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Advances in Databases: 19th British National Conference on by Richard Hull, Bharat Kumar, Arnaud Sahuguet, Ming Xiong PDF

By Richard Hull, Bharat Kumar, Arnaud Sahuguet, Ming Xiong (auth.), Barry Eaglestone, Siobhán North, Alexandra Poulovassilis (eds.)

ISBN-10: 3540439056

ISBN-13: 9783540439059

This booklet constitutes the refereed court cases of the nineteenth British nationwide convention on Databases, BNCOD 2002, held in Sheffield, united kingdom, in July 2002.
The 10 revised complete papers and nine posters offered including one invited paper have been conscientiously reviewed and chosen for inclusion within the quantity. The booklet bargains topical sections on question processing, information warehousing and knowledge mining, caliber and integrity, and net and dispensed databases.

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Bouganim, F. Fabret, C. Mohan, and P. Valduriez. A dynamic query processing architecture for data integration systems. IEEE Data Engineering Bulletin, 23(2):42–48, 2000. 7. L. Bouganim, F. Fabret, C. Mohan, and P. Valduriez. Dynamic query scheduling in data integration systems. In Proc. of ICDE 2000, pages 425–434, 2000. 8. I. Foster and C. Kesselman. The Grid: Blueprint for a New Computing Infrastructure. , 1999. 9. P. Haas and J. Hellerstein. Ripple joins for online aggregation. In Proc. of ACM SIGMOD 1999, pages 287–298, 1999.

This can be achieved by modifying the construction of r AB to keep counts. The significant issue is then sharpened: how to rewrite queries to use the counts. 2. Investigate extending Technique I to push selections and projections into the decomposition. 3. Investigate the use of other decompositions. A natural candidate is a decomposition induced by approximate multi-valued dependencies, which creates two correction relations r+ , r− . 4. Investigate methods for maintaining an HV decomposition.

In the rate-based pipeline scheduling algorithm, all result tuples have the same importance. The algorithm maximises the result output rate by prioritising and scheduling the flow of data across pipelined operators. Characteristics of the operators, such as cost and productivity, can be dynamically changed (due to blocked inputs, finished operators, etc). Productivity differs from selectivity in that selectivity describes how many tuples will eventually be produced, whereas productivity describes how many tuples will be produced at that point in the execution [25].

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Advances in Databases: 19th British National Conference on Databases, BNCOD 19 Sheffield, UK, July 17–19, 2002 Proceedings by Richard Hull, Bharat Kumar, Arnaud Sahuguet, Ming Xiong (auth.), Barry Eaglestone, Siobhán North, Alexandra Poulovassilis (eds.)


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