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The Query Clustering Problem: A Set Partitioning Approach
December 1995 (vol. 7 no. 6)
pp. 885-899
ASCII Text
x 
 
Ram D. Gopal, R. Ramesh, "The Query Clustering Problem: A Set Partitioning Approach," IEEE Transactions on Knowledge and Data Engineering, vol. 7, no. 6, pp. 885-899, December, 1995.
 
 
BibTex
x
 
@article{ 10.1109/69.476495,
author = {Ram D. Gopal and R. Ramesh},
title = {The Query Clustering Problem: A Set Partitioning Approach},
journal ={IEEE Transactions on Knowledge and Data Engineering},
volume = {7},
number = {6},
issn = {1041-4347},
year = {1995},
pages = {885-899},
doi = {http://doi.ieeecomputersociety.org/10.1109/69.476495},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Knowledge and Data Engineering
TI - The Query Clustering Problem: A Set Partitioning Approach
IS - 6
SN - 1041-4347
SP885
EP899
EPD - 885-899
A1 - Ram D. Gopal,
A1 - R. Ramesh,
PY - 1995
KW - Batch processing
KW - clustering techniques
KW - combinatorial optimization
KW - join operator
KW - query clustering relational databases
KW - set partitions.
VL - 7
JA - IEEE Transactions on Knowledge and Data Engineering
ER -
 

Abstract—In this research, we address the query clustering problem which involves determining globally optimal execution strategies for a set of queries. The need to process a set of queries together often arises in deductive database systems, scientific database systems, large bibliographic retrieval systems and several other database applications. We address the optimization problem from the perspective of overlaps in data requirements, and model the batched operations using a set-partitioning approach In this model, we first consider the case of m queries each involving a two-way join operation. We develop a recursive methodology to determine all the processing strategies in this case. Next, we establish certain dominance properties among the strategies, and develop exact as well as heuristic algorithms for selecting an appropriate strategy. We extend this analysis to a clustering approach, and outline a framework for optimizing multiway joins. The results show that the proposed approach is viable and efficient, and can easily be incorporated into the query processing component of most database systems.

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Index Terms:
Batch processing, clustering techniques, combinatorial optimization, join operator, query clustering relational databases, set partitions.
Citation:
Ram D. Gopal, R. Ramesh, "The Query Clustering Problem: A Set Partitioning Approach," IEEE Transactions on Knowledge and Data Engineering, vol. 7, no. 6, pp. 885-899, Dec. 1995, doi:10.1109/69.476495
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