面向对象XML数据查询的代价估计研究

由于XML具有丰富的表达能力、自描述性和灵活性等优点,而面向对象的概念又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。而面向对象XML数据查询的值匹配条件的查询代价估计问题是一种典型的多元素查询条件的代价估计问题。XML数据的值分布与其他值信息的分布有关,还与XML数据的结构信息有关,很难使用某种单一的代价估计方法。针对以上问题,提出了一种基于直方图,在估计过程中结合查询树结构的代价估计方法。     

基于条件偏好的XML查询结果排序方法

摘要为了解决XML查询的信息过载问题,提出了基于条件偏好的XML多查询结果排序方法。该方法把用户指定的内容查询谓词作为上下文条件,然后在原始XML数据和查询历史上利用概率信息检索模型推测当前用户偏好,评估结果元素中被查询指定的属性单元值与未指定的属性单元值之间的关联关系以及未指定的属性单元值与用户偏好之间的相关程度,进而构建查询结果元素打分函数;在此基础上,利用打分函数计算结果元素的排序分值,并以此对查询结果进行排序。实验结果表明,提出的排序方法具有较高的排序准确性,能够较好地满足用户需求和偏好。     

半结构化中文信息检索中查询结果相关度算法的研究

本文研究了对富含文本信息的XML数据进行基于关键字的查询时,查询结果与查询条件之间相关度的计算问题,分析了利用传统信息检索技术解决该问题时存在的一些不足,提出了一种基于节点的动态的关键字权重计算法,以及综合考虑关键字在查询结果中的频率分布特征和结构分布特征的查询结果相关度计算法,有效解决了XML数据中的结构信息对相关度计算的影响,实验证明本文中的方法取得了较好的检索性能。     

XCluster:基于聚类支持查询的XML多文档压缩方法

XML已成为各种网络应用中数据存储和数据交换的标准.XML数据管理面临的最大困难在于结构与数据混合存储导致大量数据冗余,这极大地增加了XML数据存储、交换和处理的代价.对XML文档进行压缩可以在一定程度上解决这个问题.但现有XML压缩方法大都仅压缩单文档中的冗余信息.利用XML文档间的相似性,提出一种支持查询的多XML文档压缩存储方法XCluster.XCluster先利用XML有根有序标签树上改进的pq-gram近似距离对XML文档集进行层次聚类;然后合并每个聚类结果子集中文档的结构得到结构代表并进行字典编码压缩;同时合并不同文档内同一标签下的值内容,并根据其数据类型进行相应编码压缩.实验结果表明,在真实和生成的XML多文档数据集上,XCluster比XGrind和XQilla具有更好的压缩效果和查询效率.     

使用DTD优化XML数据流上的XPath查询

如何在XML数据流上高效地执行XPath查询,是XML数据流管理的关键问题。DTD结构信息对提高XML查询效率有很大帮助,已有的大部分算法没有利用这一资源。提出了一种使用DTD进行XML数据流查询处理的方法,具有以下特征:利用树自动机表示XPath;通过XPath树自动机与DTD树匹配,预先标识不匹配查询结构的DTD节点;给出一种利用DTD的XML流索引方法DBXSI;执行查询时,根据流索引信息直接跳过某些与查询不匹配的节点及子树。实验结果表明:该方法可有效支持Xpath查询,效率优于传统算法。     

F-Index:一种加速Twig查询处理的扁平结构索引

如何快速、有效地处理twig形式的查询是XML查询处理的关键问题,通过过滤与查询无关的元素可以减少查询中需要处理的元素数目,从而提高查询的执行效率.提出一种扁平结构索引F-Index,能够快速过滤所有与查询无关的索引结点,进而过滤掉查询无关的元素,在处理深度嵌套的复杂结构XML文档时具有很大的优势.提出一种新的查询算法,能够有效处理过滤后剩余元素的匹配问题.基于不同数据集的实验表明,使用F-Index进行过滤可以极大地提高查询处理的性能.     

