See 
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow_V2/4908/display/redirect>

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apache_beam.runners.dataflow.internal.apiclient:apiclient.py:734 Starting GCS 
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apache_beam.runners.dataflow.internal.apiclient:apiclient.py:750 Completed GCS 
upload to 
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0519163719-272688-nthvafm2.1684514239.272845/scikit_learn-1.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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apache_beam.runners.dataflow.internal.apiclient:apiclient.py:734 Starting GCS 
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apache_beam.runners.dataflow.internal.apiclient:apiclient.py:750 Completed GCS 
upload to 
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0519163719-272688-nthvafm2.1684514239.272845/scikit_learn-1.0.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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apache_beam.runners.dataflow.internal.apiclient:apiclient.py:734 Starting GCS 
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gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0519163719-272688-nthvafm2.1684514239.272845/scikit_learn-1.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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apache_beam.runners.dataflow.internal.apiclient:apiclient.py:734 Starting GCS 
upload to 
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0519163719-272688-nthvafm2.1684514239.272845/apache_beam-2.49.0.dev0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl...
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apache_beam.runners.dataflow.internal.apiclient:apiclient.py:750 Completed GCS 
upload to 
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0519163719-272688-nthvafm2.1684514239.272845/apache_beam-2.49.0.dev0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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apache_beam.runners.dataflow.internal.apiclient:apiclient.py:734 Starting GCS 
upload to 
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apache_beam.runners.dataflow.internal.apiclient:apiclient.py:750 Completed GCS 
upload to 
gs://temp-storage-for-end-to-end-tests/staging-it/beamapp-jenkins-0519163719-272688-nthvafm2.1684514239.272845/pipeline.pb
 in 0 seconds.
INFO     
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:909 Create job: 
<Job
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apache_beam.runners.dataflow.internal.apiclient:apiclient.py:911 Created job 
with id: [2023-05-19_09_38_52-12886453873428163493]
INFO     
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:912 Submitted job: 
2023-05-19_09_38_52-12886453873428163493
INFO     
apache_beam.runners.dataflow.internal.apiclient:apiclient.py:913 To access the 
Dataflow monitoring console, please navigate to 
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INFO     
apache_beam.runners.dataflow.test_dataflow_runner:test_dataflow_runner.py:58 
Console log: 
INFO     
apache_beam.runners.dataflow.test_dataflow_runner:test_dataflow_runner.py:59 
https://console.cloud.google.com/dataflow/jobs/us-central1/2023-05-19_09_38_52-12886453873428163493?project=apache-beam-testing
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:193 Job 
2023-05-19_09_38_52-12886453873428163493 is in state JOB_STATE_RUNNING
INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:38:53.997Z: JOB_MESSAGE_WARNING: Autoscaling is enabled for 
Dataflow Streaming Engine. Workers will scale between 1 and 100 unless 
maxNumWorkers is specified.
INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:38:54.111Z: JOB_MESSAGE_DETAILED: Autoscaling is enabled for job 
2023-05-19_09_38_52-12886453873428163493. The number of workers will be between 
1 and 100.
INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:38:54.143Z: JOB_MESSAGE_DETAILED: Autoscaling was automatically 
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:38:58.606Z: JOB_MESSAGE_BASIC: Worker configuration: 
e2-standard-2 in us-central1-c.
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:00.993Z: JOB_MESSAGE_DETAILED: Expanding SplittableParDo 
operations into optimizable parts.
INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.011Z: JOB_MESSAGE_DETAILED: Expanding CollectionToSingleton 
operations into optimizable parts.
INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.074Z: JOB_MESSAGE_DETAILED: Expanding CoGroupByKey 
operations into optimizable parts.
INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.113Z: JOB_MESSAGE_DETAILED: Expanding 
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INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.140Z: JOB_MESSAGE_DETAILED: Expanding GroupByKey operations 
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INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.176Z: JOB_MESSAGE_DETAILED: Lifting 
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INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.195Z: JOB_MESSAGE_DEBUG: Annotating graph with Autotuner 
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.234Z: JOB_MESSAGE_DETAILED: Fusing adjacent ParDo, Read, 
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INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.261Z: JOB_MESSAGE_DETAILED: Fusing consumer 
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INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.294Z: JOB_MESSAGE_DETAILED: Fusing consumer 
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INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.325Z: JOB_MESSAGE_DETAILED: Fusing consumer 
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2023-05-19T16:39:01.354Z: JOB_MESSAGE_BASIC: Running job using Streaming Engine
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.371Z: JOB_MESSAGE_BASIC: Using cloud KMLS key to protect 
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.465Z: JOB_MESSAGE_DEBUG: Workflow config is missing a 
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.488Z: JOB_MESSAGE_DEBUG: Adding StepResource setup and 
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.516Z: JOB_MESSAGE_DEBUG: Adding workflow start and stop 
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.548Z: JOB_MESSAGE_DEBUG: Assigning stage ids.
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.729Z: JOB_MESSAGE_DEBUG: Starting worker pool setup.
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.760Z: JOB_MESSAGE_DEBUG: Starting worker pool setup.
INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:01.792Z: JOB_MESSAGE_BASIC: Starting 1 workers in 
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INFO     
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:25.656Z: JOB_MESSAGE_BASIC: Your project already contains 100 
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on the custom metrics, you can delete old / unused metric descriptors. See 
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 and 
https://developers.google.com/apis-explorer/#p/monitoring/v3/monitoring.projects.metricDescriptors.delete
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:39:42.930Z: JOB_MESSAGE_DETAILED: Autoscaling: Raised the number 
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:40:13.052Z: JOB_MESSAGE_DETAILED: Workers have started 
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apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:238 
2023-05-19T16:42:52.794Z: JOB_MESSAGE_WARNING: The workers of given job are 
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WARNING  
apache_beam.runners.dataflow.dataflow_runner:dataflow_runner.py:249 Timing out 
on waiting for job 2023-05-19_09_38_52-12886453873428163493 after 303 seconds
=============================== warnings summary 
===============================
../../build/gradleenv/2050596099/lib/python3.11/site-packages/hdfs/config.py:15
  
