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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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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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Table of Contents (12) Chapters Close

Preface 1. Introducing Elastic Stack 2. Getting Started with Elasticsearch FREE CHAPTER 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

Searching from full text

Full-text queries can work on unstructured text fields. These queries are aware of the analysis process. Full-text queries apply the analyzer on the search terms before performing the actual search operation. It finds out the right analyzer to be applied by first checking if a field-level search_analyzer is defined, and then by checking if a field-level analyzer is defined. If analyzers at field level are not defined, it tries the analyzer defined at the index level.

The full-text queries are thus aware of the analysis process on the underlying field and apply the right analysis process before forming the actual search queries. These analysis-aware queries are also called high-level queries. Let us understand how the high-level query flow works.

Here, we can see how one high-level query on the field...

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