A multi-node parallel main-memory OLAP system is proposed in this paper which is considered by the character of OLAP queries and the performance of main-memory database system. In this system, multi-dimensional OLAP queries with aggregate functions are distributed to each computing node to get aggregate results and final result can be available by merging all the aggregate results from multiple computing nodes. Comparing with other solutions, this system uses horizontal distribution policy to distribute massive data in multi-node with only consideration of memory capacity of computation node. According to feature of distributed aggregate function, system can improve parallel processing capacity by lazy results merging which can reduce the volume of message between nodes, the overall performance of parallel query processing can be improved. This system is easy to deploy, it is also practical with good scalability and performance for the requirements of enterprise massive data processing.