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Mastering Elasticsearch 5.x

You're reading from   Mastering Elasticsearch 5.x Master the intricacies of Elasticsearch 5 and use it to create flexible and scalable search solutions

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786460189
Length 428 pages
Edition 3rd Edition
Languages
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Author (1):
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Bharvi Dixit Bharvi Dixit
Author Profile Icon Bharvi Dixit
Bharvi Dixit
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Table of Contents (13) Chapters Close

Preface 1. Revisiting Elasticsearch and the Changes FREE CHAPTER 2. The Improved Query DSL 3. Beyond Full Text Search 4. Data Modeling and Analytics 5. Improving the User Search Experience 6. The Index Distribution Architecture 7. Low-Level Index Control 8. Elasticsearch Administration 9. Data Transformation and Federated Search 10. Improving Performance 11. Developing Elasticsearch Plugins 12. Introducing Elastic Stack 5.0

Implementing your own auto-completion


Completion suggester does have limitations..!!

The completion suggester has been designed to be a powerful and easily implemented solution for autocompletion but it supports only prefix queries, as we have seen in the previous section. Most of the time, autocomplete needs only to work as a prefix query, for example, if I type elastic, then I expect elasticsearch as a suggestion, but not nonelastic.

There are some use cases when one wants to implement more general, partial word completion. The completion suggester fails to fulfill this requirement.

The second limitation of the completion suggester is it does not allow advance queries and filters searched.

To get rid of both these limitations, we are going to implement a custom auto-complete feature based on n-grams, which works in almost all the scenarios.

Creating an index

Let's create an index, location-suggestion with the following settings and mappings:

curl -XPUT "http://localhost:9200/location-suggestion...
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