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Elasticsearch 7.0 Cookbook

You're reading from   Elasticsearch 7.0 Cookbook Over 100 recipes for fast, scalable, and reliable search for your enterprise

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789956504
Length 724 pages
Edition 4th Edition
Languages
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Author (1):
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Alberto Paro Alberto Paro
Author Profile Icon Alberto Paro
Alberto Paro
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Table of Contents (19) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Managing Mapping 3. Basic Operations 4. Exploring Search Capabilities 5. Text and Numeric Queries 6. Relationship and Geo Queries 7. Aggregations 8. Scripting in Elasticsearch 9. Managing Clusters 10. Backups and Restoring Data 11. User Interfaces 12. Using the Ingest Module 13. Java Integration 14. Scala Integration 15. Python Integration 16. Plugin Development 17. Big Data Integration 18. Another Book You May Enjoy

Mapping feature and feature vector fields

It's common to have the requirement to score a document dynamically, depending on the context. For example, scoring more particular documents that are inside a category—the classic scenario is to boost (increase low scored) documents that are based on value such as page rank, hits, or categories.

Elasticsearch 7.x provides two new ways to boost your scores based on values: one is the feature fields and the other is its extension to a vector of values.

Getting ready

You need an up-and-running Elasticsearch installation, as we described in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started.

To execute these commands, any HTTP client...

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