CG_Hadoop: computational geometry in MapReduce

  title={CG_Hadoop: computational geometry in MapReduce},
  author={Ahmed Eldawy and Yuan Li and Mohamed F. Mokbel and Ravi Janardan},
Hadoop, employing the MapReduce programming paradigm, has been widely accepted as the standard framework for analyzing big data in distributed environments. Unfortunately, this rich framework was not truly exploited towards processing large-scale computational geometry operations. This paper introduces CG_Hadoop; a suite of scalable and efficient MapReduce algorithms for various fundamental computational geometry problems, namely, polygon union, skyline, convex hull, farthest pair, and closest… CONTINUE READING
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