Consistent Daily Sales Products
Find products with lowest variance in daily sales.
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.
The task
Find products with lowest variance in daily sales.
A correct answer returns 119 rows with 2 columns: product_id, variance.
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
| id | user_id | total | discount | item_count | status | order_date | shipped_date | shipping_city | shipping_country |
|---|---|---|---|---|---|---|---|---|---|
order_items 496 rows
id INTEGER (PK) · order_id INTEGER · product_id INTEGER · quantity INTEGER · unit_price REAL · subtotal REAL
| id | order_id | product_id | quantity | unit_price | subtotal |
|---|---|---|---|---|---|
The first rows of each table are shown. See how all the tables relate on the database schema page.
Expected output
| product_id | variance |
|---|---|
First 5 of 119 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
- 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
- Deriving a new column from an expression and naming it with an alias
Hint and approach
Try the challenge first. Open these only when you need them.
Show the hint
variance formula
Show the step-by-step approach
How the model solution is built, in the order the database evaluates it:
- Build an inner query first (a derived table):
- Read from the
order_itemstable. - Join
ordersonorder_items.order_id=orders.id. - Group the rows by
order_items.product_idandorders.order_date, so the result has one row for each combination. - For each group, compute
SUM(order_items.quantity).
- Read from the
- Group the rows by
product_id, so the result has one row for each value. - For each group, compute
AVG(sales*sales)andAVG(sales). - Calculate
variancefrom those aggregates:AVG(sales*sales) - AVG(sales)*AVG(sales). - Sort the result by
variance.
Model solution
Checking your session…
What to watch for
- 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.
- GROUP BY on several columns. Each extra GROUP BY column splits the groups further. Grouping by a column that is unique per row gives back one group per row.
Related SQL challenges
- Measure Monthly Revenue Volatility per ProductSimilar levelHard
- Find Products That Customers Buy More Than OnceSimilar levelHard
- Calculate Revenue and Units Sold per Product CategoryEasierMedium
- Find Each Customer's Busiest Day by Order CountSimilar levelHard
- Calculate Month-over-Month Revenue Change per ProductSimilar levelHard
Keep learning
- Lesson: SQL Subqueries
- Lesson: INNER JOIN
- Lesson: GROUP BY Multiple Columns
- Lesson: GROUP BY
- All SQL practice challenges, by difficulty and topic
- SQL interview questions with answers
- SQL Playground: run any query on the same database