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GROUP BY does. They enable analytics queries that previously required subqueries or application-layer processing.
How Window Functions Differ from GROUP BY
GROUP BY can’t do this — it removes the individual rows.
The OVER Clause
Every window function uses anOVER clause that defines the window — the set of rows to compute over.
OVER() means the window is the entire result set.
Ranking Functions
Example output:
PARTITION BY: Per-Group Rankings
AddPARTITION BY to rank within groups instead of across the whole result set:
LAG and LEAD: Accessing Adjacent Rows
LAG accesses a previous row; LEAD accesses a following row — without a self-join.
Running Totals and Moving Averages
UseROWS BETWEEN to define a frame — the subset of rows to include in the calculation.
Frequently Asked Questions
Can I filter on a window function result in a WHERE clause?
No — window functions are evaluated afterWHERE. To filter on a window function result, wrap the query in a subquery or CTE:
What’s the difference between ROWS and RANGE in the frame clause?
ROWS counts physical rows. RANGE groups rows with the same ORDER BY value together. For most use cases (running totals, moving averages), ROWS gives the expected behavior. RANGE can produce surprising results when there are ties in the order column.
Do window functions work with indexes?
Window functions don’t use indexes for the window computation itself, but the query can still use indexes for theWHERE clause to reduce the rows being processed. Complex window queries benefit from Reading EXPLAIN in MySQL to understand the execution plan.
Troubleshooting
See also
- CTEs in MySQL — commonly paired with window functions for multi-step analytics
- GROUP BY and HAVING in MySQL — aggregation without the window — understand the difference

