See
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/8691/display/redirect>
Changes:
------------------------------------------
[...truncated 238.40 KB...]
stageStates: []
startTime: '2021-11-29T13:26:03.710096Z'
steps: []
tempFiles: []
type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)>
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:830 Created job
with id: [2021-11-29_05_26_03-8860964971367960163]
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:831 Submitted job:
2021-11-29_05_26_03-8860964971367960163
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:832 To access the
Dataflow monitoring console, please navigate to
https://console.cloud.google.com/dataflow/jobs/us-central1/2021-11-29_05_26_03-8860964971367960163?project=apache-beam-testing
Worker logs:
https://console.cloud.google.com/dataflow/jobs/us-central1/2021-11-29_05_26_03-8860964971367960163?project=apache-beam-testing
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:191 Job
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:03.025Z: JOB_MESSAGE_BASIC: Dataflow Runner V2 auto-enabled.
Use --experiments=disable_runner_v2 to opt out.
[32mINFO [0m
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2021-11-29T13:26:03.025Z: JOB_MESSAGE_BASIC: Streaming Engine auto-enabled. Use
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[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:06.225Z: JOB_MESSAGE_WARNING: Autoscaling is enabled for
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maxNumWorkers is specified.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:06.614Z: JOB_MESSAGE_DETAILED: Autoscaling is enabled for job
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1 and 100.
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:06.641Z: JOB_MESSAGE_DETAILED: Autoscaling was automatically
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2021-11-29T13:26:13.435Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
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2021-11-29T13:26:13.534Z: JOB_MESSAGE_DETAILED: Expanding
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:13.565Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations
into streaming Read/Write steps
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:13.597Z: JOB_MESSAGE_DETAILED: Lifting
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:13.633Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:13.671Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read,
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:13.697Z: JOB_MESSAGE_DETAILED: Fusing consumer
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:13.731Z: JOB_MESSAGE_DETAILED: Fusing consumer
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:13.765Z: JOB_MESSAGE_DETAILED: Fusing consumer
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2021-11-29T13:26:13.808Z: JOB_MESSAGE_DEBUG: Workflow config is missing a
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2021-11-29T13:26:13.964Z: JOB_MESSAGE_BASIC: Starting 1 workers in
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:26:29.173Z: 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
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2021-11-29T13:26:55.708Z: JOB_MESSAGE_DETAILED: Autoscaling: Raised the number
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[33mWARNING [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:247 Timing out
on waiting for job 2021-11-29_05_26_03-8860964971367960163 after 60 seconds
> Task :sdks:python:test-suites:dataflow:py37:validatesRunnerStreamingTests
[32mPASSED[0m
- generated xml file:
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/sdks/python/pytest_validatesRunnerStreamingTests-df-py37-noxdist.xml>
-
[32m[1m================= 1 passed, 5109 deselected in 635.04 seconds
==================[0m
> Task :sdks:python:test-suites:dataflow:py36:validatesRunnerStreamingTests
[31m[1mERROR [0m
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sec. Received 1 messages from
projects/apache-beam-testing/subscriptions/exercise_streaming_metrics_subscription_outputec32fb1f-6bf4-4644-ab48-ada1d0f84434.
> Task :sdks:python:test-suites:dataflow:py38:validatesRunnerStreamingTests
[32mPASSED[0m
[33m=============================== warnings summary
===============================[0m
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/build/gradleenv/-1734967051/lib/python3.8/site-packages/tenacity/_asyncio.py>:42
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/build/gradleenv/-1734967051/lib/python3.8/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/latest/warnings.html
- generated xml file:
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/sdks/python/pytest_validatesRunnerStreamingTests-df-py38-noxdist.xml>
-
[33m[1m=========== 1 passed, 5109 deselected, 1 warnings in 634.23 seconds
============[0m
> Task :sdks:python:test-suites:dataflow:py36:validatesRunnerStreamingTests
[31mFAILED[0m
=================================== FAILURES ===================================
