batch

DE//AGENT currently lists 8 resources under batch: 3 tutorials, 3 patterns, 2 runbooks. Everything below is derived from the live registry — counts, capabilities, verification state and security posture come from the curated records, never from marketing copy.

Documented learning objectives across these resources:

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

1 more objectives live on the individual resource pages.

These resources map to stages: Data Processing (7), Streaming (1). Follow the four-phase roadmap to place this topic inside a progression instead of learning it in isolation.

Every entry, its shape and its trust state — sorted by the registry's composite score. This table is the honest version of a marketing comparison: no sponsored placements, no unverifiable claims.

How scores are computed: source quality score.

Highest composite score first:

1. Incremental Batch with a Watermark score 37.25 — intermediate
2. Idempotent Partition Overwrite score 34.75 — beginner
3. Lambda vs Kappa (batch + stream) score 34.75 — advanced

Scores rank provenance, completeness and trust — read how verification works before adopting anything.

Start here if you're new: Idempotent Partition Overwrite, The batch processing mental model.

Reach for these with production experience: Lambda vs Kappa (batch + stream).

Security-flagged entries: Late files (3 flags), Missing partition (3 flags). Flags mean the record declares capabilities like credential use or write access — read the security posture on each page before connecting.

Known limits: Little history,Frequently mutating data without a reliable change marker (use CDC) (Incremental Batch with a Watermark)

• The batch processing mental model — Batch processing in partition terms. Learn what a partition, a shuffle and a spill are, why "the job is slow" resolves into four named causes — skew, partition count, spill, over-s… details
• Capstone — the batch pipeline checklist — Bring the API → S3 → Spark → Parquet starter up end to end, then audit it: offline transform tests, idempotent partition-scoped writes, complete partitions, replay-safe extraction,… details
• Incremental processing with a watermark — Full reloads stop scaling once a table grows past millions of rows. Process a bounded window instead: a watermark ends it, a lookback absorbs late files, and an idempotent write (p… details

Adjacent topics: tutorial (3 shared), architecture (3 shared), idempotency (2 shared), partitions (2 shared), incremental (2 shared), watermark (2 shared).

Study path: the roadmap places this topic in a progression · the scoring model explains the numbers · the trust rule catalog shows every security check these entries passed through.