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A Materialized View for the Same Generation Query in Deductive Databases

机译:演绎数据库中同代查询的物化视图

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Traditionally, deductive databases are designed as extensions to relational databases by either integrating a logic programming language, such as PROLOG, with a conventional relational database system that provides storage persistence needed for any database system, or by integrating an expert system with a relational database system. Deductive databases take advantage of a special kind of rule recursion called linear recursion to provide inference capabilities to improve the intelligence of the database system. The simplicity of implementation of linear recursive rules, like same generation rules, is far from the difficulty and the cost of computing the results of queries based on these recursive rules. Thus, to reduce costs and improve performance of the same generation queries, many techniques were suggested. In this paper, we propose the use of materialized views to speed up the evaluation of these queries and explain how to maintain the materialized view if the underlying base relation is updated. Finally, simulations are used to compare the materialized view approach with other approaches that are used to compute the results of the same generation queries.
机译:传统上,通过将逻辑编程语言(例如PROLOG)与提供任何数据库系统所需的存储持久性的常规关系数据库系统集成在一起,或通过将专家系统与关系数据库系统集成在一起,将演绎数据库设计为关系数据库的扩展。 。演绎数据库利用一种称为线性递归的特殊规则递归来提供推理功能,以提高数据库系统的智能性。与相同的生成规则一样,线性递归规则的实现简单性也远非基于这些递归规则计算查询结果的难度和成本。因此,为了降低成本并提高同代查询的性能,提出了许多技术。在本文中,我们建议使用实例化视图来加快对这些查询的评估,并说明如果基础基础关系已更新,则如何维护实例化视图。最后,使用模拟将物化视图方法与用于计算同一代查询结果的其他方法进行比较。

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