[jira] [Created] (HIVE-8300) Missing guava lib causes IllegalStateException when deserializing a task [Spark Branch]

["Rui Li (JIRA)" <ji...@apache.org>]

Rui Li created HIVE-8300:
----------------------------

             Summary: 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


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.



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