An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Improved query performance with variant indexes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
CubiST: a new algorithm for improving the performance of ad-hoc OLAP queries
Proceedings of the 3rd ACM international workshop on Data warehousing and OLAP
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
Physical Database Design for Data Warehouses
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Aggregate-Query Processing in Data Warehousing Environments
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Eager Aggregation and Lazy Aggregation
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
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We present a novel approach to speeding up the evaluation of OLAP queries that return aggregates over dimensions containing hierarchies. Our approach is based on our previous version of CubiST (Cubing with Statistics Trees), which pre-computes and stores all possible aggregate views in the leaves of a statistics tree during a one-time scan of the data. However, it uses a single statistics tree to answer all possible OLAP queries. Our new version remedies this limitation by materializing a family of derived trees from the single statistics tree. Given an input query, our new query evaluation algorithm selects the smallest tree in the family which can provide the answer. Our experiments have shown drastic reductions in processing times compared with the original CubiST as well as existing ROLAP and MOLAP systems.