Consistent query answers from virtually integrated XML data

When data sources are virtually integrated, there is no common and centralized method to maintain global consistency, so inconsistencies with regard to global integrity constraints are very likely to occur. In this paper, we consider the problem of defining and computing consistent query answers when queries are posed to virtual XML data integration systems, which are specified following the local-as-view approach. We propose a powerful XML constraint model to define global constraints, which can express keys and functional dependencies, and which also extends the newly introduced conditional functional dependencies to XML. We provide an approach to defining XML views, which supports not only edge-path mappings but also data-value bindings to express the join operator. We give formal definitions of repair and consistent query answers with the XML data integration settings. Given a query on the global system, we present a two-step method to compute consistent query answers. First, the given query is transformed using the global constraints, such that to run the transformed query on the original global system will generate exactly the consistent query answers. Because the global instance is not materialized, the query on the global instance is then rewritten in the form of queries on the underlying data sources by reversing rules in view definitions. We illustrate that the XPath query transformations can be implemented in XQuery. Finally, we implement prototypes of our method and evaluate our algorithms in the experiments.     

Query optimization in XML structured-document databases

While the information published in the form of XML-compliant documents keeps fast mounting up, efficient and effective query processing and optimization for XML have now become more important than ever. This article reports our recent advances in XML structured-document query optimization. In this article, we elaborate on a novel approach and the techniques developed for XML query optimization. Our approach performs heuristic-based algebraic transformations on XPath queries, represented as PAT algebraic expressions, to achieve query optimization. This article first presents a comprehensive set of general equivalences with regard to XML documents and XML queries. Based on these equivalences, we developed a large set of deterministic algebraic transformation rules for XML query optimization. Our approach is unique, in that it performs exclusively deterministic transformations on queries for fast optimization. The deterministic nature of the proposed approach straightforwardly renders high optimization efficiency and simplicity in implementation. Our approach is a logical-level one, which is independent of any particular storage model. Therefore, the optimizers developed based on our approach can be easily adapted to a broad range of XML data/information servers to achieve fast query optimization. Experimental study confirms the validity and effectiveness of the proposed approach.     

Enabling Schema-Free XQuery with meaningful query focus

The widespread adoption of XML holds the promise that document structure can be exploited to specify precise database queries. However, users may have only a limited knowledge of the XML structure, and may be unable to produce a correct XQuery expression, especially in the context of a heterogeneous information collection. The default is to use keyword-based search and we are all too familiar with how difficult it is to obtain precise answers by these means. We seek to address these problems by introducing the notion of Meaningful Query Focus (MQF) for finding related nodes within an XML document. MQF enables users to take full advantage of the preciseness and efficiency of XQuery without requiring (perfect) knowledge of the document structure. Such a Schema-Free XQuery is potentially of value not just to casual users with partial knowledge of schema, but also to experts working in data integration or data evolution. In such a context, a schema-free query, once written, can be applied universally to multiple data sources that supply similar content under different schemas, and applied “forever” as these schemas evolve. Our experimental evaluation found that it is possible to express a wide variety of queries in a schema-free manner and efficiently retrieve correct results over a broad diversity of schemas. Furthermore, the evaluation of a schema-free query is not expensive: using a novel stack-based algorithm we developed for computing MQF, the overhead is from 1 to 4 times the execution time of an equivalent schema-aware query. The evaluation cost of schema-free queries can be further reduced by as much as 68% using a selectivity-based algorithm we develop to enable the integration of MQF operation into the query pipeline.     

Answering XML Queries Using Path-Based Indexes: A Survey

The problem of answering XML queries using path-based indexes is to find efficient methods for accelerating the XML query with pre-designed index structures over the XML database. This problem received increasing interests and have been lucubrated in recent years. Regular path expression is the core of the XML query languages e.g., XPath and XQuery. Most of the state-of-the-art path-based XML indexes, therefore, hammer at how to efficiently answer the path-based XML queries. This paper surveys various approaches to indexing XML data proposed in the literature. We give a step by step analysis to show the evolution of index structures for XML path information, based on tree structures or more commonly, directed labeled graphs. For each approach, we first present the specific issue it aims to tackle, and then the proposed solution presented. Furthermore, construction, physical data storage and maintenance costs, are analyzed.     

