Early Grouping Gets the Skew

Helmer, Sven ; Neumann, Thomas ; Moerkotte, Guido

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URL: https://ub-madoc.bib.uni-mannheim.de/745
URN: urn:nbn:de:bsz:180-madoc-7457
Document Type: Working paper
Year of publication: 2002
The title of a journal, publication series: Technical Reports
Volume: 02-009
Place of publication: Mannheim
Publication language: English
Institution: School of Business Informatics and Mathematics > Sonstige - Fakultät für Wirtschaftsinformatik und Wirtschaftsmathematik
MADOC publication series: Veröffentlichungen der Fakultät für Mathematik und Informatik > Institut für Informatik > Technical Reports
Subject: 004 Computer science, internet
Subject headings (SWD): Abfrageverarbeitung , Aggregation
Keywords (English): databases , query optimization , aggregation
Abstract: We propose a new algorithm for external grouping with large results. Our approach handles skewed data gracefully and lowers the amount of random IO on disk considerably. Contrary to existing grouping algorithms, our new algorithm does not require the optimizer to employ complicated or error-prone procedures adjusting the parameters prior to query plan execution. We implemented several variants of our algorithm as well as the most commonly used algorithms for grouping and carried out extensive experiments on both synthetic and real data. The results of these experiments reveal the dominance of our approach. In case of heavily skewed data we outperform the other algorithms by a factor of two.

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