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Again, the number of reduce tasks ≫ the number of reducers.
The faster nodes will run more reduce tasks and lunch immediately another wave of reducers when they finish.
When all data have been grouped and sorted, the different reduce tasks are executed in parallel by different reducers.
It has two main tasks: map and reduce tasks.
The reduce tasks are also scheduled using the same policy.
All map tasks need to finish to start reduce tasks.
In each container both map and reduce tasks can run.
COED runs as a series of map and reduce tasks.
Slots are used to execute map and reduce tasks.
This includes the number of map and reduce tasks, the executable files used by map and reduce tasks, as well as their hardware and software requirements.
Therefore, the number of reduce tasks and the maximum number of map and reduce tasks per node varies depending on the size of input data.
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