What is the main difference between "overwrite" and "append" modes when writing data in Databricks?

The main difference between "overwrite" and "append" modes in Databricks relates to how the data is managed when writing to a data source.

In the overwrite mode, the existing data in the specified location is completely replaced with the new data being written. This means that if you have a dataset already stored, invoking the overwrite mode will result in the complete removal of the old data followed by the insertion of the new data. This is particularly useful when you want to ensure that your dataset reflects the most current information without retaining outdated records.

On the other hand, the append mode is designed to add new data to the existing dataset without modifying what is already there. When using append, you simply add additional records to the existing data, preserving all previous entries. This approach is beneficial when new rows or records need to be added to the dataset without changing or losing existing information.

The clear distinction in the functionality of these two modes is critical for data management strategies, depending on whether the goal is to refresh a dataset entirely or to incrementally build on the existing data. Hence, option A accurately captures this fundamental difference.