Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Azure Data Engineering Cookbook

You're reading from   Azure Data Engineering Cookbook Get well versed in various data engineering techniques in Azure using this recipe-based guide

Arrow left icon
Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803246789
Length 608 pages
Edition 2nd Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Ahmad Osama Ahmad Osama
Author Profile Icon Ahmad Osama
Ahmad Osama
Nagaraj Venkatesan Nagaraj Venkatesan
Author Profile Icon Nagaraj Venkatesan
Nagaraj Venkatesan
Luca Zanna Luca Zanna
Author Profile Icon Luca Zanna
Luca Zanna
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Chapter 1: Creating and Managing Data in Azure Data Lake 2. Chapter 2: Securing and Monitoring Data in Azure Data Lake FREE CHAPTER 3. Chapter 3: Building Data Ingestion Pipelines Using Azure Data Factory 4. Chapter 4: Azure Data Factory Integration Runtime 5. Chapter 5: Configuring and Securing Azure SQL Database 6. Chapter 6: Implementing High Availability and Monitoring in Azure SQL Database 7. Chapter 7: Processing Data Using Azure Databricks 8. Chapter 8: Processing Data Using Azure Synapse Analytics 9. Chapter 9: Transforming Data Using Azure Synapse Dataflows 10. Chapter 10: Building the Serving Layer in Azure Synapse SQL Pool 11. Chapter 11: Monitoring Synapse SQL and Spark Pools 12. Chapter 12: Optimizing and Maintaining Synapse SQL and Spark Pools 13. Chapter 13: Monitoring and Maintaining Azure Data Engineering Pipelines 14. Index 15. Other Books You May Enjoy

Configuring partitions to optimize data flows

Data flows, by default, create partitions behind the scenes to make transformation activities such as join, filter, and sort run faster. Partitions split the large data into multiple smaller pieces so that the backend processes in the data flows can divide and conquer their tasks and finish the execution quickly.

In this recipe, we will take a slow-running data flow and adjust the partitioning to reduce the execution time.

Getting ready

Create a Synapse Analytics workspace as explained in the Provisioning an Azure Synapse Analytics workspace recipe.

Complete the Performing data transformation using activities such as join, sort, and filter and Monitoring data flows and pipelines recipes in this chapter.

How to do it…

Perform the following steps to optimize data flows:

  1. Log in to portal.azure.com, go to All resources, and search for packtadesynapse. Click on the workspace. Click Open Synapse Studio. Click...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image