Complete guide to open source big data stack / Michael Frampton.
2018
QA76.9.B45
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Citation
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Unlimited
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Can lend chapters, not whole ebooks
Details
Title
Complete guide to open source big data stack / Michael Frampton.
Author
ISBN
9781484221495 (electronic book)
1484221494 (electronic book)
9781484221488
1484221494 (electronic book)
9781484221488
Published
[Berkeley, CA] : Apress, 2018.
Copyright
©2018
Language
English
Description
1 online resource
Item Number
10.1007/978-1-4842-2149-5 doi
Call Number
QA76.9.B45
Dewey Decimal Classification
005.7
Summary
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.
Note
Includes index.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Online resource; title from PDF title page (viewed January 26, 2018).
Available in Other Form
Print version: 9781484221488
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