22,248 research outputs found

    Distribution design in object oriented databases : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Science in Information Systems

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    The advanced development of object oriented database systems has attracted much research. However, very few of them contribute to the distribution design of object oriented databases. The main tasks of distribution design are fragmenting the database schema and allocating the fragments to different sites of a network. The aim of fragmentation and allocation is to improve the performance and increase the availability of a database system. Even though much research has been done on distributed databases, the research almost always refers to the relational data model (RDM). Very few efforts provide distribution design techniques for distributed object oriented databases. The aim of this work is to generalise distribution design techniques from relational databases for object oriented databases. First, the characteristics of distributed databases in general and the techniques used for fragmentation and allocation for the RDM are reviewed. Then, fragmentation operations for a rather generic object oriented data model (OODM) are developed. As with the RDM, these operations include horizontal and vertical fragmentation. A third operation named splitting is also introduced for OODM. Finally, normal predicates are introduced for OODM. A heuristic procedure for horizontal fragmenting of OODBs is also presented. The adaption of horizontal fragmentation techniques for relational databases to object oriented databases is the main result of this work

    Incremental object horizontal fragmentation.

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    In intranets, extranets and internet applications, data are by nature complex and distributed over different sites. Object-oriented database management systems meet the requirements of these applications. It offers complex structures, object identity, inheritance between classes and extensibility to capture complex data. A distributed database system partitions large and complex data into smaller pieces and allocates them at different sites to enhance application performance by reducing data communication and replication costs. The design issues of distributed database system require solving several interrelated problems: data fragmentation, allocation and optimization. There are three types of fragmentation---horizontal, vertical and hybrid. Horizontal fragmentation of a class keeps all attributes and methods of the class but some instance objects in each horizontal fragment. In other words, a horizontal fragment is a subset of class extent or instance objects. Application queries, query access frequencies, instance objects, and object database schema including class composition hierarchies and class inheritance are used as input to generate these fragments. When there are major changes in these input over time, the performance of the distributed object-based system degrades and requires re-fragmentation. The re-fragmentation is started from scratch with static fragmentation approach using all input data (old and changed part). In this thesis, we propose a new algorithm called Incremental Object Horizontal Fragmentation (IOHF) for distributed object-oriented database systems. This algorithm uses the changed part of input data and previous fragments to define new fragments more quickly, saving system resources and making data at distributed sites more available for network and web access. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2002 .D49. Source: Masters Abstracts International, Volume: 42-01, page: 0256. Adviser: Christie Ezeife. Thesis (M.Sc.)--University of Windsor (Canada), 2002

    Partout: A Distributed Engine for Efficient RDF Processing

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    The increasing interest in Semantic Web technologies has led not only to a rapid growth of semantic data on the Web but also to an increasing number of backend applications with already more than a trillion triples in some cases. Confronted with such huge amounts of data and the future growth, existing state-of-the-art systems for storing RDF and processing SPARQL queries are no longer sufficient. In this paper, we introduce Partout, a distributed engine for efficient RDF processing in a cluster of machines. We propose an effective approach for fragmenting RDF data sets based on a query log, allocating the fragments to nodes in a cluster, and finding the optimal configuration. Partout can efficiently handle updates and its query optimizer produces efficient query execution plans for ad-hoc SPARQL queries. Our experiments show the superiority of our approach to state-of-the-art approaches for partitioning and distributed SPARQL query processing

    The Design of a Distributed Database for Doctoral Studies Management

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    This paper aims to create a system that manages doctoral school requirements. The management of doctoral school implies administration of information like PhD personal information, Supervisors, Teachers, and other information that may be useful. We will debate on distributed database term as the proposed database project will have the same structure for four universities. Each university will be able to work on this database by accessing its own set of data and properly using the information received. This project will track the creation of a database to manage all the information needed and provide answers using these data.Distributed Database, Fragmentation, Top-Down Design Process

    Distributed databases

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    Mòdul 3 del llibre Database Architecture. UOC, 20122022/202
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