Exam DP203 Storage 3 Azure Lake Database: Difference between revisions
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The third [[Exam_DP203_Storage|Storage]] type is: Azure Lake Database. | The third [[Exam_DP203_Storage|Storage]] type is: Azure Lake Database. | ||
The underlying data is in Parquet or CSV files only. | The underlying data is in Parquet or CSV files only. Me: it is not clear where abouts these files are located. | ||
Serverless SQL Pool, or Spark. | Serverless SQL Pool, or Spark. |
Revision as of 21:15, 16 November 2024
The third Storage type is: Azure Lake Database.
The underlying data is in Parquet or CSV files only. Me: it is not clear where abouts these files are located.
Serverless SQL Pool, or Spark.
To create a Lake Database, go into Synapse Studio Data tab, and click the + button and select Lake Database under "Workspace". This creates a new section "Lake Database" under which the database is created, under Data - Workspace.
In the design section, you can choose a template from different business scenarios, or choose to create it as empty. Then after you can add tables to it, including key relationships between tables.
You can run select statements on the tables either with the Serverless pool using standard SQL syntax like:
USE RetailDB; GO SELECT CustomerID, FirstName, LastName FROM Customer ORDER BY LastName;
or by running a Spark notebook and running:
%%sql INSERT INTO `RetailDB`.`Customer` VALUES (123, 'John', 'Yang') %%sql SELECT * FROM `RetailDB`.`Customer` WHERE CustomerID = 123