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max_parallel_apply_workers_per_subscription

max_parallel_apply_workers_per_subscription sets the maximum number of parallel apply workers per subscription. It is a sighup setting present in PG16–18; the latest recorded boot default is 2.
Note

Fact — official short description: “Maximum number of parallel apply workers per subscription.”

Identity

Type , Valueinteger
Upstream pg_settings type
Context , Valuesighup
Takes effect after configuration reload
Unit , Value
Raw unit
Range , Value01024
Raw limits in the last observed version
Enum values , Value
— for non-enum types
Category , ValueReplication / Subscribers
Upstream classification
Latest boot value , Value2
2

Lifecycle

Fact Value
First observed PG16
Present in PG16–19 Beta 3
Removed in No
Introduction commit 216a784829c2 — Perform apply of large transactions by parallel workers.
Commit date 2023-01-09
Discussion thread 1

Default history

Measured PG9.0–19 Beta 3 boot defaults
Versions Raw boot_val Unit Human value
PG16–19 Beta 3 2 2

How it works

Maximum number of parallel apply workers per subscription. A configuration reload applies a new value; existing work already in flight is not retroactively changed.

A subscription leader can use up to this many parallel workers to apply suitable in-progress transactions. More workers do not parallelize every transaction and consume the global logical-replication and background-worker pools.

Monitor and change max_parallel_apply_workers_per_subscription together with max_logical_replication_workers, max_sync_workers_per_subscription, max_worker_processes. 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 Size max_parallel_apply_workers_per_subscription from topology, failover roles, slot/subscription count, and reconnect headroom. Test worst-case primary latency, standby replay, and disk retention before production.
OLAP Read standbys and logical subscribers often see long queries or large transactions. Put explicit bounds on replay/apply and monitor lag, worker saturation, slot restart_lsn, and conflict cancellations.
Small nodes Configure only replication capacity that is actually used. Even a small topology needs bounded timeouts and slot lifecycle; unlimited retention is not reliability.

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 Unmodified
OLAP Unmodified
CRIT Unmodified
TINY Unmodified
Caution

Advice — pending human review. Fact from the current Pigsty template projection: OLTP: PG16–19 Beta 3 unmodified; OLAP: PG16–19 Beta 3 unmodified; CRIT: PG16–19 Beta 3 unmodified; TINY: PG16–19 Beta 3 unmodified. No Pigsty-specific rationale is inferred from an absent override.

Common pitfalls

  • Changing it on the wrong primary, standby, sender, or subscriber role.
  • Watching only configured bytes/time instead of actual lag, slot position, and worker state.
  • Failing over to a node that lacks the old primary’s capacity or prerequisites.
  • Using infinite waits or WAL retention to hide a failed consumer.

max_logical_replication_workers · max_sync_workers_per_subscription · max_worker_processes · max_replication_slots · max_active_replication_origins · hot_standby

References