Join query optimisation in the distributed databases using a hybrid harmony search and artificial bee colony algorithm

摘要

The query optimiser is a vital part of any distributed database mechanism. Reducing the execution period of the query depends on reaching an ideal query execution plan. Due to this issue's NP-hard nature, a hybrid harmony search and an artificial bee colony algorithm can be useful. The harmony is used to call query plans and signify them by S-dimension real vectors. A harmony memory is a place for creating and storing a primary population of harmony vectors. Then, bees explore harmony memory as a food source. The production of a novel nominate harmony out of all query plans in the harmony memory requires a pitch adjustment principle, a memory consideration one, and a random re-initialisation. Lastly, the new candidate vector replaces the worst harmony vector when it works better. The simulation outcomes have indicated that the introduced method reduces the expenses of evaluating a query compared to the harmony search and bee colony optimisation algorithms. However, this method has a longer execution time.