See <https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/9663/display/redirect>
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[32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:911 Create job: <Job clientRequestId: '20220802153454814357-2535' createTime: '2022-08-02T15:35:10.314454Z' currentStateTime: '1970-01-01T00:00:00Z' id: '2022-08-02_08_35_09-10614664617212284206' location: 'us-central1' name: 'beamapp-jenkins-0802153454-812993-nthvafm2' projectId: 'apache-beam-testing' stageStates: [] startTime: '2022-08-02T15:35:10.314454Z' steps: [] tempFiles: [] type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)> [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:913 Created job with id: [2022-08-02_08_35_09-10614664617212284206] [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:914 Submitted job: 2022-08-02_08_35_09-10614664617212284206 [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:915 To access the Dataflow monitoring console, please navigate to https://console.cloud.google.com/dataflow/jobs/us-central1/2022-08-02_08_35_09-10614664617212284206?project=apache-beam-testing Worker logs: https://console.cloud.google.com/dataflow/jobs/us-central1/2022-08-02_08_35_09-10614664617212284206?project=apache-beam-testing [32mINFO [0m apache_beam.runners.dataflow.test_dataflow_runner:test_dataflow_runner.py:58 Console log: [32mINFO [0m apache_beam.runners.dataflow.test_dataflow_runner:test_dataflow_runner.py:59 https://console.cloud.google.com/dataflow/jobs/us-central1/2022-08-02_08_35_09-10614664617212284206?project=apache-beam-testing > Task :sdks:python:test-suites:dataflow:py37:validatesRunnerStreamingTests [gw3] [32mPASSED[0m apache_beam/transforms/util_test.py::ReshuffleTest::test_reshuffle_preserves_timestamps [33m=============================== warnings summary ===============================[0m ../../build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py:15 ../../build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py:15 ../../build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py:15 ../../build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py:15 ../../build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py:15 ../../build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py:15 ../../build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py:15 ../../build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py:15 ../../build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py:15 <https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py>:15: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses from imp import load_source -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html - generated xml file: <https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/sdks/python/pytest_validatesRunnerStreamingTests-df-py37-xdist.xml> - [33m============ [32m30 passed[0m, [33m[1m5 skipped[0m, [33m[1m9 warnings[0m[33m in 2533.73s (0:42:13)[0m[33m ============[0m >>> RUNNING integration tests with pipeline options: >>> --runner=TestDataflowRunner --project=apache-beam-testing >>> --region=us-central1 >>> --staging_location=gs://temp-storage-for-end-to-end-tests/staging-it >>> --temp_location=gs://temp-storage-for-end-to-end-tests/temp-it >>> --output=gs://temp-storage-for-end-to-end-tests/py-it-cloud/output >>> --sdk_location=<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/sdks/python/build/apache-beam.tar.gz> >>> --requirements_file=postcommit_requirements.txt --num_workers=1 >>> --sleep_secs=20 --streaming >>> --dataflow_worker_jar=<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/runners/google-cloud-dataflow-java/worker/build/libs/beam-runners-google-cloud-dataflow-java-fn-api-worker-2.42.0-SNAPSHOT.jar> >>> >>> --kms_key_name=projects/apache-beam-testing/locations/global/keyRings/beam-it/cryptoKeys/test >>> >>> --dataflow_kms_key=projects/apache-beam-testing/locations/global/keyRings/beam-it/cryptoKeys/test >>> pytest options: --capture=no --timeout=4500 --color=yes >>> --log-cli-level=INFO >>> collect markers: -m=it_validatesrunner and not no_sickbay_streaming and >>> no_xdist [1m============================= test session starts ==============================[0m platform linux -- Python 3.7.12, pytest-7.1.2, pluggy-1.0.0 rootdir: <https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/sdks/python,> configfile: pytest.ini plugins: xdist-2.5.0, timeout-2.1.0, forked-1.4.0, requests-mock-1.9.3 timeout: 4500.0s timeout method: signal timeout func_only: False [1m----------------------------- live log collection ------------------------------[0m [33mWARNING [0m root:avroio_test.py:54 python-snappy is not installed; some tests will be skipped. 