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数据库与MapReduce融合的大数据管理技术探索
作者姓名:张延松
作者单位:1.数据工程与知识工程 教育部重点实验室(中国人民大学),北京 100872;2.中国人民大学 信息学院,北京 100872;3.中国人民大学 中国调查与数据中心,北京 100872
摘    要:大数据管理是随着时代和技术发展而提出和演化的命题。随着大数据从传统的结构化数据向无结构化数据的转移,Key/value存储、NoSQL、MapReduce等技术成为数据库技术之外大数据管理的多样化手段。MapReduce以其开放性成为当前大数据的代表技术,在大数据应用中,如何让MapReduce与数据库高效协同,发挥各自的技术优势和平台优势,提供高性能、高可扩展性、高可用性的大数据服务平台成为重要的研究课题。本文讨论在大数据存储、管理与服务主题上的观点和技术路线,探索将MapReduce作为数据库新的应用与开发平台的可行性。

关 键 词:大数据  Key/value存储  MapReduce  大数据仓库  
收稿时间:2012-08-30

Research on Big Data Management with Architecture of Fusion of Database and MapReduce
Authors:Zhang Yansong
Affiliation:1. Key Laboratory Data Engineering and Knaledge Ergineering Lab, Renmin University of China, Beijing 100872, China; 2. School of Information, Renmin University of China, Beijing 100872, China; 3. National Survey and Research Center, Renmin University of China, Beijing 100872, China
Abstract:Big data management is a proposition that came up and is evolving along with time and technology development. As big data research focus moves from traditional structured data to unstructured data, Key/value store, NoSQL, MapReduce etc. became diverse means for big data management besides database. MapReduce is the mainstream technique for big data because of its open feature. It is a critical issue to make MapReduce cooperate with database efficiently in order to provide a big data service platform of high performance, high scalability and high availability. This paper discusses the technical opinions on big data storing, management and service topics, and explores the feasibility of use MapReduce as new application and development platform for databases.
Keywords:Big data  Key/value store  MapReduce  Big data warehouse  
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