How do I find duplicates across multiple columns?

Solution 1:

Duplicated id for pairs name and city:

select s.id, t.* 
from [stuff] s
join (
    select name, city, count(*) as qty
    from [stuff]
    group by name, city
    having count(*) > 1
) t on s.name = t.name and s.city = t.city

Solution 2:

 SELECT name, city, count(*) as qty 
 FROM stuff 
 GROUP BY name, city HAVING count(*)> 1

Solution 3:

Something like this will do the trick. Don't know about performance, so do make some tests.

select
  id, name, city
from
  [stuff] s
where
1 < (select count(*) from [stuff] i where i.city = s.city and i.name = s.name)

Solution 4:

Using count(*) over(partition by...) provides a simple and efficient means to locate unwanted repetition, whilst also list all affected rows and all wanted columns:

SELECT
    t.*
FROM (
    SELECT
        s.*
      , COUNT(*) OVER (PARTITION BY s.name, s.city) AS qty
    FROM stuff s
    ) t
WHERE t.qty > 1
ORDER BY t.name, t.city

While most recent RDBMS versions support count(*) over(partition by...) MySQL V 8.0 introduced "window functions", as seen below (in MySQL 8.0)

CREATE TABLE stuff(
   id   INTEGER  NOT NULL
  ,name VARCHAR(60) NOT NULL
  ,city VARCHAR(60) NOT NULL
);
INSERT INTO stuff(id,name,city) VALUES 
  (904834,'jim','London')
, (904835,'jim','London')
, (90145,'Fred','Paris')
, (90132,'Fred','Paris')
, (90133,'Fred','Paris')

, (923457,'Barney','New York') # not expected in result
;
SELECT
    t.*
FROM (
    SELECT
        s.*
      , COUNT(*) OVER (PARTITION BY s.name, s.city) AS qty
    FROM stuff s
    ) t
WHERE t.qty > 1
ORDER BY t.name, t.city
    id | name | city   | qty
-----: | :--- | :----- | --:
 90145 | Fred | Paris  |   3
 90132 | Fred | Paris  |   3
 90133 | Fred | Paris  |   3
904834 | jim  | London |   2
904835 | jim  | London |   2

db<>fiddle here

Window functions. MySQL now supports window functions that, for each row from a query, perform a calculation using rows related to that row. These include functions such as RANK(), LAG(), and NTILE(). In addition, several existing aggregate functions now can be used as window functions; for example, SUM() and AVG(). For more information, see Section 12.21, “Window Functions”.

Solution 5:

A little late to the game on this post, but I found this way to be pretty flexible / efficient

select 
    s1.id
    ,s1.name
    ,s1.city 
from 
    stuff s1
    ,stuff s2
Where
    s1.id <> s2.id
    and s1.name = s2.name
    and s1.city = s2.city