Book Image

Elasticsearch 8.x Cookbook - Fifth Edition

By : Alberto Paro
Book Image

Elasticsearch 8.x Cookbook - Fifth Edition

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)

Creating a standard Java HTTP client

An HTTP client is one of the easiest clients to create. It's very handy because it allows for the calling, not only of the internal methods as the native protocol does, but also of third-party calls implemented in plugins that can only be called via HTTP.

Getting ready

You need an up-and-running Elasticsearch installation, as we described in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started.

To correctly execute the following commands, you will need an index populated with the ch04/populate_kibana.txt commands that are available in the online code.

A Maven tool or an Integrated Development Environment (IDE) that natively supports it for Java programming, such as Visual Studio Code, Eclipse, or IntelliJ IDEA, must be installed. Elasticsearch code is targeting Java 17, so it's best practice to have installed JDK 17 or above.

The code for this recipe is in the chapter_13/http_java_client directory...