基于XML技术的web数据库应用系统的设计与实现

文章介绍了XML技术的特性和在数据管理和查询中的应用,讨论了基于XML技术的web数据库系统的工作原理,详细阐述了基于XML技术的web数据库应用系统的设计与实现过程,结合实际介绍了系统开发过程中使用的关键技术。     

基于DOM的XML数据库的索引技术研究

XML作为一种数据交换的国际标准，已经贯穿于Internet应用的各个领域之中，如何快速准确地存储和查询XML数据的数据库技术是一个重要的研究课题。XML索引技术对XML数据库查询处理起着至关重要的作用，提出了基于DOM的XML数据库的索引技术(路径连接索引、值索引和引用索引)，解决了传统的基于树的遍历的XML数据查询方法性能上的不足，并着重对处理含有谓词和引用关系等较复杂的查询路径的不同处理方法进行了对比和分析，还给出了索引空间利用率、查询性能和索引维护代价3个方面的标准测试结果，表明新的索引技术可以有效地提高查询处理效率。     

半结构数据上的结构化查询

文章在目前的一些XML存储查询技术基础上应用OODB的思想,提出了一个类SQL的结构化查询语言,并利用对象集合的方法统一定义了数据库的代数系统.同时实现了一个可以进行类似SQL的结构化查询的XML存储的原型系统,并给出了一些查询的测试数据.     

基于全文检索的XML存储查询系统

XML数据库已经成为数据库领域的重要成员,但是在商业数据库产品中它主要构建在关系数据库基础之上,这自然引入很多难题.针对XML的关系数据库存储,提出一种新的XML索引编码,解决了在关系数据库中集成全文检索技术和XML结构连接查询算法的问题,同时借助全文检索技术达到XML查询加速的效果.该方案应用于实际软件开发项目中.很好地解决了XML文档的关系数据库存储管理工作,并且具有很高的查询效率.     

基于XML的数据映射技术

本文将Java技术与XML技术进行有机结合,研究了数据库操作中,XML技术映射数据库中表与Java类的方法,通过Java技术动态解析XML映射,为操作数据库建立对象查询语句,并应用Java技术对对象查询语句转换为标准SQL语句提出了新的实现方法。     

基于XML的数据映射技术

本文将Tava技术与XML技术进行有机结合，研究了数据库操作中，XML技术映射数据库中表与Jaya类的方法，通过Java技术动态解析XML映射，为操作数据库建立对象查询语句，并应用Jaya技术对对象查询语句转换为标准SQL语句提出了新的实现方法。     

基于XML Enabled数据库技术的应用研究

利用XML Enabled数据库DB2XML API技术可以实现传统数据库向XML数据的动态转换，并在此基础上对生成的XML文档进行查询和显示。这种方法在保留了现有数据的基础上，减少了数据库读取次数，又满足了XML应用的需求，可作为一种面向B2CXML应用的通用方法。     

基于XML的异构数据库查询技术研究

文中提出了一种基于XML的异构数据库查询核心系统体系结构,并阐述了在IBMWAS平台下实现该查询核心系统的方法。由于采用JSP、Servlet及JavaBean等技术来实现XML数据的处理,该查询核心系统具有很好的可移性和可扩展性等特点。     

XBackend:一种Native XML数据库系统的后端实现策略

随着XML技术研究与应用的深入,涌现出了大量XML文档.为了对XML文档进行管理和查询,大多数RDBMS扩充了处理XML数据的功能.这种方式将XML数据映射到关系表中,会破坏XML数据的树型结构.查询时,需要多次的表连接,降低了查询效率.原生XML数据库以XML文档作为基本的逻辑存储单位,建立底层的物理存储模型.提出了一种原生XML数据库的后端实现策略--XBackend,包括存储策略、索引策略、数据库恢复策略. XBackend底层存储是专门为XML数据设计的,配合适当的索引,具有更高的存储和查询效率.数据库恢复策略保证了原生XML数据库数据的一致性状态.实验结果表明XBackend具有很好的性能.     

