Query Optimization using Multiple Techniques

Query optimization is the overall process of choosing the most efficient means of executing a SQL statement. The optimizer attempts to generate the best execution plan for a SQL statement. The best execution plan is defined as the plan with the lowest cost among all considered candidate plans. SQL is a nonprocedural language, so the optimizer is free to merge, reorganize, and process in any order. The cost is a number that represents the estimated resource usage for an execution plan. The cost computation accounts for factors of query execution such as I/O, CPU, and communication. To implement query optimization methods such as Heuristic Greedy based optimization, Iterative Improvement based cost optimization and Ant Colony optimization algorithms. Show Comparison of cost, execution time and response time between Heuristic Greedy based optimization; Ant Colony Optimization and Iterative Improvement based cost optimization algorithms. Keywords Query Optimization, Heuristic-based optimizers, Ant-Colony 1. INTRODUCTION Query processing denotes to the range of activities elaborate in retrieve data from databases. The activities involve translation of queries in high-level database languages into looks that can be used at the objective level of the file system, a range of query-optimizing changes, and actual evaluation of queries [4]. Query process is the method by which the query results are retrieved from a high-level query like SQL or OQL. Generally, the query optimizer can't be accessed directly by any users, after queries are accepted to database server, and construed by the parser, then passed to the query optimizer where optimization happens. There are three parts that a query passes over during the DBMS’ processing of that query: Parsing and translation 
 Optimization