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From Sandy Ryza <sandy.r...@cloudera.com>
Subject Re: Large number of pyspark.daemon processes
Date Sat, 24 Jan 2015 00:51:12 GMT
Hi Sven,

What version of Spark are you running?  Recent versions have a change that
allows PySpark to share a pool of processes instead of starting a new one
for each task.

-Sandy

On Fri, Jan 23, 2015 at 9:36 AM, Sven Krasser <krasser@gmail.com> wrote:

> Hey all,
>
> I am running into a problem where YARN kills containers for being over
> their memory allocation (which is about 8G for executors plus 6G for
> overhead), and I noticed that in those containers there are tons of
> pyspark.daemon processes hogging memory. Here's a snippet from a container
> with 97 pyspark.daemon processes. The total sum of RSS usage across all of
> these is 1,764,956 pages (i.e. 6.7GB on the system).
>
> Any ideas what's happening here and how I can get the number of
> pyspark.daemon processes back to a more reasonable count?
>
> 2015-01-23 15:36:53,654 INFO  [Reporter] yarn.YarnAllocationHandler (Logging.scala:logInfo(59))
- Container marked as failed: container_1421692415636_0052_01_000030. Exit status: 143. Diagnostics:
Container [pid=35211,containerID=container_1421692415636_0052_01_000030] is running beyond
physical memory limits. Current usage: 14.9 GB of 14.5 GB physical memory used; 41.3 GB of
72.5 GB virtual memory used. Killing container.
> Dump of the process-tree for container_1421692415636_0052_01_000030 :
> 	|- PID PPID PGRPID SESSID CMD_NAME USER_MODE_TIME(MILLIS) SYSTEM_TIME(MILLIS) VMEM_USAGE(BYTES)
RSSMEM_USAGE(PAGES) FULL_CMD_LINE
> 	|- 54101 36625 36625 35211 (python) 78 1 332730368 16834 python -m pyspark.daemon
> 	|- 52140 36625 36625 35211 (python) 58 1 332730368 16837 python -m pyspark.daemon
> 	|- 36625 35228 36625 35211 (python) 65 604 331685888 17694 python -m pyspark.daemon
>
> 	[...]
>
>
> Full output here: https://gist.github.com/skrasser/e3e2ee8dede5ef6b082c
>
> Thank you!
> -Sven
>
> --
> http://sites.google.com/site/krasser/?utm_source=sig
>

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