MapReduce在气象数据传输时效统计中的应用
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公益性行业(气象)科研专项(GYHY201206031)


Application of MapReduce in the statistic of meteorological data transferring efficiency
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    摘要:

    气象数据的传输时效保障已成为探测和信息部门的重要工作之一,快速统计各类数据到报率和及时率成为一项迫切需求.基于MapReduce编程模型设计了各类数据到报率和及时率的算法,在Hadoop平台上利用该算法实现了各类数据的逐日到报率和及时率的统计,选择文本方式和Sequence File方式作为MapReduce计算模型的输入数据源进行对比试验.试验结果表明,Sequence File作为数据源能更好地提升MapReduce并行运算的性能.

    Abstract:

    The rapid statistic of the efficiency of meteorological data transferring has become a pressing need for information center of Beijing Meteorological Bureau.In order to improve the transferring efficiency of meteorological data, an algorithm was designed based on MapReduce model for statistics of the arriving ratio and timely rate of meteorological data.The algorithm was then realized on Hadoop platform and comparative experiments were done using text file and Sequence File as input source data.Results show that the MapReduce-based algorithm performs better with Sequence File data.Compared with traditional statistic processes, the proposed algorithm is high in effectiveness and simple in process flow, thus is feasible and applicable for statistic of meteorological data transferring efficiency.

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赵文芳,刘旭林,桑雪竹,王鳞春. MapReduce在气象数据传输时效统计中的应用[J].南京信息工程大学学报(自然科学版),2018,10(2):238-243
ZHAO Wenfang, LIU Xulin, SANG Xuezhu, WANG Linchun. Application of MapReduce in the statistic of meteorological data transferring efficiency[J]. Journal of Nanjing University of Information Science & Technology, 2018,10(2):238-243

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  • 收稿日期:2016-04-08
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  • 在线发布日期: 2018-04-04
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