Skip to main content
cancel
Showing results for 
Search instead for 
Did you mean: 

Join us at the 2025 Microsoft Fabric Community Conference. March 31 - April 2, Las Vegas, Nevada. Use code FABINSIDER for $400 discount. Register now

Reply
mrozzano
Advocate I
Advocate I

Change lakehouse destination from append, replace, or fixed to use 'automatic' instead ?

If I set a dataflow lakehouse destination to use "append", "replace", or "fixed" settings, is there a way to reconfigure the destination to use "automatic settings" instead, without dropping the table or recreating the destination ?

 

If there's not an easy way to reconfigure to use automatic settings, is there a least-impactful method to recreate the destination using automatic settings ?

1 ACCEPTED SOLUTION
v-kongfanf-msft
Community Support
Community Support

Hi @mrozzano ,

 

Currently, Data Factory dataflow destination configurations (such as Lakehouse) do not support changing the write mode directly (switching from “append”, “replace”, or “fixed” to “automatic”). Because the write mode is part of the target configuration, modifying it usually requires the target to be recreated.

 

One can try using parameterized dataflow where the write mode is parameterized in the dataflow. Dynamically passing parameter values in the pipeline to control the write behavior.

For more details, you can refer to below document:

Parameters - Microsoft Fabric | Microsoft Learn


Best Regards,
Adamk Kong

 

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

View solution in original post

1 REPLY 1
v-kongfanf-msft
Community Support
Community Support

Hi @mrozzano ,

 

Currently, Data Factory dataflow destination configurations (such as Lakehouse) do not support changing the write mode directly (switching from “append”, “replace”, or “fixed” to “automatic”). Because the write mode is part of the target configuration, modifying it usually requires the target to be recreated.

 

One can try using parameterized dataflow where the write mode is parameterized in the dataflow. Dynamically passing parameter values in the pipeline to control the write behavior.

For more details, you can refer to below document:

Parameters - Microsoft Fabric | Microsoft Learn


Best Regards,
Adamk Kong

 

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

Helpful resources

Announcements