Answering cooperative recursive queries in web federated databases

Mira Balaban, Nikolai Berezansky, Ehud Gudes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Evaluation of recursive queries and computing transitive closures require multiple accesses to the involved relations. In a federated database this leads to multiple accesses to the participants of the federation. Since the components are not uniform in terms of computation power, reliability, and communication delays, it might be desirable to minimize the number of accesses to the individual databases, and to maximize the size of the obtained answer with respect to time. Based on this observation, we developed cooperative query planning methods, termed Deep Federated Semi-Naive (DFSN), for computing the strong partial transitive closure of a relation. We have implemented and tested these algorithms in a real database environment. The experimental results show better performance of the DFSN methods over the conservative semi-naive approaches in that they produce large answer sets in time that is considerately shorter than the time needed by the conservative approaches.

Original languageEnglish
Title of host publicationNext Generation Information Technologies and Systems - 5th International Workshop, NGITS 2002, Proceedings
EditorsAlon Halevy, Avigdor Gal
PublisherSpringer Verlag
Number of pages15
ISBN (Electronic)354043819X, 9783540438199
StatePublished - 1 Jan 2002
Event5th International Workshop on Next Generation Information Technologies and Systems, NGITS 2002 - Caesarea, Israel
Duration: 24 Jun 200225 Jun 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference5th International Workshop on Next Generation Information Technologies and Systems, NGITS 2002

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


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