See <https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/904/display/redirect?page=changes>
Changes: [xqhu] Ignore flags for beam_sql magic [xqhu] Raise the error when some functions are misused [xqhu] change how to import [noreply] Add WatchFilePattern (#25393) [noreply] Support gauge metrics in portable mode (#25396) [noreply] Validate that GBK coders are always set correctly. (#25394) [noreply] Fix tox error running hdfsIntegrationTest (#25446) [noreply] Adding support for DLQ for ZetaSQL (#25426) [noreply] Remove python 3.6 references (#25445) [noreply] Fix pulling licenses (#25456) ------------------------------------------ [...truncated 27.47 KB...] Collecting cffi>=1.12 Using cached cffi-1.15.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (427 kB) Collecting oauth2client>=1.4.12 Using cached oauth2client-4.1.3-py2.py3-none-any.whl (98 kB) Collecting rsa<5,>=3.1.4 Using cached rsa-4.9-py3-none-any.whl (34 kB) Collecting pyasn1-modules>=0.2.1 Using cached pyasn1_modules-0.2.8-py2.py3-none-any.whl (155 kB) Collecting google-resumable-media<3.0dev,>=0.6.0 Using cached google_resumable_media-2.4.1-py2.py3-none-any.whl (77 kB) Requirement already satisfied: packaging>=20.0.0 in <https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/ws/src/build/gradleenv/1329484227/lib/python3.7/site-packages> (from google-cloud-bigquery<4,>=1.6.0->apache-beam==2.46.0.dev0) (23.0) Collecting google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.0,<3.0.0dev,>=1.31.5 Using cached google_api_core-2.11.0-py3-none-any.whl (120 kB) Collecting grpc-google-iam-v1<0.13dev,>=0.12.3 Using cached grpc_google_iam_v1-0.12.6-py2.py3-none-any.whl (26 kB) Collecting grpcio-status>=1.33.2 Using cached grpcio_status-1.51.1-py3-none-any.whl (5.1 kB) Collecting overrides<7.0.0,>=6.0.1 Using cached overrides-6.5.0-py3-none-any.whl (17 kB) Collecting sqlparse>=0.3.0 Using cached sqlparse-0.4.3-py3-none-any.whl (42 kB) Collecting docopt Using cached docopt-0.6.2-py2.py3-none-any.whl Collecting pyparsing!=3.0.0,!=3.0.1,!=3.0.2,!=3.0.3,<4,>=2.4.2 Using cached pyparsing-3.0.9-py3-none-any.whl (98 kB) Collecting sortedcontainers<3.0.0,>=2.1.0 Using cached sortedcontainers-2.4.0-py2.py3-none-any.whl (29 kB) Collecting exceptiongroup>=1.0.0 Using cached exceptiongroup-1.1.0-py3-none-any.whl (14 kB) Collecting attrs>=19.2.0 Using 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PyJWT[crypto]<3,>=1.0.0 Using cached PyJWT-2.6.0-py3-none-any.whl (20 kB) Collecting portalocker<3,>=1.0 Using cached portalocker-2.7.0-py2.py3-none-any.whl (15 kB) Collecting isodate>=0.6.0 Using cached isodate-0.6.1-py2.py3-none-any.whl (41 kB) Collecting requests-oauthlib>=0.5.0 Using cached requests_oauthlib-1.3.1-py2.py3-none-any.whl (23 kB) Collecting pyasn1>=0.1.7 Using cached pyasn1-0.4.8-py2.py3-none-any.whl (77 kB) Requirement already satisfied: py in <https://ci-beam.apache.org/job/beam_LoadTests_Python_Combine_Dataflow_Streaming/ws/src/build/gradleenv/1329484227/lib/python3.7/site-packages> (from pytest-forked->pytest-xdist<3,>=2.5.0->apache-beam==2.46.0.dev0) (1.11.0) Collecting oauthlib>=3.0.0 Using cached oauthlib-3.2.2-py3-none-any.whl (151 kB) Building wheels for collected packages: apache-beam Building wheel for apache-beam (setup.py): started Building wheel for apache-beam (setup.py): finished with status 'done' Created wheel for apache-beam: filename=apache_beam-2.46.0.dev0-py3-none-any.whl size=3013053 sha256=7f97bad70360ad4f10b9deccdc893654556599954efc72d481c3eaac24fa6af0 Stored in directory: /home/jenkins/.cache/pip/wheels/e6/1f/28/9337974c607f5f016ef124646a645ebf2fb34bdd32df5f9dd8 Successfully built apache-beam Installing collected packages: