XML Query Research Articles

RSS query algebra: Towards a better news management

Existing XML query algebras are not fully appropriate to retrieve RSS news items mainly due to three reasons: (1) RSS document is text rich and its content is dependent on the wording and verification of the author, thus semantic-aware operators are needed; (2) news items are dynamic and consequently time oriented retrieval is needed; and (3) a news item may evolve through time, or overlap with other news items and hence identifying relationships between items is needed. In this paper, we aim to solve these issues by providing a dedicated RSS algebra based on semantic-aware operators which are capable of considering RSS characteristics. The provided operators are application domain specific and can be tuned according to the user preferences. We also provide a set of query rewriting and equivalence rules that would be used during query simplification and optimization. In addition and in order to validate our proposal, we develop a prototype called EasyRSSManager that allows a user to formulate RSS query using our operators.

Storing and querying fuzzy XML data in relational databases

Information imprecision and uncertainty exist in many real-world applications and for this reason fuzzy data management has been extensively investigated in various database management systems. Currently, introducing native support for XML data in relational database management systems (RDBMs) has attracted considerable interest with a view to leveraging the powerful and reliable data management services provided by RDBMs. Although there is a rich literature on XML-to-relational storage, none of the existing solutions satisfactorily addresses the problem of storing fuzzy XML data in RDBMs. In this paper, we study the methodology of storing and querying fuzzy XML data in relational databases. In particular, we present an edge-based approach to shred fuzzy XML data into relational data. The unique feature of our approach is that no schema information is required for our data storage. On this basis, we present a generic approach to translate path expression queries into SQL for processing XML queries.

XML keyword search with promising result type recommendations

Keyword search enables inexperienced users to easily search XML database with no specific knowledge of complex structured query languages and XML data schemas. Existing work has addressed the problem of selecting data nodes that match keywords and connecting them in a meaningful way, e.g., SLCA and ELCA. However, it is time-consuming and unnecessary to serve all the connected subtrees to the users because in general the users are only interested in part of the relevant results. In this paper, we propose a new keyword search approach which basically utilizes the statistics of underlying XML data to decide the promising result types and then quickly retrieves the corresponding results with the help of selected promising result types. To guarantee the quality of the selected promising result types, we measure the correlations between result types and a keyword query by analyzing the distribution of relevant keywords and their structures within the XML data to be searched. In addition, relevant result types can be efficiently computed without keyword query evaluation and any schema information. To directly return top-k keyword search results that conform to the suggested promising result types, we design two new algorithms to adapt to the structural sensitivity of the keyword nodes over the keyword search results. Lastly, we implement all proposed approaches and present the relevant experimental results to show the effectiveness of our approach.

Optimize Twig Query Pattern Based on XML Schema

Aiming at the core operation for XML data queries—Tree Pattern Queries, we propose an effective method for minimizing XML query based on XML Schema. The method can make use of the structure constraints information provided by XML Schema to optimize the tree query pattern containing the logic nodes AND and OR. Such tree pattern preferably satisfies requirements of XQuery queries describing and optimizing to support the high-performance implementation of XQuery.

XML Data Storage and Query Optimization in Relational Database by XPath Processing Model

XML is de facto new standard for data representation and exchanging on the web. Along with the growth of XML data, traditional relational databases support XML data processing across-the-board. Consistent storage and efficient query for XML data is the chief problem in XML supported relational databases. This work presents mechanisms of Storage and query optimization for XML data in relational database. XML data are treated as a kind of data type in relational database, and XML tables are used to store native XML data in fixed schema. Structural summary index is built and maintained in relational database and an optimizing mechanism based on XPath model named Compressed XML Query Tree will also be presented in order to improve efficiency of XML data query by reducing superabundant join operations from ancestor- descendent axis. All strategies are appropriate for classical XML query algorithms. Algorithms for XML query will be performed in experiments on real XML datasets in relational database and query workloads to report the performance of our mechanism and show the efficiency compared with other mechanisms.

