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JYOCH's avatar
JYOCH
Frequent Visitor
2 years ago
Solved

Fabric

Hi all,,, I am trying to read the necessesary data from customer tables in fabric sql end point. as a part of it i am creating views and now i have to update some columns as per the requirement. I ...
Need Help
  • Anonymous's avatar
    Anonymous
    2 years ago

    Hi JYOCH ,

    As the following official documentation refers, the SQL analytics endpoint in Microsoft Fabric operates in read-only mode over lakehouse delta tables. This means you can only read data from delta tables using the SQL analytics endpoint. They can save functions, views, and set SQL object-level security. To modify data in Lakehouse delta tables, you have to switch to lakehouse mode and use Apache Spark. 

    What is the SQL analytics endpoint for a lakehouse? - Microsoft Fabric | Microsoft Learn

    To modify data in Lakehouse delta tables, it is necessary to switch to lakehouse mode and utilize Apache Spark.

     

    Given this, you might find the following alternatives useful:

    • Directly modify the underlying tables instead of using a view. The ALTER TABLE statement can be used to add or modify columns in a table.
    • Create a new view that includes the updated columns. The CREATE VIEW statement can be used to create a new view based on the existing tables, and the updated columns can be included in the SELECT statement.

    Best Regards

Anonymous's avatar
Anonymous
Not applicable
2 years ago

Hi JYOCH ,

As the following official documentation refers, the SQL analytics endpoint in Microsoft Fabric operates in read-only mode over lakehouse delta tables. This means you can only read data from delta tables using the SQL analytics endpoint. They can save functions, views, and set SQL object-level security. To modify data in Lakehouse delta tables, you have to switch to lakehouse mode and use Apache Spark. 

What is the SQL analytics endpoint for a lakehouse? - Microsoft Fabric | Microsoft Learn

To modify data in Lakehouse delta tables, it is necessary to switch to lakehouse mode and utilize Apache Spark.

 

Given this, you might find the following alternatives useful:

  • Directly modify the underlying tables instead of using a view. The ALTER TABLE statement can be used to add or modify columns in a table.
  • Create a new view that includes the updated columns. The CREATE VIEW statement can be used to create a new view based on the existing tables, and the updated columns can be included in the SELECT statement.

Best Regards