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Elastic Stack 8.x Cookbook

Elastic Stack 8.x Cookbook

By : Huage Chen, Yazid Akadiri
5 (3)
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Elastic Stack 8.x Cookbook

Elastic Stack 8.x Cookbook

5 (3)
By: Huage Chen, Yazid Akadiri

Overview of this book

Learn how to make the most of the Elastic Stack (ELK Stack) products—including Elasticsearch, Kibana, Elastic Agent, and Logstash—to take data reliably and securely from any source, in any format, and then search, analyze, and visualize it in real-time. This cookbook takes a practical approach to unlocking the full potential of Elastic Stack through detailed recipes step by step. Starting with installing and ingesting data using Elastic Agent and Beats, this book guides you through data transformation and enrichment with various Elastic components and explores the latest advancements in search applications, including semantic search and Generative AI. You'll then visualize and explore your data and create dashboards using Kibana. As you progress, you'll advance your skills with machine learning for data science, get to grips with natural language processing, and discover the power of vector search. The book covers Elastic Observability use cases for log, infrastructure, and synthetics monitoring, along with essential strategies for securing the Elastic Stack. Finally, you'll gain expertise in Elastic Stack operations to effectively monitor and manage your system.
Table of Contents (16 chapters)
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Building advanced search queries with Query DSL

In this recipe, we’ll explore more advanced Query DSL techniques to enhance your search and analysis tasks.

Getting ready

Ensure that you have completed the previous Searching with Query DSL recipe.

You can find the snippets for this recipe at https://github.com/PacktPublishing/Elastic-Stack-8.x-Cookbook/blob/main/Chapter3/snippets.md#building-advanced-search-query-with-query-dsl.

How to do it...

In the previous recipe, we mostly saw queries for full-text search, ideal for searching words within bodies of text. But how do we query for numbers, dates, and IPs? This is where the range query becomes useful. Let’s explore how to find movies released between 1925 and 1927:

  1. Start with a range query for the "release_year" field: Go to Dev Tools | Console in Kibana and try the query with the following code snippet (you can find the snippet at https://github.com/PacktPublishing/Elastic-Stack-8.x-Cookbook...
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