Abstract
This paper deals with the problem of integrated physical database design involving two optimization techniques: horizontal data partitioning (HDP) and bitmap join indexes (BJI). These techniques compete for the same resource representing selection attributes. This competition incurs attribute interchangeability phenomena, where same attribute(s) may be used to select either HDP or BJI schemes. Existing studies dealing with integrated physical database design problem not consider this competition. We propose to study its contribution on simplifying the complexity of our problem. Instead of tackling it in an integrated way, we propose to start by assigning to each technique its own attributes and then it launches its own selection algorithm. This assignment is done using the K-Means method. Our design is compared with the state of the art work using APB1 benchmark. The results show that an interchangeability attribute-aware database designer can improve significantly query performance within the less space budget.
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
Aouiche, K., Boussaid, O., Bentayeb, F.: Automatic Selection of Bitmap Join Indexes in Data Warehouses. In: Tjoa, A.M., Trujillo, J. (eds.) DaWaK 2005. LNCS, vol. 3589, pp. 64–73. Springer, Heidelberg (2005)
Baralis, E., Paraboschi, S., Teniente, E.: Materialized view selection in a multidimensional database. In: VLDB, pp. 156–165 (August 1997)
Bellatreche, L., Boukhalfa, K., Abdalla, H.I.: Saga: A combination of genetic and simulated annealing algorithms for physical data warehouse design. In: Bell, D.A., Hong, J. (eds.) BNCOD 2006. LNCS, vol. 4042, pp. 212–219. Springer, Heidelberg (2006)
Bellatreche, L., Boukhalfa, K., Richard, P.: Referential horizontal partitioning selection problem in data warehouses: Hardness study and selection algorithms. International Journal of Data Warehousing and Mining 5(4), 1–23 (2009)
Bellatreche, L., Missaoui, R., Necir, H., Drias, H.: A data mining approach for selecting bitmap join indices. Journal of Computing Science and Engineering 2(1), 206–223 (2008)
Boukhalfa, K., Bellatreche, L., Alimazighi, Z.: Hp&bji: A combined selection of data partitioning and join indexes for improving olap performance. Annals of Information Systems 3, 179–2001 (2008)
Chaudhuri, S.: Index selection for databases: A hardness study and a principled heuristic solution. IEEE TKDE 16(11), 1313–1323 (2004)
Chaudhuri, S., Narasayya, V.: An efficient cost-driven index selection tool for microsoft sql server. In: VLDB, pp. 146–155 (August 1997)
Eadon, G., Chong, E.I., Shankar, S., Raghavan, A., Srinivasan, J., Das, S.: Supporting table partitioning by reference in oracle. In: SIGMOD, pp. 1111–1122 (2008)
Gebaly, K.E.L., Aboulnaga, A.: Robustness in automatic physical database design. In: 11th International Conference on Extending Database Technology (EDBT 2008), pp. 145–156 (2008)
Gray, J., Slutz, D.: Data mining the sdss skyserver database. Techreport Technical Report MSR-TR-2002-01, Microsoft Research (2002)
Ioannidis, Y., Kang, Y.: Randomized algorithms algorithms for optimizing large join queries. In: SIGMOD, pp. 9–22 (1990)
Karloff, H., Mihail, M.: On the complexity of the view-selection problem. pp. 167–173 (1999)
Kimura, H., Huo, G., Rasin, A., Madden, S., Zdonik, S.: Coradd: Correlation aware database designer for materialized views and indexes. PVLDB 3(1), 1103–1113 (2010)
MacQueen, J.B.: Some methods for classification and analysis of multivariate observations. In: Symposium on Mathematical Statistics and Probability, pp. 281–297 (1967)
Mahboubi, H., Darmont, J.: Data mining-based fragmentation of xml data warehouses. In: ACM DOLAP, pp. 9–16 (2008)
Papadomanolakis, S., Ailamaki, A.: Autopart: Automating schema design for large scientific databases using data partitioning. In: International Conference on Scientific and Statistical Database Management, pp. 383–392 (June 2004)
Sanjay, A., Narasayya, V.R., Yang, B.: Integrating vertical and horizontal partitioning into automated physical database design. In: SIGMOD, pp. 359–370 (June 2004)
Sanjay, A., Surajit, C., Narasayya, V.R.: Automated selection of materialized views and indexes in microsoft sql server. In: VLDB, pp. 496–505 (2000)
Stöhr, T., Märtens, H., Rahm, E.: Multi-dimensional database allocation for parallel data warehouses. In: VLDB, pp. 273–284 (2000)
Zilio, D.C., Rao, J., Lightstone, S., Lohman, G.M., Storm, A., Garcia-Arellano, C., Fadden, S.: Db2 design advisor: Integrated automatic physical database design. In: VLDB, pp. 1087–1097 (August 2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bouchakri, R., Bellatreche, L. (2011). On Simplifying Integrated Physical Database Design. In: Eder, J., Bielikova, M., Tjoa, A.M. (eds) Advances in Databases and Information Systems. ADBIS 2011. Lecture Notes in Computer Science, vol 6909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23737-9_24
Download citation
DOI: https://doi.org/10.1007/978-3-642-23737-9_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23736-2
Online ISBN: 978-3-642-23737-9
eBook Packages: Computer ScienceComputer Science (R0)