Preventing Race Conditions with SERIALIZABLE Isolation in Supabase for High-Concurrency Updates

Question

Question: I'm working with Supabase/PostgreSQL in a Next.js application and need to ensure that an is_processing flag is updated only once per user, even if multiple requests are sent in parallel. The goal is to prevent any duplicate operations by ensuring that once is_processing = true, additional requests won’t proceed until it’s reset.

Approach So Far I initially created a PostgreSQL function using SERIALIZABLE isolation to handle concurrency, with the function attempting to set is_processing to true if it’s initially false. Here’s the function:

CREATE OR REPLACE FUNCTION serialized_update_processing_flag(user_id UUID) RETURNS BOOLEAN AS $$
DECLARE
    result BOOLEAN;
BEGIN
    SET TRANSACTION ISOLATION LEVEL SERIALIZABLE;
UPDATE users
SET is_processing = true
WHERE id = user_id
  AND is_processing = false
RETURNING true INTO result;

RETURN result IS NOT NULL;

EXCEPTION
    WHEN serialization_failure THEN
        RETURN FALSE;
END;
$$ LANGUAGE plpgsql;

Problem: Running this function directly throws an error: "SET TRANSACTION ISOLATION LEVEL must be called before any query."

Alternative Implementation in Next.js I moved the transaction management into my Next.js code, starting with SERIALIZABLE isolation at the application level. Here’s the revised approach:

const client = await pool.connect();
try {
  // Start a transaction with SERIALIZABLE isolation level
  await client.query('BEGIN');
  await client.query('SET TRANSACTION ISOLATION LEVEL SERIALIZABLE');
// Call the RPC function
  const { rows } = await client.query(
    'SELECT serialized_update_recharge_flag($1) AS success',
    [userId]
  );
await client.query('COMMIT');
// Check the result
  console.log('ROWWW', rows);
  return rows[0].success;
} catch (error) {
  await client.query('ROLLBACK');
  console.error(Error in serialized transaction: ${error});
  throw error;
} finally {
  client.release();
}

Issue with High-Concurrency Requests This approach has been somewhat effective, but when I simulate around 30 parallel requests, some of them still manage to bypass the SERIALIZABLE isolation level, resulting in multiple operations setting is_processing = true concurrently.

Questions How can I reliably enforce strict SERIALIZABLE isolation in this setup to prevent any concurrent updates from slipping through? Are there alternative methods in PostgreSQL or Supabase for handling high-concurrency, single-update situations with atomicity? I’d appreciate any suggestions or solutions to ensure consistent behavior and prevent duplicate operations, especially under high parallel loads. Thank you!

Preventing Race Conditions with SERIALIZABLE Isolation in Supabase for High-Concurrency Updates

0 Answers0