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Titles
English : MapReduce:State-of-the-Art and Research Directions
Abstract Digital data that come from different applications such as, wireless sensor, bioinformatics next generation sequencing, and high throughput instruments are growing in high rate. Dealing with demands of analysis of ever-growing data requires new techniques in software, hardware, and algorithms. MapReduce is a programming model initiated by Google’s Team for processing huge datasets in distributed systems; it helps programmers to write programs that process big data. The aim of this paper is to investigate MapReduce research trends, and current research efforts for enhancing MapReduce performance and capabilities. This Study concluded that the research directions of MapReduce concerned with either enhancing MapReduce programming model or adopting MapReduce for deploying existing algorithm to run with MapReduce programming model.
Publication year 2013
Organization Name
    Central Laboratory for Agricultural Expert System (CLAES)
City Dubai
serial title 2013 2nd International Conference on Computer Technology and Science (ICCTS 2014)
Web Page
Author(s) from ARC
External authors (outside ARC)
    Mohamed E. El-Sharkawi Faculty of Computers and information , Cairo University
    Osama Ismail Faculty of Computers and information , Cairo University
Agris Categories Documentation and information
AGROVOC
TERMS
Computer software. Models.
Proposed Agrovoc big data;
Publication Type Conference/Workshop

 
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