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psycopg2-binary, protobuf, portalocker, parameterized, overrides, orjson, objsize, mock, joblib, jmespath, iniconfig, idna, greenlet, google-crc32c, fasteners, fastavro, execnet, exceptiongroup, dill, deprecation, cloudpickle, charset-normalizer, certifi, attrs, sqlalchemy, scikit-learn, rsa, requests, python-dateutil, pytest, pydot, pyasn1-modules, proto-plus, isodate, hypothesis, httplib2, googleapis-common-protos, google-resumable-media, dnspython, cffi, requests_mock, pytest-xdist, pytest-timeout, pymongo, pandas, oauth2client, hdfs, grpcio-status, google-auth, freezegun, docker, cryptography, 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, 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pytest-7.4.0 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-1.3.0 scipy-1.10.1 shapely-1.8.5.post1 six-1.16.0 sniffio-1.3.0 sortedcontainers-2.4.0 sqlalchemy-1.4.49 sqlparse-0.4.4 tenacity-8.2.2 testcontainers-3.7.1 threadpoolctl-3.2.0 typing-extensions-4.7.1 urllib3-1.26.16 websocket-client-1.6.1 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:Using provided Python SDK container image: gcr.io/cloud-dataflow/v1beta3/beam_python3.8_sdk:beam-master-20230705 INFO:root:Python SDK container image set to "gcr.io/cloud-dataflow/v1beta3/beam_python3.8_sdk:beam-master-20230705" 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. 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INFO:apache_beam.runners.dataflow.internal.apiclient:Create job: <Job clientRequestId: '20230714150749470410-5652' createTime: '2023-07-14T15:07:50.335834Z' currentStateTime: '1970-01-01T00:00:00Z' id: '2023-07-14_08_07_49-4908261760408134229' location: 'us-central1' name: 'load-tests-python-dataflow-streaming-combine-1-0714125349' projectId: 'apache-beam-testing' stageStates: [] startTime: '2023-07-14T15:07:50.335834Z' steps: [] tempFiles: [] type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)> INFO:apache_beam.runners.dataflow.internal.apiclient:Created job with id: [2023-07-14_08_07_49-4908261760408134229] INFO:apache_beam.runners.dataflow.internal.apiclient:Submitted job: 2023-07-14_08_07_49-4908261760408134229 INFO:apache_beam.runners.dataflow.internal.apiclient:To access the Dataflow monitoring console, please navigate to https://console.cloud.google.com/dataflow/jobs/us-central1/2023-07-14_08_07_49-4908261760408134229?project=apache-beam-testing INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-07-14_08_07_49-4908261760408134229 is in state JOB_STATE_PENDING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:57.486Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-f. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:58.597Z: JOB_MESSAGE_DETAILED: Expanding SplittableParDo operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:58.630Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:58.689Z: JOB_MESSAGE_DETAILED: Expanding CoGroupByKey operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:58.747Z: JOB_MESSAGE_DETAILED: Expanding SplittableProcessKeyed operations into optimizable parts. 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INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:58.913Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:58.939Z: JOB_MESSAGE_DETAILED: Fusing consumer Read synthetic/Map(<lambda at iobase.py:911>) into Read synthetic/Impulse INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:58.964Z: 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:2023-07-14T15:07:58.988Z: 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:2023-07-14T15:07:59.018Z: 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:2023-07-14T15:07:59.044Z: JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 0/KeyWithVoid into Measure time: Start INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:59.067Z: 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:2023-07-14T15:07:59.091Z: 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:2023-07-14T15:07:59.116Z: 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:2023-07-14T15:07:59.146Z: 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:2023-07-14T15:07:59.167Z: 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:2023-07-14T15:07:59.189Z: JOB_MESSAGE_DETAILED: Fusing consumer Consume 0 into Combine with Top 0/UnKey INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:59.215Z: JOB_MESSAGE_DETAILED: Fusing consumer Measure time: End 0 into Consume 0 INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:59.295Z: JOB_MESSAGE_DEBUG: Workflow config is missing a default resource spec. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:59.322Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and teardown to workflow graph. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:59.343Z: JOB_MESSAGE_BASIC: Running job using Streaming Engine INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:59.377Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop steps. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:59.405Z: JOB_MESSAGE_DEBUG: Assigning stage ids. