Abstract
A combinatorial query is a request for tuples from multiple relations that satisfy a conjunction of constraints on tuple attribute values. Managing combinatorial queries using the traditional database systems is very challenging due to the combinatorial nature of the problem. Indeed, for queries involving a large number of constraints, relations and tuples, the response time to satisfy these queries becomes an issue. To overcome this difficulty in practice we propose a new model integrating the Constraint Satisfaction Problem (CSP) framework into the database systems. Indeed, CSPs are very popular for solving combinatorial problems and have demonstrated their ability to tackle, in an efficient manner, real life large scale applications under constraints. In order to compare the performance in response time of our CSP-based model with the traditional way for handling combinatorial queries and implemented by MS SQL Server, we have conducted several experiments on large size databases. The results are very promizing and show the superiority of our method comparing to the traditional one.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Atzeni, P., Antonellis, V.D.: Relational database theory. Benjamin-Cummings Publishing Co (1993)
Liu, C., Foster, I.T.: A framework and algorithms for applying constraint solving within relational databases. In: W(C)LP 2005, pp. 147–158 (2005)
Revesz, P.: Introduction to Constraint Databases. Springer, New York (2002)
Chuang, L., Yang, L., Foster, I.T.: Efficient relational joins with arithmetic constraints on multiple attributes. In: IDEAS, pp. 210–220 (2005)
Vardi, M.Y.: The complexity of relational query languages. In: Annual ACM Symposium on Theory of Computing (1982)
Chandra, A.: Structure and complexity of relational queries. In: The 21st IEEE Symposium, pp. 333–347 (1980)
Dechter, R.: Constraint Processing. Morgan Kaufmann, San Francisco (2003)
Hentenryck, P.V.: Constraint Satisfaction in Logic Programming. MIT Press, Cambridge (1989)
Haralick, R., Elliott, G.: Increasing tree search efficiency for Constraint Satisfaction Problems. Artificial Intelligence 14, 263–313 (1980)
Mackworth, A.K., Freuder, E.: The complexity of some polynomial network-consistency algorithms for constraint satisfaction problems. Artificial Intelligence 25, 65–74 (1985)
Mackworth, A.K.: Consistency in networks of relations. Artificial Intelligence 8, 99–118 (1977)
Vardi, M.Y.: Constraint sastisfaction and database theory: A tutorial. In: PODS 2000 (2000)
Swami, A.: Optimization of large join queries: combining heuristics and combinatorial techniques. In: The 1989 ACM SIGMOD international conference on Management of data, pp. 367–376 (1989)
Jarke, M., Koch, J.: Query optimization in database systems. In: ACM Computing Surveys (CSUR), pp. 111–152 (1984)
Miguel, I., Shen, Q.: Solution techniques for constraint satisfaction problems: Foundations. Artificial Intelligence Review 15(4) (2001)
Mohr, R., Henderson, T.: Arc and path consistency revisited. Artificial Intelligence 28, 225–233 (1986)
Bessière, C.: Arc-consistency and arc-consistency again. Artificial Intelligence 65, 179–190 (1994)
Bessière, C., Freuder, E., Regin, J.: Using inference to reduce arc consistency computation. In: IJCAI 1995, Montréal, Canada, pp. 592–598 (1995)
Zhang, Y., Yap, R.H.C.: Making ac-3 an optimal algorithm. In: Seventeenth International Joint Conference on Artificial Intelligence (IJCAI 2001), Seattle, WA, pp. 316–321 (2001)
Bessière, C., Régin, J.C.: Refining the basic constraint propagation algorithm. In: Seventeenth International Joint Conference on Artificial Intelligence (IJCAI 2001), Seattle, WA, pp. 309–315 (2001)
Lecoutre, C., Radoslaw, S.: Generalized arc consistency for positive table constraints. In: Benhamou, F. (ed.) CP 2006. LNCS, vol. 4204, pp. 284–298. Springer, Heidelberg (2006)
Lecoutre, C., Vion, J.: Bound consistencies for the csp. In: Proceeding of the second international workshop Constraint Propagation And Implementation (CPAI 2005) held with the 10th International Conference on Principles and Practice of Constraint Programming (CP 2005), Sitges, Spain (September 2005)
Mackworth, A.K.: On reading sketch maps. In: IJCAI 1977, pp. 598–606 (1977)
Sabin, D., Freuder, E.C.: Contradicting conventional wisdom in constraint satisfaction. In: Proc. 11th ECAI, Amsterdam, Holland, pp. 125–129 (1994)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mouhoub, M., Feng, C. (2008). Efficient Handling of Relational Database Combinatorial Queries Using CSPs. In: Nguyen, N.T., Borzemski, L., Grzech, A., Ali, M. (eds) New Frontiers in Applied Artificial Intelligence. IEA/AIE 2008. Lecture Notes in Computer Science(), vol 5027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69052-8_39
Download citation
DOI: https://doi.org/10.1007/978-3-540-69052-8_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69045-0
Online ISBN: 978-3-540-69052-8
eBook Packages: Computer ScienceComputer Science (R0)