Can you run the command 'ulimit -n' to see the current limit ? To configure ulimit settings on Ubuntu, edit */etc/security/limits.conf* Cheers
On Wed, Apr 29, 2015 at 2:07 PM, Bill Jay <bill.jaypeter...@gmail.com> wrote: > Hi all, > > I am using the direct approach to receive real-time data from Kafka in the > following link: > > https://spark.apache.org/docs/1.3.0/streaming-kafka-integration.html > > > My code follows the word count direct example: > > > https://github.com/apache/spark/blob/master/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala > > > > After around 12 hours, I got the following error messages in Spark log: > > 15/04/29 20:18:10 ERROR JobScheduler: Error generating jobs for time > 1430338690000 ms > org.apache.spark.SparkException: ArrayBuffer(java.io.IOException: Too many > open files, java.io.IOException: Too many open files, java.io.IOException: > Too many open files, java.io.IOException: Too many open files, > java.io.IOException: Too many open files) > at > org.apache.spark.streaming.kafka.DirectKafkaInputDStream.latestLeaderOffsets(DirectKafkaInputDStream.scala:94) > at > org.apache.spark.streaming.kafka.DirectKafkaInputDStream.compute(DirectKafkaInputDStream.scala:116) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:300) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:300) > at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:299) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:287) > at scala.Option.orElse(Option.scala:257) > at > org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:284) > at > org.apache.spark.streaming.dstream.MappedDStream.compute(MappedDStream.scala:35) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:300) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:300) > at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:299) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:287) > at scala.Option.orElse(Option.scala:257) > at > org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:284) > at > org.apache.spark.streaming.dstream.MappedDStream.compute(MappedDStream.scala:35) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:300) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:300) > at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:299) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:287) > at scala.Option.orElse(Option.scala:257) > at > org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:284) > at > org.apache.spark.streaming.dstream.MappedDStream.compute(MappedDStream.scala:35) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:300) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:300) > at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:299) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:287) > at scala.Option.orElse(Option.scala:257) > at > org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:284) > at > org.apache.spark.streaming.dstream.MappedDStream.compute(MappedDStream.scala:35) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:300) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:300) > at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:299) > at > org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:287) > at scala.Option.orElse(Option.scala:257) > at > org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:284) > at > org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:38) > at > org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:116) > at > org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:116) > at > scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251) > at > scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at > scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > at > scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251) > at > scala.collection.AbstractTraversable.flatMap(Traversable.scala:105) > at > org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:116) > at > org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:239) > at > org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:237) > at scala.util.Try$.apply(Try.scala:161) > at > org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:237) > at org.apache.spark.streaming.scheduler.JobGenerator.org > $apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:174) > at > org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$start$1$$anon$1$$anonfun$receive$1.applyOrElse(JobGenerator.scala:85) > at akka.actor.Actor$class.aroundReceive(Actor.scala:465) > at > org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$start$1$$anon$1.aroundReceive(JobGenerator.scala:83) > at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516) > at akka.actor.ActorCell.invoke(ActorCell.scala:487) > at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238) > at akka.dispatch.Mailbox.run(Mailbox.scala:220) > at > akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393) > 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) > > Thanks for the help. > > Bill >
