An encoding scheme based on fractional number for querying and updating XML data

In order to facilitate the XML query processing, several labeling schemes have been proposed to directly determine the structural relationships between two arbitrary XML nodes without accessing the original XML documents. However, the existing XML labeling schemes have to re-label the pre-existing nodes or re-calculate the label values when a new node is inserted into the XML document during an update process. In this paper, we devise a novel encoding scheme based on the fractional number to encode the labels of the XML nodes. Moreover, we propose a mapping method to convert our proposed fractional number based encoding scheme to bit string based encoding scheme with the intention to minimize the label size and save the storage space. By applying our proposed bit string encoding scheme to the range-based labeling scheme and the prefix labeling scheme, the process of re-labeling the pre-existing nodes can be avoided when nodes are inserted as leaf nodes and sibling nodes without affecting the order of XML nodes. In addition, we propose an algorithm to control the increment of label size when new nodes are inserted frequently at a fix place of an XML tree. Experimental results show that our proposed bit string encoding scheme provides efficient support to the process of XML updating without sacrificing the query performance when it is applied to the range-based labeling schemes.     

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.     

Matching twigs in fuzzy XML

A considerable amount of twig pattern matching algorithms have been proposed to holistically process a twig query. Those algorithms mainly focus on twig pattern query with the AND-logic. However, there is often a need to process a twig query with the OR-predicates. Furthermore, the existing algorithms fall short in their ability to support twig query with OR-logic in fuzzy XML. To overcome this limitation, in this paper, we first introduce a novel encoding scheme to represent node information in fuzzy XML. Based on the encoding scheme, we then propose an effective algorithm for matching a twig pattern query with the AND/OR-logic in fuzzy XML. Our approach adopts a compact stack technique to process the complicated twig query consisting of both AND-logic and OR-logic. More importantly, our method eliminates re-scanning unnecessary portions of XML documents and redundant intermediate results. Finally, the experimental results demonstrate the performance advantages of our approach.     

Parallel labeling of massive XML data with MapReduce

The volume of XML data has become enormous and still grows very quickly as many data have been typed in XML by virtue of its simplicity and extensibility. While a tree labeling algorithm has a crucial role in XML query processing, conventional algorithms are all sequential so that they fail to label a large volume of XML data in a timely manner. To address this issue, we devise parallel tree labeling algorithms for massive XML data. Specifically, we focus on how to efficiently label a single large XML file in parallel. We first propose parallel versions of two prominent tree labeling schemes based on the MapReduce framework. We then present techniques for runtime workload balancing and data repartition to solve performance issues caused by data skewness and MapReduce’s inherited limitation. Through extensive experiments with synthetic and real-world datasets on 15 nodes, we show that our parallel labeling algorithms are up to 17 times faster than conventional algorithms, providing strong durability against data skewness.     

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。     

A novel XML keyword query approach using entity subtree

Keyword query is an important means to find object information in XML document. Most of the existing keyword query approaches adopt the subtrees rooted at the smallest lowest common ancestors of the keyword matching nodes as the basic result units. The structural relationships among XML nodes are excessively emphasized but the semantic relevance is not fully exploited.To change this situation, we propose the concept of entity subtree and emphasis the semantic relevance among different nodes as querying information from XML. In our approach, keyword query cases are improved to a new keyword-based query language, Grouping and Categorization Keyword Expression (GCKE) and the core query algorithm, finding entity subtrees (FEST) is proposed to return high quality results by fully using the keyword semantic meanings exposed by GCKE. We demonstrate the effectiveness and the efficiency of our approach through extensive experiments.     

图结构模糊XML文档上的模式匹配算法

模糊XML文档是指包含不确定信息的XML文档。在模糊XML文档查询方面,现有的研究成果较少,并且都是基于树型结构的XML文档进行的。针对图结构下模糊XML文档的特征,设计了一组高效的图结构模糊XML文档上的模式匹配算法。该算法基于一种适合于图结构文档的索引方式,采用自底向上的结点匹配顺序,大大减少了结点的重复判断操作,也不需要进行局部匹配结果的归并以及针对PC关系设计额外的过滤函数。理论分析以及实验结果证明,提出的模式匹配算法不仅在小枝查询性能上优于现有的相关算法,而且能够较好地实现DAG模式匹配查询。     

