基于分布结构自适应筛选的数据库存储优化设计

Database storage optimization based on adaptive filtering of distributed structure

摘要:

通过对数据库的存储结构优化设计,提高数据库的吞吐量。传统方法采用存储节点校验数据适应度分区的数据库存储模型,数据库中存在重复冗余数据,不能自适应滤除,导致数据存储开销较大。提出了一种基于分布结构自适应筛选的数据库存储优化模型,首先进行数据库的存储机制和分布式数据结构分析,采用相空间重构方法进行存储空间的结构分布重组,采用分布结构自适应筛选方法对提取的数据信息流进行重复冗余数据滤波处理,改善数据在数据库存储空间中的结构分布,实现数据库存储优化。仿真结果表明,采用改进的方法进行数据库构建,能提高数据库存储吞吐量,降低数据存储开销,提高数据库的访问和调度性能,展示较好的应用价值。

Abstract:

Through to the database storage structure optimization design, improve the throughput of the database.Traditional methods using calibration data storage nodes fitness database storage model of partition, repeat redundant data exist in the database, not adaptive filtering, data storage overhead.Put forward a kind of adaptive filter based on the distribution structure of database storage optimization model, the first database storage mechanism and the distributed data structure analysis, phase space reconstruction method is used to reorganize, the structure of the storage space distribution distribution structure adaptive filtering method is used to extract the data flow of repeat redundant data filtering processing, improving the structure of the data in the database storage space distribution, optimized database storage.The simulation results show that the improved method of database construction, can improve the database storage throughput, reduce data storage overhead, improve the performance of database access and scheduling show good application value.