Node.js - PostgreSQL Group rows by days

In this article, we would like to show you how in the group rows by days in Postgres database from Node.js level.

Note: at the end of this article you can find database preparation SQL queries.

const pg = require('pg');

const types = pg.types;
types.setTypeParser(1114, (stringValue) => {
    return stringValue;
});

const client = new pg.Client({
    host: '127.0.0.1',
    user: 'my_username',
    database: 'my_database',
    password: 'my_password',
    port: 5432,
});

const fetchEventsGroupedByMonths = async () => {
	const query = `
            SELECT
                DATE_TRUNC('day', "event_timestamp") AS "day",
                COUNT(*)
            FROM "events"
            GROUP BY DATE_TRUNC('day', "event_timestamp")
            ORDER BY DATE_TRUNC('day', "event_timestamp")
    `;
    await client.connect();  // creates connection
    try {
        const { rows } = await client.query(query);  // sends query
        return rows;
    } finally {
        await client.end();  // closes connection
    }
};

fetchEventsGroupedByMonths()
    .then(result => console.table(result))
    .catch(error => console.error(error.stack));

Result: 

┌─────────┬───────────────────────┬───────┐
│ (index) │          day          │ count │
├─────────┼───────────────────────┼───────┤
│    0    │ '2021-03-11 00:00:00' │  '1'  │
│    1    │ '2021-03-21 00:00:00' │  '1'  │
│    2    │ '2021-03-22 00:00:00' │  '2'  │
│    3    │ '2021-03-23 00:00:00' │  '1'  │
│    4    │ '2021-04-05 00:00:00' │  '2'  │
│    5    │ '2021-04-16 00:00:00' │  '1'  │
│    6    │ '2021-04-17 00:00:00' │  '1'  │
│    7    │ '2021-04-23 00:00:00' │  '3'  │
└─────────┴───────────────────────┴───────┘

Database preparation

create_tables.sql file:

CREATE TABLE "events" (
	"id" SERIAL NOT NULL,
	"event_timestamp" TIMESTAMP NOT NULL,
	PRIMARY KEY ("id")
);

insert_data.sql file:

INSERT INTO "events" 
    ("event_timestamp")
VALUES
    ('2021-03-11 11:41:31'),
    ('2021-03-21 12:42:32'),
    ('2021-03-22 14:44:34'),
    ('2021-03-22 15:45:35'),
    ('2021-03-23 16:46:36'),
    ('2021-04-05 17:47:37'),
    ('2021-04-05 19:49:39'),
    ('2021-04-16 20:50:40'),
    ('2021-04-17 15:45:35'),
    ('2021-04-23 16:46:36'),
    ('2021-04-23 19:49:39'),
    ('2021-04-23 20:50:40');

Native SQL query (used in the above example):

SELECT
    DATE_TRUNC('day', "event_timestamp") AS "day",
    COUNT(*)
FROM "events"
GROUP BY DATE_TRUNC('day', "event_timestamp")
ORDER BY DATE_TRUNC('day', "event_timestamp")