A Selectivity Model for Fragmented Relations: Applied in Information Retrieval

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

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
126 Downloads (Pure)


New application domains cause today's 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 to improve efficient processing of query types such as top {\rm{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 languageUndefined
Pages (from-to)635-639
Number of pages5
JournalIEEE transactions on knowledge and data engineering
Issue number5
Publication statusPublished - May 2004


  • METIS-221591
  • EWI-6257
  • IR-49347

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