Looks like 1 worker is doing the job. Can you repartition the RDD? Also what is the number of cores that you allocated? Things like this, you can easily identify by looking at the workers webUI (default worker:8081)
Thanks Best Regards On Tue, Aug 19, 2014 at 6:35 PM, Laird, Benjamin < benjamin.la...@capitalone.com> wrote: > Hi all, > > I'm doing some testing on a small dataset (HadoopRDD, 2GB, ~10M records), > with a cluster of 3 nodes > > Simple calculations like count take approximately 5s when using the > default value of executor.memory (512MB). When I scale this up to 2GB, > several Tasks take 1m or more (while most still are <1s), and tasks hang > indefinitely if I set it to 4GB or higher. > > While these worker nodes aren't very powerful, they seem to have enough > RAM to handle this: > > Running 'free –m' shows I have >7GB free on each worker. > > Any tips on why these jobs would hang when given more available RAM? > > Thanks > Ben > > ------------------------------ > > The information contained in this e-mail is confidential and/or > proprietary to Capital One and/or its affiliates. The information > transmitted herewith is intended only for use by the individual or entity > to which it is addressed. If the reader of this message is not the > intended recipient, you are hereby notified that any review, > retransmission, dissemination, distribution, copying or other use of, or > taking of any action in reliance upon this information is strictly > prohibited. If you have received this communication in error, please > contact the sender and delete the material from your computer. >
