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Title: A Database Optimization Model with Quantitative Benchmark
Authors: Jayakody, J.A.D.C.A.
Lokuliyana, S.
Herrmann, J.
Kandawala, D.S.A.
Murray, I.
Nanayakkara, S.E.C.
Keywords: database optimization
query optimization
quantitative evaluatio
Issue Date: 2016
Publisher: ICCTICT 2016
Abstract: Query optimization and in dexing have an immense impact on database optimization. This has been considered in many different perspectives which provide several different solutions in each case. The purpose of this paper is to primarily provide a comprehensive review and discussion of the core problems through the research on query optimization technology and indexing, based on a number of optimization techniques commonly used in the general approach of a query. A new database optimization model is designed and experiments show that this model can significantly reduce the amount of query execution time to improve the optimization effici ency. Regardless of research on the database optimization model, significant work has been done to comparatively evaluate three scenarios; non-optimized query, optimized query without following any optimization standard, and optimized query via proposed opti mization model using the same experimental methodology. Furt her, this paper describes a benchmark that was developed specifically for the purpose of measuring the quantitative evaluati ons of the proposed database optimization model.
ISSN: 978-1-5090-0082-1/16/
Appears in Collections:Miscellaneous/Information Technology

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