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Build failed in Jenkins: beam_PostCommit_Py_VR_Dataflow #8731
See <https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/8731/display/redirect>
Changes:
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[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:12.758Z: JOB_MESSAGE_DETAILED: Autoscaling was automatically enabled for job 2021-12-09_05_30_09-6892477530468586944.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:18.017Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-a.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:19.871Z: JOB_MESSAGE_DETAILED: Expanding SplittableParDo operations into optimizable parts.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:19.920Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton operations into optimizable parts.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:19.982Z: JOB_MESSAGE_DETAILED: Expanding CoGroupByKey operations into optimizable parts.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.019Z: JOB_MESSAGE_DETAILED: Expanding SplittableProcessKeyed operations into optimizable parts.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.061Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations into streaming Read/Write steps
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.091Z: JOB_MESSAGE_DETAILED: Lifting ValueCombiningMappingFns into MergeBucketsMappingFns
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.161Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner information.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.202Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.229Z: JOB_MESSAGE_DETAILED: Fusing consumer generate_metrics into ReadFromPubSub/Read
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.265Z: JOB_MESSAGE_DETAILED: Fusing consumer dump_to_pub/ToProtobuf into generate_metrics
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.286Z: JOB_MESSAGE_DETAILED: Fusing consumer dump_to_pub/Write into dump_to_pub/ToProtobuf
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[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.509Z: JOB_MESSAGE_DEBUG: Starting worker pool setup.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.547Z: JOB_MESSAGE_DEBUG: Starting worker pool setup.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.577Z: JOB_MESSAGE_BASIC: Starting 1 workers in us-central1-a...
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:47.443Z: 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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[33mWARNING [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:247 Timing out on waiting for job 2021-12-09_05_30_09-6892477530468586944 after 60 seconds
> Task :sdks:python:test-suites:dataflow:py37:validatesRunnerStreamingTests
[32mPASSED[0m
[33m=============================== warnings summary ===============================[0m
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PytestUnknownMarkWarning,
-- 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-py37-noxdist.xml> -
[33m[1m=========== 1 passed, 5125 deselected, 1 warnings in 614.82 seconds ============[0m
> Task :sdks:python:test-suites:dataflow:py36:validatesRunnerStreamingTests
[32mPASSED[0m
[33m=============================== warnings summary ===============================[0m
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[33m[1m=========== 1 passed, 5125 deselected, 1 warnings in 648.74 seconds ============[0m
> Task :sdks:python:test-suites:dataflow:py38:validatesRunnerStreamingTests
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[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 0x7f1c02700d90>
pipeline = <apache_beam.pipeline.Pipeline object at 0x7f1c02700040>
options = <apache_beam.options.pipeline_options.PipelineOptions object at 0x7f1c02700280>
[1m def run_pipeline(self, pipeline, options):[0m
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[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
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[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 0 messages. Diffs (item, count):[0m
[1m[31mE Expected but not in actual: dict_items([(b'message a', 1), (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 -------------------------------
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[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-1209133001-645203.1639056601.645348/parameterized-0.7.4.tar.gz...
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[32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:664 Completed GCS upload to gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-1209133001-645203.1639056601.645348/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-1209133001-645203.1639056601.645348/dataflow-worker.jar...
[32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:664 Completed GCS upload to gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-1209133001-645203.1639056601.645348/dataflow-worker.jar in 5 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-1209133001-645203.1639056601.645348/pipeline.pb...
