What will happen each time a job leveraging Delta Lake's Change Data Feed is run?

The correct answer highlights that when a job leveraging Delta Lake's Change Data Feed is run, inserted or updated records will indeed be appended to the target table.

Delta Lake's Change Data Feed (CDF) allows for efficient tracking of changes such as inserts and updates to the data in a Delta table. When you enable CDF, the system captures the modifications made to your data, enabling users to read only the changes since a specific version or timestamp. This means that when a job processes the Change Data Feed, it will identify the newly inserted or modified records and append them to the target table. This behavior is particularly useful in scenarios requiring near real-time data processing and synchronization of datasets, as it allows for incremental updates rather than processing the entire dataset every time.

In contrast, the other options suggest actions that do not align with how Delta Lake's Change Data Feed operates. Overwriting all inserted values would negate the point of capturing incremental changes, while merging only unique keys does not accurately represent the functionality of CDF, which focuses on appending changes rather than selective merging. Lastly, completely dropping the target table goes against the principle of appending updates; it would erase existing data instead of incorporating new changes. Thus, the correct understanding is that CDF