一种改进的基于约束关系的XML查询重写算法研究

查询重写是解决数据集成、查询优化和物理层数据独立性等问题的关键技术.以往工作主要集中在关系数据模型方面.最近Michigan大学Timber研究小组提出一种全新的基于约束的XML查询重写算法.然而,该算法未考虑存在内定谓词情况下的重写问题,应用范围受到一定限制.在原算法的重写思想基础上,提出了一种基于约束的XML查询重写的改进算法.通过引入映射规则中的约束条件,消除阻碍重写的Skolem函数,从而解决内定谓词问题,增大原算法的应用范围.证明了改进算法的正确性.性能分析和测试结果表明,改进算法并不增加实质性的性能代价.     

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XDR纲要的空间元数据存储策略

提出一种基于XDR纲要的空间元数据存储体系结构,建立XDR纲要,将以XML表达的空间元数据映射到SQL Server 2000关系数据库中,可以使用加注释XDR纲要的XML视图对应到数据库的查询,并以XML文件的形式返回查询结果。     

基于代价的XML Schema到关系模式的映射策略研究

XML作为一种数据交换的国际标准,已经广泛应用于各个领域,如何准确地实现XML与关系数据库的转换已经成为一个重要的研究课题。本文主要研究XML Schema到关系模式的映射方法,通过对XML Schema的结构和语法进行分析,提取元素的语义信息,找到真正的复杂类型的元素,将XML Schema转换为E_Schema,E_Schema表达方式简单且信息完整,结合基于查询代价的思想对E_Schema进行处理,得到最优模式,再将其转换成关系模式,而且能保持原有的层次关系,从而实现了一个更为简单、完善的映射方案。     

基于关系的XML数据存储

ＸＭＬ正成为Ｉｎｔｅｒｎｅｔ上数据表示与交换的标准,如何存储ＸＭＬ数据是一个关键问题。我们在系统实现时采用了基于关系数据库的存储方式。文章对于关系模式如何由ＤＴＤ生成、等问题,做了详细的探讨。     

基于演化计算的XML数据的关系存储

随着XML规范的制定和推广，XML数据管理技术受到数据库界广泛重视，XML数据的存储是XML数据管理的关键．研究了利用数据库技术和人工智能技术，为XML数据的关系存储提供一种灵活的策略．首次提出了代价驱动的基于遗传算法的关系存储策略CDGABRS，针对不同的用户和查询模型，产生不同的映射模型方案，引进遗传算法，计算对应的系统开销，从中求出使系统的存储代价和查询代价最优的关系存储方案．实验证明了CDGABRS方法的可行性和高效性．     

Efficient schema-based XML-to-Relational data mapping

Storing and querying XML documents using a RDBMS is a challenging problem since one needs to resolve the conflict between the hierarchical, ordered nature of the XML data model and the flat, unordered nature of the relational data model. This conflict can be resolved by the following XML-to-Relational mappings: schema mapping, data mapping and query mapping. In this paper, we propose: (i) a lossless schema mapping algorithm to generate a database schema from a DTD, which makes several improvements over existing algorithms, (ii) two linear data mapping algorithms based on DOM and SAX, respectively, to map ordered XML data to relational data. To our best knowledge, there is no published linear schema-based data mapping algorithm for mapping ordered XML data to relational data. Experimental results are presented to show that our algorithms are efficient and scalable.     

Dynamically Updating XML Data: Numbering Scheme Revisited

Almost all existing approaches use certain numbering scheme to encode XML elements to facilitate query processing when XML data is stored in databases. For example, under the most popular region-based numbering scheme, the starting and ending positions of an element in a document are used as the code to identify the element so that the ancestor/descendant relationship between two elements can be determined by merely examining their codes. While such numbering scheme can greatly improve query performance, renumbering large amount of elements caused by updates becomes a performance bottleneck if XML documents are frequently updated. Unfortunately, no satisfactory work has been reported for efficient update of XML data. In this paper, we first formalize the XML data update problem by defining the basic operators to support most XML update queries. We then present a new numbering scheme that not only requires minimal code-length in comparison with existing numbering schema but also improves update performance when XML data is frequently updated at arbitrary positions. The fundamental difference between our new scheme and existing ones is that, instead of maintaining the explicit codes for elements, we only store the necessary information and generate the codes when they are needed in query processing. In addition to present the basic scheme, we also discuss some optimization techniques to further reduce the update cost. Results of a comprehensive performance study are provided to show the advantages of the new scheme.     

