Which code block will output a DataFrame with the schema "customer_id LONG, predictions DOUBLE"?

The choice that correctly outputs a DataFrame with the schema of "customer_id LONG, predictions DOUBLE" involves using the select method to specify the relevant fields directly from the DataFrame.

In the correct option, the DataFrame df is being queried to select the "customer_id" column explicitly while simultaneously applying the model to transform the data in the specified columns. The invocation of model(*columns).alias("predictions") indicates that the output of the model is being treated as a new column named "predictions." This ensures that both "customer_id" and "predictions" are present in the resulting DataFrame, while also preserving the appropriate data types. Furthermore, using .alias("predictions") is essential for keeping the schema clear and correctly named.

The other options fall short of achieving the desired schema for various reasons. For instance, some may not utilize the proper DataFrame transformation or selection method to include the required columns effectively. Others may not ensure that the model's output is aliased correctly, potentially leading to naming or type mismatches. Therefore, the choice that utilizes both select and aliasing is the only one that guarantees the output schema of "customer_id LONG, predictions DOUBLE