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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-21744) Add retry logic when create new broadcast
Date Mon, 28 Aug 2017 16:55:06 GMT

     [ https://issues.apache.org/jira/browse/SPARK-21744?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-21744:
------------------------------------

    Assignee:     (was: Apache Spark)

> Add retry logic when create new broadcast
> -----------------------------------------
>
>                 Key: SPARK-21744
>                 URL: https://issues.apache.org/jira/browse/SPARK-21744
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core
>    Affects Versions: 1.6.1, 2.1.0, 2.2.0
>            Reporter: zhoukang
>            Priority: Minor
>
> When driver submit new stage and there is a bad disk before spark,then driver may will
exit caused by exception below:
> {code:java}
> Job aborted due to stage failure: Task serialization failed: java.io.IOException: Failed
to create local dir in /home/work/hdd5/yarn/xxx/appcache/application_1463372393999_144979/blockmgr-1f96b724-3e16-4c09-8601-1a2e3b758185/3b.
> org.apache.spark.storage.DiskBlockManager.getFile(DiskBlockManager.scala:73)
> org.apache.spark.storage.DiskStore.contains(DiskStore.scala:173)
> org.apache.spark.storage.BlockManager.org$apache$spark$storage$BlockManager$$getCurrentBlockStatus(BlockManager.scala:391)
> org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:801)
> org.apache.spark.storage.BlockManager.putIterator(BlockManager.scala:629)
> org.apache.spark.storage.BlockManager.putSingle(BlockManager.scala:987)
> org.apache.spark.broadcast.TorrentBroadcast.writeBlocks(TorrentBroadcast.scala:99)
> org.apache.spark.broadcast.TorrentBroadcast.<init>(TorrentBroadcast.scala:85)
> org.apache.spark.broadcast.TorrentBroadcastFactory.newBroadcast(TorrentBroadcastFactory.scala:34)
> org.apache.spark.broadcast.BroadcastManager.newBroadcast(BroadcastManager.scala:63)
> org.apache.spark.SparkContext.broadcast(SparkContext.scala:1332)
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:863)
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskCompletion$14$$anonfun$apply$1.apply$mcVI$sp(DAGScheduler.scala:1090)
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskCompletion$14$$anonfun$apply$1.apply(DAGScheduler.scala:1086)
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskCompletion$14$$anonfun$apply$1.apply(DAGScheduler.scala:1086)
> scala.Option.foreach(Option.scala:236)
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskCompletion$14.apply(DAGScheduler.scala:1086)
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskCompletion$14.apply(DAGScheduler.scala:1085)
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:1085)
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1528)
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1493)
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1482)
> org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> {code}
> We can add retry logic when create broadcast to lower the probability of this scenario
occurrence。And there is no side-effect for normal scenario.



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