Thanks, Guangya! Inspired by your comments, I've also been thinking about the option of using Apache Aurora to provide some of the features I want. Spark could be deployed in standalone mode on top of Aurora on top of Mesos. :)
Funny enough, two of my colleagues (Tim St. Clair and Erik Erlandson) seem to be tracking and commenting on the epic you linked to. :) On Wed, Sep 9, 2015 at 12:59 AM, Guangya Liu <[email protected]> wrote: > Hi RJ, please check my answers in line. > > Thanks, > > Guangya > > On Wed, Sep 9, 2015 at 1:24 PM, RJ Nowling <[email protected]> wrote: > >> Hi Guangya, >> >> My use case is actually trying to run Spark (in coarse grain mode) with >> multiple users. I wanted ways to better ensure fair scheduling across >> users. Spark provides very few primitives so I was hoping I could use Mesos >> to limit resources per user and control how the cluster is partitioned. For >> example, I may prefer that a Spark jobs share multiple machines without >> using all resources on a single machine for fault tolerance. >> > For this scenario, you may want to schedule those offered resource again > in framework level, you can leverage fenzo or what ever to enhance the > scheduler part for spark to achieve your goal. > >> >> I'm also considering the case of running multiple frameworks. In this >> case, frameworks would have to coordinate to enforce user quotas and such. >> It seems that this would be better solved somewhere below the framework >> level. >> > For this scenario, there is an epic for "quota management" which can fill > your requirement but it is still undergoing and not available now. > epic: https://issues.apache.org/jira/browse/MESOS-1791 > Design doc: > https://docs.google.com/document/d/16iRNmziasEjVOblYp5bbkeBZ7pnjNlaIzPQqMTHQ-9I/edit?pli=1#heading=h.9g7fqjh6652v > >> >> RJ >> >> >> >> On Sep 8, 2015, at 11:47 PM, Guangya Liu <[email protected]> wrote: >> >> Hi RJ, >> >> I think that your final goal is that you want to use framework running on >> top of mesos to execute some tasks. Such logic should be in the framework >> part. The netflix open sourced a framework scheduler library named as >> fenzo, you may want to take a look at this one to see if it can help you. >> >> >> http://techblog.netflix.com/2015/08/fenzo-oss-scheduler-for-apache-mesos.html >> https://github.com/Netflix/Fenzo >> >> Thanks, >> >> Guangya >> >> ------------------------------ >> Date: Tue, 8 Sep 2015 23:09:36 -0500 >> Subject: Re: Setting maximum per-node resources in offers >> From: [email protected] >> To: [email protected] >> >> Thanks, Klaus. >> >> I think I was probably misunderstanding the role of the allocator in >> Mesos versus the scheduler in the framework sitting on top of Mesos. >> Probably out of scope for Mesos to divide up resources as I was suggesting. >> >> On Tue, Sep 8, 2015 at 10:48 PM, Klaus Ma <[email protected]> wrote: >> >> If it's the only framework, you will receive all nodes from Mesos as >> offers. You can re-schedule those resources to run tasks on each node. >> >> >> On 2015年09月09日 03:03, RJ Nowling wrote: >> >> Hi all, >> >> I have a smallish cluster with a lot of cores and RAM per node. I want >> to support multiple users so I'd like to set up Mesos to provide a maximum >> of 8 cores per node in the resource offers. Resource offers should include >> multiple nodes to reach the requirements of the user. For example, if the >> user requests 32 cores, I would like 8 cores from each of 4 nodes. >> >> Is this possible? Or can someone suggest alternatives? >> >> Thanks, >> RJ >> >> >> -- >> Klaus Ma (马达), PMP® | http://www.cguru.net >> >> >> >
