Thanks Andrew. I was expecting this to be the issue. Are there any pointers about how to change the serialization to Kryo ?
On Mon, Feb 24, 2014 at 10:17 PM, Andrew Ash <and...@andrewash.com> wrote: > This is because Joda's DateTimeFormatter is not serializable (doesn't > implement the empty Serializable interface) > http://joda-time.sourceforge.net/apidocs/org/joda/time/format/DateTimeFormat.html > > One ugly thing I've done before is to instantiate a new DateTimeFormatter > in every line, so like this: > > myRDD.filter(x => > DateTimeFormat.forPattern("YYYY-mm-dd").parseString(x.getCreatedAt).isAfter(start) > ).count > > It's very inefficient but it gets things closer to working. > > Another thing to try is to switch to using Kryo serialization instead of > the default Java serialization, which I think did handle DTF formatting > correctly. Back in 0.7.x days though, there was an issue where some of the > Joda libraries wouldn't correctly serialize with Kryo, but I think that's > since been fixed: > https://groups.google.com/forum/#!topic/cascalog-user/35cdnNIamKU > > HTH, > Andrew > > > On Mon, Feb 24, 2014 at 6:57 PM, Soumya Simanta > <soumya.sima...@gmail.com>wrote: > >> I want to filter a RDD by comparing dates. >> >> myRDD.filter( x => new DateTime(x.getCreatedAt).isAfter(start) ).count >> >> >> I'm using the JodaTime library but I get an exception about a Jodatime >> class not serializable. >> >> Is there a way to configure this or an easier alternative for this >> problem. >> >> >> org.apache.spark.SparkException: Job aborted: Task not serializable: >> java.io.NotSerializableException: org.joda.time.format.DateTimeFormatter >> >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1028) >> >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1026) >> >> at >> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) >> >> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) >> >> at org.apache.spark.scheduler.DAGScheduler.org >> $apache$spark$scheduler$DAGScheduler$$abortStage(DAGScheduler.scala:1026) >> >> at org.apache.spark.scheduler.DAGScheduler.org >> $apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:794) >> >> at org.apache.spark.scheduler.DAGScheduler.org >> $apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:737) >> >> at >> org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:569) >> >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:207) >> >> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498) >> >> at akka.actor.ActorCell.invoke(ActorCell.scala:456) >> >> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237) >> >> at akka.dispatch.Mailbox.run(Mailbox.scala:219) >> >> at >> akka.dispatch.ForkJoinExecutorConfigurator$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) >> > >