Automatic Parallelization of XQuery Programs

XQuery is a functional language with implicit parallelism. It is an important approach to improve the efficiency of XML query by taking full advantage of multi-core environment in the parallel implementation of XQuery language. In this paper, we propose an implementation method for parallelizing XML query represented by XQuery programs automatically. According to the features of its functional language, an XQuery program is divided into a number of tasks that can be executed in parallel. Then, on the basis of the running cost evaluation, three kinds of parallelism are applied to different tasks and they are data parallelism, task parallelism and pipeline parallelism. Under the guidance of a novel scheduling strategy, the execution of the XQuery program is parallelized automatically. The experiments show that this approach improves the efficiency of the execution of XQuery programs and the computing resources of multi-core computer are used efficiently.

Structural Join in the ‘XSQS’ Native XML Database

Query processing has attracted significant attention since XML database is proposed. This paper focuses on structural join mainly in our native XML storage and query system (XSQS). A hybrid structural join strategy based on tree-merge algorithm and stack-tree algorithm is proposed. Moreover, a path index scheme is designed to accelerate the query processing. Experimental results show that the proposed hybrid strategy and the index have a good performance in query processing of XSQS.

Processing and Evaluating Partial Tree Pattern Queries on XML Data

XML query languages typically allow the specification of structural patterns using XPath. Usually, these structural patterns are in the form of trees (Tree-Pattern Queries-TPQs). Finding the occurrences of such patterns in an XML tree is a key operation in XML query evaluation. The multiple previous algorithms presented for this operation focus mainly on the evaluation of tree-pattern queries. Recently, requirements for flexible querying of XML data have motivated the consideration of query classes that are more expressive and flexible than TPQs for which efficient nonmain-memory evaluation algorithms are not known. In this paper, we consider a class of queries, called Partial Tree-Pattern Queries (PTPQs), which generalize and strictly contain TPQs. PTPQs represent a broad fragment of XPath which is very useful in practice. In order to process PTPQs, we introduce a set of sound and complete inference rules to characterize structural relationship derivation. We provide necessary and sufficient conditions for detecting query unsatisfiability and node redundancy. We also show that PTPQs can be represented as directed acyclic graphs augmented with the “same-path” constraints. In order to leverage existing efficient evaluation algorithms for less expressive classes of queries, we design two approaches that evaluate a PTPQ by decomposing it into a set of simpler queries: algorithm IndexTPQGen, exploits a structural summary of the XML data and evaluates a PTPQ by generating an equivalent set of TPQs and unioning their answers. Algorithm PartialPathJoin decomposes the PTPQ into partial-path queries, and merge-joins their solutions. We also develop PartialTreeStack, an original polynomial time holistic algorithm for PTPQs. To the best of our knowledge, this is the first algorithm to support the evaluation of such a broad structural fragment of XPath in the inverted lists evaluation model. We provide a theoretical analysis of our algorithm and identify cases where it is asymptotically optimal. An extensive experimental evaluation shows that it is more efficient, robust, and stable than the other two and it outperforms a state-of-the art XQuery engine on PTPQs.

Holistic Boolean-Twig Pattern Matching for Efficient XML Query Processing

Twig pattern matching is a critical operation for XML query processing, and the holistic computing approach has shown superior performance over other methods. Since Bruno et al. introduced the first holistic twig join algorithm, TwigStack, numerous so-called holistic twig join algorithms have been proposed. Yet practical XML queries often require support for more general twig patterns, such as the ones that allow arbitrary occurrences of an arbitrary number of logical connectives (AND, OR, and NOT); such types of twigs are referred to as B-twigs (i.e., Boolean-Twigs) or AND/OR/NOT-twigs. We have seen interesting work on generalizing the holistic twig join approach to AND/OR-twigs and AND/NOT-twigs, but have not seen any further effort addressing the problem of AND/OR/NOT-Twigs at the full scale, which therefore forms the main theme of this paper. In this paper, we investigate novel mechanisms for efficient B-twig pattern matching. In particular, we introduce “B-twig normalization” as an important first-step in our approach toward eventually conquering the complexity of B-twigs, and then present BTwigMerge-the first holistic twig join algorithm designed for B-twigs. Both analytical and experimental results show that BTwigMerge is optimal for B-twig patterns with AD (Ancestor-Descendant) edges and/or PC (Parent-Child) edges.

