Postgres job queue
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PostgreSQL-based job queue with priority scheduling, batch claiming, and progress tracking. Use when building job queues without external dependencies. Triggers on PostgreSQL job queue, background jobs, task queue, priority queue, SKIP LOCKED.
SKILL.md
5.4 KB, ~1.3k tokens by cl100k_base, as published. Nobody here has run it
PostgreSQL Job Queue
Production-ready job queue using PostgreSQL with priority scheduling, batch claiming, and progress tracking.
Installation
OpenClaw / Moltbot / Clawbot
npx clawhub@latest install postgres-job-queue
When to Use
- Need job queue but want to avoid Redis/RabbitMQ dependencies
- Jobs need priority-based scheduling
- Long-running jobs need progress visibility
- Jobs should survive service restarts
Schema Design
CREATE TABLE jobs (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
job_type VARCHAR(50) NOT NULL,
priority INT NOT NULL DEFAULT 100,
status VARCHAR(20) NOT NULL DEFAULT 'pending',
data JSONB NOT NULL DEFAULT '{}',
-- Progress tracking
progress INT DEFAULT 0,
current_stage VARCHAR(100),
events_count INT DEFAULT 0,
-- Worker tracking
worker_id VARCHAR(100),
claimed_at TIMESTAMPTZ,
-- Timing
created_at TIMESTAMPTZ DEFAULT NOW(),
started_at TIMESTAMPTZ,
completed_at TIMESTAMPTZ,
-- Retry handling
attempts INT DEFAULT 0,
max_attempts INT DEFAULT 3,
last_error TEXT,
CONSTRAINT valid_status CHECK (
status IN ('pending', 'claimed', 'running', 'completed', 'failed', 'cancelled')
)
);
-- Critical: Partial index for fast claiming
CREATE INDEX idx_jobs_claimable ON jobs (priority DESC, created_at ASC)
WHERE status = 'pending';
CREATE INDEX idx_jobs_worker ON jobs (worker_id)
WHERE status IN ('claimed', 'running');
Batch Claiming with SKIP LOCKED
CREATE OR REPLACE FUNCTION claim_job_batch(
p_worker_id VARCHAR(100),
p_job_types VARCHAR(50)[],
p_batch_size INT DEFAULT 10
) RETURNS SETOF jobs AS $$
BEGIN
RETURN QUERY
WITH claimable AS (
SELECT id
FROM jobs
WHERE status = 'pending'
AND job_type = ANY(p_job_types)
AND attempts < max_attempts
ORDER BY priority DESC, created_at ASC
LIMIT p_batch_size
FOR UPDATE SKIP LOCKED -- Critical: skip locked rows
),
claimed AS (
UPDATE jobs
SET status = 'claimed',
worker_id = p_worker_id,
claimed_at = NOW(),
attempts = attempts + 1
WHERE id IN (SELECT id FROM claimable)
RETURNING *
)
SELECT * FROM claimed;
END;
$$ LANGUAGE plpgsql;
Go Implementation
const (
PriorityExplicit = 150 // User-requested
PriorityDiscovered = 100 // System-discovered
PriorityBackfill = 30 // Background backfills
)
type JobQueue struct {
db *pgx.Pool
workerID string
}
func (q *JobQueue) Claim(ctx context.Context, types []string, batchSize int) ([]Job, error) {
rows, err := q.db.Query(ctx,
"SELECT * FROM claim_job_batch($1, $2, $3)",
q.workerID, types, batchSize,
)
if err != nil {
return nil, err
}
defer rows.Close()
var jobs []Job
for rows.Next() {
var job Job
if err := rows.Scan(&job); err != nil {
return nil, err
}
jobs = append(jobs, job)
}
return jobs, nil
}
func (q *JobQueue) Complete(ctx context.Context, jobID uuid.UUID) error {
_, err := q.db.Exec(ctx, `
UPDATE jobs
SET status = 'completed',
progress = 100,
completed_at = NOW()
WHERE id = $1`,
jobID,
)
return err
}
func (q *JobQueue) Fail(ctx context.Context, jobID uuid.UUID, errMsg string) error {
_, err := q.db.Exec(ctx, `
UPDATE jobs
SET status = CASE
WHEN attempts >= max_attempts THEN 'failed'
ELSE 'pending'
END,
last_error = $2,
worker_id = NULL,
claimed_at = NULL
WHERE id = $1`,
jobID, errMsg,
)
return err
}
Stale Job Recovery
func (q *JobQueue) RecoverStaleJobs(ctx context.Context, timeout time.Duration) (int, error) {
result, err := q.db.Exec(ctx, `
UPDATE jobs
SET status = 'pending',
worker_id = NULL,
claimed_at = NULL
WHERE status IN ('claimed', 'running')
AND claimed_at < NOW() - $1::interval
AND attempts < max_attempts`,
timeout.String(),
)
if err != nil {
return 0, err
}
return int(result.RowsAffected()), nil
}
Decision Tree
| Scenario | Approach |
|---|---|
| Need guaranteed delivery | PostgreSQL queue |
| Need sub-ms latency | Use Redis instead |
| < 1000 jobs/sec | PostgreSQL is fine |
| > 10000 jobs/sec | Add Redis layer |
| Need strict ordering | Single worker per type |
Related Skills
- Related: service-layer-architecture — Service patterns for job handlers
- Related: realtime/dual-stream-architecture — Event publishing from jobs
NEVER Do
- NEVER use SELECT then UPDATE — Race condition. Use SKIP LOCKED.
- NEVER claim without SKIP LOCKED — Workers will deadlock.
- NEVER store large payloads — Store references only.
- NEVER forget partial index — Claiming is slow without it.
Gives 0 of the 12 instructions most databases sql skills give in ~1.3k tokens
Counted across 589 of the 662 authors here whose files we hold, read 2026-08-06
- use parameterized queriesin 36 of 589, across 32 files
- use timestamptz for timestampsin 30 of 589, across 12 files
- create indexes concurrentlyin 29 of 589, across 23 files
- index foreign keysin 28 of 589, across 17 files
- use numeric type for moneyin 25 of 589, across 8 files
- select only required columnsin 24 of 589, across 19 files
- use cursor pagination instead of OFFSETin 23 of 589, across 15 files
- add indexes manually on foreign key columnsin 22 of 589, across 11 files
- read individual rule files for detailed explanationsin 18 of 589, across 4 files
- configure connection poolingin 18 of 589, across 16 files
- put equality columns before range columns in indexesin 17 of 589, across 9 files
- normalize to third normal formin 17 of 589, across 8 files
Said here and by no other author read
- use SKIP LOCKED for batch claiming
- create a partial index on pending jobs
- store references instead of large payloads
- implement stale job recovery
- reset failed jobs to pending if attempts remain
- increment attempts when claiming
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.