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Join queries optimization in the distributed databases using a hybrid multi-objective algorithm
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DOI：10.1007/s10586-021-03451-9.png)
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Abstract
En 中文
In the distributed database systems, the relations needed by a query can be kept in several locations. This process significantly increases potential corresponding Query Execution Plans (QEP's);
a user query. Hence;
th, in addition to the expense of local computing, the charge of transferring data between different cloud sites should also be considered. It does not sound logical to investigate all potential query plans in a high setting like this. The best query plan (regarding cost) must be generated;
processing a given query. A new hybrid multi-objective genetic and bat algorithm, a Multi-Objective Genetic Algorithm with BAT (MOGABAT), is used in the present article to produce the best query plans. The functionality comparison is made on different join graph structures, among MOGABAT, Multi-Objective BAT (MOBAT), and Non-dominated Sorting Genetic Algorithm II (NSGA-II). The obtained results have shown that the quality of generated query plans is enhanced;
the join graph structures. Nevertheless, more execution time is needed.
Keywords:
Distributed Query
Multi-Objective Optimization
MOBAT
Genetic Algorithm
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