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

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@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