Article

Achieving scalability in OLAP materialized view selection

Authors:

Thomas P. Nadeau,

Toby J. TeoreyAuthors Info & Claims

DOLAP '02: Proceedings of the 5th ACM international workshop on Data Warehousing and OLAP

Pages 28 - 34

https://doi.org/10.1145/583890.583895

Published: 08 November 2002 Publication History

Abstract

The goal of on-line analytical processing (OLAP) is to quickly answer queries from large amounts of data residing in a data warehouse. Materialized view selection is an optimization problem encountered in OLAP systems. Published work on the problem of materialized view selection presents solutions scalable in the number of possible views. However, the number of possible views is exponential relative to the number of database dimensions. A truly scalable solution must be polynomial time relative to the number of dimensions. We present such a solution, our Polynomial Greedy Algorithm. Complexity analysis proves scalability, and a performance study verifies the result. Empirical evidence demonstrates benefits close to existing algorithms. We conclude the Polynomial Greedy Algorithm functions effectively where existing algorithms fail dramatically.

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Cited By

Srivastava TFernandez R(2024)Saving Money for Analytical Workloads in the CloudProceedings of the VLDB Endowment10.14778/3681954.368201817:11(3524-3537)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.14778/3681954.3682018
Kumar AKumar T(2020)Materialized View Selection Using Self-Adaptive Perturbation Operator-Based Particle Swarm OptimizationInternational Journal of Applied Evolutionary Computation10.4018/ijaec.202007010411:3(50-67)Online publication date: Jul-2020
https://doi.org/10.4018/ijaec.2020070104
Gosain ASachdeva K(2020)Random Walk Grey Wolf Optimizer Algorithm for Materialized View Selection (RWGWOMVS)Novel Approaches to Information Systems Design10.4018/978-1-7998-2975-1.ch005(101-122)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-2975-1.ch005
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Index Terms

Achieving scalability in OLAP materialized view selection
1. Information systems
  1. Data management systems
    1. Database design and models
      1. Data model extensions

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cover image ACM Conferences

DOLAP '02: Proceedings of the 5th ACM international workshop on Data Warehousing and OLAP

November 2002

88 pages

ISBN:1581135904

DOI:10.1145/583890

General Chair:
Il-Yeol Song
Drexel University
,
Program Chair:
Dimitri Theodoratos
New Jersey Institute of Technology

Copyright © 2002 ACM.

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Published: 08 November 2002

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CIKM02

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CIKM02: Eleventh ACM International Conference on Information and Knowledge Management

November 8, 2002

Virginia, McLean, USA

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Overall Acceptance Rate 29 of 79 submissions, 37%

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Cited By

Srivastava TFernandez R(2024)Saving Money for Analytical Workloads in the CloudProceedings of the VLDB Endowment10.14778/3681954.368201817:11(3524-3537)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.14778/3681954.3682018
Kumar AKumar T(2020)Materialized View Selection Using Self-Adaptive Perturbation Operator-Based Particle Swarm OptimizationInternational Journal of Applied Evolutionary Computation10.4018/ijaec.202007010411:3(50-67)Online publication date: Jul-2020
https://doi.org/10.4018/ijaec.2020070104
Gosain ASachdeva K(2020)Random Walk Grey Wolf Optimizer Algorithm for Materialized View Selection (RWGWOMVS)Novel Approaches to Information Systems Design10.4018/978-1-7998-2975-1.ch005(101-122)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-2975-1.ch005
Ordonez-Ante LVan Seghbroeck GWauters TVolckaert BDe Turck F(2020)A Workload-Driven Approach for View Selection in Large Dimensional DatasetsJournal of Network and Systems Management10.1007/s10922-020-09526-zOnline publication date: 14-Mar-2020
https://doi.org/10.1007/s10922-020-09526-z
Saedi A(2018)Solving View Selection Problem to Query Plan Using Meta Heuristic Methods2018 1st Annual International Conference on Information and Sciences (AiCIS)10.1109/AiCIS.2018.00025(70-76)Online publication date: Nov-2018
https://doi.org/10.1109/AiCIS.2018.00025
Arun BKumar T(2017)Materialized View Selection using Artificial Bee Colony OptimizationInternational Journal of Intelligent Information Technologies10.4018/IJIIT.201701010213:1(26-49)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.4018/IJIIT.2017010102
Kumar TArun B(2017)Materialized View Selection Using Bumble Bee Mating OptimizationInternational Journal of Decision Support System Technology10.4018/IJDSST.20170701019:3(1-27)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.4018/IJDSST.2017070101
Haider MKumar T(2017)Query Frequency based View SelectionInternational Journal of Business Analytics10.4018/IJBAN.20170101034:1(36-55)Online publication date: Jan-2017
https://doi.org/10.4018/IJBAN.2017010103
Goswami RBhattacharyya DDutta M(2017)Materialized view selection using evolutionary algorithm for speeding up big data query processingJournal of Intelligent Information Systems10.1007/s10844-017-0455-649:3(407-433)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1007/s10844-017-0455-6
Vijay Kumar TKumar AArun B(2017)Cuckoo Search-Based View SelectionEmerging Research in Computing, Information, Communication and Applications10.1007/978-981-10-4741-1_30(327-337)Online publication date: 17-Nov-2017
https://doi.org/10.1007/978-981-10-4741-1_30
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