Skip to main content
Springer Nature Link
Log in

Enhancing an Extensible Query Optimizer with Support for Multiple Equivalence Types

  • Conference paper
  • First Online:
Advances in Databases and Information Systems (ADBIS 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2151))

Abstract

Database management systems are continuously being extended with support for new types of data and advanced querying capabilities. In large part because of this, query optimization has remained a very active area of research throughout the past two decades. At the same time, current commercial optimizers are hard to modify, to incorporate desired changes in, e.g., query algebras or transformation rules. This has led to a number of research contributions aiming to create extensible query optimizers, such as Starburst, Volcano, and OPT++.

This paper reports on a study that has enhanced Volcano to support a relational algebra with added temporal operators, such as temporal join and aggregation. These enhancements include the introduction of algorithms and cost formulas for the new operators, six types of query equivalences, and accompanying query transformation rules. The paper describes extensions to Volcano’s structure and algorithms and summarizes implementation experiences.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. J. A. Blakeley, W. J. McKenna, and G. Graefe. Experiences Building the Open OODB Query Optimizer. In Proceedings ofACMSIGMOD, pp. 287–296 (1993).

    Google Scholar 

  2. R. Bliujute, S. Saltenis, G. Slivinskas, and C. S. Jensen. Developing a DataBlade for a New Index In Proceedings of IEEE ICDE, pp. 314–323 (1999).

    Google Scholar 

  3. M. J. Carey and D. Kossmann. Processing Top N and Bottom N Queries. Data Engineering Bulletin, 20(3): 12–19 (1997).

    Google Scholar 

  4. S. Chaudhuri. An Overview of Query Optimization in Relational Systems. In Proceedings of ACM PODS, pp. 34–43 (1998).

    Google Scholar 

  5. G. Graefe. The Cascades Framework for Query Optimization. Data Engineering Bulletin, 18(3):19–29(1995).

    Google Scholar 

  6. G. Graefe and D. J. DeWitt. The Exodus Optimizer Generator. In Proceedings of ACM SIGMOD, pp. 160–172 (1987).

    Google Scholar 

  7. G. Graefe and W. J. McKenna. The Volcano Optimizer Generator: Extensibility and Efficient Search. In Proceedings of IEEE ICDE, pp. 209–218 (1993).

    Google Scholar 

  8. L. M. Haas et al. Starburst Mid-Flight: As the Dust Clears. IEEETKDE, 2(1):143–160 (1990).

    MathSciNet  Google Scholar 

  9. Informix Software. DataBlade Overview. URL: 〈http://www.informix.com/products/options/udo/datablade/〉, current as of May 29, 2001.

  10. M. Jaedicke and B. Mitschang. User-Defined Table Operators: Enhancing Extensibility for ORDBMS. In Proceedings ofVLDB, pp. 494–505 (1999).

    Google Scholar 

  11. N. Kabra and D. J. De Witt. OPT++: An Object-Oriented Implementation for Extensible Database Query Optimization. VLDB Journal, 8(1):55–78 (1999).

    Article  Google Scholar 

  12. W. J. McKenna, L. Burger, C. Hoang, and M. Truong. EROC: A Toolkit for Building NEATO Query Optimizers. In Proceedings of VLDB, pp. 111–121 (1996).

    Google Scholar 

  13. Oracle Technology Network. Overview of PL/SQL. URL: 〈otn.oracle.com/tech/pl_sql/〉, current as of May 29, 2001.

    Google Scholar 

  14. P. G. Selinger et al. Access Path Selection in a Relational Database Management System. In Proceedings ofACMSIGMOD, pp. 23–34 (1979).

    Google Scholar 

  15. G. Slivinskas, C. S. Jensen, and R. T. Snodgrass. A Foundation for Conventional and Temporal Query Optimization Addressing Duplicates and Ordering. IEEE TKDE, 13(1):21–49 (2001).

    Google Scholar 

  16. G. Slivinskas, C. S. Jensen, and R. T. Snodgrass. Adaptable Query Optimization and Evaluation in Temporal Middleware. In Proceedings of ACM SIGMOD, pp. 127–138 (2001).

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Aalborg University, Denmark

    Giedrius Slivinskas & Christian S. Jensen

Authors
  1. Giedrius Slivinskas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christian S. Jensen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Mathematics and Informatics, Akademijos st. 4, 2600, Vilnius, Lithuania

    Albertas Caplinskas

  2. Department of Informatics Systems, University of Klagenfurt, Universitätsstr. 65, 9020, Klagenfurt, Austria

    Johann Eder

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Slivinskas, G., Jensen, C.S. (2001). Enhancing an Extensible Query Optimizer with Support for Multiple Equivalence Types. In: Caplinskas, A., Eder, J. (eds) Advances in Databases and Information Systems. ADBIS 2001. Lecture Notes in Computer Science, vol 2151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44803-9_6

Download citation

  • DOI: https://doi.org/10.1007/3-540-44803-9_6

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42555-7

  • Online ISBN: 978-3-540-44803-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics