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DiKi-I
Post Partisan
Post Partisan

Mashup exception while writing from Dataflow to lakehouse

Hi ,
I'm getting below mashup error while writing to lakehouse from dataflow gen2. Could someone please help??
I tried to recreate lakehouse but still getting the same error.

DiKiI_0-1747669975072.png

 

1 ACCEPTED SOLUTION
DiKi-I
Post Partisan
Post Partisan

The dataflow is reading from lakehouse file folder with few transformations. The error message is really vague. There was a null value in that column which was not allowing the data to be loaded into the lakehouse. I was able to do load after removing null values from the column. The data type was text, seems like a limitation or bug.

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3 REPLIES 3
v-priyankata
Community Support
Community Support

Hi @DiKi-I ,

Thank you for reaching out to Microsoft Fabric Community.
Glad to hear you found the solution, please Accept your answer as a solution and give it a 'Kudos' so others can find it easily.
Thank you.

DiKi-I
Post Partisan
Post Partisan

The dataflow is reading from lakehouse file folder with few transformations. The error message is really vague. There was a null value in that column which was not allowing the data to be loaded into the lakehouse. I was able to do load after removing null values from the column. The data type was text, seems like a limitation or bug.

ibarrau
Super User
Super User

Hi. The message states clear that it can't find a column in the table. It could be because it doesn't exist at the source or the credentials entered don't have permission to see the column. Take a deeper look at the table you are trying to move to the lakehouse and make sure the column exists. The failure could be because one of the steps at the dataflow is specifically naming that column. For example if you have a changed type step that names that specific column. It can't change the type. You could remove it from there and check if it continues.

I hope that helps,


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

Happy to help!

LaDataWeb Blog

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