Abstract
Many large-scale online services use structured storage to persist metadata and sometimes data. The structured storage is typically provided by standard database servers such as Microsoft’s SQL Server. It is important to understand the workloads seen by these servers, both for provisioning server hardware as well as to exploit opportunities for energy savings and server consolidation. In this paper we analyze disk I/O traces from production servers in four internet services as well as servers running TPC benchmarks. We show using a range of load metrics that the services differ substantially from each other and from standard TPC benchmarks. Online services also show significant diurnal patterns in load that can be exploited for energy savings or consolidation. We argue that TPC benchmarks do not capture these important characteristics and argue for developing benchmarks that can be parameterized with workload features extracted from live production workload traces.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Hamilton, J.: Internet-scale service efficiency (September 2008), http://mvdirona.com/jrh/TalksAndPapers/JamesRH_Ladis2008.pdf
Narayanan, D., Donnelly, A., Rowstron, A.: Write off-loading: Practical power management for enterprise storage. In: Proc. USENIX Conference on File and Storage Technologies (FAST), San Jose, CA, February 2008, pp. 256–267 (2008)
Narayanan, D., Donnelly, A., Thereska, E., Elnikety, S., Rowstron, A.: Everest: Scaling down peak loads through I/O off-loading. In: Proc. Symposium on Operating Systems Design and Implementation (OSDI), San Diego, CA, December 2008, pp. 15–28 (2008)
Narayanan, D., Thereska, E., Donnelly, A., Elnikety, S., Rowstron, A.: Migrating enterprise storage to SSDs: analysis of tradeoffs. In: Proceedings of EuroSys 2009, Nuremberg, Germany. ACM, New York (2009)
Kavalanekar, S., Worthington, B., Zhang, Q., Sharda, V.: Characterization of storage workload traces from production Windows servers. In: Proc. IEEE International Symposium on Workload Characterization (IISWC), Austin, TX, October 2008, pp. 119–128 (2008)
Zhu, Q., Chen, Z., Tan, L., Zhou, Y., Keeton, K., Wilkes, J.: Hibernator: Helping disk arrays sleep through the winter. In: Proceedings of the ACM Symposium on Operating Systems Principles (SOSP 2005), Brighton, United Kingdom (October 2005)
Narayanan, D., Thereska, E., Ailamaki, A.: Continuous resource monitoring for self-predicting DBMS. In: Proceedings of IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2005), Atlanta, GA. IEEE, Los Alamitos (2005)
Sankar, S., Vaid, K.: Storage characterization for unstructured data in online services applications. In: Proc. IEEE International Symposium on Workload Characterization (IISWC) (to appear)
SNIA: IOTTA repository (January 2009), http://iotta.snia.org/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kavalanekar, S., Narayanan, D., Sankar, S., Thereska, E., Vaid, K., Worthington, B. (2009). Measuring Database Performance in Online Services: A Trace-Based Approach. In: Nambiar, R., Poess, M. (eds) Performance Evaluation and Benchmarking. TPCTC 2009. Lecture Notes in Computer Science, vol 5895. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10424-4_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-10424-4_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10423-7
Online ISBN: 978-3-642-10424-4
eBook Packages: Computer ScienceComputer Science (R0)