Book Image

Mastering Elasticsearch 5.x - Third Edition

By : Bharvi Dixit
Book Image

Mastering Elasticsearch 5.x - Third Edition

By: Bharvi Dixit

Overview of this book

Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. Elasticsearch leverages the capabilities of Apache Lucene, and provides a new level of control over how you can index and search even huge sets of data. This book will give you a brief recap of the basics and also introduce you to the new features of Elasticsearch 5. We will guide you through the intermediate and advanced functionalities of Elasticsearch, such as querying, indexing, searching, and modifying data. We’ll also explore advanced concepts, including aggregation, index control, sharding, replication, and clustering. We’ll show you the modules of monitoring and administration available in Elasticsearch, and will also cover backup and recovery. You will get an understanding of how you can scale your Elasticsearch cluster to contextualize it and improve its performance. We’ll also show you how you can create your own analysis plugin in Elasticsearch. By the end of the book, you will have all the knowledge necessary to master Elasticsearch and put it to efficient use.
Table of Contents (20 chapters)
Mastering Elasticsearch 5.x - Third Edition
About the Author
About the Reviewer
Customer Feedback

Controlling scores using the function score query

In most cases, you are good to go with the default scoring algorithms of Elasticsearch to return the most relevant results. However, some cases require you to have more control over the calculation of a score. This is especially required while implementing domain-specific logics where you need to implement a very specific scoring formula and alter the final score. Elasticsearch provides you with the function_score query to take control of all these things.

The function_score query allows you to take complete control of how a score needs to be calculated for a particular query. The syntax of the function_score query is given as follows:

  "query": {"function_score": { 
    "query": {}, 
    "boost": "boost for the whole query", 
    "functions": [ 
    "max_boost": number, 
    "score_mode": "(multiply|max|...)", 
    "boost_mode": "(multiply|replace|...)", 
    "min_score" : number 

The function_score query has...