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Synopsis
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:
What You Will Learn:
- Make big data architecture without using complex Greek letter architectures
- Build a cheap but effective cluster infrastructure
- Make queries, reports, and graphs that business demands
- Manage and exploit unstructured and No-SQL data sources
- Use tools to monitor the performance of your architecture
- Integrate all technologies and decide which ones replace and which ones reinforce
Who 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 layerLes informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Raúl Estrada is the co-founder of Treu Technologies, an enterprise for Social Data Marketing and BigData research. He is an Enterprise Architect with more than 15 years of experience in cluster management and Enterprise Software. Prior to founding Treu Technologies, Estrada worked as an Enterprise Architect in Application Servers & evangelist for Oracle Inc. He loves functional languages like Elixir and Scala, and also has a Master of Computer Science degree.
Isaac Ruiz has been a Java programmer since 2001, and a consultant and architect since 2003. He has participated in projects of different areas and varied scopes (education, communications, retail, and others). Ruiz specializes in systems integration and has participated in projects mainly related to the financial sector. He is a supporter of free software. Ruiz likes to experiment with new technologies (frameworks, languages, methods).
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Big Data Smack: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka
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Paperback. Etat : As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less 1.3. N° de réf. du vendeur G1484221745I2N00
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Kartoniert / Broschiert. Etat : 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. N° de réf. du vendeur 123474193
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Big Data SMACK : A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka
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Big Data SMACK: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka
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Big Data SMACK
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9781484221747
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Big Data SMACK
Edité par
Apress, Apress Sep 2016, 2016
ISBN 10 : 1484221745
ISBN 13 : 9781484221747
Neuf
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. Neuware -Learn how to integrate full-stack open source big data architecture and to choose the correct technology¿Scala/Spark, Mesos, Akka, Cassandra, and Kafkäin 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 layerAPress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 292 pp. Englisch. N° de réf. du vendeur 9781484221747
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Big Data SMACK : A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9781484221747
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Big Data SMACK: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka
impression à la demandeVendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 584. N° de réf. du vendeur C9781484221747
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Big Data Smack: A Guide to Apache Scala/Spark, Mesos, Akka, Cassandra, and Kafka
Edité par
Apress, Incorporated, 2016
ISBN 10 : 1484221745
ISBN 13 : 9781484221747
Neuf
Couverture souple
Vendeur : Books Puddle, New York, NY, Etats-Unis
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Etat : New. pp. 264. N° de réf. du vendeur 26374909994
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Big Data Smack: A Guide to Apache Scala/Spark, Mesos, Akka, Cassandra, and Kafka
Edité par
Apress, Incorporated, 2016
ISBN 10 : 1484221745
ISBN 13 : 9781484221747
Neuf
Couverture souple
Vendeur : Majestic Books, Hounslow, Royaume-Uni
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