Progressive processing of subspace dominating queries

Progressive processing of subspace dominating queries A top- k dominating query reports the k items with the highest domination score. Algorithms for efficient processing of this query have been recently proposed in the literature. Those methods, either index based or index free, apply a series of pruning criteria toward efficient processing. However, they are characterized by several limitations, such as (1) they lack progressiveness (they report the k best items at the end of the processing), (2) they require a multi-dimensional index or they build a grid-based index on-the-fly, which suffers from performance degradation, especially in high dimensionalities, and (3) they do not support vertically decomposed data. In this paper, we design efficient algorithms that can handle any subset of the dimensions in a progressive manner. Among the studied algorithms, the Differential Algorithm shows the best overall performance. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

Progressive processing of subspace dominating queries

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Publisher
Springer Journals
Copyright
Copyright © 2011 by Springer-Verlag
Subject
Computer Science; Database Management
ISSN
1066-8888
eISSN
0949-877X
D.O.I.
10.1007/s00778-011-0231-0
Publisher site
See Article on Publisher Site

Abstract

A top- k dominating query reports the k items with the highest domination score. Algorithms for efficient processing of this query have been recently proposed in the literature. Those methods, either index based or index free, apply a series of pruning criteria toward efficient processing. However, they are characterized by several limitations, such as (1) they lack progressiveness (they report the k best items at the end of the processing), (2) they require a multi-dimensional index or they build a grid-based index on-the-fly, which suffers from performance degradation, especially in high dimensionalities, and (3) they do not support vertically decomposed data. In this paper, we design efficient algorithms that can handle any subset of the dimensions in a progressive manner. Among the studied algorithms, the Differential Algorithm shows the best overall performance.

Journal

The VLDB JournalSpringer Journals

Published: Dec 1, 2011

References

  • Breaking the Memory Wall in MonetDB
    Boncz, P.A.; Kersten, M.L.; Manegold, S.

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