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NULL and Three-Valued Logic / write query
M09-A06 - Transfer checkpoint - combine a null branch with a non-null condition
M09-A06 - Transfer checkpoint - combine a null branch with a non-null condition. Reason about missing information with IS NULL and unknown Boolean results.
- Result grain
- one product row matching either a NULL category branch or a known-category zero-stock active branch
- Exact columns
- product_id; product_name; category; stock_count; discontinued
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Cursor at line 1, column 1.
Scenario
Reason about missing information deliberately: compare NULL with IS predicates, classify UNKNOWN separately, and keep empty strings, zeroes, and false booleans distinct from absence.
NULL and Three-Valued Logic / write query
One-sentence task
M09-A06 - Transfer checkpoint - combine a null branch with a non-null condition. Reason about missing information with IS NULL and unknown Boolean results.
Learn mode disclosure
Theory, concept names, full schema help, and progressive hints are available.
Structured output contract
- Result grain
- one product row matching either a NULL category branch or a known-category zero-stock active branch
- Exact columns
- product_id; product_name; category; stock_count; discontinued
- 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
- order by product_id
- Validation
- select-only; hidden deterministic variants.
Relevant tables
Time and difficulty
- Estimated time
- 9 minutes
- Difficulty
- 3/5
Objective and concepts
Debug the requested SQL output contract for null and three-valued logic 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
A NULL restock_date makes the comparison UNKNOWN, not false; the CASE keeps all three outcomes visible.
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 product_id, product_name, CASE WHEN restock_date < DATE '2026-02-01' THEN 'TRUE' WHEN NOT (restock_date < DATE '2026-02-01') THEN 'FALSE' ELSE 'UNKNOWN' END AS restock_before_feb FROM products ORDER BY product_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.
- NULL is not a comparable value: A missing value is tested with equals or not equals and no rows behave as expected. Repair: Use IS NULL for missing values and IS NOT NULL for known values.
- UNKNOWN is not false: Rows with NULL comparisons are treated as if the comparison returned ordinary false. Repair: Classify TRUE, FALSE, and UNKNOWN separately before deciding which rows survive a WHERE clause.
- Fallback display is not filtering: COALESCE is used to show a label and assumed to have selected missing rows. Repair: Filter with IS NULL or IS NOT NULL, then use COALESCE only when the output should display a fallback.
- Empty zero and false are still values: Empty text, zero counts, or false booleans are treated as missing information. Repair: Keep NULL separate from empty strings, whitespace, zero, and false unless the contract explicitly normalizes them.
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