DocumentCode :
3123836
Title :
Adaptive Multi-join Query Processing in PDBMS
Author :
Wu, Sai ; Vu, Quang Hieu ; Li, Jianzhong ; Kian-Lee Tan
Author_Institution :
Sch. of Comput., Nat. Univ. of Singapore, Singapore
fYear :
2009
fDate :
March 29 2009-April 2 2009
Firstpage :
1239
Lastpage :
1242
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 However, these assumptions are no longer valid in a peer-based database management system (PDBMS).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 being processed, 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.
Keywords :
database management systems; peer-to-peer computing; query processing; statistical analysis; PDBMS; adaptive multijoin query processing; peer-based database management system; statistical data; Buildings; Data engineering; Database systems; Distributed computing; Distributed databases; Indexing; Peer to peer computing; Query processing; Runtime; Statistical distributions; Adaptive Multi-Join; P2P;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering, 2009. ICDE '09. IEEE 25th International Conference on
Conference_Location :
Shanghai
ISSN :
1084-4627
Print_ISBN :
978-1-4244-3422-0
Electronic_ISBN :
1084-4627
Type :
conf
DOI :
10.1109/ICDE.2009.210
Filename :
4812510
Link To Document :
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