129 research outputs found
Actualidad literaria hispanoargelina (II): la reciente obra de Souad Hadj-Ali Mouhoub
No full textBibliographical commentary on three works by the Algerian author Souad Hadj-Ali Mouhoub.Comentario bibliográfico sobre tres obras de la autora argelina Souad Hadj-Ali Mouhoub
Optimisation de la performance des entrepôts de données XML par fragmentation et répartition
No full textXML data warehouses form an interesting basis for decision-support applications that exploit heterogeneous data from multiple sources. However, XML-native database systems currently suffer from limited performances, both in terms of manageable data volume and response time for complex analytical queries. It is therefore necessary to design methods to optimize performances.In this thesis, we propose to address both these issues by fragmenting and distributing XML data warehouses on grids. To the best of our knowledge, we propose the first fragmentation methods for XML data warehouses. These methods exploit an XQuery workload and output a derived horizontal fragmentation schema.We first adapted the most efficient fragmentation methods from the relational context to XML, and then proposed an original k-means-based fragmentation method that allows mastering the number of fragments. We finally propose an approach aimed at distributing XML data warehouses on grid architectures.Our proposals exploit a unified XML warehouse reference model that we propose to synthesize and enhance related work from the literature.Finally, we experimentally validate our proposal and compare our fragmentation and distribution methods. For this purpose, we designed and developed an XML data warehouse benchmark: XWeB. Our results show that our methods help overcome the data volume andquery execution time limitations. They also show that our k-means-based fragmentation method outperforms classical derived horizontal fragmentation methods, both in terms of performance gain and overhead.Les entrepôts de données XML forment une base intéressante pour les applications décisionnelles qui exploitent des données hétérogènes et provenant de sources multiples. Cependant, les Systèmes de Gestion de Bases de Données (SGBD) natifs XML actuels présentent des limites en termes de volume de données gérable, d'une part, et de performance des requêtes d'interrogation complexes, d'autre part. Il apparaît donc nécessaire de concevoir des méthodes pour optimiser ces performances.Pour atteindre cet objectif, nous proposons dans ce mémoire de pallier conjointement ces limitations par fragmentation puis par répartition sur une grille de données. Pour cela, nous nous sommes intéressés dans un premier temps à la fragmentation des entrepôts des données XML et nous avons proposé des méthodes qui sont à notre connaissance les premières contributions dans ce domaine. Ces méthodes exploitent une charge de requêtes XQuery pour déduire un schéma de fragmentation horizontale dérivée.Nous avons tout d'abord proposé l'adaptation des techniques les plus efficaces du domaine relationnel aux entrepôts de données XML, puis une méthode de fragmentation originale basée sur la technique de classification k-means. Cette dernière nous a permis de contrôler le nombre de fragments. Nous avons finalement proposé une approche de répartition d'un entrepôt de données XML sur une grille. Ces propositions nous ont amené à proposer un modèle de référence pour les entrepôts de données XML qui unifie et étend les modèles existants dans la littérature.Nous avons finalement choisi de valider nos méthodes de manière expérimentale. Pour cela, nous avons conçu et développé un banc d'essais pour les entrepôts de données XML : XWeB. Les résultats expérimentaux que nous avons obtenus montrent que nous avons atteint notre objectif de maîtriser le volume de données XML et le temps de traitement de requêtes décisionnelles complexes. Ils montrent également que notre méthode de fragmentation basée sur les k-means fournit un gain de performance plus élevé que celui obtenu par les méthodes de fragmentation horizontale dérivée classiques, à la fois en terme de gain de performance et de surcharge des algorithmes
XML Warehousing and OLAP
No full textWith the eXtensible Markup Language (XML) becoming a standard for representing business data (Beyer et al., 2005), a new trend toward XML data warehousing has been emerging for a couple of years, as well as efforts for extending the XQuery language with near On-Line Analytical Processing (OLAP) capabilities (grouping, aggregation, etc.). Though this is not an easy task, these new approaches, techniques and architectures aim at taking specificities of XML into account (e.g., heterogeneous number and order of dimensions or complex measures in facts, ragged dimension hierarchies…) that would be intricate to handle in a relational environment. The aim of this article is to present an overview of the major XML warehousing approaches from the literature, as well as the existing approaches for performing OLAP analyses over XML data (which is termed XML-OLAP or XOLAP; Wang et al., 2005). We also discuss the issues and future trends in this area and illustrate this topic by presenting the design of a unified, XML data warehouse architecture and a set of XOLAP operators expressed in an XML algebra. </jats:p
History of Fuuta Jalon
