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From squito <...@git.apache.org>
Subject [GitHub] spark issue #15505: [SPARK-18890][CORE] Move task serialization from the Tas...
Date Thu, 19 Jan 2017 16:10:16 GMT
Github user squito commented on the issue:

    https://github.com/apache/spark/pull/15505
  
    This might be a really dumb question, but please humor me -- can you explain to me the
threads involved, both before and after this change?  I must be missing something, because
it seems to me it will be the same thread both before and after this change.
    
    `taskScheduler.resourceOffers()` is only called by `CoarseGrainedSchedulerBackend`, inside
its event loop.  `taskScheduler` has a handful of other threads that interact with it, but
nothing that will trigger resource offers.  Eg. some methods end up calling `backend.reviveOffers()`,
but that pushes an event into the `CoarseGrainedSchedulerBackend`'s event queue anyway.
    
    OTOH, though this PR doesn't change the thread that serialization is happening, after
this change serialization happens *without a lock* on the `taskScheduler`.  This could be
important because when a task finishes, we need to both (1) update the taskset's internal
state & process the result and (2) schedule new tasks on the freed resources.  Those two
can happen in different threads, but both involve locks on `taskScheduler`; by moving serialization
so it no longer requires a lock, this reduces contention on that lock and improves performance.
    
    Is that accurate, or am I completely missing something?


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