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https://issues.apache.org/jira/browse/YARN-972?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13725459#comment-13725459
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Sandy Ryza commented on YARN-972:
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[~ste...@apache.org],
bq. Those caches are the key to performance, and if you are trying to
overburden the cores with work then its the cache miss penalty that kills the
jobs.
This is routinely done on clusters already. Nodes in probably the majority of
clusters are configured with more slots than cores. This is sensible because
many types of task do a lot of IO and do not even saturate half of a single
core.
bq. Optimising for todays 4-8 cores is a premature optimisation.
In what way are we optimising for 4-8 cores?
> 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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