Bonifati, A. and Dumbrava, S. and Fletcher, G. and Hidders, Jan and Hofer, M. and Martens, W. and Murlak, F. and Shinavier, J. and Staworko, S. and Tomaszuk, D. (2025) Threshold queries in theory and in the wild. The VLDB Journal 34 (4), ISSN 1066-8888.
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Abstract
Threshold queries are an important class of queries that only require computing or counting answers up to a specified threshold value. To the best of our knowledge, threshold queries have been largely disregarded in the research literature, which is surprising considering how common they are in practice. In this paper, we present a deep theoretical analysis of threshold query evaluation and show that thresholds can be used to significantly improve the asymptotic bounds of state-of-the-art query evaluation algorithms. We also empirically show that threshold queries are significant in practice. In surprising contrast to conventional wisdom, we found important scenarios in real-world data sets in which users are interested in computing the results of queries up to a certain threshold, independent of a ranking function that orders the query results.
Metadata
| Item Type: | Article |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Research Centres and Institutes: | Birkbeck Knowledge Lab, Data Analytics, Birkbeck Institute for |
| Depositing User: | Jan Hidders |
| Date Deposited: | 27 Jun 2025 15:25 |
| Last Modified: | 22 Sep 2025 19:43 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/55828 |
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