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Practical Real-time Data Processing and Analytics

You're reading from Practical Real-time Data Processing and Analytics

Product type Book

Published in Sep 2017

Publisher Packt

ISBN-13 9781787281202

Pages 360 pages

Edition 1st Edition

Languages

Concepts

Table of Contents (20) Chapters

Title Page

Credits

About the Authors

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Introducing Real-Time Analytics

2. Real Time Applications – The Basic Ingredients

3. Understanding and Tailing Data Streams

4. Setting up the Infrastructure for Storm

5. Configuring Apache Spark and Flink

6. Integrating Storm with a Data Source

7. From Storm to Sink

8. Storm Trident

9. Working with Spark

10. Working with Spark Operations

11. Spark Streaming

12. Working with Apache Flink

13. Case Study

Introduction

We will discuss and implement a Geofencing use case as a case study. Geofencing is the use of the Global Positioning System (GPS) satellite network and/or local radio-frequency identifiers (such as WiFi nodes or Bluetooth beacons) to create virtual boundaries around a location. Geofencing is paired with software/hardware to detect the virtual boundary and take the appropriate action defined by the user. Most of the Geofencing use cases are solved with IOT. Real-time use cases based on Geofencing are:

Suppose your children took your car to buy goods from the market and you don't want them to go beyond 5 KM/Miles from your home or you want to know your kids/other family member's location on a map to track them
When you have put your car in for servicing and you want it not to go beyond 1 KM/Miles from the car service center
When you are approaching home, the garage gate opens automatically without having to get out of the car and manually open it by pushing/pulling it
When you are...

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