#signal #shutdown #high-performance #result #signals


Migrations package for archimedes, a high performance Rust/PostgreSQL job queue

5 releases

0.2.4 Mar 23, 2023
0.2.3 Mar 23, 2023
0.2.2 Mar 22, 2023
0.2.1 Mar 22, 2023
0.1.1 Mar 21, 2023

45 downloads per month
Used in 2 crates

MIT license




Rewrite of Graphile Worker in Rust. If you like this library go sponsor Benjie project, all research has been done by him, this library is only a rewrite in Rust 🦀. The port should mostly be compatible with graphile-worker (meaning you can run it side by side with Node.JS).

The following differs from Graphile Worker :

  • No support for batch job
  • In Graphile Worker, each process has it's worker_id. In rust there is only one worker_id, then jobs are processed in your async runtime thread.

Job queue for PostgreSQL running on Rust - allows you to run jobs (e.g. sending emails, performing calculations, generating PDFs, etc) "in the background" so that your HTTP response/application code is not held up. Can be used with any PostgreSQL-backed application.

Add the worker to your project:

cargo add archimedes

Create tasks and run the worker

The definition of a task consist simply of an async function and a task identifier

struct HelloPayload {
    name: String,

async fn say_hello(_ctx: WorkerCtx, payload: HelloPayload) -> Result<(), ..> {
    println!("Hello {} !", payload.name);

async fn main() -> Result<(), ..> {
        .define_job("say_hello", say_hello)


Schedule a job via SQL

Connect to your database and run the following SQL:

SELECT archimedes_worker.add_job('say_hello', json_build_object('name', 'Bobby Tables'));


You should see the worker output Hello Bobby Tables !. Gosh, that was fast!


  • Standalone and embedded modes
  • Designed to be used both from JavaScript or directly in the database
  • Easy to test (recommended: `runTaskListOnce` util)
  • Low latency (typically under 3ms from task schedule to execution, uses LISTEN/NOTIFY to be informed of jobs as they're inserted)
  • High performance (uses SKIP LOCKED to find jobs to execute, resulting in faster fetches)
  • Small tasks (uses explicit task names / payloads resulting in minimal serialisation/deserialisation overhead)
  • Parallel by default
  • Adding jobs to same named queue runs them in series
  • Automatically re-attempts failed jobs with exponential back-off
  • Customisable retry count (default: 25 attempts over ~3 days)
  • Crontab-like scheduling feature for recurring tasks (with optional backfill)
  • Task de-duplication via unique job_key
  • Append data to already enqueued jobs with "batch jobs"
  • Open source; liberal MIT license
  • Executes tasks written in Rust (these can call out to any other language or networked service)
  • Written natively in Rust
  • If you're running really lean, you can run Archimedes in the same Node process as your server to keep costs and devops complexity down.


NOT production ready (use it at your own risk).


PostgreSQL 12+ Might work with older versions, but has not been tested.

Note: Postgres 12 is required for the generated always as (expression) feature


cargo add archimedes


archimedes manages its own database schema (archimedes_worker). Just point at your database and we handle our own migrations:

Library usage: running jobs

archimedes can be used as a library inside your Rust application. There are two main use cases for this: running jobs, and queueing jobs. Here are the APIs for running jobs.


run(options: RunnerOptions): Promise<Runner>

Runs until either stopped by a signal event like SIGINT or by calling the stop() method on the resolved object.

The resolved 'Runner' object has a number of helpers on it, see Runner object for more information.

runOnce(options: RunnerOptions): Promise<void>

Equivalent to running the CLI with the --once flag. The function will run until there are no runnable jobs left, and then resolve.

runMigrations(options: RunnerOptions): Promise<void>

Equivalent to running the CLI with the --schema-only option. Runs the migrations and then resolves.


The following options for these methods are available.

