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ASF GitHub Bot logged work on BEAM-9085:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 10/Mar/20 16:24
            Start Date: 10/Mar/20 16:24
    Worklog Time Spent: 10m 
      Work Description: kamilwu commented on issue #11092: [BEAM-9085] Fix 
performance regression in SyntheticSource
URL: https://github.com/apache/beam/pull/11092#issuecomment-597180032
 
 
   R: @tvalentyn 
   
   I did many tests and gathered the results in one single document: 
https://docs.google.com/document/d/1AegjUCc5w4B90_rvR8WAfIeL65PHUi4oGYkodgPS0o0/edit?usp=sharing.
 The previous solution (https://github.com/apache/beam/pull/10885) didn't work 
very well on big `element_size`, which was most probably the cause of failures 
and slowdowns.
   
   Although this PR is still a bit slower than we have now using numpy 1.16 and 
Python 2.7, I'd rather avoid downgrading numpy via supplying an additional 
requirements.txt file to a Dataflow job. According to this document 
(https://numpy.org/neps/nep-0029-deprecation_policy.html), the support for 
numpy 1.16 will be dropped on Jan 13, 2021 - and this looks like a temporary 
solution.
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 400818)
    Time Spent: 4h  (was: 3h 50m)

> 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: 4h
>  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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