Optimizing Large Join Queries in Mediation Systems

  • Ramana Yerneni
  • Chen Li
  • Jeffrey Ullman
  • Hector Garcia-Molina
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1540)


In data integration systems, queries posed to a mediator need to be translated into a sequence of queries to the underlying data sources. In a heterogeneous environment, with sources of diverse and limited query capabilities, not all the translations are feasible. In this paper, we study the problem of finding feasible and efficient query plans for mediator systems. We consider conjunctive queries on mediators and model the source capabilities through attribute-binding adornments. We use a simple cost model that focuses on the major costs in mediation systems, those involved with sending queries to sources and getting answers back. Under this metric, we develop two algorithms for source query sequencing - one based on a simple greedy strategy and another based on a partitioning scheme. The first algorithm produces optimal plans in some scenarios, and we show a linear bound on its worst case performance when it misses optimal plans. The second algorithm generates optimal plans in more scenarios, while having no bound on the margin by which it misses the optimal plans. We also report on the results of the experiments that study the performance of the two algorithms.


Cost Model Vertex Cover Optimal Plan User Query Physical Plan 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Ramana Yerneni
    • 1
  • Chen Li
    • 1
  • Jeffrey Ullman
    • 1
  • Hector Garcia-Molina
    • 1
  1. 1.Stanford UniversityUSA

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