spark-instrumented-optimizer/resource-managers
Devaraj K 51066b437b [SPARK-14228][CORE][YARN] Lost executor of RPC disassociated, and occurs exception: Could not find CoarseGrainedScheduler or it has been stopped
## What changes were proposed in this pull request?
I see the two instances where the exception is occurring.

**Instance 1:**

```
17/11/10 15:49:32 ERROR util.Utils: Uncaught exception in thread driver-revive-thread
org.apache.spark.SparkException: Could not find CoarseGrainedScheduler.
        at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:160)
        at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:140)
        at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:187)
        at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:521)
        at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(CoarseGrainedSchedulerBackend.scala:125)
        at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(CoarseGrainedSchedulerBackend.scala:125)
        at scala.Option.foreach(Option.scala:257)
        at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anon$1$$anonfun$run$1.apply$mcV$sp(CoarseGrainedSchedulerBackend.scala:125)
        at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1344)
        at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anon$1.run(CoarseGrainedSchedulerBackend.scala:124)
        at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
        at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
        at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
        at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
        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)
```

In CoarseGrainedSchedulerBackend.scala, driver-revive-thread starts with DriverEndpoint.onStart() and keeps sending the ReviveOffers messages periodically till it gets shutdown as part DriverEndpoint.onStop(). There is no proper coordination between the driver-revive-thread(shutdown) and the RpcEndpoint unregister, RpcEndpoint unregister happens first and then driver-revive-thread shuts down as part of DriverEndpoint.onStop(), In-between driver-revive-thread may try to send the ReviveOffers message which is leading to the above exception.

To fix this issue, this PR moves the shutting down of driver-revive-thread to CoarseGrainedSchedulerBackend.stop() which executes before the DriverEndpoint unregister.

**Instance 2:**

```
17/11/10 16:31:38 ERROR cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Error requesting driver to remove executor 1 for reason Executor for container container_1508535467865_0226_01_000002 exited because of a YARN event (e.g., pre-emption) and not because of an error in the running job.
org.apache.spark.SparkException: Could not find CoarseGrainedScheduler.
        at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:160)
        at org.apache.spark.rpc.netty.Dispatcher.postLocalMessage(Dispatcher.scala:135)
        at org.apache.spark.rpc.netty.NettyRpcEnv.ask(NettyRpcEnv.scala:229)
        at org.apache.spark.rpc.netty.NettyRpcEndpointRef.ask(NettyRpcEnv.scala:516)
        at org.apache.spark.rpc.RpcEndpointRef.ask(RpcEndpointRef.scala:63)
        at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint$$anonfun$receive$1.applyOrElse(YarnSchedulerBackend.scala:269)
        at org.apache.spark.rpc.netty.Inbox$$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:221)
        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)
```

Here YarnDriverEndpoint tries to send remove executor messages after the Yarn scheduler backend service stop, which is leading to the above exception. To avoid the above exception,
1) We may add a condition(which checks whether service has stopped or not) before sending executor remove message
2) Add a warn log message in onFailure case when the service is already stopped

In this PR, chosen the 2) option which adds a log message in the case of onFailure without the exception stack trace since the option 1) would need to to go through for every remove executor message.

## How was this patch tested?
I verified it manually, I don't see these exceptions with the PR changes.

Author: Devaraj K <devaraj@apache.org>

Closes #19741 from devaraj-kavali/SPARK-14228.
2017-12-06 10:39:15 -08:00
..
kubernetes/core [SPARK-14228][CORE][YARN] Lost executor of RPC disassociated, and occurs exception: Could not find CoarseGrainedScheduler or it has been stopped 2017-12-06 10:39:15 -08:00
mesos [SPARK-18935][MESOS] Fix dynamic reservations on mesos 2017-11-29 14:15:35 -08:00
yarn [SPARK-14228][CORE][YARN] Lost executor of RPC disassociated, and occurs exception: Could not find CoarseGrainedScheduler or it has been stopped 2017-12-06 10:39:15 -08:00