  • concurrency: Maximum number of concurrent job running at the same time. archimedes uses an async runtime so it has no problem going beyond your number of CPUs.
  • no_handle_signals: If set true, we won't install signal handlers and it'll be up to you to handle graceful shutdown of the worker if the process receives a signal.
  • poll_interval: Frequency at which we check for new job
  • the database is identified through one of these options:
    • pg_pool: A sqlx::PgPool instance to use
  • schema can be used to change the default archimedes_worker schema to something else (equivalent to --schema on the CLI)
  • forbidden_flags see Forbidden flags below

One of these must be provided (in order of priority):

  • pg_pool sqlx::PgPool instance
  • database_url setting
  • DATABASE_URL envvar

Runner object

The run method above resolves to a 'Runner' object that has the following methods and properties:

  • stop(): Promise<void> - stops the runner from accepting new jobs, and returns a promise that resolves when all the in progress tasks (if any) are complete.
  • add_job: AddJobFunction - see add_job.

Example: adding a job with runner.add_job

See add_job for more details.

runner.add_job("my_task", my_payload);



Library usage: queueing jobs

You can also use the archimedes_worker library to queue jobs using one of the following APIs.

make_worker_util(options: WorkerUtilsOptions): Promise<WorkerUtils>


Useful for adding jobs from within JavaScript in an efficient way.

Runnable example:

We recommend building one instance of WorkerUtils and sharing it as a singleton throughout your code.


  • exactly one of these keys must be present to determine how to connect to the database:
    • database_url: A PostgreSQL connection string to the database containing the job queue, or
    • pg_pool: A sqlx::PgPool instance to use
  • schema can be used to change the default graphile_worker schema to something else (equivalent to --schema on the CLI)


A WorkerUtils instance has the following methods:

  • add_job(name: String, payload: serde_json::Value, opts: JobOptions) - a method you can call to enqueue a job, see addJob.
  • migrate() - a method you can call to update the graphile-worker database schema; returns a promise.

quick_add_job(options: WorkerUtilsOptions, job: Job): Result<Job>

If you want to quickly add a job and you don't mind the cost of opening a DB connection pool and then cleaning it up right away for every job added, there's the quickAddJob convenience function. It takes the same options as makeWorkerUtils as the first argument; the remaining arguments are for addJob.

NOTE: you are recommended to use makeWorkerUtils instead where possible, but in one-off scripts this convenience method may be enough.

Runnable example:

const { quickAddJob } = require("graphile-worker");

async function main() {
  await quickAddJob(
    // makeWorkerUtils options
    { connectionString: "postgres:///my_db" },

    // Task identifier

    // Payload
    { value: 42 },

    // Optionally, add further task spec details here

main().catch((err) => {


The add_job API exists in many places in graphile-worker, but all the instances have exactly the same call signature. The API is used to add a job to the queue for immediate or delayed execution. With job_key and job_key_mode it can also be used to replace existing jobs.

NOTE: quick_add_job is similar to add_job, but accepts an additional initial parameter describing how to connect to the database).

The add_job arguments are as follows:

  • identifier: the name of the task to be executed
  • payload: an optional JSON-compatible object to give the task more context on what it is doing, or a list of these objects in "batch job" mode
  • options: an optional object specifying:
    • queue_name: the queue to run this task under
    • run_at: a Date to schedule this task to run in the future
    • max_attempts: how many retries should this task get? (Default: 25)
    • job_key: unique identifier for the job, used to replace, update or remove it later if needed (see Replacing, updating and removing jobs); can be used for de-duplication (i.e. throttling or debouncing)
    • job_key_mode: controls the behavior of job_key when a matching job is found (see Replacing, updating and removing jobs)


add_job("task_2", json!({ "name": "John" })).await?;

Batch jobs

Not supported for now, if you are interested in porting this to rust, you can express your interested by opening an issue.

Creating task executors

A task executor is a simple async RUST function which receives as input the job payload and a collection of helpers. It does the work and then returns. If it returns then the job is deemed a success and is deleted from the queue (unless this is a "batch job"). If it throws an error then the job is deemed a failure and the task is rescheduled using an exponential-backoff algorithm.

IMPORTANT: we automatically retry the job if it fails, so it's often sensible to split large jobs into smaller jobs, this also allows them to run in parallel resulting in faster execution. This is particularly important for tasks that are not idempotent (i.e. running them a second time will have extra side effects) - for example sending emails.

