The research develop a distributed mining system coordinating multi computers to promote efficiency of sequential pattern mining. First, because of the inaccuracy of directly supporting sequential pattern mining. Then, the work propose a Advanced Dynamic Load Balance algorithm -ADLB. Different to previous works, ADLB divides subtask dispatches into several stages. According to different situations, the static and dynamic load balance method are applied adeptly to prevent the task partition from skew and reduce the communication overhead simultaneously. Furthermore, we also improve the performance with on the basis of citing literature 20. Choose a proper mining algorithm for each database but not apply a single algorithm for all databases with different features. In addition, we combine the sixteen computers that adoptee distributed mining. In comparison with the previous works, the experimental results shows ADLB can effectively reduce the runtime and obtain a better speed-up ratio. This result demonstrates the potentials of ADLB for mining sequential pattern in Very Large Databases.