基于XML的多分支模式匹配算法

随着XML文档大量涌现,如何有效地管理和查询XML数据已经成为亟待解决的问题。在数据库中,基于视图的查询重写技术是查询优化的一个重要技术,利用缓存的视图结果回答新查询不需要访问源数据库进行查询,能够节省查询处理时间。本文在研究基于物化视图的查询重写的过程中,给定一个查询和一个视图,首先判断该查询在视图下是否存在查询重写,而重写的存在问题与模式包含问题密切相关,为此,提出使用多分支的模式匹配算法实现对多分支路径的模式匹配,解决重写是否存在的问题。     

基于视图的XML重写技术的研究综述

支持正则路径表达式的查询技术,被认为是半结构化数据模式下的XML查询研究领域中一种颇具有研究价值的XML查询计算方法.基于视图的查询重写技术充分利用视图中的信息来对查询进行优化,提高查询效率.本文讨论了对于支持正则路径表达式的XML查询如何进行重写的问题以及对不同技术的分析.     

XML递归安全视图的查询重写算法

XML(Extensive Markup Language)安全视图和查询重写是实现访问控制的关键技术.研究了基于XML递归安全视图的查询重写问题,分析了以前有关查询重写的研究工作,提出了一种基于XPath查询语言的能处理递归视图的查询重写算法,并对算法进行了分析,解决了当安全视图中存在递归时把查询进行有效重写的问题,避免了视图的物化和保存.     

XQuery视图机制

从XML数据安全性考虑,在已经使用XQuery作为查询语言的前提下,为增强XQuery对XML文档查询能力,创造了类似关系数据库视图的XQuery视图机制,使得不同用户对XML文档具有不同的查看能力,保证查询安全可靠.XQuery视图由查询来定义其内容,分为实视图和虚视图两种.虚视图根据需要计算视图定义的查询,而实视图不管以后是否需要,只要一创建就计算其视图定义,类似关系数据库视图,实视图和虚视图对于数据查询都是必要的.     

XQuery视图机制

从XML数据安全性考虑，在已经使用XQuery作为查询语言的前提下，为增强XQuery对XML文档查询能力，创造了类似关系数据库视图的XQuery视图机制，使得不同用户对XML文档具有不同的查看能力，保证查询安全可靠。XQuery视图由查询来定义其内容，分为实视图和虚视图两种。虚视图根据需要计算视图定义的查询，而实视图不管以后是否需要，只要一创建就计算其视图定义，类似关系数据库视图，实视图和虚视图对于数据查询都是必要的。     

基于XPath的XML查询重写算法

XML安全视图和查询重写是实现访问控制的关键技术。研究基于XML递归安全视图的查询重写问题,提出一种基于XPath查询语言、能处理递归视图的查询重写算法,避免了视图的物化和保存。该算法具有较高通用性,实验结果验证了其有效性。     

基于视图的正则路径查询重写

正则路径查询的重写是实现XML查询重写优化的基础。通过比较正则路径视图和正则路径查询的结构信息,分析了两者之间进行映射应满足的条件,描述了正则路径视图到正则路径查询的映射和基于有穷自动机的映射过滤算法,并从理论上阐明了两个算法的重写等价性。借助于此两个算法,能够极大地减少需要求解的映射数目和提高正则路径查询处理的效率。     

基于安全更新视图的XML更新控制方法

为了便于用户对XML文档进行更新,同时又保证安全性,提出了一种基于安全更新视图的XML文档的更新控制方法.通过在安全视图的基础上引入Insert、Delete和Replace等更新标记,形成安全更新视图,并提供给用户.对于安全更新视图上用户提交的更新请求Q,给出了授权检查算法和重写为原XML文档上等价更新操作的算法.此方法可以有效地处理XML文档上的更新请求,完成对XML的更新控制;同时由于只向用户提供了对其可见的安全更新视图,从而避免了信息泄漏.     

