Algorithms for Computing Inequality Joins

Brahma Dathan, Stefan Trausan Matu

Abstract

Although the problem of joins has been known ever since the concept of relational databases was introduced, much of the research in that area has addressed the question of equijoins. In this paper, we look at the problem of inequality joins, which compares attributes using operators other than equality. We develop an algorithm for computing inequality joins on two relations with comparisons on two pairs of attributes and then extend the work to queries involving more than two comparisons. Our work also derives a lower bound for inequality joins on two relations and show that the two-comparisons algorithm is optimal.

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Paper Citation


in Harvard Style

Dathan B. (2018). Algorithms for Computing Inequality Joins.In Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-318-6, pages 357-364. DOI: 10.5220/0006826803570364


in Bibtex Style

@conference{data18,
author={Brahma Dathan},
title={Algorithms for Computing Inequality Joins},
booktitle={Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2018},
pages={357-364},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006826803570364},
isbn={978-989-758-318-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Algorithms for Computing Inequality Joins
SN - 978-989-758-318-6
AU - Dathan B.
PY - 2018
SP - 357
EP - 364
DO - 10.5220/0006826803570364