Join query optimization in the distributed database system using an artificial bee colony algorithm and genetic operators

As the main factor in the distributed database systems, query optimization is aimed at finding an optimal execution plan to reduce the runtime. In such systems, because of the repeated relations on various sites, the query optimization is very challenging. Moreover, the query optimization issue with large‐scale distributed databases is an NP‐hard problem. Therefore, in this paper, an Artificial Bee Colony Algorithm based on Genetic Operators (ABC‐GO) is proposed to find a solution to join the query optimization problems in the distributed database systems. The ABC algorithm has the global–local search capabilities and genetic operators to create new candidate solutions for improving the performance of the ABC algorithm. The obtained results have shown that the cost of the query evaluation is minimized and the quality of Top‐K query plans is improved for a given distributed query. Moreover, this method decreases the overhead. However, it needs a longer execution time.

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