基于直方图的XPath含值谓词路径选择性代价估计

路径选择性代价估计是XML查询优化的基础，也是研究的热点．目前的方法采用大量正态分布和独立性分布假设是造成误差的根本原因．定义了一种新颖的值一位置直方图用于统计XML数据中的结构和值的分布情况，并提出了6种直方图运算．在此基础上，给出用直方图计算估计路径中任一结，最选择性的方法．实验证明，这种方法无需独立性分布假设，也能在数据结构和数值分布不均匀的情况下。精确地估计路径选择性代价．     

基于整枝连接算法的多版本XML文档查询

XML文档采用树型数据模型,XML查询语言通常是一些基于多个元素的选择胃词组成的查询模式。整枝连接方法用来匹配XML查询模式,用相互连接的多栈结构一次性生成匹配结果。但它不支持多版本XML文档,本文就是探讨如何解决这个问题。     

一种基于领域知识的XML数据模糊查询

为了解决普通用户对XML数据的模糊查询问题,提出了一种基于领域知识的XML数据模糊查询方法.以模糊集理论为基础,首先介绍了XML数据模糊查询的构成形式;然后提出了将领域知识和模糊集的隶属函数相结合的方法实现XML数据的模糊查询条件转换,转换过程考虑了查询谓词的重要程度和用户偏好;最后按结果元素对模糊查询的满足程度对模糊查询结果进行排序.该方法无需改变传统的XML查询语言和XDBMS就能够实现模糊查询,从而提高了用户与系统之间的交互能力.实验结果表明,提出的模糊查询方法具有较高的查全率和准确率.     

一种基于结构索引的XML模式匹配方法

XML文档采用了树型的数据模型,对其查询通常是用带有选择谓词的模式树在XML数据中进行匹配.因此,找出XML文档中所有符合模式树结构的元素集,是XML查询处理的核心操作.本文提出了结构索引JoinGuide,并在此基础上提出了一种新的XML模式匹配方法.它使用JoinGuide来对模式树进行预匹配,这样在XML文档上查询时可以利用索引上的匹配结果来忽略部分连接谓词和不必要的候选XML元素序列.本文还提出了三种具体算法来利用索引匹配结果进行进一步的查询.实验结果表明本文中的模式树匹配方法优于以往的匹配方法,并且索引所需的空间很小.     

A relational model for XML structural joins and their size estimations

XML structural joins, which evaluate the containment (ancestor-descendant) relationships between XML elements, are important operations of XML query processing. Estimating structural join size accurately and quickly is crucial to the success of XML query plan selection and the query optimization. XML structural joins are essentially complex θ-joins, which render well-known estimation techniques for relational equijoins, such as discrete cosine transform, wavelet transform, and sketch, not applicable. In this paper, we model structural joins from a relational point of view and convert the complex θ-joins to equijoins so that those well-known estimation techniques become applicable to structural join size estimation. Theoretical analyses and extensive experiments have been performed on these estimation methods. It is shown that discrete cosine transform requires the least memory and yields the best estimates among the three techniques. Compared with state-of-the-art method IM-DA-Est, discrete cosine transform is much faster, requires less memory, and yields comparable estimates.     

A multiple-depth structural index for branching query

XML structural index, which acts as a schema, plays an important role in XML query optimization and formulation. To provide a reasonable structural index for branching path query under space constraint, we propose an adaptive index of multiple local branching depths and multiple local bisimilarities, which is constructed by maximizing marginal gain for given query load. It cannot only give good support to branching path queries but also have much smaller size compared with that of same sort of index. Detailed experiments have shown that the index is effective and efficient for XML branching path query.     

XML数据的查询技术

XML规范已成为当前网络应用(包括数字图书馆、Web服务以及电子商务)中事实上的数据表达、交换的标准.针对XML数据的查询在当前XML数据管理研究中占有重要的地位,也是当前XML数据处理研究领域的热点方向,相关的研究文献有很多.根据查询模式描述的不同,将当前XML查询技术归入两大类:XML Query方式和XML IR方式.后者又进而可分以为3个子类:XML IR/keyword方式、XML IR/fragment和XML IR/query方式,并从中挑选出3个研究者关注的问题进行了简述,它们是:Twig查询模式的处理、SLCA(smallest lowest common ancestor)节点的获取以及对所获取的XML片段相似性的度量.以方便普通用户使用为准则探讨了相关XML查询技术的优、缺点,将如下4个问题作为需要进一步关注的研究内容:结构化关键字查询及相应的结构相似性度量方法,如何消除XML Query查询处理模式(包含XML IR/query)和XML IR/keyword查询处理模式间数据冗余的问题,XML Query查询方式的理论探讨及其实现以及针对特定应用的XML数据的有效管理.     

