Research On Database Compression Technology And Application In Dam Business System

The 21st century is a era of information explosion, and its related data stores in the relational database, which causes a tremendous pressure to memory, and low access efficiency. So the relational database compression technology got a lot of attention from the industry.The reconstruction of the Fengman dam is a major water conservancy project of the country, which costs even more than 10 years to complete, during which there're thousands of bidding disciplines, construction contract, purchase contract, claims and fines, financial settlement and other business data, which are not only used for real-time application, but also stored as historical record.In view of the above situation, database compression technology to the software of dam business system and comprehensive consideration between the space and efficiency are very necessary and meaningful.This paper bases on the actual project of Jilin Fengman hydropower station.First, the technology related to database compression is studied, in which spliting-compression is the key research object, including the definition of small-range attributes, the study of identifying algorithms and spliting-compression, analyzed the performance bottleneck of current resolution of compression algorithm.Then combining with the background of dam business, the paper analyzed the characteristics of the dam business data, which leaded to the applicability in dam business system for splitting-compression.From the angle of the access probability, the paper put forward the concept of boundary attribute, and based on boundary attribute and the boundary value, it also put forward the optimization of spliting-compression algorithm, and the optimum effect are analyzed in theory,then realized the algorithm in the dam business system; The paper presented at last the testing and analysis of the algorithm. Results show that optimized spliting-compression saves 15%-22% space and it has a 11% better performance, also the more tuples are, the better performance it has.Generally, the relational database compression method, which has a great generality, can also apply to other relational database management software.