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ElasticSearch Blueprints

You're reading from  ElasticSearch Blueprints

Product type Book
Published in Jul 2015
Publisher Packt
ISBN-13 9781783984923
Pages 192 pages
Edition 1st Edition
Languages

Table of Contents (15) Chapters

Elasticsearch Blueprints
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Google-like Web Search Building Your Own E-Commerce Solution Relevancy and Scoring Managing Relational Content Analytics Using Elasticsearch Improving the Search Experience Spicing Up a Search Using Geo Handling Time-based Data Index

Restaurant categorization based on distance


In an e-commerce solution, to search restaurants, it's required that you increase the searchable characteristics of the application. This means that if we are able to give a snapshot of results other than the top-10 results, it would add to the searchable characteristics of the search. For example, if we are able to show how many restaurants serve Indian, Thai, or other cuisines, it would actually help the user to get a better idea of the result set.

In a similar manner, if we can tell them if the restaurant is near, at a medium distance, or far away, we can really pull a chord in the restaurant search user experience, as shown in the following map:

Implementing this is not hard, as we have something called the distance range aggregation. In this aggregation type, we can handcraft the range of distance we are interested in and create a bucket for each of them. We can also define the key name we need, as shown in the following code:

curl -XPOST 'http...
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