Batch Processing

Incremental vs full reload, watermarks, idempotent writes and reprocessing strategy. This path sequences the category's 6 resources by roadmap stage and composite score — work top-down inside each step.

Data Processing

1. Incremental Batch with a Watermark 37.25 — Incremental Batch with a Watermark
2. Idempotent Partition Overwrite 34.75 — Idempotent Partition Overwrite
3. The batch processing mental model 34.15 — The batch processing mental model
4. Capstone — the batch pipeline checklist 34.15 — Capstone — the batch pipeline checklist
5. Incremental processing with a watermark 34.15 — Incremental processing with a watermark
6. Missing partition 29.25 — Missing partition

• Name the four causes of a slow batch job: skew, partition count, spill, over-scan
• Explain what a shuffle does to a hot key
• State the idempotent-write invariant for re-runnable batch jobs
• Run a batch pipeline end to end with offline tests
• Prove idempotency with a two-run row-count check
• Ship the completeness, hardening, and baseline guards
• Bound incremental work with a watermark and a lookback window
• Write incremental output idempotently so a re-run is safe

Security-flagged: Missing partition — review the security posture first. Verification on these records: 6 community. Nothing here is independently audited — the trust scan and your own review are the controls.

Phase 1 of the roadmap. Stage context: Data Processing · side-by-side comparison · all learning topics