Are you by any chance building this on NFS ? As far as I know the build is
severely bottlenecked by filesystem calls during assembly (each class file
in each dependency gets a fstat call or something like that).  That is
partly why building from say a local ext4 filesystem or a SSD is much
faster irrespective of memory / CPU.

Thanks
Shivaram


On Fri, Apr 25, 2014 at 2:09 PM, Akhil Das <ak...@sigmoidanalytics.com>wrote:

> You can always increase the sbt memory by setting
>
> export JAVA_OPTS="-Xmx10g"
>
>
>
>
> Thanks
> Best Regards
>
>
> On Sat, Apr 26, 2014 at 2:17 AM, Williams, Ken <
> ken.willi...@windlogics.com> wrote:
>
>>  No, I haven't done any config for SBT.  Is there somewhere you might be
>> able to point me toward for how to do that?
>>
>>
>>
>> -Ken
>>
>>
>>
>> *From:* Josh Rosen [mailto:rosenvi...@gmail.com]
>> *Sent:* Friday, April 25, 2014 3:27 PM
>> *To:* user@spark.apache.org
>> *Subject:* Re: Build times for Spark
>>
>>
>>
>> Did you configure SBT to use the extra memory?
>>
>>
>>
>> On Fri, Apr 25, 2014 at 12:53 PM, Williams, Ken <
>> ken.willi...@windlogics.com> wrote:
>>
>> I've cloned the github repo and I'm building Spark on a pretty beefy
>> machine (24 CPUs, 78GB of RAM) and it takes a pretty long time.
>>
>>
>>
>> For instance, today I did a 'git pull' for the first time in a week or
>> two, and then doing 'sbt/sbt assembly' took 43 minutes of wallclock time
>> (88 minutes of CPU time).  After that, I did 'SPARK_HADOOP_VERSION=2.2.0
>> SPARK_YARN=true sbt/sbt assembly' and that took 25 minutes wallclock, 73
>> minutes CPU.
>>
>>
>>
>> Is that typical?  Or does that indicate some setup problem in my
>> environment?
>>
>>
>>
>> --
>>
>> Ken Williams, Senior Research Scientist
>>
>> *WindLogics*
>>
>> http://windlogics.com
>>
>>
>>
>>
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>>
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