空间查询语言GSQL的研究与实现

针对关系数据库操纵语言SQL不能处理复杂的空间数据类型的问题,在SQL基本原理的基础上,结合OGIS(开放式地理信息系统)协会提出的空间数据模型,提出了空间查询语言GSQL,并设计了查询解释器,实现了对空间数据的各种空间分析运算,并能够对空间和属性数据进行联合查询。     

基于SQL Server的演绎规则处理器

设计并实现了一种基于SQLServer的演绎规则处理器,其主要功能是把演绎规则转换为含有SQL语句的过程代码,利用该处理器用户可用一阶逻辑谓词定义和查询IDB关系。     

空间查询语言GSQL及其解释器的研究与设计

空间查询语言是空间数据库与应用软件的接口,但由于传统的SQL不支持空间数据类型而对空间查询语句无能为力.本文在OpenGIS SQL的基础上,对空间查询语言GSQL进行研究,并对其解释器进行详细的研究和设计.     

浅析SQL语言在数据库中的应用

SQL是一种结构化的查询语言,是一种用在数据库查询上和有关程序设计的语言,SQL语言大多用在存取、查询、更新和删除方面的数据库系统,同时它也是数据库里脚本文件的扩展名。SQL作为一种高级的编程语言,是数据库服务器和客户端相互沟通的重要工具。SQL语言作为一种访问和操作数据库的计算机语言,也可以协同数据库程序一起工作。在数据库的应用过程中,数据库的查询工作是不可避免的,也是数据库应用中很重要的一个方面,在这个关键的应用上,SQL语言的作用是很重要的。所以,本文就SQL语言在数据库中的应用做相关的分析。     

非一致数据库的查询研究

提出的方法能灵活地进行数据库SQL查询,它可以干扰一系列的约束条件,并且这种方法能够允许用户假定一组约束和查询一起。系统重写这个查询去查找相应的与约束一致的数据。这个重写是SQL,以便能被商业数据库系统有效地优化和执行。使用TPC-H基准的数据和查询比较脏数据多粒度的执行性能,实验显示该方法是可行的。     

SQL模糊查询的运用分析

在关系型数据库中SQL语句是一个强大的工具,可以用来实现数据库的查询。本文针对SQL模糊查询进行了分析,并提出了SQL简单模糊查询在使用中存在的一些问题。     

DOOL程序语义等价转换为Datalog 程序的转换规则

演绎对象数据库(DOOD)是演绎数据库与面向对象数据库两者优点相结合的产物。笔者设计实现了一个演绎对象数据库系统原型SD-DOOD,它是基于演绎数据库系统SD-DDBS的。然而,它使用的是演绎对象库语言DOOL,而演绎数据库语言是基于Datalog的,因此该文提出了应用一些转换规则来将DOOL程序转换为Datalog,通过规则转换,能求出DOOL程序的最小不动点(即程序值),从而使得系统的查询操作全都由SD-DDBS最终得出结果。文中详细介绍了转换规则的具体内容。     

用VBA实现Access的查询

在Access中,要设计一个查询程序是十分快捷的。它提供的查询向导,可以一步步地引导程序员迅速建立查询,并可用SQL及Design方式查看。另外,它所提供的Query Defs对象,则可以方便地用VBA编制出基于特殊要求的查询程序。 下面三个例子就是用VBA实现查询功能的程序。     

SQL分组查询的教学探讨

SQL分组查询是SQL数据查询语句的一个教学难点。首先分析了学生在学习分组查询时存在的主要问题,然后结合实际教学经验,提出了一种通过对分组查询实例的执行过程进行分析来学习分组查询的教学方法,初步实践表明可以有效提高SQL分组查询的教学效果。     

嵌入式数据库中利用Lex,Yacc设计SQL编译器

随着嵌入式数据库系统的不断发展,对其数据查询的能力提出了新的要求。基于自行设计的嵌入式数据库系统,利用Lex和Yacc工具实现了嵌入式SQL编译器的设计,进一步对所生成的语法树进行了初步的优化研究。结果表明此编译器大大增强支持SQL查询语言的能力。     

基于Ontology的数据库自然语言查询接口的研究

提出了一种基于Ontology的关系数据库自然语言查询接口的系统模型及设计框架.采用WordNet作为基本数据库并在WordNet之上定义领域词库,可以提高语法分析的识别率;同时利用Ontlogly知识表达能力存储关系数据库概念模型,并对概论模型的内容进行扩充;另外对Ontology和WordNet的同义词集进行关联,可以提高语义的识别率.用户的输入查询语句通过语法分析、语义分析生成中间表达式语言DRS,然后通过模板技术转换成SQL,通过DBMS执行SQL并返回结果.实验证明,这种方案不但实用可行,而且通过逐步完善Ontology知识库的定义,可以大大提高查询的命中率;另外通过WordNet和Ontology定义领域词库和领域知识,提高了系统的可移植性.最后,所提供的方法可以很容易地移植到其他领域.     

