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

## Explanation **Option B is the correct answer** because it provides a practical and flexible solution: 1. **PySpark with Python control flow**: By wrapping the SQL queries in PySpark, you can use Python's datetime module to check the current day of the week and conditionally execute the final query only on Sundays. 2. **Daily execution**: The program can run every day, but the final query will only execute when the condition (day == Sunday) is met. 3. **Minimal changes**: This approach requires minimal changes to the existing SQL program while providing the exact functionality requested. **Why other options are incorrect**: - **Option A**: Submitting a feature request is not a practical solution as it depends on Databricks implementing new functionality, which could take significant time and may not align with their product roadmap. - **Option C**: Running the entire program only on Sundays defeats the purpose of having daily execution for the other queries. - **Option D**: Restricting table access based on days would be complex to implement, could break other processes, and doesn't solve the conditional execution problem. - **Option E**: Redesigning the data model is an over-engineered solution that doesn't address the scheduling requirement and would require significant development effort. **Implementation approach**: ```python from pyspark.sql import SparkSession from datetime import datetime spark = SparkSession.builder.appName("ConditionalQuery").getOrCreate() # Run first queries every day spark.sql("SELECT * FROM table1 WHERE ...") spark.sql("SELECT * FROM table2 WHERE ...") # Check if today is Sunday if datetime.today().weekday() == 6: # 6 = Sunday # Run final query only on Sundays spark.sql("SELECT * FROM final_table WHERE ...") ``` This solution is efficient, maintainable, and directly addresses the requirement for conditional execution based on day of the week.

Author: Keng Suppaseth