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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 relationships

We saw in the previous sections how to model and store products and run various queries on products. The product data had partly structured data and partly textual data. What if we also had detailed features of the products available to us? We may have many different types of products and each product may have completely different types of detailed features. For example, for products that fall into the Laptops category, we would have features such as screen size, processor type, and processor clock speed.

At the same time, products in the Automobile GPS Systems category may have features such as screen size, whether GPS can speak street names, or whether it has free lifetime map updates available.

Because we may have tens of thousands of products in hundreds of product categories, we may have tens of thousands of features. One solution might be to create...

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