Complete Guide to Open Source Big Data Stack

• Describes the step-by-step construction of a real-world big data stack from open source software
• Explains popular Apache-based systems such as Hadoop, HBase, Cassandra, Riak, Brooklyn, Spark, Kafka, and more
• Author builds a data stack for this book and then recounts the process, including successes, failures, and lessons learned

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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

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.