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https://issues.apache.org/jira/browse/BEAM-9085?focusedWorklogId=405070&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-405070
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ASF GitHub Bot logged work on BEAM-9085:
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Author: ASF GitHub Bot
Created on: 18/Mar/20 00:28
Start Date: 18/Mar/20 00:28
Worklog Time Spent: 10m
Work Description: tvalentyn commented on issue #11092: [BEAM-9085] Fix
performance regression in SyntheticSource
URL: https://github.com/apache/beam/pull/11092#issuecomment-600364689
Yes, I agree; we should be migrating the tests to Python 3. I think we'll
pick the option that works well on Py3 and move or branch the generation on Py2
vs Py3, if we don't find one-fit-all solution. Afterall, the input generation
should not be the slowest part of the pipeline.
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Issue Time Tracking
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Worklog Id: (was: 405070)
Time Spent: 6h 10m (was: 6h)
> Performance regression in np.random.RandomState() skews performance test
> results across Python 2/3 on Dataflow
> --------------------------------------------------------------------------------------------------------------
>
> Key: BEAM-9085
> URL: https://issues.apache.org/jira/browse/BEAM-9085
> Project: Beam
> Issue Type: Bug
> Components: testing
> Reporter: Kamil Wasilewski
> Assignee: Kamil Wasilewski
> Priority: Major
> Time Spent: 6h 10m
> Remaining Estimate: 0h
>
> Tests show that the performance of core Beam operations in Python 3.x on
> Dataflow can be a few time slower than in Python 2.7. We should investigate
> what's the cause of the problem.
> Currently, we have one ParDo test that is run both in Py3 and Py2 [1]. A
> dashboard with runtime results can be found here [2].
> [1] sdks/python/apache_beam/testing/load_tests/pardo_test.py
> [2] https://apache-beam-testing.appspot.com/explore?dashboard=5678187241537536
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