Multi-table joins through bitmapped join indices
ACM SIGMOD Record
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
Bitmap index design and evaluation
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Multidimensional access methods
ACM Computing Surveys (CSUR)
Heuristic optimization of OLAP queries in multidimensionally hierarchically clustered databases
Proceedings of the 4th ACM international workshop on Data warehousing and OLAP
Optimizing Queries with Aggregate Views
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Performing Group-By before Join
Proceedings of the Tenth 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
Back to the Future: Dynamic Hierarchical Clustering
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Including Group-By in Query Optimization
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
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
Processing Operations with Restrictions in RDBMS without External Sorting: The Tetris Algorithm
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Improving OLAP Performance by Multidimensional Hierarchical Clustering
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Processing star queries on hierarchically-clustered fact tables
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Hierarchy-Based update propagation in decision support systems
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part II
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Multidimensional aggregation queries constitute the single most important class of queries for data warehousing applications and decision support systems. The bottleneck in the evaluation of these queries is the join of the usually huge fact table with the restricted dimension tables (star-join). Recently, a multidimensional hierarchical clustering schema for star schemas is suggested. Subsequently, query evaluation plans for multidimensional queries appeared that essentially implement a star join as a multidimensional range restriction.We present a number of transformations for such plans. The transformations place grouping/aggregation operations before joins and safely prune aggregated tuples. They can be applied at no or minimal extra I/O cost. We show how these transformations can be used to construct a new evaluation plan for grouping/aggregation queries over multidimensional hierarchically clustered schemas. The new plan improves previous results by grouping and aggregating tuples and by excluding aggregated tuples from further consideration at an early stage of the computation of a query.