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https://issues.apache.org/jira/browse/SPARK-23351?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16363115#comment-16363115
 ] 

Shixiong Zhu commented on SPARK-23351:
--------------------------------------

[~davidahern] It's better to ask the vendor for support. They may have a 
different release cycle.

> checkpoint corruption in long running application
> -------------------------------------------------
>
>                 Key: SPARK-23351
>                 URL: https://issues.apache.org/jira/browse/SPARK-23351
>             Project: Spark
>          Issue Type: Bug
>          Components: Structured Streaming
>    Affects Versions: 2.2.0
>            Reporter: David Ahern
>            Priority: Major
>
> hi, after leaving my (somewhat high volume) Structured Streaming application 
> running for some time, i get the following exception.  The same exception 
> also repeats when i try to restart the application.  The only way to get the 
> application back running is to clear the checkpoint directory which is far 
> from ideal.
> Maybe a stream is not being flushed/closed properly internally by Spark when 
> checkpointing?
>  
>  User class threw exception: 
> org.apache.spark.sql.streaming.StreamingQueryException: Job aborted due to 
> stage failure: Task 55 in stage 1.0 failed 4 times, most recent failure: Lost 
> task 55.3 in stage 1.0 (TID 240, gbslixaacspa04u.metis.prd, executor 2): 
> java.io.EOFException
>  at java.io.DataInputStream.readInt(DataInputStream.java:392)
>  at 
> org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider.org$apache$spark$sql$execution$streaming$state$HDFSBackedStateStoreProvider$$readSnapshotFile(HDFSBackedStateStoreProvider.scala:481)
>  at 
> org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider$$anonfun$org$apache$spark$sql$execution$streaming$state$HDFSBackedStateStoreProvider$$loadMap$1.apply(HDFSBackedStateStoreProvider.scala:359)
>  at 
> org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider$$anonfun$org$apache$spark$sql$execution$streaming$state$HDFSBackedStateStoreProvider$$loadMap$1.apply(HDFSBackedStateStoreProvider.scala:358)
>  at scala.Option.getOrElse(Option.scala:121)
>  at 
> org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider.org$apache$spark$sql$execution$streaming$state$HDFSBackedStateStoreProvider$$loadMap(HDFSBackedStateStoreProvider.scala:358)
>  at 
> org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider.getStore(HDFSBackedStateStoreProvider.scala:265)
>  at 
> org.apache.spark.sql.execution.streaming.state.StateStore$.get(StateStore.scala:200)
>  at 
> org.apache.spark.sql.execution.streaming.state.StateStoreRDD.compute(StateStoreRDD.scala:61)
>  at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
>  at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
>  at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>  at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
>  at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
>  at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>  at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
>  at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
>  at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
>  at org.apache.spark.scheduler.Task.run(Task.scala:108)
>  at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
>  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)



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