| Supporting capacity planning for DB2 UDB |
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IBM Centre for Advanced Studies Conference
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Proceedings of the 2002 conference of the Centre for Advanced Studies on Collaborative research
table of contents
Toronto, Ontario, Canada
Page: 15
Year of Publication: 2002
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Authors
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Hamzeh Zawawy
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School of Computing, Queen's University, Kingston, Ontario, Canada K7L 3N6 and IBM® Toronto Laboratory, Toronto, Ontario, Canada M3C 1H7
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Patrick Martin
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School of Computing, Queen's University, Kingston, Ontario, Canada K7L 3N6
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Hossam Hassanein
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School of Computing, Queen's University, Kingston, Ontario, Canada K7L 3N6
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IBM Press
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| Bibliometrics |
Downloads (6 Weeks): 5, Downloads (12 Months): 24, Citation Count: 3
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ABSTRACT
Capacity planning is the process of determining the most cost-effective computing environment that meets the current and future demands of a computing system. Capacity planning is important for large database management systems (DBMSs) whose performance can be greatly affected by the amount of available resources and whose workloads can change significantly over time. In this paper, we examine support for capacity planning for DBMSs. We describe an analytical model that is used to estimate performance under different scenarios and discuss how to obtain the input parameters to the model for an OLTP workload running on IBM® DB2® Universal DatabaseTM. We then give an example of how the model can be used to solve a typical capacity planning problem.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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{4} Raj Jain, The Art of Computer Systems Performance Analysis, John Wiley & Sons Inc.1991.
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{6} L. Belady, A Study of Replacement Algorithms for a Virtual-Storage Computer, IBM Systems Journal 5 (2), July 1966.
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{7} TPC Benchmarks, Transaction Processing Performance Council, http://www.tpc.org/information/benchma rks.asp, February 2002.
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{8} M.E. Senko, V.Y. Lum, and P.J. Owens, A File Organization evaluation model, Proceedings IFIP Conference 1968, pp. 514-19.
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{10} Ken Sevcik, Data Base System Performance Prediction Using An Analytical Model, IEEE Computer, February 1981.
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{11} D. Ferrari, Computer Systems Performance Evaluation, Prentice Hall, 1978.
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{12} H. Zawawy, Capacity Planning for Database Management Systems using Analytical Modeling, M.Sc. thesis, Dept of Computing and Information Science, Queen's University, 2002.
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CITED BY 3
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Ted J. Wasserman , Patrick Martin , Haider Rizvi, Sizing DB2 UDB® servers for business intelligence workloads, Proceedings of the 2004 conference of the Centre for Advanced Studies on Collaborative research, p.135-149, October 04-07, 2004, Markham, Ontario, Canada
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Ted J. Wasserman , Patrick Martin , David B. Skillicorn , Haider Rizvi, Developing a characterization of business intelligence workloads for sizing new database systems, Proceedings of the 7th ACM international workshop on Data warehousing and OLAP, November 12-13, 2004, Washington, DC, USA
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