Introduction to parallel computing: design and analysis of algorithms
Introduction to parallel computing: design and analysis of algorithms
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
An introduction to spatial database systems
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
A Case Study of Software Process Improvement During Development
IEEE Transactions on Software Engineering
Efficient Organization of Large Multidimensional Arrays
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
Parallel Data Cube Construction for High Performance On-Line Analytical Processing
HIPC '97 Proceedings of the Fourth International Conference on High-Performance Computing
High performance multidimensional analysis of large datasets
Proceedings of the 1st ACM international workshop on Data warehousing and OLAP
A dynamic load balancing strategy for parallel datacube computation
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
CubiST: a new algorithm for improving the performance of ad-hoc OLAP queries
Proceedings of the 3rd ACM international workshop on Data warehousing and OLAP
Iceberg-cube computation with PC clusters
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Understanding the Crucial Role of AttributeInteraction in Data Mining
Artificial Intelligence Review
High performance multidimensional analysis and data mining
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
Distributed and Parallel Databases - Special issue: Parallel and distributed data mining
Coarse Grained Parallel On-Line Analytical Processing (OLAP) for Data Mining
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Implementation of Parallel Collection Equi-Join Using MPI
PARA '02 Proceedings of the 6th International Conference on Applied Parallel Computing Advanced Scientific Computing
A Parallel Scalable Infrastructure for OLAP and Data Mining
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
CubiST++: Evaluating Ad-Hoc CUBE Queries Using Statistics Trees
Distributed and Parallel Databases
Parallel ROLAP Data Cube Construction on Shared-Nothing Multiprocessors
Distributed and Parallel Databases
The cgmCUBE project: Optimizing parallel data cube generation for ROLAP
Distributed and Parallel Databases
PnP: sequential, external memory, and parallel iceberg cube computation
Distributed and Parallel Databases
A cubic-wise balance approach for privacy preservation in data cubes
Information Sciences: an International Journal
Developing high-performance parallel applications using EPAS
ISPA'05 Proceedings of the Third international conference on Parallel and Distributed Processing and Applications
A New Parallel Data Cube Construction Scheme
International Journal of Grid and High Performance Computing
Normalised LCS-based method for indexing multidimensional data cube
International Journal of Intelligent Information and Database Systems
Data guided approach to generate multi-dimensional schema for targeted knowledge discovery
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
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On-Line Analytical Processing (OLAP) techniques are increasingly being used in decision support systems to provide analysis of data. Queriesposed on such systems are quite complex and require different views ofdata. Analytical models need to capture the multidimensionality of theunderlying data, a task for which multidimensional databases are wellsuited. Multidimensional OLAP systems store data in multidimensional arrayson which analytical operations are performed. Knowledge discovery and datamining requires complex operations on the underlying data which can be veryexpensive in terms of computation time. High performance parallel systemscan reduce this analysis time.Precomputed aggregate calculations in a Data Cube can provide efficientquery processing for OLAP applications. In this article, we presentalgorithms for construction of data cubes on distributed-memory parallelcomputers. Data is loaded from a relational database into amultidimensional array. We present two methods, sort-based and hash-basedfor loading the base cube and compare their performances. Data cubes areused to perform consolidation queries used in roll-up operations usingdimension hierarchies. Finally, we show how data cubes are used for datamining using Attribute Focusing techniques. We present results for these onthe IBM-SP2 parallel machine. Results show that our algorithms andtechniques for OLAP and data mining on parallel systems are scalable to a large number of processors, providing a high performance platform for such applications.