HardSQL challenge #213WINDOW FUNCTIONRUNNING TOTALPARTITION

Calculate Cumulative Spend per Customer

Return each order with the running total spent by that user up to that date.

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.

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The task

Calculate cumulative spend per user ordered by date.

A correct answer returns 200 rows with 3 columns: user_id, order_date, cum_spend.

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
iduser_idtotaldiscountitem_countstatusorder_dateshipped_dateshipping_cityshipping_country
1432638.110.253cancelled2024-04-24NULLLos AngelesUSA
2829470.195delivered2024-03-152023-04-09ChicagoUSA
3136683.240.082delivered2023-02-152023-07-10Los AngelesUSA

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_idorder_datecum_spend
12022-09-264064.75
22023-04-021618.29
42022-08-222501.23
42024-04-203344.9300000000003
42024-11-154863.29

First 5 of 200 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

  • Accumulating a value row by row with an ordered window
  • Restarting a window calculation for each group with PARTITION BY

Hint and approach

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

Show the hint

SUM OVER partition

Show the step-by-step approach

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

  1. Read from the orders table.
  2. Compute SUM(total) as a running window function: it covers the rows from the start up to the current one, ordered by order_date, restarting for each user_id.

Model solution

Checking your session…

What to watch for

PARTITION BY starts a new running total for each user and ORDER BY sets the direction in which it grows. Take out the partition and you get one total across all customers.

  • Running totals. With ORDER BY and no frame, rows that tie on the sort column are added together in one step. Use ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW for a strict row-by-row total.
  • PARTITION BY. PARTITION BY is not GROUP BY: it keeps every row and only decides which rows a window function looks at.
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Same technique, other tables

More practice on this pattern with different columns:

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