XML查询语言XQuery的分析与研究

XML的应用变得日益广泛,XML数据库技术也得到了迅速发展,当越来越多的数据资料以XML为标准格式进行存储时,却由于其格式的不同导致了传统的数据库及查询语法无法适用。分析了一种全新的XML查询语言XQuery,并对FLWOR表达式进行了重要阐述。     

基于XML的异构数据集成模式的研究

随着信息技术的发展,任何一个独立单位都有可能成为一个异构的数据源。为实现企业异构数据库间信息的共享和集成,对数据集成的原理以及主要技术进行了研究,重点分析了 XML 与数据库之间的映射、XML 文档存储模式、将 XML 查询转化为 SQL 的查询转换问题以及如何将关系数据发布为 XML 文档。该方案简单易行,保证了各系统仍然按照原来的方式运行,只是在需要进行信息交换时通过转换接口把本地数据库数据转换成 XML 文档即可。     

XML形式数据模型及其查询代数

提出了XML的形式数据模型及其查询代数,主要包括以下几个方面：构造先后序关系、引入带根连通有向图、建立XML形式数据模型(XFDM)和XML查询代数(XFQA)。它形成了一个较为完整的XML数据库管理系统的理论基础,可以作为XML以及其它半结构化数据库管理系统查询存储、查询分解、查询优化和查询实现的形式化基础。     

A Semantic Cache Framework for Secure XML Queries

Secure XML query answering to protect data privacy and semantic cache to speed up XML query answering are two hot spots in current research areas of XML database systems. While both issues are explored respectively in depth,they have not been studied together,that is,the problem of semantic cache for secure XML query answering has not been addressed yet. In this paper,we present an interesting joint of these two aspects and propose an efficient framework of semantic cache for secure XML query answering,which can improve the performance of XML database systems under secure circumstances. Our framework combines access control,user privilege management over XML data and the state-of-the-art semantic XML query cache techniques,to ensure that data are presented only to authorized users in an efficient way. To the best of our knowledge,the approach we propose here is among the first beneficial efforts in a novel perspective of combining caching and security for XML database to improve system performance. The efficiency of our framework is verified by comprehensive experiments.     

A comparison of two approaches to utilizing XML in parametric databases for temporal data

The parametric data model captures an object in terms of a single tuple. This feature eliminates unnecessary self-join operations to combine tuples scattered in a temporal relation. Despite this advantage, this model is relatively difficult to implement on top of relational databases because the sizes of attributes are unfixed. Since data boundaries are not problematic in XML, XML can be an elegant solution to implement parametric databases for temporal data. There are two approaches to implementing parametric databases using XML: (1) a native XML database with XQuery engine, and (2) an XML storage with a temporal query language. To determine which approach is appropriate in parametric databases, we consider four questions: the effectiveness of XML in modeling temporal data, the applicability of XML query languages, the user-friendliness of the query languages, and system performances of two approaches. By evaluating the four questions, we show that the latter approach is more appropriate to utilizing XML in parametric databases.     

Scaling XML query processing: distribution, localization and pruning

Distributing data collections by fragmenting them is an effective way of improving the scalability of a database system. While the distribution of relational data is well understood, the unique characteristics of the XML data and query model present challenges that require different distribution techniques. In this paper, we show how XML data can be fragmented horizontally and vertically. Based on this, we propose solutions to two of the problems encountered in distributed query processing and optimization on XML data, namely localization and pruning. Localization takes a fragmentation-unaware query plan and converts it to a distributed query plan that can be executed at the sites that hold XML data fragments in a distributed system. We then show how the resulting distributed query plan can be pruned so that only those sites are accessed that can contribute to the query result. We demonstrate that our techniques can be integrated into a real-life XML database system and that they significantly improve the performance of distributed query execution.     

面向对象的XML查询系统的设计与实现

设计和开发了面向对象的XML数据查询系统原型OOX(object-oriented XML).OOX系统中包括了面向对象XML数据查询系统的一些核心功能,如存储、索引、查询等.其最大的特点是:它是一个可以实现对富含面向对象XML数据进行查询的XML查询系统;支持用继承扩展的XML模式语言DTD的解析,支持用继承扩展的XML查询语言XML-RL;采用了先进的路经仓索引模式以及高效的查询处理技术,可以实现高效的查询处理.     

