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Elasticsearch Query Language the Definitive Guide

Elasticsearch Query Language the Definitive Guide

By : Bahaaldine Azarmi, Stephen Brown, Farbod Shirzadian, Alejandro Sanchez, Alexis Charveriat
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Elasticsearch Query Language the Definitive Guide

Elasticsearch Query Language the Definitive Guide

By: Bahaaldine Azarmi, Stephen Brown, Farbod Shirzadian, Alejandro Sanchez, Alexis Charveriat

Overview of this book

Built to simplify high-scale data analytics in Elasticsearch, this practical guide will take you from foundational concepts to advanced applications across search, observability, and security. It will help you overcome common challenges such as efficiently querying large datasets, applying advanced analytics without deep prior knowledge, and resolving for a unique and consolidated query language. Written by senior experts at Elastic with extensive field experience, this book delivers actionable guidance rooted in solving today’s data challenges at scale. After introducing ESQL and its architecture, the chapters explore real-world applications across various domains, including analytics, raw log analysis, observability, and cybersecurity. Advanced topics such as scaling, optimization, and future developments are also covered to help you maximize your ESQL capabilities. By the end of this book, you’ll be able to leverage ESQL for comprehensive data management and analysis, optimizing your workflows and enhancing your productivity with Elasticsearch.
Table of Contents (4 chapters)
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Summary

In this chapter, we explored how Elasticsearch and ES|QL can be used for data analysis. Presented with a business problem, we learnt how to explore our dataset on small and large scope, showcasing how easy it is to pivot across multiple dimensions with ES|QL.We were able to provide valuable insights, iteratively altering our queries and approach to refine our findings. We also saw how we could combine multiple datasets together to expand our investigation scope. Finally, we’ve showcased the native integration of ES|QL into Kibana visualization tools, allowing us to create an impactful message.In the next chapter, we will explore how ES|QL can be used to process unstructured text data, allowing users to create read-time insights and accelerate their time to value.

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