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Learning Elasticsearch

You're reading from   Learning Elasticsearch Structured and unstructured data using distributed real-time search and analytics

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787128453
Length 404 pages
Edition 1st Edition
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Author (1):
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Abhishek Andhavarapu Abhishek Andhavarapu
Author Profile Icon Abhishek Andhavarapu
Abhishek Andhavarapu
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Elasticsearch FREE CHAPTER 2. Setting Up Elasticsearch and Kibana 3. Modeling Your Data and Document Relations 4. Indexing and Updating Your Data 5. Organizing Your Data and Bulk Data Ingestion 6. All About Search 7. More Than a Search Engine (Geofilters, Autocomplete, and More) 8. How to Slice and Dice Your Data Using Aggregations 9. Production and Beyond 10. Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

Mapping the same field with different mappings

Sometimes you want to index the same field with different mappings. For example, you want to index the title field both as text and as keyword. You can use the keyword field for an exact match and the text field for text search. You can do this by defining two fields, one with keyword mapping and other with text mapping, as shown next:

{
"properties": {
"title_text": {
"type": "text"
},
"title_keyword": {
"type": "keyword"
}
}
}

You can index the document as follows:

{
"title_text" : "Learning Elasticsearch",
"title_keyword" : "Learning Elasticsearch"
}

While indexing, the same value is used for both the title_text and title_keyword fields. The document source will now have two fields with...

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