Parallelizing multidimensional index structures

K. V Ravi Kanth, Divyakant Agrawal, Amr El Abbadi, Ambuj Singh, Terence R. Smith

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Indexing multidimensional data is inherently complex leading to slow query processing. This behavior becomes more pronounced with the increase in database size and/or number of dimensions. In this paper, we address this issue by processing an index structure in parallel. First, we study different ways of partitioning an index structure. We then propose efficient algorithms for processing each query in parallel on the index structure. Using these strategies, we parallelized two multidimensional index structures - R* and LIB and evaluated the performance gains for the Gazetteer and the Catalog data of the Alexandria Digital Library on the Meiko CS-2.

Original languageEnglish
Title of host publicationIEEE Symposium on Parallel and Distributed Processing - Proceedings
Editors Anon
PublisherIEEE
Pages376-383
Number of pages8
Publication statusPublished - 1996
Externally publishedYes
EventProceedings of the 1996 8th IEEE Symposium on Parallel and Distributed Processing - New Orleans, LA, USA
Duration: 23 Oct 199626 Oct 1996

Other

OtherProceedings of the 1996 8th IEEE Symposium on Parallel and Distributed Processing
CityNew Orleans, LA, USA
Period23/10/9626/10/96

Fingerprint

Query processing
Digital libraries
Processing

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Kanth, K. V. R., Agrawal, D., El Abbadi, A., Singh, A., & Smith, T. R. (1996). Parallelizing multidimensional index structures. In Anon (Ed.), IEEE Symposium on Parallel and Distributed Processing - Proceedings (pp. 376-383). IEEE.

Parallelizing multidimensional index structures. / Kanth, K. V Ravi; Agrawal, Divyakant; El Abbadi, Amr; Singh, Ambuj; Smith, Terence R.

IEEE Symposium on Parallel and Distributed Processing - Proceedings. ed. / Anon. IEEE, 1996. p. 376-383.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kanth, KVR, Agrawal, D, El Abbadi, A, Singh, A & Smith, TR 1996, Parallelizing multidimensional index structures. in Anon (ed.), IEEE Symposium on Parallel and Distributed Processing - Proceedings. IEEE, pp. 376-383, Proceedings of the 1996 8th IEEE Symposium on Parallel and Distributed Processing, New Orleans, LA, USA, 23/10/96.
Kanth KVR, Agrawal D, El Abbadi A, Singh A, Smith TR. Parallelizing multidimensional index structures. In Anon, editor, IEEE Symposium on Parallel and Distributed Processing - Proceedings. IEEE. 1996. p. 376-383
Kanth, K. V Ravi ; Agrawal, Divyakant ; El Abbadi, Amr ; Singh, Ambuj ; Smith, Terence R. / Parallelizing multidimensional index structures. IEEE Symposium on Parallel and Distributed Processing - Proceedings. editor / Anon. IEEE, 1996. pp. 376-383
@inproceedings{fd0ac59239284b688daa6c8ff47b04da,
title = "Parallelizing multidimensional index structures",
abstract = "Indexing multidimensional data is inherently complex leading to slow query processing. This behavior becomes more pronounced with the increase in database size and/or number of dimensions. In this paper, we address this issue by processing an index structure in parallel. First, we study different ways of partitioning an index structure. We then propose efficient algorithms for processing each query in parallel on the index structure. Using these strategies, we parallelized two multidimensional index structures - R* and LIB and evaluated the performance gains for the Gazetteer and the Catalog data of the Alexandria Digital Library on the Meiko CS-2.",
author = "Kanth, {K. V Ravi} and Divyakant Agrawal and {El Abbadi}, Amr and Ambuj Singh and Smith, {Terence R.}",
year = "1996",
language = "English",
pages = "376--383",
editor = "Anon",
booktitle = "IEEE Symposium on Parallel and Distributed Processing - Proceedings",
publisher = "IEEE",

}

TY - GEN

T1 - Parallelizing multidimensional index structures

AU - Kanth, K. V Ravi

AU - Agrawal, Divyakant

AU - El Abbadi, Amr

AU - Singh, Ambuj

AU - Smith, Terence R.

PY - 1996

Y1 - 1996

N2 - Indexing multidimensional data is inherently complex leading to slow query processing. This behavior becomes more pronounced with the increase in database size and/or number of dimensions. In this paper, we address this issue by processing an index structure in parallel. First, we study different ways of partitioning an index structure. We then propose efficient algorithms for processing each query in parallel on the index structure. Using these strategies, we parallelized two multidimensional index structures - R* and LIB and evaluated the performance gains for the Gazetteer and the Catalog data of the Alexandria Digital Library on the Meiko CS-2.

AB - Indexing multidimensional data is inherently complex leading to slow query processing. This behavior becomes more pronounced with the increase in database size and/or number of dimensions. In this paper, we address this issue by processing an index structure in parallel. First, we study different ways of partitioning an index structure. We then propose efficient algorithms for processing each query in parallel on the index structure. Using these strategies, we parallelized two multidimensional index structures - R* and LIB and evaluated the performance gains for the Gazetteer and the Catalog data of the Alexandria Digital Library on the Meiko CS-2.

UR - http://www.scopus.com/inward/record.url?scp=0030417835&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0030417835&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0030417835

SP - 376

EP - 383

BT - IEEE Symposium on Parallel and Distributed Processing - Proceedings

A2 - Anon, null

PB - IEEE

ER -