MapReduce Based Association Rule Incremental Updating Algorithm
Jianxin Chen · Computer Technology and Development · 2012
Cloud computing,with its powerful storage and computing power,has become one of the most effective way for solving the problem of massive data mining.FUP is one of the most classic incremental updating algorithms for association rules.But it can not meet the need of massive data mining very well because it needs to scan the dataset frequently.In this paper,in order to enhance the incremental updating efficiency of association rules for massive data,a MapReduce based incremental updating algorithm for association rules is proposed by combing FUP algorithm and MapReduce programming mode,which is named MRFUP.MRFUP scans the original dataset only once,and takes full advantage of the powerful storage and computing power provided by cloud computing.The results of the experiments deployed on Hadoop show that MRFUP can improve the ability and efficiency of processing massive data;It adapts to mine association rules from massive data.