This may have to do with fine-grain Vs coarse-grain resource allocation. Things may be easier for you, Diptanu, if you are using one Docker container per task (sort of coarse grain). In that case, I believe there's no need to alter a running Docker container's resources. Instead, the resource update of your executor translates into the right Docker containers running. There's some details to be worked out there, I am sure. It sounds like Tom's strategy uses the same Docker container for multiple tasks. Tom, do correct me otherwise.
On Wed, Dec 3, 2014 at 3:38 AM, Tom Arnfeld <[email protected]> wrote: > When Mesos is asked to a launch a task (with either a custom Executor or > the built in CommandExecutor) it will first spawn the executor which _has_ > to be a system process, launched via command. This process will be launched > inside of a Docker container when using the previously mentioned > containerizers. > > Once the Executor registers with the slave, the slave will send it a > number of *launchTask* calls based on the number of tasks queued up for > that executor. The Executor can then do as it pleases with those tasks, > whether it's just a *sleep(1)* or to spawn a subprocess and do some other > work. Given it is possible for the framework to specify resources for both > tasks and executors, and the only thing which _has_ to be a system > process is the executor, the mesos slave will limit the resources of the > executor process to the sum of (TaskInfo.Executor.Resources + > TaskInfo.Resources). > > Mesos also has the ability to launch new tasks on an already running > executor, so it's important that mesos is able to dynamically scale the > resource limits up and down over time. Designing a framework around this > idea can lead to some complex and powerful workflows which would be a lot > more complex to build without Mesos. > > Just for an example... Spark. > > 1) User launches a job on spark to map over some data > 2) Spark launches a first wave of tasks based on the offers it received > (let's say T1 and T2) > 3) Mesos launches executors for those tasks (let's say E1 and E2) on > different slaves > 4) Spark launches another wave of tasks based on offers, and tells mesos > to use the same executor (E1 and E2) > 5) Mesos will simply call *launchTasks(T{3,4})* on the two already > running executors > > At point (3) mesos is going to launch a Docker container and execute your > executor. However at (5) the executor is already running so the tasks will > be handed to the already running executor. > > Mesos will guarantee you (i'm 99% sure) that the resources for your > container have been updated to reflect the limits set on the tasks > *before* handing the tasks to you. > > I hope that makes some sense! > > -- > > Tom Arnfeld > Developer // DueDil > > > On Wed, Dec 3, 2014 at 10:54 AM, Diptanu Choudhury <[email protected]> > wrote: > >> Thanks for the explanation Tom, yeah I just figured that out by reading >> your code! You're touching the memory.soft_limit_in_bytes and >> memory.limit_in_bytes directly. >> >> Still curios to understand in which situations Mesos Slave would call the >> external containerizer to update the resource limits of a container? My >> understanding was that once resource allocation happens for a task, >> resources are not taken away until the task exits[fails, crashes or >> finishes] or Mesos asks the slave to kill the task. >> >> On Wed, Dec 3, 2014 at 2:47 AM, Tom Arnfeld <[email protected]> wrote: >> >>> Hi Diptanu, >>> >>> That's correct, the ECP has the responsibility of updating the resource >>> for a container, and it will do as new tasks are launched and killed for an >>> executor. Since docker doesn't support this, our containerizer (Deimos does >>> the same) goes behind docker to the cgroup for the container and updates >>> the resources in a very similar way to the mesos-slave. I believe this is >>> also what the built in Docker containerizer will do. >>> >>> >>> https://github.com/duedil-ltd/mesos-docker-containerizer/blob/master/containerizer/commands/update.py#L35 >>> >>> Tom. >>> >>> -- >>> >>> Tom Arnfeld >>> Developer // DueDil >>> >>> >>> On Wed, Dec 3, 2014 at 10:45 AM, Diptanu Choudhury <[email protected]> >>> wrote: >>> >>>> Hi, >>>> >>>> I had a quick question about the external containerizer. I see that >>>> once the Task is launched, the ECP can receive the update calls, and the >>>> protobuf message passed to ECP with the update call is >>>> containerizer::Update. >>>> >>>> This protobuf has a Resources [list] field so does that mean Mesos >>>> might ask a running task to re-adjust the enforced resource limits? >>>> >>>> How would this work if the ECP was launching docker containers because >>>> Docker doesn't allow changing the resource limits once the container has >>>> been started? >>>> >>>> I am wondering how does Deimos and mesos-docker-containerizer handle >>>> this. >>>> >>>> -- >>>> Thanks, >>>> Diptanu Choudhury >>>> Web - www.linkedin.com/in/diptanu >>>> Twitter - @diptanu <http://twitter.com/diptanu> >>>> >>> >>> >> >> >> -- >> Thanks, >> Diptanu Choudhury >> Web - www.linkedin.com/in/diptanu >> Twitter - @diptanu <http://twitter.com/diptanu> >> > >
