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https://issues.apache.org/jira/browse/HIVE-7292?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16160923#comment-16160923
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Daniil Bastrich commented on HIVE-7292:
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[~xuefuz], I see the following case: I use Mesos DC/OS and Spark on Mesos.
Because it's very convenient. But if I want to use Hive on Spark in Mesos
DC/OS, I need special framework Apache Myriad to run YARN on Mesos. It's very
cluttering because I run one Resource Manager on another Resource Manager, and
it creates a lot of redundant abstraction levels.
And there are questions about that on the Internet (e.g.
http://grokbase.com/t/hive/user/15997dye2q/hive-on-spark-on-mesos)
Can we create the new sub-task for this feature?
> Hive on Spark
> -------------
>
> Key: HIVE-7292
> URL: https://issues.apache.org/jira/browse/HIVE-7292
> Project: Hive
> Issue Type: Improvement
> Components: Spark
> Reporter: Xuefu Zhang
> Assignee: Xuefu Zhang
> Labels: Spark-M1, Spark-M2, Spark-M3, Spark-M4, Spark-M5
> Attachments: Hive-on-Spark.pdf
>
>
> Spark as an open-source data analytics cluster computing framework has gained
> significant momentum recently. Many Hive users already have Spark installed
> as their computing backbone. To take advantages of Hive, they still need to
> have either MapReduce or Tez on their cluster. This initiative will provide
> user a new alternative so that those user can consolidate their backend.
> Secondly, providing such an alternative further increases Hive's adoption as
> it exposes Spark users to a viable, feature-rich de facto standard SQL tools
> on Hadoop.
> Finally, allowing Hive to run on Spark also has performance benefits. Hive
> queries, especially those involving multiple reducer stages, will run faster,
> thus improving user experience as Tez does.
> This is an umbrella JIRA which will cover many coming subtask. Design doc
> will be attached here shortly, and will be on the wiki as well. Feedback from
> the community is greatly appreciated!
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