spill

DE//AGENT currently lists 2 resources under spill: 2 tutorials. 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:

• Collect the four pieces of evidence a failing Spark run needs — via The 3am batch incident path
• Decide between revert, a config change, and a code fix — via The 3am batch incident path
• Record the skew/spill/scan signature for the cost-per-run history — via The 3am batch incident path
• Classify a slow stage into skew, partition count, spill, or scan — via Tune a slow job — memory, partitions, baselines
• Apply the single highest-impact fix with an expected effect — via Tune a slow job — memory, partitions, baselines
• Verify the change against baseline shuffle/spill/scan metrics — via Tune a slow job — memory, partitions, baselines

These resources map to stage: Data Processing (2). 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. The 3am batch incident path score 34.15 — advanced
2. Tune a slow job — memory, partitions, baselines score 34.15 — advanced

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

Reach for these with production experience: The 3am batch incident path, Tune a slow job — memory, partitions, baselines.

• The 3am batch incident path — The nightly job is crawling or dead under memory pressure or skew. Follow the incident path: collect the four pieces of evidence, read p50 vs p99 and the spill bytes, decide revert… details
• Tune a slow job — memory, partitions, baselines — Run the tuning loop on a slow batch job: parse task-duration and shuffle metrics, classify the stage as skew, partition count, spill or scan, apply the single highest-impact change… details

Adjacent topics: tutorial (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.