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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/01/04 14:53:00 UTC

[jira] [Resolved] (SPARK-8602) Shared cached DataFrames

     [ https://issues.apache.org/jira/browse/SPARK-8602?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-8602.
---------------------------------
    Resolution: Not A Problem

> Shared cached DataFrames
> ------------------------
>
>                 Key: SPARK-8602
>                 URL: https://issues.apache.org/jira/browse/SPARK-8602
>             Project: Spark
>          Issue Type: New Feature
>          Components: SQL
>    Affects Versions: 1.4.0
>            Reporter: John Muller
>            Priority: Major
>
> Currently, the only way I can think of to share HiveContexts, SparkContexts, or cached DataFrames is to use spark-jobserver and spark-jobserver-extras:
> https://gist.github.com/anonymous/578385766261d6fa7196#file-exampleshareddf-scala
> But HiveServer2 users over plain JDBC cannot access the shared dataframe. Request is to add this directly to SparkSQL and treat it like a shared temp table Ex. 
> SELECT a, b, c
> FROM TableA
> CACHE DATAFRAME
> This would be very useful for Rollups and Cubes, though I'm not sure what this may mean for HiveMetaStore. 



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