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Posted to issues@spark.apache.org by "Shixiong Zhu (JIRA)" <ji...@apache.org> on 2016/01/28 19:45:39 UTC
[jira] [Commented] (SPARK-10251) Some internal spark classes are
not registered with kryo
[ https://issues.apache.org/jira/browse/SPARK-10251?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15122076#comment-15122076 ]
Shixiong Zhu commented on SPARK-10251:
--------------------------------------
Current KryoSerializer doesn't provide an approach for other projects (e.g. Streaming) registering their classes (e.g. OpenHashMapBasedStateMap introduced in 1.6). So spark.kryo.registrationRequired cannot be enabled in a Streaming app.
Maybe we should add some internal configuration for that?
> Some internal spark classes are not registered with kryo
> --------------------------------------------------------
>
> Key: SPARK-10251
> URL: https://issues.apache.org/jira/browse/SPARK-10251
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.4.1
> Reporter: Soren Macbeth
> Assignee: Ram Sriharsha
> Fix For: 1.6.0
>
>
> When running a job using kryo serialization and setting `spark.kryo.registrationRequired=true` some internal classes are not registered, causing the job to die. This is still a problem when this setting is false (which is the default) because it makes the space required to store serialized objects in memory or disk much much more expensive in terms of runtime and storage space.
> {code}
> 15/08/25 20:28:21 WARN spark.scheduler.TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, a.b.c.d): java.lang.IllegalArgumentException: Class is not registered: scala.Tuple2[]
> Note: To register this class use: kryo.register(scala.Tuple2[].class);
> at com.esotericsoftware.kryo.Kryo.getRegistration(Kryo.java:442)
> at com.esotericsoftware.kryo.util.DefaultClassResolver.writeClass(DefaultClassResolver.java:79)
> at com.esotericsoftware.kryo.Kryo.writeClass(Kryo.java:472)
> at com.esotericsoftware.kryo.Kryo.writeClassAndObject(Kryo.java:565)
> at org.apache.spark.serializer.KryoSerializerInstance.serialize(KryoSerializer.scala:250)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:236)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> {code}
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