Working with Distinct in MySQL

Intro

When viewing data, we often run into duplicate entries. For example, we may want to query addresses, and we should expect to see multiple addresses with the same country. If we would like to see a unique list of countries, states, etc we can use the DISTINCT clause. In this article, we will learn how to use DISTINCT in MySql.

The Syntax

The basic syntax of DISTINCT is as follows:

SELECT DISTINCT
	[column_names]
FROM
	[table_name]

Here we can type a single or multiple columns.

Getting Setup

We will be using docker in this article, but feel free to install your database locally instead. Once you have docker installed, create a new file called docker-compose.yml and add the following.

version: '3'
 
services:
  db:
    image: mysql:latest
    container_name: db
    environment:
      MYSQL_ROOT_PASSWORD: root_pass
      MYSQL_DATABASE: app_db
      MYSQL_USER: db_user
      MYSQL_PASSWORD: db_user_pass
    ports:
      - "6033:3306"
    volumes:
      - dbdata:/var/lib/mysql
  phpmyadmin:
    image: phpmyadmin/phpmyadmin
    container_name: pma
    links:
      - db
    environment:
      PMA_HOST: db
      PMA_PORT: 3306
      PMA_ARBITRARY: 1
    restart: always
    ports:
      - 8081:80

volumes:
  dbdata:

Next, run docker-compose up.

Now, navigate to http://localhost:8081/ to access phpMyAdmin. Then log in with the username root and pass root_pass.

Click the SQL tab and you are ready to go.

Creating a DB

In this article, we will need some data to work with. If you don't understand these commands, don't worry, we will cover them in later articles.

We will be using the sample db provided here: https://dev.mysql.com/doc/sakila/en/. However, we will only enter what we need rather than import the whole db.

With the SQL tab open (or your own sql cli going), let's first create our DB and select it.

create DATABASE if not EXISTS sakila;

USE sakila;

Next, let's create an actor table.

CREATE TABLE actor (
  actor_id SMALLINT UNSIGNED NOT NULL AUTO_INCREMENT,
  first_name VARCHAR(45) NOT NULL,
  last_name VARCHAR(45) NOT NULL,
  last_update TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
  PRIMARY KEY  (actor_id),
  KEY idx_actor_last_name (last_name)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

And finally, let's enter a few rows.

INSERT INTO actor VALUES 
(1,'PENELOPE','GUINESS','2006-02-15 04:34:33'),
(2,'NICK','WAHLBERG','2006-02-15 04:34:33'),
(3,'ED','CHASE','2006-02-15 04:34:33'),
(4,'JENNIFER','DAVIS','2006-02-15 04:34:33'),
(5,'JOHNNY','LOLLOBRIGIDA','2006-02-15 04:34:33'),
(6,'BETTE','NICHOLSON','2006-02-15 04:34:33'),
(7,'GRACE','MOSTEL','2006-02-15 04:34:33'),
(8,'MATTHEW','JOHANSSON','2006-02-15 04:34:33'),
(9,'GRACE','JOHANSSON','2006-02-15 04:34:33')

One Distinct Column

Let’s start by selecting one column. Here we can see many duplicates.

SELECT last_name FROM actor;

Now, let’s do the same but use the DISTINCT clause.

SELECT DISTINCT last_name FROM actor;

Now we have a unique list.

Distinct Multiple Columns

Before we found the unique of one column, however, we can always use multiple combinations to select unique combinations.

For example, let’s say we want to select the unique city and state combinations. We will see repeat states, but not city and state combinations.

Without distinct here is what we get.

SELECT 
    state, city
FROM
    customers
ORDER BY 
    state, 
    city;

+---------------+----------------+ | state | city | +---------------+----------------+ | BC | Tsawassen | | BC | Vancouver | | CA | Brisbane | | CA | Burbank | .. | CA | San Francisco | | CA | San Francisco | ... | MA | Boston | | MA | Boston | | MA | Brickhaven | | MA | Brickhaven | | MA | Brickhaven | ... | NY | NYC | | NY | NYC | | NY | NYC | | NY | NYC | | NY | NYC | ...

Now, with DISTINCT.

SELECT DISTINCT
    state, city
FROM
    customers
ORDER BY 
    state, 
    city;

+---------------+----------------+ | state | city | +---------------+----------------+ | BC | Tsawassen | | BC | Vancouver | | CA | Brisbane | | CA | Burbank | | CA | Burlingame | | CA | Glendale | | CA | Los Angeles | | CA | Pasadena | | CA | San Diego | ...