Distributing the power of OLAP

Doka, K; Tsoumakos, D; Koziris, N

dc.contributor.author	Doka, K	en
dc.contributor.author	Tsoumakos, D	en
dc.contributor.author	Koziris, N	en
dc.date.accessioned	2014-03-01T02:46:46Z
dc.date.available	2014-03-01T02:46:46Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32832
dc.subject	Data cube	en
dc.subject	Data earehousing	en
dc.subject	P2P	en
dc.subject.other	Aggregate queries	en
dc.subject.other	Brown dwarfs	en
dc.subject.other	Centralized algorithms	en
dc.subject.other	Data cube	en
dc.subject.other	Data earehousing	en
dc.subject.other	Distributed systems	en
dc.subject.other	Multidimensional data	en
dc.subject.other	Network node	en
dc.subject.other	Overlay nodes	en
dc.subject.other	P2P	en
dc.subject.other	Storage overhead	en
dc.subject.other	Unstructured peer-to-peer	en
dc.subject.other	Geometry	en
dc.subject.other	Peer to peer networks	en
dc.subject.other	Stars	en
dc.subject.other	Systems analysis	en
dc.subject.other	Distributed computer systems	en
dc.title	Distributing the power of OLAP	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/1851476.1851521	en
heal.identifier.secondary	http://dx.doi.org/10.1145/1851476.1851521	en
heal.publicationDate	2010	en
heal.abstract	In this paper we present the Brown Dwarf, a distributed system designed to efficiently store, query and update multidimensional data over an unstructured Peer-to-Peer overlay, without the use of any proprietary tool. Brown Dwarf manages to distribute a highly effective centralized structure among peers on-the-y. Both point and aggregate queries are then naturally answered on-line through cooperating nodes that hold parts of a fully or partially materialized data cube. Updates are also performed on-line, eliminating the usually costly over-night process. Our initial evaluation on an actual testbed proves that Brown Dwarf manages to distribute the structure across the overlay nodes incurring only a small storage overhead compared to the centralized algorithm. Moreover, it accelerates cube creation up to 5 times and querying up to several tens of times by exploiting the capabilities of the available network nodes working in parallel. Copyright 2010 ACM.	en
heal.journalName	HPDC 2010 - Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing	en
dc.identifier.doi	10.1145/1851476.1851521	en
dc.identifier.spage	324	en
dc.identifier.epage	327	en