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An efficient join for nested relational databases

  • Hong-Cheu Liu
  • Chaiyaporn Chirathamjaree
Relational and Extended Relational Approaches
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1134)

Abstract

The join operation is one of the most expensive and critical issues in nested relational query processing. Many natural queries cannot be expressed by extended join operators proposed for the nested relational model so far without restructuring operations. In this paper, we consider a more general form of join, called P-join, which does not require as many restructuring operators and combines the advantages of the extended natural join and the recursive join for efficient data access. We propose an algorithm for computing the P-join and estimate cost required by using various join techniques developed in relational database systems. The complexity of the P-join algorithm is not more than other join algorithms with expensive restructuring operators involved and additional block shuffle for reading unnecessary data files.

Keywords

Relational Database Extended Cartesian Product Query Optimisation Storage Structure Storage Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    E. Bertino. An indexing technique for object-oriented databases. In Proceedings of the IEEE Conference on Data Engineering, 1991.Google Scholar
  2. 2.
    E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Transactions on Knowledge and Data Engineering, 1989.Google Scholar
  3. 3.
    C. Beeri. New Data Models and Languages — the Challenge. In Proceedings of the 11th ACM Symposium on Principles of Database Systems, pages 1–15, 1992.Google Scholar
  4. 4.
    R. Cattell. Object Data Management. Revised Edition, Addison-Wesley, 1994.Google Scholar
  5. 5.
    L.S. Colby. A Recursive Algebra and Query Optimisation for Nested Relations. In Proceedings of the ACM SIGMOD International Conference on the Management of Data, pages 273–283, 1989.Google Scholar
  6. 6.
    V. Deshpande and P.A. Larson. The design and implementation of a parallel join algorithm for nested relations on shared-memory multiprocessors. In Proceedings of the IEEE Conference on Data Engineering, 1992.Google Scholar
  7. 7.
    A. Deshpande and D. Van Gucht. An implementation for nested relational databases. In Proceedings of the International Conference on Very Large Data Bases, 1988.Google Scholar
  8. 8.
    G. Graefe. Query Evaluation Techniques for Large Databases. ACM Computing Surveys, 25(2), 1993.Google Scholar
  9. 9.
    M. Gyssens and D. Van Gucht. The Powerset Algebra as a Result of Adding Programming Constructs to the Nested Relational Algebra. In Proceedings of ACM Symposium on Principles of Database Systems, pages 225–232, 1988.Google Scholar
  10. 10.
    A. Hafez and G. Ozsoyoglu. Storage structures for nested relations. IEEE Database Engineering, 11(3), 1988.Google Scholar
  11. 11.
    Y. Jan. Algebraic Optimisation for Nested Relations. In Proceedings of the 23rd Hawaii International Conference on System Sciences, Vol.2, pages 278–287, 1990.Google Scholar
  12. 12.
    H.F. Korth. Optimisation of Object-Retrieval Queries. In Proceedings of the 2nd International Workshop on Object-Oriented Database Systems, pages 352–357, 1988.Google Scholar
  13. 13.
    M. Kifer, W. Kim and Y. Sagiv. Querying Object-Oriented Databases. In Proceedings of the ACM SIGMOD International Conference on the Management of Data, pages 393–402, 1992.Google Scholar
  14. 14.
    W. Kim. Object-Oriented Database System: Promises, Reality and Future. In Proceedings of the 19th Very Large Data Bases Conference, pages 676–687, 1993.Google Scholar
  15. 15.
    H.-C. Liu and K. Ramamohanarao. Multiple Paths Join for Nested Relational Databases. In Proceedings of Fifth Australasian Database Conference, pages 30–44, 1994.Google Scholar
  16. 16.
    H.-C. Liu and K. Ramamohanarao. Algebraic Equivalences among Nested Relational Expressions. In Proceedings of Third International Conference on Information and Knowledge Management, Gaitherburg, Maryland, pages 234–243, 1994Google Scholar
  17. 17.
    P. Mishra and M.H. Eich. Join Processing in Relational Databases. In ACM Computing Surveys, 24(1): 63–113.Google Scholar
  18. 18.
    M.A. Roth, H.F. Korth and A. Silberschatz. Extended Algebra and Calculus for non-1NF Relational Databases. ACM Transactions on Database Systems, 13(4):389–417, 1988.CrossRefGoogle Scholar
  19. 19.
    R. Sacks-Davis, A, Kent, K. Ramamohanarao, J. Thom, J. Zobel. ATLAS: A Nested Relational Database System for Text Applications. IEEE Transactions on Knowledge and Data Engineering, pages 454–470, June, 1995.Google Scholar
  20. 20.
    M.H. Scholl and H.J. Schek. The Relational Object Model. In Proceedings of International Conference on Database Theory, pages 89–105, 1990.Google Scholar
  21. 21.
    H.J. Schek and M.H. Scholl. The Relational Model with Relation-Valued Attributes, Information Systems, Vol. 11, No. 2, pages 137–147, 1986.CrossRefGoogle Scholar
  22. 22.
    K. Tanaka and T.S. Chang. On Natural Joins in Object-Oriented Databases. In Proceedings of First International Conference on Deductive and Object-Oriented Databases, Elsevier Science Publishing Company, pages 335–346, 1990.Google Scholar
  23. 23.
    J. Ullman. Principles of Database and Knowledge-Base System, Vol. 2. Computer Science Press. 1989.Google Scholar
  24. 24.
    P. Valduriez. Join indices. ACM Transactions on Database Systems. 12(2), 1987.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Hong-Cheu Liu
    • 1
  • Chaiyaporn Chirathamjaree
    • 1
  1. 1.Department of Computer ScienceEdith Cowan UniversityMount LawleyAustralia

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