Updating Recursive XML Views of Relations

This paper investigates the view update problem for XML views published from relational data.We consider XML views defined in terms of mappings directed by possibly reeursive DTDs compressed into DAGs and stored in relations. We provide new techniques to efficiently support XML view updates specified in terms of XPath expressions with recursion and complex filters.The interaction between XPath recursion and DAG compression of XML views makes the analysis of the XML view update problem rather intriguing.Furthermore,many issues are still open even for relational view updates, and need to be explored.In response to these,on the XML side,we revise the notion of side effects and update semantics based on the semantics of XML views,and present efficient algorithms to translate XML updates to relational view updates. On the relational side,we propose a mild condition on SPJ views,and show that under this condition the analysis of deletions on relational views becomes PTIME while the insertion analysis is NP-complete.We develop an efficient algorithm to process relational view deletions,and a heuristic algorithm to handle view insertions.Finally,we present an experimental study to verify the effectiveness of our techniques.     

基于Schema路径分析的XML数据库存储策略

With XML standards playing more and more important role at information exchanges in data management,the XML database storing strategy which supports huge amount XML data control from bottom layer of database has become the key part of fields such as content management. This article proposes an efficiently XML storing strategy from the perspective of constraint schema of XML instance based on XML Schema path analysis.     

Extending the relational model to deal with probabilistic data

According to the soundness and completeness of information in databases,the expressive form and the semantics of incomplete information are discussed in this paper.On the basis of the discussion,the current studies on incomplete data in relational databases are reviewed.In order to represent stochastic uncertainty in most general sense in the real world,probabilistic data are introduced into relational databases.An extended relational data model is presented to express and manipulate probabilistic data and the operations in relational algebra based on the extended model are defined in this paper.     

AbIx: An Approach to Content-Based Approximate Query Processing in Peer-to-Peer Data Systems

In recent years there has been a significant interest in peer-to-peer （P2P） environments in the community of data management. However, almost all work, so far, is focused on exact query processing in current P2P data systems. The autonomy of peers also is not considered enough. In addition, the system cost is very high because the information publishing method of shared data is based on each document instead of document set. In this paper, abstract indices （AbIx） are presented to implement content-based approximate queries in centralized, distributed and structured P2P data systems. It can be used to search as few peers as possible but get as many returns satisfying users＇ queries as possible on the guarantee of high autonomy of peers. Also, abstract indices have low system cost, can improve the query processing speed, and support very frequent updates and the set information publishing method. In order to verify the effectiveness of abstract indices, a simulator of 10,000 peers, over 3 million documents is made, and several metrics are proposed. The experimental results show that abstract indices work well in various P2P data systems.     

CSchema: A Downgrading Policy Language for XML Access Control

The problem of regulating access to XML documents has attracted much attention from both academic and industry communities. In existing approaches, the XML elements specified by access policies axe either accessible or inaccessible according to their sensitivity. However, in some cases, the original XML elements are sensitive and inaccessible, but after being processed in some appropriate ways, the results become insensitive and thus accessible. This paper proposes a policy language to accommodate such cases, which can express the downgrading operations on sensitive data in XML documents through explicit calculations on them. The proposed policy language is called calculation-embedded schema （CSchema）, which extends the ordinary schema languages with protection type for protecting sensitive data and specifying downgrading operations. CSchema language has a type system to guarantee the type correctness of the embedded calculation expressions and moreover this type system also generates a security view after type checking a CSchema policy. Access policies specified by CSchema are enforced by a validation procedure, which produces the released documents containing only the accessible data by validating the protected documents against CSchema policies. These released documents are then ready to be accessed by, for instance, XML query engines. By incorporating this validation procedure, other XML processing technologies can use CSchema as the access control module.     

