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 our fraud detection model

HDFS is a system designed for storing massive volumes of data. In our case, we start with the 3-year banking transaction history of a fictitious customer of a bank. Our dataset includes 2,191 transactions that have resulted in the transfer of money from the customer's account to other accounts. These transactions happened using a variety of methods, such as payments at a POS terminal, direct debits, transfers from internet banking, and so on. The result of these transactions is that money leaves the account of the customer and gets credited to another account. All the times, the customer's bank wants to ensure that the money only leaves the account of the customer when the customer has authorized it. Otherwise, a transaction is a fraudulent transaction and it must be stopped.

Storing and processing 2,191 records might seem a trivial task from the point of view of HDFS and Spark. However, if a bank has 10 million customers, then to build a fraud model for...