Prove temporary import resources disappear after cancellation
Cancelled imports leave temporary files and open connections. A subsequent run inherits resource pressure and appears slower for an unrelated reason.
- Focused work estimate
- 3h + prerequisites
- Priority in the scenario
- Medium
- Engineering practice
- Resource lifecycle · Cancellation
Estimated field mix
- Site reliability40%
- Data engineering30%
- Performance engineering30%
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 wholesaler imports supplier rows into a staging catalog. The current prototype reads the entire file into memory and restarts from zero after a failure. Build the prototype and generated CSV fixture locally before measuring improvements.
Setup prerequisites
- Generate a deterministic 250,000-row synthetic CSV with quoted newlines, invalid records and a stated maximum record size.
- Create a disposable staging database and an import process constrained to 256 MiB; record runtime and available CPU.
Preceding work
Complete these dependencies, or supply their agreed outputs before taking this ticket.
- PBATCH-101 · Generate a catalog file that includes difficult CSV boundaries
- PBATCH-102 · Measure peak import memory across parsing, validation and writes
- PBATCH-103 · Attribute import time to parsing, validation and database waits
- PBATCH-104 · Stream records without buffering the rest of the catalog
- PBATCH-105 · Batch staging writes without changing duplicate-SKU behavior
- PBATCH-106 · Stop validation workers from creating an unbounded reorder queue
- PBATCH-107 · Report import progress from committed records instead of bytes read
- PBATCH-108 · Resume an interrupted catalog import from a committed checkpoint
Acceptance criteria
- Define ownership and cleanup for temporary files, file descriptors, workers and database connections.
- Cancel safely at read, validation and commit stages while preserving the last valid recovery checkpoint.
- Make repeated cancellation safe and keep the source fixture intact.
Implementation constraints
- Check resource inventories before and after; avoid asserting cleanup from a completion message alone.
Verification to include
- Cancel at each controlled stage and verify owned resources return to the declared baseline.
- Run cancellation twice, then resume or start a fresh import and confirm correct results without restarting the environment.
Deliverables
- Cleanup implementation, resource inventory and cancellation regressions
Rollout and recovery
Run cleanup rehearsal before accepting performance results; quarantine uncertain staging state for explicit recovery rather than deleting it silently.
Value of the work
For the engineer: Practice streaming, backpressure, allocation analysis and resumable work while retaining exact import semantics.
For the team: Develop a repeatable import performance and recovery exercise that exposes memory, throughput and data-quality tradeoffs.
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.