基于XQuery处理器的异构数据集成中间件

利用中间件方式进行异构数据集成是异构数据集成研究的热点.针对目前中间件方式处理关系数据库数据与XML数据集成在查询易用性以及效率的不足,基于各数据源的数据格式以及存储方式,把异构数据源分成关系数据库数据源,XML数据源和非结构化数据源三类,对每一类用XML模式处理,构建虚拟视图,使待集成的异构数据源构建成一个逻辑数据库...     

网格环境下基于XML的异构数据集成系统

分析地震、地质行业的数据资源特点,在数据网格中间件OGSA-DAI基础上提出一种基于XML的分布异构数据访问与集成框架,实现数据的透明访问和联合查询。系统以XML作为公共数据模型,使用三层模式集成机制,以XQuery同时作为XML模式之间的映射语言及全局查询语言,简化全局视图的构造和系统的查询处理。     

科技数据集成系统中的查询处理

主要研究基于XML的数据集成中介器系统,继承传统的包装器/中介器架构模式,在多个分布式异构数据源上构建全局统一视图,以XQuery为查询语言,提供对外统一访问接口;并应用于集成异构科技数据源,整合离散科学数据资源,实现时科技数据资源的规范化管理和高效利用.     

基于XML的异构数据集成系统的查询处理

讨论了基于XML的Web异构数据源集成系统中的查询处理,并提出了针对全局视图的语义缓存的实现方法,包括查询与缓存入口的匹配算法,网络环境下缓存建立和淘汰算法;最后描述了Gav模式集成方式下的查询分解和优化方法。     

基于XML虚拟数据库的异构数据源集成模型研究

解决企业数据源异构需要一种公共的数据源模型给用户提供统一的用户视图,XML以其所具有的自描述性、灵活性、强大的数据交换能力等优势克服了其他数据模式的缺点.结合当前数据集成方面的技术,提出了一种基于XML虚拟数据库的异构数据源集成模型,该模型很好地解决了异构数据源集成方面存在的一系列问题,并从数据模型和数据交换上阐述了该模型的可行性.剖析了该模型中的模式集成、异构数据集成视图、全局查询等.介绍了该模型在中国石油QHSE信息系统中的成功应用.     

基于XML的多分支模式匹配算法

随着XML文档大量涌现,如何有效地管理和查询XML数据已经成为亟待解决的问题。在数据库中,基于视图的查询重写技术是查询优化的一个重要技术,利用缓存的视图结果回答新查询不需要访问源数据库进行查询,能够节省查询处理时间。本文在研究基于物化视图的查询重写的过程中,给定一个查询和一个视图,首先判断该查询在视图下是否存在查询重写,而重写的存在问题与模式包含问题密切相关,为此,提出使用多分支的模式匹配算法实现对多分支路径的模式匹配,解决重写是否存在的问题。     

异构数据的视图集成研究

视图集成是异构数据源集成问题的关键技术之一.论文引进XML技术,利用其作为一种数据格式描述的元语言标准的优势,改进了已有视图集成方法,采用XQuery语言建立了真正意义上的虚拟的全局视图,为异构数据集成访问奠定了基础.     

基于本体的XML语义集成和查询的研究

XML因其结构上的灵活性和易扩展性已经成为Web上异构数据转换和传输的标准,但是含有不同模式的XML数据源之间却很难进行相互操作,这给XML数据检索带来了更大的不便.先提出一种从XML模式到OWL本体的映射算法,然后借助共享全局本体和同义词典实现多个映射后的本体在语义上的集成从而解决XML结构异构的问题,最后提出一种利用语义集成进行XML语义查询的框架并初步实现.     

基于HGAV的多源异构数据集成方法

针对信息系统中海量数据多源异构和难以共享的问题, 提出了多源异构数据虚拟集成框架. 数据集成系统中的GAV(Global-as-View)模式映射方法面对信息量分布不均匀的数据源时, 查询效率较低, 在对GAV改进的基础上, 提出了基于HGAV(Hierarchical-Global-as-view)的模式映射算法, 通过引入中间数据源模式, 形成分层的全局视图, 大大缩减了映射空间, 简化了映射集合, 便于查询的重写和优化. 利用宁东智慧环保项目中的五大类数据对本文所提出的算法加以验证, 实验结果表明该算法相较于GAV模式映射算法提高了数据集成效率, 缩短了查询时间.     

基于移动Agent和XML的异构数据库集成模型研究

为了解决异构数据库的数据集成和共享问题,提出了一个基于移动Agent和XML的异构数据库集成模型:采用虚拟法和XML技术,建立了全局数据集成框架;同时,采用移动Agent技术,解决了局部数据库数据智能集成的问题,优化了查询处理模块,有效地提高了数据库的查询效率.     

