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ElasticSearch Cookbook - Second Edition

You're reading from   ElasticSearch Cookbook - Second Edition Over 130 advanced recipes to search, analyze, deploy, manage, and monitor data effectively with ElasticSearch

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783554836
Length 472 pages
Edition 2nd 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 (14) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Downloading and Setting Up 3. Managing Mapping 4. Basic Operations 5. Search, Queries, and Filters 6. Aggregations 7. Scripting 8. Rivers 9. Cluster and Node Monitoring 10. Java Integration 11. Python Integration 12. Plugin Development Index

Mapping base types


Using explicit mapping allows you to be faster when you start inserting data using a schema-less approach, without being concerned about the field types. Therefore, in order to achieve better results and performance when indexing, it's necessary to manually define a mapping.

Fine-tuning the mapping has some advantages, as follows:

  • Reduces the size of the index on disk (disabling functionalities for custom fields)

  • Indexes only interesting fields (a general boost to performance)

  • Precooks data for a fast search or real-time analytics (such as aggregations)

  • Correctly defines whether a field must be analyzed in multiple tokens or whether it should be considered as a single token

ElasticSearch also allows you to use base fields with a wide range of configurations.

Getting ready

You need a working ElasticSearch cluster and an index named test (refer to the Creating an index recipe in Chapter 4, Basic Operations) where you can put the mappings.

How to do it...

Let's use a semi-real-world...

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