BIT Numerical Mathematics

, Volume 23, Issue 3, pp 274–294 | Cite as

Interpolation-based index maintenance

  • Walter A. Burkhard
Part I Computer Science

Abstract

A new interpolation-based order preserving hashing algorithm suitable for on-line maintenance of large dynamic external files under sequences of four kinds of operationsinsertion, update, deletion, andorthogonal range query is proposed. The scheme, an adaptation of linear hashing, requires no index or address directory structure and utilizesO(n) space for files containingn records; all of the benefits of linear hashing are inherited by this new scheme. File implementations yielding average successful search lengths much less than 2 and average unsuccessful search lengths much less than 4 for individual records are obtainable; the actual storage required is controllable by the implementor.

Keywords

data structures hashing range queries order preservation algorithms complexity 

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References

  1. 1.
    R. Bayer and E. McCreight,Organization and maintenance of large ordered indexes. Acta Informatica 1, 3 (1972), 173–189.CrossRefGoogle Scholar
  2. 2.
    J. L. Bentley,Multidimensional binary search trees used for associative searching, Communications of the ACM 18, 9 (1975), 504–517.CrossRefGoogle Scholar
  3. 3.
    P. Flajolet,On the performance evaluation of extendible hashing and trie searching, Technical report RJ3258, IBM San Jose (1981).Google Scholar
  4. 4.
    S. P. Gosh and M. E. Senko,File organization: on the selection of random-access index points for sequential files, Journal of the ACM 16 (1969), 569–579.CrossRefGoogle Scholar
  5. 5.
    G. H. Gonnet,Expected length of the longest probe sequence in hash code searching, Journal of the ACM, to appear.Google Scholar
  6. 6.
    P.-Å. Larson,Performance analysis of linear hashing with partial expansions. Technical report series A number 9 (1980), Department of Information Processing, Åbo Akademi, Åbo, Finland.Google Scholar
  7. 7.
    W. Litwin,Trie hashing, Proceedings of the ACM-SIGMOD Conference (1981), 19–29.Google Scholar
  8. 8.
    W. Litwin,Linear Hashing: a new tool for file and table addressing, Proceedings Sixth International Conference on Very Large Data Bases (1980), 212–223.Google Scholar
  9. 9.
    D. G. Lomet,Digital B-trees, Proceedings Seventh International Conference on Very Large Data Bases (1981), 333–344.Google Scholar
  10. 10.
    J. Nievergelt, H. Hinterberger and K. C. Sevcik,The grid file: an adaptable symmetric multi-key file structure, Report 46 (1981), Eidgenössische Technische Hochschule, Zürich.Google Scholar
  11. 11.
    J. A. Orenstein and T. H. Merrett,A class of data structures for associative searching. Preprint (1982), McGill University.Google Scholar
  12. 12.
    J. T. Robinson,The K-D-B tree: a search structure for large multidimensional dynamic indexes, Technical report February 1981, Department of Computer Science, Carnegie-Mellon University.Google Scholar
  13. 13.
    R. L. Rivest,Partial-match retrieval algorithms, SIAM Journal of Computing, 5, 1 (1976), 19–50.CrossRefGoogle Scholar
  14. 14.
    M. Tamminen,The EXCELL method for efficient geometric access to data, Acta Polytechnica Scandinavica, Mathematics and Computer Science Series No. 34 (1981), Helsinki.Google Scholar

Copyright information

© BIT Foundations 1983

Authors and Affiliations

  • Walter A. Burkhard
    • 1
  1. 1.Department of Electrical Engineering and Computer SciencesUniversity of California, San DiegoLa Jolla

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