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Elasticsearch Essentials

You're reading from  Elasticsearch Essentials

Product type Book
Published in Jan 2016
Publisher
ISBN-13 9781784391010
Pages 240 pages
Edition 1st Edition
Languages

Table of Contents (18) Chapters

Elasticsearch Essentials
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Getting Started with Elasticsearch Understanding Document Analysis and Creating Mappings Putting Elasticsearch into Action Aggregations for Analytics Data Looks Better on Maps: Master Geo-Spatiality Document Relationships in NoSQL World Different Methods of Search and Bulk Operations Controlling Relevancy Cluster Scaling in Production Deployments Backups and Security Index

Text search


Searching is broadly divided into two types: exact term search and full text search. An exact term search is something in which we look out for the exact terms; for example, any named entity such as the name of a person, location, or organization or date. These searches are easier to make since the search engine simply looks out for a yes or no and returns the documents.

However, full text search is different as well as challenging. Full text search refers to the search within text fields, where the text can be unstructured as well as structured. The text data can be in the form of any human language and based on the natural languages, which are very hard for a machine to understand and give relevant results. The following are some examples of full text searches:

  • Find all the documents with search in the title or content fields, and return the results with matches in titles with the higher score

  • Find all the tweets in which people are talking about terrorism and killing and return...

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