pruning

DE//AGENT currently lists 2 resources under pruning: 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:

• Map a too-big scan to its layout cause — statistics, row groups, encodings — via Format-driven performance incidents — small scans and wrong layouts
• Explain how pruning fails when statistics are absent — via Format-driven performance incidents — small scans and wrong layouts
• Use the lifecycle's cost undercurrent to size the blast radius — via Format-driven performance incidents — small scans and wrong layouts
• Choose a clustering key from predicate selectivity — via Make queries prune — clustering keys and scan diagnosis
• Prove pruning with partitions_scanned versus partitions_total — via Make queries prune — clustering keys and scan diagnosis
• Fix the scan or compute problem you actually measured — via Make queries prune — clustering keys and scan diagnosis

These resources map to stages: Foundations (1), Warehousing (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. Format-driven performance incidents — small scans and wrong layouts score 34.15 — intermediate
2. Make queries prune — clustering keys and scan diagnosis score 34.15 — intermediate

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

• Format-driven performance incidents — small scans and wrong layouts — When a scan reads the whole lake for one column, the cause is usually the file layout, not the engine — missing statistics, row groups sized without intent, encodings chosen by def… details
• Make queries prune — clustering keys and scan diagnosis — Choose a clustering key from the predicates of your most expensive queries, prove the prune with partitions_scanned versus partitions_total, and fix the disease you actually have —… details

Adjacent topics: tutorial (2 shared), performance (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.