No, i dont have any special settings. if i keep only reading line in my code, it's throwing NPE.
*Thanks*, <https://in.linkedin.com/in/ramkumarcs31> On Fri, Oct 30, 2015 at 2:14 PM, Saisai Shao <sai.sai.s...@gmail.com> wrote: > Do you have any special settings, from your code, I don't think it will > incur NPE at that place. > > On Fri, Oct 30, 2015 at 4:32 PM, Ramkumar V <ramkumar.c...@gmail.com> > wrote: > >> spark version - spark 1.4.1 >> >> my code snippet: >> >> String brokers = "ip:port,ip:port"; >> String topics = "x,y,z"; >> HashSet<String> TopicsSet = new >> HashSet<String>(Arrays.asList(topics.split(","))); >> HashMap<String, String> kafkaParams = new HashMap<String, String>(); >> kafkaParams.put("metadata.broker.list", brokers); >> >> JavaPairInputDStream<String, String> messages = >> KafkaUtils.createDirectStream( >> jssc, >> String.class, >> String.class, >> StringDecoder.class, >> StringDecoder.class, >> kafkaParams, >> TopicsSet >> ); >> >> messages.foreachRDD(new Function<JavaPairRDD<String , String>,Void> () { >> public Void call(JavaPairRDD<String , String> tuple) { >> JavaRDD<String>rdd = tuple.values(); >> rdd.saveAsTextFile("hdfs://myuser:8020/user/hdfs/output"); >> return null; >> } >> }); >> >> >> *Thanks*, >> <https://in.linkedin.com/in/ramkumarcs31> >> >> >> On Fri, Oct 30, 2015 at 1:57 PM, Saisai Shao <sai.sai.s...@gmail.com> >> wrote: >> >>> What Spark version are you using, also a small code snippet of how you >>> use Spark Streaming would be greatly helpful. >>> >>> On Fri, Oct 30, 2015 at 3:57 PM, Ramkumar V <ramkumar.c...@gmail.com> >>> wrote: >>> >>>> I can able to read and print few lines. Afterthat i'm getting this >>>> exception. Any idea for this ? >>>> >>>> *Thanks*, >>>> <https://in.linkedin.com/in/ramkumarcs31> >>>> >>>> >>>> On Thu, Oct 29, 2015 at 6:14 PM, Ramkumar V <ramkumar.c...@gmail.com> >>>> wrote: >>>> >>>>> Hi, >>>>> >>>>> I'm trying to read from kafka stream and printing it textfile. I'm >>>>> using java over spark. I dont know why i'm getting the following >>>>> exception. >>>>> Also exception message is very abstract. can anyone please help me ? >>>>> >>>>> Log Trace : >>>>> >>>>> 15/10/29 12:15:09 ERROR scheduler.JobScheduler: Error in job generator >>>>> java.lang.NullPointerException >>>>> at >>>>> org.apache.spark.streaming.DStreamGraph$$anonfun$getMaxInputStreamRememberDuration$2.apply(DStreamGraph.scala:172) >>>>> at >>>>> org.apache.spark.streaming.DStreamGraph$$anonfun$getMaxInputStreamRememberDuration$2.apply(DStreamGraph.scala:172) >>>>> at >>>>> scala.collection.TraversableOnce$$anonfun$maxBy$1.apply(TraversableOnce.scala:225) >>>>> at >>>>> scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:51) >>>>> at >>>>> scala.collection.IndexedSeqOptimized$class.reduceLeft(IndexedSeqOptimized.scala:68) >>>>> at >>>>> scala.collection.mutable.ArrayBuffer.reduceLeft(ArrayBuffer.scala:47) >>>>> at >>>>> scala.collection.TraversableOnce$class.maxBy(TraversableOnce.scala:225) >>>>> at >>>>> scala.collection.AbstractTraversable.maxBy(Traversable.scala:105) >>>>> at >>>>> org.apache.spark.streaming.DStreamGraph.getMaxInputStreamRememberDuration(DStreamGraph.scala:172) >>>>> at >>>>> org.apache.spark.streaming.scheduler.JobGenerator.clearMetadata(JobGenerator.scala:267) >>>>> at org.apache.spark.streaming.scheduler.JobGenerator.org >>>>> $apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:178) >>>>> at >>>>> org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:83) >>>>> at >>>>> org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:82) >>>>> at >>>>> org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) >>>>> 15/10/29 12:15:09 ERROR yarn.ApplicationMaster: User class threw >>>>> exception: java.lang.NullPointerException >>>>> java.lang.NullPointerException >>>>> at >>>>> org.apache.spark.streaming.DStreamGraph$$anonfun$getMaxInputStreamRememberDuration$2.apply(DStreamGraph.scala:172) >>>>> at >>>>> org.apache.spark.streaming.DStreamGraph$$anonfun$getMaxInputStreamRememberDuration$2.apply(DStreamGraph.scala:172) >>>>> at >>>>> scala.collection.TraversableOnce$$anonfun$maxBy$1.apply(TraversableOnce.scala:225) >>>>> at >>>>> scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:51) >>>>> at >>>>> scala.collection.IndexedSeqOptimized$class.reduceLeft(IndexedSeqOptimized.scala:68) >>>>> at >>>>> scala.collection.mutable.ArrayBuffer.reduceLeft(ArrayBuffer.scala:47) >>>>> at >>>>> scala.collection.TraversableOnce$class.maxBy(TraversableOnce.scala:225) >>>>> at >>>>> scala.collection.AbstractTraversable.maxBy(Traversable.scala:105) >>>>> at >>>>> org.apache.spark.streaming.DStreamGraph.getMaxInputStreamRememberDuration(DStreamGraph.scala:172) >>>>> at >>>>> org.apache.spark.streaming.scheduler.JobGenerator.clearMetadata(JobGenerator.scala:267) >>>>> at org.apache.spark.streaming.scheduler.JobGenerator.org >>>>> $apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:178) >>>>> at >>>>> org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:83) >>>>> at >>>>> org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:82) >>>>> at >>>>> org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) >>>>> >>>>> >>>>> >>>>> *Thanks*, >>>>> <https://in.linkedin.com/in/ramkumarcs31> >>>>> >>>>> >>>> >>> >> >
