Welcome to DiSC 2003
SIGMOD 2002
 = SIGMOD'02 Website
 = SIGMOD/PODS'02 Plena
<<< = SIGMOD'02 Papers>>>
 = Demos
 = Industrial Sessions
 = Panels
 = Tutorials
PODS 2002
 SIGMOD RECORD 2002
 ADBIS 2002
CIKM 2002
CoopIS 2002
 EDBT 2002
 ER 2002
Data Engineering Bul
DEXA_EC-WEB 2002
DMKD 2002
 DPDJ 2002
HYPERTEXT 2002
ICDE 2002
ICDM 2002
JCDL 2002
KDD 2002
 KDD_EXPLORATIONS 20
KRDB 2002
MDM 2002
MIS 2002
RIDE 2002
SBBD 2002
 SIGIR 2002
 SIGIR FORUM 2002
SSDBM 2002
TODS 2002
TIME 2002
VLDB 2002
VLDBJ 2002

An adaptive peer-to-peer network for distributed caching of OLAP results


Panos Kalnis, Wee Siong Ng, Beng Chin Ooi, Dimitris Papadias, and Kian-Lee Tan

  View Paper (PDF)  

Return to Data warehousing and archive


Abstract

Peer-to-Peer (P2P) systems are becoming increasingly popular as they enable users to exchange digital information by participating in complex networks. Such systems are inexpensive, easy to use, highly scalable and do not require central administration. Despite their advantages, however, limited work has been done on employing database systems on top of P2P networks.Here we propose the PeerOLAP architecture for supporting On-Line Analytical Processing queries. A large number low-end clients, each containing a cache with the most useful results, are connected through an arbitrary P2P network. If a query cannot be answered locally (i.e. by using the cache contents of the computer where it is issued), it is propagated through the network until a peer that has cached the answer is found. An answer may also be constructed by partial results from many peers. Thus PeerOLAP acts as a large distributed cache, which amplifies the benefits of traditional client-side caching. The system is fully distributed and can reconfigure itself on-the-fly in order to decrease the query cost for the observed workload. This paper describes the core components of PeerOLAP and presents our results both from simulation and a prototype installation running on geographically remote peers.


DiSC'03 © 2003 Association for Computing Machinery