一种基于路径分块索引的XML查询方法

针对XML的相对路径查询及引用路径查询问题，提出了一种面向XML数据的路径分块索引KI。探讨了KI索引构造方法、索引节点分裂算法和相关查询处理的算法，并用VC++实现，利用Shakespeare和Xorder数据集进行了XML查询测试，实验结果表明，提出的KI索引能有效地提高XML查询效率。     

基于路径仓的面向对象XML查询处理技术

XML正在迅速成为Internet上数据表示和交换的标准，存储与查询XML数据变得日益重要，如何快速、准确地查询面向对象的XML数据成为当前研究的热点，索引技术是提高查询效率的有效方法。该文基于路径仓索引模式，提出了一种面向对象的XML数据的查询处理技术。     

基于索引的XML查询技术研究

介绍了目前XML数据查询技术的研究现状，对主要的XML索引查询技术作了较深入的探讨，其中包括：基于路径索引的XML查询方法，如DataGuide、1-index、A（k）索引等；基于编码的XML索引查询方法，如Anc_Desc_B^＋、XR树＋XR-Stack算法等。文中对相关XML索引查询方法的优点和不足进行了分析。     

XML数据索引技术

对XML数据建立有效的索引,是左右XML数据处理性能的重要因素.深入地讨论了目前XML索引技术的研究现状,将XML索引技术分为两大类:节点记录类索引(本身还可以分为3个小的类型)和结构摘要类索引.根据XML数据查询处理效率以及XML数据修改对XML索引的要求,讨论了相关XML索引方法的优点和不足,并归结出XML索引后续研究的3个方向:XML结构信息的获取,路径信息的多维处理,数据修改合法性的有效支持,以及涉及能够同时有效满足XML查询和信息获取的索引.     

一种改进的建立XML数据路径索引的方法

随着XML日益普遍的应用，如何快速准确地访问XML文档中的数据已成为亟待解决的关键问题，建立路径索引是提高查询效率的一种重要手段，本文分析了可能导致路径索引复杂度过大的原因,提出了一种分步建立和更新路径索引的方法，对于具有复杂引用关系的源数据，根据查询的需要只对数据中部分路径建立索引，并通过阈值控制索引的规模，实验结果表明，本文提出的方法可以有效地降低建立和维护XML数据的路径索引的代价。     

基于XML索引技术的有效外延连接

首先给出了XML文档树、元素外延和名字路径等的形式化定义.接着,将编码方案、路径索引和名字外延的思想相结合,提出了一种改进的XML数据的索引结构(类型索引集、名字索引集和外延索引),解决了基于传统索引技术的XML数据查询方法性能上的不足,它既可以有效地支持结构连接的计算以快速地判断任意结点之间的子孙后代关系,也可以有效地支持基于名字外延的路径连接算法以快速地判断任意结点之间的父子关系,然后还可以快速地支持对包含拥有关系的小枝查询;进而给出了基于该索引结构的外延连接算法,并着重对其处理含有父子关系和拥有关系等较复杂的XPath查询路径的不同处理过程进行了对比和分析,使得对于一条长度为n的XPath绝对路径查询,最多只需要n/z-1次外延连接,且能够根据双亲结构信息等利用外延索引尽可能跳过不需要参与连接的结点,实验结果表明,提出的新的索引结构可以有效地提高查询处理的性能.     

面向原生XML数据库的自适应路径索引

路径索引是改善原生XML数据库(NXD)性能的一项重要技术.然而现有NXD中的路径索引缺乏动态性、白适应性,妨碍了NXD的查询性能改善.本文根据Chung C等提出的面向XML数据的自适应路径索引(APEX)[1],结合NXD的特点,提出面向NXD的自适应路径索引(NXD.APEX).NXD.APEX继承了APEX自适应性,并通过加入时间特征到APEX的常用路径挖掘算法中,使NXD-APEX能有效处理具有时间局部性的查询.同时针对NXD-APEX可能导致的大空间开销问题,提出一种基于收益的索引筛选算法.试验表明:NXD-APEX能以合理的空间开销有效地改善NXD的查询性能.     

一种改进的建立XML数据的路径索引的方法

随着XML日益普遍的应用,如何快速准确地访问XML文档中的数据已成为亟待解决的关键问题,建立路径索引是提高查询效率的一种重要手段.本文分析了可能导致路径索引复杂度过大的原因,提出一种分步建立和更新路径索引的方法,对于具有复杂引用关系的源数据,根据查询的需要只对数据中部分路径建立索引,并通过阈值控制索引的规模.实验结果表明,本文提出的方法可以有效地降低建立和维护XML数据的路径索引的代价.     

