Architecture of Automated Database Tuning Using SGA Parameters

Business Data always growth from kilo byte, mega byte, giga byte, tera byte, peta byte, and so far. There is no way to avoid this increasing rate of data till business still running. Because of this issue, database tuning be critical part of a information system. Tuning a database in a cost-effectiv...

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Bibliographic Details
Main Authors: Hitesh KUMAR SHARMA, Aditya SHASTRI, Ranjit BISWAS
Format: Article
Language:English
Published: Bucharest University of Economic Studies 2012-05-01
Series:Database Systems Journal
Subjects:
Online Access:http://www.dbjournal.ro/archive/7/7_1.pdf
Description
Summary:Business Data always growth from kilo byte, mega byte, giga byte, tera byte, peta byte, and so far. There is no way to avoid this increasing rate of data till business still running. Because of this issue, database tuning be critical part of a information system. Tuning a database in a cost-effective manner is a growing challenge. The total cost of ownership (TCO) of information technology needs to be significantly reduced by minimizing people costs. In fact, mistakes in operations and administration of information systems are the single most reasons for system outage and unacceptable performance [3]. One way of addressing the challenge of total cost of ownership is by making information systems more self-managing. A particularly difficult piece of the ambitious vision of making database systems self-managing is the automation of database performance tuning. In this paper, we will explain the progress made thus far on this important problem. Specifically, we will propose the architecture and Algorithm for this problem.
ISSN:2069-3230