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Posted to issues@kylin.apache.org by "Alexander (JIRA)" <ji...@apache.org> on 2019/02/22 13:17:00 UTC
[jira] [Created] (KYLIN-3824) Spark - Extract Fact Table Distinct
Columns step causes java.lang.OutOfMemoryError: Java heap space
Alexander created KYLIN-3824:
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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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