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  1. Design of a reliable task processing queue

    Alex Burkhart <burkharta77@gmail.com> — 2025-01-18T10:44:07Z

    Hey team,

I'm looking for help to organize locks and transaction for a reliable task
queue.

REQUIREMENTS

1. Pending actions are persisted to a database. There's a trace once they
are done.
2. Application workers pick actions one by one. At any given time, each
action can be assigned to at most one worker (transaction).
3. If multiple actions have same "lock_id", only one of them is processed
at the time. That has to be action with smallest id.

MY ATTEMPT

I got something approximate working with the following setup.

=== BEGIN DATABASE QUERY ===

DROP TABLE IF EXISTS actions;

CREATE TABLE actions (
  id SERIAL PRIMARY KEY,
  lock_id BIGINT,
  action VARCHAR(255),
  done BOOLEAN DEFAULT false
);

-- Sample data for testing.

INSERT INTO actions (lock_id, action) VALUES
  (26, 'Create instance 26'),
  (8, 'Update instance 8'),
  (26, 'Update instance 26'),
  (8, 'Delete instance 8');

=== END DATABASE QUERY ===

I use Go client to simulate workers utilizing the "actions" table.

=== BEGIN GO CLIENT ===

package main

import (
"context"
"fmt"
"os"
"os/signal"
"time"

"github.com/jackc/pgx/v5/pgxpool"
)

func main() {
ctx, cancel := signal.NotifyContext(context.Background(), os.Interrupt)
defer cancel()

pool, err := pgxpool.New(ctx, "postgres://postgres:password@localhost
/database")
if err != nil {
panic(err)
}
defer pool.Close()

tx, err := pool.Begin(ctx)
if err != nil {
panic(err)
}
defer tx.Rollback(ctx)

fmt.Println("BEGIN")

var (
id     int32
lockid int64
action string
)
if err := tx.QueryRow(
ctx,
`SELECT id, lock_id, action
     FROM actions
     WHERE done = false
     ORDER BY id
     LIMIT 1
     FOR NO KEY UPDATE
     SKIP LOCKED`,
).Scan(&id, &lockid, &action); err != nil {
panic(err)
}

fmt.Println("LOCKING", lockid, "...")

if _, err := tx.Exec(ctx, fmt.Sprintf("SELECT pg_advisory_xact_lock(%d)",
lockid)); err != nil {
panic(err)
}

fmt.Println("EXECUTING", action)

select {
case <-ctx.Done():
// Pretend to do work for 10 seconds.
case <-time.After(10 * time.Second):
if _, err := tx.Exec(ctx, "UPDATE actions SET done = true WHERE id = $1",
id); err != nil {
panic(err)
}
if err := tx.Commit(ctx); err != nil {
panic(err)
}

fmt.Println("DONE")
}

fmt.Println("UNLOCKED")
}

=== END GO CLIENT ===

This code generates transaction like this.

=== BEGIN TRANSACTION ===

BEGIN;

-- Lock one row in "actions" table.

SELECT id, lock_id, action
FROM actions
WHERE done = false
ORDER BY id
LIMIT 1
FOR NO KEY UPDATE
SKIP LOCKED;

-- Lock other transactions that process same lock_id.

SELECT pg_advisory_xact_lock(%lock_id);

-- Work on the action... mark it done at the end.

UPDATE actions SET done = true WHERE id = %d;

COMMIT;

=== END TRANSACTION ===

Which almost does the job. By running the Go client concurrently, it picks
actions one by one and processes only one transaction with same "lock_id"
at a time.

However I'm worried about the gap between the row lock and "lock_id" lock.
This leaves a room for requirement "That has to be action with smallest id"
to be unsatisfied.

QUESTION

Is there a way to improve this attempt and close the gap? Or a completely
different strategy? I was brainstorming how to lock all rows where columns
have the same value or using ARRAY but struggle to put together a reliable
solution.

