HardSQL challenge #389WINDOW FUNCTIONGROUP BYPERCENTAGE

Top Revenue Contribution Products

Find products contributing highest percentage to total revenue.

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

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The task

Find products contributing highest percentage to total revenue.

A correct answer returns 119 rows with 2 columns: product_id, pct.

Tables used in this challenge

order_items 496 rows

id INTEGER (PK) · order_id INTEGER · product_id INTEGER · quantity INTEGER · unit_price REAL · subtotal REAL

First 3 rows of the order_items table
idorder_idproduct_idquantityunit_pricesubtotal
11765192.21961.05
21823107.1321.3
316515.395.39

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
product_idpct
1192.452710408004472
382.3258683116096046
602.0503148858723774
321.9265537311594283
511.8933695353978115

First 5 of 119 rows. This is the output of the model solution on the practice database.

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
  • Attaching a total or average to every row with an aggregate OVER ()
  • Sorting the result with ORDER BY
  • 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 subtotal / total SUM

Show the step-by-step approach

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

  1. Read from the order_items table.
  2. Group the rows by product_id, so the result has one row for each value.
  3. For each group, compute SUM(subtotal).
  4. Compute SUM(SUM(subtotal)) with an empty OVER (), so the figure for the whole result is repeated on every row.
  5. Combine those values into pct: SUM(subtotal) * 100.0 / SUM(SUM(subtotal)) OVER ().
  6. Sort the result by pct descending.

Model solution

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What to watch for

  • 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.
  • 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.
  • 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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