基于双路索引的XML查询优化研究

为实现各种形式的XML数据查询,介绍一种双路索引方法,采用倒排序技术建立绝对索引模型和相对索引模型,并提出相关查询处理的算法。绝对索引模型将查询路径表达式缩短,减少比较次数,相对索引模型建立父子索引表补全路径,用较小的索引结构替代原始查询。采用DBLP数据集进行测试,实验结果表明,该方法可以提高查询处理的性能。     

基于优化过滤策略的XML数据查询处理

如何高效地处理XML查询，是目前研究的热点。由于当前方法存在过多扫描无用节点引起效率下降的问题，本文设计了一种XML数据的二级索引结构，基于该结构给出路径查询处理算法。首先，本文对XML模式中每个节点按路径类型进行分类编码，然后把每个节点按该编码进行聚类存储。在查询时，就可以先根据模式信息和查询信息得到目标节点的编码，然后只需将二级索引中这些编码对应的部分载入内存，进行过滤操作。这样就不必扫描整个索引，提高CPU和IO效率。本文还对二级索引结构进行扩展，使本文的过滤索引能方便应用在有分支结构的查询上。实验结果表明，本文的XML数据过滤算法效率优于基于Bit vector的过滤算法，并且索引结构所需要的存储空间也小于Bitvector索引。     

Data storage practices and query processing in XML databases: A survey

With the rapid emergence of XML as a data exchange standard over the Web, storing and querying XML data have become critical issues. The two main approaches to storing XML data are (1) to employ traditional storage such as relational database, object-oriented database and so on, and (2) to create an XML-specific native storage. The storage representation affects the efficiency of query processing. In this paper, firstly, we review the two approaches for storing XML data. Secondly, we review various query optimization techniques such as indexing, labeling and join algorithms to enhance query processing in both approaches. Next, we suggest an indexing classification scheme and discuss some of the current trends in indexing methods, which indicate a clear shift towards hybrid indexing.     

Efficiently Querying Large XML Data Repositories: A Survey

Extensible markup language (XML) is emerging as a de facto standard for information exchange among various applications on the World Wide Web. There has been a growing need for developing high-performance techniques to query large XML data repositories efficiently. One important problem in XML query processing is twig pattern matching, that is, finding in an XML data tree D all matches that satisfy a specified twig (or path) query pattern Q. In this survey, we review, classify, and compare major techniques for twig pattern matching. Specifically, we consider two classes of major XML query processing techniques: the relational approach and the native approach. The relational approach directly utilizes existing relational database systems to store and query XML data, which enables the use of all important techniques that have been developed for relational databases, whereas in the native approach, specialized storage and query processing systems tailored for XML data are developed from scratch to further improve XML query performance. As implied by existing work, XML data querying and management are developing in the direction of integrating the relational approach with the native approach, which could result in higher query processing performance and also significantly reduce system reengineering costs.     

Secure query processing against encrypted XML data using Query-Aware Decryption

Dissemination of XML data on the internet could breach the privacy of data providers unless access to the disseminated XML data is carefully controlled. Recently, the methods using encryption have been proposed for such access control. However, in these methods, the performance of processing queries has not been addressed. A query processor cannot identify the contents of encrypted XML data unless the data are decrypted. This limitation incurs overhead of decrypting the parts of the XML data that would not contribute to the query result. In this paper, we propose the notion of Query-Aware Decryption for efficient processing of queries against encrypted XML data. Query-Aware Decryption allows us to decrypt only those parts that would contribute to the query result. For this purpose, we disseminate an encrypted XML index along with the encrypted XML data. This index, when decrypted, informs us where the query results are located in the encrypted XML data, thus preventing unnecessary decryption for other parts of the data. Since the size of this index is much smaller than that of the encrypted XML data, the cost of decrypting this index is negligible compared with that for unnecessary decryption of the data itself. The experimental results show that our method improves the performance of query processing by up to six times compared with those of existing methods. Finally, we formally prove that dissemination of the encrypted XML index does not compromise security.     

基于面向对象XML数据的索引机制

XML正在迅速成为Internet上信息表示和数据交换的重要标准.而面向对象的特征具有很强的建模能力,将面向对象的概念引入到XML可以提高XML模式语言的建模能力.而现有的索引模式都不支持面向对象XML数据的查询,由此提出了一种基于面向对象XML数据的OOCtree（Object-Oriented compact tree）索引模式,它是一棵包含组级和元素级的两级双向树.组级提供简洁的结构概要和继承信息,可以在查询早期阶段裁剪大量的搜索空间;元素级提供详细的孩子父亲连接关系,可以快速地访问某元素的父亲,极大地提高了查询处理效率.     

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.     

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.     

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.     

Multiple similarity queries: a basic DBMS operation for mining inmetric databases

Metric databases are databases where a metric distance function is defined for pairs of database objects. In such databases, similarity queries in the form of range queries or k-nearest-neighbor queries are the most important query types. In traditional query processing, single queries are issued independently by different users. In many data mining applications, however, the database is typically explored by iteratively asking similarity queries for answers of previous similarity queries. We introduce a generic scheme for such data mining algorithms and we investigate two orthogonal approaches, reducing I/O cost as well as CPU cost, to speed-up the processing of multiple similarity queries. The proposed techniques apply to any type of similarity query and to an implementation based on an index or using a sequential scan. Parallelization yields an additional impressive speed-up. An extensive performance evaluation confirms the efficiency of our approach     

基于XML的数据管理技术

随着Web技术的快速发展,如何有效地存储、索引、查询和显示XML数据已经成为数据库研究领域的一个热点研究问题。本文介绍了XML数据的3种不同存储方法;XML搜索查询的工具和语言;XML数据的访问控制模型;XML最直接的显示方法以及正在实现的真正的XML数据库等。通过这些XML数据管理技术,可以了解到当下XML研究领域的先进技术和方法,指导今后的研究方向和重点。