From stars to galaxies: skyline queries on aggregate data

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Standard

From stars to galaxies : skyline queries on aggregate data. / Magnani, Matteo; Assent, Ira.

International Conference on Extending Database Technology . ed. / Giovanna Guerrini ; Norman W. . Paton . Association for Computing Machinery, 2013. p. 477-488 .

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Harvard

Magnani, M & Assent, I 2013, From stars to galaxies: skyline queries on aggregate data. in G Guerrini & NW . Paton (eds), International Conference on Extending Database Technology . Association for Computing Machinery, pp. 477-488 , International Conference on Extending Database Technology , Genoa, Italy, 18/03/2013. https://doi.org/10.1145/2452376.2452432

APA

Magnani, M., & Assent, I. (2013). From stars to galaxies: skyline queries on aggregate data. In G. Guerrini , & N. W. . Paton (Eds.), International Conference on Extending Database Technology (pp. 477-488 ). Association for Computing Machinery. https://doi.org/10.1145/2452376.2452432

CBE

Magnani M, Assent I. 2013. From stars to galaxies: skyline queries on aggregate data. Guerrini G, . Paton NW, editors. In International Conference on Extending Database Technology . Association for Computing Machinery. pp. 477-488 . https://doi.org/10.1145/2452376.2452432

MLA

Magnani, Matteo and Ira Assent "From stars to galaxies: skyline queries on aggregate data". and Guerrini , Giovanna . Paton , Norman W. (editors). International Conference on Extending Database Technology . Association for Computing Machinery. 2013, 477-488 . https://doi.org/10.1145/2452376.2452432

Vancouver

Magnani M, Assent I. From stars to galaxies: skyline queries on aggregate data. In Guerrini G, . Paton NW, editors, International Conference on Extending Database Technology . Association for Computing Machinery. 2013. p. 477-488 https://doi.org/10.1145/2452376.2452432

Author

Magnani, Matteo ; Assent, Ira. / From stars to galaxies : skyline queries on aggregate data. International Conference on Extending Database Technology . editor / Giovanna Guerrini ; Norman W. . Paton . Association for Computing Machinery, 2013. pp. 477-488

Bibtex

@inproceedings{5654d8e3459b4482ab2447b6cdbf9e02,
title = "From stars to galaxies: skyline queries on aggregate data",
abstract = "The skyline operator extracts relevant records from multidimensional databases according to multiple criteria. This operator has received a lot of attention because of its ability to identify the best records in a database without requiring to specify complex parameters like the relative importance of each criterion. However, it has only been defined with respect to single records, while one fundamental functionality of database query languages is aggregation, enabling operations over sets of records. In this paper we introduce aggregate skylines, where the skyline works as a filtering predicate on sets of records. This operator can be used to express queries in the form: return the best groups depending on the features of their elements, and thus provides a powerful combination of grouping and skyline functionality. We define a semantics for aggregate skylines based on a sound theoretical framework and study its computational complexity. We propose efficient algorithms to implement this operator and test them on real and synthetic data, showing that they outperform a direct SQL implementation of up to two orders of magnitude.",
author = "Matteo Magnani and Ira Assent",
year = "2013",
doi = "10.1145/2452376.2452432",
language = "English",
isbn = "978-1-4503-1597-5 ",
pages = "477--488 ",
editor = "{ Guerrini }, Giovanna and {. Paton }, { Norman W. }",
booktitle = "International Conference on Extending Database Technology",
publisher = "Association for Computing Machinery",
note = "International Conference on Extending Database Technology , EDBT ; Conference date: 18-03-2013 Through 21-03-2013",

}

RIS

TY - GEN

T1 - From stars to galaxies

T2 - International Conference on Extending Database Technology

AU - Magnani, Matteo

AU - Assent, Ira

N1 - Conference code: 16

PY - 2013

Y1 - 2013

N2 - The skyline operator extracts relevant records from multidimensional databases according to multiple criteria. This operator has received a lot of attention because of its ability to identify the best records in a database without requiring to specify complex parameters like the relative importance of each criterion. However, it has only been defined with respect to single records, while one fundamental functionality of database query languages is aggregation, enabling operations over sets of records. In this paper we introduce aggregate skylines, where the skyline works as a filtering predicate on sets of records. This operator can be used to express queries in the form: return the best groups depending on the features of their elements, and thus provides a powerful combination of grouping and skyline functionality. We define a semantics for aggregate skylines based on a sound theoretical framework and study its computational complexity. We propose efficient algorithms to implement this operator and test them on real and synthetic data, showing that they outperform a direct SQL implementation of up to two orders of magnitude.

AB - The skyline operator extracts relevant records from multidimensional databases according to multiple criteria. This operator has received a lot of attention because of its ability to identify the best records in a database without requiring to specify complex parameters like the relative importance of each criterion. However, it has only been defined with respect to single records, while one fundamental functionality of database query languages is aggregation, enabling operations over sets of records. In this paper we introduce aggregate skylines, where the skyline works as a filtering predicate on sets of records. This operator can be used to express queries in the form: return the best groups depending on the features of their elements, and thus provides a powerful combination of grouping and skyline functionality. We define a semantics for aggregate skylines based on a sound theoretical framework and study its computational complexity. We propose efficient algorithms to implement this operator and test them on real and synthetic data, showing that they outperform a direct SQL implementation of up to two orders of magnitude.

U2 - 10.1145/2452376.2452432

DO - 10.1145/2452376.2452432

M3 - Article in proceedings

SN - 978-1-4503-1597-5

SP - 477

EP - 488

BT - International Conference on Extending Database Technology

A2 - Guerrini , Giovanna

A2 - . Paton , Norman W.

PB - Association for Computing Machinery

Y2 - 18 March 2013 through 21 March 2013

ER -