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Elasticsearch Essentials

Elasticsearch Essentials

By : Bharvi Dixit
4.3 (6)
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Elasticsearch Essentials

Elasticsearch Essentials

4.3 (6)
By: Bharvi Dixit

Overview of this book

With constantly evolving and growing datasets, organizations have the need to find actionable insights for their business. ElasticSearch, which is the world's most advanced search and analytics engine, brings the ability to make massive amounts of data usable in a matter of milliseconds. It not only gives you the power to build blazing fast search solutions over a massive amount of data, but can also serve as a NoSQL data store. This guide will take you on a tour to become a competent developer quickly with a solid knowledge level and understanding of the ElasticSearch core concepts. Starting from the beginning, this book will cover these core concepts, setting up ElasticSearch and various plugins, working with analyzers, and creating mappings. This book provides complete coverage of working with ElasticSearch using Python and performing CRUD operations and aggregation-based analytics, handling document relationships in the NoSQL world, working with geospatial data, and taking data backups. Finally, we’ll show you how to set up and scale ElasticSearch clusters in production environments as well as providing some best practices.
Table of Contents (12 chapters)
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11
Index

Introducing relevant searches


Relevancy is the root of a search engine's value proposition and can be defined as the art of ranking content for a user's search based on how much that content satisfies the needs of the user or the business.

In an application, it does not matter how beautiful your user interface looks or how many functionalities you are providing to the user; search relevancy cannot be avoided at any cost. So, despite of the mystical behavior of search engines, you have to find a solution to get relevant results. The relevancy becomes more important because a user does not care about the whole bunch of documents that you have. The user enters their keywords, selects filters, and focuses on a very small amount of data—the relevant results. And if your search engine fails to deliver according to expectations, the user might be annoyed, which might be a loss for your business.

A search engine like Elasticsearch comes with a built-in intelligence. You enter the keyword and within...

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