Supabase is an open-source alternative to Firebase that offers a wide range of capabilities for building robust and scalable applications. One of the key advantages of Supabase is its integration with PostgreSQL, a powerful and reliable database management system. In this blog post, we will explore how to leverage Supabase and PostgreSQL to create a highly efficient queue system.
A queue system is crucial for handling asynchronous tasks and managing job processing. By utilizing a queue, we can ensure that tasks are processed in a controlled and organized manner, improving performance and scalability. Let's dive into the process of setting up a queue system with Supabase and PostgreSQL.
Setting up the Queue System
To set up the queue system, we need to enable the required extensions in PostgreSQL. Specifically, we need to enable the pg_net and pg_cron extensions, which provide the necessary functionality for our queue system.
Please navigate to the Extensions page in your Supabase project and enable both the pg_net and pg_cron extensions.
Next, we can define the necessary table structure. The three key tables we'll be working with are job_queue, current_jobs, and workers. The job_queue table stores the pending jobs, while the current_jobs table keeps track of the jobs currently being processed. The workers table maintains records of the available worker instances.
To create these tables, execute the following SQL code:
CREATE TABLE job_queue (
job_id serial PRIMARY KEY,
http_verb TEXT NOT NULL CHECK (http_verb IN ('GET', 'POST', 'DELETE')),
payload jsonb,
status TEXT NOT NULL DEFAULT '',
retry_count INTEGER DEFAULT 0,
retry_limit INTEGER DEFAULT 10,
url_path TEXT DEFAULT '',
content TEXT DEFAULT '',
created_at TIMESTAMPTZ DEFAULT NOW()
);
CREATE TABLE current_jobs (
request_id BIGINT NOT NULL,
job_id BIGINT NOT NULL
);
CREATE TABLE workers (
id SERIAL PRIMARY KEY,
locked BOOLEAN NOT NULL DEFAULT FALSE
);
-- Adding two workers:
INSERT INTO workers (locked)
VALUES (FALSE), (FALSE);
-- You can also add a worker with:
INSERT INTO workers
DEFAULT VALUES;
-- Adding 10 workers:
do $$
begin
execute (
select string_agg('INSERT INTO workers DEFAULT VALUES',';')
from generate_series(1,10)
);
end;
$$;
Functions for Job Processing
To process jobs in the queue system, we must define several functions that work together. Let's discuss the purpose and functionality of each function:
process_current_jobs_if_unlocked
:This function checks if there is an available worker by selecting an unlocked worker from theworkers
table. If a worker is found, it locks the worker, processes the current jobs using theprocess_current_jobs
function, and unlocks the worker afterward.process_current_jobs
: This function iterates over the records in thecurrent_jobs
table and retrieves the response from thepg_net
extension using thenet._http_collect_response
function. It checks the status and status code of the response and performs the necessary actions based on the result. If the job is successful, it updates thejob_queue
table with the completion status and content and deletes the corresponding record from thecurrent_jobs
table. If the job fails, it updates thejob_queue
table with the failure status and increases the retry count, and deletes the record from thecurrent_jobs
table. If the job is still in progress or not found, it raises a notice.process_job
: This trigger function is called after a record is inserted into thejob_queue
table. It updates the status of the job to "processing" and retrieves the API key from thevault.decrypted_secrets
table. It then calls therequest_wrapper
function to process the job by making an HTTP request to the specified URL. The request ID is inserted into thecurrent_jobs
table for tracking purposes.request_wrapper
: This function is a convenience wrapper around thepg_net
extension functions (net.http_delete
,net.http_post
, andnet.http_get
) for making HTTP requests. It accepts the method, URL, parameters, body, and headers as input and returns the request ID.retry_failed_jobs
: This function is responsible for retrying failed jobs. It selects the failed jobs from thejob_queue
table based on the status and retry count. It then updates the retry count and calls therequest_wrapper
function to process the job again. The new request ID is inserted into thecurrent_jobs
table.
The trigger function process_job()
plays a vital role in executing job processing when a new job is added to the queue. Then, there are schedule functions to update the status and response acquired from the requests.