A Hybrid Fragmentation Approach for Distributed Deductive Database Systems

Fragmentation of base relations in distributed database management systems increases the level of concurrency and therefore system throughput for query processing. Algorithms for horizontal and vertical fragmentation of relations in relational, object-oriented and deductive databases exist; however, hybrid fragmentation techniques based on variable bindings appearing in user queries and query-access-rule dependency are lacking for deductive database systems. In this paper, we propose a hybrid fragmentation approach for distributed deductive database systems. Our approach first considers the horizontal partition of base relations according to the bindings imposed on user queries, and then generates vertical fragments of the horizontally partitioned relations and clusters rules using affinity of attributes and access frequency of queries and rules. The proposed fragmentation technique facilitates the design of distributed deductive database systems. Received 4 August 1999 / Revised 30 March 2000 / Accepted in revised form 6 October 2000     

基于SQL Server 2000的通用模糊查询工具设计

本文设计并实现了一个基于SQL Server 2000的通用模糊查询工具,该工具可以把带权重的模糊查询转换为标准的SQL语句。用户可以对SQL Server中建立的任何数据库表进行模糊查询。系统提供了以下功能：定义模糊谓词及其隶属函数;定义模糊算子;构造带权重的模糊的、精确的或混合的查询语句,权重和阈值可以由用户给出。满足查询条件的记录将根据匹配度的降序输出。本系统的设计方法也可以推广到其他的数据库系统,如Oracle,Access等。     

基于文件存储GIS的SQL解析器的设计与实现

针对利用文件存储的GIS系统不能自动实现查询这一问题，结合SQL-99标准和GIS软件MAPGIS定义的语法规则，运用编译原理中的词法分析、语法分析等理论，实现了将用户输入的普通查询表达式解释为一个标准的SQL语句，并输出查询结果。该SQL解析器已经成功地运用在MAPGIS文件管理的属性检索模块中。     

An inductive database system based on virtual mining views

Inductive databases integrate database querying with database mining. In this article, we present an inductive database system that does not rely on a new data mining query language, but on plain SQL. We propose an intuitive and elegant framework based on virtual mining views, which are relational tables that virtually contain the complete output of data mining algorithms executed over a given data table. We show that several types of patterns and models that are implicitly present in the data, such as itemsets, association rules, and decision trees, can be represented and queried with SQL using a unifying framework. As a proof of concept, we illustrate a complete data mining scenario with SQL queries over the mining views, which is executed in our system.     

多媒体对象查询语言及其查询处理

文章研究了多媒体数据库的查询需求,提出结构化的多媒体对象查询语言MOQL(multi-media object query language).它能够支持基于类型、结构特征、同步关系、时态关系和内容信息的多媒体查询.以DB2数据库为存储机制,定义了一组代数算子和变换规则,利用它们可以将用户定义的MOQL查询变换为代数表达式,进行代数优化,并将代数查询表达式转换为能够在DB2数据库上运行的DB2SQL和C++查询过程.     

Coupled Transformation of Schemas, Documents, Queries, and Constraints

Coupled transformation occurs when multiple software artifacts must be transformed in such a way that they remain consistent with each other. For instance, when a database schema is adapted in the context of system maintenance, the persistent data residing in the system's database needs to be migrated to conform to the adapted schema. Also, queries embedded in the application code and any declared referential constraints must be adapted to take the schema changes into account. As another example, in XML-to-relational data mapping, a hierarchical XML Schema is mapped to a relational SQL schema with appropriate referential constraints, and the XML documents and queries are converted into relational data and relational queries. The 2LT project is aimed at providing a formal basis for coupled transformation. This formal basis is found in data refinement theory, point-free program calculation, and strategic term rewriting. We formalize the coupled transformation of a data type by an algebra of information-preserving data refinement steps, each witnessed by appropriate data conversion functions. Refinement steps are modeled by so-called two-level rewrite rules on type expressions that synthesize conversion functions between redex and reduct while rewriting. Strategy combinators are used to composed two-level rewrite rules into complete rewrite systems. Point-free program calculation is applied to optimized synthesize conversion function, to migrate queries, and to normalize data type constraints. In this paper, we provide an overview of the challenges met by the 2LT project and we give a sketch of the solutions offered.     

Query by class,rule, and concept

The ideal query language for a knowledge base will probably never be found: easy formulation and easy evaluation of queries are two conflicting goals. Easy formulation asks for a flexible, expressive language near to human language or gestures. Easy evaluation of queries requires an effective mapping to machine code, which computes the correct answer in a finite number of steps. This article approaches the problem by a query language with three faces. The first projects queries to concepts of the knowledge representation language KL-One for easy formulation and readability. The second presents queries as rules of a deductive database with fixpoint semantics. The third presents queries as classes whose instances are the materialized answer (view) to the query. The methods for maintaining and updating the views are compiled from their deductive interpretation.     

Ultrawrap: SPARQL execution on relational data

The Semantic Web’s promise of web-wide data integration requires the inclusion of legacy relational databases,¹ i.e. the execution of SPARQL queries on RDF representation of the legacy relational data. We explore a hypothesis: existing commercial relational databases already subsume the algorithms and optimizations needed to support effective SPARQL execution on existing relationally stored data. The experiment is embodied in a system, Ultrawrap, that encodes a logical representation of the database as an RDF graph using SQL views and a simple syntactic translation of SPARQL queries to SQL queries on those views. Thus, in the course of executing a SPARQL query, the SQL optimizer uses the SQL views that represent a mapping of relational data to RDF, and optimizes its execution. In contrast, related research is predicated on incorporating optimizing transforms as part of the SPARQL to SQL translation, and/or executing some of the queries outside the underlying SQL environment.Ultrawrap is evaluated using two existing benchmark suites that derive their RDF data from relational data through a Relational Database to RDF (RDB2RDF) Direct Mapping and repeated for each of the three major relational database management systems. Empirical analysis reveals two existing relational query optimizations that, if applied to the SQL produced from a simple syntactic translations of SPARQL queries (with bound predicate arguments) to SQL, consistently yield query execution time that is comparable to that of SQL queries written directly for the relational representation of the data. The analysis further reveals the two optimizations are not uniquely required to achieve a successful wrapper system. The evidence suggests effective wrappers will be those that are designed to complement the optimizer of the target database.