高校图书馆大数据服务关键技术研究

C. Ye
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引用次数: 6

摘要

随着高校图书馆信息技术的发展,高校图书馆的海量数据具有大数据的基本特征。然而,高校图书馆目前的现状是缺乏海量数据的分布式存储和计算模型,缺乏处理包括结构化、半结构化和非结构化数据在内的多种数据源的能力,缺乏简单、灵活的大数据服务应用模型。为了解决国内高校图书馆在服务创新中存在的海量数据分布式存储计算、多元数据源分布式管理、大数据服务简单灵活应用等问题,本文分析了大数据处理、Hadoop生态系统的研究内容以及高校图书馆对大数据服务的需求。提出了一种基于Hadoop的高校图书馆大数据服务技术框架。该框架包括海量数据的分布式存储与并行计算模型、多种数据源的分布式管理模型和高校图书馆多元化服务应用模型。该框架充分考虑了大数据环境下高校图书馆在数据存储与计算、数据管理、服务应用等方面的服务创新变化。它可以在一定程度上解决高校图书馆大数据服务的关键技术问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the key technology of big data service in university library
With the development of information technology of university library, the mass data of the university library has the basic characteristics of Big Data. However, the current situation of the university library is the lack of distributed storage and computing model for massive data, the lack of capacity to handl the diverse data sources, including the structured, semi-structured and unstructured data, the lack of a simple, flexible application model of big data service. In order to solve the problems in the service innovation of University Libraries in China, such as the problem of distributed storage and computation of massive data, the distributed management of diverse data sources, the simple and flexible application of big data services, this paper analyzes the research contents of big data processing, Hadoop ecosystem and the demand for big data services in University Libraries, and presents a technology framework for big data service in University Libraries based Hadoop. The framework includes the distributed storage and parallel computing model of mass data, the distributed management model of diverse data sources and the model of diversified service application for university libraries. This framework takes full account of the service innovation change of University Library under the environment of big data, such as data storage and calculation, data management and service applications et al. It can solve the key technical problems of big data service of University Library in a certain extent.
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