Measure Efficiency of Window Functions in Query Execution

Analyzing Window Function Performance with EXPLAIN ANALYZE

Write a PostgreSQL query to analyze a query that uses a window function using EXPLAIN ANALYZE.

Solution:

-- Analyze the performance of a query using a window function to calculate running totals.
EXPLAIN ANALYZE 
SELECT name, salary,
       SUM(salary) OVER (ORDER BY hire_date) AS running_total
FROM Employees;

Explanation:

• Purpose of the Query:
• To inspect how PostgreSQL handles window functions and their performance implications.
• Demonstrates the use of analytical functions within a query plan.
• Key Components:
• SUM(salary) OVER (ORDER BY hire_date) : The window function calculating a running total.
• EXPLAIN ANALYZE : Provides both estimated and actual execution details.
• Real-World Application:
• Ideal for financial or trend analysis reports where cumulative metrics are needed.

Notes:

• Window functions can be resource-intensive; analyzing their performance helps in optimization.

For more Practice: Solve these Related Problems:

• Write a PostgreSQL query using EXPLAIN ANALYZE to analyze a query that uses the ROW_NUMBER() window function over the "Orders" table.
• Write a PostgreSQL query using EXPLAIN ANALYZE to evaluate the performance of a query that computes a running total using SUM() over a window in the "Sales" table.
• Write a PostgreSQL query using EXPLAIN ANALYZE to analyze a query that uses the RANK() window function on the "Employees" table ordered by "salary".
• Write a PostgreSQL query using EXPLAIN ANALYZE to measure the execution plan of a query that uses multiple window functions in the "Products" table.

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