The Tool Desk
Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →For background jobs in a PostgreSQL-backed application, a common starting point is a durable jobs table and bounded claims using FOR UPDATE SKIP LOCKED. PostgreSQL coordinates which transaction claims a row; your application or queue library must define retries, delivery guarantees, ordering scope, fairness, and recovery. Treat handlers as repeatable, use an explicit claim order, and use notifications only to wake workers—not as the record of pending work.
How do PostgreSQL workers claim jobs concurrently?
A worker can select eligible rows, lock them, and update their state in one short transaction. FOR UPDATE prevents concurrent transactions from updating the selected rows while the lock is held. SKIP LOCKED lets another worker skip rows already locked instead of waiting at the same queue head. PostgreSQL describes this as useful for multiple consumers of a queue-like table, while warning that it returns an inconsistent view of the data. It is not a general-purpose way to read a consistent snapshot. See the PostgreSQL 17 SELECT documentation.
WITH picked AS (
SELECT id
FROM jobs
WHERE state = 'ready'
AND run_at <= now()
ORDER BY priority DESC, run_at, id
FOR UPDATE SKIP LOCKED
LIMIT 20
)
UPDATE jobs AS j
SET state = 'running',
claimed_at = now(),
attempts = attempts + 1
FROM picked
WHERE j.id = picked.id
RETURNING j.*;This illustrates a query shape, not a schema or performance guarantee. The eligibility predicate identifies due work, the ordering defines selection preference, the unique id breaks ties, and the limit bounds each claim. Commit the claim promptly if processing involves slow external work. Check the execution plan, indexes, transaction behavior, batch size, and recovery strategy against your PostgreSQL version and workload.
Do not hold row locks for the full duration of a long-running handler unless that is an intentional design. A lease-based design instead commits a claim with an expiry and needs recovery logic for expired leases. It also needs protection against an old worker completing after a newer attempt has reclaimed the job. PostgreSQL row locks coordinate database transactions; they do not supply that lease policy automatically.
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What does SKIP LOCKED guarantee?
It avoids waiting for rows whose row locks cannot be acquired immediately. It does not ensure that every eligible job is claimed promptly, prevent ordinary table-level locking, or promise fairness. Advisory locks are another PostgreSQL coordination primitive, but their meaning is an application protocol: session-level locks remain until released or the session ends, while transaction-level locks end with the transaction. PostgreSQL does not force every code path to follow the same advisory-lock convention.
Do retries make job effects exactly once?
No. A row can be claimed by one worker at a time while the claim transaction is active, but a crash, lost acknowledgement, or uncertain outcome can cause work to be attempted again. The pg-boss documentation explicitly describes its own delivery as at least once and advises handlers to tolerate repeat execution; that statement is specific to pg-boss, not a universal guarantee for every PostgreSQL queue. See the pg-boss introduction.
Exactly-once effects across a PostgreSQL transaction and an unrelated service are not achieved merely by locking a job row. A payment API, email provider, or remote service generally does not commit atomically with the database transaction. Design handlers to be idempotent where possible, using an idempotency key or deduplication record. For effects that must stay coordinated with database changes, transactional outbox or inbox patterns may help, provided the receiving side participates in the corresponding deduplication protocol.
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Which retry fields and policies should a queue define?
Retries are queue policy, not behavior supplied by SKIP LOCKED. A practical job record or associated state commonly needs to represent:
- Attempt count and the next eligible time.
- A maximum-attempt rule or another explicit terminal-failure policy.
- Error details sufficient for diagnosis.
- A way to inspect, re-drive, or otherwise handle terminal failures.
- Recovery for abandoned claims, such as an expired lease or stale worker heartbeat, if the design uses leases.
Choose a backoff schedule and terminal policy to fit the job’s failure modes; PostgreSQL does not choose either for you. If retrying work can overlap with a later attempt, also define how stale workers are prevented from overwriting newer state or duplicating external effects.
What ordering does a PostgreSQL queue provide?
Separate three questions: which jobs are eligible first, which jobs workers claim first, and which jobs finish or produce side effects first. An explicit ORDER BY controls the selection preference; include a unique tie-breaker for deterministic selection among otherwise equal rows. PostgreSQL warns that without ORDER BY, result order is unspecified, and combining LIMIT with no unique deterministic ordering can select an unpredictable subset. See the SELECT reference.
