Answer: They could wrap the queries using PySpark and use Python's control flow system to determine when to run the final query.

**Explanation:** **Why B is correct:** 1. **Python control flow**: PySpark allows you to wrap SQL queries and use Python's datetime functions to check the current day of the week. 2. **Conditional execution**: You can use `if` statements to execute the final query only when `datetime.today().weekday() == 6` (Sunday). 3. **Daily execution**: The program can still run daily, but the final query only executes on Sundays. 4. **Flexibility**: This approach provides the most control and doesn't require changing data models or restricting access. **Why other options are incorrect:** - **A**: Submitting a feature request is not a practical solution for immediate implementation. - **C**: Running the entire program only on Sundays contradicts the requirement to run daily. - **D**: Restricting table access would prevent the query from running, but it's not a clean solution and could affect other processes. - **E**: Redesigning the data model is overly complex for a simple scheduling requirement. **Implementation example:** ```python from datetime import datetime from pyspark.sql import SparkSession spark = SparkSession.builder.getOrCreate() # Run daily queries spark.sql("SELECT * FROM daily_table") spark.sql("SELECT * FROM intermediate_table") # Only run final query on Sundays if datetime.today().weekday() == 6: # Sunday spark.sql("SELECT * FROM final_table") ```

Author: Keng Suppaseth