演绎数据库中语义查询的动态优化算法

演绎数据库的语义查询优化是利用数据库中的完整性约束，将用户提交的查询转换为与原查询等价且执行效率更高的查询规则。该文提出的动态语义优化算法在查询计算过程中动态约去存在的空展开式，使得查询时间开销的节省可用所除去的空展开式规模大小衡量，较适用于含有大量空展开式的演绎数据库。     

演绎数据库中的语义查询优化方法

语义查询优化的目的是使用语义知识来进行有效的查询，以提高查询效率，通过语义编译和语义转换，把一个查询转换成一个或多个更为有效的等价查询。本文介绍在演绎数据库中语义查询优化方法。     

一种自底向上的静态语义查询优化算法

演绎数据库语义查询优化是运用数据库中的语义知识，即完整性约束条件，将用户提交的一种查询转换为能有效执行，并与原查询等价的查询的一种优化方法．至今在这一领域已有了许多的算法，但大多是基于自顶向下的查询计算模式．而本文提出的静态语义查询优化算法及其改进算法是在优化“并”和“连接”操作的过程中进行自底向上的查询计算，因此相对自顶向下的计算方式更有效地提高了查询执行效率．     

语义查询优化技术研究综述

1.引言传统的查询优化器利用语法变换对查询进行优化,从生成的查询计划中选择一个具有最小代价的执行计划。然而,随着数据库技术和网络技术的发展,尤其是在异构数据库环境下和面向对象的数据库中,处理的对象结构更为复杂,传统的查询优化器显得力不从心。语义查询优化利用数据库上的语义规则将一个查询变为一个语义等价且更加高效地查询,以此来弥补传统查询优化技术的不足。虽然,语义查询优化能够产生较好的优化效果,但必须有效地解决以下一些问题:     

自适应的数据库查询缓存

传统的缓存采取较为机械的管理方法,不能随数据库运行的动态信息调整自身参数以得到更优的性能。数据库语义缓存能够让数据库“理解”查询语义,可以为数据库的动态调节提供信息。而查询缓存是语义缓存的一种,在 SQL解析与查询执行之间,通过研究查询缓存的自主管理来提高数据库的查询性能。首先介绍了数据库常用的语义缓存与自主计算,然后对查询缓存进行了形式化定义,并提出了自适应的查询缓存模型。最后在MySQL的查询缓存上进行了实验,得到了较好的效果。     

并行数据库查询优化技术的最新进展

传统的查询树及基于多重加权树的查询优化方法,研究得比较成熟,语义查询优化方法将一个查询变换成一个或数个语义等价的查询,基于Agent的并行数据库查询优化采用Multi-Agent技术自动查找与给定查询有关的完整性约束条件,使得多个关系间连接操作的效率得到很大地提高.并行数据库的查询优化领域的3个重要方向为基于机群系统的并行数据库查询优化研究,将MAS技术及专家系统引入本领域,将模拟退火算法及神经网络算法引入本领域.     

面向海量数据统计分析查询的中间层语义缓存

海量数据库应用系统中对统计分析查询进行优化,缩短查询响应时间是系统性能提高的关键。中间层语义缓存提供了一种优化海量数据统计分析性能的途径。文章通过对中间层语义缓存的研究,提出了一个适合海量数据统计分析的中间层语义缓存解决方案。     

数据库查询优化技术的历史、现状与未来

传统的查询树优化方法,即基于左线性树、右线性树、浓密树、操作森林的并行数据库查询优化方法,各有优劣,对其的研究比较深入、成熟;基于多重加权树的查询优化方法,研究了其并行查询计划模型、并行查询计划的复杂性模型和查询优化算法;语义查询优化方法将一个查询变换成一个或数个语义等价的查询,进而寻找并执行这些等价查询中具有较好实现策略的一个;基于Agent的并行数据库查询优化采用Multi-Agent技术自动查找与给定查询有关的完整性约束条件,使得多个关系间连接操作的效率得到很大的提高;基于遗传算法的并行优化算法,深入研究了基于机群并行数据库中关系存储的选择、多连接查询优化和查询处理等关键技术。     

基于语义相似度的数据库自适应查询松弛方法

为了解决数据库空查询结果问题,提出了一种基于语义相似度的数据库自适应查询松弛方法.首先,基于初始查询条件和数据分布推测用户对查询指定属性的重视程度,据此提出了一种属性权重评估方法;然后,通过考察属性值的特征信息,分别提出了分类型属性值之间和数值型属性值之间的语义相似度评估方法;在此基础上,根据松弛阈值、属性权重和属性值...     

