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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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Toc

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 arrays


An array or a multivalue field is very common in data models (such as multiple phone numbers, addresses, names, aliases, and so on), but it is not natively supported in traditional SQL solutions.

In SQL, multivalue fields require the creation of accessory tables that must be joined in order to gather all the values, leading to poor performance when the cardinality of records is huge.

ElasticSearch, which works natively in JSON, provides support for multivalue fields transparently.

Getting ready

You need a working ElasticSearch cluster.

How to do it...

Every field is automatically managed as an array. For example, in order to store tags for a document, this is how the mapping must be:

{
  "document" : {
    "properties" : {
      "name" : {"type" : "string",  "index":"analyzed"},"tag" : {"type" : "string", "store" : "yes" , "index":"not_analyzed"},…
…
    }
  }
}

This mapping is valid for indexing this document:

{"name": "document1", "tag": "awesome"}

It can also be used for the following...

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