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An Adaptive Query Execution System for Data Integration (1999)
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BibTeX
@INPROCEEDINGS{Ives99anadaptive,
author = {Zachary Ives and Daniela Florescu and Inria Roquencourt and Marc Friedman and Alon Levy and Daniel Weld},
title = {An Adaptive Query Execution System for Data Integration},
booktitle = {},
year = {1999},
pages = {299--310}
}
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Abstract
Query processing in data integration occurs over networkbound, autonomous data sources. This requires extensions to traditional optimization and execution techniques for three reasons: there is an absence of quality statistics about the data, data transfer rates are unpredictable and bursty, and slow or unavailable data sources can often be replaced by overlapping or mirrored sources. This paper presents the Tukwila data integration system, designed to support adaptivity at its core using a two-pronged approach. Interleaved planning and execution with partial optimization allows Tukwila to quickly recover from decisions based on inaccurate estimates. During execution, Tukwila uses adaptive query operators such as the double pipelined hash join, which produces answers quickly, and the dynamic collector, which robustly and efficiently computes unions across overlapping data sources. We demonstrate that the Tukwila architecture extends previous innovations in adaptive execution (such as...
Keyphrases
data integration adaptive query execution system data transfer rate data source tukwila architecture execution technique hash join partial optimization tukwila data integration system previous innovation computes union adaptive execution dynamic collector autonomous data source quality statistic adaptive query operator unavailable data source inaccurate estimate two-pronged approach traditional optimization query processing
