Big Data SMACK : A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka

Isaac Ruiz

ISBN 10: 1484221745 / ISBN 13: 9781484221747

Verlag: Apress, Apress, 2016

Beschreibung

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.

Bestandsnummer des Verkäufers 9781484221747

Bibliografische Details

• Titel: Big Data SMACK : A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka
• Verlag: Apress, Apress
• Erscheinungsjahr: 2016
• Sprache: Englisch
• ISBN-10: 1484221745
• ISBN-13: 9781484221747
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

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: Scala

The engine: Spark (SQL, MLib, Streaming, GraphX)

The container: Mesos, Docker

The view: Akka

The storage: Cassandra

The message broker: Kafka

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 layer

Über die Autorin bzw. den Autor

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).