Window Functions – Evaluation Order

Understanding the evaluation order of window functions in SQL is crucial for writing efficient and accurate queries. Window functions are evaluated at a specific stage in the SQL query execution process, which impacts how data is processed and results are derived.

Evaluation Sequence

1. FROM Clause: The query starts by identifying and joining the source tables.
2. WHERE Clause: Filters rows based on specified conditions.
3. GROUP BY Clause: Aggregates data into groups, if applicable.
4. HAVING Clause: Filters groups based on aggregate conditions.
5. WINDOW FUNCTIONS: Computes window functions after the grouping and filtering stages.
6. ORDER BY Clause: Finally, the result set is ordered according to specified columns.

Evaluation Sequence

1. FROM: Defines the source tables.
2. WHERE: Filters rows.
3. GROUP BY: Groups rows.
4. HAVING: Filters groups.
5. WINDOW FUNCTIONS: Computes window functions.
6. ORDER BY: Orders the final result set.

Example

SELECT employee_id, 
       department_id, 
       salary, 
       AVG(salary) OVER (PARTITION BY department_id ORDER BY salary) AS avg_salary
FROM employees
WHERE salary > 50000
GROUP BY department_id, employee_id, salary
HAVING COUNT(employee_id) > 1
ORDER BY avg_salary DESC;

Key Points

• Sequential Processing:
  Window functions are processed after grouping and filtering.
• Dependency on Intermediate Results:
  Window functions can leverage results from previous clauses.

Practical Tips

1. Optimize Filters:
   Use WHERE and HAVING clauses effectively to reduce the dataset size before applying window functions.
2. Order Matters:
   Ensure the correct sequence of operations to achieve desired results.

Benefits

• Efficient Query Execution:
  Optimizes performance by evaluating functions in the correct order.
• Accurate Results:
  Ensures that window function calculations are based on the filtered and grouped data.
• Streamlined Analysis:
  Simplifies complex data processing workflows.