Thank you,
Alex

  2. Re: Design of a reliable task processing queue

    Peter J. Holzer <hjp-pgsql@hjp.at> — 2025-01-19T11:37:01Z

    On 2025-01-18 19:44:07 +0900, Alex Burkhart wrote:
> REQUIREMENTS
> 
> 1. Pending actions are persisted to a database. There's a trace once they are
> done.
> 2. Application workers pick actions one by one. At any given time, each action
> can be assigned to at most one worker (transaction).
> 3. If multiple actions have same "lock_id", only one of them is processed at
> the time. That has to be action with smallest id.
> 
> MY ATTEMPT
> 
> I got something approximate working with the following setup.
> 
> === BEGIN DATABASE QUERY ===
> 
> DROP TABLE IF EXISTS actions;
> 
> CREATE TABLE actions (
>   id SERIAL PRIMARY KEY,
>   lock_id BIGINT,
>   action VARCHAR(255),
>   done BOOLEAN DEFAULT false
> );
> 
[... removed Go code ...]
> This code generates transaction like this.
> 
> === BEGIN TRANSACTION ===
> 
> BEGIN;
> 
> -- Lock one row in "actions" table.
> 
> SELECT id, lock_id, action
> FROM actions
> WHERE done = false
> ORDER BY id
> LIMIT 1
> FOR NO KEY UPDATE
> SKIP LOCKED;
> 
> -- Lock other transactions that process same lock_id.
> 
> SELECT pg_advisory_xact_lock(%lock_id);
> 
> -- Work on the action... mark it done at the end.
> 
> UPDATE actions SET done = true WHERE id = %d;
> 
> COMMIT;
> 
> === END TRANSACTION ===
> 
> Which almost does the job. By running the Go client concurrently, it picks
> actions one by one and processes only one transaction with same "lock_id" at a
> time.
> 
> However I'm worried about the gap between the row lock and "lock_id" lock. This
> leaves a room for requirement "That has to be action with smallest id" to be
> unsatisfied.

I'd be worried about that, too.

Let's assume you have two entries in your queue:

    123, 26, 'Create instance 26', false
    124, 26, 'Update instance 26', false

And also two worker threads. Then this scenario is possible:

    Worker A executes the SELECT ... SKIP LOCKED query and gets the
    record with ID 123

    Worker B executes the SELECT ... SKIP LOCKED query. Since record 123
    is already locked it gets the record with ID 124

    Worker B executes the SELECT pg_advisory_xact_lock(26) query
    successfully and can continue

    Worker A executes the SELECT pg_advisory_xact_lock(26) query, but
    blocks and has to wait for worker B to commit (or rollback).

So in this case the update would happen before the create, which isn't
good.


> QUESTION
> 
> Is there a way to improve this attempt and close the gap?

I'm not sure if I like this solution (if feels a bit hacky), but the
following should work, IMHO:

 1) After the first select, do another on all records with the same
    lock_id:
      SELECT id, lock_id, action
          FROM actions
          WHERE lock_id = %d AND done = false
          ORDER BY id
          FOR NO KEY UPDATE
 2) Check whether the id you got first is the smallest of all.
 3) If it isn't, rollback and start over.
 4) If it is, you have now locked all the rows with the same lock_id and
    can continue.

The advisory lock isn't needed then.

        hp

-- 
   _  | Peter J. Holzer    | Story must make more sense than reality.
|_|_) |                    |
| |   | hjp@hjp.at         |    -- Charles Stross, "Creative writing
__/   | http://www.hjp.at/ |       challenge!"

  3. Re: Design of a reliable task processing queue

    Shaheed Haque <shaheedhaque@gmail.com> — 2025-01-19T15:17:14Z

    As with all things distributed, it's useful to start with some notion of
what the word "reliable" means to you. For example, when your pseudo code,
is replaced by the real code, can that fail? And if it fails, is it known
that the work in hand can simply be redone?

Those answers will need to be understood alongside the design of the db
handling, to ensure the real world behaviour is as required.

On Sun, 19 Jan 2025, 08:23 Alex Burkhart, <burkharta77@gmail.com> wrote:

