[1]张磊,张公让,张金广.一种网格化聚类算法的MapReduce并行化研究[J].计算机技术与发展,2013,(02):60-64.
　ZHANG Lei,ZHANG Gong-rang,ZHANG Jin-guang.MapReduce Parallelization Research of a Clustering Algorithm Based on Grid[J].,2013,(02):60-64.
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一种网格化聚类算法的MapReduce并行化研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年02期
页码:
60-64
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
MapReduce Parallelization Research of a Clustering Algorithm Based on Grid
文章编号:
1673-629X（2013）02-0060-05
作者:
张磊1; 2; 张公让1; 2; 张金广1; 2
[1]合肥工业大学 管理学院;[2]教育部过程优化与智能决策重点实验室
Author(s):
ZHANG Lei; ZHANG Gong-rang; ZHANG Jin-guang
关键词:
网格; 聚类; 数据挖掘; MapReduce并行化
Keywords:
grid; clustering algorithm; data mining; MapReduce parallelization
文献标志码:
A
摘要:
面对增量式增长的聚类数据,受云计算并行化处理模式的启发,文中对一种网格化聚类算法进行了MapReduce并行化研究.该算法首先利用网格处理技术对数据进行预处理,用网格预处理后所得单元的重心点取代该单元中保存的所有点,然后在MapReduce框架下将各个单元的重心点作为聚类分析的基本数据单元,进行聚类分析.实验结果表明,该算法MapReduce并行化后部署在Hadoop集群上运行,具有与原来相同的聚类效果,并能节省聚类分析的时间和降低计算的复杂度,适合用于高纬度、增量式的海量数据的分析和挖掘
Abstract:
As the incremental growth of clustering data and inspired by the parallel processing model of cloud computing,conducted the MapReduce parallelization research for a clustering algorithm based on gird. This algorithm,firstly,preprocessed the data using the grid processing method,then used the center of gravity of the grid unit as the basic data unit for the clustering analysis under the MapReduce framework,instead of using all the points stored in the unit. The result of experiments demonstrate that this clustering algorithm after its MapReduce parallelization had the same result as before running in the Hadoop cluster. This clustering algorithm can also save the time of analysis and reduce the computational complexity. So,it is suitable for the analysis and data mining of incremental massive data with high latitudes

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更新日期/Last Update: 1900-01-01