一种新型的多OROLAP模型及其优化算法

journal6 ›› 2004, Vol. 25 ›› Issue (3): 29-35.

一种新型的多OROLAP模型及其优化算法

(1.香港理工大学电子计算学系,香港九龙红磡;2.中南大学信息科学与工程学院,湖南长沙 410083)

出版日期:2004-09-15 发布日期:2012-09-22

A Novel Multi-OROLAP Model and its Optimization Algorithms

Online:2004-09-15 Published:2012-09-22
About author:WANG Guo-jun (1970-),male,was born in Changsha,Hunan,Currently he is a Research Fellow in the Department of Computing,Hong Kong Polytechnic University,Hung Hom,Kowloon,Hong Kong,as well as an associate professor in the Department of Computer Science,Central South University,Changsha,Hunan,P.R.China.His research interests include computer networking,fault-tolerant computing,mobile computing,data warehousing,OLAP technologies,and software engineering.
Supported by:
this research is supported in part by Hong Kong Polytechnic University Central Research Grant G-YY41 and in part by the China Postdoctoral Science Foundation (2003033472)

摘要/Abstract

摘要：OLAP模型是实现高效的联机分析处理、数据挖掘和高级商务智能应用的基础，ROLAP模型、MOLAP模型和OOLAP模型是当前数据仓库和商务智能领域的研究热点.提出了一种新型的基于组播服务的多对象-关系型OLAP模型，简称多OROLAP模型.具有扩展性好、计算速度快、可分布性等特点.研究了多OROLAP模型、数据仓库增量式快速刷新算法、内外存对象存储优化算法、内外存对象透明交换算法、内外存对象自适应选择算法.同时还研究了典型的用户查询和分析模式对多OROLAP模型及其算法、分布式数据仓库中组成员的管理和维护的影响.

关键词： 多数据仓库, 多OROLAP模型, 组播服务, 分布式计算, 优化算法

Abstract: OLAP model is the foundation for implementing efficient on-line analysis processing,data mining and advanced business intelligence applications.ROLAP,MOLAP and OOLAP models are well known models in the current data warehousing and business intelligence research areas.In this paper,the authors propose a novel multi-data warehouse model called Multi-OROLAP model based on multicast services,which has the advantages such as scalability,efficient computation,and distributability.The authors focus on the Multi-OROLAP model and algorithms used within this model,including the incremental refreshing algorithms for data warehouses,storage optimization algorithms,transparent exchange algorithms,and adaptive selection algorithms for main and secondary memory objects.Typical user query and analysis patterns and their performance impact on the Multi-OROLAP model and algorithms,group membership management and maintenance of multi-data warehouses are also discussed.

Key words: multi-data warehouse, multi-OROLAP model, multicast services, distributed computing, optimization algorithms

王国军, 曹建农, 陈振冲. 一种新型的多OROLAP模型及其优化算法[J]. journal6, 2004, 25(3): 29-35.

WANG Guo-Jun, CAO Jian-Nong, CHEN Zhen-Chong. A Novel Multi-OROLAP Model and its Optimization Algorithms[J]. journal6, 2004, 25(3): 29-35.

参考文献

[1] INMON W H.Building the Data Warehouse (Second Edition) [M].New York:John Wiley & Sons,1996.

[2] STANOI I,AGRAWAL D,ABBADI A E.Weak Consistency in Multi-Data Warehouses [R].Proceedings of the Fifth International Conference on Foundations of Data Organizations (FODO98),Kobe,Japan,1998.

[3] NOAMAN A Y,BARKER K.A Horizontal Fragmentation Algorithm for the Fact Relation in a Multi-Data Warehouse [R].Proceedings of the Eighth International Conference on Information and Knowledge Management,1999,pp.154-161,Kansas City,Missouri,USA.

[4] AMMOURA A,ZAIANE O R,GOEBEL R.Towards a Novel OLAP Interface for Multi-Data Warehouses [R].Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery,DaWaK 2001,Munich,Germany,2001,pp.174-185.

[5] WOLFSON O,MILO A.The Multicast Policy and its Relationship to Replicated Data Placement [J].ACM Transactions on Database Systems,March 1991,16(1):181-205.

[6] KEMME B,ALONSO G.A New Approach to Developing and Implementing Eager Database Replication Protocols [J].ACM Transactions on Database Systems,September 2000,25(3):333-379.

