基于实时同步的分页缓存及分区存贮的海量数据查询优化研究

Research on Massive Amounts of Data Query Optimization of Cached Pages and Partition Store Based on Real-Time Synchronization

随着海量数据的集中出现,对数据中心的海量数据的组织、查询和存取日益成为影响其性能的关键因素。传统的数据库优化技术只能实现降低查询处理时间或减少存储以及维护开销中的某一个或者某几个,无法达到同时优化的效果。提出一种基于实时同步的分页缓存及分区存贮(DBMS-Cache-DCS)的海量数据查询优化方法,实验结果表明,通过该方法可以同时降低访问处理时间。

With the emergence of massive data, the massive data of organization, query, and access of the data center is increasingly becoming a key factor affecting its performance. The optimization techniques of traditional database can only achieve lower processing time, or reduce storage and maintenance overhead in one or several functions, which can not be achieved while optimizing results. Presents an optimiza-tion method of real-time synchronization and paging Cache partition storage （DBMS-Cache-DCS）. The experimental results show that this method can reduce the visiting and aprocessing time.