Lohit Vijayarenu created MAPREDUCE-5689:
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Summary: MRAppMaster does not preempt reducer when scheduled Maps
cannot be full filled
Key: MAPREDUCE-5689
URL: https://issues.apache.org/jira/browse/MAPREDUCE-5689
Project: Hadoop Map/Reduce
Issue Type: Bug
Affects Versions: 2.2.0, 3.0.0
Reporter: Lohit Vijayarenu
We saw corner case where Jobs running on cluster were hung. Scenario was
something like this. Job was running within a pool which was running at its
capacity. All available containers were occupied by reducers and last 2
mappers. There were few more reducers waiting to be scheduled in pipeline.
At this point two mappers which were running failed and went back to scheduled
state. two available containers were assigned to reducers, now whole pool was
full of reducers waiting on two maps to be complete. 2 maps never got scheduled
because pool was full.
Ideally reducer preemption should have kicked in to make room for Mappers from
this code in RMContaienrAllocator
{code}
int completedMaps = getJob().getCompletedMaps();
int completedTasks = completedMaps + getJob().getCompletedReduces();
if (lastCompletedTasks != completedTasks) {
lastCompletedTasks = completedTasks;
recalculateReduceSchedule = true;
}
if (recalculateReduceSchedule) {
preemptReducesIfNeeded();
{code}
But in this scenario lastCompletedTasks is always completedTasks because maps
were never completed. This would cause job to hang forever. As workaround if we
kill few reducers, mappers would get scheduled and caused job to complete.
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