Coordinating Mobile Agents by the XML-Based Tuple Space

This paper presents Xspace,a programmable coordination paradigm for Internet applications based on mobile agents.The Xspace system fully exploits the advantages of the XML language and Linda-like coordination.It supports XML documents as tuple fields and multiple matching routines implementing different relations among XML documents,including those given by XML query languages,The Xspace uses Java as the implementation language;it is based on object-oriented XMLized tuple spaces to implement a portable and programmable coordination paradigm for mobile agents.The dsign and implementation procedures of Xspace are described in this paper,Experiment and performance evaluation are also made.Finally,some conclusinos and remarks are given.     

A survey of uncertain data management

Uncertain data are data with uncertainty information,which exist widely in database applications.In recent years,uncertainty in data has brought challenges in almost all database management areas such as data modeling,query representation,query processing,and data mining.There is no doubt that uncertain data management has become a hot research topic in the field of data management.In this study,we explore problems in managing uncertain data,present state-of-the-art solutions,and provide future research directions in this area.The discussed uncertain data management techniques include data modeling,query processing,and data mining in uncertain data in the forms of relational,XML,graph,and stream.     

Incremental mining of the schema of semistructured data

Semistructued data are specified in lack of any fixed and rigid schema,even though typically some implicit structure appears in the data.The huge amounts of on-line applications make it important and imperative to mine the schema of semistructured data ,both for the users(e.g.,to gather useful information and facilitate querying)and for the systems (e.g.,to optimize access).The critical problem is to discover the hidden structure in the semistructured data.Current methods in extracting Web data structure are either in a general way independent of application background,or bound in some concrete environment such as HTML,XML etc.But both face the burden of expensive cost and difficulty in keeping along with the frequent and complicated variances of Web data.In this paper,the problem of incremental mining of schema for semistructured data after the update of the raw data is discusses.An algorithm for incrementally mining the schema of semistructured data is provided,and some experimental results are also given,which show that incremental mining for semistructured data is more efficient than non-incremental mining.     

Efficient aggregation algorithms on very large compressed data warehouses

Multidimensional aggregation is a dominant operation on data warehouses for on-line analytical processing(OLAP).Many efficinet algorithms to compute multidimensional aggregation on relational database based data warehouses have been developed.However,to our knowledge,there is nothing to date in the literature about aggregation algorithms on multidimensional data warehouses that store datasets in mulitidimensional arrays rather than in tables.This paper presents a set of multidimensional aggregation algorithms on very large and compressed multidimensional data warehouses.These algorithms operate directly on compressed datasets in multidimensional data warehouses without the need to first decompress them.They are applicable to a variety of data compression methods.The algorithms have different performance behavior as a function of dataset parameters,sizes of out puts and ain memory availability.The algorithms are described and analyzed with respect to the I/O and CPU costs,A decision procedure to select the most efficient algorithm ,given an aggregation request,is also proposed.The analytical and experimental results show that the algorithms are more efficient than the traditional aggregation algorithms.     

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.     

XN-Store:一种原生XML数据库的存储方案

随着XML相关标准的推广与应用,Web上出现了大量的XML文档,为了进行有效的管理,有必要将XML文档存储到数据库中,存储方案已成为XML数据管理领域研究的一个重要课题,将XML文档映射为关系表,存储到传统的RDBMS中,会破坏XML数据的树形结构,造成查询效率的下降,提出了一种新的用于原生XML数据库的存储方案--XN-Store,该方案基于索引结构将XML节点作为记录直接存储到分页文件中,建立起持久化文档对象模型,从而保持了XML数据原有的树形结构.XN-Store不仅降低了XML文档的存储空间开销,而且实现了XML节点的快速串行化输出和访问操作.作为通用的原生XML存储方案,XN-Store支持各种二级索引的创建,以提高XML查询处理的效率,采用多种数据集,分别在XN-Store和先前的XML存储系统上进行实验,比较存储空间、存储时间、串行化时间和节点访问时间.实验结果表明,XN-Store是一种高性能的原生XML数据库存储方案.     

