Research on communication mechanism optimization based on distributed graph computing environment
Jianchao Lin, Chunna Cao, Chunhui Ren · 2023
In recent years, with the rapid development of the Internet of Things, the Internet, and social networks, the storage of data in the network is growing at an explosive rate and is becoming more and more closely related to the real natural world. Driven by large-scale data mining and machine learning applications, distributed graph computing models that use graph data structures to describe data and relationships between data have been increasingly widely used. Therefore, this paper studies the optimization of communication mechanisms based on a distributed graph computing environment. Firstly, a BSP model based on a pure message-passing communication mechanism of a distributed graph computing system is established. Secondly, the optimization model is evaluated from two aspects: data communication and convergence condition judgment. Finally, large-scale data sets are used to test and evaluate performance optimization. The results show that this method can greatly improve the efficiency of graph parallel computing.