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Complete Guide to Open Source Big Data Stack

  • Michael Frampton

Table of contents

  1. Front Matter
    Pages i-xx
  2. Michael Frampton
    Pages 1-15
  3. Michael Frampton
    Pages 17-58
  4. Michael Frampton
    Pages 59-95
  5. Michael Frampton
    Pages 97-137
  6. Michael Frampton
    Pages 139-175
  7. Michael Frampton
    Pages 177-217
  8. Michael Frampton
    Pages 219-257
  9. Michael Frampton
    Pages 259-294
  10. Michael Frampton
    Pages 295-337
  11. Michael Frampton
    Pages 339-356
  12. Back Matter
    Pages 357-365

About this book

Introduction

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 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


Keywords

Big data stack Open source software Apache cloud stack Apache Brooklyn Hadoop Cassandra RIAK Apache Spark Apache Kafka Apache Zeppelin Data visualization

Authors and affiliations

  • Michael Frampton
    • 1
  1. 1.ParaparaumuNew Zealand

Bibliographic information

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