MediumSQL challenge #135GROUP BY

Summarise Each Order: Total Quantity and Amount

Return one row per order with its total item quantity and total amount.

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

Get total quantity and total amount per order.

A correct answer returns 200 rows with 3 columns: order_id, qty, amount.

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
order_idqtyamount
191287.74
21494.29
35722.6800000000001
4533.75
5153765.82

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

  • 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

Hint and approach

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

Show the hint

SUM(quantity), SUM(subtotal)

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 order_id, so the result has one row for each value.
  3. For each group, compute SUM(quantity) and SUM(subtotal).

Model solution

Checking your session…

What to watch for

The amounts come from summing order_items.subtotal. In this practice dataset they do not match orders.total, because the two tables were generated independently; do not expect them to reconcile.

  • 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(*).
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Same technique, other tables

More practice on this pattern with different columns:

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