Efficient processing of XPath queries using indexes

A number of indexing techniques have been proposed in recent times for optimizing the queries on XML and other semi-structured data models. Most of the semi-structured models use tree-like structures and query languages (XPath, XQuery, etc.) which make use of regular path expressions to optimize the query processing. In this paper, we propose two algorithms called Entry-point algorithm (EPA) and Two-point Entry algorithms that exploit different types of indices to efficiently process XPath queries. We discuss and compare two approaches namely, Root-first and Bottom-first in implementing the EPA. We present the experimental results of the algorithms using XML benchmark queries and data and compare the results with that of traditional methods of query processing with and without the use of indexes, and ToXin indexing approach. Our algorithms show improved performance results than the traditional methods and Toxin indexing approach.     

Cost-based holistic twig joins

An evaluation of XML queries such as XQuery or XPath expressions represents a challenging task due to its complexity. Many algorithms have been introduced to cope with this problem. Some of them, called binary joins, evaluate separated parts of a query and subsequently merge intermediate results, while the others, called holistic twig joins, evaluate a query as a whole. Moreover, these algorithms also differ in what index data structure they use to handle XML data. There exist cost-based approaches utilizing binary joins and various index data structures; however, they share a limitation. The limitation is that they cannot perform a join between query nodes not having a direct XPath relationship. Such a join can be advantageous especially if their joint selectivity is high. Since holistic joins work with all query nodes they overcome this limitation. In this article, we introduce such a holistic twig join called CostTwigJoin. To the best of our knowledge, CostTwigJoin is the first holistic join capable of combining various index data structures during an evaluation of an XML query. Usage of the holistic join has yet another advantage for cost-based approaches: an optimizer does not have to resolve the order of binary joins; therefore, the search space is reduced. In this article, we perform thorough experiments on hundreds of queries to evaluate our approach and demonstrate its advantages.     

基于模式语义的非膨胀性Pattern Tree简化

近年来,XQuery逐渐成为XML查询语言的事实标准。PatternTree被广泛应用于XQuery查询处理。PatternTree用匹配方法处理查询,其本身的大小和复杂程度决定了匹配的效率。该文论述了利用模式语义简化PatternTree的规则。这种方法避免了因插入冗余节点而导致PatternTree的膨胀。三个判断冗余节点的规则不但可以判断叶节点的冗余,而且可以在保留叶节点的情况下,判断非叶节点的冗余。实验证明了方法的可行性和有效性。     

基于关系数据库有效地实现RPE查询

各种XML查询语言的共同特点就是利用正则路径表达式(RPE)来导航XML文档的查询。本文结合我们提出的一种新的XML数据的关系存储模式，对有效地实现RPE查询的相关研究工作进行了总结，并提出了两个有效地实现包含连接的索引改进归并连接算法。算法采用索引定位技术、短路技术和预侦技术来减少连接代价。因此，不仅能够在当前上下文计算环境下有效地实现包含连接的计算，而且能够大量地避免包含连接中不必要的扫描和搜索。     

支持全文检索的XQuery查询处理及优化的研究

XQuery作为由W3C组织提出的一种XML查询语言,正在成为当前应用于XML数据库中对XML数据操作的一个规范。为了提高对XML中文本内容的查询支持,W3C又进一步设计了支持全文检索功能的语法规范。针对最新的XQuery及全文检索语法特征,文章提出了支持全文检索功能XQuery的解析与查询执行策略,为XQuery的查询处理提供解决方案。在此基础上,针对全文检索功能的查询执行计划,提出了适用于窗口查询,距离查询,是否排序查询的优化方案,以减少查询执行的代价,提高XQuery查询的效率。     

基于代数的Transform查询优化策略

XQuery/Update中定义了一种特殊的查询--Transform查询.Transform查询类似于关系数据库中的假设查询,可以表示成假设查询的一般形式:"Q when{U}",即查询Q的查询结果是假设数据库执行了更新操作{U}以后的结果,而更新操作U实际不修改数据库的状态.Transform查询需要拷贝XML数据库中的结点,并对拷贝的结点执行更新操作,所以不影响数据库的状态.但该操作通常拷贝和更新了大量与查询结果无关的结点,因此如何减少拷贝与更新操作的代价是Transform查询处理优化的关键.提出了基于OrientXA的Transform查询优化方法,并在NativeXML数据库系统OrientX 3.0里实现和验证了该方法.     

