Optimizing Large Join Queries in Mediation Systems

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Optimizing Large Join Queries in Mediation Systems (1999)

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by Ramana Yerneni , Chen Li , Jeffrey Ullman , Hector Garcia-molina

Venue:	International Conference on Database Theory (ICDT
Citations:	40 - 11 self

BibTeX

@INPROCEEDINGS{Yerneni99optimizinglarge,
    author = {Ramana Yerneni and Chen Li and Jeffrey Ullman and Hector Garcia-molina},
    title = {Optimizing Large Join Queries in Mediation Systems},
    booktitle = {International Conference on Database Theory (ICDT},
    year = {1999},
    pages = {348--364}
}

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Abstract

. 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 mor...

Keyphrases

mediation system large join query optimal plan case performance linear bound attribute-binding adornment first algorithm limited query capability simple cost model conjunctive query source query mediator system simple greedy strategy source capability partitioning scheme major cost efficient query plan heterogeneous environment data integration system data source second algorithm generates optimal plan mediator need

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