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and teardown to workflow graph. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.593Z: JOB_MESSAGE_BASIC: Running job using Streaming Engine INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.629Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop steps. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.650Z: JOB_MESSAGE_DEBUG: Assigning stage ids. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.814Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.838Z: JOB_MESSAGE_BASIC: Starting 5 ****s in us-central1-a... INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:09.880Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-06-16_08_08_02-15928940161055252249 is in state JOB_STATE_RUNNING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:08:33.221Z: 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:2023-06-16T15:08:55.291Z: 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:2023-06-16T15:09:26.985Z: JOB_MESSAGE_DETAILED: Workers have started successfully. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:09:36.036Z: JOB_MESSAGE_DETAILED: All ****s have finished the startup processes and began to receive work requests. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T15:31:14.665Z: JOB_MESSAGE_WARNING: The ****s of given job are going to be updated. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T16:01:25.165Z: 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:2023-06-16T16:26:19.974Z: 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:2023-06-16T16:51:27.221Z: 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:2023-06-16T17:16:18.759Z: 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:2023-06-16T17:41:20.307Z: 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:2023-06-16T18:08:32.216Z: 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:2023-06-16T18:34:33.805Z: 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:2023-06-16T18:59:34.925Z: 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:2023-06-16T19:24:26.545Z: 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:2023-06-16T19:49:29.092Z: 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:Job 2023-06-16_08_08_02-15928940161055252249 is in state JOB_STATE_CANCELLING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T20:00:48.235Z: JOB_MESSAGE_BASIC: Cancel request is committed for workflow job: 2023-06-16_08_08_02-15928940161055252249. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T20:00:48.292Z: JOB_MESSAGE_DETAILED: Cleaning up. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T20:00:48.332Z: JOB_MESSAGE_DEBUG: Starting **** pool teardown. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T20:00:48.359Z: JOB_MESSAGE_BASIC: Stopping **** pool... INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T20:00:48.389Z: JOB_MESSAGE_DEBUG: Starting **** pool teardown. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-06-16T20:00:48.412Z: JOB_MESSAGE_BASIC: Stopping **** pool... 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 1558, 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>/2023-06-16_08_08_02-15928940161055252249?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://ge.apache.org/s/f2jirogpfocfa 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]
