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From "Polina Koleva (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (IGNITE-3084) Spark Data Frames Support in Apache Ignite
Date Sun, 19 Mar 2017 17:34:41 GMT

    [ https://issues.apache.org/jira/browse/IGNITE-3084?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15931844#comment-15931844
] 

Polina Koleva edited comment on IGNITE-3084 at 3/19/17 5:33 PM:
----------------------------------------------------------------

HI,
I am Polina, master student, 2nd year at University of Freiburg, Germany. I wish to participate
in gsoc 2017 and I find this Jira Task interesting. I have already worked on a master project
with Spark (mainly Spark SQL), Hadoop and Hive. Moreover, I have been working as a part-time
Java developer since 2013. Unfortunately, I do not have any experience working with Ignite.
Can you provide any advice or a good starting point to understand more about this issue?


was (Author: polinank):
HI,
I am Polina, master student, 2nd year at University of Freiburg, Germany. I wish to participate
in gsoc 2017 and I find this Jira Task interesting. I have already worked on a master project
with Spark, Hadoop and Hive. Moreover, I have been working as a part-time Java developer since
2013. Unfortunately, I do not have any experience working with Ignite. Can you provide any
advice or a good starting point to understand more about this issue?

> 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: Ignite RDD
>    Affects Versions: 1.5.0.final
>            Reporter: Vladimir Ozerov
>            Assignee: Valentin Kulichenko
>              Labels: bigdata, gsoc2017
>             Fix For: 2.0
>
>
> 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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