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Text Matching and Normalization / write query
M08-A06 - Normalization checkpoint - compare normalized city text while preserving display
M08-A06 - Normalization checkpoint - compare normalized city text while preserving display. Distinguish exact text, patterns, case-insensitive matching, and deliberate normalization.
- Result grain
- one customer row whose normalized city equals austin
- Exact columns
- customer_id; customer_name; city
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 text deliberately: choose LIKE, percent, underscore, ILIKE, and column-side normalization based on the exact wording instead of visible-row luck.
Text Matching and Normalization / write query
One-sentence task
M08-A06 - Normalization checkpoint - compare normalized city text while preserving display. Distinguish exact text, patterns, case-insensitive matching, and deliberate normalization.
Learn mode disclosure
Theory, concept names, full schema help, and progressive hints are available.
Structured output contract
- Result grain
- one customer row whose normalized city equals austin
- Exact columns
- customer_id; customer_name; city
- 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 customer_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 text matching and normalization 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
PostgreSQL ILIKE performs a case-insensitive pattern match; plain LIKE remains case-sensitive.
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 customer_id, customer_name, city FROM customers WHERE city ILIKE 'austin' ORDER BY customer_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.
- Percent is arbitrary length: A percent wildcard is treated as if it matched exactly one character. Repair: Use percent for any-length prefixes, suffixes, or substrings, and underscore for a single unknown character.
- LIKE is case-sensitive here: A lower-case pattern is expected to match Austin without requesting case-insensitive behavior. Repair: Use ILIKE when the requirement explicitly says case-insensitive.
- Wildcards are not equality text: A pattern such as percent Trail percent is compared with equals and returns no contains matches. Repair: Use LIKE for wildcard patterns and equals only for exact stored text.
- Normalize the stored value: Only the literal is lowercased or trimmed, leaving mixed-case or spaced source rows unmatched. Repair: Apply LOWER and TRIM to the city column for comparison while selecting the original city for display.
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