基于物化视图的查询系统研究与实现

在数据库领域,如何加快查询的执行速度非常重要。查询重写技术能透明地利用物化视图回答查询,避免了直接访问大量的原始记录以及耗时的连接和聚集计算,提高了查询 的执行速度。本文讨论了基于数据库中的外键连接关系进行扩展的查询重写方法,以此为核心研究了针对小型数据库的物化视图查询系统,并通过实验证明了物化视图策略的有效性。     

一种通用连接查询的重写方法

使用实视图进行查询优化的关键,是从实视图中找到执行代价较小的查询重写.本文提出了一种基于目标的方法,可以找到更多的候选方案,当查询的内置谓词只包含特征变量时该方法更加有效.在更多时候,它可以找到由Bucket算法找到的所有重写,而且更高效.     

Incremental Design of a Data Warehouse

A data warehouse (DW) can be seen as a set of materialized views defined over remote base relations. When a query is posed, it is evaluated locally, using the materialized views, without accessing the original information sources. The DWs are dynamic entities that evolve continuously over time. As time passes, new queries need to be answered by them. Some of these queries can be answered using exclusively the materialized views. In general though new views need to be added to the DW.In this paper we investigate the problem of incrementally designing a DW when new queries need to be answered and possibly extra space is allocated for view materialization. Based on an AND/OR dag representation of multiple queries, we model the problem as a state space search problem. We design incremental algorithms for selecting a set of new views to additionally materialize in the DW that: (a) fits in the extra space, (b) allows a complete rewriting of the new queries over the materialized views, and (c) minimizes the combined new query evaluation and new view maintenance cost. Finally, we discuss methods for pruning the search space so that efficiency is improved.     

HIFUN - a high level functional query language for big data analytics

We present a high level query language, called HIFUN, for defining analytic queries over big datasets, independently of how these queries are evaluated. An analytic query in HIFUN is defined to be a well-formed expression of a functional algebra that we define in the paper. The operations of this algebra combine functions to create HIFUN queries in much the same way as the operations of the relational algebra combine relations to create algebraic queries. The contributions of this paper are: (a) the definition of a formal framework in which to study analytic queries in the abstract; (b) the encoding of a HIFUN query either as a MapReduce job or as an SQL group-by query; and (c) the definition of a formal method for rewriting HIFUN queries and, as a case study, its application to the rewriting of MapReduce jobs and of SQL group-by queries. We emphasize that, although theoretical in nature, our work uses only basic and well known mathematical concepts, namely functions and their basic operations.     

Web数据集成系统基于QC模型的物化视图选择

在Web数据集成系统中,物化视图能够有效地减少网络传输代价,提高系统的查询效率．如何选择查询进行物化,使得选中的查询满足集成层的空间限制,同时获取最大物化收益,成为集成系统中一个迫切需要解决的问题．传统方法没有考虑到海量XML查询之间的包含关系,其选择的物化视图中可能包含冗余的信息．针对上述问题,提出了①Web数据集成系统中海量查询集合的QC(query containment)模型,该模型能够捕捉查询之间最常见的包含关系;②基于QC模型的物化视图选择算法,算法考虑了物化视图选择相关的主要因素,包括查询提交的频率、空间代价、查询重写能力和查询结果的完备性,提出了查询位图的物化视图组织方式,从而获取更加合理的物化视图选择方案．实验结果证明了该方法的有效性．     

数据集成中XML数据查询语义重写

查询重写是数据库研究的一个基本问题，它和查询优化，数据仓库，数据集成，语义缓存等数据库问题密切相关，为提高集成系统的查询效率，系统选择提交频率较高的XML查询物化为中间层视图，用户提交查询后，系统尽可能利用中间视图层中视图，而不是访问数据源来回答查询，这个问题实际可以归结为半结构化查询重写问题，考虑到中间视图层空间的有限性，已有视图应当尽可能回答更多的查询，传统查询重写方法有考虑半结构化数据之间的约束，而根据约束可以等价变换查询，从而提高中间视图层中的表达能力，提出了一种新的半结构化查询重写的方法，该方法在保证算法正确性和完备性的基础上，利用上半结构化数据中的约束，尤其是XML文件中的路径依赖，来增强中间层物化视图的表达能力，理论分析和初步原型实验证明方法的有效性。     

