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Hadoop Blueprints

You're reading from   Hadoop Blueprints Use Hadoop to solve business problems by learning from a rich set of real-life case studies

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Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781783980307
Length 316 pages
Edition 1st Edition
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Authors (3):
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Sudheesh Narayan Sudheesh Narayan
Author Profile Icon Sudheesh Narayan
Sudheesh Narayan
Tanmay Deshpande Tanmay Deshpande
Author Profile Icon Tanmay Deshpande
Tanmay Deshpande
Anurag Shrivastava Anurag Shrivastava
Author Profile Icon Anurag Shrivastava
Anurag Shrivastava
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Table of Contents (9) Chapters Close

Preface 1. Hadoop and Big Data FREE CHAPTER 2. A 360-Degree View of the Customer 3. Building a Fraud Detection System 4. Marketing Campaign Planning 5. Churn Detection 6. Analyze Sensor Data Using Hadoop 7. Building a Data Lake 8. Future Directions

Creating the target List


Now our MapReduce program is ready to run on the Hadoop cluster. We are now going to prepare the input data from the customer master database of Furnitica. The customer master data contains many details that might not be very relevant for our MapReduce job.

A subset of fields available in the master data is as follows:

  • Customer ID

  • Date of birth

  • Income

  • Gender

Let us assume here that we will now make a selection of customers living in the city where we are going to send the campaign folders. This city is the target of the campaign. A single row in our selection is shown in Table 3:

Customer ID

10023

Age (derived from date of birth)

55

Income

75000

Gender (derived from M/F, where 0 is male and 1 is female)

0

Table 3 A selection from the customer master data

We want to send the folder number 1 to our target customers so we will add this information in our inputdata.csv as well. The resulting input data file inputdata.csv is as follows:

10023,25,75000,1,1 
10024,55,25000...
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