--
-- Execute current jobs function if there are available workers
--
CREATE OR REPLACE FUNCTION process_current_jobs_if_unlocked()
RETURNS VOID AS $$
DECLARE
worker RECORD;
BEGIN
-- Find an unlocked worker
SELECT * INTO worker FROM workers FOR UPDATE SKIP LOCKED LIMIT 1;
IF worker IS NOT NULL THEN
RAISE NOTICE 'Using worker_id: %', worker.id;
-- Lock the worker (this is already done by the SELECT ... FOR UPDATE)
-- Process current jobs
PERFORM process_current_jobs();
-- Unlock the worker
UPDATE workers SET locked = FALSE WHERE id = worker.id;
ELSE
RAISE NOTICE 'No unlocked workers available';
END IF;
END;
$$ LANGUAGE plpgsql;
--
-- Loop through records in current_jobs and get response from pg_net
--
CREATE OR REPLACE FUNCTION process_current_jobs()
RETURNS VOID
SECURITY DEFINER
SET search_path = public, extensions, net, vault
AS $$
DECLARE
current_job RECORD;
response_result RECORD;
BEGIN
FOR current_job IN SELECT * FROM current_jobs
FOR UPDATE SKIP LOCKED
LOOP
RAISE NOTICE 'Processing job_id: %, request_id: %', current_job.job_id, current_job.request_id;
SELECT
status,
(response).status_code AS status_code,
(response).body AS body
INTO response_result
FROM net._http_collect_response(current_job.request_id);
IF response_result.status = 'SUCCESS' AND response_result.status_code BETWEEN 200 AND 299 THEN
RAISE NOTICE 'Job completed (job_id: %)', current_job.job_id;
UPDATE job_queue
SET status = 'complete',
content = response_result.body::TEXT
WHERE job_id = current_job.job_id;
DELETE FROM current_jobs
WHERE request_id = current_job.request_id;
ELSIF response_result.status = 'ERROR' THEN
RAISE NOTICE 'Job failed (job_id: %)', current_job.job_id;
UPDATE job_queue
SET status = 'failed',
retry_count = retry_count + 1
WHERE job_id = current_job.job_id;
DELETE FROM current_jobs
WHERE request_id = current_job.request_id;
ELSE
RAISE NOTICE 'Job still in progress or not found (job_id: %)', current_job.job_id;
END IF;
END LOOP;
END;
$$ LANGUAGE plpgsql;
--
-- Called after a record is insert in the queue
--
CREATE OR REPLACE FUNCTION process_job()
RETURNS TRIGGER
SECURITY DEFINER
SET search_path = public, extensions, net, vault
AS $$
DECLARE
request_id BIGINT;
api_key TEXT;
did_timeout BOOLEAN;
response_message TEXT;
response_status_code INTEGER;
BEGIN
RAISE NOTICE 'Processing job_id: %', NEW.job_id;
UPDATE job_queue
SET status = 'processing'
WHERE job_id = NEW.job_id;
-- Get the API key
SELECT decrypted_secret
INTO api_key
FROM vault.decrypted_secrets
WHERE name = 'service_role';
-- Call the request_wrapper to process the job
request_id := request_wrapper(
method := NEW.http_verb,
url := 'https://contoso.supabase.co/functions/v1/consume_job' || COALESCE(NEW.url_path, ''),
body := COALESCE(NEW.payload::jsonb, '{}'::jsonb),
headers := jsonb_build_object('Authorization', 'Bearer ' || api_key, 'Content-Type', 'application/json')
);
INSERT INTO current_jobs (request_id, job_id)
VALUES (request_id, NEW.job_id);
RETURN NEW;
END;
$$ LANGUAGE plpgsql;
--
-- Convenience function around pg_net:
--
CREATE OR REPLACE FUNCTION request_wrapper(
method TEXT,
url TEXT,
params JSONB DEFAULT '{}'::JSONB,
body JSONB DEFAULT '{}'::JSONB,
headers JSONB DEFAULT '{}'::JSONB
)
RETURNS BIGINT
SECURITY DEFINER
SET search_path = public, extensions, net
LANGUAGE plpgsql
AS $$
DECLARE
request_id BIGINT;
timeout INT;
