This paper presents hash join optimization based on shared cache CMP (chip multi-processor). Firstly, it proposes a multithreaded execution framework of hash join based on Radix-Join algorithm, and then analyzes the factors which affect the performance of multithreaded Radix-Join algorithm through two instances. Based on the analysis, the performance of various threads and their shared-cache access behaviors in the hash join multithreaded execution framework were optimized, and optimize memory access of hash join in cluster join phase. It then analyzes the speedup of multithreaded cluster partition in theory was analyzed. All of the algorithms are implemented in the INGRES and EaseDB. In the experiments, the performance of the multithreaded execution framework of hash join is tested, and the results show that the proposed algorithm could effectively resolve the cache access conflict and load balance of CMP cores in multithreaded environment and hash join performance is improved.