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https://issues.apache.org/jira/browse/BEAM-11666?focusedWorklogId=634683&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-634683
]
ASF GitHub Bot logged work on BEAM-11666:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 05/Aug/21 17:23
Start Date: 05/Aug/21 17:23
Worklog Time Spent: 10m
Work Description: KevinGG commented on pull request #15118:
URL: https://github.com/apache/beam/pull/15118#issuecomment-893646115
> What's the next step on this PR? @ihji or @KevinGG
The change seems to fix the flakiness by avoiding the flaky execution route.
I think we need @rohdesamuel 's input to figure out the fix of the root
cause. If it's caused by multi-threading racing, can we refactor the test?
If the flakiness occurs frequently, we can add a TODO in the fix, lower the
priority of the ticket, and merge this PR as a temporary work-around.
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Issue Time Tracking
-------------------
Worklog Id: (was: 634683)
Time Spent: 1h 40m (was: 1.5h)
> apache_beam.runners.interactive.recording_manager_test.RecordingManagerTest.test_basic_execution
> is flaky
> ---------------------------------------------------------------------------------------------------------
>
> Key: BEAM-11666
> URL: https://issues.apache.org/jira/browse/BEAM-11666
> Project: Beam
> Issue Type: Bug
> Components: test-failures
> Reporter: Valentyn Tymofieiev
> Assignee: Irwin Alejandro Rodirguez Ramirez
> Priority: P1
> Labels: flake
> Time Spent: 1h 40m
> Remaining Estimate: 0h
>
> Happened in: https://ci-beam.apache.org/job/beam_PreCommit_Python_Commit/16819
> {noformat}
> self =
> <apache_beam.runners.interactive.recording_manager_test.RecordingManagerTest
> testMethod=test_basic_execution>
> @unittest.skipIf(
> sys.version_info < (3, 6, 0),
> 'This test requires at least Python 3.6 to work.')
> def test_basic_execution(self):
> """A basic pipeline to be used as a smoke test."""
>
> # Create the pipeline that will emit 0, 1, 2.
> p = beam.Pipeline(InteractiveRunner())
> numbers = p | 'numbers' >> beam.Create([0, 1, 2])
> letters = p | 'letters' >> beam.Create(['a', 'b', 'c'])
>
> # Watch the pipeline and PCollections. This is normally done in a
> notebook
> # environment automatically, but we have to do it manually here.
> ib.watch(locals())
> ie.current_env().track_user_pipelines()
>
> # Create the recording objects. By calling `record` a new
> PipelineFragment
> # is started to compute the given PCollections and cache to disk.
> rm = RecordingManager(p)
> > numbers_recording = rm.record([numbers], max_n=3, max_duration=500)
> apache_beam/runners/interactive/recording_manager_test.py:331:
> _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> _
> apache_beam/runners/interactive/recording_manager.py:435: in record
> self._clear(pipeline_instrument)
> apache_beam/runners/interactive/recording_manager.py:319: in _clear
> self._clear_pcolls(cache_manager, set(to_clear))
> apache_beam/runners/interactive/recording_manager.py:323: in _clear_pcolls
> cache_manager.clear('full', pc)
> _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> _
> self =
> <apache_beam.runners.interactive.testing.test_cache_manager.InMemoryCache
> object at 0x7fa3903ac208>
> labels = ('full',
> 'ee5c35ce3d-140340882711664-140340882712560-140340476166608')
> def clear(self, *labels):
> # type (*str) -> Boolean
>
> """Clears the cache entry of the given labels and returns True on
> success.
>
> Args:
> value: An encodable (with corresponding PCoder) value
> *labels: List of labels for PCollection instance
> """
> > raise NotImplementedError
> E NotImplementedError
> {noformat}
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