MediumSQL challenge #123HAVING

Find Orders with More Than 3 Items Using HAVING SUM

Return the orders whose line quantities add up to more than three items.

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 orders having more than 3 items.

A correct answer returns 170 rows with 2 columns: order_id, qty.

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_idqty
19
35
45
515
65

First 5 of 170 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
  • Filtering groups after aggregation with HAVING

Hint and approach

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

Show the hint

HAVING

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).
  4. Filter the groups in HAVING: keep those where qty is greater than 3.

Model solution

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What to watch for

SQLite lets HAVING refer to the alias defined in the SELECT list. PostgreSQL and SQL Server do not, and need the SUM(quantity) expression repeated there.

  • HAVING. Conditions on single rows belong in WHERE and conditions on aggregates in HAVING. Putting a row filter in HAVING works, but it groups rows that are about to be thrown away.
  • 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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