知识组织

面向大数据的数字图书馆数据库缓存模型设计

  • 王敬东
展开
  • 1. 中国科学院文献情报中心;
    2. 中国科学院大学;
    3. 东北电力大学信息工程学院
王敬东,中国科学院文献情报中心、中国科学院大学博士研究生,东北电力大学信息工程学院讲师,E-mail:wangjingdong@mail.las.ac.cn.

收稿日期: 2014-09-15

  修回日期: 2014-10-23

  网络出版日期: 2014-11-20

基金资助

本文系国家自然科学基金项目“知识可视化模型及知识发现策略研究”(项目编号:51277023)研究成果之一.

Design of Digital Library Database Cache Model Oriented to Big Data

  • Wang Jingdong
Expand
  • 1. National Science Library, Chinese Academy of Sciences, Beijing 100190;
    2. University of Chinese Academy of Sciences, Beijing 100190;
    3. School of Electronic and Computer Engineering, Northeast Dianli University, Jilin 132012

Received date: 2014-09-15

  Revised date: 2014-10-23

  Online published: 2014-11-20

摘要

设计面向大数据的数字图书馆信息系统数据库缓存模型,从模型的功能架构、运行流程方面进行介绍,规定应用程序接口,在尽可能不改动数字图书馆信息系统原程序的基础上,实现用户操作序列或进程行为序列的捕捉,并使用HammerOra数据库测试工具对本模型进行测试,结果证明缓存模型适合处理数字图书馆海量信息系统产生的数据,具有良好的经济性和有效性.

本文引用格式

王敬东 . 面向大数据的数字图书馆数据库缓存模型设计[J]. 图书情报工作, 2014 , 58(22) : 95 -99,148 . DOI: 10.13266/j.issn.0252-3116.2014.22.015

Abstract

This paper designs a digital library database cache model oriented to big data, introduces model's functional architecture and operation process, and defines the application program interface. Then it realizes to capture user's operating sequence or process behavior sequence based on the exsiting library information system programming. At last, the model is tested by HammerOra that is a database test tool. The result demonstrates the model is suitable for processing data generated by massive information systemof digital library and it is economic and effective.

参考文献

[1] 朱静薇,李红艳.大数据时代下图书馆的挑战及其应对策略[J].现代情报,2013,33(5):9-13.

[2] Francisco P S,Marta P M,Ricardo J P.Elastic SI-Cache:Consistent and scalable caching in multi-tier architectures[J].The VLDB Journal,2011,20(6): 841-865.

[3] Askitis N, Sinha R.Engineering scalable, cache and space efficient tries for strings[J].The VLDB Journal,2011,19(5): 633-660.

[4] 向林燕.基于网格的Web缓存系统的研究与实现[D].长春:吉林大学,2013.

[5] Theo H,Andreas B.Value complete,column complete,predicate complete[J].The VLDB Journal,2013,17(4):805-826.

[6] Qu Zhaoyang.Electric system database cach model based on predictive forest combination algorithm[J].Electrical Measurement & Instrumentation,2013,45(8):70-74.

[7] Nitesh V,Aleksander K.Editorial:Special issue on learning from imbalanced data sets[J].SIGKDD Explorations,2012,6(1):1-6.

[8] 卓海艺.基于HBase的海量数据实时查询系统设计与实现[D].北京:北京邮电大学,2013.

[9] Li Yinan, Chen I R.Adaptive per-user per-object cache consistency management for mobile data access in wireless mesh networks[J].Journal of Parallel and Distributed Computing,2011,71 (7):1034-1046.

[10] Shao Yichuan,Yao Xingjia.Research of real-time data warehouse storage strategy based on multi-ievel caches[J].Physics Procedia,2012,25(3):2315-2321.

[11] Judith H,Andreas K,Christoph Z.Cache efficient data structures and algorithms for adaptive multidimensional multilevel finite element solvers[J].Applied Numerical Mathematics,2012,58 (4):435-448.

[12] 秦秀磊,张文博,魏峻.云计算环境下分布式缓存技术的现状与挑战[J].软件学报,2013,24(1):50-66.

文章导航

/

〈 〉