MapReduce for Data Intensive Scientific Analyses

@article{Ekanayake2008MapReduceFD,
  title={MapReduce for Data Intensive Scientific Analyses},
  author={Jaliya Ekanayake and Shrideep Pallickara and Geoffrey C. Fox},
  journal={2008 IEEE Fourth International Conference on eScience},
  year={2008},
  pages={277-284}
}
Most scientific data analyses comprise analyzing voluminous data collected from various instruments. Efficient parallel/concurrent algorithms and frameworks are the key to meeting the scalability and performance requirements entailed in such scientific data analyses. The recently introduced MapReduce technique has gained a lot of attention from the scientific community for its applicability in large parallel data analyses. Although there are many evaluations of the MapReduce technique using… CONTINUE READING
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