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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 FREE CHAPTER
2. Introducing Elastic Stack 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

Summary

In this chapter, you learned how to use Elasticsearch to build powerful analytics applications. We covered how to slice and dice the data to get powerful insight. We started with metric aggregation and dealt with numerical datatypes. We then covered bucket aggregation in order to find out how to slice the data into buckets or segments, in order to drill down into specific segments.

We also went over how pipeline aggregations work. We did all of this while dealing with a real-world-like dataset of network traffic data. We illustrated how flexible Elasticsearch is as an analytics engine. Without much additional data modeling and extra effort, we can analyze any field, even when the data is on a big data scale. This is a rare capability that's not offered by many data stores. As you will see in Chapter 7, Visualizing Data with Kibana, Kibana leverages many of the aggregations...

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