Architecture of Automated Database Tuning Using SGA Parameters
Journal Title: Database Systems Journal - Year 2012, Vol 3, Issue 1
Abstract
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.
Authors and Affiliations
Hitesh KUMAR SHARMA, Aditya SHASTRI, Ranjit BISWAS
Problem Decomposition Method to Compute an Optimal Cover for a Set of Functional Dependencies
The paper proposes a problem decomposition method for building optimal cover for a set of functional dependencies to decrease the solving time. At the beginning, the paper includes an overview of the covers of func...
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...
PL/SQL and Bind Variable: the two ways to increase the efficiency of Network Databases
Modern data analysis applications are driven by the Network databases. They are pushing traditional database and data warehousing technologies beyond their limits due to their massively increasing data volumes and...
Clustering Analysis for Credit Default Probabilities in a Retail Bank Portfolio
Methods underlying cluster analysis are very useful in data analysis, especially when the processed volume of data is very large, so that it becomes impossible to extract essential information, unless specific instrument...