liupengcheng created SPARK-26689:
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Summary: Bad disk causing broadcast failure
Key: SPARK-26689
URL: https://issues.apache.org/jira/browse/SPARK-26689
Project: Spark
Issue Type: Bug
Components: Spark Core
Affects Versions: 2.4.0, 2.1.0
Environment: Spark on Yarn
Mutliple Disk
Reporter: liupengcheng
We encoutered an application failure in our production cluster which caused by
the bad disk problems. It will incur application failure.
{code:java}
Job aborted due to stage failure: Task serialization failed:
java.io.IOException: Failed to create local dir in
/home/work/hdd5/yarn/c3prc-hadoop/nodemanager/usercache/h_user_profile/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 have multiple disk on our cluster nodes, however, it still fails. I think
it's because spark does not handle bad disk in `DiskBlockManager` currently.
Actually, we can handle bad disk in multiple disk environment to avoid
application failure.
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