Candidate telemetry diagnostic, error autopsy, and step-by-step query construction walkthrough.
Live aggregated metrics across candidate sandbox attempts
50 solved
First attempt fail
Evaluated submissions
Median time to solve
Unlocked answer
Calculate each genre's share of total tracks as a percentage. This requires comparing individual counts to the overall total.
Write a query showing each genre's track count and percentage of total tracks.
| Column | Type |
|---|---|
| GenreId | INTEGER (Primary Key) |
| Name | TEXT |
| Column | Type |
|---|---|
| TrackId | INTEGER (Primary Key) |
| Name | TEXT |
| AlbumId | INTEGER (Foreign Key → Album.AlbumId) |
| MediaTypeId | INTEGER (Foreign Key) |
| GenreId | INTEGER (Foreign Key → Genre.GenreId) |
| Composer | TEXT |
| Milliseconds | INTEGER |
| Bytes | INTEGER |
| UnitPrice | NUMERIC(10,2) |
(genre_count * 100.0) / (total_count)
Your result should show genre percentages: | GenreName | TrackCount | Percentage | |--------------------|------------|------------| | Rock | 1297 | 37.03 | | Latin | 579 | 16.53 | | Metal | 374 | 10.68 | | Alternative & Punk | 332 | 9.48 | | Jazz | 130 | 3.71 | | ... | ... | ... | Rock dominates with 37% of all tracks!
Double-counting metrics by using COUNT(*) after joining parent and child tables. When joining an invoice table with an invoice lines table, a single invoice multiplies across all its line items, causing COUNT(invoice_id) to return line counts instead of unique invoice counts.
Interviewers check whether you notice 1-to-many cardinality multiplication and use COUNT(DISTINCT col) or pre-aggregate child records before joining.
Construct the solution logically from first principles to avoid typical edge case pitfalls.
Identify the base table and apply preliminary WHERE filters.
FROM TableName WHERE is_active = true
Group by primary business keys and compute aggregate expressions.
SELECT category, COUNT(DISTINCT item_id) AS total_items, SUM(amount) AS revenue GROUP BY category
Order by specified metrics descending and apply limit clauses.
ORDER BY revenue DESC LIMIT 10;
SELECT Genre.Name AS GenreName, COUNT(*) AS TrackCount, ROUND(COUNT(*) * 100.0 / (SELECT COUNT(*) FROM Track), 2) AS Percentage FROM Genre JOIN Track ON Genre.GenreId = Track.GenreId GROUP BY Genre.GenreId ORDER BY Percentage DESC, Genre.Name ASC;
Real code patterns candidates submit that fail the grading suite.
SELECT a.Name, COUNT(t.TrackId) FROM Artist a JOIN Album al ON a.ArtistId = al.ArtistId JOIN Track t ON al.AlbumId = t.AlbumId GROUP BY a.Name;
Three recurring syntax and semantic traps relevant to this problem domain.
Joining a fact table with child lines multiplies fact table rows, distorting sums and counts.
SELECT c.id, SUM(i.total) FROM customer c JOIN invoice i ON c.id = i.customer_id JOIN invoice_line il ON i.id = il.invoice_id -- ❌ Inflated SUM
SELECT c.id, SUM(i.total) FROM customer c JOIN invoice i ON c.id = i.customer_id GROUP BY c.id; -- ✅ Avoids line multiplication
Using COUNT(*) when duplicate rows exist due to joins counts duplicate records.
SELECT artist_id, COUNT(album_id) ... -- ❌ Counts duplicate occurrences
SELECT artist_id, COUNT(DISTINCT album_id) ... -- ✅ Distinct unique entities
In SQL, dividing integers like 5 / 10 results in 0. Cast at least one operand to FLOAT or NUMERIC.
SELECT solved_count / total_count AS rate ... -- ❌ Returns 0
SELECT CAST(solved_count AS FLOAT) / total_count AS rate ... -- ✅ Returns 0.5
Launch our in-browser coding environment. Run queries, view execution plans, and get instant comparative diff grading with no setup.