Efficient disk allocation for fast similarity searching

S. Prabhakar, D. Agrawal, A. El Abbadi

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

16 Citations (Scopus)

Abstract

As databases increasingly integrate non-textual information it is becoming necessary to support efficient similarity searching in addition to range searching. Recently, declustering techniques have been proposed for improving the performance of similarity searches through parallel I/O. In this paper, we propose a new scheme which provides good declustering for similarity searching. In particular, it does global declustering as opposed to local declustering, exploits the availability of extra disks and does not limit the partitioning of the data space. Our technique is based upon the Cyclic declustering schemes which were developed for range and partial match queries. We establish, in general, that Cyclic declustering techniques outperform previously proposed techniques.

Original languageEnglish
Title of host publicationAnnual ACM Symposium on Parallel Algorithms and Architectures
Place of PublicationNew York, NY, United States
PublisherACM
Pages78-87
Number of pages10
Publication statusPublished - 1 Jan 1998
Externally publishedYes
EventProceedings of the 1998 10th Annual ACM Symposium on Parallel Algorithms and Architectures, SPAA - Puerto Vallarta, Mexico
Duration: 28 Jun 19982 Jul 1998

Other

OtherProceedings of the 1998 10th Annual ACM Symposium on Parallel Algorithms and Architectures, SPAA
CityPuerto Vallarta, Mexico
Period28/6/982/7/98

Fingerprint

Availability

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality

Cite this

Prabhakar, S., Agrawal, D., & El Abbadi, A. (1998). Efficient disk allocation for fast similarity searching. In Annual ACM Symposium on Parallel Algorithms and Architectures (pp. 78-87). New York, NY, United States: ACM.

Efficient disk allocation for fast similarity searching. / Prabhakar, S.; Agrawal, D.; El Abbadi, A.

Annual ACM Symposium on Parallel Algorithms and Architectures. New York, NY, United States : ACM, 1998. p. 78-87.

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

Prabhakar, S, Agrawal, D & El Abbadi, A 1998, Efficient disk allocation for fast similarity searching. in Annual ACM Symposium on Parallel Algorithms and Architectures. ACM, New York, NY, United States, pp. 78-87, Proceedings of the 1998 10th Annual ACM Symposium on Parallel Algorithms and Architectures, SPAA, Puerto Vallarta, Mexico, 28/6/98.
Prabhakar S, Agrawal D, El Abbadi A. Efficient disk allocation for fast similarity searching. In Annual ACM Symposium on Parallel Algorithms and Architectures. New York, NY, United States: ACM. 1998. p. 78-87
Prabhakar, S. ; Agrawal, D. ; El Abbadi, A. / Efficient disk allocation for fast similarity searching. Annual ACM Symposium on Parallel Algorithms and Architectures. New York, NY, United States : ACM, 1998. pp. 78-87
@inproceedings{3e090b2c3569454584ca41ce99db405d,
title = "Efficient disk allocation for fast similarity searching",
abstract = "As databases increasingly integrate non-textual information it is becoming necessary to support efficient similarity searching in addition to range searching. Recently, declustering techniques have been proposed for improving the performance of similarity searches through parallel I/O. In this paper, we propose a new scheme which provides good declustering for similarity searching. In particular, it does global declustering as opposed to local declustering, exploits the availability of extra disks and does not limit the partitioning of the data space. Our technique is based upon the Cyclic declustering schemes which were developed for range and partial match queries. We establish, in general, that Cyclic declustering techniques outperform previously proposed techniques.",
author = "S. Prabhakar and D. Agrawal and {El Abbadi}, A.",
year = "1998",
month = "1",
day = "1",
language = "English",
pages = "78--87",
booktitle = "Annual ACM Symposium on Parallel Algorithms and Architectures",
publisher = "ACM",

}

TY - GEN

T1 - Efficient disk allocation for fast similarity searching

AU - Prabhakar, S.

AU - Agrawal, D.

AU - El Abbadi, A.

PY - 1998/1/1

Y1 - 1998/1/1

N2 - As databases increasingly integrate non-textual information it is becoming necessary to support efficient similarity searching in addition to range searching. Recently, declustering techniques have been proposed for improving the performance of similarity searches through parallel I/O. In this paper, we propose a new scheme which provides good declustering for similarity searching. In particular, it does global declustering as opposed to local declustering, exploits the availability of extra disks and does not limit the partitioning of the data space. Our technique is based upon the Cyclic declustering schemes which were developed for range and partial match queries. We establish, in general, that Cyclic declustering techniques outperform previously proposed techniques.

AB - As databases increasingly integrate non-textual information it is becoming necessary to support efficient similarity searching in addition to range searching. Recently, declustering techniques have been proposed for improving the performance of similarity searches through parallel I/O. In this paper, we propose a new scheme which provides good declustering for similarity searching. In particular, it does global declustering as opposed to local declustering, exploits the availability of extra disks and does not limit the partitioning of the data space. Our technique is based upon the Cyclic declustering schemes which were developed for range and partial match queries. We establish, in general, that Cyclic declustering techniques outperform previously proposed techniques.

UR - http://www.scopus.com/inward/record.url?scp=0031622612&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031622612&partnerID=8YFLogxK

M3 - Conference contribution

SP - 78

EP - 87

BT - Annual ACM Symposium on Parallel Algorithms and Architectures

PB - ACM

CY - New York, NY, United States

ER -