XFlat: Query-friendly encrypted XML view publishing

The security of published XML data receives exceptional attention due to its sensitive nature in many applications. This paper proposes an XML view publishing method called XFlat. Compared with other methods, XFlat focuses on query performance over the published XML view while simultaneously protecting the sensitive data via encryption techniques. XFlat decomposes an XML tree into a set of sub-trees, in each of which multiple users have the same accessibility to all nodes, and may encrypt and store each sub-tree in a flat, sequential manner. This storage strategy can avoid the nested encryption cost in view construction and the nested decryption cost in query evaluation. In addition, we discuss how to generate a user-specific schema and how to minimize the total space cost of the published XML view when considering the overhead of the relationships among the sub-trees. We also propose an XML schema index to enhance query performance over the final XML view. The experimental results demonstrate the effectiveness and efficiency of the proposed XFlat method.     

Pattern Tree最小简单分解策略

PatternTree(PTQ)是复杂的树状结构,求解PTQ需要在XML文档集合中查找与之匹配的数据。在PTQ中,只有部分节点是需要输出的查询目标节点,其余节点则是中间结果。因此,如何在求解过程中尽量避免中间结果的产生,是XML查询优化面临的一个关键问题。论文提出了一种PTQ分解策略,能够根据不同查询操作的粒度,将PTQ分解为可用一种内部操作实现的最大片断集合。从而有效的限制中间结果的产生,提高查询效率。     

一种新的XML文档的存储平台SDML的实现技术

目前,XML文档数据库(NXD—Native XML DBMS)的设计和存储正受到越来越多的关注,这是由于它可以灵活地表示各种数据,尤其是那些关系模式无法表达的复杂的数据。已经有一些NXD产品出现。而对XML文档的存储的好坏直接影响到它的查询效率,基于此我们自主提出了一种高效的XML文档存储平台SDML。详细讨论了它的存储结构和实现细节。特别提出了如何解决具有大量结构相同元素的存储方法,并给出了在其上进行查询、插入、删除和索引维护等操作的解决方案。给出了这种结构I／O费用代价,并进行了相关的实现,为NXD的存储优化提供一种新的途径。     

一种XML文档索引及查询处理方式

本文首先论述了传统XML路径模式索引方式，在此基础上提出面向元素的XML文档索引方式和相关算法，以及使用扩展的后序遍历序号进行元素节点标识的方案，并给出了该索引方式和元素节点标识方案下规则路径表达式查询和树型模式查询处理的方法，最后说明该方式在效率上优于传统索引方式下规则路径表达式查询和树型模式查询处理。     

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.     

Native XML数据库的文档编码机制研究

Native XML数据库快速查询的实现,可以采用基于XML文档编码的结构连接算法。而结构连接算法的实现需要对XML文档进行编码,以便于快速判断XML文档树结点之间的祖先后裔关系。在对现有编码机制进行综述的前提下,提出一种新的XML文档编码机制——前缀整除编码（PDIV）机制。该机制编码形式简单,只需要一个正整数即可充分表示结点在XML文档树中的位置信息;可以实现祖先后裔关系的快速查询;支持XML文档的更新操作;编码长度较短,编码长度约为o（ln（n））。     

Object-stack: An object-oriented approach for top-k keyword querying over fuzzy XML

Keyword search is the most popular technique of searching information from XML (eXtensible markup language) document. It enables users to easily access XML data without learning the structure query language or studying the complex data schemas. Existing traditional keyword query methods are mainly based on LCA (lowest common ancestor) semantics, in which the returned results match all keywords at the granularity of elements. In many practical applications, information is often uncertain and vague. As a result, how to identify useful information from fuzzy data is becoming an important research topic. In this paper, we focus on the issue of keyword querying on fuzzy XML data at the granularity of objects. By introducing the concept of “object tree”, we propose the query semantics for keyword query at object-level. We find the minimum whole matching result object trees which contain all keywords and the partial matching result object trees which contain partial keywords, and return the root nodes of these result object trees as query results. For effectively and accurately identifying the top-K answers with the highest scores, we propose a score mechanism with the consideration of tf*idf document relevance, users’ preference and possibilities of results. We propose a stack-based algorithm named object-stack to obtain the top-K answers with the highest scores. Experimental results show that the object-stack algorithm outperforms the traditional XML keyword query algorithms significantly, and it can get high quality of query results with high search efficiency on the fuzzy XML document.     

