[jira] [Resolved] (YARN-972) Allow requests and scheduling for fractional virtual cores

["Sandy Ryza (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/YARN-972?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sandy Ryza resolved YARN-972.
-----------------------------

    Resolution: Won't Fix
    
> Allow requests and scheduling for fractional virtual cores
> ----------------------------------------------------------
>
>                 Key: YARN-972
>                 URL: https://issues.apache.org/jira/browse/YARN-972
>             Project: Hadoop YARN
>          Issue Type: Improvement
>          Components: api, scheduler
>    Affects Versions: 2.0.5-alpha
>            Reporter: Sandy Ryza
>            Assignee: Sandy Ryza
>
> As this idea sparked a fair amount of discussion on YARN-2, I'd like to go deeper into the reasoning.
> Currently the virtual core abstraction hides two orthogonal goals.  The first is that a cluster might have heterogeneous hardware and that the processing power of different makes of cores can vary wildly.  The second is that a different (combinations of) workloads can require different levels of granularity.  E.g. one admin might want every task on their cluster to use at least a core, while another might want applications to be able to request quarters of cores.  The former would configure a single vcore per core.  The latter would configure four vcores per core.
> I don't think that the abstraction is a good way of handling the second goal.  Having a virtual cores refer to different magnitudes of processing power on different clusters will make the difficult problem of deciding how many cores to request for a job even more confusing.
> Can we not handle this with dynamic oversubscription?
> Dynamic oversubscription, i.e. adjusting the number of cores offered by a machine based on measured CPU-consumption, should work as a complement to fine-granularity scheduling.  Dynamic oversubscription is never going to be perfect, as the amount of CPU a process consumes can vary widely over its lifetime.  A task that first loads a bunch of data over the network and then performs complex computations on it will suffer if additional CPU-heavy tasks are scheduled on the same node because its initial CPU-utilization was low.  To guard against this, we will need to be conservative with how we dynamically oversubscribe.  If a user wants to explicitly hint to the scheduler that their task will not use much CPU, the scheduler should be able to take this into account.
> On YARN-2, there are concerns that including floating point arithmetic in the scheduler will slow it down.  I question this assumption, and it is perhaps worth debating, but I think we can sidestep the issue by multiplying CPU-quantities inside the scheduler by a decently sized number like 1000 and keep doing the computations on integers.
> The relevant APIs are marked as evolving, so there's no need for the change to delay 2.1.0-beta.

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