Abstract
Join query optimization has a direct impact on the performance of a database system. This work presents an evolutionary multi-agent system applied to the join ordering problem related to database query planning. The proposed algorithm was implemented and embedded in the core of a database management system (DBMS). Parameters of the algorithm were calibrated by means of a factorial design and an analysis based on the variance. The algorithm was compared with the official query planner of the H2 DBMS, using a methodology based on benchmark tests. The results show that the proposed evolutionary multi-agent system was able to generate solutions associated with low execution costs in the majority of the cases.
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