Each task function is passed two arguments:

  • payload - the payload you passed when calling add_job
  • ctx - an object containing:
    • job - the whole job (including uuid, attempts, etc) - you shouldn't need this
    • pg_pool - a helper to use to get a database client
    • add_job - a helper to schedule a job

Handling batch jobs


More detail on scheduling jobs through SQL

You can schedule jobs directly in the database, e.g. from a trigger or function, or by calling SQL from your application code. You do this using the graphile_worker.add_job function (or the experimental graphile_worker.add_jobs function for bulk inserts, see below).

NOTE: the addJob JavaScript method simply defers to this underlying add_job SQL function.

add_job accepts the following parameters (in this order):

  • identifier - the only required field, indicates the name of the task executor to run (omit the .js suffix!)
  • payload - a JSON object with information to tell the task executor what to do, or an array of one or more of these objects for "batch jobs" (defaults to an empty object)
  • queue_name - if you want certain tasks to run one at a time, add them to the same named queue (defaults to null)
  • run_at - a timestamp after which to run the job; defaults to now.
  • max_attempts - if this task fails, how many times should we retry it? Default: 25.
  • job_key - unique identifier for the job, used to replace, update or remove it later if needed (see Replacing, updating and removing jobs); can also be used for de-duplication
  • priority - an integer representing the jobs priority. Jobs are executed in numerically ascending order of priority (jobs with a numerically smaller priority are run first).
  • flags - an optional text array (text[]) representing a flags to attach to the job. Can be used alongside the forbiddenFlags option in library mode to implement complex rate limiting or other behaviors which requiring skipping jobs at runtime (see Forbidden flags).
  • job_key_mode - when job_key is specified, this setting indicates what should happen when an existing job is found with the same job key:
    • replace (default) - all job parameters are updated to the new values, including the run_at (inserts new job if matching job is locked)
    • preserve_run_at - all job parameters are updated to the new values, except for run_at which maintains the previous value (inserts new job if matching job is locked)
    • unsafe_dedupe - only inserts the job if no existing job (whether or not it is locked or has failed permanently) with matching key is found; does not update the existing job

Typically you'll want to set the identifier and payload:

SELECT graphile_worker.add_job(
    'to', 'someone@example.com',
    'subject', 'graphile-worker test'

It's recommended that you use PostgreSQL's named parameters for the other parameters so that you only need specify the arguments you're using:

SELECT graphile_worker.add_job('reminder', run_at := NOW() + INTERVAL '2 days');

TIP: if you want to run a job after a variable number of seconds according to the database time (rather than the application time), you can use interval multiplication; see run_at in this example:

SELECT graphile_worker.add_job(
  payload := $2,
  queue_name := $3,
  max_attempts := $4,
  run_at := NOW() + ($5 * INTERVAL '1 second')

NOTE: graphile_worker.add_job(...) requires database owner privileges to execute. To allow lower-privileged users to call it, wrap it inside a PostgreSQL function marked as SECURITY DEFINER so that it will run with the same privileges as the more powerful user that defined it. (Be sure that this function performs any access checks that are necessary.)


Experimental: this API may change in a semver minor release.

For bulk insertion of jobs, we've introduced the graphile_worker.add_jobs function. It accepts the following options:

  • specs - an array of graphile_worker.job_spec objects
  • job_key_preserve_run_at - an optional boolean detailing if the run_at should be preserved when the same job_key is seen again

The job_spec object has the following properties, all of which correspond with the add_job option of the same name above.

  • identifier
  • payload
  • queue_name
  • run_at
  • max_attempts
  • job_key
  • priority
  • flags

Note: job_key_mode='unsafe_dedupe' is not supported in add_jobs - you must add jobs one at a time using add_job to use that. The equivalent of job_key_mode='replace' is enabled by default, to change this to the same behavior as job_key_mode='preserve_run_at' you should set job_key_preserve_run_at to true.

Example: scheduling job from trigger

This snippet creates a trigger function which adds a job to execute task_identifier_here when a new row is inserted into my_table.

CREATE FUNCTION my_table_created() RETURNS trigger AS $$
  PERFORM graphile_worker.add_job('task_identifier_here', json_build_object('id', NEW.id));


Example: one trigger function to rule them all

If your tables are all defined with a single primary key named id then you can define a more convenient dynamic trigger function which can be called from multiple triggers for multiple tables to quickly schedule jobs.