Query rewritings using views for XPath queries,framework, and methodologies

Query rewriting using views is a technique that allows a query to be answered efficiently by using pre-computed materialized views. It has many applications, such as data caching, query optimization, schema integration, etc. This issue has been studied extensively for relational databases and, as a result, the technology is maturing. For XML data, however, the work is inadequate. Recently, several frameworks have been proposed for query rewriting using views for XPath queries, with the requirement that a rewriting must be complete. In this paper, we study the problem of query rewriting using views for XPath queries without requiring that the rewriting be complete. This will increase its applicability since in many cases, complete rewritings using views do not exist. We give formal definitions for various concepts to formulate the problem, and then propose solutions. Our solutions are built under the framework for query containment. We look into the problem from both theoretic perspectives, and algorithmic approaches. Two methods to generate rewritings using views are proposed, with different characteristics in terms of generalities and efficiencies. The maximality properties of the rewritings generated by these methods are discussed.     

Efficient evaluation of query rewriting plan over materialized XML view

The query rewriting plan generation over XML views has received wide attention recently. However, little work has been done on efficient evaluation of the query rewriting plans, which is not trivial since the plan may contain an exponential size of sub-plans. This paper investigates the reason for the potentially exponential number of sub-plans, and then proposes a new space-efficient form called ABCPlan (Plan with Automata Based Combinations) to equivalently represent the original query rewriting plan. ABCPlan contains a set of buckets containing suffix paths in the query tree and an automata to indicate the combination of the suffix paths from different buckets as valid query rewriting sub-plans. We also design an evaluation method called ABCScan, which constructs a unified evaluation tree for the ABCPlan and handles the evaluation tree in one scan of the XML view. In the evaluation, we introduce node existence automata to encode the structure of the sub-tree and convert the satisfaction of the ABCPlan into the intersection problem of deterministic finite automata. The experiments show that ABCPlan based method outperforms existing methods significantly in terms of scalability and efficiency.     

一种扩充语义的实视图重写查询技术

分组聚集查询已成为数据仓库领域研究的核心问题之一,实视图是提高分组聚集查询性能的有效手段。利用维属性间的层次关系,对一般意义上的实视图重写查询进行了扩展,讨论了单一视图重写查询的限制条件,并给出重写方法,在此基础上,提出了一种利用多个实视图重写查询的优化选择算法,并通过实验表明,该算法进一步提高了分组聚集查询效率。     

Updating XML views published over relational databases: Towards the existence of a correct update mapping

XML data management using relational database systems has been intensively studied in the last few years. However, in order for such systems to be viable, they must support not only queries, but also updates over virtual XML views that wrap the relational data. While view updating is a long-standing difficult issue in the relational context, the flexible XML data model and nested XML query language both pose additional challenges for view updating.

This paper addresses the question, if for a given update over an XML view, a correct relational update translation exists. First, we propose a clean extended-source theory as criteria for determining whether a given translation mapping is correct. To determine the existence of such a correct mapping, we classify a view update as either un-translatable, conditionally or unconditionally translatable under a given update translation policy. This classification depends on several features of the XML view and the update: (a) granularity of the update at the view side, (b) properties of the view construction, and (c) types of duplication appearing in the view. These features are represented in the Annotated Schema Graph. This is further utilized by our Schema-driven Translatability Reasoning algorithm (STAR) to classify a given update into one of the three above update categories. The correctness of the algorithm is proven using our clean extended-source theory. This technique represents a practical approach that can be applied by any existing view update system in industry and academia for analyzing the translatability of a given update statement before translation of it is attempted. To illustrate the working algorithm, we provide a concrete case study on the translatability of XML view updates.