BEGIN
timeout := 3000;
IF method = 'DELETE' THEN
SELECT net.http_delete(
url:=url,
params:=params,
headers:=headers,
timeout_milliseconds:=timeout
) INTO request_id;
ELSIF method = 'POST' THEN
SELECT net.http_post(
url:=url,
body:=body,
params:=params,
headers:=headers,
timeout_milliseconds:=timeout
) INTO request_id;
ELSIF method = 'GET' THEN
SELECT net.http_get(
url:=url,
params:=params,
headers:=headers,
timeout_milliseconds:=timeout
) INTO request_id;
ELSE
RAISE EXCEPTION 'Method must be DELETE, POST, or GET';
END IF;
RETURN request_id;
END;
$$;
--
-- Retrying jobs flagged as failures to increase reliability
--
CREATE OR REPLACE FUNCTION retry_failed_jobs()
RETURNS VOID
SECURITY DEFINER
SET search_path = public, extensions, net, vault
AS $$
DECLARE
r RECORD;
request_id BIGINT;
api_key TEXT;
response_result net._http_response_result;
BEGIN
RAISE NOTICE 'Retrying failed jobs';
-- Get the API key
SELECT decrypted_secret
INTO api_key
FROM vault.decrypted_secrets
WHERE name = 'service_role';
FOR r IN (
SELECT * FROM job_queue
WHERE status = 'failed' AND retry_count < retry_limit
FOR UPDATE SKIP LOCKED
) LOOP
RAISE NOTICE 'Retrying job_id: %', r.job_id;
UPDATE job_queue
SET retry_count = retry_count + 1
WHERE job_id = r.job_id;
-- Call the request_wrapper to process the job
request_id := request_wrapper(
method := r.http_verb,
-- Edge function call (like AWS lambda)
url := 'https://contoso.supabase.co/functions/v1/consume_job' || COALESCE(r.url_path, ''),
body := COALESCE(r.payload::jsonb, '{}'::jsonb),
headers := jsonb_build_object('Authorization', 'Bearer ' || api_key, 'Content-Type', 'application/json')
);
INSERT INTO current_jobs (request_id, job_id)
VALUES (request_id, r.job_id);
END LOOP;
END;
$$ LANGUAGE plpgsql;
-- Adding the trigger to the queue table:
CREATE TRIGGER process_job_trigger
AFTER INSERT ON job_queue
FOR EACH ROW
EXECUTE FUNCTION process_job();
These functions work together to process jobs in the queue system, handle retries for failed jobs, and ensure the proper flow of job execution. We are also using Postgres SKIP LOCKED feature on the following functions: retry_failed_jobs()
, process_current_jobs()
and process_current_jobs_if_unlocked()
.
Scheduling Tasks
Scheduling tasks is essential for regular job processing and retrying failed jobs. In this part, we'll explore how to schedule tasks using the cron.schedule()
function in PostgreSQL.
Scheduling Retry Jobs
To automatically retry failed jobs at specific intervals, we can use the cron.schedule()
function. Here's an example:
SELECT cron.schedule(
'retry_failed_jobs',
'*/10 * * * *',
$$ SELECT retry_failed_jobs(); $$
);
In this example, the retry_failed_jobs
function is scheduled to run every 10 minutes (*/10 * * * *
). This function is responsible for retrying failed jobs by calling the retry_failed_jobs()
function.
Scheduling Current Job Processing
To process current jobs periodically, we can schedule the process_current_jobs_if_unlocked
function. Here's an example:
SELECT cron.schedule(
'process_current_jobs_if_unlocked_',
'* * * * *',
$$ SELECT process_current_jobs_if_unlocked(); $$
);
In this example, the process_current_jobs_if_unlocked
function is scheduled to run every minute (* * * * *
). This function checks if there is an unlocked worker available and processes current jobs if there is one.
Setting Up Sub-Minute Pooling
For an optimal setup that distributes the workload evenly, we can use sub-minute pooling with the help of pg_sleep()
. Here's an example:
-- Run this in PSQL to schedule pooling workers 20 seconds apart:
SET statement_timeout TO 0;
CREATE OR REPLACE FUNCTION schedule_jobs()
RETURNS VOID
AS $body$
BEGIN
-- Schedule retry job
SELECT cron.schedule(
'retry_failed_jobs',
'*/10 * * * *',
$$ SELECT retry_failed_jobs(); $$
);
-- Schedule first job
PERFORM cron.schedule(
'process_current_jobs_if_unlocked_job_1',
'* * * * *',
$$ SELECT process_current_jobs_if_unlocked(); $$
);
-- Schedule second job with a 20-second delay
PERFORM pg_sleep(20);
PERFORM cron.schedule(
'process_current_jobs_if_unlocked_job_2',
'* * * * *',
$$ SELECT process_current_jobs_if_unlocked(); $$
);
-- Schedule third job with another 20-second delay
PERFORM pg_sleep(20);
PERFORM cron.schedule(
'process_current_jobs_if_unlocked_job_3',
'* * * * *',
$$ SELECT process_current_jobs_if_unlocked(); $$
);
END;
$body$ LANGUAGE plpgsql;
In this example, we define the schedule_jobs()
function to set up the scheduling. Firstly, we set the statement timeout to 0 to avoid any timeouts during the execution. Then, we schedule the retry job and the first job to run immediately. After that, we introduce a 20-second delay using pg_sleep(20)
before scheduling the second and third jobs. This delay helps distribute the jobs evenly across multiple workers.
By using the cron.schedule()
function and setting up sub-minute pooling, we can ensure that failed jobs are retried periodically and parallel jobs are processed efficiently.
Consuming the Queue with Supabase Edge Function
Supabase Edge Functions play a crucial role in serverless execution at the edge. They can be used to consume tasks from the job queue. Here's an example of an Edge Function that fetches and processes jobs from the queue:
import { serve } from "https://deno.land/std@0.192.0/http/server.ts";
console.log("Function that will handle the tasks!");
serve(async (req) => {
const payload = await req.text();
const url = new URL(req.url);
const headers = req.headers;
const method = req.method;
// Bundle variables in the 'data' variable as a JSON object
const data = { payload, url, headers, method };
return new Response(
JSON.stringify(data),
{ headers: { "Content-Type": "application/json" } },
);
});
Securing the SQL Functions
Securing the SQL functions is of utmost importance to prevent unauthorized access. To revoke the execution permission on the functions from anonymous and authenticated users, you can use the following SQL code:
-- SQL code to revoke execute permission on the functions
REVOKE ALL PRIVILEGES ON FUNCTION process_current_jobs_if_unlocked
FROM anon, authenticated;
REVOKE ALL PRIVILEGES ON FUNCTION process_job
FROM anon, authenticated;
REVOKE ALL PRIVILEGES ON FUNCTION process_current_jobs
FROM anon, authenticated;
REVOKE ALL PRIVILEGES ON FUNCTION request_wrapper
FROM anon, authenticated;
REVOKE ALL PRIVILEGES ON FUNCTION retry_failed_jobs
FROM anon, authenticated;
Conclusion
Building a queue system with Supabase and PostgreSQL offers a powerful solution for handling asynchronous tasks and managing job processing. By leveraging the table structure, functions, scheduled tasks, and edge functions, you can create a robust and scalable queue system.
In this blog post, we explored the process of setting up the queue system, which involved enabling the necessary PostgreSQL extensions, defining functions for job processing, scheduling tasks, securing the functions, and consuming the queue using Supabase Edge Functions. Note that this example takes into consideration the URL path to execute and you could expand it with similar ideas to the RESTful service example.
With a complete understanding of both processing and consuming the jobs in the queue, you now have the knowledge to implement a highly efficient queue system in your applications. Happy queuing!