Article

Design and development of a multiversion OLAP application

Authors:

Jarernsri L. Mitrpanont,

Somchart FugkeawAuthors Info & Claims

SAC '06: Proceedings of the 2006 ACM symposium on Applied computing

Pages 493 - 497

https://doi.org/10.1145/1141277.1141392

Published: 23 April 2006 Publication History

Get Access

Abstract

This paper proposes a temporal version mapping concept and a SQL query rewriting technique to support the OLAP query analysis in multidimensional database (MDB) systems modeled on multiversion schema. Based on our proposed model, an integration solution of MDB schema change and multiversion OLAP query analysis performed over the changed database schema are taken into account. In addition, we present the system design and implementation of our prototype system to demonstrate our research idea.

References

[1]

J. Trujillo and M. Palomar, An Object Oriented Approach to Multidimensional Database Conceptual (OOMD), Proc. 1st ACM international workshop on Data warehousing and OLAP (DOLAP), Washington, D.C., United States, pp. 16--21, 1998.]]

Digital Library

Google Scholar

[2]

M. Blaschka, FIESTA: A Framework for Schema Evolution in Multidimensional Information Systems, Proc. 6th CASE Doctoral Consortium, Heidelberg, Germany, 1999.]]

Google Scholar

[3]

Jost Enderle, Nicole Schneider, and Thomas Seidl, Efficiently Processing Queries on Interval-and-Value Tuples in Relational Databases, Proc. 31st VLDB 2005, Trondheim, Norway, 2005.]]

Digital Library

Google Scholar

[4]

C. A. Hurtado, A. O. Mendelzon, and A. A. Vaisman, Updating OLAP Dimensions, Proc. 2nd International Workshop on DOLAP '99, Kansan, Missouri, USA, 1999.]]

Digital Library

Google Scholar

[5]

J. Eder and C. Koncilia, Changes of Dimension Data in Temporal Data Warehouse, Proc. 3rd International Conf. on DaWak'01, Munich, Germany, 2001.]]

Digital Library

Google Scholar

[6]

B. Bebel, J. Eder, C. Koncilia, T. Morzy, and R. Wrembel, Creation and Management of Versions in Multiversion Data Warehouse, Proc. of 19th ACM SAC'04, Nicosia, Cyprus, 2004.]]

Digital Library

Google Scholar

[7]

R. Kimball, "The Data Warehouse Toolkit", Wiley, New York, 1996.]]

Google Scholar

[8]

M. Body, M. Miquel, Y. Bedard, and A. Tchounikine, A Multidimensional Structure and Multiversion for OLAP Applications, Proc. 5th ACM DOLAP'02, McLean, Virginia, USA, 2002.]]

Digital Library

Google Scholar

[9]

J. L. Mitrpanont and S. Fugkeaw, Multi-Version and Evolution Support for Multidimensional Database Schema, Proc. IASTED International Conference on Databases and Applications (DBA 2005), Innsbruck, Austria, 2005.]]

Google Scholar

[10]

T. Morzy and R. Wrembel, On Querying Versions of Multiversion Data Warehouse, Proc. International Workshop on DOLAP'04, Washington DC, USA., 2004]]

Digital Library

Google Scholar

[11]

A. Koeller, E. A. Rundensteiner, and N. Hachem, Exploiting Versions for Online Data Warehouse Maintenance in MOLAP Servers. Proc. Of the VLDB Conference, China, 2002.]]

Google Scholar

Cited By

View all

Ravat FSong JTeste O(2016)OLAP Analysis Operators for Multi-State Data WarehousesInternational Journal of Data Warehousing and Mining10.4018/IJDWM.201610010212:4(20-53)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.4018/IJDWM.2016100102
Saroha KGosain A(2014)Multi-version data warehouse: A survey2014 5th International Conference - Confluence The Next Generation Information Technology Summit (Confluence)10.1109/CONFLUENCE.2014.6949236(40-45)Online publication date: Sep-2014
https://doi.org/10.1109/CONFLUENCE.2014.6949236
Mitrpanont JFugkeaw S(2006)Direct Access Versioning for Multidimensional Database Schema CreationProceedings of the Sixth IEEE International Conference on Computer and Information Technology10.1109/CIT.2006.79Online publication date: 20-Sep-2006
https://dl.acm.org/doi/10.1109/CIT.2006.79

Index Terms

Design and development of a multiversion OLAP application
1. Information systems
  1. Data management systems
    1. Database design and models
      1. Data model extensions

Recommendations

Processing OLAP queries in hierarchically clustered databases
Special issue: Advances in OLAP

On-Line Analytical Processing (OLAP) is a technology that encompasses applications requiring a multidimensional and hierarchical view of data. OLAP applications often require fast response time to complex grouping/aggregation queries on enormous ...
Building a novel physical design of a distributed big data warehouse over a Hadoop cluster to enhance OLAP cube query performance
Abstract
Improving OLAP (Online Analytical Processing) query performance in a distributed system on top of Hadoop is a challenging task. An OLAP Cube query comprises several relational operations, such as selection, join, and group-by ...
Highlights
- The Group-by aggregation may involve high communication cost during the shuffle phase.
OLAP in Multifunction Multidimensional Databases
ADBIS 2013: Proceedings of the 17th East European Conference on Advances in Databases and Information Systems - Volume 8133

Most models proposed for modeling multidimensional data warehouses consider a same function to determine how measure values are aggregated. We provide a more flexible conceptual model allowing associating each measure with several aggregation functions ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

SAC '06: Proceedings of the 2006 ACM symposium on Applied computing

April 2006

1967 pages

ISBN:1595931082

DOI:10.1145/1141277

Conference Chair:
Hisham M. Haddad
Kennesaw State University, Kennesaw, Georgia

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 April 2006

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

SAC06

Sponsor:

SIGAPP

SAC06: The 2006 ACM Symposium on Applied Computing

April 23 - 27, 2006

Dijon, France

Acceptance Rates

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

Upcoming Conference

SAC '25

Sponsor:
sigapp

The 40th ACM/SIGAPP Symposium on Applied Computing

March 31 - April 4, 2025

Catania , Italy

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
401
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)1

Reflects downloads up to 21 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Ravat FSong JTeste O(2016)OLAP Analysis Operators for Multi-State Data WarehousesInternational Journal of Data Warehousing and Mining10.4018/IJDWM.201610010212:4(20-53)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.4018/IJDWM.2016100102
Saroha KGosain A(2014)Multi-version data warehouse: A survey2014 5th International Conference - Confluence The Next Generation Information Technology Summit (Confluence)10.1109/CONFLUENCE.2014.6949236(40-45)Online publication date: Sep-2014
https://doi.org/10.1109/CONFLUENCE.2014.6949236
Mitrpanont JFugkeaw S(2006)Direct Access Versioning for Multidimensional Database Schema CreationProceedings of the Sixth IEEE International Conference on Computer and Information Technology10.1109/CIT.2006.79Online publication date: 20-Sep-2006
https://dl.acm.org/doi/10.1109/CIT.2006.79

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Processing OLAP queries in hierarchically clustered databases

Building a novel physical design of a distributed big data warehouse over a Hadoop cluster to enhance OLAP cube query performance

OLAP in Multifunction Multidimensional Databases