Parallel Query Optimization: Exploiting Bushy and Pipeline Parallelism with Genetic Programs

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@TechReport{stillger:1996:tr,

• author = "Michael Stillger and Myra Spiliopoulou and Johann-Christoph Freytag",
• title = "Parallel Query Optimization: Exploiting Bushy and Pipeline Parallelism with Genetic Programs",
• institution = "DBIS, Humboldt University",
• year = "1996",
• type = "Technical Report",
• number = "HUB-IB-65",
• address = "Berlin, Germany",
• month = jun,
• keywords = "genetic algorithms, genetic programming",
• URL = "http://www.dbis.informatik.hu-berlin.de/fileadmin/research/papers/techreports/1996-hub_ib_65-stillger.ps.gz",
• URL = "http://citeseer.ist.psu.edu/stillger96parallel.html",
• abstract = "Parallel query optimization is one of the hardest problems in the databases area. The various cost models reflecting the query execution parameters determine the structure and size of the solutions space. To explore this space, research has turned towards combinatorial optimization techniques, heuristics and genetic algorithms, which have been primarily studied for sequential query processing. In this study, we propose a genetic programming strategy for the optimization of parallel bushy query execution plans. Genetic programming has evolved from genetic algorithms, and is more flexible and expressive. We consider two cost functions modelling different modes of interoperator parallelism. We analyse the behaviour of the search strategy and observe that it is affected by the cost function. Despite this, our experiments show that our strategy converges to optimal plans of very good quality, and performs best when bushy interoperator parallelism is exploited.",
• size = "33 pages",

}

Genetic Programming entries for Michael Stillger Myra Spiliopoulou Johann-Christoph Freytag

Citations