Book Image

ElasticSearch Cookbook

By : Alberto Paro
Book Image

ElasticSearch Cookbook

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 (19 chapters)
ElasticSearch Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Counting


It is often required to return only the count of the matched results and not the results themselves.

There are a lot of scenarios involving counting, some of them are as follows:

  • To return a number (for example, how many posts for a blog, how many comments for a post)

  • Validating if some items are available: are there posts? are there comments?

Getting ready

You need a working ElasticSearch cluster and an index populated with the script available in online code.

How to do it...

For executing a counting query, we need to perform the following steps:

  1. From command line, we will execute the following count query:

    curl -XGET 'http://127.0.0.1:9200/test-index/test-type/_count' -d '{"match_all":{}}'
    
  2. The result returned by ElasticSearch, if everything is all right, should be as follows:

    {
      "count" : 3,
      "_shards" : {
        "total" : 5,
        "successful" : 5,
        "failed" : 0
      }
    }

The result is composed by the count result (a long type) and the shards status at the time of the query.

How it works.....