Keep performance fixtures useful after the inbox schema changes
A new nullable column changed the seed loader. The benchmark still completes, but most rows now take a cheap fallback path that users rarely see.
- Focused work estimate
- 2h + prerequisites
- Priority in the scenario
- Medium
- Engineering practice
- Regression fixtures · Data validation
Estimated field mix
- Quality engineering50%
- Data engineering30%
- Performance engineering20%
Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.
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Project context
A fictional maintenance service lists open work orders beside years of closed history. A query that was cheap in a small demo now scans far more rows than it returns. Recreate the schema and synthetic workload locally; no customer database or supplied fixture is assumed.
Setup prerequisites
- Create an isolated local database with tenants, work orders and assignment history.
- Seed 200,000 synthetic work orders with documented skew and a repeatable random seed; record PostgreSQL version, settings and resource limits.
Preceding work
Complete these dependencies, or supply their agreed outputs before taking this ticket.
- PQUERY-101 · Seed an inbox where one tenant owns most of the closed history
- PQUERY-102 · Capture buffer reads and row estimates for the slow inbox query
- PQUERY-103 · Count hidden assignment queries made by one inbox request
- PQUERY-104 · Batch latest-assignee lookup for the current inbox page
- PQUERY-106 · Replace deep offset paging with a stable inbox cursor
Acceptance criteria
- Validate row counts, state distributions, null ratios and assignment fan-out before a run.
- Reject fixtures whose version or invariants do not match the query comparison manifest.
- Retain representative expected responses so a faster wrong query cannot pass.
Implementation constraints
- Express fixture invariants separately from the query implementation; avoid asserting only that SQL returns some rows.
Verification to include
- Deliberately skew null ratios and remove assignment history; the fixture gate must report both changes.
- Regenerate the approved fixture and run the same checks successfully without hand-edited counts.
Deliverables
- Fixture-validation command and schema-change procedure
Rollout and recovery
Run validation before every benchmark; invalid data stops comparison and is rebuilt in the disposable database.
Value of the work
For the engineer: Practice reading execution plans, balancing read and write cost, and validating performance without weakening tenant boundaries.
For the team: Create reproducible query diagnostics and reversible index or query proposals for an operational application.
Evidence boundaries
Outcome Evidence: Tests, patches, and runbooks are requested deliverables. They become Outcome Evidence only through a qualified Mission and immutable Evidence IDs.
Ownership Evidence: Independent adaptation must be observed under a declared verification policy and cite immutable Evidence IDs. Completing a planning ticket establishes no Ownership Evidence.