SQL Window Functions Explained

When I first learned SQL, GROUP BY felt like all I needed. Then I hit a question it couldn’t answer: “Show me every trip, and next to it, that rider’s total spend.”

GROUP BY collapses rows. I wanted to keep every row and still see an aggregate beside it. That’s what window functions are for.

In this post we’ll use a small taxi company database (a safari schema with trips and drivers tables) to walk through the basics.

What is a window function?

A window function performs a calculation across a set of rows related to the current row without collapsing them into one.

The general shape is:

function_name(...) OVER (
    PARTITION BY column_a
    ORDER BY column_b
)

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• OVER() is what makes it a window function.
• PARTITION BY splits rows into groups (windows). It’s like GROUP BY, but rows aren’t merged.
• ORDER BY sets the order of rows inside each window, which matters for ranking and for “previous/next row” logic.

The simplest example is a bare counter:

SELECT trip_id, fare,
       ROW_NUMBER() OVER () AS fare_position
FROM safari.trips;

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Every row gets 1, 2, 3, 4… and nothing is collapsed.

The three ranking functions

These three look similar but behave differently when there are ties.

SELECT
    trip_id,
    rider_rating,
    ROW_NUMBER() OVER (ORDER BY rider_rating DESC) AS row_num,
    RANK()       OVER (ORDER BY rider_rating DESC) AS rank_num,
    DENSE_RANK() OVER (ORDER BY rider_rating DESC) AS dense_rank_num
FROM safari.trips
WHERE driver_id = 2
ORDER BY rider_rating DESC;

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Function Behavior on ties Example output ROW_NUMBER() Never repeats; always counts up by 1 1, 2, 3, 4 RANK() Tied rows share a rank, then it skips numbers 1, 2, 2, 4 DENSE_RANK() Tied rows share a rank, no gaps 1, 2, 2, 3

When to use which:

• ROW_NUMBER() when you need a unique position for every row (for example, picking exactly one row per group).
• RANK() for leaderboards, where skipping a position after a tie feels natural (two silver medals, no bronze).
• DENSE_RANK() when you want consecutive rank numbers regardless of ties.

Note that with ROW_NUMBER(), tied rows get an arbitrary order unless you add a tiebreaker column to ORDER BY.

Example 1: Rank all drivers by revenue

Rank all drivers by total revenue, highest first.

Window functions run after GROUP BY. So I aggregate first in a CTE, then rank the result.

WITH driver_revenue AS (
    SELECT driver_id, SUM(fare) AS total_revenue
    FROM safari.trips
    GROUP BY driver_id
)
SELECT
    dr.driver_id,
    d.driver_name,
    dr.total_revenue,
    RANK() OVER (ORDER BY dr.total_revenue DESC) AS revenue_rank
FROM driver_revenue dr
JOIN safari.drivers d ON d.driver_id = dr.driver_id;

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No PARTITION BY here, because we want one ranking across everyone.

Example 2: Aggregates without losing rows

Show every trip with the rider’s total spend alongside it.

A plain GROUP BY would give one row per rider. With a window, every trip stays:

SELECT
    rider_id,
    trip_id,
    fare,
    SUM(fare) OVER (PARTITION BY rider_id) AS rider_total_spend
FROM safari.trips;

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Each row now shows its own fare and the rider’s total. From here it’s easy to calculate things like “what percentage of this rider’s spend was this trip?” (fare / SUM(fare) OVER (...)).

Example 3: Comparing to the previous row with LAG

For driver 8, show each trip’s fare, the previous trip’s fare, and the change.

LAG() looks backward a row within the window. (LEAD() looks forward.)

SELECT
    t.driver_id,
    d.driver_name,
    t.trip_date,
    t.fare,
    LAG(t.fare) OVER (PARTITION BY t.driver_id ORDER BY t.trip_date) AS previous_fare,
    t.fare - LAG(t.fare) OVER (PARTITION BY t.driver_id ORDER BY t.trip_date) AS fare_change
FROM safari.trips t
JOIN safari.drivers d ON d.driver_id = t.driver_id
WHERE t.driver_id = 8
ORDER BY t.trip_date;

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What happens on the first trip? There’s no previous row, so LAG() returns NULL, and fare - NULL is also NULL as there’s no change to report.

Example 4: Top row per group

For every driver, find their single highest-fare trip.

This is a very common problem, and probably the most useful pattern among these examples. Number the rows within each driver, then keep only number 1.

WITH ranked_trips AS (
    SELECT
        driver_id,
        trip_id,
        fare,
        trip_date,
        ROW_NUMBER() OVER (PARTITION BY driver_id ORDER BY fare DESC) AS fare_rank
    FROM safari.trips
)
SELECT
    d.driver_name,
    t.trip_id,
    t.fare,
    t.trip_date
FROM ranked_trips t
JOIN safari.drivers d ON d.driver_id = t.driver_id
WHERE t.fare_rank = 1
ORDER BY t.fare DESC;

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Why the CTE? You can’t filter on a window function in WHERE, because WHERE is evaluated before window functions run. Wrapping it in a CTE (or subquery) lets you filter on the computed column afterward.

Also note that we use ROW_NUMBER(). If a driver has two trips tied for the highest fare, you get exactly one. Swap in RANK() and you’d get both. Pick based on what the question means.

Summary

• OVER() turns a function into a window function.
• PARTITION BY defines the groups; ORDER BY defines the order within them.
• Window functions keep your rows; GROUP BY collapses them.
• ROW_NUMBER = unique, RANK = ties with gaps, DENSE_RANK = ties without gaps.
• LAG/LEAD compare a row to its neighbors; the edge rows get NULL.
• To filter on a window result, wrap the query in a CTE or subquery.

Once these click, a lot of problems that used to need self-joins or messy subqueries become a few readable lines.