SaurabhChawla100 commented on pull request #29413:
URL: https://github.com/apache/spark/pull/29413#issuecomment-672939687


   
   
   
   > I am wondering if we don't want to drop any events, why don't we just set 
the capacity to `Integer.MAX_VALUE`? The `LinkedBlockingQueue` doesn't really 
allocate that much memory at the beginning.
   > 
   > And I find there's concern about it:
   > 
   > 
https://github.com/apache/spark/blob/643cd876e4cfc7faa307db9a2d1dd1b5ca0881f1/core/src/main/scala/org/apache/spark/scheduler/AsyncEventQueue.scala#L47-L48
   > 
   > But I doubt it now. Because we never throw such explicit error but only 
drop events when `offer` returns `false`, right?
   > 
   > And even if we want to throw the error, OOM is still possible when users 
set a huge capacity, right?
   > 
   > Another thought is, the default value(10000) of 
`spark.scheduler.listenerbus.eventqueue.capacity` is probably too small.
   
    **I am wondering if we don't want to drop any events, why don't we just set 
the capacity to `Integer.MAX_VALUE`? The `LinkedBlockingQueue` doesn't really 
allocate that much memory at the beginning.** - This will cause Driver to OOM 
for long Running Jobs if there are large number of events came at point of 
time, since these event takes driver memory when present on queue.
   
   **But I doubt it now. Because we never throw such explicit error but only 
drop events when offer returns false, right?** - yes thats right
   
    **And even if we want to throw the error, OOM is still possible when users 
set a huge capacity, right?** - Generally on running production spark jobs. 
when we set the huge capacity of the queue, at that point of higher Driver 
memory is also set compared to what was there previously .
   
   **Another thought is, the default value(10000) of 
`spark.scheduler.listenerbus.eventqueue.capacity` is probably too small.** - 
yes this is very small, with this size seen lots event drop.


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