Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A data model for supporting on-line analytical processing
CIKM '96 Proceedings of the fifth international conference on Information and knowledge management
Caching multidimensional queries using chunks
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Database abstractions: aggregation and generalization
ACM Transactions on Database Systems (TODS)
Modelling Large Scale OLAP Scenarios
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Modeling Multidimensional Databases
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Selection of Views to Materialize in a Data Warehouse
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Materialized Views Selection in a Multidimensional Database
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
A Foundation for Multi-dimensional Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Algorithms for Materialized View Design in Data Warehousing Environment
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Summarizability in OLAP and Statistical Data Bases
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
The Cube-Query-Languages (CQL) for Multidimensional Statistical and Scientific Database Systems
Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
Querying Multidimensional Databases
DBLP-6 Proceedings of the 6th International Workshop on Database Programming Languages
WATCHMAN: A Data Warehouse Intelligent Cache Manager
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
On-Line Analytical Processing in Distributed Data Warehouses
IDEAS '98 Proceedings of the 1998 International Symposium on Database Engineering & Applications
Query optimization by using derivability in a data warehouse environment
Proceedings of the 3rd ACM international workshop on Data warehousing and OLAP
Finding an efficient rewriting of OLAP queries using materialized views in data warehouses
Decision Support Systems
Set-Derivability of Multidimensional Aggregates
DaWaK '99 Proceedings of the First International Conference on Data Warehousing and Knowledge Discovery
Supporting Hot Spots with Materialized Views
DaWaK 2000 Proceedings of the Second International Conference on Data Warehousing and Knowledge Discovery
PROMISE: Predicting Query Behavior to Enable Predictive Caching Strategies for OLAP Systems
DaWaK 2000 Proceedings of the Second International Conference on Data Warehousing and Knowledge Discovery
Usability-based caching of query results in OLAP systems
Journal of Systems and Software
XCube: XML for data warehouses
DOLAP '03 Proceedings of the 6th ACM international workshop on Data warehousing and OLAP
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Proper management of multidimensional aggregates is a fundamental prerequisite for efficient OLAP. The experimental OLAP server CubeStar, which concepts are described in this paper, was designed exactly for that purpose. All logical query processing is based solely on a specific algebra for multidimensional data. However, a relational database system is used for the physical storage of the data. Therefore, in popular terms CubeStar can be classified as a ROLAP system. In comparison to commercially available systems, CubeStar is superior in two aspects: First, the implemented multidimensional data model allows more adequate modeling of hierarchical dimensions, because properties which apply only to certain dimensional elements can be modeled context-sensitively. This fact is reflected by an extended star schema on the relational side. Second, CubeStar supports multidimensional query optimization by caching multidimensional aggregates. Since summary tables are not created in advance but as needed, hot spots can be adequately represented. The dynamic and partition-oriented caching method allows cost reductions of up to 60% with space requirements of less than 10% of the size of the fact table.