Proceedings of the sixteenth international conference on Very large databases
Adaptive parallel aggregation algorithms
SIGMOD '95 Proceedings of the 1995 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
An array-based algorithm for simultaneous multidimensional aggregates
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
High Performance OLAP and Data Mining on Parallel Computers
Data Mining and Knowledge Discovery
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
Handling Data Skew in Multiprocessor Database Computers Using Partition Tuning
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
A Taxonomy and Performance Model of Data Skew Effects in Parallel Joins
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
Practical Skew Handling in Parallel Joins
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Storage Estimation for Multidimensional Aggregates in the Presence of Hierarchies
VLDB '96 Proceedings of the 22th 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
Parallel ROLAP Data Cube Construction on Shared-Nothing Multiprocessors
Distributed and Parallel Databases
Parallel querying of ROLAP cubes in the presence of hierarchies
Proceedings of the 8th ACM international workshop on Data warehousing and OLAP
The cgmCUBE project: Optimizing parallel data cube generation for ROLAP
Distributed and Parallel Databases
Parallel data cube storage structure for range sum queries and dynamic updates
Journal of Computer Science and Technology
PnP: sequential, external memory, and parallel iceberg cube computation
Distributed and Parallel Databases
Proceedings of the 2005 conference on Software Engineering: Evolution and Emerging Technologies
Materialized aR-Tree in Distributed Spatial Data Warehouse
Intelligent Data Analysis - Analysis of Symbolic and Spatial Data
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
A New Parallel Data Cube Construction Scheme
International Journal of Grid and High Performance Computing
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In recent years, OLAP technologies have become one of the important applications in the database industry. In particular, the datacube operation proposed in [5] receives strong attention among researchers as a fundamental research topic in the OLAP technologies. The datacube operation requires computation of aggregations on all possible combinations of each dimension attribute. As the number of dimensions increases, it becomes very expensive to compute datacubes, because the required computation cost grows exponentially with the increase of dimensions. Parallelization is very important factor for fast datacube computation. However, we cannot obtain sufficient performance gain in the presence of data skew even if the computation is parallelized. In this paper, we present a dynamic load balancing strategy, which enables us to extract the effectiveness of parallizing datacube computation sufficiently. We perform experiments based on simulations and show that our strategy performs well.