An efficient algorithm of frequent XML query pattern mining for ebXML applications in e-commerce

Providing efficient query to XML data for ebXML applications in e-commerce is crucial, as XML has become the most important technique to exchange data over the Internet. ebXML is a set of specifications for companies to exchange their data in e-commerce. Following the ebXML specifications, companies have a standard method to exchange business messages, communicate data, and business rules in e-commerce. Due to its tree-structure paradigm, XML is superior for its capability of storing and querying complex data for ebXML applications. Therefore, discovering frequent XML query patterns has become an interesting topic for XML data management in ebXML applications. In this paper, we present an efficient mining algorithm, namely ebXMiner, to discover the frequent XML query patterns for ebXML applications. Unlike the existing algorithms, we propose a new idea by collecting the equivalent XML queries and then enumerating the candidates from infrequent XML queries in our ebXMiner. Furthermore, our simulation results show that ebXMiner outperforms other algorithms in its execution time.     

Adaptive relaxation for querying heterogeneous XML data sources

Searching XML data with a structured XML query can improve the precision of results compared with a keyword search. However, the structural heterogeneity of the large number of XML data sources makes it difficult to answer the structured query exactly. As such, query relaxation is necessary. Previous work on XML query relaxation poses the problem of unnecessary computation of a big number of unqualified relaxed queries. To address this issue, we propose an adaptive relaxation approach which relaxes a query against different data sources differently based on their conformed schemas. In this paper, we present a set of techniques that supports this approach, which includes schema-aware relaxation rules for relaxing a query adaptively, a weighted model for ranking relaxed queries, and algorithms for adaptive relaxation of a query and top-k query processing. We discuss results from a comprehensive set of experiments that show the effectiveness and the efficiency of our approach.     

S2CX: From relational data via SQL/XML to (Un-)Compressed XML

The gap between storing data in relational databases and transferring data in form of XML has been closed e.g. by SQL/XML queries that generate XML data out of relational data sources. However, only few relational database systems support the evaluation of SQL/XML queries. And even in those systems supporting SQL/XML, the evaluation of such queries is quite slow compared to the evaluation of SQL queries. In this paper, we present S2CX, an approach that allows to efficiently evaluate SQL/XML queries on any relational database system, no matter whether it supports SQL/XML or not. As a result to an SQL/XML query, S2CX supports different output formats ranging from plain XML to different compressed XML representations including a succinct encoding of XML data, schema-aware compressed XML to grammar compressed XML. In many cases, S2CX produces compressed XML as a result to an SQL/XML query even faster than the evaluation of SQL/XML queries into non-compressed XML as provided by Oracle 11 g and by DB2. Furthermore, our approach to query evaluation scales better, i.e., the larger the dataset, the faster is our approach compared to SQL/XML query evaluation in Oracle 11 g and in DB2.     

Detecting common subexpressions for multiple query optimization over loosely-coupled heterogeneous data sources

The research presented in this paper supports the identification of common subexpressions as candidates for potential materialized views that form the basis of multiple query optimization in a loosely-coupled distributed system where query expressions access heterogeneous data sources, including relations and data-centric XML. This paper introduces a unifying mixed multigraph formalism to represent SQL, XQuery, and LINQ queries in a common query graph model and a heuristics-based algorithm to detect common subexpressions. The identified common subexpressions represent an opportunity for defining a materialized view to avoid repeating computation. The common subexpressions may access only relations, only XML, or a combination of relations and XML. The mixed multigraph model and the heuristic rules presented in this paper have distinguished advantages over the existing approaches that consider only relational or XML data sources individually. The mixed multigraph model can present SQL, XQuery, and LINQ queries in a single graph model and the heuristic rules are designed to consider the identical and subsumed conditions at the same time. A prototype implementation of the algorithm illustrates the applicability of the approach using various examples from the research literature as well as scenarios over a Criminal Justice enterprise that include common subexpressions across relational and XML data sources.     

Dynamic interval-based labeling scheme for efficient XML query and update processing

XML data can be represented by a tree or graph structure and XML query processing requires the information of structural relationships among nodes. The basic structural relationships are parent-child and ancestor-descendant, and finding all occurrences of these basic structural relationships in an XML data is clearly a core operation in XML query processing. Several node labeling schemes have been suggested to support the determination of ancestor-descendant or parent-child structural relationships simply by comparing the labels of nodes. However, the previous node labeling schemes have some disadvantages, such as a large number of nodes that need to be relabeled in the case of an insertion of XML data, huge space requirements for node labels, and inefficient processing of structural joins. In this paper, we propose the nested tree structure that eliminates the disadvantages and takes advantage of the previous node labeling schemes. The nested tree structure makes it possible to use the dynamic interval-based labeling scheme, which supports XML data updates with almost no node relabeling as well as efficient structural join processing. Experimental results show that our approach is efficient in handling updates with the interval-based labeling scheme and also significantly improves the performance of the structural join processing compared with recent methods.     

