Query estimation by adaptive sampling

Yi Leh Wu, Divyakant Agrawal, Amr El Abbadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)


The ability to provide accurate and efficient result estimations of user queries is very important for the query optimizer in database systems. In this paper, we show that the traditional estimation techniques with data reduction points of view do not produce satisfiable estimation results if the query patterns are dynamically changing. We further show that to reduce query estimation error, instead of accurately capturing the data distribution, it is more effective to capture the user query patterns. In this paper, we propose query estimation techniques that can adapt to user query patterns for more accurate estimates of the size of selection or range queries over databases.

Original languageEnglish
Title of host publicationProceedings - International Conference on Data Engineering
EditorsR Agrawal, K Dittrich, A Ngu
Number of pages10
Publication statusPublished - 1 Jan 2002
Externally publishedYes
Event18th International Conference on Data Engineering - San Jose, CA, United States
Duration: 26 Feb 20021 Mar 2002


Other18th International Conference on Data Engineering
CountryUnited States
CitySan Jose, CA


ASJC Scopus subject areas

  • Software
  • Engineering(all)
  • Engineering (miscellaneous)

Cite this

Wu, Y. L., Agrawal, D., & El Abbadi, A. (2002). Query estimation by adaptive sampling. In R. Agrawal, K. Dittrich, & A. Ngu (Eds.), Proceedings - International Conference on Data Engineering (pp. 639-648)