sortedcontainers, pytz, pyasn1, parameterized, docopt, crcmod, charset-normalizer, zstandard, wrapt, websocket-client, urllib3, tomli, threadpoolctl, tenacity, sqlparse, scipy, rsa, regex, pyyaml, python-dateutil, pyparsing, pymysql, pymongo, PyJWT, pyhamcrest, pycparser, pyasn1-modules, pyarrow, psycopg2-binary, proto-plus, portalocker, pbr, overrides, orjson, objsize, oauthlib, joblib, jmespath, isodate, iniconfig, idna, greenlet, googleapis-common-protos, google-crc32c, fasteners, fastavro, execnet, exceptiongroup, dill, deprecation, cloudpickle, certifi, cachetools, attrs, sqlalchemy, scikit-learn, requests, pydot, pandas, mock, hypothesis, httplib2, grpcio-status, google-resumable-media, google-auth, freezegun, cffi, botocore, s3transfer, requests-oauthlib, requests_mock, pytest, oauth2client, hdfs, grpc-google-iam-v1, google-auth-httplib2, google-api-core, docker, cryptography, azure-core, testcontainers, pytest-timeout, pytest-forked, msrest, google-cloud-core, google-apitools, boto3, apache-beam, pytest-xdist, 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, azure-storage-blob, msal-extensions, google-cloud-pubsublite, azure-identity Successfully installed PyJWT-2.6.0 apache-beam-2.46.0.dev0 attrs-22.2.0 azure-core-1.26.3 azure-identity-1.12.0 azure-storage-blob-12.14.1 boto3-1.26.70 botocore-1.29.70 cachetools-4.2.4 certifi-2022.12.7 cffi-1.15.1 charset-normalizer-3.0.1 cloudpickle-2.2.1 crcmod-1.7 cryptography-39.0.1 deprecation-2.1.0 dill-0.3.1.1 docker-6.0.1 docopt-0.6.2 exceptiongroup-1.1.0 execnet-1.9.0 fastavro-1.7.1 fasteners-0.18 freezegun-1.2.2 google-api-core-2.11.0 google-apitools-0.5.31 google-auth-2.16.0 google-auth-httplib2-0.1.0 google-cloud-bigquery-3.5.0 google-cloud-bigquery-storage-2.16.2 google-cloud-bigtable-1.7.3 google-cloud-core-2.3.2 google-cloud-datastore-1.15.5 google-cloud-dlp-3.11.1 google-cloud-language-1.3.2 google-cloud-pubsub-2.14.1 google-cloud-pubsublite-1.6.0 google-cloud-recommendations-ai-0.7.1 google-cloud-spanner-3.27.1 google-cloud-videointelligence-1.16.3 google-cloud-vision-3.3.1 google-crc32c-1.5.0 google-resumable-media-2.4.1 googleapis-common-protos-1.58.0 greenlet-2.0.2 grpc-google-iam-v1-0.12.6 grpcio-status-1.48.2 hdfs-2.7.0 httplib2-0.21.0 hypothesis-6.68.1 idna-3.4 iniconfig-2.0.0 isodate-0.6.1 jmespath-1.0.1 joblib-1.2.0 mock-2.0.0 msal-1.21.0 msal-extensions-1.0.0 msrest-0.7.1 oauth2client-4.1.3 oauthlib-3.2.2 objsize-0.6.1 orjson-3.8.6 overrides-6.5.0 pandas-1.3.5 parameterized-0.8.1 pbr-5.11.1 portalocker-2.7.0 proto-plus-1.22.2 psycopg2-binary-2.9.5 pyarrow-9.0.0 pyasn1-0.4.8 pyasn1-modules-0.2.8 pycparser-2.21 pydot-1.4.2 pyhamcrest-1.10.1 pymongo-3.13.0 pymysql-1.0.2 pyparsing-3.0.9 pytest-7.2.1 pytest-forked-1.6.0 pytest-timeout-2.1.0 pytest-xdist-2.5.0 python-dateutil-2.8.2 pytz-2022.7.1 pyyaml-6.0 regex-2022.10.31 requests-2.28.2 requests-oauthlib-1.3.1 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-1.4.46 sqlparse-0.4.3 tenacity-5.1.5 testcontainers-3.7.1 threadpoolctl-3.1.0 tomli-2.0.1 urllib3-1.26.14 websocket-client-1.5.1 wrapt-1.14.1 zstandard-0.19.0 > 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:Default Python SDK image for environment is apache/beam_python3.7_sdk:2.46.0.dev INFO:root:Using provided Python SDK container image: gcr.io/cloud-dataflow/v1beta3/python37-fnapi:beam-master-20230126 INFO:root:Python SDK container image set to "gcr.io/cloud-dataflow/v1beta3/python37-fnapi:beam-master-20230126" 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-1-0214150235.1676387292.587932/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-1-0214150235.1676387292.587932/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-1-0214150235.1676387292.587932/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-1-0214150235.1676387292.587932/pipeline.pb in 0 seconds. INFO:apache_beam.runners.dataflow.internal.apiclient:Create job: <Job clientRequestId: '20230214150812588980-6820' createTime: '2023-02-14T15:08:13.693346Z' currentStateTime: '1970-01-01T00:00:00Z' id: '2023-02-14_07_08_13-17476471195205100016' location: 'us-central1' name: 'load-tests-python-dataflow-streaming-combine-1-0214150235' projectId: 'apache-beam-testing' stageStates: [] startTime: '2023-02-14T15:08:13.693346Z' steps: [] tempFiles: [] type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)> INFO:apache_beam.runners.dataflow.internal.apiclient:Created job with id: [2023-02-14_07_08_13-17476471195205100016] INFO:apache_beam.runners.dataflow.internal.apiclient:Submitted job: 2023-02-14_07_08_13-17476471195205100016 INFO:apache_beam.runners.dataflow.internal.apiclient:To access the Dataflow monitoring console, please navigate to https://console.cloud.google.com/dataflow/jobs/us-central1/2023-02-14_07_08_13-17476471195205100016?project=apache-beam-testing INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-02-14_07_08_13-17476471195205100016 is in state JOB_STATE_PENDING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:19.010Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-a. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.316Z: JOB_MESSAGE_DETAILED: Expanding SplittableParDo operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.373Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.446Z: JOB_MESSAGE_DETAILED: Expanding CoGroupByKey operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.541Z: JOB_MESSAGE_DETAILED: Expanding SplittableProcessKeyed operations into optimizable parts. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.584Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations into streaming Read/Write steps INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.648Z: JOB_MESSAGE_DETAILED: Lifting ValueCombiningMappingFns into MergeBucketsMappingFns INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.716Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner information. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.770Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.810Z: JOB_MESSAGE_DETAILED: Fusing consumer Read synthetic/Map(<lambda at iobase.py:908>) into Read synthetic/Impulse INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.853Z: 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:2023-02-14T15:08:20.885Z: 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:2023-02-14T15:08:20.922Z: 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:2023-02-14T15:08:20.954Z: JOB_MESSAGE_DETAILED: Fusing consumer Combine with Top 0/KeyWithVoid into Measure time: Start INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:20.990Z: 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:2023-02-14T15:08:21.034Z: 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:2023-02-14T15:08:21.073Z: 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:2023-02-14T15:08:21.106Z: 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:2023-02-14T15:08:21.140Z: 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:2023-02-14T15:08:21.188Z: JOB_MESSAGE_DETAILED: Fusing consumer Consume 0 into Combine with Top 0/UnKey INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:21.225Z: JOB_MESSAGE_DETAILED: Fusing consumer Measure time: End 0 into Consume 0 INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:21.335Z: JOB_MESSAGE_BASIC: Running job using Streaming Engine INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:21.380Z: JOB_MESSAGE_DEBUG: Workflow config is missing a default resource spec. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:21.426Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and teardown to workflow graph. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:21.463Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop steps. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:21.505Z: JOB_MESSAGE_DEBUG: Assigning stage ids. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:22.600Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:22.641Z: JOB_MESSAGE_DEBUG: Starting **** pool setup. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:22.670Z: JOB_MESSAGE_BASIC: Starting 5 ****s in us-central1-a... INFO:apache_beam.runners.dataflow.dataflow_runner:Job 2023-02-14_07_08_13-17476471195205100016 is in state JOB_STATE_RUNNING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:08:32.917Z: 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:2023-02-14T15:09:01.572Z: 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:2023-02-14T15:09:33.245Z: JOB_MESSAGE_DETAILED: Workers have started successfully. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:09:45.260Z: JOB_MESSAGE_DETAILED: All ****s have finished the startup processes and began to receive work requests. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T15:50:49.877Z: 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:2023-02-14T15:51:51.361Z: 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:2023-02-14T15:53:59.599Z: 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:2023-02-14T15:54:54.235Z: 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:2023-02-14T16:22:15.174Z: 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:2023-02-14T16:35:52.467Z: 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:2023-02-14T16:36:57.255Z: 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:2023-02-14T16:38:58.298Z: 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:2023-02-14T16:56:56.102Z: 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:2023-02-14T17:08:01.254Z: 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:2023-02-14T17:17:58.523Z: 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:2023-02-14T17:18:59.564Z: 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:2023-02-14T17:30:01.307Z: 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:2023-02-14T17:33:02.304Z: 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:2023-02-14T17:50:03.512Z: 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:2023-02-14T17:57:04.356Z: 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:2023-02-14T18:01:05.779Z: 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:2023-02-14T18:10:07.256Z: 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:2023-02-14T18:23:08.391Z: 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:2023-02-14T18:26:09.469Z: 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:2023-02-14T18:30:10.937Z: 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:2023-02-14T18:44:11.766Z: 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:2023-02-14T18:53:12.561Z: 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:2023-02-14T18:54:13.686Z: 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:2023-02-14T19:05:14.502Z: 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:2023-02-14T19:18:16.242Z: 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:2023-02-14T19:23:17.046Z: 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:2023-02-14T19:26:18.057Z: 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:2023-02-14T19:38:19.107Z: 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:2023-02-14T19:44:20.220Z: 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:2023-02-14T19:57:21.011Z: 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:2023-02-14T20:03:22.234Z: 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:2023-02-14T20:10:23.644Z: 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:2023-02-14T20:11:24.505Z: 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:Job 2023-02-14_07_08_13-17476471195205100016 is in state JOB_STATE_CANCELLING INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T20:18:33.322Z: JOB_MESSAGE_BASIC: Cancel request is committed for workflow job: 2023-02-14_07_08_13-17476471195205100016. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T20:18:33.350Z: JOB_MESSAGE_DETAILED: Cleaning up. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T20:18:33.385Z: JOB_MESSAGE_DEBUG: Starting **** pool teardown. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T20:18:33.406Z: JOB_MESSAGE_BASIC: Stopping **** pool... INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T20:18:33.437Z: JOB_MESSAGE_DEBUG: Starting **** pool teardown. INFO:apache_beam.runners.dataflow.dataflow_runner:2023-02-14T20:18:33.458Z: 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 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>/2023-02-14_07_08_13-17476471195205100016?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 5h 12m 31s 15 actionable tasks: 9 executed, 4 from cache, 2 up-to-date Publishing build scan... https://gradle.com/s/bfnawm3z765u4 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]