Selection order is not completion order. With multiple workers running jobs at once, a later-claimed job can finish before an earlier one. If a locking SELECT with ORDER BY waits on a lock under READ COMMITTED, PostgreSQL documents that changed ordering-column values can also lead to returned rows appearing out of order. SKIP LOCKED skips locked rows rather than waiting on them, but neither behavior establishes a general ordering or fairness contract.
How can jobs for one account or resource remain sequential?
If only jobs sharing an entity—such as an account, order, or resource—must be serialized, define that ordering scope explicitly and allow at most one active job for a key at a time. This avoids imposing strict global FIFO when unrelated entities can proceed in parallel. A queue library may provide a per-key policy: pg-boss documents key_strict_fifo, which holds successors behind active, retrying, or failed jobs for a key. That is pg-boss behavior, not a PostgreSQL guarantee; consult its queue API documentation.
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Does SKIP LOCKED or priority guarantee fairness?
No. A priority rule can repeatedly favor new high-priority work and leave lower-priority jobs waiting; skipping locked queue-head rows can also change which workers get which jobs. Neither is a starvation-freedom promise. If low-priority work must make progress, choose and implement a policy that gives it a chance—for example, age-aware priority or separate service capacity—and monitor how long eligible jobs wait. Such behavior belongs to the queue policy, not to PostgreSQL’s locking clause.
Strict global FIFO can reduce the ability to work around a slow or locked head item. Per-key sequencing is often a more targeted constraint: preserve order where business rules require it while permitting independent keys to run concurrently. The policy should say what happens when an earlier job for a key is retrying or terminally failed, since holding later work can preserve order but also block progress.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Should workers use LISTEN/NOTIFY or polling?
Keep the jobs table as the durable source of truth. A worker can listen for a notification as a wake-up hint, then query the table for eligible work. PostgreSQL delivers notifications issued within a transaction only after that transaction commits; a listener inside its own transaction does not receive them at the client until that transaction ends. Identical channel-and-payload notifications in one transaction can be folded. Details are in the PostgreSQL 17 NOTIFY documentation.
Notifications do not replace reconciliation. A listener may disconnect, so retain periodic polling or another reconnect check that queries durable state. Keep listener transactions short: PostgreSQL documents a finite notification queue, and a full queue can make a transaction issuing NOTIFY fail at commit; long-running listener transactions can delay queue cleanup.
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Index the eligibility and ordering path used by the actual claim query, then inspect plans under realistic queue depth and lock contention. Keep claim batches bounded. Useful operational signals include claim latency, age of the oldest eligible job, retry and terminal-failure volume, lock waits, worker heartbeats, and database connection use. There is no universal jobs-per-second figure or threshold established here; capacity depends on the schema, workload, query plan, and contention.
Job state changes create update and delete churn. Set a retention policy for completed records and monitor vacuum behavior as the queue grows. PostgreSQL’s routine vacuuming documentation explains how vacuum makes space from obsolete row versions reusable. Choose maintenance settings from observed table statistics and workload rather than assuming one setting fits every queue.
When is PostgreSQL a sensible queue choice?
A PostgreSQL queue can be a practical fit when the application already depends on PostgreSQL, job creation must be coordinated with application data, and expected backlog, throughput, and latency work within the database’s operational budget. A separate broker may be a better architectural fit when background traffic needs a distinct failure domain or queue-specific capabilities and scale that the database design should not carry. No workload-matched benchmark here establishes that PostgreSQL is universally faster or slower than a broker.
Quick Recap
Evaluate the design against these questions:
- Must enqueueing be atomic with a change to application data?
- What backlog, throughput, and latency are expected, and can the database sustain them alongside application queries?
- What delivery and duplicate-effect semantics can handlers tolerate?
- Is ordering global, per queue, or only per entity?
- Which retry, scheduling, rate-limit, and terminal-failure features are required?
- What retention and database maintenance cost will the queue add?
- Is it acceptable for application data and background work to share PostgreSQL’s failure domain?
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