%0 Journal Article %A BAO Qiulan %A CHEN Yang %A LIAO Jia %A LIAO Xuehua %A ZHU Zhousen %T Relay computation and dynamic diversion of computing-intensive large flow data %D 2021 %R 10.11772/j.issn.1001-9081.2020111725 %J Journal of Computer Applications %P 2646-2651 %V 41 %N 9 %X In view of the problems such as the slow computation of large flow data, the high computation pressure on the server, a set of relay computation and dynamic diversion model of computing-intensive large flow data was proposed. Firstly, in the distributed environment, the in-memory data storage technology was used to determine the computation amounts and complexity levels of the computation tasks. At the same time, the nodes were sorted by the node resource capacity, and the tasks were dynamically allocated to different nodes for parallel computing. Meanwhile, the computation tasks were decomposed by a relay processing mode, so as to guarantee the performance and accuracy requirements of high flow complex computing tasks. Through analysis and comparison, it can be seen that the running time of multiple nodes is shorter than that of the single node, and the computation speed of multiple nodes is faster than that of the single node when dealing with data volume of more than 10 000 levels. At the same time, when the model is applied in practice, it can be seen that the model can not only reduce the running time in high concurrency scenarios but also save more computing resources. %U http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2020111725