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Frank Kane's Taming Big Data with Apache Spark and Python

You're reading from Frank Kane's Taming Big Data with Apache Spark and Python Real-world examples to help you analyze large datasets with Apache Spark

Product type Paperback

Published in Jun 2017

Publisher Packt

ISBN-13 9781787287945

Length 296 pages

Edition 1st Edition

Languages

Python

Tools

Apache Spark

Concepts

Big Data

Author (1):

Frank Kane

View More author details

Table of Contents (8) Chapters

Preface

1. Getting Started with Spark

2. Spark Basics and Spark Examples FREE CHAPTER

3. Advanced Examples of Spark Programs

4. Running Spark on a Cluster

5. SparkSQL, DataFrames, and DataSets

6. Other Spark Technologies and Libraries

7. Where to Go From Here? – Learning More About Spark and Data Science

Setting up our Amazon Web Services / Elastic MapReduce account and PuTTY

To get started with Amazon Web Services, first we're going to walk through how to create an account on AWS if you haven't one already. When we're done, we're going to figure out how to actually connect to the instances that we might be spinning up on Web Services. When we create a cluster for Spark, we need a way to log in to the master node on that cluster and actually run our script there. To do so, we need to get our credentials for logging in to any instances that our Spark cluster spins up. We'll also set up a Terminal, if you're on Windows, called PuTTY, and go through how to actually use that to connect to your instances.

Okay, let's go through how to set up an Amazon Web Services account and get started with Elastic MapReduce. We'll also figure out how to connect to our instances on Elastic MapReduce. Head over to aws.amazon.com:

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Authors (1)

Frank Kane

Frank Kane

Frank Kane has spent nine years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers all the time. He holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology and teaches others about big data analysis.

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