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

Chapter 5.  Improving the User Search Experience

In the previous chapter, we extended our knowledge with different approaches to data modeling, and discussed how relational data can be managed using nested and parent-child data types. We also talked about the aggregation module of Elasticsearch for data analytics purposes, including the concept of instant aggregations introduced in Elasticsearch 5.0, along with all four categories of aggregations, for instance, metric, bucket, pipeline, and the latest matrix aggregation available in Elasticsearch. In this chapter, we will focus on the topics for improving the user search experience using suggesters, which allow you to correct user query spelling mistakes and build efficient autocomplete mechanisms. In addition to that, we'll also cover how to implement synonym search in the applications. By the end of this chapter, we will have covered the following topics:

  • Using the Elasticsearch suggesters to correct user spelling mistakes

  • Using the term...