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https://issues.apache.org/jira/browse/BEAM-9822?focusedWorklogId=428613&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-428613
 ]

ASF GitHub Bot logged work on BEAM-9822:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 29/Apr/20 15:20
            Start Date: 29/Apr/20 15:20
    Worklog Time Spent: 10m 
      Work Description: nielm opened a new pull request #11570:
URL: https://github.com/apache/beam/pull/11570


   
   There is minimal benefit in separating these 2 stages, and significant
   benefity in merging them: Gather and Sort encodes incoming
   MutationGroups into a List<byte[]> which would contain up to 1GB.
   This is then output (copied) to the CreateBatches where it is decoded
   back into MutationGroups.
   
   Removing this encode/decode should save up to 2GB of RAM.
   
   Note, this PR is dependent on PR #11528,  PR #11532 and PR #11529
   
   Post-Commit Tests Status (on master branch)
   
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   XLang | --- | --- | --- | [![Build 
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   Pre-Commit Tests Status (on master branch)
   
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   --- |Java | Python | Go | Website
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   Non-portable | [![Build 
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   Portable | --- | [![Build 
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   See 
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 for trigger phrase, status and link of all Jenkins jobs.
   


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Issue Time Tracking
-------------------

    Worklog Id:     (was: 428613)
    Time Spent: 0.5h  (was: 20m)

> SpannerIO: Reduce memory usage - especially when streaming
> ----------------------------------------------------------
>
>                 Key: BEAM-9822
>                 URL: https://issues.apache.org/jira/browse/BEAM-9822
>             Project: Beam
>          Issue Type: Bug
>          Components: io-java-gcp
>    Affects Versions: 2.20.0
>            Reporter: Niel Markwick
>            Priority: Major
>              Labels: google-cloud-spanner
>             Fix For: 2.21.0
>
>          Time Spent: 0.5h
>  Remaining Estimate: 0h
>
> SpannerIO uses a lot of memory. 
> In Streaming Dataflow, it uses many times as much (because dataflow creates 
> many worker threads)
> Lower the memory use, and change default parameters during streaming to use 
> smaller batches and disable grouping.



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