What is a window function in SQL?

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A window function in SQL performs calculations across a set of rows that are related to the current row, without collapsing them into a single result (unlike GROUP BY). It is evaluated using an OVER() clause that defines the “window” (range of rows) for the calculation.

🔑 Key Points about Window Functions

1. Operate on a set of rows but return a value for each row.

2. Do not reduce the result set like aggregates (SUM, AVG with GROUP BY).

3. Require the OVER() clause, which can include:

   • PARTITION BY → Divides rows into groups (like GROUP BY).

   • ORDER BY → Defines order of rows for calculations.

🔑 Common Window Functions

1. Ranking Functions

   • ROW_NUMBER() → Assigns unique numbers to rows.

   • RANK() → Ranks rows, leaving gaps on ties.

   • DENSE_RANK() → Ranks rows without gaps.

   SELECT name, salary,
          RANK() OVER (ORDER BY salary DESC) AS rank
   FROM employees;
   

2. Aggregate Functions

   • SUM(), AVG(), COUNT(), MIN(), MAX()

   • Work across a partition but keep all rows.

   SELECT department, salary,
          AVG(salary) OVER (PARTITION BY department) AS avg_salary
   FROM employees;
   

3. Value Functions

   • LEAD() → Fetches next row’s value.

   • LAG() → Fetches previous row’s value.

   • FIRST_VALUE(), LAST_VALUE() → Return first/last value in the window.

   SELECT name, salary,
          LAG(salary) OVER (ORDER BY salary) AS prev_salary
   FROM employees;
   

⚡ Summary

• A window function applies aggregate-like calculations per row, based on a defined window of rows.

• Unlike GROUP BY, it keeps individual rows visible.

• Useful for analytics: running totals, rankings, comparisons, moving averages.

👉 In short: Window functions = Aggregates + Per-row context.

Read More :

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