Please use this identifier to cite or link to this item:
https://doi.org/10.1109/ICDE.2009.210
Title: | Adaptive multi-join query processing in PDBMS | Authors: | Wu, S. Vu, Q.H. Li, J. Tan, K.-L. |
Issue Date: | 2009 | Citation: | Wu, S.,Vu, Q.H.,Li, J.,Tan, K.-L. (2009). Adaptive multi-join query processing in PDBMS. Proceedings - International Conference on Data Engineering : 1239-1242. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDE.2009.210 | 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 However, these assumptions are no longer valid in a Peerbased DataBase Management System (PDBMS).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 areused 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. © 2009 IEEE. | Source Title: | Proceedings - International Conference on Data Engineering | URI: | http://scholarbank.nus.edu.sg/handle/10635/41573 | ISBN: | 9780769535456 | ISSN: | 10844627 | DOI: | 10.1109/ICDE.2009.210 |
Appears in Collections: | Staff Publications |
Show full item record
Files in This Item:
There are no files associated with this item.
SCOPUSTM
Citations
5
checked on May 20, 2022
Page view(s)
212
checked on May 12, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.