CREATE FUNCTION trigger_job() RETURNS trigger AS $$
  PERFORM graphile_worker.add_job(TG_ARGV[0], json_build_object(
    'schema', TG_TABLE_SCHEMA,
    'table', TG_TABLE_NAME,
    'op', TG_OP,

You might use this trigger like this:

CREATE TRIGGER send_verification_email
  AFTER INSERT ON user_emails
  WHEN (NEW.verified is false)
  EXECUTE PROCEDURE trigger_job('send_verification_email');
CREATE TRIGGER user_changed
  EXECUTE PROCEDURE trigger_job('user_changed');
CREATE TRIGGER generate_pdf
  EXECUTE PROCEDURE trigger_job('generate_pdf');
CREATE TRIGGER generate_pdf_update
  EXECUTE PROCEDURE trigger_job('generate_pdf');

Replacing, updating and removing jobs

Replacing/updating jobs

Jobs scheduled with a job_key parameter may be replaced/updated by calling add_job again with the same job_key value. This can be used for rescheduling jobs, to ensure only one of a given job is scheduled at a time, or to update other settings for the job.

For example after the below SQL transaction, the send_email job will run only once, with the payload '{"count": 2}':

SELECT graphile_worker.add_job('send_email', '{"count": 1}', job_key := 'abc');
SELECT graphile_worker.add_job('send_email', '{"count": 2}', job_key := 'abc');

In all cases if no match is found then a new job will be created; behavior when an existing job with the same job key is found is controlled by the job_key_mode setting:

  • replace (default) - overwrites the unlocked job with the new values. This is primarily useful for rescheduling, updating, or debouncing (delaying execution until there have been no events for at least a certain time period). Locked jobs will cause a new job to be scheduled instead.
  • preserve_run_at - overwrites the unlocked job with the new values, but preserves run_at. This is primarily useful for throttling (executing at most once over a given time period). Locked jobs will cause a new job to be scheduled instead.
  • unsafe_dedupe - if an existing job is found, even if it is locked or permanently failed, then it won't be updated. This is very dangerous as it means that the event that triggered this add_job call may not result in any action. It is strongly advised you do not use this mode unless you are certain you know what you are doing.

The full job_key_mode algorithm is roughly as follows:

  • If no existing job with the same job key is found:
    • a new job will be created with the new attributes.
  • Otherwise, if job_key_mode is unsafe_dedupe:
    • stop and return the existing job.
  • Otherwise, if the existing job is locked:
    • it will have its key cleared
    • it will have its attempts set to max_attempts to avoid it running again
    • a new job will be created with the new attributes.
  • Otherwise, if the existing job has previously failed:
    • it will have its attempts reset to 0 (as if it were newly scheduled)
    • it will have its last_error cleared
    • it will have all other attributes updated to their new values, including run_at (even when job_key_mode is preserve_run_at).
  • Otherwise, if job_key_mode is preserve_run_at:
    • the job will have all its attributes except for run_at updated to their new values.
  • Otherwise:
    • the job will have all its attributes updated to their new values.

Removing jobs

Pending jobs may also be removed using job_key:

SELECT graphile_worker.remove_job('abc');

job_key caveats

IMPORTANT: jobs that complete successfully are deleted, there is no permanent job_key log, i.e. remove_job on a completed job_key is a no-op as no row exists.

IMPORTANT: the job_key is treated as universally unique (whilst the job is pending/failed), so you can update a job to have a completely different task_identifier or payload. You must be careful to ensure that your job_key is sufficiently unique to prevent you accidentally replacing or deleting unrelated jobs by mistake; one way to approach this is to incorporate the task_identifier into the job_key.

IMPORTANT: If a job is updated using add_job when it is currently locked (i.e. running), a second job will be scheduled separately (unless job_key_mode = 'unsafe_dedupe'), meaning both will run.

IMPORTANT: calling remove_job for a locked (i.e. running) job will not actually remove it, but will prevent it from running again on failure.

