GitHub user sarahgerweck opened a pull request:

    https://github.com/apache/spark/pull/1752

    Optionally parallelize the Spark build.

    This introduces a new environment variable, `SPARK_BUILD_THREADS`,
    that controls the level of Maven parallelization (if set). This uses
    Maven 3's syntax for the number of threads: either a simple integer or
    something like `1.5C` to indicate 1.5 times the number of cores on the
    build server.
    
    On my hardware, (Intel Xeon E5-1620 v2, roughly equivalent to a fast
    i7), a setting of `1.5C` speeds up the build by about 15%.
    
    This will trigger some warnings that the Scala plugins are not marked as
    threadsafe. Several repeated builds show no differences in the compiled
    distribution (save timestamps), but this isn't proof that it can never
    fail.

You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/AtScaleInc/spark parBuild

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/spark/pull/1752.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #1752
    
----
commit 3cac93065df7c5620c1f4024193c1081a418cdbb
Author: Sarah Gerweck <[email protected]>
Date:   2014-08-03T09:40:59Z

    Optionally parallelize the Spark build.
    
    This introduces a new environment variable, `SPARK_BUILD_THREADS`,
    that controls the level of Maven parallelization (if set). This uses
    Maven 3's syntax for the number of threads: either a simple integer or
    something like `1.5C` to indicate 1.5 times the number of cores on the
    build server.
    
    On my hardware, (Intel Xeon E5-1620 v2, roughly equivalent to a fast
    i7), a setting of `1.5C` speeds up the build by about 15%.
    
    This will trigger some warnings that the Scala plugins are not marked as
    threadsafe. Several repeated builds show no differences in the compiled
    distribution (save timestamps), but this isn't proof that it can never
    fail.

----


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