Sort-merge join is an important implementation method of join in database system, and is more widely used than hash join. Under distributed environment, data is sharded and distributed across many nodes, and usually needed to be transmitted by network which is very expensive. Therefore, it is far more challenging to efficiently process sort-merge join in distributed database. Traditional strategy firstly sorts data, and then carries out merge-join based on sorted data, which are both related with original data. But original data usually has useless data blocks, which does not participate in join, but will increase the extra cost during join including network cost. The bigger of data size, the higher of possibility of useless data blocks. Traditional sort-merge join strategy does not prehandle these useless data. In this study, a parallel sort-merge join is proposed based on prune, called Pr_PSMJ, which can efficiently prune the useless data ahead from join data, and improve the efficiency of join. Firstly, a bilateral adjacency list (BAL) is constructed by the statistic information from shards of join data. Using BAL, the useless data of join data can be pruned and the correctness of final join result is guaranteed. Secondly, after the pruning, the optimal local-join executing place can be computed by BAL, and the quantity of data mitigating among nodes is minimized. Finally, during the join step, for the independence of local-join guaranteed by BAL, the executing of sort-merge join can be easily parallelled, and in every executing node, it is natural to parallel the local-partitial-join using multi-core environment. The final result is achieved by merging local-result. Because high efficient prune operation is done before executing join, Pr_PSMJ is almost fit for every sort-merge strategy, and it is a good lesson for other join strategies. The correctness, efficiency, and adaptability of algorithm are analyzed based on Pr_PSMJ. By experiments, it is proved that under distributed environment, orienting large data, Pr_PSMJ can effectively decrease the overhead of network and improve the join efficiency than other strategies.