> Hey team,
>
> I'm looking for help to organize locks and transaction for a reliable task
> queue.
>
> REQUIREMENTS
>
> 1. Pending actions are persisted to a database. There's a trace once they
> are done.
> 2. Application workers pick actions one by one. At any given time, each
> action can be assigned to at most one worker (transaction).
> 3. If multiple actions have same "lock_id", only one of them is processed
> at the time. That has to be action with smallest id.
>
> MY ATTEMPT
>
> I got something approximate working with the following setup.
>
> === BEGIN DATABASE QUERY ===
>
> DROP TABLE IF EXISTS actions;
>
> CREATE TABLE actions (
>   id SERIAL PRIMARY KEY,
>   lock_id BIGINT,
>   action VARCHAR(255),
>   done BOOLEAN DEFAULT false
> );
>
> -- Sample data for testing.
>
> INSERT INTO actions (lock_id, action) VALUES
>   (26, 'Create instance 26'),
>   (8, 'Update instance 8'),
>   (26, 'Update instance 26'),
>   (8, 'Delete instance 8');
>
> === END DATABASE QUERY ===
>
> I use Go client to simulate workers utilizing the "actions" table.
>
> === BEGIN GO CLIENT ===
>
> package main
>
> import (
> "context"
> "fmt"
> "os"
> "os/signal"
> "time"
>
> "github.com/jackc/pgx/v5/pgxpool"
> )
>
> func main() {
> ctx, cancel := signal.NotifyContext(context.Background(), os.Interrupt)
> defer cancel()
>
> pool, err := pgxpool.New(ctx, "postgres://postgres:password@localhost
> /database")
> if err != nil {
> panic(err)
> }
> defer pool.Close()
>
> tx, err := pool.Begin(ctx)
> if err != nil {
> panic(err)
> }
> defer tx.Rollback(ctx)
>
> fmt.Println("BEGIN")
>
> var (
> id     int32
> lockid int64
> action string
> )
> if err := tx.QueryRow(
> ctx,
> `SELECT id, lock_id, action
>      FROM actions
>      WHERE done = false
>      ORDER BY id
>      LIMIT 1
>      FOR NO KEY UPDATE
>      SKIP LOCKED`,
> ).Scan(&id, &lockid, &action); err != nil {
> panic(err)
> }
>
> fmt.Println("LOCKING", lockid, "...")
>
> if _, err := tx.Exec(ctx, fmt.Sprintf("SELECT pg_advisory_xact_lock(%d)",
> lockid)); err != nil {
> panic(err)
> }
>
> fmt.Println("EXECUTING", action)
>
> select {
> case <-ctx.Done():
> // Pretend to do work for 10 seconds.
> case <-time.After(10 * time.Second):
> if _, err := tx.Exec(ctx, "UPDATE actions SET done = true WHERE id = $1",
> id); err != nil {
> panic(err)
> }
> if err := tx.Commit(ctx); err != nil {
> panic(err)
> }
>
> fmt.Println("DONE")
> }
>
> fmt.Println("UNLOCKED")
> }
>
> === END GO CLIENT ===
>
> This code generates transaction like this.
>
> === BEGIN TRANSACTION ===
>
> BEGIN;
>
> -- Lock one row in "actions" table.
>
> SELECT id, lock_id, action
> FROM actions
> WHERE done = false
> ORDER BY id
> LIMIT 1
> FOR NO KEY UPDATE
> SKIP LOCKED;
>
> -- Lock other transactions that process same lock_id.
>
> SELECT pg_advisory_xact_lock(%lock_id);
>
> -- Work on the action... mark it done at the end.
>
> UPDATE actions SET done = true WHERE id = %d;
>
> COMMIT;
>
> === END TRANSACTION ===
>
> Which almost does the job. By running the Go client concurrently, it picks
> actions one by one and processes only one transaction with same "lock_id"
> at a time.
>
> However I'm worried about the gap between the row lock and "lock_id" lock.
> This leaves a room for requirement "That has to be action with smallest id"
> to be unsatisfied.
>
> QUESTION
>
> Is there a way to improve this attempt and close the gap? Or a completely
> different strategy? I was brainstorming how to lock all rows where columns
> have the same value or using ARRAY but struggle to put together a reliable
> solution.
>
> Thank you,
> Alex
>

  4. Re: Design of a reliable task processing queue

    auxsvr@gmail.com — 2025-01-19T16:06:12Z

    On Saturday, 18 January 2025 12:44:07 EET Alex Burkhart wrote:
> Hey team,
> 
> I'm looking for help to organize locks and transaction for a reliable task
> queue.
> 
> REQUIREMENTS
> 
> 1. Pending actions are persisted to a database. There's a trace once they
> are done.
> 2. Application workers pick actions one by one. At any given time, each
> action can be assigned to at most one worker (transaction).
> 3. If multiple actions have same "lock_id", only one of them is processed
> at the time. That has to be action with smallest id.

Why reinvent the wheel and not use production-ready code from projects such as que (Ruby), pgqueuer (Python)?
-- 
Regards,
Peter

  5. Re: Design of a reliable task processing queue

    Dominique Devienne <ddevienne@gmail.com> — 2025-01-21T12:21:36Z

    On Sun, Jan 19, 2025 at 9:23 AM Alex Burkhart <burkharta77@gmail.com> wrote:
> I'm looking for help to organize locks and transaction for a reliable task queue.

Have a look at https://github.com/tembo-io/pgmq for inspiration maybe. --DD