Automata theory based approach to the join ordering problem in relational database systems

The join query optimization problem has been widely addressed in relational database management systems (RDBMS). The problem consists of finding a join order that minimizes the time required to execute a query. Many strategies have been implemented to solve this problem including deterministic algorithms, randomized algorithms, meta-heuristic algorithms and hybrid approaches. Such methodologies deeply depend on the correct configuration of various input parameters. In this paper, a meta-heuristic approach based on the automata theory will be adapted to solve the join-ordering problem. The proposed method requires a single input parameter that facilitates its usage respect to those previously described in the literature. The algorithm was embedded into PostgreSQL and compared with the genetic competitor using the most resent TPC-DS benchmark. The proposed method is supported by experimental results achieving up to 30% faster response time than GEQO in different queries.