The Limitation of MapReduce : A Probing Case and a Lightweight Solution

@inproceedings{Ma2010TheLO,
  title={The Limitation of MapReduce : A Probing Case and a Lightweight Solution},
  author={Zhiqiang Ma and Lin Gu},
  year={2010}
}
MapReduce is arguably the most successful parallelization framework especially for processing large data sets in datacenters comprising commodity computers. However, difficulties are observed in porting sophisticated applications to MapReduce, albeit the existence of numerous parallelization opportunities. Intrinsically, the MapReduce design allows a program to scale up to handle extremely large data sets, but constrains a program’s ability to process smaller data items and exploit variable… CONTINUE READING
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