XML data sources are gaining popularity in the context of Business Intelligence and On-Line Analytical Processing (OLAP) applications, due to the amenities of XML in representing and managing complex and heterogeneous data. However, XML-native database systems currently suffer from limited performance, both in terms of volumes of manageable data and query response time. Therefore, recent research efforts are focusing on horizontal fragmentation techniques, which are able to overcome the above limitations. However, classical fragmentation algorithms are not suitable to control the number of originated fragments, which instead plays a critical role in data warehouses. In this paper, we propose the use of the K-means clustering algorithm for effectively and efficiently supporting the fragmentation of very large XML data warehouses. We complement our analytical contribution with a comprehensive experimental assessment where we compare the efficiency of our proposal against existing fragmentation algorithms.
XML is increasingly used not only for data exchange but also to represent arbitrary data sources as virtual XML repositories. In many application scenarios, fragments of such repositories are distributed over the Web. However, design and query processing models for distributed XML data have not yet been studied in detail. The goal of this paper is to study the design and management of distributed XML repositories. Following the well-established concepts of vertical and horizontal data fragmentation schemes for relational databases, we introduce a flexible distribution design approach for XML repositories. We provide a comprehensive data allocation model with a particular focus on storage efficient index structures. These index structures encode global path information about XML fragment data at local sites and provide for an efficient, local evaluation of the most common types of global path and tree pattern queries. Finally, we describe the basic principles of a distributed query processing model based on the concept of index shipping. We address the problem of querying XML data over a P2P network. In P2P networks, the allowed kinds of queries are usually exact-match queries over file names. We discuss the extensions needed to deal with XML data and XPath queries. A single peer can hold a whole document or a partial complete fragment of the latter. Each XML fragment document is identified by a distinct path expression, which is encoded in a distributed hash table. Our framework differs from content-based routing mechanisms, biased towards finding the most relevant peers holding the data. We perform fragments placement and enable fragments lookup by solely exploiting few path expressions stored on each peer. By taking advantage of quasi-zero replication of global catalogs, our system supports fast full and partial XPath querying. To this purpose, we have extended the Chord simulator and performed an experimental evaluation of our approach. Fragmentation techniques for XML data are gaining momentum within both distributed and centralized XML query engines and pose novel and unrecognized challenges to the community. Albeit not novel, and clearly inspired by the classical divide et impera principle, fragmentation for XML trees has been proved successful in boosting the querying performance, and in cutting down the memory requirements. However, fragmentation considered so far has been driven by semantics, i.e. built around query predicates. In this paper, we propose a novel fragmentation technique that founds on structural constraints of XML documents (size, tree-width, and tree-depth) and on special-purpose structure histograms able to meaningfully summarize XML documents. This allows us to predict bounding intervals of structural properties of output (XML) fragments for efficient query processing of distributed XML data. An experimental evaluation of our study confirms the effectiveness of our fragmentation methodology on some representative XML data sets. Data fragmentation offers various attractive alternatives to organizing and managing data, and presents interesting characteristics that may be exploited for efficient processing. XML, being inherently hierarchical and semi-structured, is an ideal candidate to reap the benefits offered by data fragmentation. However, fragmenting XML data and handling queries on fragmented XML are fraught with challenges: seamless XML fragmentation and processing models are required for deft handling of query execution on inter-connected and inter-related XML fragments, without the need of reconstructing the entire document in memory. Recent research has studied some of the challenges and has provided some insight on the data representation, and on the rather intuitive approaches for processing fragmented XML. In this paper, we provide a novel pipelined framework, called XFrag, for processing XQueries on XML fragments to achieve processing and memory efficiency. Moreover, we show that this model is suitable for low-bandwidth mobile environments by accounting for their intrinsic idiosyncrasies, without sacrificing accuracy and efficiency. We provide experimental results showing the memory savings achieved by our framework using the XMark benchmark. Since the introduction of extensible Markup Language (XML), XML repositories have gained a foothold in many global (and government) organizations, where, e-commerce and e-business models have maturated in handling daily transactional data among heterogeneous information systems in multi-data formats. Due to this, the amount of data available for enterprise decision-making process is increasing exponentially and are being stored and or communicated in XML. This presents an interesting challenge to investigate models, frameworks and techniques for organizing and analyzing such voluminous, yet distributed XML documents for business intelligence in the form of XML warehouse repositories and XML marts. In this paper, we address such an issue, where we propose a view-driven approach for modeling and designing of a Global XML FACT (GxFACT) repository under the MDA initiatives. Here we propose the GxFACT using logically grouped, geographically dispersed, XML document warehouses and Document Marts in a global enterprise setting. To deal with organizations' evolving decision-making needs, we also provide three design strategies for building and managing of such GxFACT in the context of modeling of further hierarchical dimensions and or global document warehouses