Can you try creating just a single spark context and then try your code.
If you want to use it for streaming pass the same sparkcontext object
instead of conf.
Note: Instead of just replying to me , try to use reply to all so that the
post is visible for the community . That way you can expect immediate
responses.
On Fri, Feb 6, 2015 at 6:09 AM, aanilpala <aanilp...@gmail.com> wrote:
> I have the following code:
>
>
> SparkConf conf = new
> SparkConf().setAppName("streamer").setMaster("local[2]");
> conf.set("spark.driver.allowMultipleContexts", "true");
> JavaStreamingContext ssc = new JavaStreamingContext(conf, new
> Duration(batch_interval));
> ssc.checkpoint("/tmp/spark/checkpoint");
>
> SparkConf conf2 = new
> SparkConf().setAppName("classifier").setMaster("local[1]");
> conf2.set("spark.driver.allowMultipleContexts", "true");
> JavaSparkContext sc = new JavaSparkContext(conf);
>
> JavaReceiverInputDStream<String> stream =
> ssc.socketTextStream("localhost", 9999);
>
> // String to Tuple3 Conversion
> JavaDStream<Tuple3<Long, String, String>> tuple_stream =
> stream.map(new Function<String, Tuple3<Long, String, String>>() {
> ... });
>
> JavaPairDStream<Integer, DictionaryEntry>
> raw_dictionary_stream =
> tuple_stream.filter(new Function<Tuple3<Long, String,String>, Boolean>()
> {
>
> @Override
> public Boolean call(Tuple3<Long, String,String>
> tuple) throws Exception {
> if((tuple._1()/Time.scaling_factor %
> training_interval) > training_dur)
> NaiveBayes.train(sc.parallelize(training_set).rdd());
>
> return true;
> }
>
>
> }).
>
> I am working on a text mining project and I want to use
> NaiveBayesClassifier
> of MLlib to classify some stream items. So, I have two Spark contexts one
> of
> which is a streaming context. The call to NaiveBayes.train causes the
> following exception.
>
> Any ideas?
>
>
> Exception in thread "main" org.apache.spark.SparkException: Job aborted
> due
> to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure:
> Lost task 0.0 in stage 0.0 (TID 0, localhost):
> java.lang.ClassCastException:
> org.apache.spark.SparkContext$$anonfun$runJob$4 cannot be cast to
> org.apache.spark.ShuffleDependency
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:60)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at
>
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at
>
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
>
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org
> $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1214)
> at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1203)
> at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1202)
> at
>
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at
> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)
> at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
> at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
> at scala.Option.foreach(Option.scala:236)
> at
>
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)
> at
>
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1420)
> at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
> at
>
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1375)
> 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)
>
>
>
>
> --
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