Complete Guide to Open Source Big Data Stack
Nonfiction, Computers, Advanced Computing, Programming, Data Modeling & Design, Database Management, General Computing
| Author: | Michael Frampton | ISBN: | 9781484221495 |
| Publisher: | Apress | Publication: | January 18, 2018 |
| Imprint: | Apress | Language: | English |
| Author: | Michael Frampton |
| ISBN: | 9781484221495 |
| Publisher: | Apress |
| Publication: | January 18, 2018 |
| Imprint: | Apress |
| Language: | English |
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
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.
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
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.
