HardSQL challenge #234WINDOW FUNCTIONPERCENTAGERUNNING TOTAL

Calculate the Cumulative Percentage of Revenue

Return each order total with the cumulative share of all revenue, from the largest order down.

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

Find cumulative revenue percentage.

A correct answer returns 200 rows with 2 columns: total, cum_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
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
totalcum_pct
4997.150.9779719076265642
4980.631.9527107532249741
4936.982.9189070348083157
4926.493.8830503611449663
4924.234.846751392070986

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
  • Attaching a total or average to every row with an aggregate OVER ()
  • Deriving a new column from an expression and naming it with an alias

Hint and approach

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

Show the hint

SUM OVER

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 total descending.
  3. Compute SUM(total) with an empty OVER (), so the figure for the whole result is repeated on every row.
  4. Combine those values into cum_pct: SUM(total) OVER (ORDER BY total DESC) * 100.0 / SUM(total) OVER ().

Model solution

Checking your session…

What to watch for

Two windows work together: one accumulates in descending order of total and the empty one supplies the grand total. This is the calculation behind a Pareto (80/20) analysis. Orders with equal totals share the same cumulative figure.

  • 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.
  • Window aggregates. A window aggregate keeps every row, while a plain aggregate collapses them. Mixing the two in one SELECT without GROUP BY is an error.
  • Calculated columns. Dividing one integer by another truncates the result in SQLite. Multiply one side by 1.0 to get decimals.
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