Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Query evaluation techniques for large databases
ACM Computing Surveys (CSUR)
Maintaining views incrementally
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Cubetree: organization of and bulk incremental updates on the data cube
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Maintenance of data cubes and summary tables in a warehouse
SIGMOD '97 Proceedings of the 1997 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
Maintenance of cube automatic summary tables
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Efficient computation of Iceberg cubes with complex measures
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
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
Fast Computation of Sparse Datacubes
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Including Group-By in Query Optimization
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
On the Computation of Multidimensional Aggregates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Aggregate view management in data warehouses
Handbook of massive data sets
Maintaining Data Cubes under Dimension Updates
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Range CUBE: Efficient Cube Computation by Exploiting Data Correlation
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Efficient computation of multiple group by queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Discovering branching and fractional dependencies in databases
Data & Knowledge Engineering
Efficient Incremental Computation of CUBE in Multiple Versions What-If Analysis
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
Incremental Computation for MEDIAN Cubes in What-If Analysis
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
The Tradeoff of Delta Table Merging and Re-writing Algorithms in What-If Analysis Application
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
An efficient method for maintaining data cubes incrementally
Information Sciences: an International Journal
Revisiting the cube lifecycle in the presence of hierarchies
The VLDB Journal — The International Journal on Very Large Data Bases
What-if analysis in MOLAP environments
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 2
An incremental maintenance scheme of data cubes
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
Data compression for incremental data cube maintenance
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
Distributed construction of data cubes from tuple stream
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
Distributed construction of data cubes from tuple stream
International Journal of Business Intelligence and Data Mining
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The data cube provides users with aggregated results that are group-bys for all possible combinations of dimension attributes. When the number of dimension attributes is n, the data cube computes 2n group-bys, each of which is called a cuboid. A data cube is often precomputed and stored as materialized views in data warehouses. The data cube needs to be updated when source relations change. The incremental maintenance of a data cube is to compute and propagate only changes of source relations rather than recompute the entire data cube from the source relations.To maintain a data cube incrementally, previous methods compute a delta cube which represents the change of the data cube. We call a cuboid in a delta cube a delta cuboid. For a data cube with 2n cuboids, a delta cube consists of 2n delta cuboids. Thus, as the number of dimension attributes increases, the cost of computing the delta cube increases significantly. In this paper, we propose an incremental maintenance method for data cubes that can maintain a data cube by using only (n ⌈n/2⌉) delta cuboids. As a result, the cost of computing delta cuboids is substantially reduced. Through various experiments, we show the performance advantages of our method over the previous methods.