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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
Anurag Shrivastava Anurag Shrivastava
Author Profile Icon Anurag Shrivastava
Anurag Shrivastava
 Deshpande Deshpande
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Deshpande
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Table of Contents (14) Chapters Close

Hadoop Blueprints
Credits
About the Authors
About the Reviewers
www.PacktPub.com
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

Designing the high-level architecture


The high-level architecture of the system that we are planning to build contains two parts. The first part is the model, which we will build using the historical transaction data. Once this model has been created, we will use it in the second part with new data to determine whether a particular transaction falls in a cluster of suspicious transactions.

Figure 1 Design of a fraud detection system

In the previous section, we have already cleansed the transaction history file to make it suitable for the machine learning algorithm. For building the model, we will use Apache Spark.

Introducing Apache Spark

Apache Spark is an open source, big data processing framework, developed in 2009 in UC Berkeley's AMPLab. It has been developed around the goals of delivering speed, ease of use, and sophisticated analytics.

It was open sourced in 2010 as an Apache project and it has now become one of the most active projects among Apache Software Foundation projects. The...

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