title: How are map and reduce workers in cluster selected?
body: <p>For mapreduce job we need to specify partitioning of input data (count of map processes - M) and count of reduce processes (R). In <a href="http://www.usenix.org/event/osdi04/tech/full_papers/dean/dean.pdf" rel="nofollow">MapReduce papers</a> is example of their often settings: cluster with 2 000 workers and M = 200 000, R = 5 000. Workers are tagged as map-worker or reduce-worker. I wonder how are these workers in cluster selected.</p>
  
  <p>Is this done so that is chosen fixed count of map-workers and fixed count of reduce-workers? (and then data stored in reduce-workers nodes has to be send to map-reduce workers)
  Or map phase is running on each node in cluster and any count of nodes are then selected as reduce-workers?
  Or is it done in another way?</p>
  
  <p>Thanks for your answers.</p>