Abstract
Trace files generated during operation of a database provide enormous amounts of information. This information varies from one DBMS to another—some databases produce more information than the others. There are many research projects which aim at analysing workloads of databases (not necessarily the trace files). Many of them work online in parallel with the usual business of a DBMS. Such approaches exclude a holistic tackling of trace files. To date, the research on offline methods had only a partial scope. In this paper we show a comprehensive method to analyse trace files off-line. The aim of this analysis is to indicate tables and queries which are not handled well in current design of the database and the application. Next, we show case-studies performed on two dissimilar database applications which show the potential of the described method.
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
Sattler, K.U., Geist, I., Schallehn, E.: Quiet: Continuous query-driven index tuning. In: VLDB, pp. 1129–1132 (2003)
Schnaitter, K., Abiteboul, S., Milo, T., Polyzotis, N.: Colt: continuous on-line tuning. In: Chaudhuri, S., Hristidis, V., Polyzotis, N. (eds.) SIGMOD Conference, pp. 793–795. ACM, New York (2006)
Bruno, N., Chaudhuri, S.: An online approach to physical design tuning. In: [6], pp. 826–835
Chaudhuri, S., Narasayya, V.R.: Autoadmin ’what-if’ index analysis utility. In: Haas, L.M., Tiwary, A. (eds.) SIGMOD Conference, pp. 367–378. ACM Press, New York (1998)
Agrawal, S., Chaudhuri, S., Narasayya, V.R.: Automated selection of materialized views and indexes in sql databases. In: Abbadi, A.E., Brodie, M.L., Chakravarthy, S., Dayal, U., Kamel, N., Schlageter, G., Whang, K.Y. (eds.) VLDB, pp. 496–505. Morgan Kaufmann, San Francisco (2000)
Proceedings of the 23rd International Conference on Data Engineering, ICDE 2007, The Marmara Hotel, Istanbul, Turkey, April 15-20, 2007. IEEE (2007)
Bruno, N., Chaudhuri, S.: Physical design refinement: The “Merge-reduce” approach. In: Ioannidis, Y., Scholl, M.H., Schmidt, J.W., Matthes, F., Hatzopoulos, M., Böhm, K., Kemper, A., Grust, T., Böhm, C. (eds.) EDBT 2006. LNCS, vol. 3896, pp. 386–404. Springer, Heidelberg (2006)
Zilio, D.C., Zuzarte, C., Lightstone, S., Ma, W., Lohman, G.M., Cochrane, R., Pirahesh, H., Colby, L.S., Gryz, J., Alton, E., Liang, D., Valentin, G.: Recommending materialized views and indexes with ibm db2 design advisor. In: ICAC, pp. 180–188. IEEE Computer Society, Los Alamitos (2004)
Dageville, B., Das, D., Dias, K., Yagoub, K., Zaït, M., Ziauddin, M.: Automatic sql tuning in oracle 10g. In: [14], pp. 1098–1109 (2004)
Agrawal, S., Chaudhuri, S., Kollár, L., Marathe, A.P., Narasayya, V.R., Syamala, M.: Database tuning advisor for microsoft sql server 2005. In: [14], pp. 1110–1121 (2004)
Valentin, G., Zuliani, M., Zilio, D.C., Lohman, G.M., Skelley, A.: Db2 advisor: An optimizer smart enough to recommend its own indexes. In: ICDE, pp. 101–110 (2000)
Shasha, D., Bonnet, P.: Database tuning: principles, experiments, and troubleshooting techniques. Morgan Kaufmann Publishers Inc, San Francisco (2003)
Lightstone, S.S., Teorey, T.J., Nadeau, T.: Physical Database Design: the database professional’s guide to exploiting indexes, views, storage, and more. The Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann Publishers Inc, San Francisco (2007)
Nascimento, M.A., Özsu, M.T., Kossmann, D., Miller, R.J., Blakeley, J.A., Schiefer, K.B. (eds.) (e)Proceedings of the Thirtieth International Conference on Very Large Data Bases, Toronto, Canada, August 31 - September 3 2004. Morgan Kaufmann, San Francisco (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Lenkiewicz, P., Stencel, K. (2010). Percentages of Rows Read by Queries as an Operational Database Quality Indicator. In: Nguyen, N.T., Katarzyniak, R., Chen, SM. (eds) Advances in Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 283. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12090-9_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-12090-9_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12089-3
Online ISBN: 978-3-642-12090-9
eBook Packages: EngineeringEngineering (R0)