A selectivity model for fragmented relations in information retrieval

H.E. Blok, R.S. Choenni, Henk Blanken, Peter M.G. Apers

Research output: Book/ReportReportAcademic

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New application domains cause todays database sizes to grow rapidly, posing great demands on technology. Data fragmentation facilitates techniques (like distribution, parallelization, and main-memory computing) meeting these demands. Also, fragmentation might help improving effcient processing of query types such as top N. Database design and query optimization require a good notion of the costs resulting from a certain fragmentation. Our mathematically derived selectivity model facilitates this. Once its two parameters have been computed based on the fragmentation, after each (though usually infrequent) update, our model can forget the data distribution, resulting in fast and quite good selectivity estimation. We show experimental verification for Zipfian distributed IR databases.
Original languageEnglish
PublisherCentre for Telematics and Information Technology (CTIT)
Number of pages10
Publication statusPublished - Jan 2001

Publication series

NameCTIT Technical Report Series
ISSN (Print)1381-3625


  • EWI-5933
  • METIS-202661
  • IR-36661


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