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https://issues.apache.org/jira/browse/SPARK-34788?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17572536#comment-17572536
 ] 

wenweijian commented on SPARK-34788:
------------------------------------

I can reproduce it. 

If the performance impact of the proposal (SyncFailedException) is little, I 
think it is worth fixing

> Spark throws FileNotFoundException instead of IOException when disk is full
> ---------------------------------------------------------------------------
>
>                 Key: SPARK-34788
>                 URL: https://issues.apache.org/jira/browse/SPARK-34788
>             Project: Spark
>          Issue Type: Improvement
>          Components: Shuffle, Spark Core
>    Affects Versions: 3.2.0
>            Reporter: wuyi
>            Priority: Major
>
> When the disk is full, Spark throws FileNotFoundException instead of 
> IOException with the hint. It's quite a confusing error to users:
> {code:java}
> 9/03/26 09:03:45 ERROR ShuffleBlockFetcherIterator: Failed to create input 
> stream from local block
> java.io.IOException: Error in reading 
> FileSegmentManagedBuffer{file=/local_disk0/spark-c2f26f02-2572-4764-815a-cbba65ddb315/executor-b4b76a4c-788c-4cb6-b904-664a883be1aa/blockmgr-36804371-24fe-4131-a3dc-00b7f98f3a3e/11/shuffle_113_1029_0.data,
>  offset=110254956, length=1875458}
>       at 
> org.apache.spark.network.buffer.FileSegmentManagedBuffer.createInputStream(FileSegmentManagedBuffer.java:111)
>       at 
> org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:442)
>       at 
> org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:64)
>       at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
>       at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
>       at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
>       at 
> org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)
>       at 
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
>       at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
>       at 
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.sort_addToSorter_0$(Unknown
>  Source)
>       at 
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.processNext(Unknown
>  Source)
>       at 
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
>       at 
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$11$$anon$1.hasNext(WholeStageCodegenExec.scala:622)
>       at 
> org.apache.spark.sql.execution.aggregate.SortAggregateExec$$anonfun$doExecute$1$$anonfun$3.apply(SortAggregateExec.scala:98)
>       at 
> org.apache.spark.sql.execution.aggregate.SortAggregateExec$$anonfun$doExecute$1$$anonfun$3.apply(SortAggregateExec.scala:95)
>       at 
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$12.apply(RDD.scala:839)
>       at 
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$12.apply(RDD.scala:839)
>       at 
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
>       at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:340)
>       at org.apache.spark.rdd.RDD.iterator(RDD.scala:304)
>       at 
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
>       at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:340)
>       at org.apache.spark.rdd.RDD.iterator(RDD.scala:304)
>       at 
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
>       at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:340)
>       at org.apache.spark.rdd.RDD.iterator(RDD.scala:304)
>       at 
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
>       at 
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
>       at org.apache.spark.scheduler.Task.doRunTask(Task.scala:139)
>       at org.apache.spark.scheduler.Task.run(Task.scala:112)
>       at 
> org.apache.spark.executor.Executor$TaskRunner$$anonfun$13.apply(Executor.scala:497)
>       at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1432)
>       at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:503)
>       at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
>       at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
>       at java.lang.Thread.run(Thread.java:748)
> Caused by: java.io.FileNotFoundException: 
> /local_disk0/spark-c2f26f02-2572-4764-815a-cbba65ddb315/executor-b4b76a4c-788c-4cb6-b904-664a883be1aa/blockmgr-36804371-24fe-4131-a3dc-00b7f98f3a3e/11/shuffle_113_1029_0.data
>  (No such file or directory)
>       at java.io.FileInputStream.open0(Native Method)
>       at java.io.FileInputStream.open(FileInputStream.java:195)
>       at java.io.FileInputStream.<init>(FileInputStream.java:138)
>       at 
> org.apache.spark.network.buffer.FileSegmentManagedBuffer.createInputStream(FileSegmentManagedBuffer.java:100)
>       ... 35 more{code}
> (The cause only says the file is not found, but we believe it's highly 
> possible due to the disk full issue after investigation.)
> And there's probably a way to detect the disk full: when we get 
> `FileNotFoundException`, we try 
> [http://weblog.janek.org/Archive/2004/12/20/ExceptionWhenWritingToAFu.html] 
> to see if SyncFailedException throws. If SyncFailedException throws, then we 
> throw IOException with the disk full hint.



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