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.

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Hadoop Blueprints
Anurag Shrivastava | Tanmay Deshpande
Sep, 2016 | 316 pages
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Table of Contents (14 chapters)
Hadoop Blueprints
Hadoop Blueprints
Credits
Credits
About the Authors
About the Authors
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Hadoop and Big Data
Hadoop and Big Data
The beginning of the big data problem
Building open source Hadoop
Enterprise Hadoop
The design of the Hadoop system
MapReduce
Building a MapReduce Version 2 program
Hadoop platform tools
Big data use cases
The architecture of Hadoop-based systems
Summary
2
A 360-Degree View of the Customer
A 360-Degree View of the Customer
Capturing business information
Setting up the technology stack
Test driving Hive and Sqoop
Engineering the solution
Presenting the view
Summary
3
Building a Fraud Detection System
Building a Fraud Detection System
Understanding the business problem
Selecting and cleansing the dataset
Machine learning for fraud detection
Designing the high-level architecture
Creating our fraud detection model
Putting the fraud detection model to use
4
Marketing Campaign Planning
Marketing Campaign Planning
Creating the solution outline
Supervised learning
Tree-structure models for classification
Finding the right dataset
Setting the up the solution architecture
Building the machine learning model
Running the Model on Hadoop
Creating the target List
Post campaign activities
Summary
5
Churn Detection
Churn Detection
A business case for churn detection
Creating the solution outline
Building a churn predictor using Hadoop
Summary
6
Analyze Sensor Data Using Hadoop
Analyze Sensor Data Using Hadoop
A business case for sensor data analytics
Creating the solution outline
Technology stack
Batch data analytics
Stream data analytics
Summary
7
Building a Data Lake
Building a Data Lake
Data lake building blocks
Hadoop security
Apache Ranger
Apache Flume
Apache Zeppelin
Technology stack for Data Lake
Data Lake business requirements
Summary
8
Future Directions
Future Directions
Hadoop solutions team
Hadoop on Cloud
NoSQL databases
Summary

About the Reviewers

Dedunu Dhananjaya is a senior software engineer in personalized learning and analytics at Pearson. He is interested in data science and analytics. Prior to Pearson, Dedunu worked at Zaizi, LIRNEasia, and WSO2. Currently, he is reading his masters in applied statistics at the University of Colombo.

Wissem El Khlifi is the first Oracle ACE from Spain and an Oracle Certified Professional DBA with over 12 years of IT experience.

He earned his computer science engineering degree from FST Tunisia and master's in computer science as well as in big data science analytics and management from UPC Barcelona. His areas of interest are Linux system administration, high availability Oracle databases, big data NOSQL database management, and big data analysis.

His career has included the following roles: Oracle and Java analyst/programmer, Oracle DBA, architect, team leader, and big data scientist. He currently works as a senior database and applications engineer for Schneider Electric/APC. He writes numerous articles on his website, http://www.oracle-class.com, and his Twitter handle is @orawiss.

Randal Scott King is the managing partner of Brilliant Data, a consulting firm specializing in data analytics. In his years of consulting, Scott has amassed an impressive list of clientele, from mid-market leaders to Fortune 500 household names. In addition to Hadoop Blueprints, he has also served as technical reviewer for other Packt Publishing books on big data and has authored the instructional videos Learning Hadoop 2 and Mastering Hadoop. Scott lives just outside Atlanta, GA, with his children. You can visit his blog at http://www.randalscottking.com.

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