The Supplier Evaluation System Based On Hadoop Research And Design

Supplier is not only a source of enterprise’s logistics, but also to enhance the competitiveness of enterprise strategy. And along with the increasingly fierce market competition, customer demand for products become more diversification and individuation.Faced with this situation, you want to win a higher corporate profits should be taken to shorten the delivery time, improve product quality and reduce the cost of other measures to the rapid response to market demand. Therefore, the suppliers of good management, the key to its ability to establish a stable and reliable supplier of common development team,which is the source of corporate profits to improve and enhance product quality, but also to ensure the competitiveness of enterprises effective protection.This article is based on the Zibo Mining Group’s information technology platform for the Group’s areas of square Supplies supplier evaluation and systematic research and design.Because the production and operation of coal enterprises relatively complex, from large Shearer, boring machines and other production equipment, to small bolt, fittings and other parts have different regions, different production scale suppliers to supply, Therefore, in order to make the enterprise in the vast amounts of material can be more intuitive, convenient,reasonable selection of the suppliers, the paper chose on the large data storage and processing is of great advantage of Hadoop platform for the enterprise to produce the large amount of material and supplier data analysis process. Paper first analyzes the related situation of enterprises in the purchase of material supplier selection and supplier evaluation model is designed. Secondly based on the current development and application of big data and Hadoop related technologies were analyzed, and puts forward the Hive combined with the Hadoop way to supplier and supplies such as data integration analysis, and store it on the HDFS, then to select the suppliers by having strong learning ability of the BP neural network algorithm is combined with the form of graphs classification processing, and supplier evaluation results are obtained. Finally, based on Spring MVC framework for supplier evaluation system designand implementationlier evaluati, the system includes landing page, user management, role management and supp on results query, and other functions. Allows companies to evaluate the selection of suppliers is more scientific, comprehensive, objective and accurate.