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