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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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What is ES|QL?

ES|QL is a new query language and a query engine introduced by Elastic, designed to enhance the way users interact with their data. As data volumes grow and the complexity of analysis increases, traditional query languages have begun to show their limitations. ES|QL was developed to address these challenges and provide a more efficient, user-friendly experience for a diverse range of users, from beginners to seasoned experts.To be clear, ES|QL has been designed to reduce the distance between Elasticsearch users and insights. Not only for analytics, but for everything users can do with Elasticsearch, such as log analytics, to metrics analytics, threat hunting for cybersecurity, and simple to complex search queries. It should not be hard for anyone to query the data.There are other ways to solve this challenge, but a combination of intuitive functions that have been used for decades in SQL-like query languages and chains of expression separated by pipes has been proven to be a straightforward way to build insight on data. ES|QL is a natural way to build queries and get insights iteratively, from simple to complex, and ensure correctness along the way. Not only that, but you will see in subsequent chapters that ES|QL is not only a language running on top of Elasticsearch, it is also a processing layer that scales. At Elastic, we do not compromise with scale; ES|QL has followed the same paradigm. Lastly, the introduction of ES|QL gave us an opportunity to build a new query engine with better performance output.

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