Efficient evaluation of reachability query for directed acyclic XML graph based on a prime number labelling schema

Many schema labelling approaches have been designed to facilitate querying of XML documents. The proposed algorithms are based on the fact that ancestor–descendant relationships among nodes can be quickly determined. Schema labelling is a family of technologies widely used in indexing tree, graph, or structured XML graph, in which a unique identifier is assigned to each node in the tree/graph. The generated identifier is then used in indexing as a reference to the actual node so that structural relationship among the nodes can be quickly captured. In this paper, we extend the prime number schema labelling algorithm for labelling DAG XML graph. Our main contribution is scaling down the original XML graph size substantially based on the Strongly Connected Component (SCC) principles. Labelling each node in DAG with an integer that is the arithmetical multiplication of the prime number associating with the node and its parent label. The schema does not depend on spanning tree. Thus, subsumption hierarchies represented in a DAG can be efficiently explored by checking the divisibility among the labels. Also, it inherits dynamic update ability and compact size features from its predecessors. Our theoretical analysis and the experimental results showed that the generated labelled schema is an efficient and a scalable one for processing reachability queries on large XML graphs.

조상-자손 관계 탐색을 지원하기 위한 XML 타입상속 색인구조의 계층적 구성기법

본 논문에서는 XML 데이터베이스에서 XML 질의처리를 효율적으로 지원하기 위한 다차원 타입상속 색인구조(MD-TIX)들의 계층적 구성기법을 제시한다. MD-TIX는 중첩요소와 여러 타입상속 계층으로 이루어진 중첩술어의 조상-자손 관계 탐색을 효율적으로 지원하기 위하여 다차원 색인구조를 이용하는 색인기법이다. 그러나 이러한 MD-TIX는 질의에 주어진 Xpath의 길이가 긴 경우에 색인 엔트리의 구성문제 때문에 색인구조의 구축과 유지관리에 어려움이 있다. 이를 극복하기 위해서, 본 논문에서는 먼저 주어진 Xpath에서 인접한 두 타입 사이의 직접 관계 탐색을 지원하는 기본 색인구조들을 구축하고, 이들을 바탕으로 Xpath상의 임의의 두 타입 사이의 간접 관계 탐색을 지원하는 유도 색인구조들을 구축한다. 이러한 과정을 전체 길이의 Xpath를 지원하는 하나의 목표 색인구조를 구축하기까지 계층적으로 구성하는 방법을 제시한다. 또한 Xpath 상에 주어진 몇 개의 부경로 탐색만을 지원하기 위한 부분적인 색인계층을 효율적으로 구축하기 위한 알고리즘을 제안한다. This paper presents a hierarchical structuring method for the multidimensional type inheritance indices (MD-TIXs) that support the processing of XML queries in XML databases. MD-TIX uses a multidimensional index structure for efficiently supporting ancestor-descendant explorations that involve both nested element and type inheritance hierarchies. However, In the case of a long Xpath, the building and maintenance of MD-TIX are very difficult because of index entry construction problem. So, we propose a type inheritance index hierarchy method for solving this difficulty. We first construct base indices that support direct relationship explorations between adjacent two types on a given Xpath, and then, based on these base indices, we construct hierarchically the derived indices that support indirect relationship explorations between any two types of Xpath until constructing one target index for supporting the full Xpath. And we also present an algorithm that efficiently constructs a partial index hierarchy for supporting given a set of sub-pathes explorations.

