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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

Spark Streaming and GraphX

The last two things I want to cover in this chapter are Spark Streaming and GraphX, which are two technologies built on top of Spark. Spark Streaming handles continually incoming real-time data, say from a series of web logs from web servers that are running all the time. GraphX offers some tools for network analysis, kind of like the social network analysis that we were doing back when we were looking at superheroes and their relationships to each other. I'm going to cover Spark Streaming and GraphX at kind of a hand-wavey high level, because they're currently incomplete. Neither one really has good support for Python yet, right now they only work in Scala and they're in the process of being ported to Java and Python. However, by the time you read this book they might very well be available. So, all we can do is talk about them at this point, but I think you'll get the idea. So, follow along and let's see what's there.

What is Spark Streaming?

Spark Streaming is...

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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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