Efficient Handling of Relational Database Combinatorial Queries Using CSPs

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.

[1]  Eugene C. Freuder,et al.  The Complexity of Some Polynomial Network Consistency Algorithms for Constraint Satisfaction Problems , 1985, Artif. Intell..

[2]  Robert M. Haralick,et al.  Increasing Tree Search Efficiency for Constraint Satisfaction Problems , 1979, Artif. Intell..

[3]  Arun N. Swami,et al.  Optimization of large join queries: combining heuristics and combinatorial techniques , 1989, SIGMOD '89.

[4]  Moshe Y. Vardi Constraint satisfaction and database theory: a tutorial , 2000, PODS.

[5]  Celso C. Ribeiro,et al.  Query Optimization in Distributed Relational Databases , 1997, J. Heuristics.

[6]  Yehoshua Chaim Sagiv,et al.  Optimization of queries in relational databases , 1981 .

[7]  Alan K. Mackworth Consistency in Networks of Relations , 1977, Artif. Intell..

[8]  Frédéric Benhamou Principles and Practice of Constraint Programming - CP 2006, 12th International Conference, CP 2006, Nantes, France, September 25-29, 2006, Proceedings , 2006, CP.

[9]  Matthias Jarke,et al.  Query Optimization in Database Systems , 1984, CSUR.

[10]  Christian Bessiere,et al.  Using Inference to Reduce Arc Consistency Computation , 1995, IJCAI.

[11]  Peter Z. Revesz,et al.  Introduction to Constraint Databases , 2002, Texts in Computer Science.

[12]  Chuang Liu,et al.  Efficient relational joins with arithmetic constraints on multiple attributes , 2005, 9th International Database Engineering & Application Symposium (IDEAS'05).

[13]  Christian Bessiere,et al.  Refining the Basic Constraint Propagation Algorithm , 2001, JFPLC.

[14]  Rina Dechter,et al.  Constraint Processing , 1995, Lecture Notes in Computer Science.

[15]  Qiang Shen,et al.  Solution Techniques for Constraint Satisfaction Problems: Advanced Approaches , 2001, Artificial Intelligence Review.

[16]  Valeria De Antonellis,et al.  Relational Database Theory , 1993 .

[17]  Thomas C. Henderson,et al.  Arc and Path Consistency Revisited , 1986, Artif. Intell..

[18]  Pascal Van Hentenryck Constraint satisfaction in logic programming , 1989, Logic programming.

[19]  Christophe Lecoutre,et al.  Generalized Arc Consistency for Positive Table Constraints , 2006, CP.

[20]  Alan K. Mackworth On Reading Sketch Maps , 1977, IJCAI.

[21]  David Harel,et al.  Structure and complexity of relational queries , 1980, 21st Annual Symposium on Foundations of Computer Science (sfcs 1980).

[22]  Roland H. C. Yap,et al.  Making AC-3 an Optimal Algorithm , 2001, IJCAI.

[23]  Moshe Y. Vardi The complexity of relational query languages (Extended Abstract) , 1982, STOC '82.

[24]  Christian Bessiere,et al.  Arc-Consistency and Arc-Consistency Again , 1993, Artif. Intell..

[25]  Robert Kooi,et al.  The Optimization of Queries in Relational Databases , 1980 .

[26]  Eugene C. Freuder,et al.  Contradicting Conventional Wisdom in Constraint Satisfaction , 1994, ECAI.

[27]  Qiang Shen,et al.  Solution Techniques for Constraint Satisfaction Problems: Foundations , 2001, Artificial Intelligence Review.