I have experienced a similar issue. The easiest fix I found was to increase the replication of the data being used in the worker to the number of workers you want to use for processing. The RDD seem to created on all the machines where the blocks are replicated. Please correct me if I am wrong.
Regards Mayur Mayur Rustagi Ph: +919632149971 h <https://twitter.com/mayur_rustagi>ttp://www.sigmoidanalytics.com https://twitter.com/mayur_rustagi On Thu, Jan 2, 2014 at 10:46 PM, Andrew Ash <[email protected]> wrote: > Hi lihu, > > Maybe the data you're accessing is in in HDFS and only resides on 4 of > your 20 machines because it's only about 4 blocks (at default 64MB / block > that's around a quarter GB). Where is your source data located and how is > it stored? > > Andrew > > > On Thu, Jan 2, 2014 at 7:53 AM, lihu <[email protected]> wrote: > >> Hi, >> I run spark on a cluster with 20 machine, but when I start an >> application use the spark-shell, there only 4 machine is working , the >> other with just idle, without memery and cpu used, I watch this through >> webui. >> >> I wonder the other machine maybe busy, so i watch the machines using >> "top" and "free" command, but this is not。 >> >> * So I just wonder why not spark assignment work to all all the 20 >> machine? this is not a good resource usage.* >> >> >> >> >> >
