An efficient Frequent Patterns Mining Algorithm based on MapReduce Framework

Recently, data collected from business have continuously growing in every enterprise. The Big Data, Cloud Computing, Data Mining has become hot topics at the present day. How to acquire important information quickly from these data is a critical issue. In this paper, we modified the traditional Apriori algorithm by improving the execution efficiency, since Aprori algorithm has confronted with a drawback that the computation time increases dramatically when data size increases. Since the one-phase algorithm only used one MapReduce operation, it will generate excessive candidates and result in insufficient memory. We design and implement an efficient algorithm: Frequent Patterns Mining Algorithm Based on MapReduce Framework (FAMR). We adopt Hadoop MapReduce as the experiment platform. The experiment results have shown that FAMR has 16.2 speedup at last in the running time compared with one-phase algorithm.