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)

Configuring result set caching in Azure Synapse dedicated SQL pool

Result set caching is a feature in Synapse dedicated SQL pools that caches the result of the query in the control node of the Synapse dedicated SQL pool instance. In other words, the first time a query is executed, the result of the query is stored in the control node of the Synapse dedicated SQL pool instance. The next time, when the same query is executed and if the underlying data hasn’t changed, the query engine will quickly return the result directly from the cache in the control node without reading the data from any of the compute nodes of the Synapse dedicated SQL pool instance. Unlike other common memory-based caches, the result set cache is persisted even after the Synapse dedicated SQL pool instance has been restarted.

In this recipe, we will learn how to turn on result set caching and how to verify if the cache is being used.

Getting ready

Create a Synapse Analytics workspace, as explained...