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https://issues.apache.org/jira/browse/BEAM-53?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15287905#comment-15287905
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ASF GitHub Bot commented on BEAM-53:
------------------------------------

GitHub user mshields822 opened a pull request:

    https://github.com/apache/incubator-beam/pull/346

    [BEAM-53] Wire PubsubUnbounded{Source,Sink} into PubsubIO

    This also refines the handling of record ids in the sink to be 
random-but-reused-on-failure, using the same trick as we do for the BigQuery 
sink.
    
    Still need to re-do the load tests I did a few weeks back with the actual 
change.
    Note that last time I tested the DataflowPipelineTranslator does not kick 
in and replace the new transforms with the correct native transforms. Need to 
dig deeper.
    
    R: @dhalperi 

You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/mshields822/incubator-beam pubsub-runner

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/incubator-beam/pull/346.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #346
    
----
commit ce655a6a7480147f7527fa23818e1d546abaa599
Author: Mark Shields <markshie...@google.com>
Date:   2016-04-12T00:36:27Z

    Make java unbounded pub/sub source the default.

commit aafcf5f9d0286ec5a6ed0d634df8ff0902897cdc
Author: Mark Shields <markshie...@google.com>
Date:   2016-05-17T23:44:30Z

    Refine record id calculation. Prepare for supporting unit tests with 
re-using record ids.

----


> PubSubIO: reimplement in Java
> -----------------------------
>
>                 Key: BEAM-53
>                 URL: https://issues.apache.org/jira/browse/BEAM-53
>             Project: Beam
>          Issue Type: New Feature
>          Components: runner-core
>            Reporter: Daniel Halperin
>            Assignee: Mark Shields
>
> PubSubIO is currently only partially implemented in Java: the 
> DirectPipelineRunner uses a non-scalable API in a single-threaded manner.
> In contrast, the DataflowPipelineRunner uses an entirely different code path 
> implemented in the Google Cloud Dataflow service.
> We need to reimplement PubSubIO in Java in order to support other runners in 
> a scalable way.
> Additionally, we can take this opportunity to add new features:
> * getting timestamp from an arbitrary lambda in arbitrary formats rather than 
> from a message attribute in only 2 formats.
> * exposing metadata and attributes in the elements produced by PubSubIO.Read
> * setting metadata and attributes in the messages written by PubSubIO.Write



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