HardSQL challenge #286JOINGROUP BYANALYSIS

Count Distinct Products Bought by Each Customer

Return each user with the number of different products they have ordered, most varied first.

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 users who ordered the highest number of distinct products.

A correct answer returns 114 rows with 2 columns: user_id, diversity.

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
user_iddiversity
7713
3712
9810
410
1249

First 5 of 114 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
  • Counting different values with COUNT(DISTINCT …)
  • Grouping rows with GROUP BY to get one result row per group
  • Combining rows from two tables on a matching key with an inner join
  • Sorting the result with ORDER BY

Hint and approach

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

Show the hint

COUNT DISTINCT product_id

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. Join order_items on orders.id = order_items.order_id.
  3. Group the rows by orders.user_id, so the result has one row for each value.
  4. For each group, compute COUNT(DISTINCT order_items.product_id), which counts each different value once.
  5. Sort the result by diversity descending.

Model solution

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What to watch for

The path is orders to order_items. A customer who bought the same product in three orders has three joined rows but one distinct product, which is why the count needs DISTINCT.

  • 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.
  • COUNT(DISTINCT). After a join, COUNT(*) counts joined rows. Counting the parent entity needs COUNT(DISTINCT its id).
  • 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.
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Same technique, other tables

More practice on this pattern with different columns:

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