Abstract
Constraint Processing and Database techniques overlap significantly. We discuss here the application of a constraint satisfaction technique, called dynamic bundling, to databases. We model the join query computation as a Constraint Satisfaction Problem (CSP) and solve it by search using dynamic bundling. First, we introduce a sort-based technique for computing dynamic bundling. Then, we describe the join algorithm that produces nested tuples. The resulting process yields a compact solution space and savings of memory, disk-space, and/or network bandwidth. We realize further savings by using bundling to reduce the number of join-condition checks. We place our bundling technique in the framework of the Progressive Merge Join (PMJ) [1] and use the XXL library [2] for implementing and testing our algorithm. PMJ assists in effective query-result-size prediction by producing early results. Our algorithm reinforces this feature of PMJ by producing the tuples as multiple solutions and is thus useful for improving size estimation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Dittrich, J.P., Seeger, B., Taylor, D.S., Widmayer, P.: On Producing Join Results Early. In: 22nd ACM Symposium on Principles of Database Systems, pp. 134–142 (2003)
den Bercken, J.V., Blohsfeld, B., Dittrich, J.P., Krämer, J., Schäfer, T., Schneider, M., Seeger, B.: XXL–A Library Approach to Supporting Efficient Implementations of Advanced Database Queries. In: 27th International Conference on Very Large Data Bases, pp. 39–48 (2001)
Rossi, F., Petrie, C., Dhar, V.: On the Equivalence of Constraint Satisfaction Problems. In: Proc. of the 9th ECAI, Stockholm, Sweden, pp. 550–556 (1990)
Bacchus, F., van Beek, P.: On the Conversion between Non-Binary and Binary Constraint Satisfaction Problems Using the Hidden Variable Method. In: Proc. of AAAI 1998, Madison, Wisconsin, pp. 311–318 (1998)
Bessière, C., Meseguer, P., Freuder, E.C., Larrosa, J.: On Forward Checking for Non-binary Constraint Satisfaction. Artificial Intelligence 141(1-2), 205–224 (2002)
Beckwith, A.M., Choueiry, B.Y., Zou, H.: How the Level of Interchangeability Embedded in a Finite Constraint Satisfaction Problem Affects the Performance of Search. In: Stumptner, M., Corbett, D.R., Brooks, M. (eds.) Canadian AI 2001. LNCS (LNAI), vol. 2256, pp. 50–61. Springer, Heidelberg (2001)
Choueiry, B.Y., Davis, A.M.: Dynamic Bundling: Less Effort for More Solutions. In: Koenig, S., Holte, R. (eds.) SARA 2002. LNCS (LNAI), vol. 2371, pp. 64–82. Springer, Heidelberg (2002)
Lal, A., Choueiry, B.Y.: Dynamic Detection and Exploitation of Value Symmetries for Non-Binary Finite CSPs. In: Third International Workshop on Symmetry in Constraint Satisfaction Problems (SymCon 2003), Kinsale, County Cork, Ireland, pp. 112–126 (2003)
Freuder, E.C.: Eliminating Interchangeable Values in Constraint Satisfaction Problems. In: Proc. of AAAI, Anaheim, CA, pp. 227–233 (1991)
Haselböck, A.: Exploiting Interchangeabilities in Constraint Satisfaction Problems. In: Proc. of the 13th IJCAI, Chambéry, France, pp. 282–287 (1993)
Roth, M.A., Horn, S.J.V.: Database compression. SIGMOD Record 22, 31–39 (1993)
Westmann, T., Kossmann, D., Helmer, S., Moerkotte, G.: The implementation and performance of compressed databases. SIGMOD Record 29, 55–67 (2000)
Chen, Z., Gehrke, J., Korn, F.: Query optimization in compressed database systems. In: ACM International Conference on Management of Data (SIGMOD), pp. 271–282 (2001)
Mamoulis, N., Papadias, D.: Constraint-based Algorithms for Computing Clique Intersection Joins. In: Sixth ACM International Symposium on Advances in Geographic Information Systems, pp. 118–123 (1998)
Bernstein, P.A., Chiu, D.M.W.: Using semi-joins to solve relational queries. J. ACM 28, 25–40 (1981)
Wallace, M., Bressan, S., Provost, T.L.: Magic checking: Constraint checking for database query optimization. In: Kuper, G.M., Wallace, M. (eds.) CONTESSA-WS 1995 and CDB 1995. LNCS, vol. 1034, pp. 148–166. Springer, Heidelberg (1995)
Bayardo, R.J.: Processing Multi-Join Queries. PhD thesis, University of Texas, Austin (1996)
Miranker, D.P., Bayardo, R.J., Samoladas, V.: Query evaluation as constraint search; an overview of early results. In: Gaede, V., Vianu, V., Brodsky, A., Srivastava, D., Günther, O., Wallace, M. (eds.) CP-WS 1996 and CDB 1997. LNCS, vol. 1191, pp. 53–63. Springer, Heidelberg (1997)
Rich, C., Rosenthal, A., Scholl, M.H.: Reducing duplicate work in relational join(s): A unified approach. In: International Conference on Information Systems and Management of Data, pp. 87–102 (1993)
Revesz, P.: Introduction to Constraint Databases. Springer, New York (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lal, A., Choueiry, B.Y. (2004). Constraint Processing Techniques for Improving Join Computation: A Proof of Concept. In: Kuijpers, B., Revesz, P. (eds) Constraint Databases. CDB 2004. Lecture Notes in Computer Science, vol 3074. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25954-1_9
Download citation
DOI: https://doi.org/10.1007/978-3-540-25954-1_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22126-5
Online ISBN: 978-3-540-25954-1
eBook Packages: Springer Book Archive