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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (BEAM-625) Make Dataflow Python Materialized PCollection representation more efficient
Date Tue, 20 Sep 2016 00:25:21 GMT

    [ https://issues.apache.org/jira/browse/BEAM-625?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15505137#comment-15505137
] 

ASF GitHub Bot commented on BEAM-625:
-------------------------------------

GitHub user katsiapis opened a pull request:

    https://github.com/apache/incubator-beam/pull/976

    [BEAM-625] Making Dataflow Python Materialized PCollection representation more efficient
(5 of several).

    Changing ToStringCoder to BytesCoder since the former can't be used with sources (it can
only be used with Sinks). Since we are opening files as 'rb', using BytesCoder makes sense.

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

    $ git pull https://github.com/katsiapis/incubator-beam python-sdk

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

    https://github.com/apache/incubator-beam/pull/976.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 #976
    
----
commit 1b97de04987231227f6612d3f8c57b1eaf76408b
Author: Gus Katsiapis <katsiapis@katsiapis-linux.mtv.corp.google.com>
Date:   2016-09-20T00:21:45Z

    Changint ToStringCoder to BytesCoder since the former can't be used with
    sources.

----


> Make Dataflow Python Materialized PCollection representation more efficient
> ---------------------------------------------------------------------------
>
>                 Key: BEAM-625
>                 URL: https://issues.apache.org/jira/browse/BEAM-625
>             Project: Beam
>          Issue Type: Improvement
>          Components: sdk-py
>            Reporter: Konstantinos Katsiapis
>            Assignee: Frances Perry
>
> This will be a several step process which will involve adding better support for compression
as well as Avro.



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