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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 <[email protected]>
Date: 2016-04-12T00:36:27Z
Make java unbounded pub/sub source the default.
commit aafcf5f9d0286ec5a6ed0d634df8ff0902897cdc
Author: Mark Shields <[email protected]>
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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