Declustering large multidimensional data sets for range queries over heterogeneous disks

  • Jonghyun Lee
  • , M. Winslett
  • , Xiaosong Ma
  • , Shengke Yu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Declustering is a technique to distribute data sets over multiple disks so that future retrievals can be well balanced over the disks and be performed in parallel. Although clusters often have heterogeneous disks, most declustering work has focused only on homogeneous environments. In this work, we investigate the declustering problem for a heterogeneous disk environment using virtual servers, and propose approaches for deciding the number of virtual servers and the mapping between virtual servers and physical disks. Our experimental results show that by combining our algorithm for choosing the number of virtual servers with a greedy algorithm for mapping virtual servers to disks, users can expect range query retrieval performance within 4% of the optimum achievable in practice on average, in all configurations studied. Compared to an intuitively natural approach to the problem, this represents an improvement of 8-31% in average fetch ratio, as well a 26-38% reduction in the standard deviation of performance for small queries.

Original languageEnglish
Title of host publication15th International Conference on Scientific and Statistical Database Management, SSDBM 2003
EditorsSilvia Nittel, Dimitrios Gunopulos
PublisherIEEE Computer Society
Pages212-221
Number of pages10
ISBN (Electronic)0769519644
DOIs
Publication statusPublished - 2003
Externally publishedYes
Event15th International Conference on Scientific and Statistical Database Management, SSDBM 2003 - Cambridge, United States
Duration: 9 Jul 200311 Jul 2003

Publication series

NameProceedings of the International Conference on Scientific and Statistical Database Management, SSDBM
Volume2003-January
ISSN (Print)1099-3371

Conference

Conference15th International Conference on Scientific and Statistical Database Management, SSDBM 2003
Country/TerritoryUnited States
CityCambridge
Period9/07/0311/07/03

Keywords

  • Aggregates
  • Bandwidth
  • Computer science
  • Data visualization
  • Databases
  • Greedy algorithms
  • Image retrieval
  • Information retrieval
  • Multidimensional systems
  • Throughput

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