Abstract
We study the MapReduce framework from an algorithmic standpoint, providing a generalization of the previous algorithmic models for MapReduce. We present optimal solutions for the fundamental problems of all-prefix-sums, sorting and multi-searching. Additionally, we design optimal simulations of the the well-established PRAM and BSP models in MapReduce, immediately resulting in optimal solutions to the problems of computing fixed-dimensional linear programming and 2-D and 3-D convex hulls. © 2011 Springer-Verlag.
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CITATION STYLE
Goodrich, M. T., Sitchinava, N., & Zhang, Q. (2011). Sorting, searching, and simulation in the MapReduce framework. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7074 LNCS, pp. 374–383). https://doi.org/10.1007/978-3-642-25591-5_39
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