On Mon, Jan 11, 2016 at 11:00 PM, Bill Farner <wfar...@apache.org> wrote:
> In the log, tasks are denormalized anyhow: > > https://github.com/apache/aurora/blob/master/api/src/main/thrift/org/apache/aurora/gen/storage.thrift#L43-L45 Right - but now we'd be making that denormalization systemically in-effective. IIUC its values-equals based denorm, I'd think we'd need diffing in a cluster using, for example, ceph + docker ~exclusively. > > > > > On Mon, Jan 11, 2016 at 9:54 PM, John Sirois <j...@conductant.com> wrote: > > > On Mon, Jan 11, 2016 at 10:40 PM, Bill Farner <wfar...@apache.org> > wrote: > > > > > Funny, that's actually how the scheduler API originally worked. I > think > > > this is worth exploring, and would indeed completely sidestep the > > paradigm > > > shift i mentioned above. > > > > > > > I think the crux might be handling a structural diff of the thrift for > the > > Tasks to keep the log dedupe optimizations in-play for the most part; ie > > store Task0 in-full, and Task1-N as thrift struct diffs against 0. Maybe > > something simpler like a binary diff would be enough too. > > > > > > > > > > On Mon, Jan 11, 2016 at 9:20 PM, John Sirois <j...@conductant.com> > > wrote: > > > > > > > On Mon, Jan 11, 2016 at 10:10 PM, Bill Farner <wfar...@apache.org> > > > wrote: > > > > > > > > > There's a chicken and egg problem though. That variable will only > be > > > > filled > > > > > in on the executor, when we're already running in the docker > > > environment. > > > > > In this case, the parameter is used to *define* the docker > > environment. > > > > > > > > > > > > > So, from a naive standpoint, the fact that Job is exploded into Tasks > > by > > > > the scheduler but that explosion is not exposed to the client seems > to > > be > > > > the impedance mismatch here. > > > > I have not thought through this much at all, but say that > fundamentally > > > the > > > > scheduler took a Job that was a list of Tasks - possibly > heterogeneous. > > > > The current Job expands to homogeneous Tasks could be just a standard > > > > convenience. > > > > > > > > In that sort of world, the customized params could be injected client > > > side > > > > to form a list of heterogeneous tasks and the Scheduler could stay > > dumb - > > > > at least wrt Task parameterization. > > > > > > > > > > > > > On Mon, Jan 11, 2016 at 9:07 PM, ben...@gmail.com < > ben...@gmail.com> > > > > > wrote: > > > > > > > > > > > As a starting point, you might be able to cook up something > > involving > > > > > > {{mesos.instance}} as a lookup key to a pystachio list. You do > > have > > > a > > > > > > unique integer task number per instance to work with. > > > > > > > > > > > > cf. > > > > > > > > > > > > > > > > > > > > > > > > > > > http://aurora.apache.org/documentation/latest/configuration-reference/#template-namespaces > > > > > > > > > > > > On Mon, Jan 11, 2016 at 8:05 PM Bill Farner <wfar...@apache.org> > > > > wrote: > > > > > > > > > > > > > I agree that this appears necessary when parameters are needed > to > > > > > define > > > > > > > the runtime environment of the task (in this case, setting up > the > > > > > docker > > > > > > > container). > > > > > > > > > > > > > > What's particularly interesting here is that this would call > for > > > the > > > > > > > scheduler to fill in the parameter values prior to launching > each > > > > task. > > > > > > > Using pystachio variables for this is certainly the most > natural > > in > > > > the > > > > > > > DSL, but becomes a paradigm shift since the scheduler is > > currently > > > > > > ignorant > > > > > > > of pystachio. > > > > > > > > > > > > > > Possibly only worth mentioning for shock value, but in the DSL > > this > > > > > > starts > > > > > > > to look like lambdas pretty quickly. > > > > > > > > > > > > > > On Mon, Jan 11, 2016 at 7:46 PM, Mauricio Garavaglia < > > > > > > > mauriciogaravag...@gmail.com> wrote: > > > > > > > > > > > > > > > Hi guys, > > > > > > > > > > > > > > > > We are using the docker rbd volume plugin > > > > > > > > < > > > > > > > > > > > > > > > > > > > > > > > > > > > > https://ceph.com/planet/getting-started-with-the-docker-rbd-volume-plugin> > > > > > > > > to > > > > > > > > provide persistent storage to the aurora jobs that runs in > the > > > > > > > containers. > > > > > > > > Something like: > > > > > > > > > > > > > > > > p = [Parameter(name='volume', value='my-ceph-volume:/foo'), > > ...] > > > > > > > > jobs = [ Service(..., container = Container(docker = > > Docker(..., > > > > > > > parameters > > > > > > > > = p)))] > > > > > > > > > > > > > > > > But in the case of jobs with multiple instances it's required > > to > > > > > start > > > > > > > each > > > > > > > > container using different volumes, in our case different ceph > > > > images. > > > > > > > This > > > > > > > > could be achieved by deploying, for example, 10 instances and > > > then > > > > > > update > > > > > > > > each one independently to use the appropiate volume. Of > course > > > this > > > > > is > > > > > > > > quite inconvenient, error prone, and adds a lot of logic and > > > state > > > > > > > outside > > > > > > > > aurora. > > > > > > > > > > > > > > > > We where thinking if it would make sense to have a way to > > > > > parameterize > > > > > > > the > > > > > > > > task instances, in a similar way that is done with > portmapping > > > for > > > > > > > example. > > > > > > > > In the job definition have something like > > > > > > > > > > > > > > > > params = [ > > > > > > > > Parameter( name='volume', > > > > > > > > value='service-{{instanceParameters.volume}}:/foo' ) > > > > > > > > ] > > > > > > > > ... > > > > > > > > jobs = [ > > > > > > > > Service( > > > > > > > > name = 'logstash', > > > > > > > > ... > > > > > > > > instanceParameters = { "volume" : ["foo", "bar", "zaa"]}, > > > > > > > > instances = 3, > > > > > > > > container = Container( > > > > > > > > docker = Docker( > > > > > > > > image = 'image', > > > > > > > > parameters = params > > > > > > > > ) > > > > > > > > ) > > > > > > > > ) > > > > > > > > ] > > > > > > > > > > > > > > > > > > > > > > > > Something like that, it would create 3 instances of the > tasks, > > > each > > > > > one > > > > > > > > running in a container that uses the volumes foo, bar, and > zaa. > > > > > > > > > > > > > > > > Does it make sense? I'd be glad to work on it but I want to > > > > validate > > > > > > the > > > > > > > > idea with you first and hear comments about the > > > api/implementation. > > > > > > > > > > > > > > > > Thanks > > > > > > > > > > > > > > > > > > > > > > > > Mauricio > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > John Sirois > > > > 303-512-3301 > > > > > > > > > > > > > > > -- > > John Sirois > > 303-512-3301 > > >
