Skip to main content
SpringerLink
Log in

The C 3 constraint object-oriented database system: An overview

  • Conference paper
  • First Online:
Constraint Databases and Applications (CDB 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1191))

Included in the following conference series:

Abstract

Constraints provide a flexible and uniform way to conceptually represent diverse data capturing spatio-temporal behavior, complex modeling requirements, partial and incomplete information etc, and have been used in a wide variety of application domains. Constraint databases have recently emerged to deeply integrate data captured by constraints in databases. This paper reports on the development of the first constraint object-oriented database system, C 3, and describes its specification, design and implementation. The C 3 system is designed to be used for both implementation and optimization of high-level constraint object-oriented query languages such as \(\mathcal{L}yri\mathcal{C}\)or constraint extensions of OQL, and for directly building software systems requiring extensible use of constraint database features. The C 3 data manipulation language, Constraint Comprehension Calculus, is an integration constraint calculus for extensible constraint domains within monoid comprehensions, which serve as an optimization-level language for object-oriented queries. The data model for constraint calculus is based on constraint spatio-temporal (CST) objects that may hold spatial, temporal or constraint data, conceptually represented by constraints. New CST objects are constructed, manipulated and queried by means of constraint calculus. The model for monoid comprehensions, in turn, is based on the notion of monoids, which is a generalization of collection and aggregation types to structures over which one can iterate and apply merge operator; this includes disjunctions and conjunctions of constraints. The focal point of our work is achieving the right balance between expressiveness, complexity and representation usefulness, without which the practical use of the system would not be possible. To that end, C 3 constraint calculus guarantees polynomial time data complexity, and, furthermore, is tightly integrated with monoid comprehensions to allow deep global optimization.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. T. Atwood, D. Barry, J. Dubl, J. Eastman, G Ferran, D. Jordan, M. Loomis, and D. Wade. The Object Database Standard: ODMG-93. Morgan Kaufmann, 1996.

    Google Scholar 

  2. T. Aschenbrenner, A. Brodsky, and Y. Kornatzky. Constraint database approach to spatio-temporal data fusion and sensor management. In Proc. ILPS95 Workshop on Constraints, Databases and Logic Programming, Portland, OR, December 1995.

    Google Scholar 

  3. F. Afrati, S. Cosmadakis, S. Grumbach, and G. Kuper. Linear versus polynomial constraints in database query languages. In A. Borning, editor, Proc. 2nd International Workshop on Principles and Practice of Constraint Programming, volume 874 of Lecture Notes in Conmputer Science, pages 181–192, Rosario, WA, 1994. Springer Verlag.

    Google Scholar 

  4. A. Brodsky, J. Jaffar, and M.J. Maher. Toward practical constraint databases. In Proc. 19th International Conference on Very Large Data Bases, Dublin, 1993.

    Google Scholar 

  5. A. Brodsky and Y. Kornatzky. The lyric language: Quering constraint objects. In Carey and Schneider, editors, Proc. ACM SIGMOD International Conference on Management of Data, San Jose, California, May 1995.

    Google Scholar 

  6. A. Brodsky, C. Lassez, J.-L. Lassez, and M. J. Maher. Separability of polyhedra for optimal filtering of spatial and constraint data. In Proc. ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems.ACM Press, 1995.

    Google Scholar 

  7. J.-H. Byon and P. Revesz. Disco: A constraint database system with sets. In CONTESSA Workshop on Constraint Databases and Applications, 1995.

    Google Scholar 

  8. A. Brodsky. Constraint databases: Promising technology or just intellectual exercise? In ACM workshop on strategic directions in computer science, to appear. Also, to be part of constraint programming survery in ACM Computing Survery, to appear, 1996.

    Google Scholar 

  9. Alexander Brodsky, Victor E. Segal, and Pavel A. Exarkhopoulo. The c 3 constraint object-oriented database system. Technical report, George Mason University, Department of Information and Software Systems Engineering. 1996.

    Google Scholar 

  10. M. Benjamin, T. Viana, K. Corbett, and A. Silva. Satisfying multiple ratedconstraints in a knowledge based decision aid. In Proc. IEEE Conf. on Artificial Intelligence Applications, Orlando, 1993.

    Google Scholar 

  11. A. Brodsky and X. S. Wang. On approximation-based query evaluation, expensive predicates and constraint objects. In Proc. ILPS95 Workshop on Constraints, Databases and Logic Programming, Portland, OR, 1995.

    Google Scholar 

  12. A. Colmerauer. An introduction to prolog 3. Communications of the ACM, 33(7):69–90, 1990.

    Google Scholar 

  13. M. Dincbas, P. Van Hentenryck, H. Simnis, A. Aggoun, T. Graf, and F. Berthier. The constraint logic programming language chip. In Proc. Fifth Generation Computer Systems, Tokyo, Japan, 1988.

    Google Scholar 

  14. O. Deux et. al. The story of o2. IEEE Transactions on Knowledge and Data Engineering, 1990.

    Google Scholar 

  15. Eclipse User's Guide, 1993.

    Google Scholar 

  16. L. Fegaras and D. Maier. Toward an effective calculus for object query processing. In Proc. ACM SIGMOD Conf. on Management of Data, 1995.

    Google Scholar 

  17. R. Gross-Brunschwiler. Implementation of Constraint Database Systems Using a Compile-Time Rewrite Approach. PhD thesis, ETH, 1996.

    Google Scholar 

  18. D. Q. Goldin and P.C. Kanellakis. Constraint query algebras. Constraints Journal, to appear.

    Google Scholar 

  19. S. Grumbach and J. Su. Dense-order constraint databases. In Proc. ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems, 1995.