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:59.571Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:59.598Z: JOB_MESSAGE_BASIC: Starting 5 ****s in us-central1-f... INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:07:59.654Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-07-14_08_07_49-4908261760408134229 is in state JOB_STATE_RUNNING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:08:15.284Z: 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:2023-07-14T15:08:42.337Z: JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of ****s to 1 so that the pipeline can catch up with its backlog and keep up with its input rate. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:08:42.364Z: JOB_MESSAGE_DETAILED: Autoscaling: Resized **** pool to 1, though goal was 5. This could be a quota issue. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:08:49.085Z: 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:2023-07-14T15:09:16.166Z: JOB_MESSAGE_DETAILED: Workers have started successfully. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:09:28.172Z: JOB_MESSAGE_DETAILED: All ****s have finished the startup processes and began to receive work requests. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:15:44.245Z: JOB_MESSAGE_WARNING: The ****s of given job are going to be updated. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T15:45:51.134Z: 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:2023-07-14T15:46:52.765Z: 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:2023-07-14T16:09:05.523Z: 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:2023-07-14T16:10:57.824Z: 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:2023-07-14T16:12:58.925Z: 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:2023-07-14T16:13:58.353Z: 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:2023-07-14T16:15:59.572Z: 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:2023-07-14T16:38:01.863Z: 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:2023-07-14T16:39:03.806Z: 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:2023-07-14T16:44:04.920Z: 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:2023-07-14T16:53:16.933Z: 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:2023-07-14T17:01:05.912Z: 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:2023-07-14T17:06:08.443Z: 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:2023-07-14T17:11:19.653Z: 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:2023-07-14T17:20:11.665Z: 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:2023-07-14T17:28:12.873Z: 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:2023-07-14T17:32:14.171Z: 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:2023-07-14T17:33:15.873Z: 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:2023-07-14T17:47:18.751Z: 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:2023-07-14T17:56:20.674Z: 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:2023-07-14T18:00:22.634Z: 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:2023-07-14T18:02:23.411Z: 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:2023-07-14T18:15:26.889Z: 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:2023-07-14T18:23:59.241Z: 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:2023-07-14T18:29:40.569Z: 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:2023-07-14T18:30:31.790Z: 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:2023-07-14T18:42:34.452Z: 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:2023-07-14T18:51:47.097Z: 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:2023-07-14T18:57:39.052Z: 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:2023-07-14T18:58:40.089Z: 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:2023-07-14T19:05:42.424Z: 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:2023-07-14T19:20:44.319Z: 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:2023-07-14T19:25:45.967Z: 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:2023-07-14T19:28:47.562Z: 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:2023-07-14T19:33:49.495Z: 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:2023-07-14T19:46:50.416Z: 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:2023-07-14T19:48:51.962Z: 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:2023-07-14T19:50:03.555Z: 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 2023-07-14_08_07_49-4908261760408134229 is in state JOB_STATE_CANCELLING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T20:01:02.823Z: JOB_MESSAGE_BASIC: Cancel request is committed for workflow job: 2023-07-14_08_07_49-4908261760408134229. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T20:01:02.859Z: JOB_MESSAGE_DETAILED: Cleaning up. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T20:01:02.927Z: JOB_MESSAGE_DEBUG: Starting **** pool teardown. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T20:01:02.954Z: JOB_MESSAGE_BASIC: Stopping **** pool... INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T20:01:02.973Z: JOB_MESSAGE_DEBUG: Starting **** pool teardown. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-07-14T20:01:02.999Z: JOB_MESSAGE_BASIC: Stopping **** pool... 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>/2023-07-14_08_07_49-4908261760408134229?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 13s 15 actionable tasks: 9 executed, 4 from cache, 2 up-to-date Publishing build scan... https://ge.apache.org/s/lgsess6sjtyvu 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]
