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https://issues.apache.org/jira/browse/HIVE-7292?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jeff Hammerbacher updated HIVE-7292:
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Description:
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!
was:
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 umber 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!
> Hive on Spark
> -------------
>
> Key: HIVE-7292
> URL: https://issues.apache.org/jira/browse/HIVE-7292
> Project: Hive
> Issue Type: Improvement
> Reporter: Xuefu Zhang
> Assignee: Xuefu Zhang
> 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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