Pessimistic Cardinality Estimation

Fuente: arXiv
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Auteurs principaux: Khamis, Mahmoud Abo, Deeds, Kyle, Olteanu, Dan, Suciu, Dan
Format: Preprint
Publié: 2024
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author Khamis, Mahmoud Abo
Deeds, Kyle
Olteanu, Dan
Suciu, Dan
author_facet Khamis, Mahmoud Abo
Deeds, Kyle
Olteanu, Dan
Suciu, Dan
contents Cardinality Estimation is to estimate the size of the output of a query without computing it, by using only statistics on the input relations. Existing estimators try to return an unbiased estimate of the cardinality: this is notoriously difficult. A new class of estimators have been proposed recently, called "pessimistic estimators", which compute a guaranteed upper bound on the query output. Two recent advances have made pessimistic estimators practical. The first is the recent observation that degree sequences of the input relations can be used to compute query upper bounds. The second is a long line of theoretical results that have developed the use of information theoretic inequalities for query upper bounds. This paper is a short overview of pessimistic cardinality estimators, contrasting them with traditional estimators.
format Preprint
id arxiv_https___arxiv_org_abs_2412_00642
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Pessimistic Cardinality Estimation
Khamis, Mahmoud Abo
Deeds, Kyle
Olteanu, Dan
Suciu, Dan
Databases
Information Theory
Cardinality Estimation is to estimate the size of the output of a query without computing it, by using only statistics on the input relations. Existing estimators try to return an unbiased estimate of the cardinality: this is notoriously difficult. A new class of estimators have been proposed recently, called "pessimistic estimators", which compute a guaranteed upper bound on the query output. Two recent advances have made pessimistic estimators practical. The first is the recent observation that degree sequences of the input relations can be used to compute query upper bounds. The second is a long line of theoretical results that have developed the use of information theoretic inequalities for query upper bounds. This paper is a short overview of pessimistic cardinality estimators, contrasting them with traditional estimators.
title Pessimistic Cardinality Estimation
topic Databases
Information Theory
url https://arxiv.org/abs/2412.00642