Processing OLAP queries in hierarchically clustered databases

Theodoratos, D; Tsois, A

dc.contributor.author	Theodoratos, D	en
dc.contributor.author	Tsois, A	en
dc.date.accessioned	2014-03-01T01:19:26Z
dc.date.available	2014-03-01T01:19:26Z
dc.date.issued	2003	en
dc.identifier.issn	0169-023X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15497
dc.subject	Grouping and aggregation query	en
dc.subject	Hierarchical clustering	en
dc.subject	Multidimensional database	en
dc.subject	On-Line Analytical Processing	en
dc.subject	Star schema	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.other	Hierarchical systems	en
dc.subject.other	Indexing (of information)	en
dc.subject.other	Online systems	en
dc.subject.other	Optimization	en
dc.subject.other	Program processors	en
dc.subject.other	Multidimensional databases	en
dc.subject.other	Database systems	en
dc.title	Processing OLAP queries in hierarchically clustered databases	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/S0169-023X(02)00180-5	en
heal.identifier.secondary	http://dx.doi.org/10.1016/S0169-023X(02)00180-5	en
heal.language	English	en
heal.publicationDate	2003	en
heal.abstract	On-Line Analytical Processing (OLAP) is a technology that encompasses applications requiring a multidimensional and hierarchical view of data. OLAP applications often require fast response time to complex grouping/aggregation queries on enormous quantities of data. Commercial relational database management systems use mainly multiple one-dimensional indexes to process OLAP queries that restrict multiple dimensions. However, in many cases, multidimensional access methods outperform one-dimensional indexing methods. We present an architecture for multidimensional databases that are clustered with respect to multiple hierarchical dimensions. It is based on the star schema and is called CSB star. We focus on processing OLAP queries over this schema using multidimensional access methods. Users can still formulate their queries over a traditional star schema, which are then rewritten by the query processor over the CSB star. We exploit the different clustering features of the CSB star to efficiently process a class of typical OLAP queries. We detect cases where the construction of an evaluation plan can be simplified, and other cases where additional processing techniques can be applied. (C) 2002 Elsevier Science B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Data and Knowledge Engineering	en
dc.identifier.doi	10.1016/S0169-023X(02)00180-5	en
dc.identifier.isi	ISI:000182417700005	en
dc.identifier.volume	45	en
dc.identifier.issue	2	en
dc.identifier.spage	205	en
dc.identifier.epage	224	en