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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

Query rescoring


One of the great features provided by Elasticsearch is the ability to change the ordering of documents after they are returned by a query. Actually, Elasticsearch does a simple trick-it recalculates the score of top matching documents, so only part of the document in the response is reordered. The reasons why we want to do this can vary. One of the reasons may be performance. For example, calculating target ordering is very costly because scripts are used and we would like to do this on the subset of documents returned by the original query. You can imagine that rescore gives us many great opportunities for business use cases. Now, let's look at this functionality and how we can benefit from using it.

What is query rescoring?

Rescoring in Elasticsearch is the process of recalculating the score for a defined number of documents returned by the query. This means that Elasticsearch first takes N documents for a given query (or the post_filter phase) and calculates their score...

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