[
https://issues.apache.org/jira/browse/HIVE-8300?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14152807#comment-14152807
]
Xuefu Zhang commented on HIVE-8300:
-----------------------------------
Thanks, Brock. I verified locally that the attached patch fixed the issue in
Spark standalone mode.
> Missing guava lib causes IllegalStateException when deserializing a task
> [Spark Branch]
> ---------------------------------------------------------------------------------------
>
> Key: HIVE-8300
> URL: https://issues.apache.org/jira/browse/HIVE-8300
> Project: Hive
> Issue Type: Bug
> Components: Spark
> Environment: Spark-1.2.0-SNAPSHOT
> Reporter: Rui Li
> Attachments: HIVE-8300.1-spark.patch
>
>
> In spark-1.2, we have guava shaded in spark-assembly. And we only ship
> hive-exec to spark cluster. So spark executor won't have (original) guava in
> its class path.
> This can cause some problem when TaskRunner deserializes a task, and throws
> something like this:
> {code}
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
> stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0
> (TID 3, node13-1): java.lang.IllegalStateException: unread block data
>
> java.io.ObjectInputStream$BlockDataInputStream.setBlockDataMode(ObjectInputStream.java:2421)
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1382)
>
> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)
>
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
> java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
>
> org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:62)
>
> org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:87)
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:164)
>
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> java.lang.Thread.run(Thread.java:744)
> {code}
> We may have to verify this issue and ship guava to spark cluster.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
