2013/11/16 by Adel Alinezhad Kolaei, Kolaei, Adel Alinezhad, Marzieh Ahmadzadeh +1
Computer Science · #Advanced Database Systems and Queries #Data Management and Algorithms #Databases (cs.DB) #FOS: Computer and information sciences #Metaheuristic Optimization Algorithms Research #Neural and Evolutionary Computing (cs.NE) #cs.DB #cs.NE
paper · pdf · doi:10.48550/arxiv.1311.4088
arxiv created 2013/11/16 · openalex publication_date 2013/11/16 · arxiv updated 2013/11/19 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
The issue of optimizing queries is a cost-sensitive process and with respect to the number of associated tables in a query, its number of permutations grows exponentially. On one hand, in comparison with other operators in relational database, join operator is the most difficult and complicated one in terms of optimization for reducing its runtime. Accordingly, various algorithms have so far been proposed to solve this problem. On the other hand, the success of any database management system (DBMS) means exploiting the query model. In the current paper, the heuristic ant algorithm has been proposed to solve this problem and improve the runtime of join operation. Experiments and observed results reveal the efficiency of this algorithm compared to its similar algorithms.