Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/handle/123456789/4388
Title: Query join ordering optimization with evolutionary multi-agent systems.
Authors: Gonçalves, Frederico Augusto de Cezar Almeida
Guimarães, Frederico Gadelha
Souza, Marcone Jamilson Freitas
Keywords: Join ordering problem
Query optimization
Multi-agent system
Evolutionary algorithm
Heuristics
Issue Date: 2014
Citation: GONÇALVES, F. A. C. A.; GUIMARÃES, F. G.; SOUZA, M. J. F. Query join ordering optimization with evolutionary multi-agent systems. Expert Systems with Applications, v. 41, p. 6934-6944, 2014. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0957417414002760#> Acesso em: 23 jan. 2015.
Abstract: This work presents an evolutionary multi-agent system applied to the query optimization phase of Relational Database Management Systems (RDBMS) in a non-distributed environment. The query optimization phase deals with a known problem called query join ordering, which has a direct impact on the performance of such systems. The proposed optimizer was programmed in the optimization core of the H2 Database Engine. The experimental section was designed according to a factorial design of fixed effects and the analysis based on the Permutations Test for an Analysis of Variance Design. The evaluation methodology is based on synthetic benchmarks and the tests are divided into three different experiments: calibration of the algorithm, validation with an exhaustive method and a general comparison with different database systems, namely Apache Derby, HSQLDB and PostgreSQL. The results show that the proposed evolutionary multi-agent system was able to generate solutions associated with lower cost plans and faster execution times in the majority of the cases.
URI: http://www.repositorio.ufop.br/handle/123456789/4388
ISSN: 09574174
metadata.dc.rights.license: O Periódico Expert Systems with Applications concede permissão para depósito do artigo no Repositório Institucional da UFOP. Número da licença: 3553111246763.
Appears in Collections:DECOM - Artigos publicados em periódicos

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