Processing Star Queries on Hierarchically-Clustered Fact Tables

Karayannidis, N; Tsois, A; Sellis, T; Pieringer, R; Markl, V; Ramsak, F; Fenk, R; Elhardt, K; Bayer, R

dc.contributor.author	Karayannidis, N	en
dc.contributor.author	Tsois, A	en
dc.contributor.author	Sellis, T	en
dc.contributor.author	Pieringer, R	en
dc.contributor.author	Markl, V	en
dc.contributor.author	Ramsak, F	en
dc.contributor.author	Fenk, R	en
dc.contributor.author	Elhardt, K	en
dc.contributor.author	Bayer, R	en
dc.date.accessioned	2014-03-01T02:49:10Z
dc.date.available	2014-03-01T02:49:10Z
dc.date.issued	2002	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34376
dc.relation.uri	http://www.dbnet.ece.ntua.gr/pubs/uploads/TR-2002-4.pdf	en
dc.relation.uri	http://www.informatik.uni-trier.de/~ley/db/conf/vldb/vldb2002.html#KarayannidisTSPMRFEB02	en
dc.relation.uri	http://wwwbayer.in.tum.de/cgi-webcon/webcon/lehrstuhldb/download/43/application/pdf	en
dc.relation.uri	http://www.vldb.org/conf/2002/S21P01.pdf	en
dc.relation.uri	http://www.dblab.ntua.gr/~atsois/344Karayannidis.pdf	en
dc.relation.uri	http://www.dbnet.ece.ntua.gr/~nikos/papers/344Karayannidis.pdf	en
dc.relation.uri	http://mistral.informatik.tu-muenchen.de/results/publications/KTS+02.pdf	en
dc.relation.uri	http://mistral.in.tum.de/results/publications/KTS+02.pdf	en
dc.relation.uri	http://www.cse.ust.hk/vldb2002/VLDB2002-proceedings/papers/S21P01.pdf	en
dc.subject	Data Warehousing	en
dc.subject	Database Management	en
dc.subject	Experimental Evaluation	en
dc.subject	Hierarchical Clustering	en
dc.subject	Process Planning	en
dc.subject	Query Processing	en
dc.subject	Real World Application	en
dc.title	Processing Star Queries on Hierarchically-Clustered Fact Tables	en
heal.type	conferenceItem	en
heal.publicationDate	2002	en
heal.abstract	Star queries are the most prevalent kind of que- ries in data warehousing, OLAP and business in- telligence applications. Thus, there is an impera- tive need for efficiently processing star queries. To this end, a new class of fact table organiza- tions has emerged that exploits path-based surro- gate keys in order to hierarchically cluster the fact table data of	en
heal.journalName	Very Large Data Bases	en