Mamdouh Alramadan created SPARK-10638:
-----------------------------------------
Summary: spark streaming stop gracefully keeps the spark context
Key: SPARK-10638
URL: https://issues.apache.org/jira/browse/SPARK-10638
Project: Spark
Issue Type: Bug
Components: Streaming
Affects Versions: 1.4.0
Reporter: Mamdouh Alramadan
With spark 1.4 on Mesos cluster, I am trying to stop the context with graceful
shutdown, I have seen this mailing list that [~tdas] addressed
http://mail-archives.apache.org/mod_mbox/incubator-spark-commits/201505.mbox/%3c176cb228a2704ab996839fb97fa90...@git.apache.org%3E
which introduces a new config that was not documented, however, even with
including it, the streaming job still stops correctly but the process doesn't
die after all e.g. the Spark Context still running. My Mesos UI still sees the
framework which is still allocating all the cores needed
the code used for the shutdown hook is:
`sys.ShutdownHookThread {
logInfo("Received SIGTERM, calling streaming stop")
streamingContext.stop(stopSparkContext = true, stopGracefully = true)
logInfo("Application Stopped")
}
`
The logs are for this process are:
```
5/09/16 16:37:51 INFO Start: Received SIGTERM, calling streaming stop
15/09/16 16:37:51 INFO JobGenerator: Stopping JobGenerator gracefully
15/09/16 16:37:51 INFO JobGenerator: Waiting for all received blocks to be
consumed for job generation
15/09/16 16:37:51 INFO JobGenerator: Waited for all received blocks to be
consumed for job generation
15/09/16 16:37:51 INFO StreamingContext: Invoking stop(stopGracefully=true)
from shutdown hook
15/09/16 16:38:00 INFO RecurringTimer: Stopped timer for JobGenerator after
time 1442421480000
15/09/16 16:38:00 INFO JobScheduler: Starting job streaming job 1442421480000
ms.0 from job set of time 1442421480000 ms
15/09/16 16:38:00 INFO JobGenerator: Stopped generation timer
15/09/16 16:38:00 INFO JobGenerator: Waiting for jobs to be processed and
checkpoints to be written
15/09/16 16:38:00 INFO JobScheduler: Added jobs for time 1442421480000 ms
15/09/16 16:38:00 INFO JobGenerator: Checkpointing graph for time 1442421480000
ms
15/09/16 16:38:00 INFO DStreamGraph: Updating checkpoint data for time
1442421480000 ms
15/09/16 16:38:00 INFO DStreamGraph: Updated checkpoint data for time
1442421480000 ms
15/09/16 16:38:00 INFO SparkContext: Starting job: foreachRDD at
StreamDigest.scala:21
15/09/16 16:38:00 INFO DAGScheduler: Got job 12 (foreachRDD at
StreamDigest.scala:21) with 1 output partitions (allowLocal=true)
15/09/16 16:38:00 INFO DAGScheduler: Final stage: ResultStage 12(foreachRDD at
StreamDigest.scala:21)
15/09/16 16:38:00 INFO DAGScheduler: Parents of final stage: List()
15/09/16 16:38:00 INFO CheckpointWriter: Saving checkpoint for time
1442421480000 ms to file
'hdfs://EMRURL/sparkStreaming/checkpoint/checkpoint-1442421480000'
15/09/16 16:38:00 INFO DAGScheduler: Missing parents: List()
.
.
.
.
15/09/16 16:38:00 INFO JobGenerator: Waited for jobs to be processed and
checkpoints to be written
15/09/16 16:38:00 INFO CheckpointWriter: CheckpointWriter executor terminated ?
true, waited for 1 ms.
15/09/16 16:38:00 INFO JobGenerator: Stopped JobGenerator
15/09/16 16:38:00 INFO JobScheduler: Stopped JobScheduler
```
And in my spark-defaults.conf I included
`spark.streaming.stopGracefullyOnShutdown true`
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
