| Titles |
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English :
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MapReduce:State-of-the-Art and Research Directions
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| 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.
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| Publication year |
2013
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| Organization Name |
Climate Change Information Center & Renewable Energy & Expert Systems
|
| City |
Dubai
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| serial title |
2013 2nd International Conference on Computer Technology and Science (ICCTS 2014)
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| Web Page |
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| Author(s) from ARC |
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| External authors (outside ARC) |
Mohamed E. El-Sharkawi
Faculty of Computers and information , Cairo University
Osama Ismail
Faculty of Computers and information , Cairo University
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| Agris Categories |
Documentation and information
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AGROVOC
TERMS |
Computer software.
Models.
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| Proposed Agrovoc |
big data;
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| Publication Type |
Conference/Workshop
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