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From "Alexander (JIRA)" <j...@apache.org>
Subject [jira] [Created] (KYLIN-3824) Spark - Extract Fact Table Distinct Columns step causes java.lang.OutOfMemoryError: Java heap space
Date Fri, 22 Feb 2019 13:17:00 GMT
Alexander created KYLIN-3824:
--------------------------------

             Summary: Spark - Extract Fact Table Distinct Columns step causes java.lang.OutOfMemoryError:
Java heap space
                 Key: KYLIN-3824
                 URL: https://issues.apache.org/jira/browse/KYLIN-3824
             Project: Kylin
          Issue Type: Bug
          Components: Spark Engine
    Affects Versions: v2.6.1
         Environment: CentOS 7
3 workers and 1 master.
4 cpu, 16GB RAM each
            Reporter: Alexander


Try to build huge cube on weak envirment.

Environment:

Cluster with 3 nodes.

Max AM container size - 5GB.

 

kylin_intermediate table ~500 files of size started from 4kb up to 300mb.

 

When spark job executor take file larger than ~70MB on step mapPartitionsToPair (194) it
got exception:

2019-02-21 20:29:40 ERROR SparkUncaughtExceptionHandler:91 - [Container in shutdown] Uncaught
exception in thread Thread[Executor task launch worker for task 1,5,main]
java.lang.OutOfMemoryError: Java heap space
 at java.util.Arrays.copyOfRange(Arrays.java:3664)
 at java.lang.String.<init>(String.java:207)
 at java.lang.String.substring(String.java:1969)
 at java.lang.String.split(String.java:2353)
 at java.lang.String.split(String.java:2422)
 at org.apache.kylin.engine.spark.SparkUtil$1.call(SparkUtil.java:164)
 at org.apache.kylin.engine.spark.SparkUtil$1.call(SparkUtil.java:160)
 at org.apache.spark.api.java.JavaPairRDD$$anonfun$toScalaFunction$1.apply(JavaPairRDD.scala:1040)
 at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
 at scala.collection.convert.Wrappers$IteratorWrapper.next(Wrappers.scala:31)
 at com.google.common.collect.Lists.newArrayList(Lists.java:145)
 at org.apache.kylin.engine.spark.SparkFactDistinct$FlatOutputFucntion.call(SparkFactDistinct.java:313)
 at org.apache.kylin.engine.spark.SparkFactDistinct$FlatOutputFucntion.call(SparkFactDistinct.java:239)
 at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186)
 at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186)
 at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
 at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
 at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
 at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
 at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
 at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
 at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
 at org.apache.spark.scheduler.Task.run(Task.scala:109)
 at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
 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)

 

 

 



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