    Google Scholar 

  20. R.H. Guting. Gral: An extensible relational database system for geometric applications. In Proc. 19th Symp. on Very Large Databases, 1989.

    Google Scholar 

  21. L.M. Haas and W.F. Cody. Exploiting extensible dbms in integrated geographic information systems. In Proc. Advances in Spatial Databases, 2nd Symposium, volume 525 of Lecture Notes in Computer Science. Springer Verlag, 1991.

    Google Scholar 

  22. T. Huynh, C. Lassez, and J-L. Lassez. Practical issues on the projection of polyhedral sets. Annals of Mathematics and Artificial Intelligence, to appear; also IBM Research Report RC 15872, IBM T.J. Watson RC, 1990.

    Google Scholar 

  23. J. Jaffar and J-L. Lassez. Constraint logic programming. In Proc. Conf. on Principles of Programming Languages, pages 111–119, 1987.

    Google Scholar 

  24. J. Jaffar, M.J. Maher, P.J. Stuckey, and R.H.C. Yap. Output in clp(▽). In Proc. Int. Conf. on Fifth Generation Computer Systems, volume 2, pages 987–995, Tokyo, Japan, 1992.

    Google Scholar 

  25. P. Kanellakis, G. Kuper, and P. Revesz. Constraint query languages. J. Computer and System Sciences, to appear. (A preliminary version appeared in Proc. 9th PODS, pages 299–313, 1990.

    Google Scholar 

  26. M. Kifer, W. Kim, and Y. Sagiv. Querying object-oriented databases. In Proc. ACM SIGMOD Intl. Conf. on Management of Data, pages 393–402, 1992.

    Google Scholar 

  27. P. Kanellakis, S. Ramaswamy, D.E. Vengroff, and J.S. Vitter. Indexing for data models with constraints and classes. In Proc. ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1993.

    Google Scholar 

  28. G. M. Kuper. Aggregation in constraint databases. In Proc. Workshop on Principles and Practice of Constraint Programming, 1993.

    Google Scholar 

  29. J-L. Lassez, T. Huynh, and K. McAloon. Simplification and elimination of redundant linear arithmetic constraints. In Proc. North American Conference on Logic Programming, pages 35–51, Cleveland, 1989.

    Google Scholar 

  30. C. Lassez and J-L. Lassez. Quantifier elimination for conjunctions of linear constraints via a convex hull algorithm. Technical Report RC16779, IBM T.J. Watson Research Center, 1991.

    Google Scholar 

  31. E.M. McCreight. Priority search trees. SIAM Journal of Computing, 14(2):257–276, May 1985.

    Google Scholar 

  32. J.A. Orenstein and F.A. Manola. Probe spatial data modeling and query processing in an image database application. IEEE Trans. on Software Engineering, 14(5):611–629, 1988.

    Google Scholar 

  33. J. Paredaens, J. Van den Bussche, and D. Van Gucht. Towards a theory of spatial database queries. In Proc. ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems, 1994.

    Google Scholar 

  34. P. Z. Revesz. A closed form for datalog queries with integer order. Theoretical Computer Science, 116(1), August 1993.

    Google Scholar 

  35. P. Z. Revesz. Datalog queries of set constraint databases. In Proc. International Conference on Database Theory, 1995.

    Google Scholar 

  36. C. Tollu S. Grumbach, J. Su. Linear constraint databases. In Proc. LCC; To appear in LNCS Springer-Verlag volume, 1995.

    Google Scholar 

  37. M. Stonebraker, M. Rowe, and L. Hiroshama. The implementation of Postgress. IEEE Transactions on Knowledge and Data Engineering, 1990.

    Google Scholar 

  38. D. Srivastava. Subsumption and indexing in constraint query languages with linear arithmetic constraints. Annals of Mathematics and Artificial Intelligence, to appear, 1992.

    Google Scholar 

  39. D. Srivastava, R. Ramakrishnan, and P. Revesz. Constraint objects. In Proc. 2nd Workshop on the Principles and Practice of Constraint Programming, Orcas Island, WA, May 1994.

    Google Scholar 

  40. L. Vandeurzen, M. Gyssens, and D. Van Gucht. On the desirability and limitations of linear spatial query languages. In M. J. Egenhofer and J. R. Herring, editors, Proc. 4th Symposium on Advances in Spatial Databases, volume 951 of Lecture Notes in Computer Science, pages 14–28. Springer Verlag, 1995.

    Google Scholar 

  41. A. Wolf. The dasdba geo-kernel, concepts, experiences, and the second step. In Design and Implementation of Large Spatial Databases, Proc. 1st Symp. on Spatial Databases. Springer Verlag, 1989.

    Google Scholar 

  42. S. Zdonik. Query optimization in object oriented databases. In Proc. 23rd annual Hawaii International Conference of System Scienced, 1989.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information and Software Systems Engineering, George Mason University, 22030, Fairfax, VA, USA

    Alexander Brodsky & Victor E. Segal

Authors
  1. Alexander Brodsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Victor E. Segal
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Volker Gaede Alexander Brodsky Oliver Günther Divesh Srivastava Victor Vianu Mark Wallace

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Brodsky, A., Segal, V.E. (1996). The C 3 constraint object-oriented database system: An overview. In: Gaede, V., Brodsky, A., Günther, O., Srivastava, D., Vianu, V., Wallace, M. (eds) Constraint Databases and Applications. CDB 1997. Lecture Notes in Computer Science, vol 1191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62501-1_30

Download citation

  • DOI: https://doi.org/10.1007/3-540-62501-1_30

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62501-8

  • Online ISBN: 978-3-540-68049-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation