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@xxxxxxxxx> 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
