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PVLDB
2008
84views more  PVLDB 2008»
13 years 12 months ago
When is it time to rethink the aggregate configuration of your OLAP server?
OLAP servers based on relational backends typically exploit materialized aggregate tables to improve response times of complex analytical queries. One of the key problems in this ...
Katja Hose, Daniel Klan, Matthias Marx, Kai-Uwe Sa...
DKE
2002
107views more  DKE 2002»
14 years 7 days ago
View selection using randomized search
An important issue in data warehouse development is the selection of a set of views to materialize in order to accelerate OLAP queries, given certain space and maintenance time co...
Panos Kalnis, Nikos Mamoulis, Dimitris Papadias
DASFAA
2009
IEEE
96views Database» more  DASFAA 2009»
14 years 7 months ago
Materialized View Selection in XML Databases
Materialized views, a rdbms silver bullet, demonstrate its efficacy in many applications, especially as a data warehousing/decison support system tool. The pivot of playing materia...
Nan Tang, Jeffrey Xu Yu, Hao Tang, M. Tamer Ö...
PODS
2003
ACM
132views Database» more  PODS 2003»
15 years 17 days ago
The view selection problem for XML content based routing
We consider the view selection problem for XML content based routing: given a network, in which a stream of XML documents is routed and the routing decisions are taken based on re...
Ashish Kumar Gupta, Dan Suciu, Alon Y. Halevy
VLDB
2002
ACM
157views Database» more  VLDB 2002»
15 years 20 days ago
A formal perspective on the view selection problem
The view selection problem is to choose a set of views to materialize over a database schema, such that the cost of evaluating a set of workload queries is minimized and such that ...
Rada Chirkova, Alon Y. Halevy, Dan Suciu
ICDE
2009
IEEE
149views Database» more  ICDE 2009»
15 years 2 months ago
Online Tuning of Aggregation Tables for OLAP
Materializing results from complex aggregation queries helps to significantly improve response times in OLAP servers. This problem is known as the view selection problem: choosing ...
Katja Hose, Daniel Klan, Kai-Uwe Sattler