[SPARK-22760] where driver is stopping, and some executors lost because of YarnSchedulerBackend.stop, then there is a problem.

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Won't Fix
• Affects Version/s: 2.2.1
• Component/s: Spark Core, YARN
• Assignee: Unassigned
• Reporter: KaiXinXIaoLei
• Created: 12/Dec/17 01:21
• Updated: 12/Feb/19 21:20
• Resolved: 12/Feb/19 21:20

Description

Using SPARK-14228 , i still find a problem:

17/12/12 15:34:45 INFO YarnClientSchedulerBackend: Asking each executor to shut down
17/12/12 15:34:45 INFO YarnClientSchedulerBackend: Disabling executor 63.
17/12/12 15:34:45 ERROR Inbox: Ignoring error
org.apache.spark.SparkException: Could not find CoarseGrainedScheduler or it has been stopped.
	at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:163)
	at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:133)
	at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:192)
	at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:516)
	at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.reviveOffers(CoarseGrainedSchedulerBackend.scala:356)
	at org.apache.spark.scheduler.TaskSchedulerImpl.executorLost(TaskSchedulerImpl.scala:497)
	at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint.disableExecutor(CoarseGrainedSchedulerBackend.scala:301)
	at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnDriverEndpoint$$anonfun$onDisconnected$1.apply(YarnSchedulerBackend.scala:121)
	at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnDriverEndpoint$$anonfun$onDisconnected$1.apply(YarnSchedulerBackend.scala:120)
	at scala.Option.foreach(Option.scala:236)
	at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnDriverEndpoint.onDisconnected(YarnSchedulerBackend.scala:120)
	at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:142)
	at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:204)
	at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:100)
	at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:217)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
	at java.lang.Thread.run(Thread.java:745)

and sometimes, the below problem is also exists:

17/12/11 15:50:53 INFO YarnClientSchedulerBackend: Stopped
17/12/11 15:50:53 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
17/12/11 15:50:53 ERROR Inbox: Ignoring error
org.apache.spark.SparkException: Unsupported message OneWayMessage(101.8.73.53:42930,RemoveExecutor(68,Executor for container container_e05_1512975871311_0007_01_000069 exited because of a YARN event (e.g., pre-emption) and not because of an error in the running job.)) from 101.8.73.53:42930
        at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1$$anonfun$apply$mcV$sp$2.apply(Inbox.scala:118)
        at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1$$anonfun$apply$mcV$sp$2.apply(Inbox.scala:117)
        at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anonfun$receive$1.applyOrElse(CoarseGrainedSchedulerBackend.scala:126)
        at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:117)
        at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:205)
        at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:101)
        at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:213)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)
org.apache.spark.SparkException: Could not find CoarseGrainedScheduler.
        at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:154)
        at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:134)
        at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:186)
        at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:512)
        at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint$$anonfun$org$apache$spark$scheduler$cluster$YarnSchedulerBackend$$handleExecutorDisconnectedFromDriver$1.apply(YarnSchedulerBackend.scala:255)
        at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint$$anonfun$org$apache$spark$scheduler$cluster$YarnSchedulerBackend$$handleExecutorDisconnectedFromDriver$1.apply(YarnSchedulerBackend.scala:255)
        at scala.util.Success.foreach(Try.scala:236)
        at scala.concurrent.Future$$anonfun$foreach$1.apply(Future.scala:206)
        at scala.concurrent.Future$$anonfun$foreach$1.apply(Future.scala:206)

I analysis this reason. When the number of executors is big, and YarnSchedulerBackend.stopped=False after YarnSchedulerBackend.stop() is running, some executor is stopped, and YarnSchedulerBackend.onDisconnected() will be called, then the problem is exists

Issue Links

• links to: [Github] Pull Request #19945 (KaiXinXiaoLei)
• links to: [Github] Pull Request #19951 (KaiXinXiaoLei)