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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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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)

Graph

In this section, we will discuss Graph, which is part of the X-Pack Gold and Platinum subscription. Graph lets you discover and analyze relationships in your data. It works on your existing indexes and doesn't require any special configuration. The Graph has two components:

  • The functionality required for Elasticsearch to compute the Graph.
  • The UI in Kibana to visualize the graphical representation.

To better explain the functionality of Graph, let's build a recommendation system for an online store. We want to know the relations between items frequently bought together and use that information to make suggestions to the users. This information can be very valuable. For example, in a physical store, items frequently bought together can be placed adjacent to each other. We can also use this information to give the user a coupon or e-mail the user about various...

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