My Account Log in

1 option

Complete Guide to Open Source Big Data Stack / by Michael Frampton.

O'Reilly Online Learning: Academic/Public Library Edition Available online

View online
Format:
Book
Author/Creator:
Frampton, Mike, Author.
Language:
English
Subjects (All):
Big data.
Database management.
Artificial intelligence—Data processing.
Big Data.
Database Management.
Data Science.
Apache Mesos (Electronic resource).
Local Subjects:
Big Data.
Database Management.
Data Science.
Physical Description:
1 online resource (XX, 365 p. 167 illus., 131 illus. in color.)
Edition:
1st ed. 2018.
Place of Publication:
Berkeley, CA : Apress : Imprint: Apress, 2018.
System Details:
text file
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.
Contents:
Chapter 1: The Big Data Stack Overview
Chapter 2: Cloud Storage
Chapter 3: Apache Brooklyn
Chapter 4: Apache Mesos
Chapter 5: Stack Storage Options
Chapter 6: Processing
Chapter 7: Streaming
Chapter 8: Frameworks
Chapter 9: Visualization
Chapter 10: The Big Data Stack
.
Notes:
Includes index.
ISBN:
9781484221495
1484221494
OCLC:
1023436605

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Library Catalog Using Articles+ Library Account