On Thu, Jan 9, 2014 at 4:11 AM, Matei Zaharia <[email protected]>wrote:
> Oh, you shouldn’t use spark-class for your own classes. Just build your > job separately and submit it by running it with “java” and creating a > SparkContext in it. spark-class is designed to run classes internal to the > Spark project. > Really? Apparently Eugen runs his jobs by: $SPARK_HOME/spark-class SPARK_CLASSPATH=PathToYour.jar com.myproject.MyJob , as he instructed me here<http://mail-archives.apache.org/mod_mbox/spark-user/201401.mbox/browser>to do this. I have to say while spark documentation is not sparse, it does not address enough, and as you can see the community is confused. Are the spark users supposed to create something like run-example for their own jobs? > > Matei > > On Jan 8, 2014, at 8:06 PM, Aureliano Buendia <[email protected]> > wrote: > > > > > On Thu, Jan 9, 2014 at 3:59 AM, Matei Zaharia <[email protected]>wrote: > >> Have you looked at the cluster UI, and do you see any workers registered >> there, and your application under running applications? Maybe you typed in >> the wrong master URL or something like that. >> > > No, it's automated: cat spark-ec2/cluster-url > > I think the problem might be caused by spark-class script. It seems to > assign too much memory. > > I forgot the fact that run-example doesn't use spark-class. > > >> >> Matei >> >> On Jan 8, 2014, at 7:07 PM, Aureliano Buendia <[email protected]> >> wrote: >> >> The strange thing is that spark examples work fine, but when I include a >> spark example in my jar and deploy it, I get this error for the very same >> example: >> >> WARN ClusterScheduler: Initial job has not accepted any resources; check >> your cluster UI to ensure that workers are registered and have sufficient >> memory >> >> My jar is deployed to master and then to workers by spark-ec2/copy-dir. >> Why would including the example in my jar cause this error? >> >> >> >> On Thu, Jan 9, 2014 at 12:41 AM, Aureliano Buendia >> <[email protected]>wrote: >> >>> Could someone explain how SPARK_MEM, SPARK_WORKER_MEMORY and >>> spark.executor.memory should be related so that this non helpful error >>> doesn't occur? >>> >>> Maybe there are more env and java config variable about memory that I'm >>> missing. >>> >>> By the way, that bit of the error asking to check the web UI, it's just >>> redundant. The UI is of no help. >>> >>> >>> On Wed, Jan 8, 2014 at 4:31 PM, Aureliano Buendia >>> <[email protected]>wrote: >>> >>>> Hi, >>>> >>>> >>>> My spark cluster is not able to run a job due to this warning: >>>> >>>> WARN ClusterScheduler: Initial job has not accepted any resources; >>>> check your cluster UI to ensure that workers are registered and have >>>> sufficient memory >>>> >>>> The workers have these status: >>>> >>>> ALIVE 2 (0 Used)6.3 GB (0.0 B Used) So there must be plenty of memory >>>> available despite the warning message. I'm using default spark config, is >>>> there a config parameter that needs changing for this to work? >>>> >>> >>> >> >> > >
