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 |