Book Image

Hadoop Blueprints

By : Anurag Shrivastava, Tanmay Deshpande
Book Image

Hadoop Blueprints

By: Anurag Shrivastava, Tanmay Deshpande

Overview of this book

If you have a basic understanding of Hadoop and want to put your knowledge to use to build fantastic Big Data solutions for business, then this book is for you. Build six real-life, end-to-end solutions using the tools in the Hadoop ecosystem, and take your knowledge of Hadoop to the next level. Start off by understanding various business problems which can be solved using Hadoop. You will also get acquainted with the common architectural patterns which are used to build Hadoop-based solutions. Build a 360-degree view of the customer by working with different types of data, and build an efficient fraud detection system for a financial institution. You will also develop a system in Hadoop to improve the effectiveness of marketing campaigns. Build a churn detection system for a telecom company, develop an Internet of Things (IoT) system to monitor the environment in a factory, and build a data lake – all making use of the concepts and techniques mentioned in this book. The book covers other technologies and frameworks like Apache Spark, Hive, Sqoop, and more, and how they can be used in conjunction with Hadoop. You will be able to try out the solutions explained in the book and use the knowledge gained to extend them further in your own problem space.
Table of Contents (14 chapters)
Hadoop Blueprints
About the Authors
About the Reviewers

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


Age (derived from date of birth)




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


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: