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Reseach Article

Implementing Semantic Query Optimization in Relational Databases

by Jyoti Mor, Indu Kashyap, R. K. Rathy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 52 - Number 9
Year of Publication: 2012
Authors: Jyoti Mor, Indu Kashyap, R. K. Rathy
10.5120/8234-1395

Jyoti Mor, Indu Kashyap, R. K. Rathy . Implementing Semantic Query Optimization in Relational Databases. International Journal of Computer Applications. 52, 9 ( August 2012), 41-46. DOI=10.5120/8234-1395

@article{ 10.5120/8234-1395,
author = { Jyoti Mor, Indu Kashyap, R. K. Rathy },
title = { Implementing Semantic Query Optimization in Relational Databases },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 52 },
number = { 9 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 41-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume52/number9/8234-1395/ },
doi = { 10.5120/8234-1395 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:52:21.742515+05:30
%A Jyoti Mor
%A Indu Kashyap
%A R. K. Rathy
%T Implementing Semantic Query Optimization in Relational Databases
%J International Journal of Computer Applications
%@ 0975-8887
%V 52
%N 9
%P 41-46
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Semantic query optimization is applied to relational databases using the inductive learning approach. This approach generates an alternate query using the learning framework and the algorithm. The alternate query should be semantically equivalent to original query. The semantically equivalent query generated should be less expensive than the original query. These can be implemented in SQL using the SQL hints. These hints allow user to implement the desired plan for the query.

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Index Terms

Computer Science
Information Sciences

Keywords

Semantic query semantic query optimization SQL hints inductive learning algorithm for learning learning framework