FoXtrot

Publish/subscribe systems have emerged in recent years as a promising paradigm for offering various popular notification services. In this context, many XML filtering systems have been proposed to efficiently identify XML data that matches user interests expressed as queries in an XML query language like XPath. However, in order to offer XML filtering functionality on an Internet-scale, we need to deploy such a service in a distributed environment, avoiding bottlenecks that can deteriorate performance. In this work, we design and implement FoXtrot, a system for filtering XML data that combines the strengths of automata for efficient filtering and distributed hash tables for building a fully distributed system. Apart from structural-matching, performed using automata, we also discuss different methods for evaluating value-based predicates. We perform an extensive experimental evaluation of our system, FoXtrot, on a local cluster and on the PlanetLab network and demonstrate that it can index millions of user queries, achieving a high indexing and filtering throughput. At the same time, FoXtrot exhibits very good load-balancing properties and improves its performance as we increase the size of the network.

Structural Join Algorithm of XML Query Based on Exhaustive Dynamic Programming

Using the advantages of exhaustive dynamic programming algorithm, on the basic ideas of the global optimal solution is derived based on local optimal solution, this paper propose a new structural selection join algorithm. The algorithm connects to the sub-tree, and then connects to the structure of the whole. Though not guaranteed optimal solution, this algorithm can improve much in the time complexity, reduce the search space and improve efficiency.

Mapping between RDF and XML with XSPARQL

One promise of Semantic Web applications is to seamlessly deal with heterogeneous data. The Extensible Markup Language (XML) has become widely adopted as an almost ubiquitous interchange format for data, along with transformation languages like XSLT and XQuery to translate data from one XML format into another. However, the more recent Resource Description Framework (RDF) has become another popular standard for data representation and exchange, supported by its own query language SPARQL, that enables extraction and transformation of RDF data. Being able to work with XML and RDF using a common framework eliminates several unnecessary steps that are currently required when handling both formats side by side. In this paper we present the XSPARQL language that, by combining XQuery and SPARQL, allows to query XML and RDF data using the same framework and transform data from one format into the other. We focus on the semantics of this combined language and present an implementation, including discussion of query optimisations along with benchmark evaluation.

Histograms as statistical estimators for aggregate queries

The traditional statistical assumption for interpreting histograms and justifying approximate query processing methods based on them is that all elements in a bucket have the same frequency—this is called uniform distribution assumption. In this paper, we analyze histograms from a statistical point of view. We show that a significantly less restrictive statistical assumption – the elements within a bucket are randomly arranged even though they might have different frequencies – leads to identical formulas for approximating aggregate queries using histograms. Under this assumption, we analyze the behavior of both unidimensional and multidimensional histograms and provide tight error guarantees for the quality of approximations. We conclude that histograms are the best estimators if the assumption holds; sampling and sketching are significantly worse. As an example of how the statistical theory of histograms can be extended, we show how XSketches – an approximation technique for XML queries that uses histograms as building blocks – can be statistically analyzed. The combination of the random shuffling assumption and the other statistical assumptions associated with XSketch estimators ensures a complete statistical model and error analysis for XSketches.

