基于动态索引和缓冲池的空间数据服务优化技术

Spatial Data Service Optimizing Based on Dynamic Index and Buffer Pool

以提高海量空间数据服务的性能为目标,针对数据访问行为和数据索引机制进行了研究,基于人的因素对于数据的影响,提出了非均匀空间访问概念、基于关注度的动态索引和缓冲池技术,设计实现了双索引运行模式,并结合实际数据进行了仿真验证。结果表明,该方法可有效提高数据命中速度和总体服务性能。

Aiming at the performance advance of spatial data service,data accessing behavior and index scheme were researched. Based on the influence from human to data,a non-uniform data accessing conception,dynamic index and buffer pool basing on attention degree were put forward,and a double-index application pattern was designed. Emulational experiments with real data prove that the methods can improve the data indexing speed and total service performance efficiently.