Skip to main content
SpringerLink
Log in

Temporal Query Processing

  • Reference work entry
  • First Online:
Encyclopedia of Database Systems

  • 16 Accesses

Definition

Temporal query processing refers to the techniques used by database management system to process temporal statements. This ranges from the implementation of query execution plans to the design of system architectures. This entry surveys different system architectures. It is possible to identify three general system architectures that have been used to systematically offer temporal query processing functionality to applications [6]: The layered approach uses an off-the-shelf database system and extends it by implementing the missing functionality in a layer between the database system and the applications. The monolithic approach integrates the necessary application-specific extensions directly into the database system. The extensible approach relies on a database system that allows to plug user-defined extensions into the database system.

Historical Background

In order to deploy systems that offer support for temporal query processing new systems must be designed and...

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 4,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 6,499.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Recommended Reading

  1. Bliujute R, Saltenis S, Slivinskas G, Jensen CS. Developing a datablade for a new index. In: Proceedings of the 15th International Conference on Data Engineering; 1999. p. 314–23.

    Google Scholar 

  2. Böhlen MH. Temporal database system implementations. ACM SIGMOD Rec. 1995;24(4):16.

    Article  Google Scholar 

  3. Böhlen MH, Snodgrass RT, Soo MD. Coalescing in temporal databases. In: Proceedings of the 22nd International Conference on Very Large Data Bases; 1996. p. 180–91.

    Google Scholar 

  4. Dunn J, Davey S, Descour A, Snodgrass RT. Sequenced subset operators: definition and implementation. In: Proceedings of the 18th International Conference on Data Engineering; 2002. p. 81–92.

    Google Scholar 

  5. Graefe G, McKenna WJ. The volcano optimizer generator: extensibility and efficient search. In: Proceedings of the 9th International Conference on Data Engineering; 1993. p. 209–18.

    Google Scholar 

  6. Koubarakis M, Sellis TK, Frank AU, Grumbach S, Güting RH, Jensen CS, Lorentzos NA, Manolopoulos Y, Nardelli E, Pernici B, Schek H, Scholl M, Theodoulidis B, Tryfona N, editors. Spatio-temporal databases: the CHOROCHRONOS approach, vol. 2520. Berlin: Springer; 2003.

    MATH  Google Scholar 

  7. Kriegel HP, Pötke M, Seidl T. Managing intervals efficiently in object-relational databases. In: Proceedings of the 26th International Conference on Very Large Data Bases; 2000. p. 407–18.

    Google Scholar 

  8. Leung TYC, Muntz RR. Stream processing: temporal query processing and optimization. In: Tansel A, Clifford J, Gadia S, Jajodia S, Segev A, Snodgrass RT, editors. Temporal databases: theory, design, and implementation. Benjamin/Cummings; 1993. p. 329–55.

    Google Scholar 

  9. Melton J, Simon AR. Understanding the new SQL: a complete guide. Los Altos: Morgan Kaufmann; 1993.

    Google Scholar 

  10. Slivinskas G, Jensen CS, Snodgrass RT. Adaptable query optimization and evaluation in temporal middleware. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2001. p. 127–38.

    Google Scholar 

  11. Snodgrass RT. Developing time-oriented database applications in SQL. Los Altos: Morgan Kaufmann; 1999.

    Google Scholar 

  12. Stonebraker M, editor. The INGRES papers: anatomy of a relational database system. Reading: Addison-Wesley; 1986.

    MATH  Google Scholar 

  13. The Postgresql Global. POSTGRESQL developer’s guide.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

    Michael H. Böhlen

  2. University of Zurich, Zürich, Switzerland

    Michael H. Böhlen

Authors
  1. Michael H. Böhlen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael H. Böhlen .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. University of Arizona, Tucson, AZ, USA

    Richard T. Snodgrass

  2. Aalborg University, Aalborg Øst, Denmark

    Christian S. Jensen

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Böhlen, M.H. (2018). Temporal Query Processing. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_408

Download citation

Publish with us

Policies and ethics

Search

Navigation