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Posted to dev@sqoop.apache.org by "Veena Basavaraj (JIRA)" <ji...@apache.org> on 2015/03/06 18:09:38 UTC

[jira] [Updated] (SQOOP-1532) Sqoop2: Support Sqoop on Spark Execution Engine

     [ https://issues.apache.org/jira/browse/SQOOP-1532?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Veena Basavaraj updated SQOOP-1532:
-----------------------------------
    Description: 
The current execution engine supported in sqoop is MR.

The goal if this ticket is to support sqoop jobs ( map only and map+reduce ) to run on spark environment.

It should at the minimum support running on the standalone spark cluster and then subsequently work with YARN/mesos.

High level goals
1. Hook up with the connector apis to provide the basic load/ extract to the spark RDD.
2. Implementation of the Sqoop RDD to support extraction from different data sources . The design proposal will discuss the alternatives on how this can be achieved.
3. Optimizing the loading/writing with 



  was:
The goal of this ticket is to support a pluggable way to select the execution engine on which we can run the sqoop jobs.




> Sqoop2: Support Sqoop on Spark Execution Engine
> -----------------------------------------------
>
>                 Key: SQOOP-1532
>                 URL: https://issues.apache.org/jira/browse/SQOOP-1532
>             Project: Sqoop
>          Issue Type: Improvement
>            Reporter: Veena Basavaraj
>            Assignee: Veena Basavaraj
>             Fix For: 1.99.6
>
>
> The current execution engine supported in sqoop is MR.
> The goal if this ticket is to support sqoop jobs ( map only and map+reduce ) to run on spark environment.
> It should at the minimum support running on the standalone spark cluster and then subsequently work with YARN/mesos.
> High level goals
> 1. Hook up with the connector apis to provide the basic load/ extract to the spark RDD.
> 2. Implementation of the Sqoop RDD to support extraction from different data sources . The design proposal will discuss the alternatives on how this can be achieved.
> 3. Optimizing the loading/writing with 



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