Focusing on the space and time complexity problems in computing betweenness centrality in large complex network,the data structure that can reduce the memory consumption and increase execution speed was brought forward based on the storage property of network data.A coarse grain parallel algorithm was designed using Python language according to the features of computing betweenness centrality.The parallel algorithm was realized in the cluster of multi core workstations.The test results indicate that the algorithm can be applied in the analysis of large network with hundred millions of edges,and has linear speedup.The speedup can reach 71 when 120 cores are used,so as to provide an operational method for the analysis of large scale complex network data.