[jira] [Created] (YARN-1969) Earliest Deadline First Scheduling

["Maysam Yabandeh (JIRA)" <ji...@apache.org>]

Maysam Yabandeh created YARN-1969:
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             Summary: Earliest Deadline First Scheduling
                 Key: YARN-1969
                 URL: https://issues.apache.org/jira/browse/YARN-1969
             Project: Hadoop YARN
          Issue Type: Improvement
            Reporter: Maysam Yabandeh
            Assignee: Maysam Yabandeh


What we are observing is that some big jobs with many allocated containers are waiting for a few containers to finish. Under *fair-share scheduling* however they have a low priority since there are other jobs (usually much smaller, new comers) that are using resources way below their fair share, hence new released containers are not offered to the big, yet close-to-be-finished job. Nevertheless, everybody would benefit from an "unfair" scheduling that offers the resource to the big job since the sooner the big job finishes, the sooner it releases its "many" allocated resources to be used by other jobs.In other words, what we require is a kind of variation of *Earliest Deadline First scheduling*, that takes into account the number of already-allocated resources and estimated time to finish.
http://en.wikipedia.org/wiki/Earliest_deadline_first_scheduling

For example, if a job is using MEM GB of memory and is expected to finish in TIME minutes, the priority in scheduling would be a function p of (MEM, TIME). The expected time to finish can be estimated by the AppMaster using TaskRuntimeEstimator#estimatedRuntime and be supplied to RM in the resource request messages. To be less susceptible to the issue of apps gaming the system, we can have this scheduling limited to *only within a queue*: i.e., adding a EarliestDeadlinePolicy extends SchedulingPolicy and let the queues to use it by setting the "schedulingPolicy" field.



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