The XFM view adaptation mechanism: An essential component for XML data warehouses

In the past few years, with many organisations providing web services for business and communication purposes, large volumes of XML transactions take place on a daily basis. In many cases, organisations maintain these transactions in their native XML format due to its flexibility for xchanging data between heterogeneous systems. This XML data provides an important resource for decision support systems. As a consequence, XML technology has slowly been included within decision support systems of data warehouse systems. The problem encountered is that existing native XML database systems suffer from poor performance in terms of managing data volume and response time for complex analytical queries. Although materialised XML views can be used to improve the performance for XML data warehouses, update problems then become the bottleneck of using materialised views. Specifically, synchronising materialised views in the face of changing view definitions, remains a significant issue. In this dissertation, we provide a method for XML-based data warehouses to manage updates caused by the change of view definitions (view redefinitions), which is referred to as the view adaptation problem. In our approach, views are defined using XPath and then modelled using a set of novel algebraic operators and fragments. XPath views are integrated into a single view graph called the XML Fragment Materialisation (XFM) View Graph, where common parts between different views are shared and appear only once in the graph. Fragments within the view graph can be selected for materialisation to facilitate the view adaptation process. While changes are applied, our view adaptation algorithms can quickly determine what part of the XFM view graph is affected. The adaptation algorithms then perform a structural adaptation to update the view graph, followed by data adaptation to update materialised fragments

A survey on tree matching and XML retrieval

International audienceWith the increasing number of available XML documents, numerous approaches for retrieval have been proposed in the literature. They usually use the tree representation of documents and queries to process them, whether in an implicit or explicit way. Although retrieving XML documents can be considered as a tree matching problem between the query tree and the document trees, only a few approaches take advantage of the algorithms and methods proposed by the graph theory. In this paper, we aim at studying the theoretical approaches proposed in the literature for tree matching and at seeing how these approaches have been adapted to XML querying and retrieval, from both an exact and an approximate matching perspective. This study will allow us to highlight theoretical aspects of graph theory that have not been yet explored in XML retrieval

The relational XQuery puzzle: a look-back on the pieces found so far

Given the tremendous versatility of relational database implementations toward awide range of database problems, it seems only natural to consider them as back-ends for XML data processing. Yet, the assumptions behind the language XQuery are considerably different to those in traditional RDBMSs. The underlying data model is a tree, data and results carry an intrinsic order, queries are described using explicit iteration and, after all, problems are everything else but regular. Solving the relational XQuery puzzle, therefore, has challenged anumber of research groups over the past years. The purpose of this article is to summarize and assess some of the results that have been obtained during this period to solve the puzzle. Our main focus is on the Pathfinder XQuery compiler, afull reference implementation of apurely relational XQuery processor. As we dissect its components, we relate them to other work in the field and also point to open problems and limitations in the context of relational XQuery processin

A node partitioning strategy for optimising the performance of XML queries

For ease of communication between heterogeneous systems, the eXtensible Markup Language (XML) has been widely adopted as a data storage format. However, XML query processing presents issues both in terms of query performance and updatability. Thus, many are choosing to shred XML data into relational databases in order to benet from its mature technology. The problem with this approach is that (often complex and time consuming) data transformation processes are required to transform XML data to relational tables and vice versa. Additionally, many of the benets of XML data can be lost during these processes. In this dissertation, we present a process that partitions nodes within an XML document into disjoint subsets. Briefly, as there are fewer partitions than there are nodes, a more efficient join operation can be performed between partitions, thus reducing the number of inefficient node comparisons. The number and size of partitions varies depending on the structure and layout in the XML document, and the number of partitions impacts query performance. Therefore, we also provide a partition classication process, which signicantly reduces the number of partitions because each partition class represents many equivalent partitions within the XML document. In this dissertation, we will demonstrate that our approach outperforms similar approaches for a large subset of XML queries by eliminating complex join operations (where possible) during the query process

