Backfill document timestamps without guessing missing offsets
Legacy created-at values mix UTC strings with offset-free dates; blindly casting them uses the database session timezone.
- Focused work estimate
- 4h + prerequisites
- Priority in the scenario
- Medium
- Engineering practice
- Data migration · Time zones
Estimated field mix
- Database engineering60%
- Data engineering40%
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 records portal stores every property in one JSON column. Queries disagree about missing values, and malformed records make ordinary filters fail.
Setup prerequisites
- Create synthetic document metadata with malformed and legacy versions.
- Use migrations and a local query API.
Preceding work
Complete these dependencies, or supply their agreed outputs before taking this ticket.
- AMETA-101 · Separate stable document identity fields from flexible attributes
- AMETA-102 · Define versioned metadata schemas with explicit size and depth limits
- AMETA-103 · Choose distinct semantics for absent, null and empty metadata values
- AMETA-104 · Extract stable document fields through an additive migration
Acceptance criteria
- Convert only timestamps with an unambiguous documented interpretation.
- Quarantine missing-offset and malformed values.
- Use resumable batches with counts by conversion outcome.
Implementation constraints
- Preserve original metadata for later review.
Verification to include
- Backfill valid offset-bearing values under two session timezones with identical UTC results.
- Process ambiguous dates and retain null target fields plus explicit errors.
Deliverables
- Timestamp backfill and timezone regression
Rollout and recovery
Dry-run first; pause on unexpected conversion categories and keep the checkpoint.
Value of the work
For the engineer: Practice relational/JSON boundaries, versioned validation and query semantics.
For the team: Review a data model that stays inspectable while allowing controlled variation.
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.