Databricks Certified Machine Learning - Associate
Get started today
Ultimate access to all questions.
Ultimate access to all questions.
A data scientist has computed updated rows containing new feature values for primary keys already stored in the Feature Store table 'features'. The updated feature values are stored in the DataFrame 'features_df'. They aim to update the rows in 'features' if the associated primary key is in 'features_df'. If a row's primary key is not in 'features_df', they want the row to remain unchanged in 'features'. Which code block using the Feature Store Client 'fs' accomplishes this task?
Explanation:
The correct answer is B because the 'merge' mode is used to update existing rows with the same primary key and leave others unchanged. This matches the scenario's requirements. Option A ('overwrite') would replace all existing data, which is not desired. Options C and D lack the 'mode' parameter, leading to default behaviors that may not suit the task. Option E is irrelevant as it involves refreshing table metadata, not data merging.