Synopsis
This manuscript provides a synthetic overview of research on data management in support of stream processing. It address all stages of the stream processing pipeline: data collection and in-transit processing at the edge, transfer towards the cloud processing sites, ingestion and persistent storage. First, the general context of stream data management is presented in light of the recent transition from Big to Fast Data. After highlighting the challenges at the data level associated with batch and real-time analytics, we introduce a subjective overview of proposals to address them. They bring solutions to the problems of in-transit stream storage and processing, fast data transfers, distributed metadata management, dynamic ingestion and transactional storage. The integration of these solutions into functional prototypes and the results of the large-scale experimental evaluations on clusters, clouds and supercomputers demonstrate their effectiveness for several real-life applications ranging from neuro-science to LHC nuclear physics. Finally, these contributions are put into the perspective of the High Performance Computing - Big Data convergence.
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From Big Data to Fast Data: Efficient Stream Data Management
Edité par
Éditions Universitaires Européennes Apr 2019, 2019
ISBN 10 : 6138485149
ISBN 13 : 9786138485148
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Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This manuscript provides a synthetic overview of research on data management in support of stream processing. It address all stages of the stream processing pipeline: data collection and in-transit processing at the edge, transfer towards the cloud processing sites, ingestion and persistent storage. First, the general context of stream data management is presented in light of the recent transition from Big to Fast Data. After highlighting the challenges at the data level associated with batch and real-time analytics, we introduce a subjective overview of proposals to address them. They bring solutions to the problems of in-transit stream storage and processing, fast data transfers, distributed metadata management, dynamic ingestion and transactional storage. The integration of these solutions into functional prototypes and the results of the large-scale experimental evaluations on clusters, clouds and supercomputers demonstrate their effectiveness for several real-life applications ranging from neuro-science to LHC nuclear physics. Finally, these contributions are put into the perspective of the High Performance Computing - Big Data convergence. 180 pp. Englisch. N° de réf. du vendeur 9786138485148
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From Big Data to Fast Data: Efficient Stream Data Management
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Éditions universitaires européennes, 2019
ISBN 10 : 6138485149
ISBN 13 : 9786138485148
Neuf
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Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Costan AlexandruAlexandru Costan is an Associate Professor at INSA Rennes and a researcher within the KerData team at IRISA Rennes. His research interests include Big Data management in HPC and clouds, fast data and stream processing. N° de réf. du vendeur 289578904
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From Big Data to Fast Data: Efficient Stream Data Management
Edité par
Éditions universitaires européennes, 2019
ISBN 10 : 6138485149
ISBN 13 : 9786138485148
Neuf
Taschenbuch
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Taschenbuch. Etat : Neu. From Big Data to Fast Data: Efficient Stream Data Management | Alexandru Costan | Taschenbuch | 180 S. | Englisch | 2019 | Éditions universitaires européennes | EAN 9786138485148 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 116752965
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From Big Data to Fast Data: Efficient Stream Data Management
Edité par
Éditions Universitaires Européennes Apr 2019, 2019
ISBN 10 : 6138485149
ISBN 13 : 9786138485148
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This manuscript provides a synthetic overview of research on data management in support of stream processing. It address all stages of the stream processing pipeline: data collection and in-transit processing at the edge, transfer towards the cloud processing sites, ingestion and persistent storage. First, the general context of stream data management is presented in light of the recent transition from Big to Fast Data. After highlighting the challenges at the data level associated with batch and real-time analytics, we introduce a subjective overview of proposals to address them. They bring solutions to the problems of in-transit stream storage and processing, fast data transfers, distributed metadata management, dynamic ingestion and transactional storage. The integration of these solutions into functional prototypes and the results of the large-scale experimental evaluations on clusters, clouds and supercomputers demonstrate their effectiveness for several real-life applications ranging from neuro-science to LHC nuclear physics. Finally, these contributions are put into the perspective of the High Performance Computing - Big Data convergence.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 180 pp. Englisch. N° de réf. du vendeur 9786138485148
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From Big Data to Fast Data: Efficient Stream Data Management
Edité par
Éditions Universitaires Européennes, 2019
ISBN 10 : 6138485149
ISBN 13 : 9786138485148
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This manuscript provides a synthetic overview of research on data management in support of stream processing. It address all stages of the stream processing pipeline: data collection and in-transit processing at the edge, transfer towards the cloud processing sites, ingestion and persistent storage. First, the general context of stream data management is presented in light of the recent transition from Big to Fast Data. After highlighting the challenges at the data level associated with batch and real-time analytics, we introduce a subjective overview of proposals to address them. They bring solutions to the problems of in-transit stream storage and processing, fast data transfers, distributed metadata management, dynamic ingestion and transactional storage. The integration of these solutions into functional prototypes and the results of the large-scale experimental evaluations on clusters, clouds and supercomputers demonstrate their effectiveness for several real-life applications ranging from neuro-science to LHC nuclear physics. Finally, these contributions are put into the perspective of the High Performance Computing - Big Data convergence. N° de réf. du vendeur 9786138485148
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