HardSQL challenge #287GROUP BYJOINANALYSIS

Find Products That Customers Buy More Than Once

Return each product with the number of customers who ordered it at least twice.

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

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The task

Find products most frequently reordered by same users.

A correct answer returns 6 rows with 2 columns: product_id, repeat_count.

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

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_idrepeat_count
1131
651
591
291
231
51

The complete result: 6 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
  • Grouping by more than one column to get a row per combination
  • Filtering groups after aggregation with HAVING
  • Combining rows from two tables on a matching key with an inner join
  • Querying the result of another query with a subquery in FROM
  • Sorting the result with ORDER BY

Hint and approach

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

Show the hint

GROUP BY product_id, user_id

Show the step-by-step approach

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

  1. Build an inner query first (a derived table):
    1. Read from the orders table.
    2. Join order_items on orders.id = order_items.order_id.
    3. Group the rows by orders.user_id and order_items.product_id, so the result has one row for each combination.
    4. For each group, compute COUNT(*).
    5. Filter the groups in HAVING: keep those where COUNT(*) is greater than 1.
  2. Group the rows by product_id, so the result has one row for each value.
  3. For each group, compute COUNT(*).
  4. Sort the result by repeat_count descending.

Model solution

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What to watch for

The inner query finds user and product pairs that occur more than once; the outer query counts those pairs per product. Two lines for the same product within one order also count as a repeat here, since the pairs are built from order lines.

  • Derived table. Columns computed in the inner query are only visible outside under their alias, so every calculated column there needs a name.
  • INNER JOIN. An inner join drops rows that have no partner on the other side, and it repeats a row once for every match, which inflates SUM and COUNT.
  • 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.
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Same technique, other tables

More practice on this pattern with different columns:

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