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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

Call Data Record Analytics using Hive


Call Data Records (CDR) are special types of records that are used in the telecom domain to keep track of calls made by individuals. We can use Hive to analyze these records in order to give special offers to customers.

Note

You can read more about CDR at https://en.wikipedia.org/wiki/Call_detail_record.

Getting ready

To perform this recipe, you should have a running Hadoop cluster as well as the latest version of Hive installed on it. Here, I am using Hive 1.2.1.

How to do it...

First of all, let's consider a situation where we have the following type of dataset with us. To analyze it, we first need to create a Hive table and load data into it:

CALLER_PHONE_NO|RECEIVER_PHONE_NUMBER|START_TIME|END_TIME|CALL_TYPE
11111|22222|2015-01-12 01:20:00|2015-01-12 01:30:00|VOICE
11111|22222|2015-02-12 01:35:00|2015-02-12 01:35:30|VOICE
11111|22222|2015-02-12 02:20:00|2015-02-12 02:20:00|SMS
33333|44444|2015-01-12 01:20:00|2015-01-12 01:30:00|VOICE
11111|33333|2015-05...
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