SIQXC: Schema Independent Queryable XML Compression for Smartphones

The explosive growth of XML use over the last decade has led to a lot of research on how to best store and access it. This growth has resulted in XML being described as a de facto standard for storage and exchange of data over the web. However, XML has high redundancy because of its self-­‐ describing nature making it verbose. The verbose nature of XML poses a storage problem. This has led to much research devoted to XML compression. It has become of more interest since the use of resource constrained devices is also on the rise. These devices are limited in storage space, processing power and also have finite energy. Therefore, these devices cannot cope with storing and processing large XML documents. XML queryable compression methods could be a solution but none of them has a query processor that runs on such devices. Currently, wireless connections are used to alleviate the problem but they have adverse effects on the battery life. They are therefore not a sustainable solution. This thesis describes an attempt to address this problem by proposing a queryable compressor (SIQXC) with a query processor that runs in a resource constrained environment thereby lowering wireless connection dependency yet alleviating the storage problem. It applies a novel simple 2 tuple integer encoding system, clustering and gzip. SIQXC achieves an average compression ratio of 70% which is higher than most queryable XML compressors and also supports a wide range of XPATH operators making it competitive approach. It was tested through a practical implementation evaluated against the real data that is usually used for XML benchmarking. The evaluation covered the compression ratio, compression time and query evaluation accuracy and response time. SIQXC allows users to some extent locally store and manipulate the otherwise verbose XML on their Smartphones

Order based labeling scheme for dynamic XML (extensible markup language) query processing

Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2012Includes bibliographical references (leaves: 43-46)Text in English; Abstract: Turkish and Englishix, 55 leavesNeed for robust and high performance XML database systems increased due to growing XML data produced by today’s applications. Like indexes in relational databases, XML labeling is the key to XML querying. Assigning unique labels to nodes of a dynamic XML tree in which the labels encode all structural relationships between the nodes is a challenging problem. Early labeling schemes designed for static XML document generate short labels; however, their performance degrades in update intensive environments due to the need for relabeling. On the other hand, dynamic labeling schemes achieve dynamicity at the cost of large label size or complexity which results in poor query performance. This thesis presents OrderBased labeling scheme which is dynamic, simple and compact yet able to identify structural relationships among nodes. A set of performance tests show promising labeling, querying, update performance and optimum label size

Pentagonal scheme for dynamic XML prefix labelling

In XML databases, the indexing process is based on a labelling or numbering scheme and generally used to label an XML document to perform an XML query using the path node information. Moreover, a labelling scheme helps to capture the structural relationships during the processing of queries without the need to access the physical document. Two of the main problems for labelling XML schemes are duplicated labels and the cost efficiency of labelling time and size. This research presents a novel dynamic XML labelling scheme, called the Pentagonal labelling scheme, in which data are represented as ordered XML nodes with relationships between them. The update of these nodes from large scale XML documents has been widely investigated and represents a challenging research problem as it means relabelling a whole tree. Our algorithms provide an efficient dynamic XML labelling scheme that supports data updates without duplicating labels or relabelling old nodes. Our work evaluates the labelling process in terms of size and time, and evaluates the labelling scheme’s ability to handle several insertions in XML documents. The findings indicate that the Pentagonal scheme shows a better initial labelling time performance than the compared schemes, particularly when using large XML datasets. Moreover, it efficiently supports random skewed updates, has fast calculations and uncomplicated implementations so efficiently handles updates. Also, it proved its capability in terms of the query performance and in determining the relationships.Libyan governmen

Child Prime Label Approaches to Evaluate XML Structured Queries

The adoption of the eXtensible Markup Language (XML) as the standard format to store and exchange semi-structure data has been gaining momentum. The growing number of XML documents leads to the need for appropriate XML querying algorithms which are able to retrieve XML data efficiently. Due to the importance of twig pattern matching in XML retrieval systems, finding all matching occurrences of a tree pattern query in an XML document is often considered as a specific task for XML databases as well as a core operation in XML query processing. This thesis presents a design and implementation of a new indexing technique, called the Child Prime Label (CPL) which exploits the property of prime numbers to identify Parent-Child (P-C) edges in twig pattern queries (TPQs) during query evaluation. The CPL approach can be incorporated efficiently within the existing labelling schemes. The major contributions of this thesis can be seen as a set of novel twig matching algorithms which apply the CPL approach and focus on reducing the overhead of storing useless elements and performing unnecessary computations during the output enumeration. The research presented here is the first to provide an efficient and general solution for TPQs containing ordering constraints and positional predicates specified by the XML query languages. To evaluate the CPL approaches, the holistic model was implemented as an experimental prototype in which the approaches proposed are compared against state-of-the-art holistic twig algorithms. Extensive performance studies on various real-world and artificial datasets were conducted to demonstrate the significant improvement of the CPL approaches over the previous indexing and querying methods. The experimental results demonstrate the validity and improvements of the new algorithms over other related methods on common various subclasses of TPQs. Moreover, the scalability tests reveal that the new algorithms are more suitable for processing large XML datasets