Compact Labeling Scheme for XML Ancestor Queries

XML documents are often viewed as trees (basically the parse tree of the document), and queries over such documents typically test for ancestor relationships among tree nodes. Search engines process such queries using an index structure summarizing the ancestor relations. In the index, each document item (tree node) is identified using some logical id (node label), such that, given two labels, the engine can determine the ancestor relationship between the corresponding nodes. The length of the labels is a main factor of the index size. Therefore, reducing this length, even by a constant factor, is a critical issue. In this work we consider the following problem. Given a rooted XML tree T, label the nodes of T in the most compact way such that given the labels of two nodes, one can determine in constant time, by looking at the labels only, whether one node is an ancestor of the other. Labelings currently being used are all variants of the following interval scheme. Number the leaves say from left to right and label each node with a pair consisting of the numbers of its smallest and largest leaf descendants. An ancestor query then amounts to an interval containment test on the labels. The maximum label length using this scheme is 2 log n, where n is the number of nodes in the tree. (All logarithms in this paper are to base 2.) The focus of this work is finding a scheme that works best in practice on real XML data. We suggest an orthogonal prefix-based approach, where the labeling is such that an ancestor query roughly amounts to testing whether one label is a prefix of the other. We present several new labeling schemes based on this approach and analyze their performance both theoretically and empirically.     

DTD约束下的XML树模式查询最小化

目前大部分XML查询语言都使用树模式来匹配待查询的XML文档树以得到所需要的、与模式树相吻合的查询结果,此效率在很大程度上取决于XML模式树的大小,那么尽可能快速地查找并删除查询模式树中的冗余节点就变得十分重要。重点讨论DTD约束下树模式的最小化问题,将DTD兄弟约束SC拓展成扩展兄弟约束ESC,使其能够表达DTD约束中的祖先-后代关系;并指出只包含{ESC,/,//,[],*}的查询树模式的最小化问题的复杂度是指数级的,且当模式树是分支受限的时候,其最小化问题的复杂度是多项式时间的;最后给出了一个多项式时间的受限分支的模式树最小化算法。     

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。     

TwigEN：一种新的小枝模式匹配算法

随着互联网的迅速发展,XML已经成为网上通用的数据表示与交换的标准。因此,如何有效地查询XML数据成为一个重要的研究课题。近年来,小枝模式匹配问题已被广泛地研究,提出了不少小枝模式匹配算法。在汲取各种小枝模式匹配算法优点的基础上,提出了一种新的小枝模式匹配算法TwigEN。根据XML文档结构它可以跳过那些在结构连接中无用的元素结点,这样不仅减少了待处理结点的数目,缩短了处理时间,而且也节省了内存空间。     

PS+Pre/Post: A novel structure and access mechanism for wireless XML stream supporting twig pattern queries

XML data broadcast is an efficient way to disseminate XML data to a large number of mobile clients in mobile wireless networks. Recently, several indexing methods have been proposed to improve the performance of XML query processing in terms of access time and tuning time over XML streams. However, existing indexing methods cannot process twig pattern XML queries. In this paper, we propose a novel structure for streaming XML data called PS+Pre/Post by integrating the path summary technique and the pre/post labeling scheme. Our proposed XML stream structure exploits the benefits of the path summary technique and the pre/post labeling scheme to efficiently process different types of XML queries over the broadcast stream. Experimental results show that our proposed XML stream structure improves the performance of access time and tuning time in processing different types of XML queries.     

SXBP：基于Pri—order编码的XML文档存储方法

随着XML技术的发展，如何利用现有的数据库技术存储和查询XML文档已成为XML数据管理领域研究的热点问题。本文介绍了一种新的文档编码方法，以及基于这种编码方式提出了一种新的XML文档存储方法。方法按照文档中结点类型将XML文档树型结构分解为结点，分别存储到对应的关系表中，这种方法能够将任意结构的文档存储到一个固定的关系模式中。同时为了便于实现数据的查询，将文档中出现的简单路径模式也存储为一个表。这种新的文档存储方法能够有效地支持文档的查询操作，并能根据结点的编码信息实现原XML文档的正确恢复。最后，对本文提出的存储方法和恢复算法进行了实验验证。