摘要
近年来气象数据呈现多源化和爆炸式增长的态势,传统的关系型数据库已不能满足气象数据发展的需求。结合气象数据的地理空间特点,提出一种基于MongoDB的气象数据存储检索系统。本系统对气象数据建立空间索引,加快了气象数据的查询效率,为精细化、格点化预报提供了有力的支撑。实验结果表明,对于海量的气象数据,MongoDB具有强大的存储和检索能力,各个方面的性能明显优于关系型数据库。
In recent years,meteorological data shows a trend of multi-source and explosive growth,the traditional relational database can not meet the needs of meteorological data development.In combination with the geospatial characteristics of meteorological data,a MongoDB-based meteorological data storage and retrieval system is proposed.The system establishes spatial index of meteorological data,which speeds up the query efficiency of meteorological data and provides a strong support for fine and lattice forecast.The experimental results show that MongoDB has strong storage and retrieval capability for massive meteorological data,and its performance in all aspects is obviously better than that of relational database.
作者
陈浩
张亚
罗希昌
张亚力
刘文静
CHEN Hao;ZHANG Ya;LUO Xi-chang;ZHANG Ya-li;LIU Wen-jing(Anhui Public Meteorological Service Center, Hefei 230031, China)
出处
《计算机与现代化》
2020年第8期100-104,共5页
Computer and Modernization
基金
国家自然科学基金资助项目(41575155)
安徽省气象局新技术集成项目(AHXJ201805)。
