[1]郭 茜,王 彪,汪 华,等.贵州省气象大数据平台架构设计[J].成都信息工程大学学报,2018,(05):531-535.[doi:10.16836/j.cnki.jcuit.2018.05.008]
GUO Xi,WANG Biao,WANG Hua,et al.Architecture Design of Guizhou Meteorological Big Data Platform[J].Journal of Chengdu University of Information Technology,2018,(05):531-535.[doi:10.16836/j.cnki.jcuit.2018.05.008]
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GUO Xi,WANG Biao,WANG Hua,et al.Architecture Design of Guizhou Meteorological Big Data Platform[J].Journal of Chengdu University of Information Technology,2018,(05):531-535.[doi:10.16836/j.cnki.jcuit.2018.05.008]
贵州省气象大数据平台架构设计
成都信息工程大学学报[ISSN:1006-6977/CN:61-1281/TN]
卷:
期数:
2018年05期
页码:
531-535
栏目:
电子信息科学与技术
出版日期:
2018-04-30
- Title:
- Architecture Design of Guizhou Meteorological Big Data Platform
- 文章编号:
- 2096-1618(2018)05-0531-05
- 关键词:
- 气象大数据平台; Impala数据库集群; GreenPlum数据库集群
- Keywords:
- meteorological big data platform; Impala cluster; GreenPlum
- 分类号:
- TP311.13
- 文献标志码:
- A
- 摘要:
- 气象大数据建设是气象信息化和气象现代化的重要内容之一。近年来,随着气象数据量暴涨,现有的气象设备与信息技术手段已很难满足气象业务需求。贵州省气象局内存在各个业务系统林立,部门内数据分散、气象数据收集缺乏全面性和系统性,“信息孤岛”的现象严重,数据整合受到不同系统和软件开发平台的限制,服务器利用率低下,CPU、内存、磁盘空间等资源得不到有效利用,数据存储存在单点故障等问题。针对以上问题,贵州省气象信息中心提出气象大数据平台整体架构的设计,帮助提高气象预报预测的准确率,使数据存储管理和服务实现集约高效和数据共享。对气象大数据平台建设中气象数据采集、数据存储和数据处理进行了概括,介绍了气象信息系统的现状,从完善顶层设计入手,对集群数据库方案选择进行对比,设计出合理、高效的气象大数据平台,实现气象大数据行业内部与外部的融合与共享。
- Abstract:
- The construction of meteorological big data is one of the important contents of the meteorological information and the modernization. In recent years, with the rise of meteorological data suddenly and sharply, the existing meteorological equipment and information technology methods are difficult to meet the needs of meteorological services. There are various business systems in Guizhou Meteorological Bureau. Data scattered in departments, data collection lack of comprehensiveness and systematisms, "information isolated island" is serious and the data integration is limited to different systems and software development platforms, server utilization rate becomes low, and there sources of CPU, memory, disk space can't be used effectively, and data storage exists single point of failure. In view of the above problems, Guizhou Meteorological Information Center proposed the design of the overall framework of the meteorological big data platform, which helps to improve the accuracy, intensive, efficient and data sharing of the forecast, and make the data storage management and service achieve intensive and high efficient data sharing. This paper summarizes meteorological data collection, data storage and data processing in the construction of meteorological big data platform, and it introduces the present situation of the meteorological information system. From the improvement of the top-level design, compare the selection of the cluster database, and designed a reasonable and efficient meteorological big data platform, in order to realize the integration and sharing of meteorological big data industry.
参考文献/References:
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备注/Memo
收稿日期:2018-04-27 基金项目:贵州省科技技术资助项目(黔科合支撑[2017]2819)
更新日期/Last Update:
2018-04-30