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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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Pranav Shukla Pranav Shukla
Author Profile Icon Pranav Shukla
Pranav Shukla
Sharath Kumar Sharath Kumar
Author Profile Icon Sharath Kumar
Sharath Kumar
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Toc

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

The basics of aggregations

In contrast to search, analytics deals with the bigger picture. Searching addresses the need for zooming in to a few records; analytics addresses the need for zooming out and slicing the data in different ways. While learning about searching, we used the API of the following form:

POST /<index_name>/<type_name>/_search
{
"query":
{
... type of query ...
}
}

All aggregation queries take a common form. Let us understand the structure.

The aggregations or aggs element allows us to aggregate data. All aggregation requests take the following form:

POST /<index_name>/<type_name>/_search
{
"aggs": {
... type of aggregation ...
},
"query": { ... type of query ... }, //optional query part
"size": 0 ...
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