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Build a single directory combining customers from USA and employees from Canada for an upcoming North-America summit.
| Column | Type |
|---|---|
| CustomerId | INTEGER (PK) |
| FirstName | TEXT NOT NULL |
| LastName | TEXT NOT NULL |
| Company | TEXT |
| Country | TEXT |
| TEXT NOT NULL | |
| SupportRepId | INTEGER (FK → Employee) |
| Column | Type |
|---|---|
| EmployeeId | INTEGER (PK) |
| LastName | TEXT NOT NULL |
| FirstName | TEXT NOT NULL |
| Title | TEXT |
| ReportsTo | INTEGER (FK → Employee) |
| BirthDate | TIMESTAMP |
| HireDate | TIMESTAMP |
| Country | TEXT |
FullName, Country, RoleTypeTitle contains 'Manager' (case-insensitive), else 'Staff'Your query should return 21 rows with 3 columns: | fullname | country | roletype | |-----------------|---------|----------| | Dan Miller | USA | Customer | | Frank Harris | USA | Customer | | Frank Ralston | USA | Customer | | Heather Leacock | USA | Customer | | Jack Smith | USA | Customer | | ... | ... | ... |
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 FirstName || ' ' || LastName AS FullName,
Country,
'Customer' AS RoleType
FROM Customer
WHERE Country = 'USA'
UNION ALL
SELECT FirstName || ' ' || LastName AS FullName,
Country,
CASE WHEN Title ILIKE '%Manager%' THEN 'Manager' ELSE 'Staff' END AS RoleType
FROM Employee
WHERE Country = 'Canada'
ORDER BY RoleType ASC, FullName 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
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