Forum Discussion
Writing to a specific warehouse schema using a dataflow gen2
- 8 months ago
tayloramy pmscorca we implemented the capability of writing to a given schema in Azure Sql, Lakehouse, Warehouse and Fabric Sql quite some time ago already.
As mentioned by miguel you need to ensure that you expand Advanced option when selecting the connector and set "Navigate using full hierarchy" to True.
Once done, on the next stage you'll be able to see the list of schema you can write to
Best regards,
Antoine
the schema is maintained and you can hover over the data destination card at the bottom of the query settings pane, right underneath the applied steps. This should give you all the information about what the data destination configuration is.
I do understand that perhaps the pipelines and dataflows experience are not exactly the same. I will pass this feedback to the appropriate set of individuals inside of my team who own this feature.
I do want to clarify that the functionality is there so, to address your initial question, Dataflows is capable of using a schema to load data as a new or existing table.
We welcome you to post any suggestions or feedback to improve the experience in the Fabric Ideas portal so other members of the community can also chime in.
Visually, when the Data destination is reopened the Navigation pane doesn't show the selected schema previously.
- miguel8 months agoCommunity Admin
Thanks! I think I understand now.
As mentioned, you can always just hover over the destination card to see the data destination settings of a query:
In this sense, and answering the original question, it is possible to use a specific schema as a data destination.
However, I was able to repro the bug that you've encountered with the warehouse connector where it doesn't provide the same experience as something like the Lakehouse connector that does navigate using the existing configuration of the data destination card. I've raised an internal bug for this and we should have a fix for it so it matches the experience of the Lakehouse.
Thank you for your patience and for reporting this!