By Topic

Large-sample and deterministic confidence intervals for online aggregation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Haas, P.J. ; IBM Almaden Res. Center, San Jose, CA, USA

The online aggregation system recently proposed by J.M. Hellerstein, et al. (1997) permits interactive exploration of large, complex datasets stored in relational database management systems. Running confidence intervals are an important component of an online aggregation system and indicate to the user the estimated proximity of each running aggregate to the corresponding final result. Large sample confidence intervals contain the final result with a prespecified probability and rest on central limit theorems, while deterministic confidence intervals contain the final query result with probability 1. We show how new and existing central limit theorems, simple bounding arguments, and the delta method can be used to derive formulas for both large sample and deterministic confidence intervals. To illustrate these techniques, we obtain formulas for running confidence intervals in the case of single table and multi table AVG, COUNT, SUM, VARIANCE, and STDEV queries with join and selection predicates. Duplicate elimination and GROUP-BY operations are also considered. We then provide numerically stable algorithms for computing the confidence intervals and analyzing the complexity of these algorithms

Published in:

Scientific and Statistical Database Management, 1997. Proceedings., Ninth International Conference on

Date of Conference:

11-13 Aug 1997