摘要
MapReduce是一种编程模型,这种模型编程简单,可以用于大规模数据集的并行计算。Apriori算法是一种发现频繁项集的基本算法,通过该算法,可以产生关联规则。针对Apriori的特点,研究了在MapReduce编程模型下,Apriori的实现方法。实验结果表明:该方法在对大数据集进行频繁项集挖掘时,可充分利用云计算的优势,从而能获得更好的时效性。
MapReduce is a programming model,which is simple,can be used for parallel computing of large-scale data sets. Apriori algorithm is a basic algorithm to discover frequent item sets,and association rules are generated from it. In view of the characteristics of Apriori,this paper analyzes the realization method of Apriori under MapReduce programming model. Experimental results show that the proposed method can make full use of the advantages of cloud computing in the frequent item sets mining on large data sets,having better effectiveness.
出处
《长春大学学报》
2016年第12期40-43,114,共5页
Journal of Changchun University
