Abstract
Advances in data exploitation (access, query, retrieval, analysis, mining) are inherent to current and future information systems. Today, accessing great volumes of information is reality; tomorrow data intensive management systems will enable huge user communities to transparently access multiple pre-existing autonomous, distributed and heterogeneous resources (data, documents, services). Existing data management solutions do not provide efficient techniques for exploiting and mining tera-datasets available in clusters, peer to peer and grid architectures. Parallel and distributed databases are a key element for achieving scalable, efficient systems that will both cost-effectively manage and extract knowledge from huge amounts of highly distributed and heterogeneous digital data repositories.
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Ā© 2007 Springer-Verlag Berlin Heidelberg
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PatiƱo-Martinez, M., Vargas-Solar, G., Baralis, E., Kemme, B. (2007). Topic 5 Parallel and Distributed Databases. In: Kermarrec, AM., BougƩ, L., Priol, T. (eds) Euro-Par 2007 Parallel Processing. Euro-Par 2007. Lecture Notes in Computer Science, vol 4641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74466-5_32
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DOI: https://doi.org/10.1007/978-3-540-74466-5_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74465-8
Online ISBN: 978-3-540-74466-5
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