Optimization of Association Rule in Horizontally Distributed Database using Unique Key Value

Abstract

proposed work describes the optimization of Association Rule for the distributed databases in terms of speed, memory used while transaction of distribution as well as extracting the data from various data sources in the network. The proposed work shall have two parts including distribution of data using Association rule and ensuring the search to be redirected to specific source based on key values used to create the sub set in association rule. The availability shall be tested by verifying if the specific source is ready or not if not the search for that part shall only be carried out on the server itself. KeywordsDatabases, Association rule, Database Mining, which is controlled by a distributed database management system (together sometimes called a distributed database system). Association rule learning is a method for discovering interesting relations between variables in large databases. It is intended to identify strong rules discovered in databases using different measures of interestingness. The proposed is the work including association rule in horizontally distributed databases in terms of homogeneous database. Prior to the existence of distributed databases the centralized databases were used in which the database is get stored in the centralized server and every node hits the query to the same database server and speed of data retrieval does get affected to solve the issue distributed databases comes into picture . The use of association rule helps to divide the entire database into different distinct computers so as to make it available all the time while the request shall be processed on a small set of data instead of entire large data. information secrete and secure. These databases help to improve the speed of retriaval and helps us to retrive the stored information from a very large databse with very less amount of time.