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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)

Indexing your data

Document are indexed using the index API. We can index a new person document into the chapter4 index as shown here:

 PUT chapter4/person/1
{
"id": 1,
"name": "user1",
"age": "55",
"gender": "M",
"email": "user1@gmail.com",
"last_modified_date": "2017-02-15"
}

The document we just indexed is uniquely identified by the index, type and identifier. You can either specify your identifier or let Elasticsearch pick one for you. If you want to specify an identifier, you have to use the PUT HTTP method. If you use the POST HTTP method, a unique identifier is automatically assigned to the document. The response to the preceding command is shown as follows:

 {
"_index": "chapter4",
"_type": "person",
&quot...
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