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Learning Elasticsearch

You're reading from   Learning Elasticsearch Structured and unstructured data using distributed real-time search and analytics

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787128453
Length 404 pages
Edition 1st Edition
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Author (1):
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Abhishek Andhavarapu Abhishek Andhavarapu
Author Profile Icon Abhishek Andhavarapu
Abhishek Andhavarapu
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Elasticsearch FREE CHAPTER 2. Setting Up Elasticsearch and Kibana 3. Modeling Your Data and Document Relations 4. Indexing and Updating Your Data 5. Organizing Your Data and Bulk Data Ingestion 6. All About Search 7. More Than a Search Engine (Geofilters, Autocomplete, and More) 8. How to Slice and Dice Your Data Using Aggregations 9. Production and Beyond 10. Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

How to Slice and Dice Your Data Using Aggregations

In this chapter, you’ll learn how to unleash the analytics power of Elasticsearch. In Elasticsearch 5.0, the aggregation framework has been completely revamped. The query syntax is very simple and easy to understand. The distributed nature of Elasticsearch makes the queries very performant and can easily scale to large datasets. We will go through the different types of aggregations Elasticsearch supports and how easy it is to run these queries. We will discuss how to use Kibana to visualize the data. You will also learn doc values and field data, the internal data structures used to power aggregations.

By the end of this chapter, we will cover the following:

  • Different types of aggregations
  • Child aggregations
  • Aggregation on nested documents
  • Aggregation on geolocations
  • Doc values
  • Memory considerations
  • Data...
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