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Posted to issues@ignite.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2017/09/25 16:35:00 UTC

[jira] [Commented] (IGNITE-3084) Spark Data Frames Support in Apache Ignite

    [ https://issues.apache.org/jira/browse/IGNITE-3084?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16179277#comment-16179277 ] 

ASF GitHub Bot commented on IGNITE-3084:
----------------------------------------

GitHub user nizhikov opened a pull request:

    https://github.com/apache/ignite/pull/2742

    IGNITE-3084: Prototype of Ignite DataFrame support. 

    * DataSource and DataFrame implementation for Ignite SQL Tables.
    * IgniteCatalog implementation. 
    * Some examples provided. 
    * There is only placeholer for an Ignite extra optimization and strategies.

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

    $ git pull https://github.com/nizhikov/ignite IGNITE-3084

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

    https://github.com/apache/ignite/pull/2742.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 #2742
    
----
commit f54c51e863665b170a6c59d6c57a9dd52caf3a13
Author: Nikolay Izhikov <ni...@gmail.com>
Date:   2017-09-05T14:02:46Z

    IGNITE-3084: Prototype of Ignite DataFrame support. IgniteCatalog implementation. Some examples provided. There is only placeholer for an Ignite extra optimization and strategies.

----


> Spark Data Frames Support in Apache Ignite
> ------------------------------------------
>
>                 Key: IGNITE-3084
>                 URL: https://issues.apache.org/jira/browse/IGNITE-3084
>             Project: Ignite
>          Issue Type: Task
>          Components: spark
>    Affects Versions: 1.5.0.final
>            Reporter: Vladimir Ozerov
>            Assignee: Nikolay Izhikov
>              Labels: bigdata
>
> Apache Spark already benefits from integration with Apache Ignite. The latter provides shared RDDs, an implementation of Spark RDD, that help Spark to share a state between Spark workers and execute SQL queries much faster. The next logical step is to enable support for modern Spark Data Frames API in a similar way.
> As a contributor, you will be fully in charge of the integration of Spark Data Frame API and Apache Ignite.



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