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow_V2/ws/src/build/gradleenv/2050596099/lib/python3.11/site-packages/hdfs/config.py>:15:
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slated for removal in Python 3.12; see the module's documentation for 
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../../build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py:121
  
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 DeprecationWarning: pkg_resources is deprecated as an API
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../../build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py:2870:
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 DeprecationWarning: Deprecated call to 
`pkg_resources.declare_namespace('google')`.
  Implementing implicit namespace packages (as specified in PEP 420) is 
preferred to `pkg_resources.declare_namespace`. See 
https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
    declare_namespace(pkg)

../../build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py:2870:
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<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow_V2/ws/src/build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py>:2870:
 DeprecationWarning: Deprecated call to 
`pkg_resources.declare_namespace('google.cloud')`.
  Implementing implicit namespace packages (as specified in PEP 420) is 
preferred to `pkg_resources.declare_namespace`. See 
https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
    declare_namespace(pkg)

../../build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py:2349
../../build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py:2349
../../build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py:2349
../../build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py:2349
  
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow_V2/ws/src/build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py>:2349:
 DeprecationWarning: Deprecated call to 
`pkg_resources.declare_namespace('google')`.
  Implementing implicit namespace packages (as specified in PEP 420) is 
preferred to `pkg_resources.declare_namespace`. See 
https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
    declare_namespace(parent)

../../build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py:2870
  
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 DeprecationWarning: Deprecated call to 
`pkg_resources.declare_namespace('google.logging')`.
  Implementing implicit namespace packages (as specified in PEP 420) is 
preferred to `pkg_resources.declare_namespace`. See 
https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
    declare_namespace(pkg)

../../build/gradleenv/2050596099/lib/python3.11/site-packages/pkg_resources/__init__.py:2870
  
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 DeprecationWarning: Deprecated call to 
`pkg_resources.declare_namespace('google.iam')`.
  Implementing implicit namespace packages (as specified in PEP 420) is 
preferred to `pkg_resources.declare_namespace`. See 
https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
    declare_namespace(pkg)

../../build/gradleenv/2050596099/lib/python3.11/site-packages/google/rpc/__init__.py:20
  
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow_V2/ws/src/build/gradleenv/2050596099/lib/python3.11/site-packages/google/rpc/__init__.py>:20:
 DeprecationWarning: Deprecated call to 
`pkg_resources.declare_namespace('google.rpc')`.
  Implementing implicit namespace packages (as specified in PEP 420) is 
preferred to `pkg_resources.declare_namespace`. See 
https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
    pkg_resources.declare_namespace(__name__)

../../build/gradleenv/2050596099/lib/python3.11/site-packages/google/api_core/operations_v1/abstract_operations_client.py:17
  
