Kedro is an open-sourced Python framework for creating maintainable and modular data science code.

Kedro

Hi team,
I'm using the new `ManagedTableDataSet` with Databricks Unity Catalog and I didn't find a way to store tables on a external location (ABFS Azure). There's a way of storing a external table with pure-spark : `df.write.mode(mode).option("path", table_path).saveAsTable(f"{catalog_name}.{schema_name}.{table_name}")` , where `table_path` its the path for the external location like `<abfss://container@storage_account.dfs.core.windows.net/raw>` .
There's a way to pass this path to the `ManagedTableDataSet`  when saving the data? Or should I go and create a `CustomManagedTableDataSet`  with this capability?

Other way would be creating the tables before the pipeline runs

I could solve it creating a `ManagedExternalTableDataSet`  that overrides the save functions like `data.write.format("delta").option("path", self.table_path)`

It sounds like this is quite common, do you think you can do a PR to add this into the dataset?

i created the pr as a draft <https://github.com/kedro-org/kedro-plugins/pull/251> . I still need to test if it works on dbricks properly