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首页> 外文期刊>American Journal of Applied Scientific Research >Innovation Method of Distributed Storage for Huge Data of Geological and Mineral Resources Based on Hadoop
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Innovation Method of Distributed Storage for Huge Data of Geological and Mineral Resources Based on Hadoop

机译：基于Hadoop的海量地质矿产数据分布式存储的创新方法

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摘要

With the emergence of big data of TB and PB geological and mineral resources, the storage of large geological data has become a worldwide problem puzzling geologists. The traditional storage and service model of geological data is facing a great challenge. For example, when the scale of data increases dramatically, general relational database can not solve the problem of insufficient scalability, stability and efficiency of database system. In response to the above problems, this paper proposes a new method of geological and mineral data storage based on cloud computing environment combined with hadoop. Taking the mineral resources potential evaluation data of Chongqing as the research object, The proposed method in this paper is compared with the traditional Oracle database storage method in data storage experiments: (1) Small file optimization comparative experiment; (2) Hadoop and Oracle comparative experiment. The performance of writing operation, memory occupancy, data import and data export are tested in different way, and the comparison chart of performance is given. The experimental results show that the new storage method proposed in this paper is more efficient than the traditional method. At the same time, it effectively overcomes the problem of small file storage in Hadoop storage. The research results provide a new technical for the storage and management of geological and mineral data all over the country.
机译：随着TB和PB地质和矿产资源大数据的出现，大地质数据的存储已成为困扰地质学家的全球性难题。传统的地质数据存储和服务模型面临着巨大的挑战。例如，当数据规模急剧增加时，一般的关系数据库无法解决数据库系统的可伸缩性，稳定性和效率不足的问题。针对上述问题，提出了一种基于云计算环境结合Hadoop的地质矿产数据存储新方法。以重庆市的矿产资源潜力评价数据为研究对象，将本文提出的方法与传统的Oracle数据库存储方法进行数据存储实验进行比较：（1）小文件优化对比实验; （2）Hadoop与Oracle的对比实验。以不同的方式测试了写入操作，内存占用，数据导入和数据导出的性能，并给出了性能对比图。实验结果表明，本文提出的新存储方法比传统存储方法更有效。同时，它有效地克服了Hadoop存储中小文件存储的问题。研究结果为全国地质和矿产数据的存储和管理提供了一种新技术。

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