Related Axis: The Extension to XPath Towards Effective XML Search

We investigate the limitations of existing XML search methods and propose a new semantics, related relationship, to effectively capture meaningful relationships of data elements from XML data in the absence of structural constraints. Then we make an extension to XPath by introducing a new axis, related axis, to specify the related relationship between query nodes so as to enhance the flexibility of XPath. We propose to reduce the cost of computing the related relationship by a new schema summary that summarizes the related relationship from the original schema without any loss. Based on this schema summary, we introduce two indices to improve the performance of query processing. Our algorithm shows that the evaluation of most queries can be equivalently transformed into just a few selection and value join operations, thus avoids the costly structural join operations. The experimental results show that our method is effective and efficient in terms of comparing the effectiveness of the related relationship with existing keyword search semantics and comparing the efficiency of our evaluation methods with existing query engines.     

XML数据的B树存储实现及更新

XML正逐渐成为 WWW数据表示和交换的标准 ,如何有效实现对于 XML数据的存储、查询及更新等操作是 XML 相关技术研究中的一个重要领域。本文首先简要介绍了我们的基于模式匹配的 XML 数据库系统 (DISXDBS)组成 ;然后研究了如何实现用 B树存储 XML 文档以及对其进行查询、更新等操作 ;最后与目前存在的几种 XML 文档的存储策略进行比较。     

一种改进的XML查询重写算法研究

查询重写是数据集成的一个关键问题,它是将用户的查询请求自动重写为直接面向数据源的查询请求。最近Michigan大学和IBM的AImaden研究中心提出了一种新的基于约束的XML查询重写算法,但是该算法没有考虑复杂模式匹配重写问题,使得该算法应用受到限制。在原来的算法重写思想基础上,提出了一种改进的XML查询重写算法,扩大原算法的应用范围,并分析了改进算法的正确性和时间复杂度。     

基于频繁叶模式的XML最大频繁查询模式挖掘算法

在XML频繁查询模式挖掘稠密数据集、长数据集中,为克服项目集挖掘过程中挖掘的项目过多、不利于结果利用等问题,提出基于频繁叶模式的最大频繁查询模式挖掘算法MFRSTMiner。该算法通过构造频繁模式扩展森林,在扩展森林的叶节点中挖掘出最大频繁子树。试验结果表明该算法能够有效地挖掘动态事务集的最大频繁查询模式。     

Designing XML documents from conceptual schemas and workload information

Due to the increase of XML-based applications, XML schema design has become an important task. One approach is to consider conceptual schemas as a basis for generating XML documents compliant to consensual information of specific domains. However, the conversion of conceptual schemas to XML schemas is not a straightforward process and inconvenient design decisions can lead to a poor query processing on XML documents generated. This paper presents a conversion approach which considers data and query workload estimated for XML applications, in order to generate an XML schema from a conceptual schema. Load information is used to produce XML schemas which can respond well to the main queries of an XML application. We evaluate our approach through a case study carried out on a native XML database. The experimental results demonstrate that the XML schemas generated by our methodology contribute to a better query performance than related approaches.

VEMBP:支持更新的XML树编码方法

对有序XML文档树进行编码,不需要访问XML原始文件就能够实现对XML数据的管理,提高了XML管理系统的效率。针对查询提出的编码方案具有很高的查询性能,但更新效率很低。为提高更新性能而设计的方案存在查询效率低或者编码空间大等问题。为了在提高更新XML文档效率的同时不对查询性能和编码空间产生负面影响,提出了一种新的编码方法VEMBP(Vector Encoding Method Based of Prime),该方法利用向量表示有序XML节点之间的顺序关系,采用素数表示有序XML文档节点之间的结构信息;并设计了一种算法来实现在没有牺牲查询性能的前提下完全避免更新过程中的二次编码和重新计算,降低了更新代价,同时编码空间也得到了控制。实验结果显示,VEMBP具有较好的查询和更新性能。     

