research-article

Worst-Case Optimal Join Algorithms: Techniques, Results, and Open Problems

Author:

Hung Q. NgoAuthors Info & Claims

SIGMOD/PODS '18: Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

Pages 111 - 124

https://doi.org/10.1145/3196959.3196990

Published: 27 May 2018 Publication History

Abstract

Worst-case optimal join algorithms are the class of join algorithms whose runtime match the worst-case output size of a given join query. While the first provably worse-case optimal join algorithm was discovered relatively recently, the techniques and results surrounding these algorithms grow out of decades of research from a wide range of areas, intimately connecting graph theory, algorithms, information theory, constraint satisfaction, database theory, and geometric inequalities. These ideas are not just paperware: in addition to academic project implementations, two variations of such algorithms are the work-horse join algorithms of commercial database and data analytics engines. This paper aims to be a brief introduction to the design and analysis of worst-case optimal join algorithms. We discuss the key techniques for proving runtime and output size bounds. We particularly focus on the fascinating connection between join algorithms and information theoretic inequalities, and the idea of how one can turn a proof into an algorithm. Finally, we conclude with a representative list of fundamental open problems in this area.

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Worst-Case Optimal Join Algorithms: Techniques, Results, and Open Problems

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cover image ACM Conferences

PODS '18: Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

May 2018

462 pages

ISBN:9781450347068

DOI:10.1145/3196959

General Chair:
Jan Van den Bussche
Hasselt University
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Marcelo Arenas
Pontificia Universidad Católica de Chile

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