it comes at start of each tasks when there is new data inserted in kafka.( data inserted is very few) kafka topic has 300 partitions - data inserted is ~10 MB.
Tasks gets failed and it retries which succeed and after certain no of fail tasks it kills the job. On Sat, Aug 22, 2015 at 2:08 AM, Akhil Das <ak...@sigmoidanalytics.com> wrote: > That looks like you are choking your kafka machine. Do a top on the kafka > machines and see the workload, it may happen that you are spending too much > time on disk io etc. > On Aug 21, 2015 7:32 AM, "Cody Koeninger" <c...@koeninger.org> wrote: > >> Sounds like that's happening consistently, not an occasional network >> problem? >> >> Look at the Kafka broker logs >> >> Make sure you've configured the correct kafka broker hosts / ports (note >> that direct stream does not use zookeeper host / port). >> >> Make sure that host / port is reachable from your driver and worker >> nodes, ie telnet or netcat to it. It looks like your driver can reach it >> (since there's partition info in the logs), but that doesn't mean the >> worker can. >> >> Use lsof / netstat to see what's going on with those ports while the job >> is running, or tcpdump if you need to. >> >> If you can't figure out what's going on from a networking point of view, >> post a minimal reproducible code sample that demonstrates the issue, so it >> can be tested in a different environment. >> >> >> >> >> >> On Fri, Aug 21, 2015 at 4:06 AM, Shushant Arora < >> shushantaror...@gmail.com> wrote: >> >>> Hi >>> >>> >>> Getting below error in spark streaming 1.3 while consuming from kafka using >>> directkafka stream. Few of tasks are getting failed in each run. >>> >>> >>> What is the reason /solution of this error? >>> >>> >>> 15/08/21 08:54:54 ERROR executor.Executor: Exception in task 262.0 in stage >>> 130.0 (TID 16332) >>> java.io.EOFException: Received -1 when reading from channel, socket has >>> likely been closed. >>> at kafka.utils.Utils$.read(Utils.scala:376) >>> at >>> kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54) >>> at kafka.network.Receive$class.readCompletely(Transmission.scala:56) >>> at >>> kafka.network.BoundedByteBufferReceive.readCompletely(BoundedByteBufferReceive.scala:29) >>> at kafka.network.BlockingChannel.receive(BlockingChannel.scala:100) >>> at kafka.consumer.SimpleConsumer.liftedTree1$1(SimpleConsumer.scala:81) >>> at >>> kafka.consumer.SimpleConsumer.kafka$consumer$SimpleConsumer$$sendRequest(SimpleConsumer.scala:71) >>> at >>> kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SimpleConsumer.scala:109) >>> at >>> kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:109) >>> at >>> kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:109) >>> at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33) >>> at >>> kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply$mcV$sp(SimpleConsumer.scala:108) >>> at >>> kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:108) >>> at >>> kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:108) >>> at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33) >>> at kafka.consumer.SimpleConsumer.fetch(SimpleConsumer.scala:107) >>> at >>> org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.fetchBatch(KafkaRDD.scala:150) >>> at >>> org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.getNext(KafkaRDD.scala:162) >>> at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71) >>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) >>> at >>> org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:210) >>> at >>> org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:63) >>> at >>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68) >>> at >>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) >>> at org.apache.spark.scheduler.Task.run(Task.scala:64) >>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203) >>> 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) >>> 15/08/21 08:54:54 INFO executor.CoarseGrainedExecutorBackend: Got assigned >>> task 16348 >>> 15/08/21 08:54:54 INFO executor.Executor: Running task 260.1 in stage 130.0 >>> (TID 16348) >>> 15/08/21 08:54:54 INFO kafka.KafkaRDD: Computing topic >>> test_hbrealtimeevents, partition 75 offsets 4701 -> 4718 >>> 15/08/21 08:54:54 INFO utils.VerifiableProperties: Verifying properties >>> >>> >>> >>> >>> Thanks >>> >>> >>
