HardSQL challenge #279WINDOW FUNCTIONGROUP BYPERCENTILE

User Spend Percentile

Assign percentile rank to users based on spend.

The challenge runs on the SQLabHub practice database (SQLite) and uses the orders table. You can solve it in the browser, with nothing to install.

Solve This SQL Challenge

The task

Assign percentile rank to users based on spend.

A correct answer returns 114 rows with 3 columns: user_id, spend, pct.

Tables used in this challenge

`orders` 200 rows

id INTEGER (PK) · user_id INTEGER · total REAL · discount REAL · item_count INTEGER · status TEXT · order_date TEXT · shipped_date TEXT · shipping_city TEXT · shipping_country TEXT

First 3 rows of the orders table
id	user_id	total	discount	item_count	status	order_date	shipped_date	shipping_city	shipping_country
1	43	2638.11	0.25	3	cancelled	2024-04-24	NULL	Los Angeles	USA
2	8	2947	0.19	5	delivered	2024-03-15	2023-04-09	Chicago	USA
3	136	683.24	0.08	2	delivered	2023-02-15	2023-07-10	Los Angeles	USA

The first rows of each table are shown. See how all the tables relate on the database schema page.

Expected output

Expected output of the challenge
user_id	spend	pct
150	254.34	0
82	368.6	0.008849557522123894
107	441.29	0.017699115044247787
34	635.74	0.02654867256637168
136	683.24	0.035398230088495575

First 5 of 114 rows. This is the output of the model solution on the practice database. The task does not fix a sort order, so your rows may come back in a different order.

What you practise

Summarising many rows into one value with COUNT, SUM, AVG, MIN or MAX
Grouping rows with GROUP BY to get one result row per group
Expressing a row's position as a fraction with PERCENT_RANK()

Hint and approach

Try the challenge first. Open these only when you need them.

Show the hint

PERCENT_RANK

Show the step-by-step approach

How the model solution is built, in the order the database evaluates it:

Read from the orders table.
Group the rows by user_id, so the result has one row for each value.
For each group, compute SUM(total).
Compute PERCENT_RANK(), the relative position from 0 to 1, ordered by SUM(total).

Model solution

Checking your session…

What to watch for

PERCENT_RANK(). PERCENT_RANK() returns a value between 0 and 1, not a percentage. Multiply by 100 to display it as one.
GROUP BY. Every selected column must either be in GROUP BY or sit inside an aggregate. SQLite accepts other columns and returns an arbitrary value for them; most databases raise an error.
Aggregate functions. Aggregates skip NULLs. AVG divides by the number of non-NULL values and COUNT(column) can be smaller than COUNT(*).