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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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516 Cloudera의 API를 이용하여 impala의 실행되었던 쿼리 확인하는 예시 2018.05.03 10859
515 Toree 0.1.0-incubating이 Scala 2.10.4까지만 지원하게 되어서 발생하는 NoSuchMethod오류 문제 해결방법(scala 2.11.x을 지원하지만 오류가 발생할 수 있음) 2018.04.20 4019
514 우분투 16.04LTS에 Zeppelin 0.7.3설치 2018.04.18 4481
513 CentOS 7.x에 Jupyter설치 2018.04.18 5447
512 Apache Toree설치(Jupyter에서 Scala, PySpark, SparkR, SQL을 사용할 수 있도록 하는 Kernel) 2018.04.17 4161
511 우분투 16.04LTS에 Jupyter설치 2018.04.17 4613
510 beeline으로 접근시 "User: gooper is not allowed to impersonate anonymous (state=08S01,code=0)"가 발생하면서 "No current connection"이 발생하는 경우 조치 2018.04.15 4303
509 Cloudera Manager 5.x설치시 embedded postgresql를 사용하는 경우의 관리정보 2018.04.13 3777
508 jupyter, zeppelin, rstudio를 이용하여 spark cluster에 job를 실행시키기 위한 정보 2018.04.13 9360
507 Cloudera Manager web UI의 언어를 한글에서 영문으로 변경하기 2018.04.03 4150
506 [우분투] suppoie 채굴 프로세스 발생시 자동으로 삭제하는 shell프로그램 2018.04.01 4677
505 Impala daemon기동시 "Could not create temporary timezone file"오류 발생시 조치사항 2018.03.29 4750
504 각 서버에 설치되는 cloudera서비스 프로그램 목록(CDH 5.14.0의 경우) 2018.03.29 3567
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 4276
502 Cloudera설치중에 "Error, CM server guid updated"오류 발생시 조치방법 2018.03.29 3213
501 Cloudera가 사용하는 서비스별 포트 2018.03.29 4012
500 Cloudera가 사용하는 서비스별 디렉토리 2018.03.29 3941
499 cloudera-scm-agent 설정파일 위치및 재시작 명령문 2018.03.29 4516
498 [CentOS] 네트워크 설정 2018.03.26 3634
497 Components of the Impala Server 2018.03.21 3591
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