Processing keyword search on XML: a survey

Keyword search is a user-friendly approach for users to retrieve information from XML data. Since an XML document can have a large size and contain a lot of information, an XML keyword search result should be a fragment of an XML document dynamically constructed at query time, which is achievable due to the structuredness of XML. Processing keyword searches on XML has several challenges, e.g., what are the elements in the XML document that are relevant to the query? How to generate the results efficiently and rank the results meaningfully? How to present the results to the user in a way such that the user can quickly find the desired information? In this survey, we review the papers in the literature that attempted to address these problems. We divide the existing approaches into several classes based on the problem they tackled, and perform a comprehensive analysis of these works.     

一种基于Schema的XML索引结构

XML Schema作为一种描述XML文档模式信息即结构信息的标准，对于XML索引的建立及查询效率的提高有着重要的作用。现有的大部分XML索引结构着重研究XML文档的结构查询，而对于XML文档的更新支持却不多，对无效查询也不能作出快速的判断。该文基于已有的XML文档的编码方式，提出了一种基于Schema的XML索引结构，不仅能支持基于有效性验证的动态更新，使得XML文档和XML Schema保持一致，而且对用户提出的无效的路径查询也能在较短时间内作出判断。     

XML查询优化研究

XML已经成为网络上信息描述和信息交换的标准.由于网络上信息的本质特性和XML数据内在的灵活性,很多用XML编码的数据都是半结构化的.随着XML应用得越来越广泛,人们提出了多种XML数据的存储模型.与此同时,XML的查询优化也是数据库领域研究的一个重要课题.综合论述了XML数据查询优化技术的现状,指出了XML查询优化的特点和研究的关键性问题.描述了查询优化技术各个方面的重要研究成果以及存在的问题,进一步展望了未来的研究方向,并在此基础上提出了对XML查询优化方法的一些观点.     

XHQE: A hybrid system for scalable selectivity estimation of XML queries

With the increasing popularity of XML applications in enterprise and big data systems, the use of efficient query optimizers is becoming very essential. The performance of an XML query optimizer depends heavily on the query selectivity estimators it uses to find the best possible query execution plan. In this work, we propose a novel selectivity estimator which is a hybrid of structural synopsis and statistics, called XHQE. The structural synopsis enhances the accuracy of estimation and the structural statistics makes it scalable to the allocated memory space. The structural synopsis is generated by labeling the nodes of the source XML dataset using a fingerprint function and merging subtrees with similar fingerprints (i.e. having similar structures). The generated structural synopsis and structural statistics are then used to estimate the selectivity of given queries. We studied the performance of the proposed approach using different types of queries and four benchmark datasets with different structural characteristics. We compared XHQE with existing algorithms such as Sampling, TreeSketch and one histogram-based algorithm. The experimental results showed that the XHQE is significantly better than other algorithms in terms of estimation accuracy and scalability for semi-uniform datasets. For non-uniform datasets, the proposed algorithm has comparable estimation accuracy to TreeSketch as the allocated memory size is highly reduced, yet the estimation data generation time of the proposed approach is much lower (e.g., TreeSketch took more than 50 times longer than that of the proposed approach for XMark dataset). Comparing to the histogram-based algorithm, our approach supports regular twig quires in addition to having higher accuracy when both run under similar memory constraints.     

Locating XML Documents in a Peer-to-Peer Network Using Distributed Hash Tables

One of the key challenges in a peer-to-peer (P2P) network is to efficiently locate relevant data sources across a large number of participating peers. With the increasing popularity of the extensible markup language (XML) as a standard for information interchange on the Internet, XML is commonly used as an underlying data model for P2P applications to deal with the heterogeneity of data and enhance the expressiveness of queries. In this paper, we address the problem of efficiently locating relevant XML documents in a P2P network, where a user poses queries in a language such as XPath. We have developed a new system called psiX that runs on top of an existing distributed hashing framework. Under the psiX system, each XML document is mapped into an algebraic signature that captures the structural summary of the document. An XML query pattern is also mapped into a signature. The query's signature is used to locate relevant document signatures. Our signature scheme supports holistic processing of query patterns without breaking them into multiple path queries and processing them individually. The participating peers in the network collectively maintain a collection of distributed hierarchical indexes for the document signatures. Value indexes are built to handle numeric and textual values in XML documents. These indexes are used to process queries with value predicates. Our experimental study on PlanetLab demonstrates that psiX provides an efficient location service in a P2P network for a wide variety of XML documents.