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Multiple Columns, Column Order, and Aliases / write query
M03-A06 - Contract checkpoint - produce three columns with exact aliases and order on a transfer table
M03-A06 - Contract checkpoint - produce three columns with exact aliases and order on a transfer table. Match exact output contracts for columns, order, and report-friendly aliases.
- Result grain
- one commerce customer row with three exact report aliases
- Exact columns
- customer_number; customer_label; sales_region
SQL editor shortcuts: Ctrl or Command Enter runs the query, Ctrl or Command Shift Enter checks it, Alt H opens the next hint, Ctrl or Command slash toggles a line comment, Ctrl or Command Shift F formats the SQL, and Escape closes transient UI.
Cursor at line 1, column 1.
Scenario
Match exact projection contracts: column count, header names, header order, aliases, and source-versus-result identifier boundaries.
Multiple Columns, Column Order, and Aliases / write query
One-sentence task
M03-A06 - Contract checkpoint - produce three columns with exact aliases and order on a transfer table. Match exact output contracts for columns, order, and report-friendly aliases.
Learn mode disclosure
Theory, concept names, full schema help, and progressive hints are available.
Structured output contract
- Result grain
- one commerce customer row with three exact report aliases
- Exact columns
- customer_number; customer_label; sales_region
- Source population
- Use the prompt setup plus FROM, JOIN, WHERE, and subquery predicates as the source population. Visible rows are only examples.
- Grouping
- Do not collapse rows unless the contract explicitly asks for aggregation, distinct tuples, or set semantics.
- Ordering
- keep aliases in that exact order; order by customer_id
- Validation
- select-only; hidden deterministic variants.
Relevant tables
Time and difficulty
- Estimated time
- 9 minutes
- Difficulty
- 2/5
Objective and concepts
Debug the requested SQL output contract for multiple columns, column order, and aliases using source grain, columns, ordering, and edge-case evidence.
Glossary links
Concept material
SQL Trail treats every query as an evidence trail: identify source grain, transform rows deliberately, then compare output to a shared contract.
A passing query must handle hidden nulls, ties, boundaries, and no-match rows when the contract makes them relevant.
Syntax card
SELECT <requested_columns>
FROM <source_table>
WHERE <source_population_filter>
GROUP BY <result_grain_columns>
ORDER BY <deterministic_tie_breakers>;- <requested_columns> means the exact output columns, aliases, and order from the visible contract.
- <source_population_filter> means the row population definition, not a copied visible-row value.
- <deterministic_tie_breakers> means all ordering and tie rules needed for repeatable output.
Why this works
AS changes the result header to order_number while the source schema column remains order_id.
Edge cases
Hidden variants preserve nulls, ties, duplicates, boundaries, no-match rows, and alternate row order when those risks apply.
PostgreSQL note
The local engine uses PostgreSQL-compatible syntax, including explicit NULL predicates, deterministic ORDER BY clauses, and transactional grading.
Worked example
SELECT order_id AS order_number FROM orders ORDER BY order_id;Assumptions, dialect notes, and common traps
- Duplicate policy
- Preserve duplicate facts unless the prompt explicitly asks for distinct tuples or set semantics.
- Null policy
- Preserve NULL, empty string, zero, and false as distinct values unless the contract says to display a fallback.
- Tie-breakers
- Use every ordering rule in the contract and end tied business metrics with deterministic secondary keys when needed.
- Zero-related entities
- Do not invent zero rows unless the contract asks for preserved parents, missing entities, or complete periods.
- Numeric tolerance
- Use exact semantic comparison unless the activity explicitly declares a numeric tolerance.
PostgreSQL-compatible local checks
Queries run in a local PGlite worker with PostgreSQL-style syntax and transactional grading.
- Aliases do not rename the source schema: The learner tries to reference a result alias as if it were a stored column. Repair: Use source column names in expressions and reserve aliases for output headers or supported ORDER BY positions.
- Output order follows SELECT order: The result columns are expected to follow physical table order instead of the requested contract. Repair: Arrange expressions in the SELECT list exactly as the output contract states.
- Commas separate result expressions: Two adjacent column names are parsed as an alias or produce a syntax error. Repair: Place commas between every projected expression before adding aliases.
- Aliases have limited scope: An alias is reused inside another expression in the same SELECT list. Repair: Repeat the source expression or stage the query later when alias reuse is needed.
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