XQuery视图机制

从XML数据安全性考虑，在已经使用XQuery作为查询语言的前提下，为增强XQuery对XML文档查询能力，创造了类似关系数据库视图的XQuery视图机制，使得不同用户对XML文档具有不同的查看能力，保证查询安全可靠。XQuery视图由查询来定义其内容，分为实视图和虚视图两种。虚视图根据需要计算视图定义的查询，而实视图不管以后是否需要，只要一创建就计算其视图定义，类似关系数据库视图，实视图和虚视图对于数据查询都是必要的。     

XQBE: A Graphical Environment to Query XML Data

XQuery, the standard query language for XML, is increasingly popular among computer scientists with SQL background, since XQuery and SQL require comparable skills. However, these experts are limited in number, and the availability of easier XQuery “dialects” could be extremely valuable. With this motivation in mind, we designed XQBE, a visual dialect of XQuery inspired by the QBE language (Query by Example). Coherent with the hierarchical nature of XML, XQBE uses one or more hierarchical structures to denote the input documents and one structure to denote the document produced in output. These structures are annotated to express selection predicates; explicit binding edges connecting the nodes of these structures visualize the input/output mappings. This paper presents XQBE through several examples and describes the main features of our implementation of the language, a visual editor coupled with an XQBE-to-XQuery translator. Indeed, the XQBE front-end is a general purpose user-friendly visual query interface, capable of providing access to any data storage system that exposes XQuery APIs. Available schema information can be exploited to guide users in querying data sets they are not familiar with. Also, switching between the visual and textual versions of the same query could be helpful for XQuery learners.     

Schema mapping and query translation in heterogeneous P2P XML databases

Peers in a peer-to-peer data management system often have heterogeneous schemas and no mediated global schema. To translate queries across peers, we assume each peer provides correspondences between its schema and a small number of other peer schemas. We focus on query reformulation in the presence of heterogeneous XML schemas, including data–metadata conflicts. We develop an algorithm for inferring precise mapping rules from informal schema correspondences. We define the semantics of query answering in this setting and develop query translation algorithm. Our translation handles an expressive fragment of XQuery and works both along and against the direction of mapping rules. We describe the HePToX heterogeneous P2P XML data management system which incorporates our results. We report the results of extensive experiments on HePToX on both synthetic and real datasets. We demonstrate our system utility and scalability on different P2P distributions.     

半结构化、层次数据的模式发现

Web数据资源及数据集成引发了半结构化数据问题,半结构化数据指其结构隐含或不规整的自描述数据。由于缺乏独立于数据的模式,有效地查询划浏览该类数据比较困难,半结构化数据的模式发现成为解决该问题的基础步骤。本文提出的算法能够快速有效地发现半结构化层次数据中的规整结构。它采用自顶向下的生成,结合有效的剪枝策略,从OEM模型表达的半结构化层次数据中构建模式树。     

Developing an efficient query system for encrypted XML documents

XQuery is a query and functional programming language that is designed for querying the data in XML documents. This paper addresses how to efficiently query encrypted XML documents using XQuery, with the key point being how to eliminate redundant decryption so as to accelerate the querying process. We propose a processing model that can automatically translate the XQuery statements for encrypted XML documents. The implementation and experimental results demonstrate the practicality of the proposed model.     

基于元数据的分布异构数据集成研究

将“虚拟法”和“数据仓库法”结合,通过统一的数据交换中心解决数字气田分布异构数据集成问题。建立包含全局模式和全局-局部映射的元数据字典,屏蔽异构数据细节,由此解决异构数据的各种冲突。提出一种由分布数据源的局部模式归并建立全局模式和映射表的算法,以提高模式集成的自动能力。     

An XML-Based Approach to Publishing and Querying the History of Databases

There is much current interest in publishing and viewing databases as XML documents. The general benefits of this approach follow from the popularity of XML and the tool set available for visualizing and processing information encoded in this universal standard. In this paper, we explore the additional and unique benefits achieved by this approach on temporal database applications. We show that XML with XQuery can provide surprisingly effective solutions to the problem of supporting historical queries on past content of database relations and their evolution. Indeed, using XML, the histories of database relations can be naturally represented by temporally grouped data models. Thus, we identify mappings from relations to XML that are most conducive to modeling and querying database histories, and show that temporal queries that would be difficult to express in SQL can be easily expressed in standard XQuery. This approach is very general, insofar as it can be used to store the version history of arbitrary documents and, for relational databases, it also supports queries on the evolution of their schema. Then, we turn to the problem of supporting efficiently the storage and the querying of relational table histories. We present an experimental study of the pros and cons of using native XML databases, versus using traditional databases, where the XML-represented histories are supported as views on the historical tables.     

A survey on XML streaming evaluation techniques

XML is currently the most popular format for exchanging and representing data on the web. It is used in various applications and for different types of data including structured, semistructured, and unstructured heterogeneous data types. During the period, XML was establishing itself, data streaming applications have gained increased attention and importance. Because of these developments, the querying and efficient processing of XML streams has became a central issue. In this study, we survey the state of the art in XML streaming evaluation techniques. We focus on both the streaming evaluation of XPath expressions and of XQuery queries. We classify the XPath streaming evaluation approaches according to the main data structure used for the evaluation into three categories: automaton-based approach, array-based approach, and stack-based approach. We review, analyze, and compare the major techniques proposed for each approach. We also review multiple query streaming evaluation techniques. For the XQuery streaming evaluation problem, we identify and discuss four processing paradigms adopted by the existing XQuery stream query engines: the transducer-based paradigm, the algebra-based paradigm, the automata-algebra paradigm, and the pull-based paradigm. In addition, we review optimization techniques for XQuery streaming evaluation. We address the problem of optimizing XQuery streaming evaluation as a buffer optimization problem. For all techniques discussed, we describe the research issues and the proposed algorithms and we compare them with other relevant suggested techniques.