Threshold Queries
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Published:2023-06-07
Issue:1
Volume:52
Page:64-73
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ISSN:0163-5808
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Container-title:ACM SIGMOD Record
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language:en
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Short-container-title:SIGMOD Rec.
Author:
Bonifati Angela1, Dumbrava Stefania2, Fletcher George3, Hidders Jan4, Hofer Matthias5, Martens Wim5, Murlak Filip6, Shinavier Joshua7, Staworko Slawek8, Tomaszuk Dominik9
Affiliation:
1. Lyon 1 Univ., Liris CNRS 2. ENSIIE & IP Paris 3. Eindhoven Univ. of Technology 4. Birkbeck, Univ. of London 5. University of Bayreuth 6. Univ. of Warsaw 7. LinkedIn 8. RelationalAI & Univ. of Lille 9. Univ. of Bialystok
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. We explore how such queries appear in practice and present a method that can be used to significantly improve the asymptotic bounds of their state-of-the-art evaluation algorithms. Our experimental evaluation of these methods shows order-of-magnitude performance improvements.
Publisher
Association for Computing Machinery (ACM)
Subject
Information Systems,Software
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