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)

Scripting in ingest processors

In Chapter 12, Using the Ingest Module, we will see several types of ingest processors.

Ingest processors are the building blocks for an ingestion pipeline; they describe an action that can be executed on a document to modify it.

Scripting is the main functionality used in processors to provide the core functionalities for completeness. Their scripting functionalities are discussed in this chapter.

Getting ready

You will need an up-and-running Elasticsearch installation, similar to the one that we described in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started.

How to do it...

We will simulate a pipeline with a set and a script processor. To modify our documents before ingesting them, we will perform the following steps:

  1. Execute a pipeline simulation API call with the two processor steps and two documents as a sample:
    POST /_ingest/pipeline/_simulate
    { “pipeline”: {
       ...