复杂对象数据库的递归查询语义

本文用代数规范方法定义了复杂对象数据库中的对象标识、对象值、查询谓词和数据库状态语义，通过对查询路径的分析，给出了个体对象查询条件匹配的语义，特别是在个体对象上施用递归查询的语义，最后，给出了ＯＯＤＢ中选择操作的语义。     

演绎数据库系统中推理机的设计与实现

演绎推理是有效实现演绎数据库系统的关键与核心，该文针对一种结构合理的演绎数据库系统的设计方案，介绍了系统中实现递归查询的推理机的设计原理及实现过程中用到的优化技术，并对推理机的运行机制进行了分析。     

DECLARE and SDS: Early efforts to commercialize deductive database technology

The Smart Data System (SDS) and its declarative query language, Declarative Reasoning, represent the first large-scale effort to commercialize deductive database technology. SDS offers the functionality of deductive reasoning in a distributed, heterogeneous database environment. In this article we discuss several interesting aspects of the query compilation and optimization process. The emphasis is on the query execution plan data structure and its transformations by the optimizing rule compiler. Through detailed case studies we demonstrate that efficient and very compact runtime code can be generated. We also discuss our experiences gained from a large pilot application (the MVV-expert) and report on several issues of practical interest in engineering such a complex system, including the migration from Lisp to C. We argue that heuristic knowledge and control should be made an integral part of deductive databases.     

Partial evaluation of queries in deductive databases

This paper presents some applications of partial evaluation method to a query optimization in deductive database. A Horn clause transformation is used for the partial evaluation of a query in an intensional database, and its application to multiple query processing is discussed. Three strategies are presented for the compatible case, ordered case and crossed case. In each case, partial evaluation is used to preprocess the intensional database in order to obtain subqueries which direct access to an extensional database.     

Processing negation and disjunction in logic programs through integrity constraints

Integrity constraints were initially defined to verify the correctness of the data that is stored in a database. They were used to restrict the modifications that can be applied to a database. However, there are many other applications in which integrity constraints can play an important role. For example, the semantic query optimization method developed by Chakravarthy, Grant, and Minker for definite deductive databases uses integrity constraints during query processing to prevent the exploration of search space that is bound to fail. In this paper, we generalize the semantic query optimization method to apply to negated atoms. The generalized method is referred to assemantic compilation. This exploration has led to two significant results. First, semantic compilation provides an alternative search space for negative query literals. The alternative search space can find answers in cases for which negation-as-finite-failure and constructive negation cannot. Second, we show how semantic compilation can be used to transform a disjunctive database with or without functions and denial constraints without negation into a new disjunctive database that complies with the integrity constraints.     

An Extension to GCWA and Query Evaluation for Disjunctive Deductive Databases

We present a simple and intuitive extension GCWA^G of the generalized closed world assumption (GCWA) from positive disjunctive deductive databases to general disjunctive deductive databases (with default negation). This semantics is defined in terms of unfounded sets and possesses an argumentation-theoretic characterization. We also provide a top-down procedure for GCWA^G, which is sound and complete with respect to GCWA^G. We investigate two query evaluation methods for GCWA^G: database partition, and database splitting. The basic idea of these methods is to divide the original deductive database into several smaller sub-databases and the query evaluation in the original database is transformed into the problem of query evaluation in smaller or simplified components. We prove that these two methods of query evaluation are all sound with respect to GCWA^G.     

时态演绎数据库—模型与查询语言

时态演绎数据库是引入有效时间、事务时间概念的演绎数据库,能比较真实地反映现实世界的现象和发展状况,因此能满足现在的许多应用,如规划、决策支持系统、医疗信息系统等,因为这些应用不仅需要当前的数据,也需要历史数据     

DOL: 一个演绎对象库语言

演绎对象数据库是对象数据模型和演绎数据库集合的产物.它集成演绎数据库的查询能力和对象数据库的强大建模能力.DOL(deductive object base language)是作者设计的一种演绎对象库语言,它支持类、类层次、继承、集合、部分集、方法及重载和否定.文章着重研究继承、重载和复杂结构化值的交互关系.定义了压缩操作子和重载操作子.基于这两个操作子,定义了与经典逻辑程序类似的直接后承操作子,并研究其不定点性质.     

A basis for deductive database systems II

This paper is the third in a series providing a theoretical basis for deductive database systems. A deductive database consists of closed typed first order logic formulas of the form A ← W, where A is an atom and W is a typed first order formula. A typed first order formula can be used as a query, and a closed typed first order formula can be used as an integrity constraint. Functions are allowed to appear in formulas. Such a deductive database system can be implemented using a PROLOG system. The main results of this paper are concerned with the nonfloundering and completeness of query evaluation. We also introduce an alternative query evaluation process and show that corresponding versions of the earlier results can be obtained. Finally, we summarize the results of the three papers and discuss the attractive properties of the deductive database system approach based on first order logic.