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Posted to issues@spark.apache.org by "Shixiong Zhu (JIRA)" <ji...@apache.org> on 2018/02/08 21:58:00 UTC
[jira] [Commented] (SPARK-23351) checkpoint corruption in long
running application
[ https://issues.apache.org/jira/browse/SPARK-23351?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16357629#comment-16357629 ]
Shixiong Zhu commented on SPARK-23351:
--------------------------------------
What's your file system? HDFS?
> 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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