Because that the popularity of cloud technology and the accumulation of large amounts of data, it is very important direction of research to reduce time for processing large amounts of data efficiently. Besides, there are many kinds of data mining technique which are used in analyzing of huge amounts of data, which contains the association rule mining algorithms and sequential pattern mining algorithms. In this study, two sequential pattern mining algorithms, GSP algorithm and AprioriAll algorithm, are parallelized through the MapReduce framework. Also, we design and study the different efficiency between the two kinds of sequential pattern mining algorithms, and analyze the different efficiency between GSP algorithm and AprioriAll algorithm. The results show that the parallelized GSP algorithm is better than the parallelized AprioriAll algorithm.