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Big Data Analytics

You're reading from   Big Data Analytics Real time analytics using Apache Spark and Hadoop

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Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781785884696
Length 326 pages
Edition 1st Edition
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Author (1):
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Venkat Ankam Venkat Ankam
Author Profile Icon Venkat Ankam
Venkat Ankam
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Table of Contents (12) Chapters Close

Preface 1. Big Data Analytics at a 10,000-Foot View 2. Getting Started with Apache Hadoop and Apache Spark FREE CHAPTER 3. Deep Dive into Apache Spark 4. Big Data Analytics with Spark SQL, DataFrames, and Datasets 5. Real-Time Analytics with Spark Streaming and Structured Streaming 6. Notebooks and Dataflows with Spark and Hadoop 7. Machine Learning with Spark and Hadoop 8. Building Recommendation Systems with Spark and Mahout 9. Graph Analytics with GraphX 10. Interactive Analytics with SparkR Index

What you need for this book

Practical exercises in this book are demonstrated on virtual machines (VM) from Cloudera, Hortonworks, MapR, or prebuilt Spark for Hadoop for getting started easily. The same exercises can be run on a bigger cluster as well.

Prerequisites for using virtual machines on your laptop:

  • RAM: 8 GB and above
  • CPU: At least two virtual CPUs
  • The latest VMWare player or Oracle VirtualBox must be installed for Windows or Linux OS
  • Latest Oracle VirtualBox, or VMWare Fusion for Mac
  • Virtualization enabled in BIOS
  • Browser: Chrome 25+, IE 9+, Safari 6+, or Firefox 18+ recommended (HDP Sandbox will not run on IE 10)
  • Putty
  • WinScP

The Python and Scala programming languages are used in chapters, with more focus on Python. It is assumed that readers have a basic programming background in Java, Scala, Python, SQL, or R, with basic Linux experience. Working experience within Big Data environments on Hadoop platforms would provide a quick jump start for building Spark applications.

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