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From David McLaughlin <dmclaugh...@apache.org>
Subject Re: schedule task instances spreading them based on a host attribute.
Date Thu, 30 Mar 2017 16:16:29 GMT
I think this is more complicated than multiple scheduling algorithms. The
problem you'll end up having if you try to solve this in the Scheduling
loop is when resources are unavailable because there are preemptible tasks
running in them, rather than hosts being down. Right now the fact that the
task cannot be scheduled is important because it triggers preemption and
will make room. An alternative algorithm that tries at all costs to
schedule the task in the TaskAssigner could decide to place the task in a
non-ideal slot and leave a preemptible task running instead.

It's also important to think of the knock-on effects here when we move to
offer affinity (i.e. the current Dynamic Reservation proposal). If you've
made this non-ideal compromise to get things scheduled - that decision will
basically be permanent until the host you're on goes down. At least with
how things work now, with each scheduling attempt the job has a fresh
chance of being put in an ideal slot.

On Thu, Mar 30, 2017 at 8:12 AM, Rick Mangi <rick@chartbeat.com> wrote:

> 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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