Research on the Optimization Algorithm of Big Data Computing System

With the social progress and development, the scale of data continues to expand, in order to realize the processing and analysis of large-scale data, graph computing system came into being. At present, with the continuous maturity of graph computing system, graph computing has been widely used in various fields, such as social field, Internet of things field and neural network field. In recent years, different graph computing models have emerged, and some typical distributed graph computing models show good expansibility in the formulation of graph data for big data processing. However, in order to further expand the expansibility, many graph calculation models are studied by algorithms. At present, the SFA algorithm is mostly used in the graph calculation system. However, with the continuous development of graph calculation, many inadaptability of the SFA algorithm appear which restricts the further development of graph calculation. Therefore, it is an urgent problem to optimize the algorithm of graph computing system. On the basis of scholars' research, this paper firstly gives a simple overview of graph calculation and graph calculation model. On this basis, it analyzes the specific formula and significance of SFA algorithm, puts forward the specific scheme of algorithm optimization, and carries out experimental detection of optimization algorithm.