Try to use --executor-memory 12g with spark-summit. Or you can set it in conf/spark-defaults.properties and rsync it to all workers and then restart. -Xiangrui
On Fri, Jun 27, 2014 at 1:05 PM, Peng Cheng <pc...@uow.edu.au> wrote: > I give up, communication must be blocked by the complex EC2 network topology > (though the error information indeed need some improvement). It doesn't make > sense to run a client thousands miles away to communicate frequently with > workers. I have moved everything to EC2 now. > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/TaskSchedulerImpl-Initial-job-has-not-accepted-any-resources-check-your-cluster-UI-to-ensure-that-woy-tp8247p8444.html > Sent from the Apache Spark User List mailing list archive at Nabble.com.
