Research Article
A Framework to Subquery Optimization using Case-based Reasoning
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 88 - Issue 2 |
| Published: February 2014 |
| Authors: Pragya Shukla, Sakshi Mathur |
10.5120/15324-3636
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Pragya Shukla, Sakshi Mathur . A Framework to Subquery Optimization using Case-based Reasoning. International Journal of Computer Applications. 88, 2 (February 2014), 27-31. DOI=10.5120/15324-3636
@article{ 10.5120/15324-3636,
author = { Pragya Shukla,Sakshi Mathur },
title = { A Framework to Subquery Optimization using Case-based Reasoning },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 88 },
number = { 2 },
pages = { 27-31 },
doi = { 10.5120/15324-3636 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Pragya Shukla
%A Sakshi Mathur
%T A Framework to Subquery Optimization using Case-based Reasoning%T
%J International Journal of Computer Applications
%V 88
%N 2
%P 27-31
%R 10.5120/15324-3636
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Query optimizers in current database management systems (DBMS) often face problems such as intolerably long optimization time and/or poor optimization results when optimizing complex subqueries using classical techniques [1]. There are computational environments where metadata acquisition and support is very expensive. A ubiquitous computing environment is an appropriate example where classical query optimization techniques are not useful any more. To tackle this challenge, we present a new similarity-based optimization technique using case-based reasoning in this paper[2]. The key idea is to identify cases of similar subqueries that often appear in a complex query and share the optimization result within each case in the query [3]. An efficient algorithm to identify similar queries in a given query and optimize the query based on similarity is presented. Our experimental results demonstrate that the proposed technique is quite promising in optimizing complex subqueries in a DBMS. It is possible to learn from each new experience in order to suggest better solutions to solve future queries.
References
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