I'm running it via pyspark against yarn in client deploy mode. I do notice in the spark web ui under Environment tab all the options I've set, so I'm guessing these are accepted.
On Sat, Apr 9, 2016 at 5:52 PM, Jacek Laskowski <ja...@japila.pl> wrote: > Hi, > > (I haven't played with GraphFrames) > > What's your `sc.master`? How do you run your application -- > spark-submit or java -jar or sbt run or...? The reason I'm asking is > that few options might not be in use whatsoever, e.g. > spark.driver.memory and spark.executor.memory in local mode. > > Pozdrawiam, > Jacek Laskowski > ---- > https://medium.com/@jaceklaskowski/ > Mastering Apache Spark http://bit.ly/mastering-apache-spark > Follow me at https://twitter.com/jaceklaskowski > > > On Sat, Apr 9, 2016 at 7:51 PM, Buntu Dev <buntu...@gmail.com> wrote: > > I'm running this motif pattern against 1.5M vertices (5.5mb) and 10M > (60mb) > > edges: > > > > tgraph.find("(a)-[]->(b); (c)-[]->(b); (c)-[]->(d)") > > > > I keep running into Java heap space errors: > > > > ~~~~~ > > > > ERROR actor.ActorSystemImpl: Uncaught fatal error from thread > > [sparkDriver-akka.actor.default-dispatcher-33] shutting down ActorSystem > > [sparkDriver] > > java.lang.OutOfMemoryError: Java heap space > > at scala.reflect.ManifestFactory$$anon$6.newArray(Manifest.scala:90) > > at scala.reflect.ManifestFactory$$anon$6.newArray(Manifest.scala:88) > > at scala.Array$.ofDim(Array.scala:218) > > at akka.util.ByteIterator.toArray(ByteIterator.scala:462) > > at akka.util.ByteString.toArray(ByteString.scala:321) > > at > > > akka.remote.transport.AkkaPduProtobufCodec$.decodePdu(AkkaPduCodec.scala:168) > > at > > > akka.remote.transport.ProtocolStateActor.akka$remote$transport$ProtocolStateActor$$decodePdu(AkkaProtocolTransport.scala:513) > > at > > > akka.remote.transport.ProtocolStateActor$$anonfun$5.applyOrElse(AkkaProtocolTransport.scala:357) > > at > > > akka.remote.transport.ProtocolStateActor$$anonfun$5.applyOrElse(AkkaProtocolTransport.scala:352) > > at > > > scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33) > > at akka.actor.FSM$class.processEvent(FSM.scala:595) > > at > > > akka.remote.transport.ProtocolStateActor.processEvent(AkkaProtocolTransport.scala:220) > > at akka.actor.FSM$class.akka$actor$FSM$$processMsg(FSM.scala:589) > > at akka.actor.FSM$$anonfun$receive$1.applyOrElse(FSM.scala:583) > > at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498) > > at akka.actor.ActorCell.invoke(ActorCell.scala:456) > > at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237) > > at akka.dispatch.Mailbox.run(Mailbox.scala:219) > > at > > > akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386) > > at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) > > at > > > scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) > > at > scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) > > at > > > scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) > > > > ~~~~~ > > > > > > Here is my config: > > > > conf.set("spark.executor.memory", "8192m") > > conf.set("spark.executor.cores", 4) > > conf.set("spark.driver.memory", "10240m") > > conf.set("spark.driver.maxResultSize", "2g") > > conf.set("spark.kryoserializer.buffer.max", "1024mb") > > > > > > Wanted to know if there are any other configs to tweak? > > > > > > Thanks! >
