Soft and Constrained Hypertree Width

Fuente: arXiv
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Main Authors: Lanzinger, Matthias, Okulmus, Cem, Pichler, Reinhard, Selzer, Alexander, Gottlob, Georg
Format: Preprint
Published: 2024
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author Lanzinger, Matthias
Okulmus, Cem
Pichler, Reinhard
Selzer, Alexander
Gottlob, Georg
author_facet Lanzinger, Matthias
Okulmus, Cem
Pichler, Reinhard
Selzer, Alexander
Gottlob, Georg
contents Hypertree decompositions provide a way to evaluate Conjunctive Queries (CQs) in polynomial time, where the exponent of this polynomial is determined by the width of the decomposition. In theory, the goal of efficient CQ evaluation therefore has to be a minimisation of the width. However, in practical settings, it turns out that there are also other properties of a decomposition that influence the performance of query evaluation. It is therefore of interest to restrict the computation of decompositions by constraints and to guide this computation by preferences. To this end, we propose a novel framework based on candidate tree decompositions, which allows us to introduce soft hypertree width (shw). This width measure is a relaxation of hypertree width (hw); it is never greater than hw and, in some cases, shw may actually be lower than hw. Most importantly, shw preserves the tractability of deciding if a given CQ is below some fixed bound, while offering more algorithmic flexibility. In particular, it provides a natural way to incorporate preferences and constraints into the computation of decompositions. A prototype implementation and preliminary experiments confirm that this novel framework can indeed have a practical impact on query evaluation.
format Preprint
id arxiv_https___arxiv_org_abs_2412_11669
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Soft and Constrained Hypertree Width
Lanzinger, Matthias
Okulmus, Cem
Pichler, Reinhard
Selzer, Alexander
Gottlob, Georg
Databases
Hypertree decompositions provide a way to evaluate Conjunctive Queries (CQs) in polynomial time, where the exponent of this polynomial is determined by the width of the decomposition. In theory, the goal of efficient CQ evaluation therefore has to be a minimisation of the width. However, in practical settings, it turns out that there are also other properties of a decomposition that influence the performance of query evaluation. It is therefore of interest to restrict the computation of decompositions by constraints and to guide this computation by preferences. To this end, we propose a novel framework based on candidate tree decompositions, which allows us to introduce soft hypertree width (shw). This width measure is a relaxation of hypertree width (hw); it is never greater than hw and, in some cases, shw may actually be lower than hw. Most importantly, shw preserves the tractability of deciding if a given CQ is below some fixed bound, while offering more algorithmic flexibility. In particular, it provides a natural way to incorporate preferences and constraints into the computation of decompositions. A prototype implementation and preliminary experiments confirm that this novel framework can indeed have a practical impact on query evaluation.
title Soft and Constrained Hypertree Width
topic Databases
url https://arxiv.org/abs/2412.11669