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Elasticsearch 8.x Cookbook

Elasticsearch 8.x Cookbook

By : Alberto Paro
4 (6)
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Elasticsearch 8.x Cookbook

Elasticsearch 8.x Cookbook

4 (6)
By: Alberto Paro

Overview of this book

Elasticsearch is a Lucene-based distributed search engine at the heart of the Elastic Stack that allows you to index and search unstructured content with petabytes of data. With this updated fifth edition, you'll cover comprehensive recipes relating to what's new in Elasticsearch 8.x and see how to create and run complex queries and analytics. The recipes will guide you through performing index mapping, aggregation, working with queries, and scripting using Elasticsearch. You'll focus on numerous solutions and quick techniques for performing both common and uncommon tasks such as deploying Elasticsearch nodes, using the ingest module, working with X-Pack, and creating different visualizations. As you advance, you'll learn how to manage various clusters, restore data, and install Kibana to monitor a cluster and extend it using a variety of plugins. Furthermore, you'll understand how to integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch and create efficient data applications powered by enhanced functionalities and custom plugins. By the end of this Elasticsearch cookbook, you'll have gained in-depth knowledge of implementing the Elasticsearch architecture and be able to manage, search, and store data efficiently and effectively using Elasticsearch.
Table of Contents (20 chapters)
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Preface

Welcome to the fifth edition of Elasticsearch Cookbook targeting Elasticsearch 8.x. It's a long journey (about 12 years) that I have been on with both Elasticsearch and readers of my books. Every version of Elasticsearch brings breaking changes and new functionalities, and the evolution of already present components is a continuous cycle of product and marketing evolution.

Elasticsearch, once a very niche product, is now one of the most used databases in the world (ranked seventh in April 2022 – source: https://db-engines.com/en/ranking), and both the on-premises (bare metal, Docker, or K8S) and multi-cloud markets provided by Elastic on Amazon, Azure, and Google will rank it as one of the next best solutions for cloud searching and storage.

The growth of Elasticsearch is mainly due to it being one of the best solutions for searching, storage, and providing analytics on unstructured content in petabyte-sized datasets, and these are the main pillars of modern data-centered companies.

In this book, you'll be guided through comprehensive recipes on Elasticsearch 8.x and see how you can create and run complex queries and analytics.

Packed with recipes on performing index mapping, aggregation, and scripting using Elasticsearch, this fifth edition of Elasticsearch Cookbook will get you acquainted with numerous solutions and quick techniques to perform both everyday and uncommon tasks, such as how to deploy Elasticsearch nodes, integrate other tools into Elasticsearch, and create different visualizations with Kibana. Finally, you will integrate your Java, Scala, Python, and big data applications, such as Apache Spark and Pig, and create efficient data applications powered by enhanced functionalities and custom plugins.

By the end of this book, you will have gained in-depth knowledge of implementing Elasticsearch architecture, and you'll be able to manage, search, and store data efficiently and effectively using Elasticsearch.

IMHO, this book is the last of a long series and, due to continuous refinements, technical/stylistic improvements, and the suggestions of about 10 years of readers, it's probably one of the most complete and effective books on Elasticsearch.

Dear reader, thus, it is a technical book. I hope you'll enjoy it from the bottom of your heart!

Sincerely,

Alberto

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