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Mastering Elasticsearch 5.x

Mastering Elasticsearch 5.x

By : Bharvi Dixit
1 (1)
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Mastering Elasticsearch 5.x

Mastering Elasticsearch 5.x

1 (1)
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 (13 chapters)
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Preface

Welcome to the world of Elasticsearch and Mastering Elasticsearch 5.x, Third Edition. While reading the book, you'll be taken through different topics—all connected to Elasticsearch. Please remember though that this book is not meant for beginners, and we really treat the book as a follow-up to Mastering Elasticsearch 5.x, Second Edition, which was based on Elasticsearch version 1.4.x. There is a lot of new content in the book since Elasticsearch has gone through many changes between versions 1.x and 5.x.

Throughout the book, we will discuss different topics related to Elasticsearch and Lucene. We start with an introduction to the world of Lucene and Elasticsearch to introduce you to the world of queries provided by Elasticsearch, where we discuss different topics related to queries, such as filtering and which query to choose in a particular situation. Of course, querying is not everything, and because of that, the book you are holding in your hands provides information on newly introduced aggregations and features that will help you give meaning to the data you have indexed in Elasticsearch indices and provide a better search experience for your users.

We have also decided to cover the approaches of data modeling and handling relational data in Elasticsearch along with taking you through the scripting module of Elasticsearch and show some examples of using the latest default scripting language, Painless.

Even though, for most users, querying and data analysis are the most interesting parts of Elasticsearch, they are not all that we need to discuss. Because of this, the book tries to bring you additional information when it comes to index architecture, such as choosing the right number of shards and replicas, adjusting the shard allocation behavior, and so on. We will also get into places where Elasticsearch meets Lucene, and we will discuss topics such as different scoring algorithms, choosing the right store mechanism, what the differences between them are, and why choosing the proper one matters.

Last but not least, we touch on the administration part of Elasticsearch by discussing discovery and recovery modules and the human-friendly cat API, which allows us to very quickly get relevant administrative information in a form that most humans should be able to read without parsing JSON responses. We also talk about ingest nodes, which allow you to preprocess data within Elasticsearch before indexing takes place and use tribe nodes, giving the ability to create federated searches across many nodes.

Because of the title of the book, we couldn't omit performance-related topics, and we decided to dedicate a whole chapter to it.

Just as with the second edition of the book, we decided to include a chapter dedicated to development of Elasticsearch plugins, showing you how to set up the Apache Maven project and develop two types of plugins—custom REST action and custom analysis.

At the end, we have included one chapter discussing the components of the complete Elastic Stack, and you should get a great overview of how to start with tools such as Logstash, Kibana, and Beats after reading the chapter.

If you think that you are interested in these topics after reading about them, we think this is a book for you, and hopefully, you will like the book after reading the last words of the summary in Chapter 12, Introducing Elastic Stack 5.0.

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