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Learning Elastic Stack 7.0

You're reading from   Learning Elastic Stack 7.0 Distributed search, analytics, and visualization using Elasticsearch, Logstash, Beats, and Kibana

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789954395
Length 474 pages
Edition 2nd Edition
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Authors (2):
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Sharath Kumar Sharath Kumar
Author Profile Icon Sharath Kumar
Sharath Kumar
Pranav Shukla Pranav Shukla
Author Profile Icon Pranav Shukla
Pranav Shukla
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Introduction to Elastic Stack and Elasticsearch
2. Introducing Elastic Stack FREE CHAPTER 3. Getting Started with Elasticsearch 4. Section 2: Analytics and Visualizing Data
5. Searching - What is Relevant 6. Analytics with Elasticsearch 7. Analyzing Log Data 8. Building Data Pipelines with Logstash 9. Visualizing Data with Kibana 10. Section 3: Elastic Stack Extensions
11. Elastic X-Pack 12. Section 4: Production and Server Infrastructure
13. Running Elastic Stack in Production 14. Building a Sensor Data Analytics Application 15. Monitoring Server Infrastructure 16. Other Books You May Enjoy

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 9, Running the Elastic Stack in Production, to model the data:

  • Defining an index template
  • Understanding the mapping

Let's 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 Modeling time series data section in Chapter 9, Running the Elastic Stack in Production.

The source code of...

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