Relational Database Based On Semantic Cache Technology Research

With the increasingly high degree of social information, the amount of data for a varietyof applications handled by the system also with the growing development needs. In particular,a sharp increase in corporate data, and multiuser sharing of information to the database facingthe access needs of increased traffic increases. These problems can lead to database transac-tion throughput increases rapidly, the response time, data processing performance. Therefore,how to improve the performance of data processing is particularly important. Caching techni-ques to improve an effective means of data processing performance, but the prefetch cachereplacement policy to have a great impact on the performance of the cache. Drawn in the comprehensive analysis of the existing cache technology development, application mode and thekey technologies on the basis of the semantic cache can effectively reduce the request interaction with the database overhead and improve the response speed of the database and improvesystem performance.The semantic caching technology is based on user history query result sets and their semantic description of the caching mechanism, compared to the traditional table caching, page caching and tuple caching technology, more to save communication costs, reduce the cache cap-acity and support network disconnection, etc.. In this paper, a comprehensive analysis of thevarious caching techniques, relational database as a research platform, the use of semantic inf-ormation in the query cache to match, then the dynamic tracking and analysis of the timing ofuser access, access to the amount of content, the business association and other users to accessfeatures, and design a user-based access to the features of semantic caching structure propos-ed semantic cache replacement algorithm based on user access to features.Semantic cache coherence maintenance algorithm analysis on the basis, in order to ensure the reliability of the system will update semantics and caching semantics to compare and cu-tting proposed semantic cache coherence based on the semantic cut maintenance update rulesand constraint conditions. On this basis, a detailed description of the database consistency str-ong consistency algorithm update maintenance algorithms and ondemand request. The algorit-hm will update the semantics of the statement and the local cache language pay to take the intersection pinpoint the update region to minimize the data access and refine the grain size tobe updated property will be updated, effectively reducing the data access data communicationoverhead.