Redis缓存技术在自动气象站资料调用中的优化应用  

Optimized Application of Redis Caching Technology in Automatic Weather Station Data Call

作　　者：詹利群 程海林 任晓炜 ZHAN Li-Qun;CHENG Hai-Lin;REN Xiao-Wei(Meteorological Information Center,Guangxi Zhuang Autonomous Region,Nanning 530022,China;Chengdu University of Information Technology,Chengdu 610225,China)

机构地区：[1]广西壮族自治区气象信息中心,南宁530022 [2]成都信息工程大学,成都610225

出　　处：《计算机系统应用》2019年第5期77-83,共7页Computer Systems & Applications

基　　金：广西科技重点研发计划项目(桂科AB16380267);国家档案局科技项目(2016-X-06)~~

摘　　要：为了提高气象自动站资料的检索查询效率,采用基于内存Key-Value结构的Redis数据库技术,通过搭建Redis数据库集群,把数据缓存在内存中并实现主从复制,提出一种适合气象自动站数据特性的数据存储结构模型,使得高频次访问的气象自动站数据能够直接从内存中读取,有效地减少数据查询响应的时间.本文分析了逐小时自动气象站观测资料的调用情况和到报时间特性,并基于Redis分别从业务库、索引库和时间库对逐小时自动站资料进行存储设计和具体实现,最后通过实验比对,得出采用Redis缓存逐小时自动气象站观测资料的检索效率比直接访问CIMISS检索效率高,该方法也可以应用到其它资料的检索调用业务场景中,具有较好的推广应用价值.In order to improve the efficiency of retrieval and query of meteorological automatic station data, Redis database technology based on memory key-value structure is adopted. By building a Redis database cluster, the data are cached in memory and the master-slave replication is realized. A data storage structure model suitable for the characteristics of meteorological automatic station data is proposed, which makes high frequency access possible. Meteorological automatic station data can be read directly from memory, effectively reducing the time of data query response. In this study, the hourly automatic weather station observation data transfer and reporting time characteristics are analyzed. Based on Redis, the hourly automatic weather station data are stored and designed from business database, index database, and time database respectively. Finally, through experimental comparison, it is concluded that the hourly automatic weather station observation data are cached by Redis, and the retrieval efficiency of proposed method is higher than that of CIMISS. This method can also be applied to other information retrieval and invocation business scenarios, and has a good application value.

关 键 词：REDIS 缓存技术 自动气象站资料 优化应用 

分 类 号：P415.12[天文地球—大气科学及气象学] TP311.13[自动化与计算机技术—计算机软件与理论]