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ElasticSearch Cookbook

ElasticSearch Cookbook

By : Alberto Paro
4.1 (7)
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ElasticSearch Cookbook

ElasticSearch Cookbook

4.1 (7)
By: Alberto Paro

Overview of this book

ElasticSearch is one of the most promising NoSQL technologies available and is built to provide a scalable search solution with built-in support for near real-time search and multi-tenancy. This practical guide is a complete reference for using ElasticSearch and covers 360 degrees of the ElasticSearch ecosystem. We will get started by showing you how to choose the correct transport layer, communicate with the server, and create custom internal actions for boosting tailored needs. Starting with the basics of the ElasticSearch architecture and how to efficiently index, search, and execute analytics on it, you will learn how to extend ElasticSearch by scripting and monitoring its behaviour. Step-by-step, this book will help you to improve your ability to manage data in indexing with more tailored mappings, along with searching and executing analytics with facets. The topics explored in the book also cover how to integrate ElasticSearch with Python and Java applications. This comprehensive guide will allow you to master storing, searching, and analyzing data with ElasticSearch.
Table of Contents (14 chapters)
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13
Index

Using explicit mapping creation


If we consider the index as a database in the SQL world, the mapping is similar to the table definition.

Getting ready

You need a working ElasticSearch cluster, a test index (refer to the Creating an index recipe in Chapter 4, Standard Operations), and basic knowledge of JSON.

How to do it...

For explicit mapping creation, we will perform the following steps:

  1. You can explicitly create a mapping by adding a new element in ElasticSearch.

    On bash:

    #create an index
    curl -XPUT http://127.0.0.1:9200/test
    #{"ok":true,"acknowledged":true}
    
    #put a record
    curl -XPUT http://127.0.0.1:9200/test/mytype/1 -d '{"name":"Paul", "age":35}'
    # {"ok":true,"_index":"test","_type":"mytype","_id":"1","_version":1}
    
    #get the mapping and pretty print it
    curl –XGET http://127.0.0.1:9200/test/mytype/_mapping?pretty=true
    
  2. The result mapping auto-created by ElasticSearch should be as follows:

    {
      "mytype" : {
        "properties" : {
          "age" : {
            "type" : "long"
          },
          "name" :...
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