Scientific and Statistical Database Management, International Conference on (2006)
July 3, 2006 to July 5, 2006
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SSDBM.2006.38
Wolfgang Lehner , Dresden University of Technology
Maik Thiele , Dresden University of Technology
Jens Albrecht , GfK Marketing Services 90319, Nuremberg
Data marts and caching are two closely related concepts in the domain of multi-dimensional data. Both store precomputed data to provide fast response times for complex OLAP queries, and for both it must be guaranteed that every query can be completely processed. However, they differ extremely in their update behaviour which we utilise to build a specific data mart extended by cache semantics. In this paper, we introduce a novel cache exploitation concept for data marts - coarse-grained caching - in which the containedness check for a multi-dimensional query is done through the comparison of the expected and the actual cardinalities. Therefore, we subdivide the multi-dimensional data into coarse partitions, the so called cubletets, which allow to specify the completeness criteria for incoming queries. We show that during query processing, the completeness check is done with no additional costs.
Wolfgang Lehner, Maik Thiele, Jens Albrecht, "Optimistic Coarse-Grained Cache Semantics for Data Marts", Scientific and Statistical Database Management, International Conference on, vol. 00, no. , pp. 311-320, 2006, doi:10.1109/SSDBM.2006.38