[31m[1m_
ExerciseStreamingMetricsPipelineTest.test_streaming_pipeline_returns_expected_user_metrics_fnapi_it
_[0m
self =
<apache_beam.runners.dataflow.dataflow_exercise_streaming_metrics_pipeline_test.ExerciseStreamingMetricsPipelineTest
testMethod=test_streaming_pipeline_returns_expected_user_metrics_fnapi_it>
[1m @pytest.mark.it_validatesrunner[0m
[1m @pytest.mark.no_sickbay_batch[0m
[1m @pytest.mark.no_xdist[0m
[1m def
test_streaming_pipeline_returns_expected_user_metrics_fnapi_it(self):[0m
[1m """[0m
[1m Runs streaming Dataflow job and verifies that user metrics are
reported[0m
[1m correctly.[0m
[1m """[0m
[1m self._inject_words(self.input_topic, MESSAGES_TO_PUBLISH)[0m
[1m> result = self.run_pipeline()[0m
[1m[31mapache_beam/runners/dataflow/dataflow_exercise_streaming_metrics_pipeline_test.py[0m:125:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
[1m[31mapache_beam/runners/dataflow/dataflow_exercise_streaming_metrics_pipeline_test.py[0m:113:
in run_pipeline
[1m return dataflow_exercise_streaming_metrics_pipeline.run(argv)[0m
[1m[31mapache_beam/runners/dataflow/dataflow_exercise_streaming_metrics_pipeline.py[0m:99:
in run
[1m result = pipeline.run()[0m
[1m[31mapache_beam/pipeline.py[0m:573: in run
[1m return self.runner.run_pipeline(self, self._options)[0m
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <apache_beam.runners.dataflow.test_dataflow_runner.TestDataflowRunner
object at 0x7fc000f375c0>
pipeline = <apache_beam.pipeline.Pipeline object at 0x7fc000f37358>
options = <apache_beam.options.pipeline_options.PipelineOptions object at
0x7fc000f80ac8>
[1m def run_pipeline(self, pipeline, options):[0m
[1m """Execute test pipeline and verify test matcher"""[0m
[1m test_options = options.view_as(TestOptions)[0m
[1m on_success_matcher = test_options.on_success_matcher[0m
[1m wait_duration = test_options.wait_until_finish_duration[0m
[1m is_streaming = options.view_as(StandardOptions).streaming[0m
[1m [0m
[1m # [BEAM-1889] Do not send this to remote workers also, there is no
need to[0m
[1m # send this option to remote executors.[0m
[1m test_options.on_success_matcher = None[0m
[1m [0m
[1m self.result = super().run_pipeline(pipeline, options)[0m
[1m if self.result.has_job:[0m
[1m # TODO(markflyhigh)(BEAM-1890): Use print since Nose dosen't show
logs[0m
[1m # in some cases.[0m
[1m print('Worker logs: %s' % self.build_console_url(options))[0m
[1m [0m
[1m try:[0m
[1m self.wait_until_in_state(PipelineState.RUNNING)[0m
[1m [0m
[1m if is_streaming and not wait_duration:[0m
[1m _LOGGER.warning('Waiting indefinitely for streaming job.')[0m
[1m self.result.wait_until_finish(duration=wait_duration)[0m
[1m [0m
[1m if on_success_matcher:[0m
[1m from hamcrest import assert_that as hc_assert_that[0m
[1m> hc_assert_that(self.result, pickler.loads(on_success_matcher))[0m
[1m[31mE AssertionError: [0m
[1m[31mE Expected: (Test pipeline expected terminated in state:
RUNNING and Expected 3 messages.)[0m
[1m[31mE but: Expected 3 messages. Got 1 messages. Diffs (item,
count):[0m
[1m[31mE Expected but not in actual: dict_items([(b'message b b',
1), (b'message c', 1)])[0m
[1m[31mE Unexpected: dict_items([])[0m
[1m[31mapache_beam/runners/dataflow/test_dataflow_runner.py[0m:68:
AssertionError
------------------------------ Captured log call -------------------------------
[32mINFO [0m apache_beam.runners.portability.stager:stager.py:692
Executing command:
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to staging location.
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[32mINFO [0m
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[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:667 Completed GCS
upload to
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-1129132419-717343.1638192259.717518/beautifulsoup4-4.10.0.tar.gz
in 0 seconds.
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:648 Starting GCS
upload to
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-1129132419-717343.1638192259.717518/dataflow_python_sdk.tar...
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:667 Completed GCS
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gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-1129132419-717343.1638192259.717518/dataflow_python_sdk.tar
in 0 seconds.
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:648 Starting GCS
upload to
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-1129132419-717343.1638192259.717518/dataflow-worker.jar...
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:667 Completed GCS
upload to
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-1129132419-717343.1638192259.717518/dataflow-worker.jar
in 4 seconds.
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:648 Starting GCS
upload to
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-1129132419-717343.1638192259.717518/pipeline.pb...
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:667 Completed GCS
upload to
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-1129132419-717343.1638192259.717518/pipeline.pb
in 0 seconds.
