Book Image

Azure Data Engineering Cookbook - Second Edition

By : Nagaraj Venkatesan, Ahmad Osama
Book Image

Azure Data Engineering Cookbook - Second Edition

By: Nagaraj Venkatesan, Ahmad Osama

Overview of this book

The famous quote 'Data is the new oil' seems more true every day as the key to most organizations' long-term success lies in extracting insights from raw data. One of the major challenges organizations face in leveraging value out of data is building performant data engineering pipelines for data visualization, ingestion, storage, and processing. This second edition of the immensely successful book by Ahmad Osama brings to you several recent enhancements in Azure data engineering and shares approximately 80 useful recipes covering common scenarios in building data engineering pipelines in Microsoft Azure. You’ll explore recipes from Azure Synapse Analytics workspaces Gen 2 and get to grips with Synapse Spark pools, SQL Serverless pools, Synapse integration pipelines, and Synapse data flows. You’ll also understand Synapse SQL Pool optimization techniques in this second edition. Besides Synapse enhancements, you’ll discover helpful tips on managing Azure SQL Database and learn about security, high availability, and performance monitoring. Finally, the book takes you through overall data engineering pipeline management, focusing on monitoring using Log Analytics and tracking data lineage using Azure Purview. By the end of this book, you’ll be able to build superior data engineering pipelines along with having an invaluable go-to guide.
Table of Contents (16 chapters)

Implementing workload management in an Azure Synapse dedicated SQL pool

How often have we seen a scenario where we have queries coming from a less important system hogging most of the resources and causing fewer resources to be available for business-critical queries, eventually resulting in dissatisfied customers/stakeholders? Wouldn’t it be nice to classify the queries based on their business needs and reserve and allocate resources accordingly?

Workload management in a Synapse dedicated SQL pool helps to classify the queries based on the user account used to run the query, the user role, and the application used and map them to resource classes. Resource classes are predefined resource pools with resource limits set as a percentage of the total number of resources. By defining rules that classify the queries and mapping them to resource classes, we could reserve resources based on the business needs and ensure that critical queries get the right amount of resources most...