Administration functions

Complete jobs

SQL: SELECT * FROM graphile_worker.complete_jobs(ARRAY[7, 99, 38674, ...]);


Marks the specified jobs (by their ids) as if they were completed, assuming they are not locked. Note that completing a job deletes it. You may mark failed and permanently failed jobs as completed if you wish. The deleted jobs will be returned (note that this may be fewer jobs than you requested).

Permanently fail jobs

SQL: SELECT * FROM graphile_worker.permanently_fail_jobs(ARRAY[7, 99, 38674, ...], 'Enter reason here');


Marks the specified jobs (by their ids) as failed permanently, assuming they are not locked. This means setting their attempts equal to their max_attempts. The updated jobs will be returned (note that this may be fewer jobs than you requested).

Rescheduling jobs


SELECT * FROM graphile_worker.reschedule_jobs(
  ARRAY[7, 99, 38674, ...],
  run_at := NOW() + interval '5 minutes',
  priority := 5,
  attempts := 5,
  max_attempts := 25


Updates the specified scheduling properties of the jobs (assuming they are not locked). All of the specified options are optional, omitted or null values will left unmodified.

This method can be used to postpone or advance job execution, or to schedule a previously failed or permanently failed job for execution. The updated jobs will be returned (note that this may be fewer jobs than you requested).

Recurring tasks (crontab)

Archimedes Worker supports triggering recurring tasks according to a cron-like schedule. This is designed for recurring tasks such as sending a weekly email, running database maintenance tasks every day, performing data roll-ups hourly, downloading external data every 20 minutes, etc.

Archimedes Worker's crontab support:

  • guarantees (thanks to ACID-compliant transactions) that no duplicate task schedules will occur
  • can backfill missed jobs if desired (e.g. if the Worker wasn't running when the job was due to be scheduled)
  • schedules tasks using Graphile Worker's regular job queue, so you get all the regular features such as exponential back-off on failure.
  • works reliably even if you're running multiple workers (see "Distributed crontab" below)

NOTE: It is not intended that you add recurring tasks for each of your individual application users, instead you should have relatively few recurring tasks, and those tasks can create additional jobs for the individual users (or process multiple users) if necessary.

Tasks are by default read from a crontab file next to the tasks/ folder (but this is configurable in library mode). Please note that our syntax is not 100% compatible with cron's, and our task payload differs. We only handle timestamps in UTC. The following diagram details the parts of a Graphile Worker crontab schedule:

Comment lines start with a #.

For the first 5 fields we support an explicit numeric value, * to represent all valid values, */n (where n is a positive integer) to represent all valid values divisible by n, range syntax such as 1-5, and any combination of these separated by commas.

The task identifier should match the following regexp /^[_a-zA-Z][_a-zA-Z0-9:_-]*$/ (namely it should start with an alphabetic character and it should only contain alphanumeric characters, colon, underscore and hyphen). It should be the name of one of your Graphile Worker tasks.

The opts must always be prefixed with a ? if provided and details configuration for the task such as what should be done in the event that the previous event was not scheduled (e.g. because the Worker wasn't running). Options are specified using HTTP query string syntax (with & separator).

Currently we support the following opts:

  • id=UID where UID is a unique alphanumeric case-sensitive identifier starting with a letter - specify an identifier for this crontab entry; by default this will use the task identifier, but if you want more than one schedule for the same task (e.g. with different payload, or different times) then you will need to supply a unique identifier explicitly.
  • fill=t where t is a "time phrase" (see below) - backfill any entries from the last time period t, for example if the worker was not running when they were due to be executed (by default, no backfilling).
  • max=n where n is a small positive integer - override the max_attempts of the job.
  • queue=name where name is an alphanumeric queue name - add the job to a named queue so it executes serially.
  • priority=n where n is a relatively small integer - override the priority of the job.

NOTE: changing the identifier (e.g. via id) can result in duplicate executions, so we recommend that you explicitly set it and never change it.

NOTE: using fill will not backfill new tasks, only tasks that were previously known.

NOTE: the higher you set the fill parameter, the longer the worker startup time will be; when used you should set it to be slightly larger than the longest period of downtime you expect for your worker.

