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Crate apalis_diesel_postgres

Crate apalis_diesel_postgres 

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§apalis-diesel-postgres

crates.io docs.rs

PostgreSQL storage backend for Apalis implemented with Diesel and r2d2.

The crate’s headline feature is a transactional enqueue APIPostgresStorage::push_with_conn — that lets you insert a job in the same PgConnection transaction as your business data. If the business transaction commits, the job is enqueued; if it rolls back, no job is enqueued and no LISTEN/NOTIFY is delivered. That removes the classic “resource written, job missing” split-brain without a separate outbox table.

The crate accepts any diesel::r2d2::Pool<ConnectionManager<PgConnection>> — you keep using the pool you already wire up — and ships everything else apalis needs: migrations, polling/notify-driven dequeue, locking, ack, retries, orphan re-enqueue, admin queries, and MakeShared for many-queue setups.

§Status

Targets the Apalis 1.0 release candidate: apalis-core 1.0.0-rc.9, apalis-sql 1.0.0-rc.9, apalis-codec 0.1.0-rc.9, diesel 2.3. Schema compatible with Apalis SQL storage (apalis.jobs, apalis.workers).

§Installation

[dependencies]
apalis-diesel-postgres = { version = "0.3", features = ["tokio"] }
diesel = { version = "2.3", features = ["postgres", "r2d2", "chrono", "serde_json"] }
serde = { version = "1", features = ["derive"] }

Runtime features (pick one):

  • tokio (default) — Diesel work runs on tokio::task::spawn_blocking.
  • ntex — Diesel work runs on ntex_rt::spawn_blocking.
  • no feature — Diesel work runs on the calling thread (compile-time compatibility only; can stall an async executor under load).

If both tokio and ntex are enabled, tokio wins. Treat --all-features as a compatibility check, not a runtime shape.

§Quick start

Build a pool, run the migrations once at startup, create a storage. The worker side (poll/lock/ack) follows the regular apalis APIs — see the Running an apalis worker section below for a full end-to-end wiring.

use apalis_diesel_postgres::{Config, PostgresStorage, build_pool, setup};

#[derive(Debug, serde::Deserialize, serde::Serialize)]
struct SendEmail {
    to: String,
}

let pool = build_pool("postgres://127.0.0.1:5432/app")?;
setup(&pool).await?;

let storage = PostgresStorage::<SendEmail>::new_with_config(
    &pool,
    &Config::new("emails"),
);

To enqueue tasks from a request handler atomically with business data, see the outbox section. To run the example end-to-end against a real database, see examples/outbox.rs:

DATABASE_URL=postgres://127.0.0.1:5432/apalis_diesel_postgres \
    cargo run --example outbox --features tokio

§Running an apalis worker

Add apalis to your Cargo.toml; it re-exports WorkerBuilder, Worker, Data and the BoxDynError alias used by handlers. PostgresStorage<T> satisfies apalis’s Backend + Send + Sync requirement, so it slots straight into WorkerBuilder::backend(...).

let pool = build_pool("postgres://127.0.0.1:5432/app")?;
setup(&pool).await?;

let storage: PostgresStorage<SendEmail> =
    PostgresStorage::new_with_config(&pool, &Config::new("emails"));

WorkerBuilder::new("emails-worker")
    .backend(storage)
    .build(handle_email)
    .run()
    .await?;

§Calling push_with_conn from inside a handler

The outbox pattern isn’t limited to HTTP handlers — the same transactional guarantees apply when one job needs to enqueue a follow-up job atomically with its own database writes. Inject the follow-up queue’s storage via Data<...>, hop onto the blocking pool, and share a &mut PgConnection between the business write and push_with_conn:

async fn handle_email(
    job: SendEmail,
    activity: Data<PostgresStorage<LogActivity>>,
) -> Result<(), BoxDynError> {
    let activity = (*activity).clone();
    let to = job.to.clone();

    tokio::task::spawn_blocking(move || -> Result<(), PgError> {
        let mut conn = activity.pool().get().map_err(PgError::Pool)?;
        conn.transaction(|c| {
            // Your business write goes here — same connection, same txn.
            activity.push_with_conn(c, LogActivity {
                kind: "email_sent".to_owned(),
                target: to,
            })?;
            Ok::<_, PgError>(())
        })
    })
    .await??;
    Ok(())
}

Wire the follow-up storage into the worker via .data(...):

let worker = WorkerBuilder::new("emails-worker")
    .backend(emails)
    .data(activity)
    .build(handle_email);

End-to-end runnable example: examples/worker.rs.