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[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:478 Pipeline has additional dependencies to be installed in SDK worker 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 [32mINFO [0m root:environments.py:376 Default Python SDK image for environment is apache/beam_python3.7_sdk:2.42.0.dev [32mINFO [0m root:environments.py:296 Using provided Python SDK container image: gcr.io/cloud-dataflow/v1beta3/python37-fnapi:beam-master-20220617 [32mINFO [0m root:environments.py:304 Python SDK container image set to "gcr.io/cloud-dataflow/v1beta3/python37-fnapi:beam-master-20220617" for Docker environment [32mINFO [0m apache_beam.internal.gcp.auth:auth.py:136 Setting socket default timeout to 60 seconds. [32mINFO [0m apache_beam.internal.gcp.auth:auth.py:139 socket default timeout is 60.0 seconds. 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[32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:732 Starting GCS upload to gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0802153533-362816-nthvafm2.1659454533.363026/dataflow_python_sdk.tar... [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:751 Completed GCS upload to gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0802153533-362816-nthvafm2.1659454533.363026/dataflow_python_sdk.tar in 0 seconds. [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:732 Starting GCS upload to gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0802153533-362816-nthvafm2.1659454533.363026/dataflow-worker.jar... > Task :sdks:python:test-suites:dataflow:py39:validatesRunnerStreamingTests [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:197 Job 2022-08-02_08_35_09-10614664617212284206 is in state JOB_STATE_RUNNING [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:09.937Z: JOB_MESSAGE_BASIC: Dataflow Runner V2 auto-enabled. Use --experiments=disable_runner_v2 to opt out. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:09.937Z: JOB_MESSAGE_BASIC: Streaming Engine auto-enabled. Use --experiments=disable_streaming_engine to opt out. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:10.937Z: JOB_MESSAGE_WARNING: Autoscaling is enabled for Dataflow Streaming Engine. Workers will scale between 1 and 100 unless maxNumWorkers is specified. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:11.045Z: JOB_MESSAGE_DETAILED: Autoscaling is enabled for job 2022-08-02_08_35_09-10614664617212284206. The number of workers will be between 1 and 100. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:11.078Z: JOB_MESSAGE_DETAILED: Autoscaling was automatically enabled for job 2022-08-02_08_35_09-10614664617212284206. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:16.697Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-b. 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[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:18.898Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations into streaming Read/Write steps [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:18.920Z: JOB_MESSAGE_DETAILED: Lifting ValueCombiningMappingFns into MergeBucketsMappingFns [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:18.942Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner information. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:18.971Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:18.999Z: JOB_MESSAGE_DETAILED: Fusing consumer generate_metrics into ReadFromPubSub/Read [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.034Z: JOB_MESSAGE_DETAILED: Fusing consumer dump_to_pub/ToProtobuf into generate_metrics [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.069Z: JOB_MESSAGE_DETAILED: Fusing consumer dump_to_pub/Write into dump_to_pub/ToProtobuf [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.099Z: JOB_MESSAGE_BASIC: Running job using Streaming Engine [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.125Z: JOB_MESSAGE_BASIC: Using cloud KMLS key to protect persistent state. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.222Z: JOB_MESSAGE_DEBUG: Workflow config is missing a default resource spec. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.260Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and teardown to workflow graph. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.285Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop steps. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.306Z: JOB_MESSAGE_DEBUG: Assigning stage ids. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.397Z: JOB_MESSAGE_DEBUG: Starting worker pool setup. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.428Z: JOB_MESSAGE_DEBUG: Starting worker pool setup. