Multi Query Optimization Algorithm Using Semantic and Heuristic Approaches
Multi Query Optimization Algorithm Using Semantic and Heuristic Approaches
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使用语义和启发式方法的多查询优化算法
DOI：
10.14257/ijdta.2016.9.6.22
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
I. .. Mohammed
中科院分区：
文献类型：
--
作者：
L. J. Muhammad;Yahaya Bala Zakariyau;A. Ali;I. .. Mohammed
多查询优化是关系数据库管理系统（RBMS）中最重要的任务之一，随着在线决策支持系统在各行各业的广泛应用，多查询优化变得越来越普遍。在多查询优化中，查询是成批优化和执行的。然而，有许多算法用于检测和统一多个查询之间的公共子表达式，并统一它们，使得执行更包含的子表达式，并从其导出其他子表达式。在这项工作中，多查询优化算法，使用语义学和语义的方法提出和编码SQL Server版本10.0.1600和三个查询之间的实验所提出的算法和最新的基本多查询优化算法（火山RU）。实验结果表明，与火山RU算法相比，该算法在所有三种查询上都给出了最优的查询计划，并且在执行时间和CPU时间方面都是最优的。
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.