Book Image

Mastering Elasticsearch 5.x - Third Edition

Book Image

Mastering Elasticsearch 5.x - Third Edition

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
Credits
About the Author
Acknowledgements
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Altering Apache Lucene scoring


In Chapter 2, The Improved Query DSL, we discussed the changes in default scoring inside Elasticsearch as well as Apache Lucene. We also covered the new default text scoring algorithm, BM25, in detail. But apart from BM25 and TF-IDF, there are some additional similarity models available in Lucene since the release of Apache Lucene 4.0 in 2012, which basically allows you to alter the default algorithm and also to choose a different scoring formula for our documents. In this section, we will take a deeper look at these similarity scoring algorithms offered by Lucene and how these features were incorporated into Elasticsearch.