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:19.464Z: JOB_MESSAGE_BASIC: Starting 1 workers in us-central1-b... [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:26.306Z: 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 [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.742Z: JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of workers to 1 so that the pipeline can catch up with its backlog and keep up with its input rate. > Task :sdks:python:test-suites:dataflow:py37:validatesRunnerStreamingTests [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:751 Completed GCS upload to gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0802153533-362816-nthvafm2.1659454533.363026/dataflow-worker.jar in 6 seconds. [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:732 Starting GCS upload to gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0802153533-362816-nthvafm2.1659454533.363026/pipeline.pb... [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:751 Completed GCS upload to gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0802153533-362816-nthvafm2.1659454533.363026/pipeline.pb in 0 seconds. [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:911 Create job: <Job clientRequestId: '20220802153533364209-2535' createTime: '2022-08-02T15:35:44.926024Z' currentStateTime: '1970-01-01T00:00:00Z' id: '2022-08-02_08_35_44-3120097248176262240' location: 'us-central1' name: 'beamapp-jenkins-0802153533-362816-nthvafm2' projectId: 'apache-beam-testing' stageStates: [] startTime: '2022-08-02T15:35:44.926024Z' steps: [] tempFiles: [] type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)> [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:913 Created job with id: [2022-08-02_08_35_44-3120097248176262240] [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:914 Submitted job: 2022-08-02_08_35_44-3120097248176262240 [32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:920 To access the Dataflow monitoring console, please navigate to https://console.cloud.google.com/dataflow/jobs/us-central1/2022-08-02_08_35_44-3120097248176262240?project=apache-beam-testing Worker logs: https://console.cloud.google.com/dataflow/jobs/us-central1/2022-08-02_08_35_44-3120097248176262240?project=apache-beam-testing [32mINFO [0m apache_beam.runners.dataflow.test_dataflow_runner:test_dataflow_runner.py:58 Console log: [32mINFO [0m apache_beam.runners.dataflow.test_dataflow_runner:test_dataflow_runner.py:59 https://console.cloud.google.com/dataflow/jobs/us-central1/2022-08-02_08_35_44-3120097248176262240?project=apache-beam-testing [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:197 Job 2022-08-02_08_35_44-3120097248176262240 is in state JOB_STATE_RUNNING [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:44.575Z: JOB_MESSAGE_BASIC: Streaming Engine auto-enabled. Use --experiments=disable_streaming_engine to opt out. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:44.575Z: JOB_MESSAGE_BASIC: Dataflow Runner V2 auto-enabled. Use --experiments=disable_runner_v2 to opt out. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:45.633Z: JOB_MESSAGE_WARNING: Autoscaling is enabled for Dataflow Streaming Engine. Workers will scale between 1 and 100 unless maxNumWorkers is specified. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:45.924Z: JOB_MESSAGE_DETAILED: Autoscaling is enabled for job 2022-08-02_08_35_44-3120097248176262240. The number of workers will be between 1 and 100. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:45.949Z: JOB_MESSAGE_DETAILED: Autoscaling was automatically enabled for job 2022-08-02_08_35_44-3120097248176262240. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:51.693Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-b. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:53.827Z: JOB_MESSAGE_DETAILED: Expanding SplittableParDo operations into optimizable parts. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:53.857Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton operations into optimizable parts. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:53.953Z: JOB_MESSAGE_DETAILED: Expanding CoGroupByKey operations into optimizable parts. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:53.993Z: JOB_MESSAGE_DETAILED: Expanding SplittableProcessKeyed operations into optimizable parts. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.022Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations into streaming Read/Write steps [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.058Z: JOB_MESSAGE_DETAILED: Lifting ValueCombiningMappingFns into MergeBucketsMappingFns [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.090Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner information. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.133Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.159Z: JOB_MESSAGE_DETAILED: Fusing consumer generate_metrics into ReadFromPubSub/Read [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.192Z: JOB_MESSAGE_DETAILED: Fusing consumer dump_to_pub/ToProtobuf into generate_metrics [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.216Z: JOB_MESSAGE_DETAILED: Fusing consumer dump_to_pub/Write into dump_to_pub/ToProtobuf [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.242Z: JOB_MESSAGE_BASIC: Running job using Streaming Engine [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.272Z: JOB_MESSAGE_BASIC: Using cloud KMLS key to protect persistent state. