Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • ElasticSearch Cookbook
  • Toc
  • feedback
ElasticSearch Cookbook

ElasticSearch Cookbook

By : Alberto Paro
4.1 (7)
close
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)
close
13
Index

Executing a facet search

Searching for results is obviously the main activity of a search engine, thus facet is very important because it often helps to complete the results.

Faceting is executed along the search doing analytics on searched results.

Getting ready

You need a working ElasticSearch cluster and required packages of the Creating a client recipe of this chapter.

The code of this recipe is in the chapter_11/faceting.py and chapter_11/faceting_pyes.py files.

How to do it...

To extend a query with the facet part, you need to define a facet section as we have already seen in Chapter 6, Facets. In the case of the official ElasticSearch client, you can add the facet DSL to the search dictionary to provide facets. We need to perform the following steps:

  1. We need to initialize the client and populate the index as follows:
    import elasticsearch
    from pprint import pprint
    
    es = elasticsearch.Elasticsearch()
    index_name = "my_index"
    type_name = "my_type"
    
    from utils import create_and_add_mapping...
bookmark search playlist font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete