Querying XML Data Research Articles

Systematic Partitioning and Labeling XML Subtrees for Efficient Processing of XML Queries in IoT Environments

With the advent of IoT, storing, indexing and querying XML data efficiently is critical. To minimize the cost of querying XML data, researchers have proposed many indexing techniques. Nearly all the techniques, partition the XML data into a number of data-streams. To evaluate a query, existing twig pattern matching algorithms process a subset of the data-streams simultaneously. Processing many data-streams simultaneously results in some or all of the following four problems, namely, the accessing of many data nodes which don’t appear in the final solution of a given query, the generation of duplicate results, the generation of huge number of intermediate results, and the cost of merging the generated intermediate results. To the best of our knowledge, all the existing twig pattern matching algorithms suffer from some or all of the above mentioned problems. This paper proposes a new twig pattern matching algorithm called MatchQTP which processes one data-stream at a time and avoids all the above mentioned four problems. It also proposes a new indexing technique called RLP-Index and a new XML node labeling scheme called RLP-Scheme, both of which are used by MatchQTP. Unlike the existing indexing techniques, RLP-Index stores a subset of the data nodes. The rest of the data nodes can be generated efficiently. This minimizes storage space utilization and query processing time and makes RLP-Index the first of its kind. Many experiments were conducted to study the performance of MatchQTP. The results show that MatchQTP is very efficient and highly scalable. It was also compared with four algorithms, three of which are used frequently in the literature to compare the performance of new algorithms and the fourth algorithm is the state-of-the-art algorithm. MatchQTP significantly and consistently outperformed all of them

A Narrative Review of Storing and Querying XML Documents Using Relational Database

Extensible Markup Language (XML) has become a common language for data interchange and data representation in the Web. The evolution of the big data environment and the large volume of data which is being represented by XML on the Web increase the challenges in effectively managing such data in terms of storing and querying. Numerous solutions have been introduced to store and query XML data, including the file systems, Object-Oriented Database (OODB), Native XML Database (NXD), and Relational Database (RDB). Previous research attempts indicate that RDB is the most powerful technology for managing XML data to date. Because of the structure variations of XML and RDB, the need to map XML data to an RDB scheme is increased. This growth has prompted numerous researchers and database vendors to propose different approaches to map XML documents to an RDB, translating different types of XPath queries to SQL queries and returning the results to an XML format. This paper aims to comprehensively review most cited and latest mapping approaches and database vendors that use RDB solution to store and query XML documents, in a narrative manner. The advantages and the drawbacks of each approach is discussed, particularly in terms of storing and querying. The paper also provides some insight into managing XML documents using RDB solution in terms of storing and querying and contributes to the XML community.

Extensible markup language keywords search based on security access control

With increasing rate of storing and sharing information in the cloud by the users, data storage brings new challenges to the Extensible Markup Language (XML) database in big data environments. The efficient retrieval of data with protection and privacy issues for accessing mass data in the cloud is more and more important. Most of existing research about XML data query and retrieval focuses on efficiency or establishing the index, and so on. However, these methods or algorithms do not take into account the data and data structure for their own safety issues. Furthermore, traditional access control rules read XML document node in a dynamic environment, relevant dynamic query-based keyword research data security and privacy protection requirements are not many. In order to improve the search efficiency with security condition, this paper examines how to generate the sub-tree of matching keywords that the user can access by the access control rules for the user's role. The corresponding algorithm is proposed to achieve safe and efficient keywords search.

Structural XML Query Processing

Since the boom in new proposals on techniques for efficient querying of XML data is now over and the research world has shifted its attention toward new types of data formats, we believe that it is crucial to review what has been done in the area to help users choose an appropriate strategy and scientists exploit the contributions in new areas of data processing. The aim of this work is to provide a comprehensive study of the state-of-the-art of approaches for the structural querying of XML data. In particular, we start with a description of labeling schemas to capture the structure of the data and the respective storage strategies. Then we deal with the key part of every XML query processing: a twig query join, XML query algebras, optimizations of query plans, and selectivity estimation of XML queries. To the best of our knowledge, this is the first work that provides such a detailed description of XML query processing techniques that are related to structural aspects and that contains information about their theoretical and practical features as well as about their mutual compatibility and general usability.