DATABASE_URL=postgres://127.0.0.1:5432/apalis_diesel_postgres \
    cargo run --example worker --features tokio

§Transactional enqueue (outbox pattern)

When a request handler must persist a resource (an order, a user, a file upload) and enqueue a follow-up job (send confirmation email, kick off processing), the two writes have to either both happen or both not happen. If they live in different transactions, you get the classic split-brain:

  • Resource written, job missing → silent loss of work.
  • Job written, resource rolled back → consumer wakes up, fails to find the row, retries forever.

PostgresStorage::push_with_conn lets you insert the apalis task on the same &mut PgConnection your handler is already using, so the task INSERT is part of your business transaction. If the transaction commits, the job is enqueued; if it rolls back, no job is enqueued and no NOTIFY is delivered. There is no manual outbox table to drain.

let task_id = tokio::task::spawn_blocking(move || {
    let mut conn = backend_pool.get()?;
    conn.transaction::<_, Box<dyn std::error::Error + Send + Sync>, _>(|c| {
        // Business write — your service's own table.
        sql_query("INSERT INTO orders (id, status) VALUES ($1, 'pending')")
            .bind::<diesel::sql_types::BigInt, _>(order_id)
            .execute(c)?;

        // Apalis enqueue — same connection, same transaction.
        let id = storage.push_with_conn(c, SendConfirmationEmail { order_id })?;
        Ok(id)
    })
})
.await??;

Key points:

  • backend_pool is your service’s pool, separate from the pool you hand to PostgresStorage. See Connection pool isolation.
  • The whole block runs inside tokio::task::spawn_blockingpush_with_conn is synchronous and would otherwise stall the runtime.
  • NOTIFY fires when the outer transaction commits, so listeners only observe committed work.

§push_task_with_conn — full control

push_with_conn(args) is the ergonomic path: auto Ulid, default scheduling. For idempotency_key, priority, run_at (delayed run), max_attempts, custom metadata, or a pre-allocated task_id, build a PgTask<Args> and call push_task_with_conn:

let mut task = PgTask::<Reminder>::new(Reminder { order_id });
task.parts.idempotency_key = Some(format!("reminder:{order_id}"));
task.parts.run_at = SystemTime::now()
    .duration_since(UNIX_EPOCH)
    .unwrap()
    .as_secs()
    + 24 * 3600; // tomorrow

storage.push_task_with_conn(conn, task)

§Constraints

  • Synchronous — wrap in tokio::task::spawn_blocking from async code so the whole transaction stays on one blocking task.
  • Don’t reuse this connection for unrelated apalis operations (fetch/ack/heartbeat) — those live on the apalis pool.
  • Idempotency conflict rolls back only the apalis batch via SAVEPOINT; the outer transaction stays alive. Decide whether to commit your business writes or roll the whole transaction back when you get Err(Error::IdempotencyConflict { .. }) — match the variant, not the message text. One duplicate key rolls back the whole enqueue batch, not just the colliding row.
  • No outer transaction → Diesel auto-commits the INSERT; the call still works, but you lose the outbox guarantee.

§Connection pool isolation

Do not share the apalis pool with your HTTP request handlers or other unrelated workloads. Apalis holds long-lived connections (fetcher polling/LISTEN, lifecycle keep-alive, listener thread). If the application exhausts the pool under load, the fetcher and heartbeat stall; lifecycle marks the worker dead and re-enqueues its in-flight tasks, which produces more load on the same pool — a cascading failure that is hard to recover from while it is happening.

