Design And Implementation Of E-commerce Guidance Management System Under Big Data

With the emergence of ubiquitous networking,e-commerce intelligence,Internet of Things,and cloud computing technology,people have already entered the century of information "big bang" and spawned the era of big data.In this new era,the filtering of massive information is a problem people face.When the demand for people to buy goods is not clear or they choose to be anxious,the shopping guide system can filter the user's potential favorite products by analyzing the user's consumption behavior data and user static data.With this feature,shopping guide system plays an important role in the development of e-commerce.As the massive data information of various e-commerce platforms has accumulated over time,the data pressure faced by the shopping guide system is enormous.In order to ensure that the system can quickly respond to users,it is urgent that the shopping guide system has the computing power to handle big data.At present,as the technology of Hadoop's ecosystem continues to improve,it has an increasingly large framework with large computing power.This paper compares and analyzes the MapReduce computing framework and high-performance Spark computing framework in Hadoop,and comprehensively considers the use of Spark computing framework in the design and implementation of this paper,in order to greatly increase the running speed of the shopping guide system.At the same time,this article hopes that the function-optimized shopping guide system can improve the shopping guide or recommendation ability of the existing e-commerce shopping guide system or recommendation system,enhance the user experience of the system platform,enhance user dependence,achieve economic and social benefits to create again.In view of the above narrative argumentation,this article first elaborated the background of the topic selection and relevant research at home and abroad.Later,his article also discussed the relevant big data processing technologies in depth,including MapReduce computing framework,distributed Spark computing framework and distribution in Hadoop.File system HDFS.On the basis of feasibility analysis,this paper presents a new design of the shopping guide recommendation system combined with big data technology,and elaborates on the core function of the shopping guide system—the shopping guide function.At the same time,the paper also introduces the related recommendation algorithm and its application of recommendation algorithm.Finally,this article combines the corresponding big data technology,designed and implemented a shopping guide system,and elaborated the core functions and implementation methods.