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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

NRT – high-level system view

The previous section of this chapter is dedicated to providing you with an understanding of the basic building blocks of an NRT application and its logical overview. The next step is to understand the functional and systems view of the NRT architectural framework. The following figure clearly outlines the various architectural blocks and cross cutting concerns:

So, if I get to describe the system as a horizontal scale from left to right, the process starts with data ingestion and transformation in near real-time using low-latency components. The transformed data is passed on to the next logical unit that actually performs highly optimized and parallel operations on the data; this unit is actually the near real-time processing engine. Once the data has been aggregated and correlated and actionable insights have been derived, it is passed on to the presenting layer, which along with real-time dash boarding and visualization, may have a persistence component that...

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