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Learning Elastic Stack 6.0

You're reading from   Learning Elastic Stack 6.0 A beginner's guide to distributed search, analytics, and visualization using Elasticsearch, Logstash and Kibana

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781787281868
Length 434 pages
Edition 1st Edition
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Authors (2):
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Pranav Shukla Pranav Shukla
Author Profile Icon Pranav Shukla
Pranav Shukla
Sharath Kumar Sharath Kumar
Author Profile Icon Sharath Kumar
Sharath Kumar
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Toc

Table of Contents (19) Chapters Close

Title Page
Credits
Disclaimer
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Introducing Elastic Stack FREE CHAPTER 2. Getting Started with Elasticsearch 3. Searching-What is Relevant 4. Analytics with Elasticsearch 5. Analyzing Log Data 6. Building Data Pipelines with Logstash 7. Visualizing data with Kibana 8. Elastic X-Pack 9. Running Elastic Stack in Production 10. Building a Sensor Data Analytics Application 11. Monitoring Server Infrastructure

Modeling data in Elasticsearch


We have seen the structure of the final record after enriching the data. That should help us model the data in Elasticsearch. Given that our data is time series data, we can apply some of the techniques mentioned in Chapter 9Running Elastic Stack in Production, to model the data:

  • Defining an index template
  • Understanding the mapping

Let us look at the index template that we will define.

Defining an index template

Since we are going to be storing time series data that is immutable, we do not want to create one big monolithic index. We'll use the techniques discussed in the section Modeling time series data in Chapter 9, Running Elastic Stack in Production.

The source code of the application in this chapter is within the GitHub repository at https://github.com/pranav-shukla/learningelasticstack/tree/master/chapter-10. As we go through the chapter, we will perform the steps mentioned in the README.md file located at that path.

Please create the index template mentioned...

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