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Multi Query Optimization is one of the most important tasks in Relational Database Management System (RBMS) and it becomes common due to high usage of online decision support management systems in every industry nowadays. In multi query optimization, queries are optimized and executed in batches. However, there are many algorithms use to detect and unified common sub-expressions among multiple queries and unified them so that the more encompassing sub- expression is executed and the other sub-expressions are derived from. In this work, multi-query optimization algorithm using heuristics and semantic approaches was proposed and encoded on SQL Server version 10.0.1600 and three queries were used for the experiment between the proposed algorithm and most recent basic Multi Query Optimization Algorithm (Volcano RU). The result of experiment showed that, Proposed Algorithm gave the best plans compared Volcano RU Algorithm, across all three queries and was best for all queries in terms of execution time and CPU time.

Multi Query Optimization Algorithm Using Semantic and Heuristic Approaches