MediumSQL challenge #147SUBQUERY

Orders with High Item Count

Find orders with item count above average.

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 orders with item count above average.

A correct answer returns 105 rows with 10 columns: id, user_id, total, discount, item_count, status, order_date, shipped_date, shipping_city, shipping_country.

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
iduser_idtotaldiscountitem_countstatusorder_dateshipped_dateshipping_cityshipping_country
2829470.195delivered2024-03-152023-04-09ChicagoUSA
41153920.440.084processing2022-01-10NULLSan JoseUSA
51401120.990.134delivered2023-06-162023-12-21DenverUSA
6501327.010.085shipped2024-02-162024-12-13SeattleUSA
1678724.780.014delivered2022-11-262024-10-04ColumbusUSA

First 5 of 105 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

  • Returning every column of a table with SELECT *
  • Filtering rows with a WHERE condition
  • Summarising many rows into one value with COUNT, SUM, AVG, MIN or MAX
  • Using the result of one query inside another

Hint and approach

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

Show the hint

AVG(item_count)

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. Filter in WHERE: keep the rows where item_count is greater than the value returned by a subquery.
  3. The subquery runs once and returns a single value. It works like this:
    1. Read from the orders table.
    2. Aggregate over all the rows that are left: compute AVG(item_count). With no GROUP BY, the result is a single row.
  4. Return every column with SELECT *.

Model solution

Checking your session…

What to watch for

  • Subquery. A subquery compared with =, > or < must return exactly one row and one column. If it can return several rows, use IN or an aggregate.
  • Aggregate functions. Aggregates skip NULLs. AVG divides by the number of non-NULL values and COUNT(column) can be smaller than COUNT(*).
  • WHERE. WHERE is evaluated before the SELECT list, so it cannot use a column alias defined there or the result of an aggregate.
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