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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

Bucket aggregations

Bucket aggregations are useful to analyze how the whole relates to its parts, so that we can gain better insight on the data. They help in segmenting the data into smaller parts. Each type of bucket aggregation slices the data into different segments, or buckets. Bucket aggregations are the most common type of aggregation used in any analysis process.

In this section, we will cover the following topics, keeping the network traffic data example at the center:

  • Bucketing on string data
  • Bucketing on numerical data
  • Aggregating filtered data
  • Nesting aggregations
  • Bucketing on custom conditions
  • Bucketing on date/time data
  • Bucketing on geospatial data

Bucketing on string data

Sometimes, we may need to bucket the...

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