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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2017/11/29 16:25:00 UTC
[jira] [Resolved] (SPARK-22622) OutOfMemory thrown by Closure
Serializer without proper failure propagation
[ https://issues.apache.org/jira/browse/SPARK-22622?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-22622.
-------------------------------
Resolution: Duplicate
It looks like, nevertheless, something huge is in your closure. It's probably not the data you think you're broadcasting. This is then at best part of SPARK-6235.
This error would kill the driver process, unless you are trying to recover it. You'd have to post more detail about what you see.
> OutOfMemory thrown by Closure Serializer without proper failure propagation
> ---------------------------------------------------------------------------
>
> Key: SPARK-22622
> URL: https://issues.apache.org/jira/browse/SPARK-22622
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.2.0
> Environment: Spark 2.2.0
> Hadoop 2.9.0
> Reporter: Raghavendra
> Priority: Critical
>
> While moving from a Stage to another, the Closure serializer is trying to Serialize the Closures and throwing OOMs.
> This is happening when the RDD size crosses 70 GB.
> I set the Driver Memory to 225 GB and yet the error persist.
> There are two issues here
> * OOM thrown when there is almost 3 times of Driver memory provided than the last Stage RDD size.(Even tried caching this into the disk before moving it into the current stage)
> * After the Error is thrown, the Spark Job does not exit. it just continues in the same state without propagating the error into the Spark UI.
> *Scenario 1*
> {color:red}Exception in thread "dag-scheduler-event-loop" java.lang.OutOfMemoryError: Requested array size exceeds VM limit
> at java.util.Arrays.copyOf(Arrays.java:3236)
> at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
> at java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
> at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
> at org.apache.spark.util.ByteBufferOutputStream.write(ByteBufferOutputStream.scala:41)
> at java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
> at java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1786)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1189)
> at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
> at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:43)
> at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
> at org.apache.spark.scheduler.DAGScheduler.submitMissingTasks(DAGScheduler.scala:1003)
> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:930)
> at org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:874)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1677)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> {color}
> *Scenario 2*
> {color:red}
> Exception in thread "dag-scheduler-event-loop" java.lang.OutOfMemoryError
> at java.io.ByteArrayOutputStream.hugeCapacity(ByteArrayOutputStream.java:123)
> at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:117)
> at java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
> at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
> at org.apache.spark.util.ByteBufferOutputStream.write(ByteBufferOutputStream.scala:41)
> at java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
> at java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1786)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1189)
> at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
> at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:43)
> at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
> at org.apache.spark.scheduler.DAGScheduler.submitMissingTasks(DAGScheduler.scala:1003)
> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:930)
> at org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:874)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1677)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> {color}
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