Database partitioning in a cluster of processors
ACM Transactions on Database Systems (TODS)
Vertical partitioning for database design: a graphical algorithm
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Principles of distributed database systems (2nd ed.)
Principles of distributed database systems (2nd ed.)
OLAP Query Routing and Physical Design in a Database Cluster
EDBT '00 Proceedings of the 7th International Conference on Extending Database Technology: Advances in Database Technology
Cache-Aware Query Routing in a Cluster of Databases
Proceedings of the 17th International Conference on Data Engineering
Multi-Dimensional Database Allocation for Parallel Data Warehouses
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
WARLOCK: A Data Allocation Tool for Parallel Warehouses
Proceedings of the 27th International Conference on Very Large Data Bases
Query-Driven Data Allocation Algorithms for Distributed Database Systems
DEXA '97 Proceedings of the 8th International Conference on Database and Expert Systems Applications
Experimental evidence on partitioning in parallel data warehouses
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
Supporting table partitioning by reference in oracle
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Data Partitioning in Data Warehouses: Hardness Study, Heuristics and ORACLE Validation
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Experimenting the Query Performance of a Grid-Based Sensor Network Data Warehouse
Globe '08 Proceedings of the 1st international conference on Data Management in Grid and Peer-to-Peer Systems
LCS-Hist: taming massive high-dimensional data cube compression
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Parallel OLAP query processing in database clusters with data replication
Distributed and Parallel Databases
A Joint Design Approach of Partitioning and Allocation in Parallel Data Warehouses
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Fragmenting very large XML data warehouses via K-means clustering algorithm
International Journal of Business Intelligence and Data Mining
An evolutionary approach to schema partitioning selection in a data warehouse
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
SAGA: a combination of genetic and simulated annealing algorithms for physical data warehouse design
BNCOD'06 Proceedings of the 23rd British National Conference on Databases, conference on Flexible and Efficient Information Handling
| Hi-index | 0.00 |
Parallel database technology has already shown its efficiency in supporting high-performance Online Analytical Processing (OLAP) applications This scenario implies achieving query optimization over relational Data Warehouses (RDW) on top of which typical OLAP functionalities, such as roll-up, drill-down and aggregate query answering, can be implemented As a result, it follows the emerging need for a comprehensive methodology able to support the design of RDW over parallel and distributed environments in all the phases, including data partitioning, fragment allocation, and data replication Existing design approaches have an important limitation: fragmentation and allocation phases are performed in an isolated manner In order to overcome this limitation, in this paper we propose a new methodology for designing parallel RDW over distributed environments, for query optimization purposes The methodology is illustrated on database clusters, as a noticeable case of distributed environments Contrary to state-of-the-art approaches where allocation is performed after fragmentation, in our approach we propose allocating fragments just during the partitioning phase Also, a naive replication algorithm that takes into account the heterogeneous characteristics of our reference architecture is proposed.