Yup, if that doesn't work for any reason, you can increase memory in 1G
increments.
Ensure that you have some head-room on top of your Xmx to account for native
memory
On Fri, May 24, 2019 at 10:34 AM Malcolm McFarland
wrote:
> Thanks Jagadish, just wanted to verify that this wasn't an obvious t
Thanks Jagadish, just wanted to verify that this wasn't an obvious thing I
was missing. I'm also setting the AM's heap size explicitly with the
yarn.am.opts configuration parameter; in this case, I'm allowing 512MB for
the JVM on top of my heap for both the AM and the container (ie,
yarn.am.contain
No, the default setup should be sufficient - the number of tasks should
have no significant impact on AM memory/resources.
If you run out-of-memory, you can of course increase yarn.am.memory.mb.
On Thu, May 23, 2019 at 10:45 AM Malcolm McFarland
wrote:
> Hey folks,
>
> Are there any guidelines
Hey folks,
Are there any guidelines for how to provision an Application Master in
relation to the number of StreamTask instances it will be managing? Ie, are
there different memory, CPU, and thread-count figures for 100S StreamTasks
vs 1000, vs 1?
Cheers,
Malcolm McFarland
Cavulus
This corr
