On the Analysis of On-Line Database Reorganization

  • Vlad I. S. Wietrzyk
  • Mehmet A. Orgun
  • Vijay Varadharajan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1884)


We consider the problem of on-line database reorganization. The types of reorganization that we discuss are restoration of clustering, purging of old data, creation of a backup copy, compaction, and construction of indexes. The contributions of this paper are both of theoretical and of experimental nature.


On-line Reorganization Dynamic Clustering Statistical Profileof Access Patterns Object Database Systems Performance Analysis Buffering 


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  1. 1.
    T. Eiter and G. Gottlob.: Identifying the minimal transversals of a hypergraph and related problems. SIAM Journal on Computing, 24(6):1278–1304, Dec. 1995.Google Scholar
  2. 2.
    V. Wietrzyk, Mehmet A. Orgun.: A Foundation for High Performance Object Database Systems. In Databases for the Millennium 2000 in proceedings of the 9th International Conference on Management of Data, Hyderabad, December, 1998.Google Scholar
  3. 3.
    V. Wietrzyk, M. A. Orgun.: VERSANT Architecture: Supporting High-Performance Object Databases. International Database Engineering and Applications Symposium, IDEAS98, Cardiff, U.K., July 1998, IEEE Computer Society Press, Los Alamitos, Calif., 1998.Google Scholar
  4. 4.
    Batory, D. S.: Optimal File Designs and Reorganization Points. ACM Trans. On Database Systems, Vol. 7, 1982.Google Scholar
  5. 5.
    J.B. Cheng, A.R. Hurson.: Effective Clustering of Complex Objects in Object-Oriented Databases. ACM SIGMOD Conference, 1991.Google Scholar
  6. 6.
    P. N. Klein, R. E. Tarjan.: A randomized linear-time algorithm for finding minimum spanning trees. In Proceedings of the 26th Annual ACM Symposium on Theory of Computing. Montreal, Que., Canada. May 23–25). ACM, New York, p. 9–15, 1994.Google Scholar
  7. 7.
    D. Alberts, G. Cattaneo, G. F. Italiano.: An empirical study of dynamic graph algorithms. Proc. 7th ACM-SIAM Symp. on Discrete Algorithms (1996).Google Scholar
  8. 8.
    R. E. Tarjan and D. D. Sleator.: A data structure for dynamic trees. J. Comp. Sys. Sci., 1983.Google Scholar
  9. 9.
    T. L. Anderson, A. J. Berre, M. Mallison et al.: The Hypermodel Benchmark in Bancilhon, Thanos, Tsichritzis (Eds.): Advances in Database Technology-EDBT’90, LNCS 416, 1990.CrossRefGoogle Scholar
  10. 10.
    VERSANT System Manual.: VERSANT Release 5.0, February 1997.Google Scholar
  11. 11.
    C. Mohan, D. Haderle, B. Lindsay, H. Pirahesh et al.: ARIES: A Transaction Recovery Method Supporting Fine-Granularity Locking and Partial Rollbacks Using Write-Ahead Logging. ACM Transactions on Database Systems, 17(1):94–162, March 1992.Google Scholar
  12. 12.
    C. Mohan, I. Narang.: Algorithms for creating indexes for very large tables without quiescing updates In Proceedings ACM SIGMOD Intl Conf Management of Data, pages pp 361–370, June 1992Google Scholar
  13. 13.
    E. Omiecinski.: Concurrent file conversion between b+ tree and linear hash files. Information Systems. 14(5) pp 371–383, 1989CrossRefGoogle Scholar
  14. 14.
    B. Salzberg, A. Dimock.: Principles of transaction-based on-line reorganization In Proceedings 18th Intl Conf Very Large Databases, pages pp 511–520, San Mateo, CA, Aug 1992 Morgan Kaufmann PublishersGoogle Scholar
  15. 15.
    G. Weikum, P. Zabback, P. Scheuermann.: Dynamic file allocation in disk arrayes In ACM SIGMOD International Conference on Management of Data, pages pp 406–415, 1991Google Scholar
  16. 16.
    G. S. Smith.: Online reorganization of key-sequenced tables and files Tandem System Review, 6(2), pp 52–59, Oct 1990.Google Scholar
