Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 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
An array-based algorithm for simultaneous multidimensional aggregates
SIGMOD '97 Proceedings of the 1997 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
Bottom-up computation of sparse and Iceberg CUBE
SIGMOD '99 Proceedings of the 1999 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
Proceedings of the 2002 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
Materialized View Selection for Multidimensional Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Performance Measurements of Compressed Bitmap Indices
VLDB '99 Proceedings of the 25th 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
QC-trees: an efficient summary structure for semantic OLAP
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Condensed Cube: An Efficient Approach to Reducing Data Cube Size
ICDE '02 Proceedings of the 18th 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
MM-Cubing: Computing Iceberg Cubes by Factorizing the Lattice Space
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Incremental maintenance of quotient cube for median
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Incremental maintenance of quotient cube based on Galois lattice
Journal of Computer Science and Technology
Indexing and incremental updating condensed data cube
SSDBM '03 Proceedings of the 15th International Conference on Scientific and Statistical Database Management
CURE for cubes: cubing using a ROLAP engine
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Quotient cube: how to summarize the semantics of a data cube
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
ROLAP implementations of the data cube
ACM Computing Surveys (CSUR)
Star-cubing: computing iceberg cubes by top-down and bottom-up integration
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
High-dimensional OLAP: a minimal cubing approach
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
The polynomial complexity of fully materialized coalesced cubes
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
ROLAP implementations of the data cube
ACM Computing Surveys (CSUR)
Reduced representations of Emerging Cubes for OLAP database mining
International Journal of Business Intelligence and Data Mining
Revisiting the cube lifecycle in the presence of hierarchies
The VLDB Journal — The International Journal on Very Large Data Bases
Extracting semantics in OLAP databases using emerging cubes
Information Sciences: an International Journal
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The lifecycle of a data cube involves efficient construction and storage, fast query answering, and incremental updating. Existing ROLAP methods that implement data cubes are weak with respect to one or more of the above, focusing mainly on construction and storage. In this paper, we present a comprehensive ROLAP solution that addresses efficiently all functionality in the lifecycle of a cube and can be implemented easily over existing relational servers. It is a family of algorithms centered around a purely ROLAP construction method that provides fast computation of a fully materialized cube in compressed form, is incrementally updateable, and exhibits quick query response times that can be improved by low-cost indexing and caching. This is demonstrated through comprehensive experiments on both synthetic and real-world datasets, whose results have shown great promise for the performance and scalability potential of the proposed techniques, with respect to both the size and dimensionality of the fact table.