Hybridation of Labeling Schemes for Efficient Dynamic Updates

<p>With XML as the leading standard for data representation over the Web, it is crucial to store and query XML data. However, relational databases are the dominant database technology in most organizations. Thus, replacing relational database with a pure XML database is not a wise choice. One most prominent solution is to map XML into relational database. This paper introduces a robust labeling scheme which is a hybrid labeling scheme combining the beauty features of extended range and ORDPATH schemes to supports dynamic updates. In addition, we also proposed a mapping scheme based on the hybrid labeling scheme. Our proposed approach is evaluated in terms of (i) loading time, (ii) storage size, (iii) query retrieval time, and (iv) dynamic updates time, as compared to ORDPATH and ME schemes. The experimental evaluation results shows that our proposed approach is scalable to support huge datasets and dynamic updates.</p>

Fraction and Prefix Encoding Scheme of Supporting Updating Data Efficiently

At present, more and more data are expressed in the form of XML format, and how to manage these data effi- ciently becomes an important issue. In order to update and query XML data efficiently, we proposed a new encoding scheme called MPES (modify prefix encoding scheme). MPES makes full good use of the advantages of fraction encod- ing and prefix encoding and it supports updating data efficiently. Furthermore, MPES also supports the representation of sibling relationship, parent-children relationship and ancestor-descendant relationship between any two nodes. The exper- imental results show that, compared with fraction encoding scheme, MPES improves the updating efficiency of XML da- ta. As compared with prefix encoding scheme, MPES improved the querying efficiency of XML data.

Storing and Updating XML Data Tree based on Linked Lists

XML has become the de facto standard for data exchange and transformation on the World Wide Web and is widely used in many applications of various fields, so it is urgent to develop some efficient methods to manage, store, query, and update XML data. There are two main methods to do this: the first method is a native approach which uses native XML databases to store XML data, and the second method use other mature commercial databases approaches to store and manage XML data considering the advantages of mature technologies of the commercial databases, especially use relational databases to store, query, and update XML data. For relational databases approach, although it can take advantage of mature technologies of relational databases, it needs to map XML data to relational data. In this paper, we research the problem of how to store XML data so that storing and updating of original XML data can be efficient than relational approach. We proposed a method to store XML data into linked lists with inverted index, in which the relationships between nodes of XML data tree are preserved by the links in linked lists. Inverted index are created for linked lists for efficiently querying and updating XML data tree. Two kinds of updates are considered including inserting a new node in or deleted an existed old node from XML data tree. Theoretical analysis of our algorithms shows that the methods proposed in the paper are efficient.

Comparative Study of Clustering Algorithms using Overall SimSUX Similarity Function for XML Documents

A huge amount of information is represented in XML format. Several tools have been developed to store, and query XML data. It becomes inevitable to develop high performance techniques for efficiently analysing extremely large collections of XML data. One of the methods that many researchers have focused on is clustering, which groups similar XML data, according to their content and structures. In previous work, there has been proposed the similarity function OverallSimSUX, that facilitates to capture the degree of similitude among the documents with a novel methodology for clustering XML documents using both structural and content features. Although this methodology shows good performance, endorsed by experiments with several corpus and statistical tests, on having had impliedly only one clustering algorithm, K-Star, we do not know the effect that it would suffer if we replaced this algorithm by other with dissimilar characteristics. Therefore to endorse completely the methodology, in this work we make a comparative study of the effects of applying the methodology for the OverallSimSUX similarity function calculation, using clustering algorithms of different classifications . Based on our analysis, we arrived to two important results: (1) The Fuzzy-SKWIC clustering algorithm works best both with methodology and without methodology, although there are not present significant differences respect to the K-Star clustering algorithm; (2) For each analysed algorithm when using the methodology, we obtain better results than when it is not taken into account.

A Formal Description of XML Tree Pattern Query for XQuery Language

In order to express tree pattern query in query plan and take advantage of formal method to analyze its behavioral characteristics, this paper present a formal description of tree pattern query based on functional language and denotational semantics. This description major focuses on behavior of a tree pattern query on matching against an eXtensible Markup Language (XML) document tree. First, we introduce a formal definition for a kind of extended generalized tree pattern (GTP++). Then we present a functional tree pattern description language (XTPL) for GTP++ and give its complete denotational semantics based on a novel data structure, named WTree, which efficiently organizes this typical XML data query results and provides flexible data access method. In the end, we present the formal semantics of identifying tree pattern from path expressions. By using formal methods, the semantics of tree pattern query is consistent and analyzable. As the core operation of XML query, this formal description can provide an initial step for analyzing the correctness of XML queries, and improves the reliability and robustness of query processing methods.

Recursive Twig Pattern Query

XQuery is a language for querying XML data which is widely used on the Internet. In XQuery, user can define recursive functions for querying and processing XML data. XML twig pattern query is considered as core operation for querying XML data which has been studied intensively in recent years. More powerful recursive queries can be achieved via combining user-defined recursive function and twig pattern query. This paper proposes recursive twig pattern query (RTPQ) to extend traditional twig pattern query with recursion and an effective holistic twig matching algorithm for RTPQ. With the help of RTPQ, recursive function call can access its result instead of evaluating local twig pattern queries in each calling. Results of experiments show that this approach can improve query efficiency and eliminate redundant intermediate results.

The Research of XML Keyword Retrieval Algorithms Based on MapReduce

In this paper, from the perspective of XML data management, first in the HDFS store large amount of data and XML data based on XML data query rewrite the traditional framework of MapReduce process, the design of large amount of data XML data set keywords retrieval algorithm, contain XML data classification and coding, index and search a four parts, solve the large amount of data of the XML document keywords retrieval problem. Then the design and implementation based on MapReduce of large amount of data XML keyword query system.

