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Design and implementation of parallel statiatical algorithm based on Hadoop's MapReduce model

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4 Author(s)
Songqing Duan ; Beijing Key Lab. of Intell. Telecommun. Software & Multimedia, Beijing Univ. of Posts & Telecommun., Beijing, China ; Bin Wu ; Bai Wang ; Juan Yang

The rapid growth of data promotes the development of parallel computing. MapReduce, which is a simplified programming model of distributed parallel computing, is becoming more and more popular. In this paper, we design and implementation of parallel statistical algorithm based on Hadoop's MapReduce model. The algorithm, which is used to grasp the overall characteristics of massive data, involves the calculation of central tendency, dispersion and distribution tendency. By experiment, we come to the conclusion that the algorithm is suitable for dealing with large-scale data.

Published in:
Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on

Date of Conference: 15-17 Sept. 2011

Page(s):
134 - 138
Print ISBN:
978-1-61284-203-5
INSPEC Accession Number:
12305867
Conference Location :
Beijing
Digital Object Identifier :
10.1109/CCIS.2011.6045047
Product Type:
Conference Publications

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