Research on Data Storage System of E-Commerce Purchasing Based on Big Data Technology

Abstract

The storage of e-commerce procurement data is randomly distributed, which is interfered by the characteristic quantity of neighborhood distribution state, resulting in insufficient query performance. In order to improve the automatic location and storage ability of e-commerce procurement data, an automatic location and storage method of e-commerce procurement data based on big data technology is proposed. The distributed adaptive storage structure model of e-commerce procurement data is constructed, and the multivariate feature mining of e-commerce procurement data is carried out by using the method of regional grid computing, and the high dimension characteristic quantity of e-commerce procurement data is extracted. Combined with phase space reconstruction method, the storage space structure of e-commerce procurement data is reorganized, and big data mining and spectral feature extraction technology are used to realize the knowledge connection of e-commerce procurement data, and the automatic location storage optimization is realized. The simulation results show that the load of automatic location storage of e-commerce procurement data is large, the storage capacity is improved, and the real-time access ability of e-commerce procurement data is better.