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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 FREE CHAPTER 2. Getting Started with Elasticsearch 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 structured data

In certain situations, we want to find out whether the given document should be included or not; that is, a simple binary answer. On the other hand, there are other types of queries which are relevance-based. Such relevance-based queries also return a score against each document to say how well that document fits the query. Most structured queries do not need relevance-based scoring, and the answer is a simple yes/no for any item to be included or excluded from the result. These structured search queries are also referred to as term level queries.

Let us understand the flow of a term-level query's execution:

Fig-3.2 Term level query flow

As you can see, the figure is divided into two parts. The left half of the figure depicts what happens at the time of indexing, and the right half of the figure depicts what happens at query time...

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