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作 者:李真 彭运星 吴彬彬 Li Zhen;Peng Yunxing;Wu Binbin(School of Resource and Environmental Engineering,Wuhan University of Technology,Wuhan Hubei 430000,China;Shenzhen Pengrui Information Technology Co.,Ltd.,Wuhan Hubei 430000,China)
机构地区:[1]武汉理工大学资源与环境工程学院,湖北武汉430000 [2]深圳鹏锐信息技术股份有限公司,湖北武汉430000
出 处:《现代工业经济和信息化》2023年第6期65-67,共3页Modern Industrial Economy and Informationization
摘 要:在物联网、移动互联网、云计算等信息技术的引擎带动下,大数据得到了迅猛的发展,攀升规模让人目不暇接,大数据的挖掘已经成为各个领域的焦点。在云平台开源项目Apache的构建中,Hadoop是重要的功能载体。基于Hadoop框架的应用,计算机集群得以快捷地实现。在油田勘探开发中越来越多的数据被挖掘出来,传统的Javs EE技术严重滞后于现代油田勘探开发功能需要,新的技术整合势在必行。根据分布式文件系统HDFS,依托Hadoop构建云平台数据存储结构模型,在油田勘探开发作业中真正实现了数据存储和查询的统一性,以及超强的灾备和预警能力,不仅显著提高了多表联合查询效率,真正意义上实现了数据资源的共享。Driven by the engines of information technology such as the Internet of Things,mobile Internet and cloud computing,big data has developed rapidly,climbing to a dizzying scale,and the mining of big data has become the focus of various fields.In the construction of the cloud platform open source project Apache,Hadoop is an important functional carrier.Based on the application of the Hadoop framework,computer clusters can be implemented quickly.As more and more data is mined in oilfield E&P,traditional JavsEE technology is seriously lagging behind the functional needs of modern oilfield E&P and new technology integration is imperative.Based on the distributed file system HDFS,the cloud platform data storage structure model is built based on Hadoop,which truly realises the unity of data storage and query in oilfield E&P operations,as well as superb disaster recovery and early warning capabilities,not only significantly improving the efficiency of multi-table joint query,but also truly realising the sharing of data resources.
关 键 词:HADOOP 油田勘探 云平台 数据存储模型 研究与应用
分 类 号:TE34[石油与天然气工程—油气田开发工程] TP333[自动化与计算机技术—计算机系统结构]
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