Time phrases are comprised of a sequence of number-letter combinations, where the number represents a quantity and the letter represents a time period, e.g. 5d for five days, or 3h for three hours; e.g. 4w3d2h1m represents 4 weeks, 3 days, 2 hours and 1 minute (i.e. a period of 44761 minutes). The following time periods are supported:

  • s - one second (1000 milliseconds)
  • m - one minute (60 seconds)
  • h - one hour (60 minutes)
  • d - one day (24 hours)
  • w - one week (7 days)

The payload is a JSON5 object; it must start with a {, must not contain newlines or carriage returns (\n or \r), and must not contain trailing whitespace. It will be merged into the default crontab payload properties.

Each crontab job will have a JSON object payload containing the key _cron with the value being an object with the following entries:

  • ts - ISO8601 timestamp representing when this job was due to execute
  • backfilled - true if the task was "backfilled" (i.e. it wasn't scheduled on time), false otherwise

Distributed crontab

TL;DR: when running identical crontabs on multiple workers no special action is necessary - it Just Works ™️

When you run multiple workers with the same crontab files then the first worker that attempts to queue a particular cron job will succeed and the other workers will take no action - this is thanks to SQL ACID-compliant transactions and our known_crontabs lock table.

If your workers have different crontabs then you must be careful to ensure that the cron items each have unique identifiers; the easiest way to do this is to specify the identifiers yourself (see the id= option above). Should you forget to do this then for any overlapping timestamps for items that have the same derived identifier one of the cron tasks will schedule but the others will not.

Crontab examples

The following schedules the send_weekly_email task at 4:30am (UTC) every Monday:

30 4 * * 1 send_weekly_email

The following does similar, but also will backfill any tasks over the last two days (2d), sets max attempts to 10 and merges in {"onboarding": false} into the task payload:

30 4 * * 1 send_weekly_email ?fill=2d&max=10 {onboarding:false}

The following triggers the rollup task every 4 hours on the hour:

0 */4 * * * rollup

Limiting backfill

When you ask Graphile Worker to backfill jobs, it will do so for all jobs matching that specification that should have been scheduled over the backfill period. Other than the period itself, you cannot place limits on the backfilling (for example, you cannot say "backfill at most one job" or "only backfill if the next job isn't due within the next 3 hours"); this is because we've determined that there's many situations (back-off, overloaded worker, serially executed jobs, etc.) in which the result of this behaviour might result in outcomes that the user did not expect.

If you need these kinds of constraints on backfilled jobs, you should implement them at runtime (rather than at scheduling time) in the task executor itself, which could use the payload._cron.ts property to determine whether execution should continue or not.

Forbidden flags

When a job is created (or updated via job_key), you may set its flags to a list of strings. When the worker is run in library mode, you may pass the forbidden_flags option to indicate that jobs with any of the given flags should not be executed.

The forbidden_flags option can be:

  • null
  • an array of strings
  • a function returning null or an array of strings
  • an (async) function returning a promise that resolve to null or an array of strings

If forbidden_flags is a function, graphile-worker will invoke it each time a worker looks for a job to run, and will skip over any job that has any flag returned by your function. You should ensure that forbidden_flags resolves quickly; it's advised that you maintain a cache you update periodically (e.g. once a second) rather than always calculating on the fly, or use pub/sub or a similar technique to maintain the forbidden flags list.

For an example of how this can be used to achieve rate-limiting logic

Rationality checks

We recommend that you limit queue_name, task_identifier and job_key to printable ASCII characters.

  • queue_name can be at most 128 characters long
  • task_identifier can be at most 128 characters long
  • job_key can be at most 512 characters long
  • schema should be reasonable; max 32 characters is preferred. Defaults to graphile_worker (15 chars)


To delete the worker code and all the tasks from your database, just run this one SQL statement:

DROP SCHEMA archimedes_worker CASCADE;


archimedes_worker is not intended to replace extremely high performance dedicated job queues, it's intended to be a very easy way to get a reasonably performant job queue up and running with rust and PostgreSQL. But this doesn't mean it's a slouch by any means - it achieves an average latency from triggering a job in one process to executing it in another of under 3ms, and a 12-core database server can queue around 99,600 jobs per second and can process around 11,800 jobs per second.

