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Record Nr. |
UNINA9910300363403321 |
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Autore |
Frampton Mike |
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Titolo |
Complete Guide to Open Source Big Data Stack [[electronic resource] /] / by Michael Frampton |
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Pubbl/distr/stampa |
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Berkeley, CA : , : Apress : , : Imprint : Apress, , 2018 |
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ISBN |
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Edizione |
[1st ed. 2018.] |
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Descrizione fisica |
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1 online resource (XX, 365 p. 167 illus., 131 illus. in color.) |
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Disciplina |
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Soggetti |
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Big data |
Database management |
Artificial intelligence—Data processing |
Big Data |
Database Management |
Data Science |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Chapter 1: The Big Data Stack Overview -- Chapter 2: Cloud Storage -- Chapter 3: Apache Brooklyn -- Chapter 4: Apache Mesos -- Chapter 5: Stack Storage Options -- Chapter 6: Processing -- Chapter 7: Streaming -- Chapter 8: Frameworks -- Chapter 9: Visualization -- Chapter 10: The Big Data Stack -- . |
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Sommario/riassunto |
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See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack—sharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more. What You’ll Learn: Install a private cloud onto the local cluster |
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using Apache cloud stack Source, install, and configure Apache: Brooklyn, Mesos, Kafka, and Zeppelin See how Brooklyn can be used to install Mule ESB on a cluster and Cassandra in the cloud Install and use DCOS for big data processing Use Apache Spark for big data stack data processing. |
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