Isbn: 9781484221747 - big data smack: a guide to apache spark, mesos, akka, cassandra, and kafka (21 risultati)

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Paperback or Softback. Condizione: New. Big Data Smack: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka. Book.

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Condizione: New.

Paperback. Condizione: New.

Condizione: New.

Condizione: New. Num Pages: 264 pages, 22 black & white illustrations, 52 colour illustrations, biography. BIC Classification: UN. Category: (P) Professional & Vocational. Dimension: 180 x 332 x 18. Weight in Grams: 582. . 2016. 1st ed. Paperback. . . . .

Condizione: New. In English.

Condizione: New. pp. 264.

Condizione: As New. Unread book in perfect condition.

Condizione: New. Num Pages: 264 pages, 22 black & white illustrations, 52 colour illustrations, biography. BIC Classification: UN. Category: (P) Professional & Vocational. Dimension: 180 x 332 x 18. Weight in Grams: 582. . 2016. 1st ed. Paperback. . . . . Books ship from the US and Ireland.

Paperback. Condizione: Brand New. 264 pages. 9.00x6.00x1.00 inches. In Stock.

Taschenbuch. Condizione: Neu. Big Data SMACK | A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka | Raul Estrada (u. a.) | Taschenbuch | xxv | Englisch | 2016 | Apress | EAN 9781484221747 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Condizione: new. Questo è un articolo print on demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Learn how to integrate full-stack open source big data architecture and to choose the correct technology-Scala/Spark, Mesos, Akka, Cassandra, and Kafka-in every layer.Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses.Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer:The language: ScalaThe engine: Spark (SQL, MLib, Streaming, GraphX)The container: Mesos, DockerThe view: AkkaThe storage: CassandraThe message broker: KafkaWhat You Will Learn:Make big data architecture without using complex Greek letter architecturesBuild a cheap but effective cluster infrastructureMake queries, reports, and graphs that business demandsManage and exploit unstructured and No-SQL data sourcesUse tools to monitor the performance of your architectureIntegrate all technologies and decide which ones replace and which ones reinforceWho This Book Is For:Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer 292 pp. Englisch.…

Condizione: New. Print on Demand pp. 264.

Condizione: New. PRINT ON DEMAND pp. 264.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Learn how to integrate full-stack open source big data architecture and to choose the correct technology-Scala/Spark, Mesos, Akka, Cassandra, and Kafka-in every layer.Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses.Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer:The language: ScalaThe engine: Spark (SQL, MLib, Streaming, GraphX)The container: Mesos, DockerThe view: AkkaThe storage: CassandraThe message broker: KafkaWhat You Will Learn:Make big data architecture without using complex Greek letter architecturesBuild a cheap but effective cluster infrastructureMake queries, reports, and graphs that business demandsManage and exploit unstructured and No-SQL data sourcesUse tools to monitor the performance of your architectureIntegrate all technologies and decide which ones replace and which ones reinforceWho This Book Is For:Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first book presenting the SMACK stackA practical guide teaching how to incorporate big dataCovers the full stack of big data architecture, discussing the practical benefits of each technology.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Learn how to integrate full-stack open source big data architecture and to choose the correct technology-Scala/Spark, Mesos, Akka, Cassandra, and Kafka-in every layer.Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses.Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer:The language: ScalaThe engine: Spark (SQL, MLib, Streaming, GraphX)The container: Mesos, DockerThe view: AkkaThe storage: CassandraThe message broker: KafkaWhat You Will Learn:Make big data architecture without using complex Greek letter architecturesBuild a cheap but effective cluster infrastructureMake queries, reports, and graphs that business demandsManage and exploit unstructured and No-SQL data sourcesUse tools to monitor the performance of your architectureIntegrate all technologies and decide which ones replace and which ones reinforceWho This Book Is For:Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layerSpringer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 292 pp. Englisch.…