[jira] [Work logged] (BEAM-7825) Python's DirectRunner emits multiple panes per window and does not discard late data

["ASF GitHub Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/BEAM-7825?focusedWorklogId=323991&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-323991 ]

ASF GitHub Bot logged work on BEAM-7825:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 05/Oct/19 23:14
            Start Date: 05/Oct/19 23:14
    Worklog Time Spent: 10m 
      Work Description: stale[bot] commented on issue #9164: [BEAM-7825] Add test showing inconsistent stream processing with DirectRunner
URL: https://github.com/apache/beam/pull/9164#issuecomment-538696939
 
 
   This pull request has been marked as stale due to 60 days of inactivity. It will be closed in 1 week if no further activity occurs. If you think that’s incorrect or this pull request requires a review, please simply write any comment. If closed, you can revive the PR at any time and @mention a reviewer or discuss it on the dev@beam.apache.org list. Thank you for your contributions.
   
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 323991)
    Time Spent: 4.5h  (was: 4h 20m)

> Python's DirectRunner emits multiple panes per window and does not discard late data
> ------------------------------------------------------------------------------------
>
>                 Key: BEAM-7825
>                 URL: https://issues.apache.org/jira/browse/BEAM-7825
>             Project: Beam
>          Issue Type: Bug
>          Components: sdk-py-core
>    Affects Versions: 2.13.0
>         Environment: OS: Debian rodete.
> Beam versions: 2.15.0.dev.
> Python versions: Python 2.7, Python 3.7
>            Reporter: Alexey Strokach
>            Priority: Major
>          Time Spent: 4.5h
>  Remaining Estimate: 0h
>
> The documentation for Beam's Windowing and Triggers functionality [states that|https://beam.apache.org/documentation/programming-guide/#triggers] _"if you use Beam’s default windowing configuration and default trigger, Beam outputs the aggregated result when it estimates all data has arrived, and discards all subsequent data for that window"_. However, it seems that the current behavior of Python's DirectRunner is inconsistent with both of those points. As the {{StreamingWordGroupIT.test_discard_late_data}} test shows, DirectRunner appears to process every data point that it reads from the input stream, irrespective of whether or not the timestamp of that data point is older than the timestamps of the windows that have already been processed. Furthermore, as the {{StreamingWordGroupIT.test_single_output_per_window}} test shows, DirectRunner generates multiple "panes" for the same window, apparently disregarding the notion of a watermark?
> The Dataflow runner passes both of those end-to-end tests.



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