i want to join all those logs in some manner. That's what i'm trying to do.
*Thanks*, <https://in.linkedin.com/in/ramkumarcs31> On Fri, Oct 30, 2015 at 4:57 PM, Saisai Shao <sai.sai.s...@gmail.com> wrote: > I don't think Spark Streaming supports multiple streaming context in one > jvm, you cannot use in such way. Instead you could run multiple streaming > applications, since you're using Yarn. > > 2015年10月30日星期五，Ramkumar V <ramkumar.c...@gmail.com> 写道： > >> I found NPE is mainly because of im using the same JavaStreamingContext >> for some other kafka stream. if i change the name , its running >> successfully. how to run multiple JavaStreamingContext in a program ? I'm >> getting following exception if i run multiple JavaStreamingContext in >> single file. >> >> 15/10/30 11:04:29 INFO yarn.ApplicationMaster: Final app status: FAILED, >> exitCode: 15, (reason: User class threw exception: >> java.lang.IllegalStateException: Only one StreamingContext may be started >> in this JVM. Currently running StreamingContext was started >> atorg.apache.spark.streaming.api.java.JavaStreamingContext.start(JavaStreamingContext.scala:622) >> >> >> *Thanks*, >> <https://in.linkedin.com/in/ramkumarcs31> >> >> >> On Fri, Oct 30, 2015 at 3:25 PM, Saisai Shao <sai.sai.s...@gmail.com> >> wrote: >> >>> From the code, I think this field "rememberDuration" shouldn't be null, >>> it will be verified at the start, unless some place changes it's value in >>> the runtime that makes it null, but I cannot image how this happened. Maybe >>> you could add some logs around the place where exception happens if you >>> could reproduce it. >>> >>> On Fri, Oct 30, 2015 at 5:31 PM, Ramkumar V <ramkumar.c...@gmail.com> >>> wrote: >>> >>>> No. this is the only exception that im getting multiple times in my >>>> log. Also i was reading some other topics earlier but im not faced this >>>> NPE. >>>> >>>> *Thanks*, >>>> <https://in.linkedin.com/in/ramkumarcs31> >>>> >>>> >>>> On Fri, Oct 30, 2015 at 2:50 PM, Saisai Shao <sai.sai.s...@gmail.com> >>>> wrote: >>>> >>>>> I just did a local test with your code, seems everything is fine, the >>>>> only difference is that I use the master branch, but I don't think it >>>>> changes a lot in this part. Do you met any other exceptions or errors >>>>> beside this one? Probably this is due to other exceptions that makes this >>>>> system unstable. >>>>> >>>>> On Fri, Oct 30, 2015 at 5:13 PM, Ramkumar V <ramkumar.c...@gmail.com> >>>>> wrote: >>>>> >>>>>> 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> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> >>>>>>>>> >>>>>>>> >>>>>>> >>>>>> >>>>> >>>> >>> >>
