| Document Date: 2009-12-30 16:05:05
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City Athens / / Company NBC / Google / Yahoo! / / Country Greece / / Currency pence / / Facility National Technical University of Athens / Stanford University / / IndustryTerm map-reduce systems / distributed file systems / cluster computing / software stack / conventional file systems / merging algorithm / Map-reduce algorithms / packet switching networks / communication/processing costs / probabilistic algorithm / mind such applications / sorting algorithm / acyclic networks / data-intensive applications / transitive closure algorithms / typical computing environment / data management applications / database-management systems / parallel sorting algorithms / commodity hardware / file systems / elapsed processing time / computing / earlier algorithm / particular algorithm / / Organization Department of Computer Science / Stanford University / School of Electrical and Computing Engineering / National Technical University of Athens / / Person Jeffrey D. Ullman / / Position controller / / ProvinceOrState California / / SportsLeague Stanford University / / Technology merging algorithm / earlier algorithm / particular algorithm / packet switching / PRAM algorithms / sorting algorithm / Algorithms An algorithm / Map-reduce algorithms / 4 one processor / transitive closure algorithms / 3.1 The algorithm / parallel sorting algorithms / operating system / operating systems / DBMS / probabilistic algorithm / gigabit Ethernet / /
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A New Computation Model for Cluster Computing Foto N. Afrati∗, and Jeffrey D. Ullman† December 30, 2009 Abstract Implementations of map-reduce are being used to perform many operations on very large