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I/O-Efficient Algorithms for CDBs

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Constraint Databases

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Abstract

In this chapter, we study thé I/O aspects of constraint databases. The goal of this chapter is to show that for many problems arising in constraint databases, it is possible to design theoretically and practically efficient algorithms. In addition, we show that certain problems are provably hard with the result that no theoretically efficient algorithms are possible for them. This chapter has three parts:

  • Algorithms for efficient retrieval of constraints from secondary storage (disk)

  • Algorithms for efficient join between two sets of constraints

  • Lower bounds for the above problems

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Bibliographic Notes

  1. G. S. Lueker. A data structure for orthogonal range queries. In Proceedings 19th IEEE Symposium on Foundations of Computer Science (FOCS’78), pages 28–34, 1978.

    Google Scholar 

  2. B. Chazelle. Lower bounds for orthogonal range searching: I. The reporting case. Journal of the ACM (JACM), 37 (2): 200–212, 1990.

    Article  MathSciNet  MATH  Google Scholar 

  3. D. E. Willard and G. S. Lueker. Adding range restriction capability to dynamic data structures. Journal of the ACM (JACM), 32 (3): 597–617, 1985.

    Article  MathSciNet  MATH  Google Scholar 

  4. F. F. Yao. Computational geometry. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science. Elsevier, 1990.

    Google Scholar 

  5. P. K. Agarwal. Range searching. In Handbook of Discrete and Com- putational Geometry, chapter 30, pages 575–598. CRC Press, 1997.

    Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  7. H. Edelsbrunner. A new approach to rectangle intersections, part I. International Journal of Computer Mathematics, 13: 209–219, 1983.

    Article  MathSciNet  MATH  Google Scholar 

  8. H. Edelsbrunner. A new approach to rectangle intersections, part II. International Journal of Computer Mathematics, 13: 221–229, 1983.

    Article  MathSciNet  MATH  Google Scholar 

  9. J. L. Bentley. Algorithms for Klee’s rectangle problems. Unpublished notes, 1977.

    Google Scholar 

  10. P. C. Kanellakis, S. Ramaswamy, D. E. Vengroff, and J. S. Vitter. Indexing for data models with constraints and classes. Journal of Computer and System Sciences (JCSS), 52 (3): 589–612, 1996.

    Article  MathSciNet  MATH  Google Scholar 

  11. S. Ramaswamy and S. Subramanian. Path caching: A technique for optimal external searching. In Proceedings of the 13th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS’94), pages 25–35. ACM Press, 1994.

    Google Scholar 

  12. S. Ramaswamy. Efficient indexing for constraint and temporal databases. In 6th International Conference on Database Theory (ICDT’97)volume 1186 of Lecture Notes in Computer Sciencepages 419–431. Springer-Verlag, 1997.

    Google Scholar 

  13. B. Chazelle. Filtering search: A new approach to query-answering. SIAM Journal on Computing, 15 (3): 703–724, 1986.

    Article  MathSciNet  MATH  Google Scholar 

  14. L. Arge and J. S. Vitter. Optimal dynamic interval management in external memory. In Proceedings 37th IEEE Symposium on Foundations of Computer Science (FOCS’96), pages 560–569, 1996.

    Google Scholar 

  15. M. H. Overmars. The Design of Dynamic Data Structures, volume 156 of Lecture Notes in Computer Science. Springer-Verlag, 1983.

    Google Scholar 

  16. M. H. Overmars. The Design of Dynamic Data Structures, volume 156 of Lecture Notes in Computer Science. Springer-Verlag, 1983.

    Google Scholar 

  17. A. Guttman. R-trees: A dynamic index structure for spatial searching. In Proceedings of the 1985 ACM SIGMOD International Conference on Management of Data (SIGMOD’85), pages 47–57. ACM Press, 1985.

    Google Scholar 

  18. N. Beckmann, H.-P. Kriegel, R. Schneider, and B. Seeger. The R*-tree: An efficient and robust access method for points and rectangles. In Proceedings of the 1990 ACM SIGMOD International Conference on Management of Data (SIGMOD’90), pages 322–331. ACM Press, 1990.

    Google Scholar 

  19. M. T. Goodrich, J.-J. Tsay, D. E. Vengroff, and J. S. Vitter. Externalmemory computational geometry. In Proceedings 34th IEEE Symposium on Foundations of Computer Science (FOCS’93), pages 714–723, 1993.

    Google Scholar 

  20. L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems. In Proceedings of the 9th ACM-SIAM Symposium on Discrete Algorithms (SODA’98), pages 685–694. ACM Press, 1998.

    Google Scholar 

  21. F. P. Preparata and M. I. Shamos. Computational Geometry: An Introduction. Texts and Monographs in Computer Science. Springer-Verlag, 1985.

    Book  Google Scholar 

  22. P. K. Agarwal. Range searching. In Handbook of Discrete and Com- putational Geometry, chapter 30, pages 575–598. CRC Press, 1997.

    Google Scholar 

  23. J. M. Hellerstein, E. Koutsoupias, and C. H. Papadimitriou. On the analysis of indexing schemes. In Proceedings of the 16th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS’97), pages 249–256. ACM Press, 1997.

    Google Scholar 

  24. V. Samoladas and D. P. Miranker. A lower bound theorem for indexing schemes and its application to multidimensional range queries. In Proceedings of the 17th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS’98), pages 44–51. ACM Press, 1998.

    Google Scholar 

  25. L. Arge, V. Samoladas, and J. S. Vitter. On two-dimensional indexability and optimal range search indexing. In Proceedings of the 18th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS’99), pages 346–357. ACM Press, 1999.

    Google Scholar 

  26. E. Koutsoupias and D. S. Taylor. Tight bounds for 2-dimensional indexing schemes. In Proceedings of the 17th ACM SIGACT-SIGMODSIGART Symposium on Principles of Database Systems (PODS’98), pages 52–58. ACM Press, 1998.

    Google Scholar 

  27. S. Subramanian and S. Ramaswamy. The P-range tree: A new data structure for range searching in secondary memory. In Proceedings of the 6th ACM-SIAM Symposium on Discrete Algorithms (SODA’95), pages 378–387. ACM Press, 1995.

    Google Scholar 

  28. L. Arge and J. S. Vitter. Optimal dynamic interval management in external memory. In Proceedings 37th IEEE Symposium on Foundations of Computer Science (FOCS’96), pages 560–569, 1996.

    Google Scholar 

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Authors
  1. Sridhar Ramaswamy
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Editor information

Editors and Affiliations

  1. Bell Labs/Lucent Technologies, 600 Mountain Avenue, 07974, Murray Hill, NJ, USA

    Gabriel Kuper  & Leonid Libkin  & 

  2. Department of Mathematics and Computer Science, University of Antwerp (UIA), Universiteitsplein 1, 2610, Wilrijk-Antwerp, Belgium

    Jan Paredaens

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© 2000 Springer-Verlag Berlin Heidelberg

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Ramaswamy, S. (2000). I/O-Efficient Algorithms for CDBs. In: Kuper, G., Libkin, L., Paredaens, J. (eds) Constraint Databases. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04031-7_16

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  • DOI: https://doi.org/10.1007/978-3-662-04031-7_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-08542-0

  • Online ISBN: 978-3-662-04031-7

  • eBook Packages: Springer Book Archive

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