Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Range queries in OLAP data cubes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Dynamic assembly of views in data cubes
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
An alternative storage organization for ROLAP aggregate views based on cubetrees
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Data cube approximation and histograms via wavelets
Proceedings of the seventh international conference on Information and knowledge management
Approximate computation of multidimensional aggregates of sparse data using wavelets
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Bottom-up computation of sparse and Iceberg CUBE
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
EDBT '00 Proceedings of the 7th International Conference on Extending Database Technology: Advances in Database Technology
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
Hierarchical Prefix Cubes for Range-Sum Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
pCube: Update-Efficient Online Aggregation with Progressive Feedback and Error Bounds
SSDBM '00 Proceedings of the 12th International Conference on Scientific and Statistical Database Management
Relative Prefix Sums: An Efficient Approach for Querying Dynamic OLAP Data Cubes
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Optimizing Scientific Databases for Client Side Data Processing
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
ProPolyne: A Fast Wavelet-Based Algorithm for Progressive Evaluation of Polynomial Range-Sum Queries
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Optimal Range Max Datacube for Fixed Dimensions
ICDT '03 Proceedings of the 9th International Conference on Database Theory
A Decathlon in Multidimensional Modeling: Open Issues and Some Solutions
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
Efficient Online Aggregates in Dense-Region-Based Data Cube Representations
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Efficient online aggregates in dense-region-based data cube representations
Transactions on large-scale data- and knowledge-centered systems II
Efficient online aggregates in dense-region-based data cube representations
Transactions on large-scale data- and knowledge-centered systems II
Efficient algorithms for k maximum sums
ISAAC'04 Proceedings of the 15th international conference on Algorithms and Computation
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Applications like Online Analytical Processing depend heavily on the ability to quickly summarize large amounts of information. Techniques were proposed recently that speed up aggregate range queries on MOLAP data cubes by storing pre-computed aggregates. These approaches try to handle data cubes of any dimensionality by dealing with all dimensions at the same time and treat the different dimensions uniformly. The algorithms are typically complex, and it is difficult to prove their correctness and to analyze their performance. We present a new technique to generate Iterative Data Cubes (IDC) that addresses these problems. The proposed approach provides a modular framework for combining one-dimensional aggregation techniques to create space-optimal high-dimensional data cubes. A large variety of cost tradeoffs for high-dimensional IDC can be generated, making it easy to find the right configuration based on the application requirements.