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https://issues.apache.org/jira/browse/SPARK-10251?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14738390#comment-14738390
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Marius Soutier commented on SPARK-10251:
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Any chance for a backport to 1.4.2?
> 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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