Fundamentals of database systems
Fundamentals of database systems
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
OLAP solutions: building multidimensional information systems
OLAP solutions: building multidimensional information systems
Principles of Database and Knowledge-Base Systems: Volume II: The New Technologies
Principles of Database and Knowledge-Base Systems: Volume II: The New Technologies
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total
ICDE '96 Proceedings of the Twelfth 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
Materialized View Selection for Multidimensional Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Storage Estimation for Multidimensional Aggregates in the Presence of Hierarchies
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Materialized view selection for multidimensional datasets
Materialized view selection for multidimensional datasets
Clustering-based materialized view selection in data warehouses
ADBIS'06 Proceedings of the 10th East European conference on Advances in Databases and Information Systems
Using functional dependencies for reducing the size of a data cube
FoIKS'12 Proceedings of the 7th international conference on Foundations of Information and Knowledge Systems
Equivalence and minimization of conjunctive queries under combined semantics
Proceedings of the 15th International Conference on Database Theory
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OLAP applications use precomputation of aggregate data to improve query response time. While this problem has been well-studied in the recent database literature, to our knowledge all previous work has focussed on the special case in which all aggregates are computed from a single cube (in a star schema, this corresponds to there being a single fact table). This is unfortunate, because many real world applications require aggregates over multiple fact tables. In this paper, we attempt to fill this lack of discussion about the issues arising in multi-cube data models by analyzing these issues. Then we examine performance issues by studying the precomputation problem for multi-cube systems. We show that this problem is significantly more complex than the single cube precomputation problem, and that algorithms and cost models developed for single cube precomputation must be extended to deal well with the multi-cube case. Our results from a prototype implementation show that for multicube workloads substantial performance improvements can be realized by using the multi-cube algorithms.