ArchIS: an XML-based approach to transaction-time temporal database systems

Effective support for temporal applications by database systems represents an important technical objective that is difficult to achieve since it requires an integrated solution for several problems, including (i) expressive temporal representations and data models, (ii) powerful languages for temporal queries and snapshot queries, (iii) indexing, clustering and query optimization techniques for managing temporal information efficiently, and (iv) architectures that bring together the different pieces of enabling technology into a robust system. In this paper, we present the ArchIS system that achieves these objectives by supporting a temporally grouped data model on top of RDBMS. ArchIS’ architecture uses (a) XML to support temporally grouped (virtual) representations of the database history, (b) XQuery to express powerful temporal queries on such views, (c) temporal clustering and indexing techniques for managing the actual historical data in a relational database, and (d) SQL/XML for executing the queries on the XML views as equivalent queries on the relational database. The performance studies presented in the paper show that ArchIS is quite effective at storing and retrieving under complex query conditions the transaction-time history of relational databases, and can also assure excellent storage efficiency by providing compression as an option. This approach achieves full-functionality transaction-time databases without requiring temporal extensions in XML or database standards, and provides critical support to emerging application areas such as RFID.     

XML queries and algebra in the Enosys integration platform

We describe the Enosys XML integration platform, focusing on the query language, algebra, and architecture of its query processor. The platform enables the development of eBusiness applications in customer relationship management, e-commerce, supply chain management, and decision support. These applications often require that data be integrated dynamically from multiple information sources. The Enosys platform allows one to build (virtual and/or materialized) integrated XML views of multiple sources, using XML queries as view definitions. During run-time, the application issues XML queries against the views. Queries and views are translated into the XCQL algebra and are combined into a single algebra expression/plan. Query plan composition and query plan decomposition challenges are faced in this process. Finally, the query processor lazily evaluates the result, using an appropriate adaptation of relational database iterator models to XML. The paper describes the platform architecture and components, the supported XML query language and the query processor architecture. It focuses on the underlying XML query algebra, which differs from the algebras that have been considered by W3C in that it is particularly tuned to semistructured data and to optimization and efficient evaluation in a system that follows the conventional architecture of database systems.     

XML查询方法的设计与研究

提出了用Petri网建立XML语义结构模型的设计方法，根据XML的DTD结构建立描述XML语义结构的Petri网模型，DTD结构中的元素声明和属性声明对应Petri网模型中的一个或一组变迁，声明中的元素或属性对应Petri 网模型中的库所，把XML查询中的路径表达式定义为Petri网库所中的Token。根据Petri网模型的结构生成存储XML数据的关系数据库模型，将XML的查询问题最终转化为数据库中数据的查询操作。 XML；Petri网；路径表达式；查询     

Storing and querying XML data using denormalized relational databases

XML database systems emerge as a result of the acceptance of the XML data model. Recent works have followed the promising approach of building XML database management systems on underlying RDBMSs. Achieving query processing performance reduces to two questions: (i) How should the XML data be decomposed into data that are stored in the RDBMS? (ii) How should the XML query be translated into an efficient plan that sends one or more SQL queries to the underlying RDBMS and combines the data into the XML result? We provide a formal framework for XML Schema-driven decompositions, which encompasses the decompositions proposed in prior work and extends them with decompositions that employ denormalized tables and binary-coded XML fragments. We provide corresponding query processing algorithms that translate the XML query conditions into conditions on the relational tables and assemble the decomposed data into the XML query result. Our key performance focus is the response time for delivering the first results of a query. The most effective of the described decompositions have been implemented in XCacheDB, an XML DBMS built on top of a commercial RDBMS, which serves as our experimental basis. We present experiments and analysis that point to a class of decompositions, called inlined decompositions, that improve query performance for full results and first results, without significant increase in the size of the database.Received: 21 December 2001, Accepted: 1 July 2003, Published online: 23 June 2004Edited by: A. HalevyAndrey Balmin: Andrey Balmin has been supported by NSF IRI-9734548.Yannis Papakonstantinou: The authors built the XCacheDB system while on leave at Enosys Software, Inc., during 2000.