HardSQL challenge #239WINDOW FUNCTIONROLLING WINDOWAGGREGATION

Calculate a Rolling Sum with ROWS BETWEEN 6 PRECEDING

Return each order date with the combined total of that order and the six before it.

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 7-day rolling revenue.

A correct answer returns 200 rows with 2 columns: order_date, SUM(total) OVER (ORDER BY order_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW).

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
order_dateSUM(total) OVER (ORDER BY order_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW)
2022-01-061843.49
2022-01-105763.93
2022-01-156916.06
2022-01-1610307.72
2022-01-1714471.49

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

  • Limiting a window to nearby rows with ROWS BETWEEN

Hint and approach

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

Show the hint

ROWS BETWEEN 6 PRECEDING

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 window function over the current row and the 6 rows before it, ordered by order_date.

Model solution

Checking your session…

What to watch for

The frame is seven rows wide, not seven days: it adds seven consecutive orders. For a true 7-day revenue figure, aggregate to one row per day first and make sure days without orders are present.

  • Window frames. A ROWS frame counts rows, not time. "6 PRECEDING" is six rows back, which is six days only when there is exactly one row per day.
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Same technique, other tables

More practice on this pattern with different columns:

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