赵亚楠, 李朝奎, 肖克炎, 范建福. 基于Hadoop的地质矿产大数据分布式存储方法[J]. 地质通报, 2019, 38(2-3): 462-470.
    引用本文: 赵亚楠, 李朝奎, 肖克炎, 范建福. 基于Hadoop的地质矿产大数据分布式存储方法[J]. 地质通报, 2019, 38(2-3): 462-470.
    ZHAO Ya'nan, LI Chaokui, XIAO Keyan, FAN Jianfu. Research on distributed storage method of geological and mineral big data based on Hadoop[J]. Geological Bulletin of China, 2019, 38(2-3): 462-470.
    Citation: ZHAO Ya'nan, LI Chaokui, XIAO Keyan, FAN Jianfu. Research on distributed storage method of geological and mineral big data based on Hadoop[J]. Geological Bulletin of China, 2019, 38(2-3): 462-470.

    基于Hadoop的地质矿产大数据分布式存储方法

    Research on distributed storage method of geological and mineral big data based on Hadoop

    • 摘要: 随着TB级乃至PB级地质矿产大数据时代的到来,地质大数据的存储难题一直困扰着地质界,传统的地质数据存储与服务模式面临诸多难题。结合Hadoop提出了一种新的基于云计算环境的地质矿产数据存储方法,将该方法与传统Oracle数据库存储方法进行了数据存储实验对比。实验结果表明,该存储方法比传统方法更高效,同时有效地解决了Hhadoop存储中出现的小文件存储问题。研究成果为地质矿产数据的存储与管理提供了一种新的管理方法。

       

      Abstract: With the advent of the era of big data of geology and mineral resources of terabytes and petabytes grades, geological large data storage problem has been bothering geologists. The traditional pattern of geological data storage and service faces many problems. In this paper, based on Hadoop, the authors put forward a new kind of geological and mineral resources data storage method based on cloud computing environment, and a comparative study of this method and the traditional storage method of the Oracle database data storage experiment was carried out. The experimental results show that the method proposed in this paper is more efficient than the traditional method and can effectively solve the problem of small file storage in Hadoop storage. The research results provide a new management method for the storage and management of geological and mineral data.

       

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