Research on Data Balancing Method under High ｌｏａｄ of Distributed Parallel Database

Jia Chen, Yingxue Cai, Song Hu, Sibo Huang, Hui Hu, Zhaoquan Cai* 

Huizhou University, Huizhou, China 

Abstract: In order to improve big data's access ability and reduce output error code in distributed parallel da-tabase, it is necessary to carry out equalization control. A ｌｏａｄ balancing control model of big data in distri-buted parallel database based on adaptive random link configuration is proposed. The coherent association detection method is used to reorganize the big data information flow in the distributed database. The output link model of the distributed database is established, and the channel impulse response of the distributed database is calculated. The optimal scheduling of the distributed database output channel is carried out by using the link random allocation method and the big data ｌｏａｄ balancing configuration is carried out by combining the data clustering method to realize the data balance processing under the high ｌｏａｄ of the distributed parallel database. The simulation results show that the proposed method can improve the ｌｏａｄ balance of distributed parallel database, and the recall of database access is better.

Keywords: distributed parallel database; ｌｏａｄ balancing; control; database access