[7] KOTIDIS Y,ROUSSOPOULOS N.An Alternative Storage Organization for ROLAP Aggregate Views Based on Cube Trees [R].Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data,1998,pp.249 - 258,Seattle,Washington,USA.

[8] CABIBBO L,TORLONE R.A Logical Approach to Multidimensional Databases [R].Proceedings of the 6th International Conference on Extending Database Technology (EDBT),pp.183-197.Springer Verlag,1998.

[9] DATTA A,RAMAMRITHAM K, THOMAS H.Curio:A Novel Solution for Efficient Storage and Indexing in Data Warehouses [R].Proceedings of the International Conference on Very Large Databases,pp.730-733,1999.

[10] TSUJI T,ISSHIKI A,HOCHIN T,et al.An Implementation Scheme of Multidimensional Arrays for MOLAP [R].Proceedings of the 13th International Workshop on Database and Expert Systems Applications (DEXA02),2002,pp.657-662.

[11] ABELLO A,SAMOS J,SALTOR F.Benefits of an Object-Oriented Multidimensional Data Model [J].Objects and Databases,2000.141-152.

[12] KAMEL N,KING R.Intelligent Database Caching Through the Use of Page-Answers and Page-Traces [J].ACM Transactions on Database Systems,December 1992,17(4):601-646.

[13] RODRIGUEZ P,SPANNER C,BIERSACK E W.Analysis of Web Caching Architectures:Hierarchical and Distributed Caching [J].IEEE/ACM Transactions on Networking,2001,9(4):404-418.

[14] LUO Q,KRISHNAMURTHY S,MOHAN C,et al.Middle-Tier Database Caching for E-Business [R].Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data,June 2002,pp.600-611,Madison,Wisconsin.

[15] BOHANNON P,MCLLROY P,RASTOGI R.Main-Memory Index Structures with Fixed-Size Partial Keys [R].Proceedings of the 2001 ACM SIGMOD International Conference on Management of Data,May 2001,pp.163 - 174,Santa Barbara,California USA.

[16] LEE I,YEOM H Y.A Single Phase Distributed Commit Protocol for Main Memory Database [R].Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS02),April 2002,pp.14-21,Ft.Lauderdale,FL,USA.

[17] KOSSMANN D,FRANKLIN M J,DRASCH G.Cache Investment:Integrating Query Optimization and Distributed Data Placement [J].ACM Transactions on Database Systems,2000,25(4):517-558.

[18] SUCIU D.Distributed Query Evaluation on Semistructured Data [J].ACM Transactions on Database Systems,2002,27(1):1-62.

[19] DATTA A,VANDERMEER D,RAMAMRITHAM K.Parallel Star Join + DataIndexes:Efficient Query Processing in Data Warehouses and OLAP [J].IEEE Transactions on Knowledge and Data Engineering,2002,14(6):1 299-1 316.

[20] LELAND W E,TAQQU M S,WILLINGER W,et al.On the Self-Similar Nature of Ethernet Traffic (Extended Version) [J].IEEE/ACM Transactions on Networking,1994,2(1):1-15.

[21] PAXSON V,FLOYD S.Wide Area Traffic:the Failure of Poisson Modeling [J].IEEE/ACM Transactions on Networking,1995,3(3):226-244.

[22] ERRAMILLI A,NARAYAN O,WILLINGER W.Experimental Queuing Analysis With Long-Range Dependent Packet Traffic [J].IEEE/ACM Transactions on Networking,1996,4(2):209-223.
[23] WILLINGER W,TAQQU M S,SHERMAN R,et al.Self-Similarity Through High-Variability:Statistical Analysis of Ethernet LAN Traffic at the Source Level [J].IEEE/ACM Transactions on Networking,1997,5(1):71-86.

[24] GROSSGLAUSER M,BOLOT J.On the Relevance of Long-Range Dependence in Network Traffic [J].IEEE/ACM Transactions on Networking,1999,7(5):629-640.

[25] PARK K,WILLINGER W.Self-Similar Traffic and Performance Evaluation [M].New York:Wiley,2000.

[26] MA S,JI C.Modeling Heterogeneous Network Traffic in Wavelet Domain [J].IEEE/ACM Transactions on Networking,2001,9(5):634-649.

[27] TIAN X,WU J,JI C.A Unified Framework for Understanding Network Traffic Using Independent Wavelet Models [R].Proceedings of the Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM02),June 2002,pp.446-454,New York,USA.