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Hadoop Real-World Solutions Cookbook- Second Edition

You're reading from   Hadoop Real-World Solutions Cookbook- Second Edition Over 90 hands-on recipes to help you learn and master the intricacies of Apache Hadoop 2.X, YARN, Hive, Pig, Oozie, Flume, Sqoop, Apache Spark, and Mahout

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Product type Paperback
Published in Mar 2016
Publisher
ISBN-13 9781784395506
Length 290 pages
Edition 2nd Edition
Tools
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Author (1):
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Tanmay Deshpande Tanmay Deshpande
Author Profile Icon Tanmay Deshpande
Tanmay Deshpande
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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started with Hadoop 2.X FREE CHAPTER 2. Exploring HDFS 3. Mastering Map Reduce Programs 4. Data Analysis Using Hive, Pig, and Hbase 5. Advanced Data Analysis Using Hive 6. Data Import/Export Using Sqoop and Flume 7. Automation of Hadoop Tasks Using Oozie 8. Machine Learning and Predictive Analytics Using Mahout and R 9. Integration with Apache Spark 10. Hadoop Use Cases Index

Olympics Athletes analytics using the Spark Shell


Spark supports an interactive Scala-based shell, which can be used to process data as and when we receive actionable commands. In this recipe, we are going to analyze one sample dataset, which contains information about the athletes that have participated in the Olympics.

Getting ready

To perform this recipe, you should have Hadoop and Spark installed. You also need to install Scala. I am using Scala 2.11.0.

How to do it...

First of all, you need to download data from https://github.com/deshpandetanmay/hadoop-real-world-cookbook/blob/master/data/OlympicAthletes.csv, and store it in HDFS using the following commands:

$hadoop fs –mkdir /athletes
$hadoop fs –put OlympicAthletes.csv /athletes

The following is some sample data from the file for your reference. The data comma-separated file contains various columns in a sequence such as the athlete name, country, year, gold, silver, bronze, and the total number of medals won by each athlete:

Yang Yilin...
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