Caching frequently asked queries is an effective way to improve the performance of both centralized and distributed databases. Intensive works have been done in this area to propose different query caching techniques and to evaluate the performance of these techniques. However, most of these works were confined to caching previous query results in a single-level caching architecture. Evaluations of these techniques were based on simulations. In this paper, we briefly discuss our innovative technique for caching both query results and execution plans in a multi-level caching architecture. Then we also present an analytical model to evaluate the performance of the proposed technique and compare it to the traditional query optimizer.
Software And Hardware
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL