Abstract: The characters of big data are volume,variety,value,velocity,and common hardware and open source.Aiming at the system inefficiency and limited scalability of traditional relational database in big data analysis,this paper presented an algorithm of Hash joins in MapReduce distributed environment based on column-store by introducing MapReduce computing model.First of all,this paper proposed the design of large data-oriented distributed computing models.Then,it proposed the partition aggregation and the heuristic optimization strategy to realize the implementation of Hash join algorithm.Lastly,the experiments evaluated execution time and load capacity.The results show that the proposed method is effective and can provid good scalability in big data analysis.

Key words: Big data, Column-store, Hash join, MapReduce, Parallel computing