Imran Rashid created SPARK-24309:
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Summary: AsyncEventQueue should handle an interrupt from a Listener
Key: SPARK-24309
URL: https://issues.apache.org/jira/browse/SPARK-24309
Project: Spark
Issue Type: Bug
Components: Scheduler, Spark Core
Affects Versions: 2.3.0
Reporter: Imran Rashid
AsyncEventQueue does not properly handle an interrupt from a Listener -- the
spark app won't even stop!
I observed this on an actual workload as the EventLoggingListener can generate
an interrupt from the underlying hdfs calls:
{noformat}
18/05/16 17:46:36 WARN hdfs.DFSClient: Error transferring data from
DatanodeInfoWithStorage[10.17.206.36:20002,DS-3adac910-5d0a-418b-b0f7-6332b35bf6a1,DISK]
to
DatanodeInfoWithStorage[10.17.206.42:20002,DS-2e7ed0aa-0e68-441e-b5b2-96ad4a9ce7a5,DISK]:
100000 millis timeout while waiting for channel to be ready for read. ch :
java.nio.channels.SocketChannel[connected local=/10.17.206.35:33950
remote=/10.17.206.36:20002]
18/05/16 17:46:36 WARN hdfs.DFSClient: DataStreamer Exception
java.net.SocketTimeoutException: 100000 millis timeout while waiting for
channel to be ready for read. ch : java.nio.channels.SocketChannel[connected
local=/10.17.206.35:33950 remote=/10.17.206.36:20002]
at
org.apache.hadoop.net.SocketIOWithTimeout.doIO(SocketIOWithTimeout.java:164)
at
org.apache.hadoop.net.SocketInputStream.read(SocketInputStream.java:161)
at
org.apache.hadoop.net.SocketInputStream.read(SocketInputStream.java:131)
at
org.apache.hadoop.net.SocketInputStream.read(SocketInputStream.java:118)
at java.io.FilterInputStream.read(FilterInputStream.java:83)
at java.io.FilterInputStream.read(FilterInputStream.java:83)
at
org.apache.hadoop.hdfs.protocolPB.PBHelper.vintPrefixed(PBHelper.java:2305)
at
org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer$StreamerStreams.sendTransferBlock(DFSOutputStream.java:516)
at
org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.transfer(DFSOutputStream.java:1450)
at
org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.addDatanode2ExistingPipeline(DFSOutputStream.java:1408)
at
org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.setupPipelineForAppendOrRecovery(DFSOutputStream.java:1559)
at
org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.processDatanodeError(DFSOutputStream.java:1254)
at
org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:739)
18/05/16 17:46:36 ERROR scheduler.AsyncEventQueue: Listener
EventLoggingListener threw an exception
[... a few more of these ...]
18/05/16 17:46:36 INFO scheduler.AsyncEventQueue: Stopping listener queue
eventLog.
java.lang.InterruptedException
at
java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireInterruptibly(AbstractQueuedSynchronizer.java:1220)
at
java.util.concurrent.locks.ReentrantLock.lockInterruptibly(ReentrantLock.java:335)
at
java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:439)
at
org.apache.spark.scheduler.AsyncEventQueue$$anonfun$org$apache$spark$scheduler$AsyncEventQueue$$dispatch$1.apply(AsyncEventQueue.scala:94)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at
org.apache.spark.scheduler.AsyncEventQueue.org$apache$spark$scheduler$AsyncEventQueue$$dispatch(AsyncEventQueue.scala:83)
at
org.apache.spark.scheduler.AsyncEventQueue$$anon$1$$anonfun$run$1.apply$mcV$sp(AsyncEventQueue.scala:79)
at org.apache.spark.util.Utils$.tryOrStopSparkContext(Utils.scala:1319)
at
org.apache.spark.scheduler.AsyncEventQueue$$anon$1.run(AsyncEventQueue.scala:78)
{noformat}
When this happens, the AsyncEventQueue will continue to pile up events in its
queue, though its no longer processing them. And then in the call to stop,
it'll block on {{queue.put(POISON_PILL)}} forever, so the SparkContext won't
stop.
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