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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

Creating an index


The first operation to do before starting indexing data in ElasticSearch is to create an index: the main container of our data.

An index is similar to the concept of a database in SQL.

Getting ready

You need a working ElasticSearch cluster.

How to do it...

The HTTP method to create an index is PUT (but POST also works), the REST URL is the index name, which is written as follows:

http://<server>/<index_name>

For creating an index, we need to perform the following steps:

  1. From command line, we can execute a PUT call as follows:

    curl -XPUT http://127.0.0.1:9200/myindex -d '{
        "settings" : {
            "index" : {
                "number_of_shards" : 2,
                "number_of_replicas" : 1
            }
        }
    }'
    
  2. The result returned by ElasticSearch, if everything is all right, should be as follows:

    {"ok":true,"acknowledged":true}
  3. If the index already exists, a 400 error is returned:

    {"error":"IndexAlreadyExistsException[[myindex] Already exists]","status":400}

How it works...

There...

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