  17. 17.
    G. Copeland, T. Keller, R. Krishnamurthy, M. Smith.: The Case for Safe RAM In Proceedings 15th Intl Conf Very Large Databases, pages pp 327–335, Amsterdam, The Netherlands, Aug 1989 Morgan Kaufmann PublishersGoogle Scholar
  18. 18.
    P. M. Chen, W. T. Ng, S. Chandra, Ch. M. Aycock, G. Rajamani, D. Lowell.: The Rio File Cache: Surviving Operating System Crashes In Proceedings of the 1996 International Conference on Architectural Support for Programming Languages and Operating systems (ASPLOS), pages pp 74–83, October 1996.Google Scholar
  19. 19.
    M. Sullivan, M. Stonebraker.: Using write protected data structures to improve software fault tolerance in highly available database management systems In Proceedings of the 1991 International Conference on Very Large Data Bases (VLDB), pages pp 171–180, September 1991.Google Scholar
  20. 20.
    D. J. DeWitt, R. H. Katz, F. F. Olken, L. D. Shapiro, M. R. Stonebraker, D. Wood.: Implementation Techniques for Main Memory database Systems In Proceedings of the 1984 ACM SIGMOD International Conference on Management of Data, pages pp 1–8, June 1984.Google Scholar
  21. 21.
    Theo Haerder, Andreas Reuter.: Principles of transaction-Oriented Database Recovery ACM Computing Surveys, 15(4):287–317, December 1983.Google Scholar
  22. 22.
    S. Akyurek, K. Salem.: management of partially safe buffers IEEE transactions on Computers, 44(3): 394–407, March 1995.Google Scholar
  23. 23.
    P. M. Chen, E. K. Lee, G. A. Gibson, R. H. Katz, D. A. Patterson.: RAID: High-Performance, Reliable Secondary Storage ACM Computing Surveys, 26(2): 145–188, June 1994.Google Scholar
  24. 24.
    Wee Teck NG, Ch. M. Aycock, G. Rajmani, P. M. Chen.: Comparing Disk and Memory’s resistance to Operating system crashes International Symposium on Software reliability Engineering, 1996.Google Scholar
  25. 25.
    R. A. Agrawal, H. V. Jagadish.: Recovery Algorithms for database Machines with Nonvolatile main memory In Database Machines. Sixth international Workshop, IWDM’89 Proceedings., June 1989.Google Scholar
  26. 26.
    M. Sullivan, R. Chillarege.: A Comparison of Software Defects in Database Management Systems and Operating Systems In Proceedings of the 1992 international Symposium on Fault-Tolerant Computing, pages 475–484, July 1992.Google Scholar
  27. 27.
    K. Elhardt, R. Bayer.: A Database cache for High Performance and Fast restart in database Systems ACM Transactions on Database Systems, 9(4): 503–525, December 1984.Google Scholar
  28. 28.
    A. Bhide, D. Dias, N. Nagui Halim, B. Smith, F. Parr.: A Case for Fault-Tolerant Memory for Transaction Processing In Proceedings of the 1993 International symposium on Fault-Tolerant Computing, pages, pp: 451–460, June 1993.Google Scholar
  29. 29.
    M. L. McAuliffe, M. J. Carey, M. H. Solomon.: Towards Effective and Efficient Free Space Management In Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, pages pp 389–400, 1996.Google Scholar
  30. 30.
    A. Mehta, J. Geller, Y. Perl, E. J. Neuhold.: The OODB Path-Method Generator (PMG) Using Precomputed Access Relevance Proc. of the 2nd Int’l Conference on Information and Knowledge Management, Washington DC, 1993, pages pp:596–605.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Vlad I. S. Wietrzyk
    • 1
  • Mehmet A. Orgun
    • 1
    • 2
  • Vijay Varadharajan
    • 1
  1. 1.School of Computing and Information TechnologyUniversity of Western Sydney - NepeanKingswoodAustralia
  2. 2.Department of ComputingMacquarie UniversitySydneyAustralia

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