From there on, the same query decomposition, optimization and execution steps are performed as described above. 从此时开始,将执行与以上所述相同的查询分解、优化和执行步骤。
As the core module of the system, the query control sub-system adopts the query decomposition theory. 作为R-SQL系统的核心模块,查询调度子系统采用了基于查询分解技术的设计思想。
Through the research on the Picture Archiving and Communication System ( PACS), and medical image archiving and query by content, a new algorithm based on multiscale wavelet decomposition and human vision model was presented. 通过对基于图像内容的查询以及医学图像数据库领域知识的研究,提出了基于小波多尺度边缘的尺度综合和模拟人类视觉心理学特点的医学图像归档及查询方法。
The detail design and implement of key parts in each module is also given, which include Global mode integration, query language conversion, query decomposition, query plan definition and local data source access. 接着给出了各模块中的关键部件的详细设计与实现,主要包括:全局模式集成,查询语言的转换,查询的分解,子查询计划的定义,局部数据源访问。
In the base of the principles of multidatabase's data model, the integrated data model of Engineering database is presented in this paper to meet the needs of practice, and a global query decomposition algorithm based on this model is designed and implemented. 该文在借鉴多数据库模式结构划分原理的基础上,根据实际应用的需要,提出了基于多数据库的工程数据库集成模式结构,并且设计和实现了基于该结构的工程数据库查询分解算法。
The paper introduces the steps of query process, gives the particular way of the query decomposition, and also analyses the query optimize method. 介绍了查询处理的步骤,给出了查询分解的具体方法,并对查询的优化问题进行研究分析。
Query Optimization mainly considered on four aspects: optimizing the query decomposition, optimizing the system, optimizing the query plan, analyzing the impact of network transmission to the query operation. 查询优化主要从四个方面进行考虑:对查询分解的优化、在系统架构上作优化处理、对查询计划的优化、分析网络传输对查询操作的影响。
At last, query decomposition and query plan optimization is described. 最后描述了Gav模式集成方式下的查询分解和优化方法。
This paper introduces an integration system model based on semi-structured data model, and describes the method of query rewriting and decomposition. 该文介绍了基于半结构化数据模型的异构数据源联合使用的实现,描述了其中的查询重写和查询分解的方法。
Then, it defines XML Extent and other conceptions, and proposes an XML path expression query algorithm named XML EMJ, gives the processing including path query decomposition and transformation, path query optimization. Four indices are discussed. 接着定义了XML外延、XML限定外延等概念,提出一种XML路径表达式查询算法&外延多路连接算法,讲述了该算法中路径查询分解与转换、路径查询优化的过程,并引入四种索引结构。
An Aggregation Partition-based Query Decomposition Method for Distributed Databased 基于集合划分的分布式数据库查询分解算法
Research on Integrated Data Model and Query Decomposition in Engineering Database Based on Multidatabase 基于多数据库的工程数据库模式集成与查询分解的研究
Semantic analyse of data request, query decomposition and conversion rules are introduced in detail. 详细介绍了数据交换引擎中数据请求的语义分析、查询分解、构建转换规则等功能模块的作用及工作原理。
An optimize algorithm of query decomposition wtih association matrix 使用关联矩阵的查询优化算法
Explore the query interface and query decomposition strategy. 探讨了基于抽象数据视图的全局查询以及查询分解的策略。
Then by making use of the mapping rules from local Ontology to global Ontology, the query tree is decomposed into sub-trees, and the query decomposition algorithm is also presented. 通过对查询语言的解析,建立查询树,然后根据从局部本体到全局本体的映射规则,该查询树被分解为对局部数据源的子查询,提出了查询分解的具体算法。
Query decomposition processing is a key problem in multidatabase systems. 全局查询分解处理是多数据库系统中的一个很重要的问题。
As the key function of information integration, heterogeneous data access system presents a SQL-like query language, and realizes the analysis, decomposition and optimization of the query language. 作为信息集成的核心,异构数据访问系统提出了一种类SQL的查询语言,并实现了查询语言的解析,分解和优化等工作。
Query processing contains parsing of global query, binding of query variable, decomposition of query and rewriting of query. 查询处理包括全局查询语句解析、查询变量绑定、查询分解和查询重写。
Query Optimization: the application of query optimization rules between query decomposition and query transformation. 7. 查询优化:查询分解及查询转换过程中的查询优化规则的应用。
The first phase is the query decomposition process. 第一阶段为查询分解阶段。
First of all, it introduces the way of building the global ontology and the local ontology. According to the mapping rules from local ontology to global ontology, it decomposes the global ontology query to the local ontology sub-query and gives the query decomposition algorithm. 首先研究了全局本体与局部本体的构建方法,根据局部本体到全局本体的映射规则,把针对全局本体的查询语句分解为对局部本体的子查询,并给出了查询分解算法。