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Complete Guide to Open Source Big Data Stack [Paperback]

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  • Category: Books (Computers)
  • Author:  Frampton, Michael
  • Author:  Frampton, Michael
  • ISBN-10:  1484221486
  • ISBN-10:  1484221486
  • ISBN-13:  9781484221488
  • ISBN-13:  9781484221488
  • Publisher:  Apress
  • Publisher:  Apress
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Nov-2018
  • Pub Date:  01-Nov-2018
  • SKU:  1484221486-11-SPRI
  • SKU:  1484221486-11-SPRI
  • Item ID: 101638365
  • List Price: $49.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Jan 23 to Jan 25
  • Notes: Brand New Book. Order Now.

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 stacksharing 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 Youll Learn

  • Install a private cloud onto the local cluster 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

Who This Book Is For

Developers, architects, IT project managers, database administrators, and others charged with developing or supporting a big data system. It is also for anyone interested in Hadoop or big data, and those experiencing problems with data size.

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.- Chaptl#m

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