The capacity of single server or CPU is unable to finish the task of the mining of mass data. Concerning this bottleneck problem, a combined algorithm which is used by genetic and MR-based parallel clustering algorithm is proposed. To make up for the defects of clustering analysis in screening the clustering center and the clusters are used by genetic algorithm, then relying on M-R parallel computing model is to accelerate the convergence of the clustering analysis. To verify reasonableness of algorithm, this algorithm what is applied to analysis of the actual log is based on building of Hadoop platform. Experimental results show that, relying on performance of distributed cluster computing and genetic clustering analysis to process log files, it can get better clustering results, and the efficiency of mining of massive log has been greatly improved.