MLTwig: A Multi-Layer Tree Pattern Matching Approach for XQuery

Twig query, also known as tree pattern query (TPQ), is considered as the core operation of XML data queries. However, a complex XML query described by XQuery often cannot be represented by a single basic TPQ. Aiming at XQuery language, this paper presents a multi-layer tree pattern representation method, named MTP, and a matching algorithm MLTwig, which can effectively use intermediate results of outer query to match inner tree pattern in MTP based on a novel data structure, WTree, thereby saving time and space. Experimental results show that this algorithm can improve the processing efficiency for XQuery expression which can be represented by MTP.

A XML Document Coding Schema Based on Binary

In order to resolve the inefficiency for XML data query and support dynamic updates, etc, this paper has proposed an improved method to encode XML document nodes. On the basic of region encoding and the prefix encoding, it introduces a XML document coding schema base on binary (CSBB). The CSBB code use binary encoding strategy and make the bit string inserted in order. The bit string inserted algorithm can generate ordered bit string to reserve space for the inserted new nodes, and not influence on the others. Experiments shows the CSBB code can effectively avoid re-encoding of nodes, and supports the nodes Dynamic Update.

Dynamically querying possibilistic XML data

Traditional databases mainly focus on the processing of deterministic data. However, information is often uncertain in practical applications. This paper aims to provide a basic framework for managing possibilistic XML (Extensible Markup Language) data queries in a dynamic environment. Existing efforts are mainly made on querying XML data towards the representation of crisp concepts based on the static labeling schemes. Once an updating operation is involved, these static labeling scheme approaches often need to search the whole original XML document again to relabel all the labels of the nodes. This re-labeling obviously sacrifices the processing performance. Different from the prior work, we adopt a novel dynamic encoding scheme which is tailored for both static and dynamic possibilistic XML documents to effectively avoid re-labeling after updates. On this basis, we propose an efficient algorithm to handle the problem of dynamic twig queries in possibilistic XML documents. Finally, we report our experimental results to show that our algorithm is superior to previous approaches.

XPath fragments on XML in columns

Purpose – This paper considers schemaless XML data stored in a column-oriented storage, particularly in C-store. Axes of the XPath language are studied and a design and analysis of algorithms for processing the XPath fragment XP{*, //, /} are described in detail. The paper aims to discuss these issues. Design/methodology/approach – A two-level model of C-store based on XML-enabled relational databases is supposed. The axes of XPath language in this environment have been studied by Cástková and Pokorný. The associated algorithms have been used for the implementation of the XPath fragment XP{*, //, /}. Findings – The main advantage of this approach is algorithms implementing axes evaluations that are mostly of logarithmic complexity in n, where n is the number of nodes of XML tree associated with an XML document. A low-level memory system enables the estimation of the number of two abstract operations providing an interface to an external memory. The algorithms developed are mostly of logarithmic complexity in n, where n is the number of nodes of XML tree associated with an XML document. Originality/value – The paper extends the approach of querying XML data stored in a column-oriented storage to the XPath fragment using only child and descendant axes and estimates the complexity of evaluating its queries.

Schema Based Storage of Xml Documents in Relational Databases

XML (Extensible Markup language) is emerging as a tool for representing an d exchanging data over the internet. When we want to store and query XML data, we can use two approaches either by using native databases or XML enabled databases. In this paper we deal with XML enabled databases. We use relational databases to store XML d ocuments. In this paper we focus on mapping of XML DTD into relations. Mapping needs three steps: 1) Simplify Complex DTD’s 2) Make DTD graph by using simplified DTD’s 3) Generate Relational schema. We present an inlining algorithm for generating relational schemas from available DTD’s. This algorithm also handles recursion in an XML document.

A visual programming language for XML manipulation

XML data flow has reached beyond the world of computer science and has spread to other areas such as data communication, e-commerce and instant messaging. Therefore, manipulating this data by non-expert programmers is becoming imperative and has emerged two alternatives. On one hand, Mashups have emerged a few years ago, providing users with visual tools for web data manipulation but not necessarily XML specific. Mashups have been leaning towards functional composition but no formal definitions have yet been defined. On the other hand, visual languages for XML have been emerging since the standardization of XML, and mostly relying on querying XML data for extraction or structure transformations. These languages are mainly based on existing textual XML languages, they have limited expressiveness and do not provide non-expert programmers with means to manipulate XML data. In this paper, we define a generic visual language called XCDL based on Colored Petri Nets allowing non-expert programmers to compose manipulation operations. The XML manipulations range from simple data selection/projection to data modification (insertion, removal, obfuscation, etc.). The language is oriented to deal with XML data (XML documents and fragments), providing users with means to compose XML oriented operations. The language core syntax is presented here along with an implemented prototype based on it.

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.