Paper Info
Title
Adaptive Multi-join Query Processing in PDBMS
Abstract
Traditionally, distributed databases assume that the small) set of nodes participating in a query is known apriori, the data is well placed, and the statistics are readily available. However, these assumptions are no longer valid in a Peer-based DataBase Management System (PDBMS). As such, it is a challenge to process and optimize queries in a PDBMS. In this paper, we present our distributed solution to this problem for multi-way join queries. Our approach first processes a multi-way join query based on an initial query evaluation plan (generated using statistical data that may be obsolete or inaccurate); as the query is beingprocessed, statistics obtained on-the-fly are used to (continuously) refine the current plan dynamically into a more effective one. We have conducted an extensive performance study which shows that our adaptive query processing strategy can reduce the network traffic significantly.
Year
DOI
Venue
2009
10.1109/ICDE.2009.210
ICDE
Keywords
Field
DocType
peer-based database management system,initial query evaluation plan,statistical data,adaptive query processing strategy,extensive performance study,adaptive multi-join query processing,network traffic,current plan dynamically,optimize query,indexing,p2p,database systems,database management systems,database management system,distributed databases,adaptive systems,distributed database,statistical analysis,databases
Query optimization,Data mining,Web search query,Query language,Information retrieval,Query expansion,Computer science,Sargable,Web query classification,Spatial query,Database,Boolean conjunctive query
Conference
ISSN
Citations 
PageRank 
1084-4627
2
0.38
References 
Authors
12
4
Name
Order
Citations
PageRank
Sai Wu195459.08
Quang Hieu Vu254224.63
Jianzhong Li33196304.46
Kian-Lee Tan46962776.65