Sorry for the late reply, but I wanted to chime in here as wanting to see this feature. We run a medium size cluster (around 1000 cores) in EC2 and I think we could get better usage of the cluster with more control over the distribution of job instances. For example it would be nice to limit the number of kafka consumers running on the same physical box.
Best, Rick On 2017-03-06 14:44 (-0400), Mauricio Garavaglia <m...@gmail.com> wrote: > Hello!> > > I have a job that have multiple instances (>100) that'd I like to spread> > across the hosts in a cluster. Using a constraint such as "limit=host:1"> > doesn't work quite well, as I have more instances than nodes.> > > As a workaround I increased the limit value to something like> > ceil(instances/nodes). But now the problem happens if a bunch of nodes go> > down (think a whole rack dies) because the instances will not run until> > them are back, even though we may have spare capacity on the rest of the> > hosts that we'd like to use. In that scenario, the job availability may be> > affected because it's running with fewer instances than expected. On a> > smaller scale, the former approach would also apply if you want to spread> > tasks in racks or availability zones. I'd like to have one instance of a> > job per rack (failure domain) but in the case of it going down, the> > instance can be spawn on a different rack.> > > I thought we could have a scheduling constraint to "spread" instances> > across a particular host attribute; instead of vetoing an offer right away> > we check where the other instances of a task are running, looking for a> > particular attribute of the host. We try to maximize the different values> > of a particular attribute (rack, hostname, etc) on the task instances> > assignment.> > > what do you think? did something like this came up in the past? is it> > feasible?> > > > Mauricio> >
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