archimedes_worker is horizontally scalable. Each instance has a customisable worker pool, this pool defaults to size 1 (only one job at a time on this worker) but depending on the nature of your tasks (i.e. assuming they're not compute-heavy) you will likely want to set this higher to benefit from Node.js' concurrency. If your tasks are compute heavy you may still wish to set it higher and then using Node's child_process (or Node v11's worker_threads) to share the compute load over multiple cores without significantly impacting the main worker's runloop. Note, however, that Graphile Worker is limited by the performance of the underlying Postgres database, and when you hit this limit performance will start to go down (rather than up) as you add more workers.

perfTest results:



We currently use the formula exp(least(10, attempt)) to determine the delays between attempts (the job must fail before the next attempt is scheduled, so the total time elapsed may be greater depending on how long the job runs for before it fails). This seems to handle temporary issues well, after ~4 hours attempts will be made every ~6 hours until the maximum number of attempts is achieved. The specific delays can be seen below:

  exp(least(10, attempt)) * interval '1 second' as delay,
  sum(exp(least(10, attempt)) * interval '1 second') over (order by attempt asc) total_delay
from generate_series(1, 24) as attempt;

 attempt |      delay      |   total_delay
       1 | 00:00:02.718282 | 00:00:02.718282
       2 | 00:00:07.389056 | 00:00:10.107338
       3 | 00:00:20.085537 | 00:00:30.192875
       4 | 00:00:54.598150 | 00:01:24.791025
       5 | 00:02:28.413159 | 00:03:53.204184
       6 | 00:06:43.428793 | 00:10:36.632977
       7 | 00:18:16.633158 | 00:28:53.266135
       8 | 00:49:40.957987 | 01:18:34.224122
       9 | 02:15:03.083928 | 03:33:37.308050
      10 | 06:07:06.465795 | 09:40:43.773845
      11 | 06:07:06.465795 | 15:47:50.239640
      12 | 06:07:06.465795 | 21:54:56.705435
      13 | 06:07:06.465795 | 28:02:03.171230
      14 | 06:07:06.465795 | 34:09:09.637025
      15 | 06:07:06.465795 | 40:16:16.102820
      16 | 06:07:06.465795 | 46:23:22.568615
      17 | 06:07:06.465795 | 52:30:29.034410
      18 | 06:07:06.465795 | 58:37:35.500205
      19 | 06:07:06.465795 | 64:44:41.966000
      20 | 06:07:06.465795 | 70:51:48.431795
      21 | 06:07:06.465795 | 76:58:54.897590
      22 | 06:07:06.465795 | 83:06:01.363385
      23 | 06:07:06.465795 | 89:13:07.829180
      24 | 06:07:06.465795 | 95:20:14.294975

What if something goes wrong?

If a job throws an error, the job is failed and scheduled for retries with exponential back-off. We use async/await so assuming you write your task code well all errors should be cascaded down automatically.

TODO If the worker is terminated (SIGTERM, SIGINT, etc), it triggers a graceful shutdown - i.e. it stops accepting new jobs, waits for the existing jobs to complete, and then exits. If you need to restart your worker, you should do so using this graceful process.

If the worker completely dies unexpectedly (e.g. panic, SIGKILL) then the jobs that that worker was executing remain locked for at least 4 hours. Every 8-10 minutes a worker will sweep for jobs that have been locked for more than 4 hours and will make them available to be processed again automatically. If you run many workers, each worker will do this, so it's likely that jobs will be released closer to the 4 hour mark. You can unlock jobs earlier than this by clearing the locked_at and locked_by columns on the relevant tables.

If the worker schema has not yet been installed into your database, the following error may appear in your PostgreSQL server logs. This is completely harmless and should only appear once as the worker will create the schema for you.

ERROR: relation "archimedes_worker.migrations" does not exist at character 16
STATEMENT: select id from "graphile_worker".migrations order by id desc limit 1;

Error codes

  • GWBKM - Invalid job_key_mode value, expected 'replace', 'preserve_run_at' or 'unsafe_dedupe'.

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