"Can you explain SQL window functions and when to use them?"
Window functions are essential for data analysis roles at every major tech company. They appear in SQL coding tests, take-home assessments, and live interviews. Understanding window functions demonstrates you can perform complex analytics without subqueries or self-joins, a skill required for data analyst, data engineer, and analytics engineer positions.
Define window functions: perform calculations across a set of rows related to the current row, without collapsing rows like GROUP BY does. The result is added as a column alongside existing data.
Explain the OVER clause syntax: FUNCTION() OVER (PARTITION BY col ORDER BY col ROWS/RANGE frame_clause).
Cover ranking functions: ROW_NUMBER() (unique sequential), RANK() (ties get same rank, gaps), DENSE_RANK() (ties get same rank, no gaps).
Cover analytical functions: LAG()/LEAD() for accessing previous/next rows, FIRST_VALUE()/LAST_VALUE() for first/last in partition, NTH_VALUE() for nth row.
Cover aggregate window functions: SUM/AVG/COUNT/MAX/MIN with OVER clause for running totals, moving averages, and cumulative calculations.
Window functions perform calculations across a set of rows (a "window") related to the current row, but unlike GROUP BY, they do not collapse rows — each row retains its identity while gaining access to aggregate or positional information. The syntax is FUNCTION() OVER (PARTITION BY ... ORDER BY ... frame_clause). PARTITION BY divides rows into groups (like GROUP BY but without collapsing), ORDER BY defines the row order within each partition, and the frame clause (ROWS BETWEEN ... AND ...) defines which rows to include in the calculation. Ranking functions are the most common: ROW_NUMBER() assigns a unique sequential number (useful for deduplication — WHERE rn = 1), RANK() handles ties by giving the same rank but leaving gaps (1,1,3), and DENSE_RANK() handles ties without gaps (1,1,2). Analytical functions like LAG(column, offset) and LEAD(column, offset) access values from previous or subsequent rows — perfect for calculating day-over-day changes or comparing consecutive events. Aggregate window functions like SUM() OVER (ORDER BY date) create running totals, and AVG() OVER (ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) calculates a 7-day moving average. A practical example: to find the top 3 highest-paid employees per department: SELECT * FROM (SELECT name, department, salary, ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) as rn FROM employees) t WHERE rn <= 3. Window functions are supported by PostgreSQL, MySQL 8+, SQL Server, BigQuery, and all modern databases.
Practice the "top N per group" pattern — it is the most common window function interview question.
Know the difference between ROWS and RANGE in frame clauses for running calculations.
Be ready to write window function queries on a whiteboard or in an online editor.
Use HireMe AI during SQL interview prep to get instant feedback on your window function queries.
For values (100, 100, 90): ROW_NUMBER gives 1,2,3 (arbitrary tiebreak); RANK gives 1,1,3 (same rank, skip next); DENSE_RANK gives 1,1,2 (same rank, no skip).
No. Window functions execute after WHERE. Use a subquery or CTE: WITH ranked AS (SELECT *, ROW_NUMBER() OVER(...) as rn FROM table) SELECT * FROM ranked WHERE rn = 1.
GROUP BY collapses rows into groups and returns one row per group. Window functions calculate across groups but keep all original rows, adding the computed value as a new column.
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