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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

Map Reduce program to find distinct values


In this recipe, we are going to learn how to write a map reduce program to find distinct values from a given set of data.

Getting ready

To perform this recipe, you should have a running Hadoop cluster as well as an eclipse that is similar to an IDE.

How to do it

Sometimes, there may be a chance that the data you have contains some duplicate values. In SQL, we have something called a distinct function, which helps us get distinct values. In this recipe, we are going to take a look at how we can get distinct values using map reduce programs.

Let's consider a use case where we have some user data with us, which contains two columns: userId and username. Let's assume that the data we have contains duplicate records, and for our processing needs, we only need distinct records through user IDs. Here is some sample data that we have where columns are separated by '|':

1|Tanmay
2|Ramesh
3|Ram
1|Tanmay
2|Ramesh
6|Rahul
6|Rahul
4|Sneha
4|Sneha

The idea here is to...

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