Using a relational database for scalable XML search

XML is a flexible and powerful tool that enables information and security sharing in heterogeneous environments. Scalable technologies are needed to effectively manage the growing volumes of XML data. A wide variety of methods exist for storing and searching XML data; the two most common techniques are conventional tree-based and relational approaches. Tree-based approaches represent XML as a tree and use indexes and path join algorithms to process queries. In contrast, the relational approach utilizes the power of a mature relational database to store and search XML. This method relationally maps XML queries to SQL and reconstructs the XML from the database results. To date, the limited acceptance of the relational approach to XML processing is due to the need to redesign the relational schema each time a new XML hierarchy is defined. We, in contrast, describe a relational approach that is fixed schema eliminating the need for schema redesign at the expense of potentially longer runtimes. We show, however, that these potentially longer runtimes are still significantly shorter than those of the tree approach. We use a popular XML benchmark to compare the scalability of both approaches. We generated large collections of heterogeneous XML documents ranging in size from 500 MB to 8 GB using the XBench benchmark. The scalability of each method was measured by running XML queries that cover a wide range of XML search features on each collection. We measure the scalability of each method over different query features as the collection size increases. In addition, we examine the performance of each method as the result size and the number of predicates increase. Our results show that our relational approach provides a scalable approach to XML retrieval by leveraging existing relational database optimizations. Furthermore, we show that the relational approach typically outperforms the tree-based approach while scaling consistently over all collections studied.

基于领域本体和关系模型的XML语义集成方法研究

由于缺乏足够的语义信息,不同模式的XML数据之间很难进行互操作。针对油气井工程中的XML数据集成需求,借助领域全局本体,提出一种模式无关的XML语义集成方法。该方法首先在XML Path路径与领域本体之间进行语义映射,屏蔽其模式差异;然后,按照模型映射方法将XML存储为关系数据;最后通过查询重写将SPARQL转换为SQL语句,实现语义查询。该方法对XML模式进行语义标注,利用关系数据库存储与查询XML数据,能有效处理领域XML数据的语义集成。     

Efficiently supporting order in XML query processing

XML is an ordered data model and XQuery expressions return results that have a well-defined order. However, little work on how order is supported in XML query processing has been done to date. In this paper we study the issues related to handling order in the XML context, namely challenges imposed by the XML data model, the variety of order requirements of the XQuery language, and the need to maintain order in the presence of updates to the XML data. We propose an efficient solution that addresses all these issues. Our solution is based on a key encoding for XML nodes that serves as node identity and at the same time encodes order. We design rules for encoding order of processed XML nodes based on the XML algebraic query execution model and the node key encoding. These rules do not require any actual sorting for intermediate results during execution. Our approach enables efficient order-sensitive incremental view maintenance as it makes most XML algebra operators distributive with respect to bag union. We prove the correctness of our order encoding approach. Our approach is implemented and integrated with Rainbow, an XML data management system developed at WPI. We have tested the efficiency of our approach using queries that have different order requirements. We have also measured the relative cost of different components related to our order solution in different types of queries. In general the overhead of maintaining order in our approach is very small relative to the query processing time.     

基于编码的XML关系数据库存储

在XML的发展过程中,如何有效地利用关系数据库技术存储和查询XML数据已经成为一个研究热点．提出了一种基于前、后序编码的XML关系数据库存储方法,该方法采用的模式映射方法能够使基于不同DTD（或schema）的XML文档保存在同一个关系表中,支持快速的XML路径查询,且具有较高的XML文档重组效率．对该方法中递归模式的处理技术也进行了讨论．实验表明,与XRel,Florescu和Kossman等人提出的XML关系数据库存储方法相比,该方法能够缩短复杂XML路径查询（如带条件谓词约束的路径查询）的响应时间．     

以XML文档发布关系数据

本文对以XML文档发布关系数据的新技术进行了综述，主要分析了两种发布关系数据到XML文档的语言描述及其实现技术，以及它们的优缺点，一种是利用并扩展SQL的功能来描述这种转换，嵌套的SQL表达式被利用来描述嵌套，扩展的SQL标量及聚集函数被利用来描述XML元素构造，实现将关系数据转换为XML文档，另一种是利用RXL（Relational to XML Transformation Language)语言来定义一个关系数据库的XML视图，该XML视图是虚的，其它应用可再利用XML查询语言XML－QL在虚拟的视图上构造一个查询，抽取XML视图中的数据片断并对抽取的部分进行物化，实现将关系数据转换为XML文档。     

XML数据库的安全查询处理

当今XML数据库查询系统必须处理快速增长的数据量和大量的用户,如果使用细粒度级别的访问控制保护敏感XML数据,则查询效率会较低,因为当用户视图需要计算得出时,很难对XML文档的每个节点实施访问控制。提出一个安全的XML查询方案,它使用缓存存储查询结果和安全信息。用户查询重写为安全的系统查询,依据缓存是否命中,决定在缓存还是源XML文档上执行得到查询结果;提出一个新的缓存替换策略LSL,它基于安全级别对缓存更新。实验结果表明,该方案能显著地改进查询系统性能。