No full textThe entire manuscript is available for download as a single PDF file. Because of the large size of this manuscript, it is also available in three PDF files. In addition, each page is available as a separate, larger, JPG file. If higher-resolution JP2 files are needed (WARNING: files average 15-20MB in size), please contact [email protected]. Fieldwork Team: M. Lamine Diallo (Lecturer of Wolof & Pular Languages) and Ahmed Diallo (Research Assistant). Technical Team: Dr. Vika Zafrin (Digital Scholarship Librarian, BU Libraries), Dr. Fallou Ngom (Director, African Language Program), Dr. Peter Quella (Assistant Director, African Studies Center), and Sarah Davis Westwood (PhD Candidate, Department of History). This collection of Fuuta Jalon Pular Ajami materials is copied as part of the African Studies Center’s African Ajami Library. This project is funded by the BU African Studies Center. We thank Prof. Tim Longman, Director of the African Studies Center, and the entire African Studies team for their support. For Inquiries: Please contact Professor Fallou Ngom ([email protected]).The material talks about the organization of the Fuuta Jalon community for expansion of Islam. Fuuta Jalon was organized into three regions: Timbi, Timbo, and Labe. The material was first written in 1901 and has been written again in 1967 by the author in Pita, Fuuta Jalon. The material was digitized in Dakar, Senegal. The video contains El hadj Mouhamadou Sall sharing biographical information and details related to the acquisition and contents of these Ajami materials
Fragmenting Very Large XML Data Warehouses via K-means Clustering Algorithm
No full textXML 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
Enhancing XML data warehouse query performance by fragmentation
No full textInternational audienceXML data warehouses form an interesting basis for decision-support applications that exploit heterogeneous data from multiple sources. However, XML-native database systems currently suffer from limited performances in terms of manageable data volume and response time for complex analytical queries. Fragmenting and distributing XML data warehouses (e.g., on data grids) allow to address both these issues. In this paper, we work on XML warehouse fragmentation. In relational data warehouses, several studies recommend the use of derived horizontal fragmentation. Hence, we propose to adapt it to the XML context. We particularly focus on the initial horizontal fragmentation of dimensions' XML documents and exploit two alternative algorithms. We experimentally validate our proposal and compare these alternatives with respect to a unified XML warehouse model we advocate for
Data mining-based fragmentation of xml data warehouses
No full textWith the multiplication of XML data sources, many XML data warehouse models have been proposed to handle data heterogeneity and complexity in a way relational data ware-houses fail to achieve. However, XML-native database sys-tems currently suffer from limited performances, both in terms of manageable data volume and response time. Frag-mentation helps address both these issues. Derived horizon-tal fragmentation is typically used in relational data ware-houses and can definitely be adapted to the XML context. However, the number of fragments produced by classical al-gorithms is difficult to control. In this paper, we propose the use of a k-means-based fragmentation approach that allows to master the number of fragments through its k parameter. We experimentally compare its efficiency to classical derived horizontal fragmentation algorithms adapted to XML data warehouses and show its superiority
XWeB: The XML Warehouse Benchmark
No full textInternational audienceWith the emergence of XML as a standard for representing business data, new decision support applications are being developed. These XML data warehouses aim at supporting On-Line Analytical Processing (OLAP) operations that manipulate irregular XML data. To ensure feasibility of these new tools, important performance issues must be addressed. Performance is customarily assessed with the help of benchmarks. However, decision support benchmarks do not currently support XML features. In this paper, we introduce the XML Warehouse Benchmark (XWeB), which aims at filling this gap. XWeB derives from the relational decision support benchmark TPC-H. It is mainly composed of a test data warehouse that is based on a unified reference model for XML warehouses and that features XML-specific structures, and its associate XQuery decision support workload. XWeB's usage is illustrated by experiments on several XML database management systems
Indices in XML Databases
No full textSince XML (eXtensible Markup Language) (Bray, Paoli, Sperberg-McQueen, Maler & Yergeau, 2004) emerged as a standard for information representation and exchange, storing, indexing, and querying, XML documents have become major issues in database research. Query processing and optimization are very important in this context, and indices are data structures that help enhance performances substantially. Though XML indexing concepts are mainly inherited from relational databases, XML indices bear numerous specificities. The aim of this chapter is to present an overview of state-of-the-art XML indices and to discuss the main issues, trade-offs, and future trends in XML indexing. Furthermore, since XML is gaining importance for representing business data for analytics (Beyer, Chamberlin, Colby, Özcan, Pirahesh & Xu, 2005), we also present an index we developed specifically for XML data warehouses.</jats:p
Benchmarking XML data warehouses
No full textAbstract. With the emergence of XML as a new standard for representing busi-ness data, new decision-support applications (namely, XML data warehouses) are being developed. To ensure their feasibility, the issue of performance must be addressed. Performance in general, and the efficiency of performance optimiza-tion techniques in particular, is usually assessed with the help of benchmarks. However, there are, to the best of our knowledge, no XML decision-support benchmark. In this paper, we present the XML Warehouse Benchmark (XWB), which aims at filling this gap. XWB is based on an original reference model for XML data warehouses, and proposes a test XML data warehouse and its associated XQuery decision-support workload that are derived from the well-known, rela-tional decision-support benchmark TPC-H. Though at an early stage of devel-opment, XWB has been successfully used to test the efficiency of indexing and view materialization techniques in XML data warehouses
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