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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

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509 Cloudera Manager 5.x설치시 embedded postgresql를 사용하는 경우의 관리정보 2018.04.13 1593
508 jupyter, zeppelin, rstudio를 이용하여 spark cluster에 job를 실행시키기 위한 정보 2018.04.13 5096
507 Cloudera Manager web UI의 언어를 한글에서 영문으로 변경하기 2018.04.03 2358
506 [우분투] suppoie 채굴 프로세스 발생시 자동으로 삭제하는 shell프로그램 2018.04.01 1935
505 Impala daemon기동시 "Could not create temporary timezone file"오류 발생시 조치사항 2018.03.29 2269
504 각 서버에 설치되는 cloudera서비스 프로그램 목록(CDH 5.14.0의 경우) 2018.03.29 1692
503 Cloudera설치중 실패로 여러번 설치하는 과정에 "Running in non-interactive mode, and data appears to exist in Storage Directory /dfs/nn. Not formatting." 오류가 발생시 조치하는 방법 2018.03.29 1987
502 Cloudera설치중에 "Error, CM server guid updated"오류 발생시 조치방법 2018.03.29 1163
501 Cloudera가 사용하는 서비스별 포트 2018.03.29 2051
500 Cloudera가 사용하는 서비스별 디렉토리 2018.03.29 1758
499 cloudera-scm-agent 설정파일 위치및 재시작 명령문 2018.03.29 2017
498 [CentOS] 네트워크 설정 2018.03.26 1695
497 Components of the Impala Server 2018.03.21 1776
496 HDFS Balancer설정및 수행 2018.03.21 1668
495 hadoop 클러스터 실행 스크립트 정리 2018.03.20 2989
494 HA(Namenode, ResourceManager, Kerberos) 및 보안(Zookeeper, Hadoop) 2018.03.16 1215
493 자주쓰는 유용한 프로그램 2018.03.16 2754
492 에러 추적(Error Tracking) 및 로그 취합(logging aggregation) 시스템인 Sentry 설치 2018.03.14 1427
491 update 샘플 2018.03.12 2584
490 이미지 관리 오픈소스 목록 2018.03.11 1763
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