Preparing the next view without exposing private workflow data.
Performance engineering · Phased project
Import a large supplier catalog without exhausting the worker
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.
Practice brief · Version 5
Project scope
10 tickets / 3 phases
Total focused work estimate
33h 45m + setup
Suggested stack
TypeScript · Node.js streams · PostgreSQL · CSV
Recommended next step
Start with PBATCH-101
Open the first ticket for its prerequisites, acceptance criteria, verification plan, and an editable task draft.
Practice streaming, backpressure, allocation analysis and resumable work while retaining exact import semantics.
What the team gains
Develop a repeatable import performance and recovery exercise that exposes memory, throughput and data-quality tradeoffs.
Before you start
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.
Delivery agreement
Ten tickets in three phases. All data and failures are locally generated; throughput targets are relative to the declared baseline and do not imply a production service-level guarantee.
AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.