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Orthogonal range queries in OLAP

Chung Keung Poon

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

We study the problem of pre-computing auxillary information to support on-line range queries for the sum and max functions on a datacube. For a d-dimensional datacube with size n in each dimension, we propose a data structure for range max queries with O((4L)d) query time and O((12L2n1/Lγ(n))d) update time where Lε{1,….,log n} is a user-controlled parameter and Y(n) is a slow-growing function. (For example, γ(n) ≤log* n and γ(24110) = 3.) The data structure uses O((6nγ(n))d) storage and can be initialized in time linear to its size. There are three major techniques employed in designing the data structure, namely, a technique for trading query and update times, a technique for trading query time and storage and a technique for extending 1-dimensional data structures to d-dimensional ones. Our techniques are also applicable to range queries over any semi-group and group operation, such as min, sum and count. © Springer-Verlag Berlin Heidelberg 2001
Original languageEnglish
Title of host publicationDatabase Theory - ICDT 2001 - 8th International Conference, Proceedings
PublisherSpringer Verlag
Pages361-374
Volume1973
ISBN (Print)9783540414568
DOIs
Publication statusPublished - 2001
Event8th International Conference on Database Theory, ICDT 2001 - London, United Kingdom
Duration: 4 Jan 20016 Jan 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1973
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Database Theory, ICDT 2001
PlaceUnited Kingdom
CityLondon
Period4/01/016/01/01

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This research was fully supported by a grant from the Research Grants Council of the Hong Kong SAR, China [Project No. 9040314 (RGC Ref. No. CityU 1159/97E)].

RGC Funding Information

  • RGC-funded

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