期刊文献+

多维数据模型的变粒度存储策略研究 被引量:2

Research of Various Granularity Storage Method of Multidimensional Data Model
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摘要 提高联机分析处理(OLAP)的响应速度是数据仓库研究的核心问题之一。文中根据多维数据模型的结构特点以及OLAP需求提出了一种变粒度存储策略。实验表明该策略能有效地减少存储空间,提高OLAP响应速度。 To improve OLAP's response time is a key problem in the study area of data warehouse. According to the structural characteristic of multidimensional data model and OLAP's needs, a various granularity storage method has been presented to store historical data. Test shows this method can efficiently decrease the storage space and improve OLAP's response time.
出处 《微机发展》 2003年第10期23-25,36,共4页 Microcomputer Development
关键词 数据仓库 数据立方体 多维数据模型 变粒度存储策略 数据库 联机分析处理 on-line analytical processing multi-dimensional data mode data cube various granularity storage method
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参考文献9

  • 1李建中,hlju.edu.cn,高宏.一种数据仓库的多维数据模型[J].软件学报,2000,11(7):908-917. 被引量:75
  • 2王腾蛟,王海洋,洪晓光,董继润.多物化视图并行增量保持三阶段模式[J].软件学报,1999,10(11):1138-1141. 被引量:2
  • 3Hafinarayan V, Rajaraman A, Ullman J D. Implementing Data Cubes Efficiently[J]. SIGMOD, 1996, 25(2) : 205 -216. 被引量:1
  • 4Baralis E, Paralmschi S, Teniente E. Materialized view selection in a multidimensional database[A]. In: Proceedings of the 23rd VLDB Conference[C]. Athens, Greece: [s. n. ],1997. 156- 165. 被引量:1
  • 5Zaharioudakis M, Cochrane R, Lapis G, et al. Answering Complex SOL Queries Using Automatic Sunmmary, Tables[ J ].SIGMOD, 2000, 29(2). 105 - 116. 被引量:1
  • 6Mumiek I, Quass D, Mumick B. Maintenance of Data Cubes and Summary Tables in a Warehouse[J]. SIGMOD, 1997,26(2): 100- 111. 被引量:1
  • 7Chen Y, Dong G, Hart J, et al. Online Analytical Processing Stream Data: Is It Feasible? [A]. In: Proc 2002 ACM-SIGMOD Int Workshop on Research Issues on Data Mining and Knowledge Discovery (DMKD'02)[C]. Madison, Wisconsin, USA: [s. n. ], 2002. 被引量:1
  • 8Tansel A, Clifford J. Temporal Database Theory, Design and Implementation[M]. Redwccxt, CA: Benjamin/Camanings Publishing Company, 1993. 418-455. 被引量:1
  • 9Codd E F, Codd S B, Salley C T. Beyond decision support[J].Computer World, 1993, 27(30): 87- 89. 被引量:1

二级参考文献1

  • 1Li C,Proceedings of the 5th International Conference on Information and Knowledge Man,1996年,81页 被引量:1

共引文献75

同被引文献15

  • 1肖娟,叶枫.基于概念层次树的数据挖掘算法及应用研究[J].计算机应用研究,2005,22(3):61-63. 被引量:4
  • 2Harinarayan V,Rajaraman A,UIIMan J D.Implementing Data Cubes Efficiently[A].Proc of ACM SIGMOD'96[C].1996.205-216. 被引量:1
  • 3Chun S J,Chung C W,Lee J H,et al.Dynamic Update Cube for Range-Sum Queries[A].Proc of the 27th VLDB Conf[C].2001.521-530. 被引量:1
  • 4Liang W,Wang H,Orlowska M E.Range Queries in Dynamic OLAP Data Cubes[J].Data and Knowledge Engineering,2000,34(1):21-38. 被引量:1
  • 5Li H G,Ling T W,Lee S Y.Range Sum Queries in Dynamic OLAP Data Cubes[A].Proc of the 3th Int'l Symp on Cooperative Database Systems for Advanced Applications[C].2001.74-81. 被引量:1
  • 6Ho C T,Agrawal R,Megiddo R,et al.Range Queries in OLAP Cubes[A].Proc of ACM SIGMOD '97[C].1997.73-88. 被引量:1
  • 7Geffner S,Agrawal D,Abbadi A,et al.Relative Prefix Sums:An Efficient Approach for Querying Dynamic OLAP Data Cubes[A].Proc of the 15th Int'l Conf on Data Engineering[C].1999.328-325. 被引量:1
  • 8Beyer K,RamaKrishnan R.Bottom-Up Computation of Sparse and Ice-Berg Cubes[A].Proc of ACM SIGMOD'99[C].1999.359-370. 被引量:1
  • 9O'Neil P,Quass D.Improved Query Performance with Variant Indexes[A].Proc of ACM SIGMOD Int'l Conf on Management of Data[C].1997.38-49. 被引量:1
  • 10Kemper A,Wiesner C.HyperQueries:Dynamic Distributed Query Processing on the Internet[R].Technical Report,Universitat Passau,Fakultat fur Mathematik und Informatik,2001. 被引量:1

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