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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2019/10/04 11:26:00 UTC

[jira] [Work logged] (BEAM-5707) Add a portable Flink streaming synthetic source for testing

     [ https://issues.apache.org/jira/browse/BEAM-5707?focusedWorklogId=323338&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-323338 ]

ASF GitHub Bot logged work on BEAM-5707:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 04/Oct/19 11:25
            Start Date: 04/Oct/19 11:25
    Worklog Time Spent: 10m 
      Work Description: mxm commented on pull request #9728: [BEAM-5707] Modify Flink streaming impulse function to include a counter
URL: https://github.com/apache/beam/pull/9728
 
 
   Flink's streaming impulse function is used for load tests which used to be
   impossible to realize with timers. This extends the functionality to send a
   per-partition counter with the impulse, instead of just an empty byte array.
   
   I've also filed https://jira.apache.org/jira/browse/BEAM-8353 to start the
   process of removing the proprietary source.
   
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 323338)
    Time Spent: 7h 50m  (was: 7h 40m)

> Add a portable Flink streaming synthetic source for testing
> -----------------------------------------------------------
>
>                 Key: BEAM-5707
>                 URL: https://issues.apache.org/jira/browse/BEAM-5707
>             Project: Beam
>          Issue Type: Improvement
>          Components: runner-flink
>            Reporter: Micah Wylde
>            Assignee: Micah Wylde
>            Priority: Minor
>             Fix For: 2.9.0
>
>          Time Spent: 7h 50m
>  Remaining Estimate: 0h
>
> Currently there are no built-in streaming sources for portable pipelines. This makes it hard to test streaming functionality in the Python SDK.
> It would be very useful to add a periodic impulse source that (with some configurable frequency) outputs an empty byte array, which can then be transformed as desired inside the python pipeline. More context in this [mailing list discussion|https://lists.apache.org/thread.html/b44a648ab1d0cb200d8bfe4b280e9dad6368209c4725609cbfbbe410@%3Cdev.beam.apache.org%3E].



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