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow_V2/ws/src/build/gradleenv/2050596099/lib/python3.11/site-packages/google/api_core/operations_v1/abstract_operations_client.py>:17:
 DeprecationWarning: The distutils package is deprecated and slated for removal 
in Python 3.12. Use setuptools or check PEP 632 for potential alternatives
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apache_beam/typehints/pandas_type_compatibility_test.py:67
  
<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow_V2/ws/src/sdks/python/apache_beam/typehints/pandas_type_compatibility_test.py>:67:
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in a future version. Use pandas.Index with the appropriate dtype instead.
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apache_beam/typehints/pandas_type_compatibility_test.py:90
  
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in a future version. Use pandas.Index with the appropriate dtype instead.
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apache_beam/typehints/pandas_type_compatibility_test.py:91
  
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in a future version. Use pandas.Index with the appropriate dtype instead.
    pd.Int64Index(range(475, 575), name='another_index'),

-- 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_V2/ws/src/sdks/python/pytest_validatesRunnerStreamingTests-df-py311-noxdist.xml>
 -
=========================== short test summary info 
============================
FAILED 
apache_beam/runners/dataflow/dataflow_exercise_streaming_metrics_pipeline_test.py::ExerciseStreamingMetricsPipelineTest::test_streaming_pipeline_returns_expected_user_metrics_fnapi_it
 - AssertionError: "Unable to match metrics for matcher  name: 'ElementCount' 
(label_key: 'output_user_name' label_value: 'generate_metrics-out0').  
(label_key: 'original_name' label_value: 'generate_metrics-out0-ElementCount'). 
 attempted: <3> committed: <3>Unable to match metrics for matcher  namespace: 
'apache_beam.runners.dataflow.dataflow_exercise_streaming_metrics_pipeline.StreamingUserMetricsDoFn'
 name: 'double_msg_counter_name' step: 'generate_metrics' attempted: <6> 
committed: <6>Unable to match metrics for matcher  namespace: 
'apache_beam.runners.dataflow.dataflow_exercise_streaming_metrics_pipeline.StreamingUserMetricsDoFn'
 name: 'msg_len_dist_metric_name' step: 'generate_metrics' attempted:  
sum_value: <29> count_value: <3> min_value: <9> max_value: <11> committed:  
sum_value: <29> count_value: <3> min_value: <9> max_value: <11>\nActual 
MetricResults:\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=TotalVcpuTime), 
labels={'original_name': 'Service-cpu_num_seconds'}), committed=556, 
attempted=556)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=TotalMemoryUsage), 
labels={'original_name': 'Service-mem_mb_seconds'}), committed=2278490, 
attempted=2278490)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=TotalPdUsage), 
labels={'original_name': 'Service-pd_gb_seconds'}), committed=8344, 
attempted=8344)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=TotalSsdUsage), 
labels={'original_name': 'Service-pd_ssd_gb_seconds'}), committed=0, 
attempted=0)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=TotalShuffleDataProcessed), 
labels={'original_name': 'Service-shuffle_service_actual_gb'}), committed=0, 
attempted=0)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=BillableShuffleDataProcessed), 
labels={'original_name': 'Service-shuffle_service_chargeable_gb'}), 
committed=0, attempted=0)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=TotalStreamingDataProcessed), 
labels={'original_name': 'Service-streaming_service_gb'}), committed=None, 
attempted=None)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=TotalGpuTime), 
labels={'original_name': 'Service-gpu_num_seconds'}), committed=0, 
attempted=0)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=BacklogBytes), 
labels={'original_name': 'dataflow_backlog_size-F0', 'execution_step': 'F0'}), 
committed=0, attempted=0)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=SystemWatermark), 
labels={'execution_step': 'F0'}), committed=None, 
attempted=None)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=CurrentVcpuCount), 
labels={'original_name': 'Service-cpu_num'}), committed=2, 
attempted=2)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=CurrentMemoryUsage), 
labels={'original_name': 'Service-mem_mb'}), committed=8192, 
attempted=8192)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=CurrentPdUsage), 
labels={'original_name': 'Service-pd_gb'}), committed=30, 
attempted=30)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=CurrentSsdUsage), 
labels={'original_name': 'Service-pd_ssd_gb'}), committed=0, 
attempted=0)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=CurrentGpuCount), 
