Complete Guide to Open Source Big Data Stack

Description

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 processingUse 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. Front Matter ....Pages i-xx The Big Data Stack Overview (Michael Frampton)....Pages 1-15 Cloud Storage (Michael Frampton)....Pages 17-58 Apache Brooklyn (Michael Frampton)....Pages 59-95 Apache Mesos (Michael Frampton)....Pages 97-137 Stack Storage Options (Michael Frampton)....Pages 139-175 Processing (Michael Frampton)....Pages 177-217 Streaming (Michael Frampton)....Pages 219-257 Frameworks (Michael Frampton)....Pages 259-294 Visualisation (Michael Frampton)....Pages 295-337 The Big Data Stack (Michael Frampton)....Pages 339-356 Back Matter ....Pages 357-365