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From "Patrick Wendell (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-1458) Expose sc.version in PySpark
Date Thu, 10 Jul 2014 19:53:05 GMT

    [ https://issues.apache.org/jira/browse/SPARK-1458?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14057857#comment-14057857
] 

Patrick Wendell commented on SPARK-1458:
----------------------------------------

[~nchammas] I updated the JIRA title to reflect the scope. We should just add this in PySpark,
should be an easy fix!

> Expose sc.version in PySpark
> ----------------------------
>
>                 Key: SPARK-1458
>                 URL: https://issues.apache.org/jira/browse/SPARK-1458
>             Project: Spark
>          Issue Type: New Feature
>          Components: PySpark, Spark Core
>    Affects Versions: 0.9.0
>            Reporter: Nicholas Chammas
>            Priority: Minor
>
> As discussed [here|http://apache-spark-user-list.1001560.n3.nabble.com/programmatic-way-to-tell-Spark-version-td1929.html],
I think it would be nice if there was a way to programmatically determine what version of
Spark you are running. 
> The potential use cases are not that important, but they include:
> # Branching your code based on what version of Spark is running.
> # Checking your version without having to quit and restart the Spark shell.
> Right now in PySpark, I believe the only way to determine your version is by firing up
the Spark shell and looking at the startup banner.



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