[jira] [Commented] (BEAM-15) Applying windowing to cached RDDs fails

["ASF GitHub Bot (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/BEAM-15?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15443503#comment-15443503 ] 

ASF GitHub Bot commented on BEAM-15:
------------------------------------

GitHub user staslev opened a pull request:

    https://github.com/apache/incubator-beam/pull/901

    [BEAM-15] Fixed StorageLevel inconsistency between DStream and RDD

    Be sure to do all of the following to help us incorporate your contribution
    quickly and easily:
    
     - [ ] Make sure the PR title is formatted like:
       `[BEAM-<Jira issue #>] Description of pull request`
     - [ ] Make sure tests pass via `mvn clean verify`. (Even better, enable
           Travis-CI on your fork and ensure the whole test matrix passes).
     - [ ] Replace `<Jira issue #>` in the title with the actual Jira issue
           number, if there is one.
     - [ ] If this contribution is large, please file an Apache
           [Individual Contributor License Agreement](https://www.apache.org/licenses/icla.txt).
    
    ---
    
    R: @amitsela 

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

    $ git pull https://github.com/staslev/incubator-beam BEAM-15-fix-incompatible-StorageLevel

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

    https://github.com/apache/incubator-beam/pull/901.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 #901
    
----
commit ddbba4348f21dd6868a53014b882d5b85781790e
Author: Stas Levin <st...@gmail.com>
Date:   2016-08-28T13:09:42Z

    Fixed StorageLevel inconsistency between DStream and RDD persist methods.

----


> Applying windowing to cached RDDs fails
> ---------------------------------------
>
>                 Key: BEAM-15
>                 URL: https://issues.apache.org/jira/browse/BEAM-15
>             Project: Beam
>          Issue Type: Bug
>          Components: runner-spark
>            Reporter: Amit Sela
>            Assignee: Amit Sela
>
> The Spark runner caches RDDs that are accessed more than once. If applying window operations to a cached RDD, it will fail because windowed RDDs will try to cache with a different cache level - windowing cache level is StorageLevel.MEMORY_ONLY_SER and RDD cache level is StorageLevel.MEMORY_ONLY.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)