Principles of distributed database systems (2nd ed.)
Principles of distributed database systems (2nd ed.)
A horizontal fragmentation algorithm for the fact relation in a distributed data warehouse
Proceedings of the eighth international conference on Information and knowledge management
Algorithms and Support for Horizontal Class Partitioning in Object-Oriented Databases
Distributed and Parallel Databases
Fast incremental maintenance of approximate histograms
ACM Transactions on Database Systems (TODS)
Horizontal data partitioning in database design
SIGMOD '82 Proceedings of the 1982 ACM SIGMOD international conference on Management of data
Multi-Dimensional Database Allocation for Parallel Data Warehouses
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Heuristic and randomized optimization for the join ordering problem
The VLDB Journal — The International Journal on Very Large Data Bases
Integrating vertical and horizontal partitioning into automated physical database design
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Experimental evidence on partitioning in parallel data warehouses
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
Reality check: a case study of an EII research prototype encountering customer needs
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Supporting table partitioning by reference in oracle
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Data mining-based fragmentation of XML data warehouses
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
Query simplification: graceful degradation for join-order optimization
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Efficient processing of drill-across queries over geographic data warehouses
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
Verification of partitioning and allocation techniques on teradata DBMS
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part I
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Most of business intelligence applications use data warehousing solutions. The star schema or its variants modelling these applications are usually composed of hundreds of dimension tables and multiple huge fact tables. Referential horizontal partitioning is one of physical design techniques adapted to optimize queries posed over these schemes. In referential partitioning, a fact table can inherit the fragmentation characteristics from dimension table(s). Most of the existing works done on referential partitioning start from a bag containing selection predicates defined on dimension tables, partition each one based on its predicates and finally propagate their fragmentation schemes to the fact table. This procedure gives all dimension tables the same probability to partition the fact table which is not always true. In order to ensure a high performance of the most costly queries, the identification of relevant dimension table(s) to referential partition a fact table is a crucial issue that should be addressed. In this paper, we first study the complexity of the problem of selecting dimension table(s) used to partition a fact table. Secondly, we present strategies to perform their selection. Finally, to validate of our proposal, we conduct intensive experimental studies using a mathematical cost model and the obtained results are verified on Oracle11G DBMS.