计算机应用与软件2016，Vol.33Issue(6)：47-50,91,5.DOI:10.3969/j.issn.1000-386x.2016.06.012
基于MapReduce的DHP算法并行化研究
RESEARCH ON PARALLELISATION OF DHP ALGORITHM BASED ON MAPREDUCE
摘要
Abstract
DHP algorithm is confronted with the problems in association rules mining for big data such as long execution time and low effi-ciency,etc.In order to solve the problems,we studied the parallelisation strategy of DHP algorithm.According to MapReduce parallel program-ming model of cloud computing platform Hadoop,we designed a parallel DHP algorithm,presented the overall flow of the algorithm and the algorithm descriptions of Map function and Reduce function.Compared with DHP algorithm,the parallel DHP algorithm makes use of the pow-erful computing capacity of Hadoop cluster,improves the efficiency of mining association rules from big data.We analysed the execution process of parallel DHP algorithm by example,and carried out experiments on a couple of datasets.Experimental results showed that the paral-lel DHP algorithm has good speedup and scalability on big data.关键词
MapReduce/Hadoop/DHP算法/关联规则Key words
MapReduce/Hadoop/DHP algorithm/Association rules分类
信息技术与安全科学引用本文复制引用
周国军,吴庆军..基于MapReduce的DHP算法并行化研究[J].计算机应用与软件,2016,33(6):47-50,91,5.基金项目
广西高校科学技术研究立项项目（LX20  （）
14300）。 （）
