I would like to know the recommended approach for implementing schema evolution in Delta tables within Databricks.
Currently, I am encountering an issue with the dataset kedro_datasets.databricks.managed_table_dataset
Whenever I attempt to add new columns using the upsert mode, an Exception is raised (there is check in the dataset implementation)
Fortunately, I have control over the schema before performing the upsert operation. Hence, once I approve the schema changes, I expect to be able to utilize schema evolution during the upsert.
In this context, I strongly believe that the exception raised during schema changes should be made optional, allowing for a smoother schema evolution process.
For me, who should accept/deny schema evolution must be spark session