[jira] [Created] (SPARK-39152) StreamCorruptedException cause job failure for disk persisted RDD

["Attila Zsolt Piros (Jira)" <ji...@apache.org>]

Attila Zsolt Piros created SPARK-39152:
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             Summary: StreamCorruptedException cause job failure for disk persisted RDD
                 Key: SPARK-39152
                 URL: https://issues.apache.org/jira/browse/SPARK-39152
             Project: Spark
          Issue Type: Improvement
          Components: Block Manager
    Affects Versions: 3.4.0
            Reporter: Attila Zsolt Piros
            Assignee: Attila Zsolt Piros


In case of a disk corruption a disk persisted RDD block will lead to job failure as the block registration is always leads to the same file. So even when the task is rescheduled on a different executor the job will fail.

*Example*

First failure (the block is locally available):
{noformat}
22/04/25 07:15:28 ERROR executor.Executor: Exception in task 17024.0 in stage 12.0 (TID 51853)
java.io.StreamCorruptedException: invalid stream header: 00000000
  at java.io.ObjectInputStream.readStreamHeader(ObjectInputStream.java:943)
  at java.io.ObjectInputStream.<init>(ObjectInputStream.java:401)
  at org.apache.spark.serializer.JavaDeserializationStream$$anon$1.<init>(JavaSerializer.scala:63)
  at org.apache.spark.serializer.JavaDeserializationStream.<init>(JavaSerializer.scala:63)
  at org.apache.spark.serializer.JavaSerializerInstance.deserializeStream(JavaSerializer.scala:122)
  at org.apache.spark.serializer.SerializerManager.dataDeserializeStream(SerializerManager.scala:209)
  at org.apache.spark.storage.BlockManager.getLocalValues(BlockManager.scala:617)
  at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:897)
  at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335)
  at org.apache.spark.rdd.RDD.iterator(RDD.scala:286)
  at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
{noformat}

Then the task might be rescheduled on a different executor but as the block is registered to the first blockmanager the error will be the same:

{noformat}
java.io.StreamCorruptedException: invalid stream header: 00000000
  at java.io.ObjectInputStream.readStreamHeader(ObjectInputStream.java:943)
  at java.io.ObjectInputStream.<init>(ObjectInputStream.java:401)
  at org.apache.spark.serializer.JavaDeserializationStream$$anon$1.<init>(JavaSerializer.scala:63)
  at org.apache.spark.serializer.JavaDeserializationStream.<init>(JavaSerializer.scala:63)
  at org.apache.spark.serializer.JavaSerializerInstance.deserializeStream(JavaSerializer.scala:122)
  at org.apache.spark.serializer.SerializerManager.dataDeserializeStream(SerializerManager.scala:209)
  at org.apache.spark.storage.BlockManager$$anonfun$getRemoteValues$1.apply(BlockManager.scala:698)
  at org.apache.spark.storage.BlockManager$$anonfun$getRemoteValues$1.apply(BlockManager.scala:696)
  at scala.Option.map(Option.scala:146)
  at org.apache.spark.storage.BlockManager.getRemoteValues(BlockManager.scala:696)
  at org.apache.spark.storage.BlockManager.get(BlockManager.scala:831)
  at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:886)
  at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335)
{noformat}

My idea is to retry the IO operations a few times and when all of them failed deregistering the block and let the following task to recompute it.



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