Implementing Data Denormalization
In most cases, dimension tables should be denormalized. In this exercise, we'll use PySpark to load two dimension tables, products
and categories
, and denormalize the products table by replacing the categoryID
column with the corresponding categoryName
from the table categories
.
Note: If you get an error about an API rate limit, this usually happens because a previous Fabric task has not completed. You can view active Fabric tasks from the Monitor page (located on the left vertical menu). Canceling old Fabric tasks in the Monitor page will usually resolve the rate limit error.
Cet exercice fait partie du cours
Transform and Analyze Data with Microsoft Fabric
Exercice interactif pratique
Passez de la théorie à la pratique avec l’un de nos exercices interactifs