Run two separate r2d2 pools against the same PostgreSQL database — one for your web service, one for apalis — and size them independently:

use apalis_diesel_postgres::{Config, PostgresStorage, build_pool_with};

// Web/backend pool — sized for request concurrency.
let backend_pool = build_pool_with(
    "postgres://127.0.0.1:5432/app",
    |b| b.max_size(20).connection_timeout(std::time::Duration::from_secs(2)),
)?;

// Apalis pool — sized for worker concurrency + lifecycle + listeners.
// Rough rule: worker_concurrency + 2 + listeners.
let apalis_pool = build_pool_with(
    "postgres://127.0.0.1:5432/app",
    |b| b.max_size(8).connection_timeout(std::time::Duration::from_secs(2)),
)?;

let storage = PostgresStorage::<()>::new_with_config(&apalis_pool, &Config::new("emails"));
// Use `backend_pool.get()` + `storage.push_with_conn(conn, args)` from
// request handlers to enqueue inside business transactions.

Recommendations:

  • Set a short connection_timeout (1–3 s) on both pools so a starved pool fails loudly instead of hanging request handlers.
  • Set statement_timeout on the session via your connection setup if workloads need it.
  • Monitor pool saturation via pool.state() (connections, idle_connections) on both pools.

§Storage modes

use apalis_diesel_postgres::{Config, PostgresStorage, SharedPostgresStorage};
use diesel::{PgConnection, r2d2::{ConnectionManager, Pool}};
type PgPool = Pool<ConnectionManager<PgConnection>>;

#[derive(Debug, serde::Deserialize, serde::Serialize)]
struct EmailJob { to: String }

fn build(pool: PgPool) {
    let config = Config::new("emails");

    // Polling fetcher (the default). Queue name = `Args` type name.
    let _polling = PostgresStorage::<EmailJob>::new(&pool);

    // Polling fetcher with an explicit queue name (use this for stable queues).
    let _polling = PostgresStorage::<EmailJob>::new_with_config(&pool, &config);

    // Polling + LISTEN/NOTIFY wakeups (lower latency, dedicated connection).
    let _notify = PostgresStorage::<EmailJob>::new_with_notify(&pool, &config);

    // One listener shared across many queues, registered via apalis `MakeShared`.
    let _shared: SharedPostgresStorage = SharedPostgresStorage::new(pool);
}

new_with_notify and SharedPostgresStorage use LISTEN "apalis::job::insert" to wake workers on insert. Polling stays as a fallback. Each notify-mode storage pins one extra pooled connection while the listener is alive — size the apalis pool accordingly.

§Examples

examples/outbox.rs — runnable, demonstrates commit / rollback / idempotency-conflict behaviour against a real database:

DATABASE_URL=postgres://127.0.0.1:5432/apalis_diesel_postgres \
    cargo run --example outbox --features tokio

§Runtime errors

The backend annotates common database failures with operation context so worker logs point at the failed lifecycle step:

  • Missing migrations: database error while fetching queued jobs: …, with a hint to call apalis_diesel_postgres::setup(&pool).await.
  • Pool acquisition failures mention DATABASE_URL, PostgreSQL reachability, and pool capacity.
  • Lock failures for non-lockable jobs: task not found while locking task, with the task id and queue. Usually means the job is delayed, completed, already locked, or in another queue.
  • Acknowledgement races: stale acknowledgement when the stored lock no longer matches the worker/attempt/lock timestamp being ack’d.
  • Heartbeat failures for missing worker rows: worker not registered, instead of a generic update-count mismatch.
  • Codec failures: failed to decode task payload or result with the configured codec — payload was written with a different codec or is corrupt.
  • Notification listener failures surface as stream errors. Polling still fetches jobs; LISTEN/NOTIFY wakeups stop until the notify stream is recreated.
  • Idempotency conflicts: Error::IdempotencyConflict { job_type, conflicting_keys, total } when an enqueue collides with the (job_type, idempotency_key) unique constraint. conflicting_keys names the exact keys that collided, so a batch caller can drop them and re-enqueue the rest. Match the variant (not the message text) to treat a duplicate as benign. One duplicate rolls back the whole batch, not just the colliding row; a surrounding transaction stays alive. The push_*_with_conn outbox methods return this directly; the Sink / TaskSink enqueue APIs wrap it (like every push error) as TaskSinkError::PushError(Error::IdempotencyConflict { .. }).