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.364Z: JOB_MESSAGE_DEBUG: Workflow config is missing a default resource spec. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.391Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and teardown to workflow graph. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.416Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop steps. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.439Z: JOB_MESSAGE_DEBUG: Assigning stage ids. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.488Z: JOB_MESSAGE_DEBUG: Starting worker pool setup. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.515Z: JOB_MESSAGE_BASIC: Starting 1 workers in us-central1-b... [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:35:54.547Z: JOB_MESSAGE_DEBUG: Starting worker pool setup. [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:36:04.216Z: 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 > Task :sdks:python:test-suites:dataflow:py39:validatesRunnerStreamingTests [33mWARNING [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:253 Timing out on waiting for job 2022-08-02_08_35_09-10614664617212284206 after 61 seconds > Task :sdks:python:test-suites:dataflow:py37:validatesRunnerStreamingTests [32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:242 2022-08-02T15:36:32.240Z: JOB_MESSAGE_DETAILED: Autoscaling: Raised the number of workers to 1 so that the pipeline can catch up with its backlog and keep up with its input rate. [33mWARNING [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:256 Timing out on waiting for job 2022-08-02_08_35_44-3120097248176262240 after 61 seconds [32mPASSED[0m [33m=============================== warnings summary ===============================[0m ../../build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py:15 <https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/build/gradleenv/-1734967052/lib/python3.7/site-packages/hdfs/config.py>:15: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses from imp import load_source -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html - generated xml file: <https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/sdks/python/pytest_validatesRunnerStreamingTests-df-py37-noxdist.xml> - [33m===== [32m1 passed[0m, [33m[1m2 skipped[0m, [33m[1m6523 deselected[0m, [33m[1m1 warning[0m[33m in 492.11s (0:08:12)[0m[33m =====[0m > Task :sdks:python:test-suites:dataflow:py39:validatesRunnerStreamingTests [32mPASSED[0m [33m=============================== warnings summary ===============================[0m ../../build/gradleenv/-1734967050/lib/python3.9/site-packages/hdfs/config.py:15 <https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/build/gradleenv/-1734967050/lib/python3.9/site-packages/hdfs/config.py>:15: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses from imp import load_source ../../build/gradleenv/-1734967050/lib/python3.9/site-packages/tenacity/_asyncio.py:42 <https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/build/gradleenv/-1734967050/lib/python3.9/site-packages/tenacity/_asyncio.py>:42: DeprecationWarning: "@coroutine" decorator is deprecated since Python 3.8, use "async def" instead def call(self, fn, *args, **kwargs): -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html - generated xml file: <https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/sdks/python/pytest_validatesRunnerStreamingTests-df-py39-noxdist.xml> - [33m==== [32m1 passed[0m, [33m[1m2 skipped[0m, [33m[1m6523 deselected[0m, [33m[1m2 warnings[0m[33m in 592.84s (0:09:52)[0m[33m =====[0m > Task :sdks:python:test-suites:dataflow:validatesRunnerStreamingTests FAILURE: Build failed with an exception. * Where: Script '<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/sdks/python/test-suites/dataflow/common.gradle'> line: 232 * What went wrong: Execution failed for task ':sdks:python:test-suites:dataflow:py39:validatesRunnerBatchTests'. > Process 'command 'sh'' finished with non-zero exit value 1 * Try: > Run with --stacktrace option to get the stack trace. > Run with --info or --debug option to get more log output. > Run with --scan to get full insights. * 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/7.4/userguide/command_line_interface.html#sec:command_line_warnings BUILD FAILED in 1h 25m 4s 100 actionable tasks: 65 executed, 33 from cache, 2 up-to-date Publishing build scan... https://gradle.com/s/cib2yvyatf3we 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]
