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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.


StringBuffer의 값을 toString()을 이용하여 문자열로 변환할때 "java.lang.OutOfMemoryError: Java heap space"가 발생하는데 이것은 StringBuffer.toString()하는 과정에서 값을 복사하는데 이때 heap메모리가 부족해서 발생하는 오류이다.

이때는 spark-submit에서 --driver-memory 5g처럼 지정하는 메모리를 크게 증가시켜서 -Xmx값을 증가시켜준다.


------------------오류내용------------------------

[2018-02-01 10:12:40,253] [internal.Logging$class] [logError(#70)] [ERROR] Task 0 in stage 20.0 failed 1 times; aborting job
[2018-02-01 10:12:40,267] [internal.Logging$class] [logError(#91)] [ERROR] Error running job streaming job 1517447030000 ms.0
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 20.0 failed 1 times, most recent failure: Lost task 0.0 in stage 20.0 (TID 20, localhost, executor driver): java.lang.OutOfMemoryError: Java heap space
        at java.util.Arrays.copyOfRange(Arrays.java:3664)
        at java.lang.StringBuffer.toString(StringBuffer.java:671)
        at com.pineone.icbms.sda.sf.TripleService.sendTripleFileToHalyard(TripleService.java:500)
        at com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe.sendTriples(AvroOneM2MDataSparkSubscribe.java:296)
        at com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe.access$100(AvroOneM2MDataSparkSubscribe.java:34)
        at com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe$ConsumerT.go(AvroOneM2MDataSparkSubscribe.java:202)
        at com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe$1.call(AvroOneM2MDataSparkSubscribe.java:101)
        at com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe$1.call(AvroOneM2MDataSparkSubscribe.java:93)
        at org.apache.spark.api.java.JavaPairRDD$$anonfun$toScalaFunction$1.apply(JavaPairRDD.scala:1040)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
        at scala.collection.Iterator$$anon$10.next(Iterator.scala:393)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
        at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
        at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
        at scala.collection.AbstractIterator.to(Iterator.scala:1336)
        at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
        at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
        at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
        at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
        at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$29.apply(RDD.scala:1354)
        at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$29.apply(RDD.scala:1354)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1951)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1951)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:99)
        at org.apache.spark.executor.Executor$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$$anonfun$run$1.apply(JobScheduler.scala:256)
        at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
        at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:255)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.OutOfMemoryError: Java heap space
        at java.util.Arrays.copyOfRange(Arrays.java:3664)
        at java.lang.StringBuffer.toString(StringBuffer.java:671)
        at com.pineone.icbms.sda.sf.TripleService.sendTripleFileToHalyard(TripleService.java:500)
        at com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe.sendTriples(AvroOneM2MDataSparkSubscribe.java:296)
        at com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe.access$100(AvroOneM2MDataSparkSubscribe.java:34)
        at com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe$ConsumerT.go(AvroOneM2MDataSparkSubscribe.java:202)
        at com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe$1.call(AvroOneM2MDataSparkSubscribe.java:101)
        at com.pineone.icbms.sda.kafka.onem2m.AvroOneM2MDataSparkSubscribe$1.call(AvroOneM2MDataSparkSubscribe.java:93)
        at org.apache.spark.api.java.JavaPairRDD$$anonfun$toScalaFunction$1.apply(JavaPairRDD.scala:1040)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
        at scala.collection.Iterator$$anon$10.next(Iterator.scala:393)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
        at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
        at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
        at scala.collection.AbstractIterator.to(Iterator.scala:1336)
        at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
        at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
        at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
        at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
        at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$29.apply(RDD.scala:1354)
        at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$29.apply(RDD.scala:1354)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1951)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1951)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:99)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
        ... 3 more

번호 제목 날짜 조회 수
501 Cloudera가 사용하는 서비스별 포트 2018.03.29 421
500 Cloudera가 사용하는 서비스별 디렉토리 2018.03.29 312
499 cloudera-scm-agent 설정파일 위치및 재시작 명령문 2018.03.29 371
498 [CentOS] 네트워크 설정 2018.03.26 290
497 Components of the Impala Server 2018.03.21 318
496 HDFS Balancer설정및 수행 2018.03.21 271
495 hadoop 클러스터 실행 스크립트 정리 2018.03.20 694
494 HA(Namenode, ResourceManager, Kerberos) 및 보안(Zookeeper, Hadoop) 2018.03.16 184
493 자주쓰는 유용한 프로그램 2018.03.16 1377
492 에러 추적(Error Tracking) 및 로그 취합(logging aggregation) 시스템인 Sentry 설치 2018.03.14 233
491 update 샘플 2018.03.12 955
490 이미지 관리 오픈소스 목록 2018.03.11 292
489 Scala에서 countByWindow를 이용하기(예제) 2018.03.08 553
488 Scala를 이용한 Streaming예제 2018.03.08 355
487 scala application 샘플소스(SparkSession이용) 2018.03.07 228
486 fuseki의 endpoint를 이용한 insert, delete하는 sparql예시 2018.02.14 195
485 프로세스를 확인해서 프로세스를 삭제하는 shell script예제(cryptonight) 2018.02.02 383
» spark-submit 실행시 "java.lang.OutOfMemoryError: Java heap space"발생시 조치사항 2018.02.01 616
483 Could not compute split, block input-0-1517397051800 not found형태의 오류가 발생시 조치방법 2018.02.01 310
482 Hadoop의 Datanode를 Decommission하고 나서 HBase의 regionservers파일에 해당 노드명을 지웠는데 여전히 "Dead regionser"로 표시되는 경우 처리 2018.01.25 401
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