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Multidimensional Performance Management

Authors: David Wiese

Abstract:

In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.

Keywords: Data warehousing, Performance Management, OLAP, Performance Tuning, Multidimensional Navigation, Performance Diagnosis

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1078729

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References:


[1] S. Chaudhuri, G. Weikum. Rethinking Database System Architecture: Towards a Self-tuning RISC style Database System. In Proceedings of VLDB, 2000.
[2] IBM Corp. DB2 UDB ESE V8 non-DPF Performance Guide for High Performance OLTP and BI. IBM Redbooks, 2004.
[3] Alur, N; Balaji, R.; Miskimen, M.; Stolz-Hofmann, D.: IBM DB2 UDB Performance Expert for Multiplatforms - A usage guide. Redbook. IBM Corp, 2003.
[4] Alur, N.; Falos, A.; Lau, A.; Lindquist, S.; Varghese, M.: DB2 UDB/WebSphere Performance Tuning Guide. Redbook. IBM Corp,2003.
[5] Chen, W-J; Ma A.; Markovic, A.; Midha, R.; Miskimen, M.; Siders, K.; Taylor, K; Weinerth, M.: DB2 Performance Expert for Multiplatforms V2. Redbook. IBM Corp, 2005.
[6] IBM Corp.: DB2 Universal Database - System Monitor Guide and Reference (Version 8). IBM Corp, 2004.
[7] Sriram, C.; Martin, P.; Powley, W.: A Data Warehouse for Performance Management of Distributed Systems. Dept. of Computing and Information Science. Queen's University at Kingston, 1998.
[8] Bauer, A.; G├╝nzel, H.: Data Warehouse Systeme Architektur, Entwicklung, Anwendung. dpunkt. Heidelberg. 2000.
[9] Codd, E.F. et al.: Providing OLAP to User-Analysts: An IT mandate. Arbor Software, 1993.
[10] Inmon, W.H.: Building the Data Warehouse. 3rd edition. Wiley. New York, 2002.
[11] Kimball, R.: The Datawarehouse Toolkit. John Wiley & Sons, New York 1996.
[12] Wiese, D.: Framework for Data Mart Design and Implementation in DB2 Performance Expert. Diploma thesis. University of Jena and IBM Böblingen. 2005.
[13] Mogin, P.: OLAP Queries and SQL1999. Issues in Database and Information Systems. Victoria University of Wellington, 2005.
[14] Hart, D.G.; Hellerstein, J.L.; Yue, P.C.: Automated drill down: An approach to automated problem isolation for performance management. In: Proceedings of the Computer Measurement Group, 1999.
[15] Harinarayan, V.; Rajaraman, A.; Ullman, J. D.: Implementing data cubes efficiently. Proceedings of the 1996 ACM SIGMOD international conference on Management of Data (SIGMOD'96). ACM Press, June 1996.
[16] Sapia, C.: On Modeling and Predicting Query Behavior in OLAP Systems. Proceedings of the International Workshop on Design and Management of Data Warehouses. Heidelberg, Germany, 14. - 15. 6. 1999.
[17] Wiese, D.; Rabinovitch, G.; Reichert, M. and Arenswald, S.: Autonomic Tuning Expert - A framework for best-practice oriented autonomic database tuning. In Proceedings of Centre for Advanced Studies on Collaborative Research (CASCON 2008). Ontario, Canada, October 27 - 30, 2008.