商业RDBMS产品的XML支持

XML已成为Web上数据表示和数据交换的标准,随着Web上大量XML数据的出现,有必要对其进行有效的管理和处理。目前,几乎所有的商业数据库产品都进行了扩充,支持XML的存储、查询和发布。综述了三大商业RDBMS产品(Mierosoft SQL Server 2000 Web R2,Oracle 9i R2及IBM DB2 UDB V8)对XML的最新支持。     

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.     

Construction of an Optimal Relational Schema for Storing XML Documents in an RDBMS without Using DTD/XML Schema

The goal of this work is to construct an optimal relational schema for storing XML documents in a relational database (RDBMS) with the possibility of subsequently processing their elements without using information about the structure of these documents (such as DTD, XML Schema, and so on). A survey of the currently available methods for solving this problem is given, and the most promising among them from the standpoint of processing large arrays of documents are selected. Then, the methods selected are refined and modified, and, on the basis of these methods, a system for storing XML documents in an RDBMS is constructed. Finally, the performance of this system for each method considered is tested, and, by the results of these tests, an optimal relational schema is selected.     

一个XML的数据模型及其存储策略

XML是用于数据表示、交换的Internet标准。通过和DTD的连接可以用像XML－QL这样的语言来执行丰富的查询操作。近年来,很多人致力于半结构化数据模型和其查询语言的研究^[1,2,5],其重点逐渐转移到XML数据集的查询上来,其中两个重要问题是使XML查询语言正规化和如何将XML数据转换为底层存储格式以获得理想的效率^[4]。表述了一个XML的正规数据模型及其代数方法,并介绍基于RDBMS实现该模型的方法。     

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。     

Comparative Analysis of XML Compression Technologies

XML provides flexibility in publishing and exchanging heterogeneous data on the Web. However, the language is by nature verbose and thus XML documents are usually larger in size than other specifications containing the same data content. It is natural to expect that the data size will continue to grow as XML data proliferates on the Web. The size problem of XML documents hinders the applications of XML, since it substantially increases the costs of storing, processing and exchanging the data. The hindrance is more apparent in bandwidth- and memory-limited settings such as those applications related to mobile communication. In this paper, we survey a range of recently proposed XML specific compression technologies and study their efforts and capabilities to overcome the size problem. First, by categorizing XML compression technologies into queriable and unqueriable compressors, we explain the efforts in the representative technologies that aim at utilizing the exposed structure information from the input XML documents. Second, we discuss the importance of queriable XML compressors and assess whether the compressed XML documents generated from these technologies are able to support direct querying on XML data. Finally, we present a comparative analysis of the state-of-the-art XML conscious compression technologies in terms of compression ratio, compression and decompression times, memory consumption, and query performance.     

XML压缩算法的分析与比较

XML为在Web上发布和交换异质数据提供了相当的灵活性。但由于这种语言自身就有冗余的特性所以XML文档在体积都大于有相同数据内容的其他类型的文档。随着XML在Web上应用的扩展其数据大小自然也会随之而增加,而这实质上增加了数据的存储量、处理量和交换量,因此XML文档的体积问题也阻碍了XML的应用,特别是阻碍了XML在具有带宽和内存容量限制的应用上如移动通讯应用。在这篇文章中,我们将大致的介绍一下最近提出的几种针对XML的压缩算法并分析它们在解决XML文档体积问题上的技术和效能。     

XML压缩算法的分析与比较

XML为在Web上发布和交换异质数据提供了相当的灵活性。但由于这种语言自身就有冗余的特性所以XML文档在体积都大于有相同数据内容的其他类型的文档。随着XML在web上应用的扩展其数据大小自然也会随之而增加．而这实质上增加了数据的存储量、处理量和交换量，因此XML文档的体积问题也阻碍了XML的应用，特别是阻碍了XML在具有带宽和内存容量限制的应用上如移动通讯应用。在这篇文章中，我们将大致的介绍一下最近提出的几种针对XML的压缩算法并分析它们在解决XML文档体积问题上的技术和效能。