Big Data-Based E-Commerce Transaction Information Collection Method

With the rapid development of e-commerce industry, online shopping has become a craze. growth transaction volume on platforms, large amount data been accumulated. From information these users, lot very valuable can be mined, such as defects products and actual needs users. In view existing collection method is not mature, in this paper, electric business platform system architecture planning design increases function management module. new Naive Bayes model established by using HBase distributed database instead traditional database. Based optimization extraction important product, dataset updated. Through efficiency test method, scalability ability test, accuracy context was sorted out after integration, sources trading were out, analysis collected conducted to optimize verify feasibility method.