Abstract
Workload adaptation is a performance management process in which an autonomic database management system (DBMS) efficiently makes use of its resources by filtering or controlling the workload presented to it in order to meet its Service Level Objectives (SLOs). The overhead incurred by filtering or controlling the workload is an important factor affecting the effectiveness of workload adaptation. This paper investigates the overhead of AWMF, a framework for workload adaptation and proposes a scalable approach for adapting mixed workload under the framework. The proposed approach allows Query Scheduler, the prototype implementation of AWMF, manage both OLAP and OLTP classes of queries to meet their performance goals by allocating DBMS resources through admission control in the presence of workload fluctuation. Experiments with IBM® DB2® Universal DatabaseTM are conducted to show the proposed approach is scalable and effective.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
D.H. Brown Associate Inc.: HP Raises the Bar for UNIX Workload Management, http://whitepapers.silicon.com/0,39024759,60104905p-39000654q,00.htm
IBM Corporation: MVS Planning: Workload Management, 7th edn. (2003)
IBM Corporation: DB2 Query Patroller Guide: Installation, Administration, and Usage (2003)
Lo, T., Douglas, M.: The Evolution of Workload Management in Data Processing Industry: A Survey. In: Proceedings of 1986 Fall Joint Computer Conference, Dallas, TX, USA, pp. 768–777 (1986)
Menascé, D.A., Almeida, V.A.F.: Capacity Planning for Web Performance: Metrics, Models, and Methods. Prentice Hall, Upper Saddle River (1998)
Niu, B., Martin, P., Powley, W.: Towards Autonomic Workload Management in DBMSs. Journal of Database Management 20(3), 1–17 (2009)
Pacifici, G., Spreitzer, M., Tantawi, A., Youssef, A.: Performance Management for Cluster Based Web Services. IEEE Journal on Selected Areas in Communications 23(12), 2333–2343 (2005)
Schroeder, B., Harchol-Balter, M., Iyengar, A., Nahum, E.: Achieving Class-based QoS for Transactional Workloads. In: Proceedings of the 22nd International Conference on Data Engineering, p. 153 (2006)
Transaction Processing Performance Council, http://www.tpc.org
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Niu, B., Shi, J. (2009). Scalable Workload Adaptation for Mixed Workload. In: Mueller, P., Cao, JN., Wang, CL. (eds) Scalable Information Systems. INFOSCALE 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 18. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10485-5_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-10485-5_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10484-8
Online ISBN: 978-3-642-10485-5
eBook Packages: Computer ScienceComputer Science (R0)