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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

Integrating the presentation layer with Storm

Visualization over data is adding power to know your data in the best way and also you can take key decisions based on those. There are numerous tools available on the market for visualization. Every visualization tool needs a database to store and process the data. Some combinations are Grafana over Elasticseach, Kibana over Elasticsearch,and Grafana over Influxdb. In this chapter, we will discuss the fusion of Grafana, Elasticsearch, and Storm.

In this example, we will use the data stream from PubNub, which provides real-time sensor data. PubNub provides all types of APIs to read data from the channel. Here, a program is required to get the values from the PubNub subscribed channel and push it into a Kafka topic. You will the find program in the code bundle.

Setting up Grafana with the Elasticsearch plugin

Grafana is analytics platform which understands your data and visualizes it on a dashboard.

Downloading Grafana

Download Grafana from https:...

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