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[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
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createTime: '2021-12-09T13:30:09.717457Z'
currentStateTime: '1970-01-01T00:00:00Z'
id: '2021-12-09_05_30_09-6892477530468586944'
location: 'us-central1'
name: 'beamapp-jenkins-1209133001-645203'
projectId: 'apache-beam-testing'
stageStates: []
startTime: '2021-12-09T13:30:09.717457Z'
steps: []
tempFiles: []
type: TypeValueValuesEnum(JOB_TYPE_STREAMING, 2)>
[32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:830 Created job with id: [2021-12-09_05_30_09-6892477530468586944]
[32mINFO [0m apache_beam.runners.dataflow.internal.apiclient:apiclient.py:831 Submitted job: 2021-12-09_05_30_09-6892477530468586944
[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-central1/2021-12-09_05_30_09-6892477530468586944?project=apache-beam-testing
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:191 Job 2021-12-09_05_30_09-6892477530468586944 is in state JOB_STATE_RUNNING
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:09.039Z: 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 2021-12-09T13:30:09.039Z: 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 2021-12-09T13:30:12.606Z: 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 2021-12-09T13:30:12.733Z: JOB_MESSAGE_DETAILED: Autoscaling is enabled for job 2021-12-09_05_30_09-6892477530468586944. The number of workers will be between 1 and 100.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:12.758Z: JOB_MESSAGE_DETAILED: Autoscaling was automatically enabled for job 2021-12-09_05_30_09-6892477530468586944.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:18.017Z: JOB_MESSAGE_BASIC: Worker configuration: e2-standard-2 in us-central1-a.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:19.871Z: JOB_MESSAGE_DETAILED: Expanding SplittableParDo operations into optimizable parts.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:19.920Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton operations into optimizable parts.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:19.982Z: JOB_MESSAGE_DETAILED: Expanding CoGroupByKey operations into optimizable parts.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.019Z: JOB_MESSAGE_DETAILED: Expanding SplittableProcessKeyed operations into optimizable parts.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.061Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations into streaming Read/Write steps
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.091Z: JOB_MESSAGE_DETAILED: Lifting ValueCombiningMappingFns into MergeBucketsMappingFns
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.161Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner information.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.202Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, Write, and Flatten operations
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.229Z: JOB_MESSAGE_DETAILED: Fusing consumer generate_metrics into ReadFromPubSub/Read
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.265Z: JOB_MESSAGE_DETAILED: Fusing consumer dump_to_pub/ToProtobuf into generate_metrics
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.286Z: 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 2021-12-09T13:30:20.352Z: JOB_MESSAGE_DEBUG: Workflow config is missing a default resource spec.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.384Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and teardown to workflow graph.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.423Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop steps.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.455Z: JOB_MESSAGE_DEBUG: Assigning stage ids.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.509Z: JOB_MESSAGE_DEBUG: Starting worker pool setup.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.547Z: JOB_MESSAGE_DEBUG: Starting worker pool setup.
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:20.577Z: JOB_MESSAGE_BASIC: Starting 1 workers in us-central1-a...
[32mINFO [0m apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:236 2021-12-09T13:30:47.443Z: 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 2021-12-09T13:31:08.924Z: 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:247 Timing out on waiting for job 2021-12-09_05_30_09-6892477530468586944 after 60 seconds
[1m[31mERROR [0m apache_beam.io.gcp.tests.pubsub_matcher:pubsub_matcher.py:158 Timeout after 600 sec. Received 0 messages from projects/apache-beam-testing/subscriptions/exercise_streaming_metrics_subscription_output86607299-c78b-41f1-b0e0-e88a118a23f6.
[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/_pytest/mark/structures.py>:331
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow/ws/src/build/gradleenv/-1734967051/lib/python3.8/site-packages/_pytest/mark/structures.py>:331: PytestUnknownMarkWarning: Unknown pytest.mark.spannerio_it - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/latest/mark.html
warnings.warn(
<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> -
[31m[1m=========== 1 failed, 5125 deselected, 2 warnings in 872.04 seconds ============[0m
> Task :sdks:python:test-suites:dataflow:py38: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: 249
* What went wrong:
Execution failed for task ':sdks:python:test-suites:dataflow:py38: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 43m 50s
92 actionable tasks: 64 executed, 28 from cache
Publishing build scan...
https://gradle.com/s/otpifietjldrs
Build step 'Invoke Gradle script' changed build result to FAILURE
Build step 'Invoke Gradle script' marked build as failure
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