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Cloudera, BigData, Semantic IoT, Hadoop, NoSQL

Cloudera CDH/CDP 및 Hadoop EcoSystem, Semantic IoT등의 개발/운영 기술을 정리합니다. gooper@gooper.com로 문의 주세요.


Spark에서 KafkaUtils.createStream을 이용하여 Kafka의 data를 가져올때 StorageLevel을 StorageLevel.MEMORY_ONLY()로 하는 경우 "Could not compute split, block input-0-1517397051800 not found"형태의 오류가 발생하는데 이는 Spark가 메모리 부족 상황이 되면 해당 데이타를 버리기 때문에 문제가 발생한다.

이때는 StorageLevel.MEMORY_ONLY()을 StorageLevel.MEMORY_AND_DISK_SER()로 변경해준다.



-------------소스코드 일부분-----

JavaPairReceiverInputDStream<byte[], byte[]> kafkaStream = KafkaUtils.createStream(jssc,byte[].class, byte[].class, kafka.serializer.DefaultDecoder.class, kafka.serializer.DefaultDecoder.class,
        conf, topic, StorageLevel.MEMORY_AND_DISK_SER());
JavaDStream<byte[]> lines = kafkaStream.map(tuple2 -> tuple2._2());


-----------------------------------오류 메세지------------------

[2018-01-31 20:17:26,404] [internal.Logging$class] [logError(#70)] [ERROR] Task 0 in stage 1020.0 failed 1 times; aborting job
[2018-01-31 20:17:26,404] [internal.Logging$class] [logError(#91)] [ERROR] Error running job streaming job 1517397060000 ms.0
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1020.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1020.0 (TID 1020, localhost, executor driver): java.lang.Exception: Could not compute split, block input-0-1517397051800 not found
        at org.apache.spark.rdd.BlockRDD.compute(BlockRDD.scala:50)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:99)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)

