Book Image

Elasticsearch Essentials

Book Image

Elasticsearch Essentials

Overview of this book

With constantly evolving and growing datasets, organizations have the need to find actionable insights for their business. ElasticSearch, which is the world's most advanced search and analytics engine, brings the ability to make massive amounts of data usable in a matter of milliseconds. It not only gives you the power to build blazing fast search solutions over a massive amount of data, but can also serve as a NoSQL data store. This guide will take you on a tour to become a competent developer quickly with a solid knowledge level and understanding of the ElasticSearch core concepts. Starting from the beginning, this book will cover these core concepts, setting up ElasticSearch and various plugins, working with analyzers, and creating mappings. This book provides complete coverage of working with ElasticSearch using Python and performing CRUD operations and aggregation-based analytics, handling document relationships in the NoSQL world, working with geospatial data, and taking data backups. Finally, we’ll show you how to set up and scale ElasticSearch clusters in production environments as well as providing some best practices.
Table of Contents (18 chapters)
Elasticsearch Essentials
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Index

Sorting your data


Data in Elasticsearch is by default sorted by a relevance score, which is computed using the Lucene scoring formula, TF/IDF. This relevance score is a floating point value that is returned with search results inside the _score parameter. By default, results are sorted in descending order.

Note

Sorting on nested and geo-points fields will be covered in the upcoming chapters.

See the following query for an example:

{
  "query": {
    "match": {
      "text": "data analytics"
    }
  }
}

We are searching for tweets that contain the data or analytics terms in their text fields. In some cases, however, we do not want the results to be sorted based on _score. Elasticsearch provides a way to sort documents in various ways. Let's explore how this can be done.

Sorting documents by field values

This section covers the sorting of documents based on the fields that contain a single value such as created_at, or followers_count. Please note that we are not talking about sorting string-based...