[33mWARNING [0m apache_beam.options.pipeline_options:pipeline_options.py:309
Discarding unparseable args: ['--sleep_secs=20',
'--kms_key_name=projects/apache-beam-testing/locations/global/keyRings/beam-it/cryptoKeys/test']
[33mWARNING [0m apache_beam.options.pipeline_options:pipeline_options.py:309
Discarding unparseable args: ['--sleep_secs=20',
'--kms_key_name=projects/apache-beam-testing/locations/global/keyRings/beam-it/cryptoKeys/test']
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:828 Create job:
<Job
clientRequestId: '20211129132419718689-7102'
createTime: '2021-11-29T13:24:26.675440Z'
currentStateTime: '1970-01-01T00:00:00Z'
id:
'2021-11-29_05_24_25-15874330441630144919'
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[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:830 Created job
with id: [2021-11-29_05_24_25-15874330441630144919]
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:831 Submitted job:
2021-11-29_05_24_25-15874330441630144919
[32mINFO [0m
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:837 To access the
Dataflow monitoring console, please navigate to
https://console.cloud.google.com/dataflow/jobs/us-central1/2021-11-29_05_24_25-15874330441630144919?project=apache-beam-testing
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:191 Job
2021-11-29_05_24_25-15874330441630144919 is in state JOB_STATE_RUNNING
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:25.951Z: 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:236
2021-11-29T13:24:25.951Z: 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:236
2021-11-29T13:24:29.256Z: 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:236
2021-11-29T13:24:30.303Z: JOB_MESSAGE_DETAILED: Autoscaling is enabled for job
2021-11-29_05_24_25-15874330441630144919. The number of workers will be between
1 and 100.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:30.331Z: JOB_MESSAGE_DETAILED: Autoscaling was automatically
enabled for job 2021-11-29_05_24_25-15874330441630144919.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:35.001Z: JOB_MESSAGE_BASIC: Worker configuration:
e2-standard-2 in us-central1-a.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:36.686Z: JOB_MESSAGE_DETAILED: Expanding SplittableParDo
operations into optimizable parts.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:36.719Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton
operations into optimizable parts.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:36.765Z: JOB_MESSAGE_DETAILED: Expanding CoGroupByKey
operations into optimizable parts.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:36.795Z: JOB_MESSAGE_DETAILED: Expanding
SplittableProcessKeyed operations into optimizable parts.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:36.824Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations
into streaming Read/Write steps
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:36.854Z: JOB_MESSAGE_DETAILED: Lifting
ValueCombiningMappingFns into MergeBucketsMappingFns
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:36.904Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner
information.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:36.937Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read,
Write, and Flatten operations
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:36.967Z: JOB_MESSAGE_DETAILED: Fusing consumer
generate_metrics into ReadFromPubSub/Read
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:36.995Z: JOB_MESSAGE_DETAILED: Fusing consumer
dump_to_pub/ToProtobuf into generate_metrics
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:37.016Z: 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:236
2021-11-29T13:24:37.051Z: JOB_MESSAGE_DEBUG: Workflow config is missing a
default resource spec.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:37.081Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and
teardown to workflow graph.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:37.126Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop
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[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:37.150Z: JOB_MESSAGE_DEBUG: Assigning stage ids.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:37.220Z: JOB_MESSAGE_DEBUG: Starting worker pool setup.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:37.244Z: JOB_MESSAGE_DEBUG: Starting worker pool setup.
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:37.265Z: JOB_MESSAGE_BASIC: Starting 1 workers in
us-central1-a...
[32mINFO [0m
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236
2021-11-29T13:24:59.555Z: 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:236
2021-11-29T13:25:23.537Z: 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:250 Timing out
on waiting for job 2021-11-29_05_24_25-15874330441630144919 after 61 seconds
[31m[1mERROR [0m
apache_beam.io.gcp.tests.pubsub_matcher:pubsub_matcher.py:162 Timeout after 600
sec. Received 1 messages from
projects/apache-beam-testing/subscriptions/exercise_streaming_metrics_subscription_outputec32fb1f-6bf4-4644-ab48-ada1d0f84434.
- generated xml file:
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/sdks/python/pytest_validatesRunnerStreamingTests-df-py36-noxdist.xml>
-
[31m[1m================= 1 failed, 5109 deselected in 862.33 seconds
==================[0m
> Task :sdks:python:test-suites:dataflow:py36:validatesRunnerStreamingTests
> FAILED
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: 204
* What went wrong:
Execution failed for task
':sdks:python:test-suites:dataflow:py36:validatesRunnerStreamingTests'.
> 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 7.0.
Use '--warning-mode all' to show the individual deprecation warnings.
See
https://docs.gradle.org/6.9.1/userguide/command_line_interface.html#sec:command_line_warnings
BUILD FAILED in 1h 37m 59s
92 actionable tasks: 62 executed, 30 from cache
Publishing build scan...
https://gradle.com/s/u2ctgerocjbu6
Build step 'Invoke Gradle script' changed build result to FAILURE
Build step 'Invoke Gradle script' marked build as failure
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