Large data sets clustering analysis based on distribution

In order to improve the efficiency we propose a distributed clustering algorithm based on large data sets.Namely data is randomly divided into several subsets without clustering all the data at a time,then we cluster all the subsets at the same time.At last we combine the genus.Experiment results show that most of time the result is the same as using traditional clustering algorithm,and it improves the clustering speed greatly.