labels={'original_name': 'Service-gpu_num'}), committed=0, 
attempted=0)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=DataWatermark), 
labels={'execution_step': 'F0'}), committed=None, 
attempted=None)\nMetricResult(key=MetricKey(step=, 
metric=MetricName(namespace=dataflow/v1b3, name=SystemLag), 
labels={'execution_step': 'F0'}), committed=1616790, attempted=1616790)" is not 
false : Unable to match metrics for matcher  name: 'ElementCount' (label_key: 
'output_user_name' label_value: 'generate_metrics-out0').  (label_key: 
'original_name' label_value: 'generate_metrics-out0-ElementCount').  attempted: 
<3> committed: <3>Unable to match metrics for matcher  namespace: 
'apache_beam.runners.dataflow.dataflow_exercise_streaming_metrics_pipeline.StreamingUserMetricsDoFn'
 name: 'double_msg_counter_name' step: 'generate_metrics' attempted: <6> 
committed: <6>Unable to match metrics for matcher  namespace: 
'apache_beam.runners.dataflow.dataflow_exercise_streaming_metrics_pipeline.StreamingUserMetricsDoFn'
 name: 'msg_len_dist_metric_name' step: 'generate_metrics' attempted:  
sum_value: <29> count_value: <3> min_value: <9> max_value: <11> committed:  
sum_value: <29> count_value: <3> min_value: <9> max_value: <11>
Actual MetricResults:
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=TotalVcpuTime), labels={'original_name': 'Service-cpu_num_seconds'}), 
committed=556, attempted=556)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=TotalMemoryUsage), labels={'original_name': 'Service-mem_mb_seconds'}), 
committed=2278490, attempted=2278490)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=TotalPdUsage), labels={'original_name': 'Service-pd_gb_seconds'}), 
committed=8344, attempted=8344)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=TotalSsdUsage), labels={'original_name': 'Service-pd_ssd_gb_seconds'}), 
committed=0, attempted=0)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=TotalShuffleDataProcessed), labels={'original_name': 
'Service-shuffle_service_actual_gb'}), committed=0, attempted=0)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=BillableShuffleDataProcessed), labels={'original_name': 
'Service-shuffle_service_chargeable_gb'}), committed=0, attempted=0)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=TotalStreamingDataProcessed), labels={'original_name': 
'Service-streaming_service_gb'}), committed=None, attempted=None)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=TotalGpuTime), labels={'original_name': 'Service-gpu_num_seconds'}), 
committed=0, attempted=0)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=BacklogBytes), labels={'original_name': 'dataflow_backlog_size-F0', 
'execution_step': 'F0'}), committed=0, attempted=0)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=SystemWatermark), labels={'execution_step': 'F0'}), committed=None, 
attempted=None)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=CurrentVcpuCount), labels={'original_name': 'Service-cpu_num'}), 
committed=2, attempted=2)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=CurrentMemoryUsage), labels={'original_name': 'Service-mem_mb'}), 
committed=8192, attempted=8192)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=CurrentPdUsage), labels={'original_name': 'Service-pd_gb'}), committed=30, 
attempted=30)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=CurrentSsdUsage), labels={'original_name': 'Service-pd_ssd_gb'}), 
committed=0, attempted=0)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=CurrentGpuCount), labels={'original_name': 'Service-gpu_num'}), 
committed=0, attempted=0)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=DataWatermark), labels={'execution_step': 'F0'}), committed=None, 
attempted=None)
MetricResult(key=MetricKey(step=, metric=MetricName(namespace=dataflow/v1b3, 
name=SystemLag), labels={'execution_step': 'F0'}), committed=1616790, 
attempted=1616790)
==== 1 failed, 9 skipped, 6922 deselected, 
44 warnings in 676.30s (0:11:16) ====

> Task :sdks:python:test-suites:dataflow:py311:validatesRunnerStreamingTests 
> FAILED

FAILURE: Build failed with an exception.

* Where:
Script 
'<https://ci-beam.apache.org/job/beam_PostCommit_Py_VR_Dataflow_V2/ws/src/sdks/python/test-suites/dataflow/common.gradle'>
 line: 283

* What went wrong:
Execution failed for task 
':sdks:python:test-suites:dataflow:py311: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.

* 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 1h 40m
24 actionable tasks: 18 executed, 4 from cache, 2 up-to-date

Publishing build scan...
https://ge.apache.org/s/67njzdzjn2jjm

Build step 'Invoke Gradle script' changed build result to FAILURE
Build step 'Invoke Gradle script' marked build as failure


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