[1]刘骥超,叶 钒,谢寒生.云计算环境下气象大数据的应用研究[J].计算机技术与发展,2019,29(05):168-171.[doi:10. 3969 / j. issn. 1673-629X. 2019. 05. 035]
　LIU Ji-chao,YE Fan,XIE Han-sheng.Research on Application of Large Meteorological Data in Cloud Computing Environment[J].,2019,29(05):168-171.[doi:10. 3969 / j. issn. 1673-629X. 2019. 05. 035]
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云计算环境下气象大数据的应用研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年05期
页码:
168-171
栏目:
应用开发研究
出版日期:
2019-05-10

文章信息/Info

Title:
Research on Application of Large Meteorological Data in Cloud Computing Environment
文章编号:
1673-629X(2019)05-0168-04
作者:
刘骥超1; 2; 叶 钒1; 2; 谢寒生1; 2
1. 海南省气象信息中心,海南 海口 570203;2. 海南省南海气象防灾减灾重点实验室,海南 海口 570203
Author(s):
LIU Ji-chao1; 2; YE Fan1; 2; XIE Han-sheng1; 2
1. Meteorological Information Center of Hainan Province,Haikou 570203,China;2. Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province,Haikou 570203,China
关键词:
云计算; Hadoop; MapReduce; 气象数据
Keywords:
cloud computing; Hadoop; MapReduce; meteorological data
分类号:
TP311
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 05. 035
摘要:
随着气象现代化的逐步推进及气象观测技术的快速发展,随之而来的是气象数据量的指数级增长,气象预报技术也是日新月异尤其是数值预报技术等,同时公众对预报准确率及精确预报的要求也越来越高。 为了提高气象预报的准确率以及气象服务水平,必须对这些海量的气象数据进行更多的挖掘利用,但利用传统技术处理这些海量数据的效率已无法满足现行业务需求,互联网技术的发展也为这些海量数据的处理提供了新的技术。 文中主要利用云计算技术 Hadoop对气象数据进行处理,将气象数据清洗处理后存储于分布式文件系统 HDFS,在此基础上采用 MapReduce 编程架构对气象数据进行复杂检索。 进行了参数调优并得到了一个初步的结果,为后续优化工作提供了更多思路以及结果对比。
Abstract:
With the gradual advance of meteorological modernization and the rapid development of meteorological observation technology,the exponential growth of meteorological data is followed. The technology of weather forecasting is also changing with each passing day,especially the numerical forecasting technique. Meanwhile,the public demand for forecast accuracy and precise forecast is also higher. In order to improve the accuracy of weather forecast and the level of meteorological service,more mining and utilization of these massive meteorological data must be made. However,the efficiency of using traditional technology to deal with these massive data can’t meet the current business needs. The development of Internet technology also provides new technologies for the processing of these massive data. We mainly use cloud computing technology Hadoop to process meteorological data. After the meteorological data is cleaned and processed,it is stored in the distributed file system HDFS. On the basis,the MapReduce programming frame is used for complex retrieval of meteorological data. We preliminarily conduct parameter tuning and obtain a preliminary result,which provides more ideas and results comparison for the subsequent optimization work.

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更新日期/Last Update: 2019-05-10