See <https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/1069/display/redirect>
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botocore, azure-core, testcontainers, s3transfer, grpc-google-iam-v1, 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-storage, google-cloud-spanner, google-cloud-resource-manager, 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, google-cloud-aiplatform, azure-identity Attempting uninstall: protobuf Found existing installation: protobuf 4.24.0rc2 Uninstalling protobuf-4.24.0rc2: Successfully uninstalled protobuf-4.24.0rc2 Successfully installed PyJWT-2.8.0 apache-beam-2.50.0.dev0 attrs-23.1.0 azure-core-1.28.0 azure-identity-1.14.0b2 azure-storage-blob-12.17.0 boto3-1.28.14 botocore-1.31.14 certifi-2023.7.22 cffi-1.15.1 charset-normalizer-3.2.0 cloudpickle-2.2.1 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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_python3.8_sdk:beam-master-20230717 INFO:root:Python SDK container image set to "gcr.io/cloud-dataflow/v1beta3/beam_python3.8_sdk:beam-master-20230717" 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-1-0728125346.1690556879.856262/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-1-0728125346.1690556879.856262/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-1-0728125346.1690556879.856262/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-1-0728125346.1690556879.856262/pipeline.pb in 0 seconds. INFO:apache_beam.runners.dataflow.internal.apiclient:Create job: <Job clientRequestId: '20230728150759857316-7777' createTime: '2023-07-28T15:08:00.994482Z' currentStateTime: '1970-01-01T00:00:00Z' id: '2023-07-28_08_08_00-6070257169298620983' location: 'us-central1' name: 'load-tests-python-dataflow-streaming-combine-1-0728125346' projectId: 'apache-beam-testing' stageStates: [] startTime: '2023-07-28T15:08:00.994482Z' steps: [] tempFiles: [] type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)> INFO:apache_beam.runners.dataflow.internal.apiclient:Created job with id: [2023-07-28_08_08_00-6070257169298620983] INFO:apache_beam.runners.dataflow.internal.apiclient:Submitted job: 2023-07-28_08_08_00-6070257169298620983 INFO:apache_beam.runners.dataflow.internal.apiclient:To access the Dataflow monitoring console, please navigate to https://console.cloud.google.com/dataflow/jobs/us-central1/2023-07-28_08_08_00-6070257169298620983?project=apache-beam-testing INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-07-28_08_08_00-6070257169298620983 is in state JOB_STATE_PENDING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:06.882Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-b. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.489Z: JOB_MESSAGE_DETAILED: Expanding SplittableParDo operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.520Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.586Z: JOB_MESSAGE_DETAILED: Expanding CoGroupByKey operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.665Z: JOB_MESSAGE_DETAILED: Expanding SplittableProcessKeyed operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.693Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations into streaming Read/Write steps INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.743Z: JOB_MESSAGE_DETAILED: Lifting ValueCombiningMappingFns into MergeBucketsMappingFns INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.798Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner information. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.852Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.878Z: JOB_MESSAGE_DETAILED: Fusing consumer Read synthetic/Map(<lambda at iobase.py:911>) into Read synthetic/Impulse INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.901Z: JOB_MESSAGE_DETAILED: Fusing consumer ref_AppliedPTransform_Read-synthetic-SDFBoundedSourceReader-ParDo-SDFBoundedSourceDoFn-_6/PairWithRestriction into Read synthetic/Map(<lambda at iobase.py:911>) INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:09.925Z: 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:2023-07-28T15:08:09.952Z: 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:2023-07-28T15:08:09.973Z: JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 0/KeyWithVoid into Measure time: Start INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:10.003Z: 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:2023-07-28T15:08:10.037Z: 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:2023-07-28T15:08:10.060Z: 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:2023-07-28T15:08:10.107Z: 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:2023-07-28T15:08:10.134Z: 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:2023-07-28T15:08:10.165Z: JOB_MESSAGE_DETAILED: Fusing consumer Consume 0 into Combine with Top 0/UnKey INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:10.189Z: JOB_MESSAGE_DETAILED: Fusing consumer Measure time: End 0 into Consume 0 INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:10.297Z: JOB_MESSAGE_DEBUG: Workflow config is missing a default resource spec. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:10.324Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and teardown to workflow graph. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:10.350Z: JOB_MESSAGE_BASIC: Running job using Streaming Engine INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:10.377Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop steps. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:10.398Z: JOB_MESSAGE_DEBUG: Assigning stage ids. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:10.565Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:10.588Z: JOB_MESSAGE_BASIC: Starting 5 ****s in us-central1-b... INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:10.640Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-07-28_08_08_00-6070257169298620983 is in state JOB_STATE_RUNNING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:08:24.491Z: 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:2023-07-28T15:08:57.718Z: 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:2023-07-28T15:09:29.899Z: JOB_MESSAGE_DETAILED: Workers have started successfully. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:09:38.981Z: JOB_MESSAGE_DETAILED: All ****s have finished the startup processes and began to receive work requests. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T15:33:19.213Z: 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:2023-07-28T15:48:10.928Z: 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:2023-07-28T16:01:12.308Z: 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:2023-07-28T16:18:16.376Z: 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:2023-07-28T16:31:14.528Z: 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:2023-07-28T16:47:57.313Z: 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:2023-07-28T17:01:26.979Z: 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:2023-07-28T17:17:21.775Z: 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:2023-07-28T17:30:23.531Z: 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:2023-07-28T17:40:23.357Z: 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:2023-07-28T17:59:21.660Z: 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:2023-07-28T18:12:25.109Z: 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:2023-07-28T18:28:27.075Z: 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:2023-07-28T18:39:28.564Z: 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:2023-07-28T18:56:30.884Z: 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:2023-07-28T19:09:03.050Z: 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:2023-07-28T19:25:31.448Z: 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:2023-07-28T19:38:34.960Z: 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:2023-07-28T19:48:36.599Z: 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:2023-07-28T20:06:38.478Z: 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:2023-07-28T20:07:18.900Z: JOB_MESSAGE_BASIC: Cancel request is committed for workflow job: 2023-07-28_08_08_00-6070257169298620983. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T20:07:18.931Z: JOB_MESSAGE_DETAILED: Cleaning up. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T20:07:18.990Z: JOB_MESSAGE_DEBUG: Starting **** pool teardown. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T20:07:19.011Z: JOB_MESSAGE_BASIC: Stopping **** pool... INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T20:07:19.030Z: JOB_MESSAGE_DEBUG: Starting **** pool teardown. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-28T20:07:19.048Z: JOB_MESSAGE_BASIC: Stopping **** pool... INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-07-28_08_08_00-6070257169298620983 is in state JOB_STATE_CANCELLING Traceback (most recent call last): File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "/usr/lib/python3.8/runpy.py", line 87, 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 748, in wait_until_finish assert duration or terminated, ( AssertionError: Job did not reach to a terminal state after waiting indefinitely. Console URL: https://console.cloud.google.com/dataflow/jobs/<RegionId>/2023-07-28_08_08_00-6070257169298620983?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/7.6.2/userguide/command_line_interface.html#sec:command_line_warnings BUILD FAILED in 5h 1m 54s 15 actionable tasks: 9 executed, 4 from cache, 2 up-to-date Publishing build scan... https://ge.apache.org/s/nfhp6ekspkhdq 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]