§Public types

use apalis_diesel_postgres::{
    CompactType, Config, JsonCodec, MIGRATIONS, PgContext, PgPool, PgTask,
    PgTaskId, PostgresStorage, SharedPostgresStorage, TaskRow, build_pool, setup,
};

Type aliases:

  • PgPool = Pool<ConnectionManager<PgConnection>>
  • PgContext = SqlContext<PgPool>
  • PgTask<Args> = Task<Args, PgContext, Ulid>
  • PgTaskId = TaskId<Ulid>
  • CompactType = Vec<u8>

§Local development

nix develop                # dev shell with rust, diesel, postgres
nix run .#services         # start local PostgreSQL on 127.0.0.1:5432

The shell exports DATABASE_URL=postgres://127.0.0.1:5432/apalis_diesel_postgres and stores data in ./.pgdata. Editor config for Zed is generated automatically; opt in to MCP config with APALIS_DIESEL_POSTGRES_WRITE_MCP=1 nix develop.

For the full pre-PR check list (cargo fmt, multiple cargo check/cargo test matrices, doc warnings), see CONTRIBUTING.md. The quick smoke path is:

env -u DATABASE_URL cargo test --features tokio --lib
DATABASE_URL=postgres://127.0.0.1:5432/apalis_diesel_postgres \
    APALIS_DIESEL_POSTGRES_REQUIRE_DATABASE=1 \
    cargo test --features tokio -- --test-threads=1

Modules§

schema

Structs§

Config
Configuration for the SQL backend
JsonCodec
Json encoding and decoding
PgAck
Acknowledges task completion by updating apalis.jobs.
PgFetcher
Marker fetcher used by the default polling backend.
PgMiddleware
Middleware layer used by the PostgreSQL backend.
PgNotify
A fetcher that waits for PostgreSQL NOTIFY events.
PgSink
Buffered task sink used by PostgresStorage.
PostgresStorage
PostgreSQL storage backend implemented with Diesel.
SharedFetcher
Fetcher used by shared storage instances.
SharedPostgresStorage
Factory for shared notify-backed PostgreSQL storage instances.
TaskRow
Represents a row from the tasks table in the database.

Enums§

Error
Error type returned by the Diesel PostgreSQL backend.
SharedPostgresError
Errors returned while creating shared storage instances.

Constants§

MIGRATIONS

Functions§

build_pool
Build a Diesel/r2d2 PostgreSQL pool from a database URL using r2d2 defaults.
build_pool_with
Build a Diesel/r2d2 PostgreSQL pool with a custom r2d2 builder configuration.
crate_name
Returns the crate name.
lock_task
Lock a due task for a worker.
lock_task_in_queue
Lock a due task scoped to a specific queue.
refresh_queue_stats_snapshot
Refresh the apalis.queue_stats_snapshot materialized view.
setup
Run the embedded Apalis-compatible migrations.
verify_schema
Verify that every embedded migration has been applied to the target database. Useful as a boot-time guard for deployments that run migrations out-of-band (CI step, ops tooling) rather than calling setup from the application process: a missing migration is surfaced here as Error::Migration instead of as opaque Database errors against columns or tables that runtime queries assume exist.

Type Aliases§

CompactType
Compact serialized payload representation.
PgContext
SQL context associated with PostgreSQL tasks.
PgPool
Diesel/r2d2 PostgreSQL pool accepted by this backend.
PgTask
Apalis task stored in PostgreSQL.
PgTaskId
PostgreSQL task identifier.