Parallel query optimization techniques for multi-join expressions based on genetic algorithm

Yang Cao*, Qiang Fang, Guo Ren Wang, Ge Yu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

The parallel query optimization for multi-join expressions is one of the key factors to improve the performance of database systems. An approach to solve the problems of the parallel query optimization for multi-join expressions by adopting GA algorithms is proposed. To improve the execution efficiency of the query processors, the authors exploit heuristic to seek the optimum parallel scheduling execution plan for multi-join expressions. The detailed testing results and performance analysis are presented. The experiment results show that the GA algorithm with heuristic knowledge is effective for parallel query processing of multi-joins, and plays an important role in improving the performance of database systems.

Original languageEnglish
Pages (from-to)250-257
Number of pages8
JournalRuan Jian Xue Bao/Journal of Software
Volume13
Issue number2
Publication statusPublished - Feb 2002
Externally publishedYes

Keywords

  • Genetic algorithm
  • Multi-join expression
  • Parallel scheduling
  • Query optimization

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