Schema mapping and query translation in heterogeneous P2P XML databases

Peers in a peer-to-peer data management system often have heterogeneous schemas and no mediated global schema. To translate queries across peers, we assume each peer provides correspondences between its schema and a small number of other peer schemas. We focus on query reformulation in the presence of heterogeneous XML schemas, including data–metadata conflicts. We develop an algorithm for inferring precise mapping rules from informal schema correspondences. We define the semantics of query answering in this setting and develop query translation algorithm. Our translation handles an expressive fragment of XQuery and works both along and against the direction of mapping rules. We describe the HePToX heterogeneous P2P XML data management system which incorporates our results. We report the results of extensive experiments on HePToX on both synthetic and real datasets. We demonstrate our system utility and scalability on different P2P distributions.     

Path Summaries and Path Partitioning in Modern XML Databases

XML path summaries are compact structures representing all the simple parent-child paths of an XML document. Such paths have also been used in many works as a basis for partitioning the document’s content in a persistent store, under the form of path indices or path tables. We revisit the notions of path summaries and path-driven storage model in the context of current-day XML databases. This context is characterized by complex queries, typically expressed in an XQuery subset, and by the presence of efficient encoding techniques such as structural node identifiers. We review a path summary’s many uses for query optimization, and given them a common basis, namely relevant paths. We discuss summary-based tree pattern minimization and present some efficient summary-based minimization heuristics. We consider relevant path computation and provide a time- and memory-efficient computation algorithm. We combine the principle of path partitioning with the presence of structural identifiers in a simple path-partitioned storage model, which allows for selective data access and efficient query plans. This model improves the efficiency of twig query processing up to two orders of magnitude over the similar tag-partitioned indexing model. We have implemented the path-partitioned storage model and path summaries in the XQueC compressed database prototype [8]. We present an experimental evaluation of a path summary’s practical feasibility and of tree pattern matching in a path-partitioned store.     

Efficient recursive XML query processing using relational database systems

Recursive queries are quite important in the context of XML databases. In addition, several recent papers have investigated a relational approach to store XML data and there is growing evidence that schema-conscious approaches are a better option than schema-oblivious techniques as far as query performance is concerned. However, the issue of recursive XML queries for such approaches has not been dealt with satisfactorily. In this paper we argue that it is possible to design a schema-oblivious approach that outperforms schema-conscious approaches for certain types of recursive queries. To that end, we propose a novel schema-oblivious approach, called Sucxent++ (Schema Unconcious XML Enabled System), that outperforms existing schema-oblivious approaches such as XParent by up to 15 times and schema-conscious approaches (Shared-Inlining) by up to eight times for recursive query execution. Our approach has up to two times smaller storage requirements compared to existing schema-oblivious approaches and 10% less than schema-conscious techniques. In addition Sucxent++ performs marginally better than Shared-Inlining and is 5.7–47 times faster than XParent as far as insertion time is concerned.     

Querying XML streams

Efficient querying of XML streams will be one of the fundamental features of next-generation information systems. In this paper we propose the TurboXPath path processor, which accepts a language equivalent to a subset of the for-let-where constructs of XQuery over a single document. TurboXPath can be extended to provide full XQuery support or used to augment federated database engines for efficient handling of queries over XML data streams produced by external sources. Internally, TurboXPath uses a tree-shaped path expression with multiple outputs to drive the execution. The result of a query execution is a sequence of tuples of XML fragments matching the output nodes. Based on a streamed execution model, TurboXPath scales up to large documents and has limited memory consumption for increased concurrency. Experimental evaluation of a prototype demonstrates performance gains compared to other state-of-the-art path processors.Received: 30 January 2003, Accepted: 4 February 2004, Published online: 8 April 2004Edited by: R. Baeza-Yates.     

XQuery简介及在.Net中的应用

XML是一种通用标记语言,它能对各种数据源的信息内容进行标记,包括结构化和半结构化文档、关系数据库和对象库,不管它们是物理存储在XML中还是通过中间产生展现为XML,都能够智能地使用XML结构化查询语言表达或查询这些类型数据。XQuery是定位于XML的查询语言,它能广泛应用于很多类型的XML数据源。