autovacuum_analyze_scale_factor

autovacuum_analyze_scale_factor — Number of tuple inserts, updates, or deletes prior to analyze as a fraction of reltuples. Observed in PG9.0–19 Beta 3; its last measured boot default is 0.1 in PG19 Beta 3, with sighup context. This is a beta-snapshot fact and can change before PostgreSQL 19 GA.

Note

Fact — official short description: “Number of tuple inserts, updates, or deletes prior to analyze as a fraction of reltuples.”

Identity

Type , Valuereal: Upstream pg_settings type
Context , Valuesighup: Takes effect after configuration reload
Unit , Value—: Raw unit
Range , Value0 – 100: Raw limits in the last observed version
Enum values , Value—: — for non-enum types
Category , ValueVacuuming / Automatic Vacuuming: Upstream classification
Latest boot value , Value0.1: 0.1

Lifecycle

Fact	Value
First observed	PG9.0 (research boundary)
Present in	PG9.0–19 Beta 3
Removed in	No
Introduction commit	Not asserted: predates the PG9.0 research boundary
Commit date	—
Discussion	—

Default history

Measured PG9.0–19 Beta 3 boot defaults
Versions	Raw `boot_val`	Unit	Human value
PG9.0–19 Beta 3	`0.1`	—	0.1

How it works

Number of tuple inserts, updates, or deletes prior to analyze as a fraction of reltuples. A configuration reload applies a new value; existing work already in flight is not retroactively changed.

The automatic-ANALYZE trigger is autovacuum_analyze_threshold plus autovacuum_analyze_scale_factor times pg_class.reltuples; inserts, updates, and deletes feed the cumulative counter. Per-table storage parameters can override the global values, and the statistics are eventually consistent estimates.

Monitor and change autovacuum_analyze_scale_factor together with autovacuum_analyze_threshold, default_statistics_target, track_counts. Validate on the relevant server role and real workload, then use its sighup context to choose session change, reload, or restart; a historical boot default is not the current effective value.

Tuning advice

Tip

Advice. These are workload-specific starting points and must be validated with measurements.

Workload	Guidance
OLTP	Tune autovacuum_analyze_scale_factor from table size, change rate, and maintenance SLA, using per-table thresholds for large/hot relations. Observe trigger intervals, dead tuples, and ANALYZE/VACUUM duration.
OLAP	Run explicit ANALYZE/VACUUM after bulk loads instead of waiting only for proportional triggers; plan freezing and visibility-map advancement separately for append-only partitions.
Small nodes	Start with upstream or the measured Pigsty matrix value. Fixed thresholds dominate on small tables; after changes, confirm worker and I/O headroom.

Pigsty

Values use the fixed 8-vCPU, 32-GiB, 100-GiB SSD fixture and render the current Pigsty templates for PG19 Beta 3; this does not assert current Pigsty support for that historical or beta release.

Template	Effective value	Versus upstream boot	Source expression
OLTP	`0.04`	different	`0.04`
OLAP	`0.04`	different	`0.04`
CRIT	`0.04`	different	`0.04`
TINY	Unmodified	—	—

Caution

Advice — pending human review. Fact from the current Pigsty template projection: OLTP: PG9.0–19 Beta 3 = 0.04 (dcs); OLAP: PG9.0–19 Beta 3 = 0.04 (dcs); CRIT: PG9.0–19 Beta 3 = 0.04 (dcs); TINY: PG9.0–19 Beta 3 unmodified. Advice, pending human review — Editorial interpretation, pending human maintainer review: the override appears intended to refresh planner statistics earlier on growing production tables; confirm it against the current Pigsty templates, hardware fixture, and operational guarantees before publication.

Common pitfalls

Changing the global value while a table storage parameter overrides it.
Treating reltuples and cumulative change statistics as exact real-time counts.
Blaming a threshold without checking long transactions, replication slots, and worker saturation.
Buying short-term quiet by deferring maintenance until wraparound failsafe activates.

autovacuum_analyze_threshold · default_statistics_target · track_counts · autovacuum · autovacuum_freeze_max_age · autovacuum_max_workers