View maintenance in a warehousing environment
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Maintenance of data cubes and summary tables in a warehouse
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Materialized views: techniques, implementations, and applications
Materialized views: techniques, implementations, and applications
Microsoft OLAP solutions
Realizing active data warehouses with off-the-shelf database technology
Software—Practice & Experience
Aggregate-Query Processing in Data Warehousing Environments
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
On the Computation of Multidimensional Aggregates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Providing OLAP Interoperability with OLAPWare
SCCC '02 Proceedings of the XII International Conference of the Chilean Computer Science Society
On-Line Analytical Processing on Large Databases Managed by Computational Grids
DEXA '04 Proceedings of the Database and Expert Systems Applications, 15th International Workshop
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
MDX Solutions: with Microsoft SQL Server Analysis Services 2005 and Hyperion Essbase
MDX Solutions: with Microsoft SQL Server Analysis Services 2005 and Hyperion Essbase
An open source and web based framework for geographic and multidimensional processing
Proceedings of the 2006 ACM symposium on Applied computing
Web-oriented business intelligence solution based on Associative Query Logic
Software—Practice & Experience
| Hi-index | 0.00 |
For a long time, the design of relational databases has focused on the optimization of atomic transactions (insert, select, update or delete). Currently, relational databases store tactical information of data warehouses, mainly for select-like operations. However, the database paradigm has evolved, and nowadays on-line analytical processing (OLAP) systems handle strategic information for further analysis. These systems enable fast, interactive and consistent information analysis of data warehouses, including shared calculations and allocations. OLAP and data warehouses jointly allow multidimensional data views, turning raw data into knowledge. OLAP allows ‘slice and dice’ navigation and a top-down perspective of data hierarchies. In this paper, we describe our experience in the migration from a large relational database management system to an OLAP system on top of a relational layer (the data warehouse), and the resulting contributions in open-source ROLAP optimization. Existing open-source ROLAP technologies rely on summarized tables with materialized aggregate views to improve system performance (in terms of response time). The design and maintenance of those tables are cumbersome. Instead, we intensively exploit cache memory, where key data reside, yielding low response times. A cold start process brings summarized data from the relational database to cache memory, subsequently reducing the response time. We ensure concurrent access to the summarized data, as well as consistency when the relational database updates data. We also improve the OLAP functionality, by providing new features for automating the creation of calculated members. This makes it possible to define new measures on the fly using virtual dimensions, without re-designing the multidimensional cube. We have chosen the XML-A de facto standard for service provision. Copyright © 2008 John Wiley & Sons, Ltd.