The Design And Implementation Of Beijing Wumart Order System

In the past,in the purchase and delivery of the purchase and delivery,the logistics company and mail system need to be carried out with the aid of logistics companies and mail systems.The work efficiency is very low.Through the establishment of a complete set of order system within the group,it can not only quickly respond to the various supermarkets in Beijing,but also analyze the past data of various supermarkets and groups,so that the future can be made for the future.Big data mining plays a solid foundation for supermarket initiative.The development and implementation of the object beauty supermarket order system based on Web Service is designed to analyze a nationwide networked business system,which is to add all the chain supermarket systems into the business system,to realize the unified management of the headquarters for the order of the central store,and to preserve the original and franchisee.The system.This article will implement the business software that is used to conduct query transactions within the company,which is completed with the basic framework of web service services.In the study of this topic,the web service should be a priority.First,from the overall framework on the analysis of the implementation method of the software,introduces the meaning of Service Web,including its internal structure,and construction methods,and then study the related model in order Wumart system,through the design of database model design,finally completed part of the target internal beauty ordering system.This subject is implemented on the service class that we want to use.Java is the programming language used for this task to accomplish most tasks,including the initial use of data types,the achievement of related services,and the user interface operation.Through the excellent framework and optimized database structure,the project can efficiently conduct large-scale data transmission in the process of internal use,and the efficient way of data aggregation lays the foundation for the future analysis of big data.