Distributed query optimization in loosely coupled multidatabase systems

  • Silvio Salza
  • Giovanni Barone
  • Tadeusz Morzy
Contributed Papers Optimization
Part of the Lecture Notes in Computer Science book series (LNCS, volume 893)

Abstract

A multidatabase system (MDBS) is a database system which integrates pre-existing databases, called component local database systems (LDBSs), to support global applications accessing data at more than one LDBS. An important research issue in MDBS is query optimization. The query optimization problem in MDBS is quite different from the case of distributed database system (DDBS) since, due to schema heterogeneity and local autonomy of component LDBSs, is not possible to assume that the query optimizer has a complete information on the execution cost and database statistics. In this paper we present a distributed query optimization algorithm that works under very general assumptions for MDBSs with relational global data model. The algorithm is based on the idea of delegating the evaluation of the execution cost of the elementary steps in a query execution plan to the LDBS where the computation is performed. The optimization process is organized as a sequence of steps, in which at each step all LDBSs work in parallel to evaluate the cost of execution plans for partial queries of increasing size, and send their cost estimates to the other LDBS that need them for the next step. The computation is totally distributed, and organized in order to perform no duplicate computation, and to discard as soon as possible the execution plans that may not lead to an optimal solution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    W. Du, A. K. Elmagarmid, Quasi serializability: a correctness criterion for global concurrency control in InterBase, Proc. of 15th Int. Conf. VLDB, 1989, pp. 347–355.Google Scholar
  2. 2.
    Du, W, et al., Query optimization in heterogeneous DBMS, Proc. of the 18th VLDB Conference, Vancouver, 1992, pp. 277–291Google Scholar
  3. 3.
    A. K. Elmagarmid, W. Du, A paradigm for concurrency control in heterogeneous distributed database systems, Proc. of 6th Int. Conf. on Data Engineering, 1990, pp. 37–46.Google Scholar
  4. 4.
    D. Georgakopolous, M. Rusinkiewicz, A. Sheth, On serializability of multidatabase transactions through forced local conflicts, Proc. 7th Int. Conf. on Data Engineering, 1991, pp. 314–323.Google Scholar
  5. 5.
    Y. E. Ioannidis and Y.C. Kang, Left-Deep vs. Bushy Trees: An Analysis of Strategy Spaces and its Implications for Query Optimization, Proc. of ACM-SIGMOD Conf. on Management of Data, Denver, USA, 1991, pp.168–177Google Scholar
  6. 6.
    W. Lu, et al., On global query optimization in multidatabase systems, Proc. of 2nd Int. Workshop on Research Issues on Data Eng., Tempe, 1992, pp. 217–227Google Scholar
  7. 7.
    W. Lu, et al., Multidatabase query optimization: issues and solutions, Proc. of 3rd Int. Workshop on Research Issues on Data Eng., Vienna, 1993, pp. 137–143Google Scholar
  8. 8.
    S. Mehrotra, R. Rastogi, Y. Breitbart, H. F. Korth, A. Silberschatz, The concurrency control problem in multidatabases: characteristics and solutions, Proc. of ACM SIGMOD Conf., 1992, pp. 288–296.Google Scholar
  9. 9.
    P. Muth, W. Klas, E. J. Neuhold, How to handle global transactions in heterogeneous database systems, Proc. 8th Int. Conf. on Data Engineering, 1992, pp. 192–198.Google Scholar
  10. 10.
    Proc. of Int. Workshop on Multidatabase and Semantic Interoperability, Tulsa, UK, 1990.Google Scholar
  11. 11.
    Proc. of Int. Workshop on Interoperability in Multidatabase Systems — RIDE, Kyoto, Japan, 1991.Google Scholar
  12. 12.
    Proc. of Int. Workshop on Interoperability in Multidatabase Systems — RIDE, Vienna, Austria, 1993.Google Scholar
  13. 13.
    S. Salza, T. Morzy, M. Matysiak, Tabu Search optimization of large join queries, Proc. of 4th Int. Conf. EDBT'94, Cambridge (UK), 1994, pp. 151–161 (Lecture Notes on Computer Science).Google Scholar
  14. 14.
    A. Sheth, J. Larson, Federated database systems for managing distributed, heterogeneous, and autonomous databases, ACM Computing Surveys, 22:183–236, 1990.Google Scholar
  15. 15.
    Zhu, Q, Larson, P-A, A query sampling method for estimating local cost parameters in a multidatabase system, Proc. of 10th Int. Conf. on Data Eng., Houston, 1994, pp. 144–153.Google Scholar

Copyright information

© Springer-Verlag 1995

Authors and Affiliations

  • Silvio Salza
    • 1
  • Giovanni Barone
    • 1
  • Tadeusz Morzy
    • 2
  1. 1.Dipartimento di Informatica e SistemisticaUniversità di Roma “La Sapienza”RomaItaly
  2. 2.Institute of Computing SciencesTechnical University of PoznańPoznańPoland

Personalised recommendations