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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

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787287945
Length 296 pages
Edition 1st Edition
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Author (1):
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Frank Kane Frank Kane
Author Profile Icon Frank Kane
Frank Kane
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Table of Contents (8) Chapters Close

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

What is Spark?

According to Apache, Spark is a fast and general engine for large-scale data processing. This is actually a really good summary of what it's all about. If you have a really massive dataset that can represent anything - weblogs, genomics data, you name it - Spark can slice and dice that data up. It can distribute the processing among a huge cluster of computers, taking a data analysis problem that's just too big to run on one machine and divide and conquer it by splitting it up among multiple machines.

Spark is scalable

The way that Spark scales data analysis problems is, it runs on top of a cluster manager, so your actual Spark scripts are just everyday scripts written in Python, Java, or Scala; they...

You have been reading a chapter from
Frank Kane's Taming Big Data with Apache Spark and Python
Published in: Jun 2017
Publisher: Packt
ISBN-13: 9781787287945
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