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2011 2nd International Symposium on Intelligence Information Processing and Trusted Computing
The Application of MapReduce in the Cloud Computing
Wuhan, China
October 22-October 23
ISBN: 978-0-7695-4498-4
ASCII Text
x 
 
Gaizhen Yang, "The Application of MapReduce in the Cloud Computing," Intelligence Information Processing and Trusted Computing, International Symposium on, pp. 154-156, 2011 2nd International Symposium on Intelligence Information Processing and Trusted Computing, 2011.
 
 
BibTex
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@article{ 10.1109/IPTC.2011.46,
author = {Gaizhen Yang},
title = {The Application of MapReduce in the Cloud Computing},
journal ={Intelligence Information Processing and Trusted Computing, International Symposium on},
volume = {0},
year = {2011},
isbn = {978-0-7695-4498-4},
pages = {154-156},
doi = {http://doi.ieeecomputersociety.org/10.1109/IPTC.2011.46},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Intelligence Information Processing and Trusted Computing, International Symposium on
TI - The Application of MapReduce in the Cloud Computing
SN - 978-0-7695-4498-4
SP154
EP156
A1 - Gaizhen Yang,
PY - 2011
KW - MapReduce
KW - Hadoop
KW - cloud platform
KW - architecture
KW - distributed programming
VL - 0
JA - Intelligence Information Processing and Trusted Computing, International Symposium on
ER -
 
Hadoop provides a sophisticated framework for cloud platform programmers, which, MapReduce is a programming model for large-scale data sets of parallel computing. By MapReduce distributed processing framework, we are not only capable of handling large-scale data, and can hide a lot of tedious details, scalability is also wonderful. This paper analyzes the Hadoop architecture and MapReduce Working principle, described how to perform a MapReduce job in the cloud platform, how to write Mapper and Reducer classes, and how to use the object, proposed a program based on the MapReduce framework that enables distributed programming, Comparison results show that use of MapReduce architecture simplifies distributed programming.
Index Terms:
MapReduce, Hadoop, cloud platform, architecture, distributed programming
Citation:
Gaizhen Yang, "The Application of MapReduce in the Cloud Computing," iptc, pp.154-156, 2011 2nd International Symposium on Intelligence Information Processing and Trusted Computing, 2011
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