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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (PHOENIX-1071) Provide integration for exposing Phoenix tables as Spark RDDs
Date Wed, 08 Apr 2015 16:00:16 GMT

    [ https://issues.apache.org/jira/browse/PHOENIX-1071?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14485434#comment-14485434
] 

ASF GitHub Bot commented on PHOENIX-1071:
-----------------------------------------

GitHub user jmahonin opened a pull request:

    https://github.com/apache/phoenix/pull/65

    PHOENIX-1071 Get the phoenix-spark integration tests running.

    Uses the BaseHBaseManagedTimeIT framework now for creating the
    test cluster and setup/teardown.
    
    Tested with Java 7u75 i386 on Ubuntu, and 7u40 x64 on OS X.

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

    $ git pull https://github.com/FileTrek/phoenix PHOENIX-1071

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

    https://github.com/apache/phoenix/pull/65.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 #65
    
----
commit a4f40723048d84cd865d425393de29d00e98919a
Author: Josh Mahonin <jmahonin@gmail.com>
Date:   2015-04-08T02:33:17Z

    PHOENIX-1071 Get the phoenix-spark integration tests running.
    
    Uses the BaseHBaseManagedTimeIT framework now for creating the
    test cluster and setup/teardown.
    
    Tested with Java 7u75 i386 on Ubuntu, and 7u40 x64 on OS X.

----


> Provide integration for exposing Phoenix tables as Spark RDDs
> -------------------------------------------------------------
>
>                 Key: PHOENIX-1071
>                 URL: https://issues.apache.org/jira/browse/PHOENIX-1071
>             Project: Phoenix
>          Issue Type: New Feature
>            Reporter: Andrew Purtell
>            Assignee: Josh Mahonin
>
> A core concept of Apache Spark is the resilient distributed dataset (RDD), a "fault-tolerant
collection of elements that can be operated on in parallel". One can create a RDDs referencing
a dataset in any external storage system offering a Hadoop InputFormat, like PhoenixInputFormat
and PhoenixOutputFormat. There could be opportunities for additional interesting and deep
integration. 
> Add the ability to save RDDs back to Phoenix with a {{saveAsPhoenixTable}} action, implicitly
creating necessary schema on demand.
> Add support for {{filter}} transformations that push predicates to the server.
> Add a new {{select}} transformation supporting a LINQ-like DSL, for example:
> {code}
> // Count the number of different coffee varieties offered by each
> // supplier from Guatemala
> phoenixTable("coffees")
>     .select(c =>
>         where(c.origin == "GT"))
>     .countByKey()
>     .foreach(r => println(r._1 + "=" + r._2))
> {code} 
> Support conversions between Scala and Java types and Phoenix table data.



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