Efficient Top-<I>K</I> Keyword Search on XML Streams

利用关键字可以在模式未知的情况下对XML 数据进行查询.在当前的XML数据流上的关键字查询处理中,打分函数往往不能都满足各种用户不同的需求.提出了一种基于skyline 的XML 数据流上的Top-K 关键字查询.对于这种查询,不需要考虑影响结果与查询相关性的复杂因素,只需利用skyline 挑选与查询最相关的结果.提出了两种XML 数据流上的有效的基于skyline 的Top-K 关键查询处理算法,包括对单查询和多查询的处理算法.通过扩展实验对两种算法的有效性和可扩展性进行了验证.经过实验验证,所提出的查询处理算法的效率几乎不受关键字个数、查询结果数量、查询数量等参数的影响,运行时间和文档大小大致呈线性关系.;Keywords are suitable for query XML streams without schema information. In current forms of keywords search on XML streams and rank functions do not always represent users' intensions. This paper addresses this problem in another aspect. In this paper, the skyline Top-K keyword queries, a novel kind of keyword queries on XML streams, are presented. For such queries, skyline is used to choose results on XML streams without considering the complicated factors influencing the relevance to queries. With skyline query processing techniques, two techniques, are presented to process skyline Top-K keyword single queries and multi-queries on XML streams efficiently. Extensive experiments are performed to verify the effectiveness and efficiency of these techniques presented in this paper. According to the experimental results, the algorithms are not sensitive to the parameters such as the number of keywords, the number of results, the number of queries, and the runtime is approximately linear to the size of document.

Efficient top- k algorithm for eXtensible Markup Language keyword search

The ability to compute top- k matches to eXtensible Markup Language (XML) queries is gaining importance owing to the increasing of large XML repositories. Current work on top- k match to XML queries mainly focuses on employing XPath, XQuery or NEXI as the query language, whereas little work has concerned on top- k match to XML keyword search. In this study, the authors propose a novel two-layer-based index construction and associated algorithm for efficiently computing top- k results for XML keyword search. Our core contribution, the two-layer-based inverted Index and associated algorithm for XML keyword search take both score-sorted-sequence and Dewey ID-sorted-sequence into consideration, and thus gain performance benefits during querying process. The authors have conducted expensive experiments and our experimental results show efficiency advantages compared with existing approaches.

On the improvement of active XML (AXML) representation and query evaluation

Active XML (AXML) as intensional data aims to exploit potential computing powers of XML, Web services and P2P architecture. It is considered a powerful extension of XML to deal with dynamic XML data from autonomous and heterogeneous data sources on a very large scale via Web services. However, AXML is still at an immature stage and various issues need to be investigated before it can be accepted widely. This paper will focus on two issues facing the current AXML system, namely the representation and the query process. We propose superior representation and improved query evaluation for AXML. For justification purposes, we compare our proposed algorithms with the existing algorithms.

The Research of Database Query Optimization Based on XML

During processing database query or dealing with huge amounts of data, the conventional query method is not only a waste of resources but also may perform repeated or useless operations which may cause the database overburdened even. For solving the problem of time-consuming in conventional database query, this paper presented a more convenient solution to the problem in conventional database queries. This paper constructed an XML document to simulate the database and transformed the database query into the XML queries. Experiments showed that speed can be significantly improved for database query and better results can be obtained.

Answering queries using views over probabilistic XML

We study the complexity of query answering using views in a probabilistic XML setting, identifying large classes of XPath queries -- with child and descendant navigation and predicates -- for which there are efficient (PTime) algorithms. We consider this problem under the two possible semantics for XML query results: with persistent node identifiers and in their absence. Accordingly, we consider rewritings that can exploit a single view, by means of compensation, and rewritings that can use multiple views, by means of intersection. Since in a probabilistic setting queries return answers with probabilities, the problem of rewriting goes beyond the classic one of retrieving XML answers from views. For both semantics of XML queries, we show that, even when XML answers can be retrieved from views, their probabilities may not be computable. For rewritings that use only compensation, we describe a PTime decision procedure, based on easily verifiable criteria that distinguish between the feasible cases -- when probabilistic XML results are computable -- and the unfeasible ones. For rewritings that can use multiple views, with compensation and intersection, we identify the most permissive conditions that make probabilistic rewriting feasible, and we describe an algorithm that is sound in general, and becomes complete under fairly permissive restrictions, running in PTime modulo worst-case exponential time equivalence tests. This is the best we can hope for since intersection makes query equivalence intractable already over deterministic data. Our algorithm runs in PTime whenever deterministic rewritings can be found in PTime.