Performance Optimization for Distributed Database Based on Cache Investment

Sanju Gupta, Swati V Chande

Abstract


As technology plays important role in every aspect of life especially in the industrial field, a vast amount of data is generated for controlling and monitoring tools and to help in system development. That results in an increased size of data, which affects the speed and performance of applications/programs. Here a design strategy is proposed to show how to improve both the speed and performance of computer applications by improving the performance of database queries. Key factors that determine computer performance (speed and performance of the processor) are the processor speed, the size of RAM, and the cache memory strategy for the processor. In this paper, we are introducing a solution that is proven to be a tool to increase the performance of queries. It will help to enhance the performance of database queries responsiveness irrespective of the database size. The proposed policy is built-up on the caching concepts i.e. cache investment. Cache investment is a method to combine query optimization and data placement. This work on the concept of investment looks beyond the performance of a single query and helps in achieving a better hit ratio in a long term for large database systems. This paper, discuss and explain the design, architecture and working of the proposed policy. The results show how this proposed policy helps in improving the performance of the database, especially relevant for today’s “big data” environment.


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