A. Use a global try-except block to catch all exceptions and log them to the 'error_log' table.

B. Wrap individual DataFrame operations (e.g., 'filter', 'select, 'groupBy') in try-except blocks to catch exceptions specific to those operations and log them.

C. Implement a custom User-Defined Function (UDF) that encapsulates the error-prone logic. Within the UDF, use try-except blocks to handle errors and return error messages along with the processed data. Add a column in Dataframe that contains the errors. Then, create table for the Dataframe using snowpark's API

D. Rely solely on Snowflake's built-in error handling mechanisms, as Snowpark automatically handles all exceptions.

E. Use Snowpark's logging API to automatically capture and log all errors without needing explicit try-except blocks. (Assume such an API exists, even if it doesn't in the current Snowpark version.)