[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Approximate Query Processing

  • Reference work entry
Encyclopedia of Database Systems

Synonyms

Approximate query answering

Definition

Query processing in a database context is the process that deduces information that is available in the database. Due to the huge amount of data available, one of the main issues of query processing is how to process queries efficiently. In many cases, it is impossible or too expensive for users to get exact answers in the short query response time. Approximate query processing (AQP) is an alternative way that returns approximate answer using information which is similar to the one from which the query would be answered. It is designed primarily for aggregate queries such as count, sum and avg, etc. Given a SQL aggregate query Q, the accurate answer is y while the approximate answer is y′. The relative error of query Q can be quantified as:

$$Error(Q) = \vert{ {y - y'}\over {y}} \vert .$$
((1))

The goal of approximate query processing is to provide approximate answers with acceptable accuracy in orders of magnitude less query response...

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

Access this chapter

Subscribe and save

Springer+ Basic
£29.99 /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
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 1,665.00
Price includes VAT (United Kingdom)
  • 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

Recommended Reading

  1. Das G. Sampling methods in approximate query answering systems. In Invited Book Chapter, Encyclopedia of Data Warehousing and Mining, John Wang (ed.). Information Science Publishing, 2005.

    Google Scholar 

  2. Das A., Gehrke J., and Riedewald M. Approximation Techniques for Spatial Data. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 2004, pp. 695–700.

    Google Scholar 

  3. Garofalakis M. and Gibbons P. Approximate Query Processing: Taming the TeraBytes: A Tutorial. In Proc. 27th Int. Conf. on Very Large Data Bases, 2001.

    Google Scholar 

  4. Hellerstein J., Haas P., and Wang H. Online Aggregation. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1997, pp. 171–182.

    Google Scholar 

  5. Ioannidis Y. Approximation in Database Systems. In Proc. 9th Int. Conf. on Database Theory, 2003, pp. 16–30.

    Google Scholar 

  6. Ioannidis Y. The History of Histograms (abridged). In Proc. 29th Int. Conf. on Very Large Data Bases, 2003, pp. 19–30.

    Google Scholar 

  7. Matias Y., Vitter J., and Wang M. Wavelet Based Histograms for Selectivity Estimation. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1998, pp. 448–459.

    Google Scholar 

  8. Morgenstein J. Computer Based Management Information Systems Embodying Answer Accuracy as a User Parameter. PhD Thesis, U.C. Berkeley, 1980.

    Google Scholar 

  9. Poosala V. and Ioannidis Y. Selectivity Estimation Without the Attribute Value Independence Assumption. In Proc. 23th Int. Conf. on Very Large Data Bases, 1997, pp. 466–475.

    Google Scholar 

  10. Poosala V., Ioannidis Y., Haas P., and Shekita E. Improved Histograms for Selectivity Estimation of Range Predicates. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1996, pp. 294–305.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this entry

Cite this entry

Liu, Q. (2009). Approximate Query Processing. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_534

Download citation

Publish with us

Policies and ethics