Threshold queries in theory and in the Wild
Document type :
Compte-rendu et recension critique d'ouvrage
DOI :
Title :
Threshold queries in theory and in the Wild
Author(s) :
Bonifati, Angela [Auteur]
Base de Données [BD]
Dumbrava, Stefania [Auteur]
Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise [ENSIIE]
Architecture, Cloud continuum, formal Models, artificial intElligence and Services in distributed computing [ACMES-SAMOVAR]
Institut Polytechnique de Paris [IP Paris]
Fletcher, George [Auteur]
Eindhoven University of Technology [Eindhoven] [TU/e]
Hidders, Jan [Auteur]
Birkbeck College [University of London]
Hofer, Matthias [Auteur]
Universität Bayreuth [Deutschland] = University of Bayreuth [Germany] = Université de Bayreuth [Allemagne]
Martens, Wim [Auteur]
Universität Bayreuth [Deutschland] = University of Bayreuth [Germany] = Université de Bayreuth [Allemagne]
Murlak, Filip [Auteur]
University of Warsaw [UW]
Shinavier, Joshua [Auteur]
Staworko, Slawomir [Auteur]
Linking Dynamic Data [LINKS]
Tomaszuk, Dominik [Auteur]
University of Bialystok
Base de Données [BD]
Dumbrava, Stefania [Auteur]
Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise [ENSIIE]
Architecture, Cloud continuum, formal Models, artificial intElligence and Services in distributed computing [ACMES-SAMOVAR]
Institut Polytechnique de Paris [IP Paris]
Fletcher, George [Auteur]
Eindhoven University of Technology [Eindhoven] [TU/e]
Hidders, Jan [Auteur]
Birkbeck College [University of London]
Hofer, Matthias [Auteur]
Universität Bayreuth [Deutschland] = University of Bayreuth [Germany] = Université de Bayreuth [Allemagne]
Martens, Wim [Auteur]
Universität Bayreuth [Deutschland] = University of Bayreuth [Germany] = Université de Bayreuth [Allemagne]
Murlak, Filip [Auteur]
University of Warsaw [UW]
Shinavier, Joshua [Auteur]
Staworko, Slawomir [Auteur]
Linking Dynamic Data [LINKS]
Tomaszuk, Dominik [Auteur]
University of Bialystok
Journal title :
Proceedings of the VLDB Endowment (PVLDB)
Pages :
1105–1118
Publisher :
VLDB Endowment
Publication date :
2022-01-01
ISSN :
2150-8097
English keyword(s) :
Information systems
Data management systems
Database management system engines
Database query processing
Query languages
Theory of computation
Theory and algorithms for application domains
Database theory
Data management systems
Database management system engines
Database query processing
Query languages
Theory of computation
Theory and algorithms for application domains
Database theory
HAL domain(s) :
Informatique [cs]/Base de données [cs.DB]
English abstract : [en]
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 ...
Show more >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.Show less >
Show more >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.Show less >
Language :
Anglais
Popular science :
Non
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