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

Summary


We have covered lots of important topics in this chapter. We first started with how to work with different type of multimatch queries under different scenarios, then we started to learn about custom scoring in Elasticsearch using the function score, and also learned about query rescoring for recalculating the score on a defined number of documents returned by the query. We finally discussed one of the most important modules of Elasticsearch, that is scripting, and learned how to work with the new default scripting language: Painless.

In the next chapter, we will see different approaches to the data modeling in Elasticsearch and will learn how to handle relationships among documents using parent-child and nested data types, along with focusing on practical considerations.