An Analytical Method to Allocate Processors in High Performance Parallel Execution of Recursive Queries

  • A. Hameurlain
  • F. Morvan
  • E. Ceccato


This paper presents an analytical method to allocate processors in high performance parallel execution of recursive queries. The proposed method consists in computing (i) the number of tuples deduced by the transitive closure in account eventually of the selection clauses propagation and (ii) the number of economical processors. The main contribution of this paper is the presentation of an efficient method to compute the economical number of processors and the performance analysis which reveals the influence of DT on the allocation of processors number, response time and the generation of an execution plan.


transItive Closure Execution Plan Processor Number Recursive Query selectIve Clause 
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  1. [1]
    F. Bancilhon, R. Ramakrishan, “An Amateur’s Introduction to Recursive Query Processing Strategies”, Proc. of ACM-SIGMOD, Washington, p. 16, May 1986.Google Scholar
  2. [2]
    H. Boral et al., “Prototyping Bubba, a Highly Parallel Database System”, IEEE Transaction Knowledge and Data Engineering. Vol. 1, No. 1, p. 4, March 1990.CrossRefGoogle Scholar
  3. [3]
    P. Bazex and A. Hameurlain, “Evaluation optimisée de relations virtuelles par parcours de structures arborescentes”, Workshop AFCET des bases de données aux bases de connaissances, Nice, p. 265, Septembre 1987.Google Scholar
  4. [4]
    J. P. Cheiney, C. DE Maindreville, “A Parallel Strategy for Transitive Closure Using Double Hash-Based Clustering”, Proc. of the 16th Intl. Conf. VLDB, Brisbane, Australia, August 1990.Google Scholar
  5. [5]
    DJ. Dewitt et al., “The Gamma Database Machine Project”, IEEE Transaction Knowledge and Data Engineering. Vol. 1, No. 1, p. 44, March 1990.MathSciNetCrossRefGoogle Scholar
  6. [6]
    A. Hameurlain, F. Morvan, “An Algorithm For Selection Operator Propagation in Resolution Graph”, Intl. Conf. On Database and Expert Systems Applications, Vienna, p. 550, Aug. 1990.Google Scholar
  7. [7]
    A. Hameurlain, F. Morvan,“Parallel Deductive Databases: Design and Implementation of a Parallel Algorithm for Computing Recursive Queries”, SUG 9th Anu. Conf.: Distributed Applications and Multiprocessor Technology, San Jose, California, p. 181, Dec. 1991.Google Scholar
  8. [8]
    A. Hameurlain et al., “Processor Number Estimation for Optimal Parallel Execution of recursive Queries”, European Workshops on Parallel Computing, Barcelona, p. 418, March 1992.Google Scholar
  9. [9]
    Y. E. Ioannidis, R. Ramakrishan, “Efficient Transitive Closure Algorithm”, Proc. of the 14th VLDB Conf. Los Angeles, California, p. 382,1988.Google Scholar
  10. [10]
    P. Selinger et al. “Access Path Selection in a relational Database Management System”, Proc. of ACM-SIGMOD, Boston, p. 23, May 1979.Google Scholar
  11. [11]
    P. Valduriez, S. Khoshafian, “Parallel Evaluation of the Transitive Closure of a Database Relation”, Intl. Journal of Parallel Programming, Vol. 17, No. 1, p. 19, Feb. 1988.CrossRefGoogle Scholar
  12. [12]
    P. Valduriez, S. Khoshafian, “Transitive Closure of Transitively Closed Relation”, Proc. of the 2nd Int. Conf. on Expert database systems, Tysons Comer, Virginia, p. 377, April 1988.Google Scholar

Copyright information

© Springer-Verlag/Wien 1992

Authors and Affiliations

  • A. Hameurlain
    • 1
  • F. Morvan
    • 1
  • E. Ceccato
    • 1
  1. 1.Lab. IRITUniversité Paul SabatierToulouseFrance

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