many queries postgres (node), no parallel queries? - node.js

Question

I am running a node server with the postgres-node (pg) package.
I wrote a program, which requests n-queries (for instance 20,000) at once to my postgres database.
When I do this with several clients who want to query 20,000 at once too, there is no parallelity. That means, the requests of the second client will be queued until the first client finished all his queries.
Is this a normal behavior for postgres? If yes, how can I prevent that one user gets all the ressources (and the others have to wait) if there is no parallelity?
This is my code:
const express = require('express');
const app = express();
const { Pool } = require("pg");
const pool = new Pool();
benchmark(){
pool.connect((err, client, done) => {
if (err) throw err;
client.query("SELECT * from member where m_id = $1", [1], (err, res) => {
done();
if (err) {
console.log(err.stack);
} else {
console.log(res.rows[0]);
}
});
});
}
app.get('/', function(req, res) {
for(let i=0;i<20000;i++){
benchmark();
}
});

Answer 1

First you need to create a connection pool, here's an example with node's pg in a separate module (node-pg-sql.js) for convenience:
node-pg-sql.js:
const { Pool } = require('pg');
const pool = new Pool(fileNameConfigPGSQL);
module.exports = {
query: (text, params, callback) => {
const start = Date.now()
return pool.query(text, params, (err, res) => {
const duration = Date.now() - start
// console.log('executed query', { text, duration, rows: res.rowCount })
callback(err, res)
})
},
getClient: (callback) => {
pool.connect((err, client, done) => {
const query = client.query.bind(client)
// monkey patch
client.query = () => {
client.lastQuery = arguments
client.query.apply(client, arguments)
}
// Timeout 5 sek
const timeout = setTimeout(() => {
// console.error('A client has been checked out for more than 5 seconds!')
// console.error(`The last executed query on this client was: ${client.lastQuery}`)
}, 5000)
const release = (err) => {
// 'done' Methode - returns client to the pool
done(err)
// clear Timeouts
clearTimeout(timeout)
// reset der Query-Method before Monkey Patch
client.query = query
}
callback(err, client, done)
})
}
}
In your postgresql.conf (on linux normally under /var/lib/pgsql/data/postgresql.conf) set max-connection to the desired value:
max_connection = 300
Keep in mind:
Each PostgreSQL connection consumes RAM for managing the connection or the client using it. The more connections you have, the more RAM you will be using that could instead be used to run the database.
While increasing your max-connections, you need to increase shared_buffers and kernel.shmmax as well in order for the client-connection increase to be effective .
Whenever you want to run a query from in one of your routes/endpoints just require the separate client-pool-file like:
const db = require('../../../node-pg-sql');
module.exports = (router) => {
router.get('/someRoute', (req, res) => {
console.log(`*****************************************`);
console.log(`Testing pg..`);
let sqlSelect = `SELECT EXISTS (
SELECT 1
FROM pg_tables
WHERE schemaname = 'someschema'
)`;
db.query(sqlSelect, (errSelect, responseSelect) => {
if (errSelect) {
/* INFO: Error while querying table */
console.log(`*****************************************`);
console.log(`ERROR WHILE CHECKING CONNECTION: ${errSelect}`);
}
else {
// INFO: No error from database
console.log(`*****************************************`);
console.log(`CONNECTION TO PGSQL WAS SUCCESSFUL..`);
res.json({ success: true, message: responseSelect, data:responseSelect.rows[0].exists });
}
})
});
}
EDIT:
"there is no parallelity.."
Node is asynchronous, you can either work with promises or spawn more clients/pools and tune your max-connections (as explained in my answer, but keep performance of your host-machine in mind), but with multiple clients running around 20.000 queries, they won't resolve with a result instantly or parallel. What is the exact goal you try to achieve?
"Is this a normal behavior for postgres?"
This is due to node's event-loop as well as due to certain performance-limitation of the host-machine running the Postgres.