摘要
针对传统多时态地形数据采用磁盘存储,导致高频存取的现势性数据读取效率低的问题,提出了MongoDB数据库支持下内外存结合的多时态海量地形数据存储管理的优化方法。该方法根据用户对现势性地形数据的高频访问需求,设计MongoDB支持的时态数据分片和索引的优化策略,通过将最新地形数据常驻于内存中,将历史数据存储于磁盘中,保证了最新的地形数据在内存中快速命中并传输给用户,可提高调度效率和绘制的流畅性。
The traditional method of managing multi-temporal data uses disk storage, which results in the low reading efficiency, especially for the latest data with high frequency access. This paper proposes a storage management optimization method for multi-temporal terrain data combining internal and external memory, supported by MongoDB database. The method designs the strategy of data distributed storage and index optimization, according to the requirement of high frequency access to the latest data. By keeping the latest terrain data resident in RAM and storing the historical data on disk, the method makes sure that the latest terrain data can be quickly hit in RAM and transmit to users efficiently, which greatly improves the scheduling efficiency and the fluency of visualization.
出处
《地理信息世界》
2014年第4期37-42,共6页
Geomatics World
基金
国家自然科学基金项目(41101354)资助
青年科学基金项目(41301431)资助
关键词
地形
内外存结合
多时态
数据管理
MONGODB
terrain
combination of internal and external memory
multi-temporal
data management
MongoDB