Driver stacktrace:
        at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
        at scala.Option.foreach(Option.scala:257)
        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
        at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
        at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1925)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1938)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1951)
        at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1354)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
        at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
        at org.apache.spark.rdd.RDD.take(RDD.scala:1327)
        at org.apache.spark.streaming.dstream.DStream$$anonfun$print$2$$anonfun$foreachFunc$3$1.apply(DStream.scala:734)
        at org.apache.spark.streaming.dstream.DStream$$anonfun$print$2$$anonfun$foreachFunc$3$1.apply(DStream.scala:733)
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:51)
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
        at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:415)
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:50)
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
        at scala.util.Try$.apply(Try.scala:192)
        at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
        at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:256)
        at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:256)
        at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:256)
        at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
        at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:255)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.Exception: Could not compute split, block input-0-1517397051800 not found
        at org.apache.spark.rdd.BlockRDD.compute(BlockRDD.scala:50)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:99)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
        ... 3 more
[2018-01-31 20:17:26,415] [onem2m.AvroOneM2MDataSparkSubscribe$ConsumerT] [go(#142)] [DEBUG] count data from kafka broker stream in AvroOneM2MDataSparkSubscribe: 39981
[2018-01-31 20:17:29,039] [sf.QueryServiceFactory] [create(#28)] [DEBUG] query gubun : FUSEKISPARQL
[2018-01-31 20:17:29,040] [sf.QueryCommon] [makeFinal(#44)] [DEBUG] Count : 0 , Vals : [] 
[2018-01-31 20:17:29,040] [sf.SparqlFusekiQueryImpl] [runModifySparql(#162)] [DEBUG] runModifySparql() on DatWarehouse server start.................................. 
[2018-01-31 20:17:29,040] [sf.SparqlFusekiQueryImpl] [runModifySparql(#165)] [DEBUG] try (first).................................. 
[2018-01-31 20:17:29,042] [sf.SparqlFusekiQueryImpl] [runModifySparql(#207)] [DEBUG] runModifySparql() on DataWarehouse server end.................................. 
[2018-01-31 20:17:29,042] [sf.SparqlFusekiQueryImpl] [runModifySparql(#212)] [DEBUG] runModifySparql() on DataMart server start.................................. 
[2018-01-31 20:17:29,043] [sf.SparqlFusekiQueryImpl] [runModifySparql(#224)] [DEBUG] runModifySparql() on DataMart server end.................................. 
[2018-01-31 20:17:29,044] [sf.QueryCommon] [makeFinal(#44)] [DEBUG] Count : 0 , Vals : [] 
[2018-01-31 20:17:29,044] [sf.SparqlFusekiQueryImpl] [runModifySparql(#162)] [DEBUG] runModifySparql() on DatWarehouse server start.................................. 
[2018-01-31 20:17:29,044] [sf.SparqlFusekiQueryImpl] [runModifySparql(#165)] [DEBUG] try (first).................................. 
[2018-01-31 20:17:29,045] [sf.SparqlFusekiQueryImpl] [runModifySparql(#207)] [DEBUG] runModifySparql() on DataWarehouse server end.................................. 
[2018-01-31 20:17:29,045] [sf.SparqlFusekiQueryImpl] [runModifySparql(#212)] [DEBUG] runModifySparql() on DataMart server start.................................. 
[2018-01-31 20:17:29,046] [sf.SparqlFusekiQueryImpl] [runModifySparql(#224)] [DEBUG] runModifySparql() on DataMart server end.................................. 
[2018-01-31 20:17:29,047] [sf.QueryCommon] [makeFinal(#44)] [DEBUG] Count : 0 , Vals : [] 
[2018-01-31 20:17:29,047] [sf.SparqlFusekiQueryImpl] [runModifySparql(#212)] [DEBUG] runModifySparql() on DataMart server start.................................. 
[2018-01-31 20:17:29,049] [sf.SparqlFusekiQueryImpl] [runModifySparql(#224)] [DEBUG] runModifySparql() on DataMart server end.................................. 
[2018-01-31 20:17:29,049] [sf.TripleService] [makeTripleFile(#333)] [INFO] makeTripleFile start==========================>
[2018-01-31 20:17:29,049] [sf.TripleService] [makeTripleFile(#334)] [DEBUG] makeTripleFile ========triple_path_file=================>/svc/apps/sda/triples/20180131/AvroOneM2MDataSparkSubscribe_TT20180131T201100S0000000991_WRK20180131T201729.nt
[2018-01-31 20:17:29,170] [sf.TripleService] [makeTripleFile(#346)] [INFO] makeTripleFile end==========================>
[2018-01-31 20:17:29,170] [onem2m.AvroOneM2MDataSparkSubscribe] [sendTriples(#288)] [INFO] Sending triples in com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe to DW start.......................
[2018-01-31 20:17:29,170] [sf.TripleService] [sendTripleFileToDW(#382)] [INFO] sendTripleFile to DW start==========================>
[2018-01-31 20:17:29,170] [sf.TripleService] [sendTripleFileToDW(#383)] [DEBUG] sendTripleFile ==============triple_path_file============>/svc/apps/sda/triples/20180131/AvroOneM2MDataSparkSubscribe_TT20180131T201100S0000000991_WRK20180131T201729.nt
[2018-01-31 20:17:29,171] [sf.TripleService] [sendTripleFileToDW(#396)] [DEBUG] sendTripleFile ==============args============>/svc/apps/sda/bin/fuseki/bin/s-post http://166.104.112.43:23030/icbms default /svc/apps/sda/triples/20180131/AvroOneM2MDataSparkSubscribe_TT20180131T201100S0000000991_WRK20180131T201729.nt 
[2018-01-31 20:17:29,171] [sf.TripleService] [sendTripleFileToDW(#399)] [DEBUG] try (first).......................
[2018-01-31 20:17:36,950] [util.Utils] [runShell(#737)] [DEBUG] Thread stdMsgT Status : TERMINATED
[2018-01-31 20:17:36,951] [util.Utils] [runShell(#738)] [DEBUG] Thread errMsgT Status : TERMINATED
[2018-01-31 20:17:36,951] [util.Utils] [runShell(#743)] [DEBUG] notTimeOver ==========================>true
[2018-01-31 20:17:36,951] [sf.TripleService] [sendTripleFileToDW(#402)] [DEBUG] resultStr in TripleService.sendTripleFileToDW() == > [, ]
[2018-01-31 20:17:36,951] [sf.TripleService] [sendTripleFileToDW(#433)] [INFO] sendTripleFile to DW  end==========================>
[2018-01-31 20:17:36,951] [onem2m.AvroOneM2MDataSparkSubscribe] [sendTriples(#290)] [INFO] Sending triples in com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe to DW end.......................
[2018-01-31 20:17:36,951] [onem2m.AvroOneM2MDataSparkSubscribe] [sendTriples(#293)] [INFO] Sending triples in com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe to Halyard start.......................
[2018-01-31 20:17:36,952] [sf.TripleService] [sendTripleFileToHalyard(#486)] [INFO] sendTripleFile to Halyard  start==========================>
[2018-01-31 20:17:37,294] [sf.QueryServiceFactory] [create(#31)] [DEBUG] query gubun : HALYARDSPARQL
[2018-01-31 20:17:37,317] [sf.SparqlHalyardQueryImpl] [insertByPost(#189)] [DEBUG] ------------------------insertByPost-----start-----------------------
[2018-01-31 20:17:37,317] [sf.SparqlHalyardQueryImpl] [insertByPost(#198)] [DEBUG] ------------------------insertByPost-----end-----------------------

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500 Cloudera가 사용하는 서비스별 디렉토리 2018.03.29 644
499 cloudera-scm-agent 설정파일 위치및 재시작 명령문 2018.03.29 963
498 [CentOS] 네트워크 설정 2018.03.26 636
497 Components of the Impala Server 2018.03.21 598
496 HDFS Balancer설정및 수행 2018.03.21 679
495 hadoop 클러스터 실행 스크립트 정리 2018.03.20 1675
494 HA(Namenode, ResourceManager, Kerberos) 및 보안(Zookeeper, Hadoop) 2018.03.16 250
493 자주쓰는 유용한 프로그램 2018.03.16 1470
492 에러 추적(Error Tracking) 및 로그 취합(logging aggregation) 시스템인 Sentry 설치 2018.03.14 422
491 update 샘플 2018.03.12 1324
490 이미지 관리 오픈소스 목록 2018.03.11 690
489 Scala에서 countByWindow를 이용하기(예제) 2018.03.08 1002
488 Scala를 이용한 Streaming예제 2018.03.08 899
487 scala application 샘플소스(SparkSession이용) 2018.03.07 1095
486 fuseki의 endpoint를 이용한 insert, delete하는 sparql예시 2018.02.14 310
485 프로세스를 확인해서 프로세스를 삭제하는 shell script예제(cryptonight) 2018.02.02 867
484 spark-submit 실행시 "java.lang.OutOfMemoryError: Java heap space"발생시 조치사항 2018.02.01 788
» Could not compute split, block input-0-1517397051800 not found형태의 오류가 발생시 조치방법 2018.02.01 492
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