The Effective Application of Cloud Computing Technology in Large Data User Behavior Engine Design

Abstract

With the constant development of socialist modernization construction in our country, our country's computer information technology has made effective progress, and makes the world into an information age. People's production and life style experience a series of change. However, with the emergence of information diversity and multi-user mode, traditional computer information technology already can't satisfy people's needs, and the development and application of cloud computing technology come to the stage. This article focuses on analyzing the big data user behavior engine design under cloud computing technology, covering big data flow management, multi-user system design, and other aspects to explore the effect of the system test. In recent years, China's mobile Internet technology has made full development, which makes the Internet operators in our country face a new development opportunity and began from traffic management to flow management. The law of user behavior is analyzed to explore the real demand of market and the users. In order to fully meet the changing needs of users, operators must constantly develop and launch new products and strengthen the function of computer technology. Cloud computing technology is such kind of engine system which can satisfy the analysis and processing of huge amounts of data. RESEARCH ON CLOUD COMPUTING SYSTEM OVERALL DESIGN The overall architecture of cloud computing system This study mainly uses cloud computing technology’s huge amounts of data computing to set up complete mobile Internet data mining analysis system. Realize the analysis for Internet user behavior engine, and according to the user's preferences online habits and behavior, provide users with targeted personalized service and form a unified organic whole of data collection, analysis and service type and marketing strategy to improve enterprise's marketing efficiency. In addition, cloud computing system mainly realizes data collection with the help of FTP server, and makes distributed computing and data batch processing at the system interface. Large data shall be deposited in Hbase database. The system can not only realize mass data storage, but those unstructured data storage. Then through Hive integration layer and summary EIL processing, use MapReduce data analysis model to transmit the processing result into the database. The system’s overall structure is shown in Figure 1: 3rd International Conference on Materials Engineering, Manufacturing Technology and Control (ICMEMTC 2016) © 2016. The authors Published by Atlantis Press 1351 Figure 1 The overall architecture of cloud computing system System topology and function distribution System topology mainly refers that a server is taken as Hapdoop platform’s master node server, and the others are Hapdoop platform’s node servers. In general, node server can be dynamically extended according to the actual need, and the master node server not only assigns tasks and flow to node server, but also monitors the work execution of the node server. More than one node server participates to complete the task, and it can improve data processing efficiency. The master node server’s software running status is shown in Figure 2: Figure 2 Master node server function structure