计算机与现代化 ›› 2020, Vol. 0 ›› Issue (08): 100-104.doi: 10.3969/j.issn.1006-2475.2020.08.016

• 数据库与数据挖掘 • 上一篇    下一篇

基于MongoDB的气象数据存储检索系统#br#

  

  1. (安徽省公共气象服务中心,安徽合肥230031)
  • 收稿日期:2020-04-16 出版日期:2020-08-17 发布日期:2020-08-18
  • 作者简介:陈浩(1978-),男,安徽全椒人,工程师,学士,研究方向:气象信息技术,E-mail: 2091142541@qq.com; 张亚(1980-),男,高级工程师,学士,E-mail: 2793905312@qq.com; 罗希昌(1986-),男,工程师,硕士,研究方向:计算机应用,人工智能,E-mial: 591047875@qq.com; 张亚力(1990-),女,助理工程师,硕士,研究方向:计算机应用技术:E-mail: zhangyaliit@163.com; 刘文静(1982-),女,工程师,硕士,研究方向:行业气象服务,E-mail: 3270293240@qq.com。
  • 基金资助:
    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)

Meteorological Data Storage and Retrieval System Based on MongoDB

  1. (Anhui Public Meteorological Service Center, Hefei 230031, China)
  • Received:2020-04-16 Online:2020-08-17 Published:2020-08-18

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。

关键词: 气象数据, MongoDB, 存储, 检索

Abstract: 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.

Key words: meteorological data, MongoDB, storage, retrieval

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