Campus Network Database Performance Optimization Technology And Its Applications

Campus network database usually takes on such characteristics as multi-media, heterogeneous, frequent queries,and a large quantity of data. But with the deepening of the campus network applications, the campus network database has become an ever-growing volume of data, resulting in a significant reduction in the database performance. It has theoretical significance as well as practical significance to know how to optimize the performance of the campus network database which is on the composition of structured data to enhance its performance, and how to reasonably design the structure of multi-media database to enhance the efficiency of its inquiry, as well as how to pertinently design query algorithm of the campus network database.The main way of optimization for database logic design is to design the right database structure to meet the Third Normal Form. On the base of expatiating the use of normalized designs to optimize database performance, and in order to reduce the number of multi-table joins and avoid frequently using the clustering function,furthermore, in order to optimize the performance of large-capacity databases among which there are large differences in the frequency of visits, the author of this paper puts forward denormalization design methods to optimize campus network database which are composed by structured data. Meanwhile, by analyzing the features of the multi-media database in the campus network, the author also adopts method which is based on data classification and expansion of relation models to builde a multi-media database. This method is easily operated and its capability is good.As we know, we can upgrade the database query performance by establishing an appropriate index, using the stored procedures and optimizing SQL statements. The author firstly analyzes the optimization methods of query. Secondly, according to the features of campus network database such as the queries repeatability is strong, there are some laws in updating the data, and in order to resolve the problem that the high-capacity database query of the statistical analysis is very slow, the author brings forward a method of query optimization algorithm which is based on semantic information and choosing a right chance to prefetch. By preserving, analyzing the repetitive semantic information, it will choosing a right chance to prefetch to check the high-frequency data to the Cache to successfully achieve the purpose of enhancing the speed of inquiry.The source of this article is A Project Supported by Scientific Research Fund of Hunan Provincial Education Department. In the practice of the performance optimization of campus network database, we can use performance monitoring and analysis tools to analyze the database performance status, or use the normalized technology and denormalized technology to improve structure design, or use the method based on data classification and the expansion of relation models to reconstruct logic design of multi-media database, or use the method of query optimization algorithm based on the semantic information and choosing the right chance to prefetch to improve the query performance of the statistical analysis in large-capacity databases. In the practice of optimizing the performance of it, the result indicates that the performance of the campus network data has been increased dramatically.