You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Devaraj K (JIRA)" <ji...@apache.org> on 2017/06/20 00:37:00 UTC

[jira] [Created] (SPARK-21146) Worker should handle and shutdown when any thread gets UncaughtException

Devaraj K created SPARK-21146:
---------------------------------

             Summary: Worker should handle and shutdown when any thread gets UncaughtException
                 Key: SPARK-21146
                 URL: https://issues.apache.org/jira/browse/SPARK-21146
             Project: Spark
          Issue Type: Improvement
          Components: Spark Core
    Affects Versions: 2.1.1
            Reporter: Devaraj K


{code:xml}
17/06/19 11:41:23 INFO Worker: Asked to launch executor app-20170619114055-0005/228 for ScalaSort
Exception in thread "dispatcher-event-loop-79" java.lang.OutOfMemoryError: unable to create new native thread
	at java.lang.Thread.start0(Native Method)
	at java.lang.Thread.start(Thread.java:714)
	at java.util.concurrent.ThreadPoolExecutor.addWorker(ThreadPoolExecutor.java:950)
	at java.util.concurrent.ThreadPoolExecutor.processWorkerExit(ThreadPoolExecutor.java:1018)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1160)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
{code}

I see in the logs that Worker's dispatcher-event got the above exception and the Worker keeps running without performing any functionality. And also Worker state changed from ALIVE to DEAD in Master's web UI.

{code:xml}
worker-20170619150349-192.168.1.120-56175 	192.168.1.120:56175 	DEAD 	88 (41 Used) 	251.2 GB (246.0 GB Used)
{code}

I think Worker should handle and shutdown when any thread gets UncaughtException.



--
This message was sent by Atlassian JIRA
(v6.4.14#64029)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org