# sql – What’s faster, SELECT DISTINCT or GROUP BY in MySQL?

## The Question :

285 people think this question is useful

If I have a table

CREATE TABLE users (
id int(10) unsigned NOT NULL auto_increment,
name varchar(255) NOT NULL,
profession varchar(255) NOT NULL,
employer varchar(255) NOT NULL,
PRIMARY KEY  (id)
)



and I want to get all unique values of profession field, what would be faster (or recommended):

SELECT DISTINCT u.profession FROM users u



or

SELECT u.profession FROM users u GROUP BY u.profession



?

• You could test for yourself as quickly as ask the question. Irritatingly, it is almost impossible to construct a scenario in which DISTINCT outperforms GROUP BY – which is annoying because clearly this is not the purpose of GROUP BY. However, GROUP BY can produce misleading results, which I think is reason enough for avoiding it.
• There’s another duplicate with a different answer. see MySql – Distinct vs Group By <<< it says GROUP BY is better
• Please see here if you want to measure the time difference between DISTINCT and GROUP BY running your query.

266 people think this answer is useful

They are essentially equivalent to each other (in fact this is how some databases implement DISTINCT under the hood).

If one of them is faster, it’s going to be DISTINCT. This is because, although the two are the same, a query optimizer would have to catch the fact that your GROUP BY is not taking advantage of any group members, just their keys. DISTINCT makes this explicit, so you can get away with a slightly dumber optimizer.

When in doubt, test!

100 people think this answer is useful

If you have an index on profession, these two are synonyms.

If you don’t, then use DISTINCT.

GROUP BY in MySQL sorts results. You can even do:

SELECT u.profession FROM users u GROUP BY u.profession DESC



and get your professions sorted in DESC order.

DISTINCT creates a temporary table and uses it for storing duplicates. GROUP BY does the same, but sortes the distinct results afterwards.

So

SELECT DISTINCT u.profession FROM users u



is faster, if you don’t have an index on profession.

19 people think this answer is useful

All of the answers above are correct, for the case of DISTINCT on a single column vs GROUP BY on a single column. Every db engine has its own implementation and optimizations, and if you care about the very little difference (in most cases) then you have to test against specific server AND specific version! As implementations may change…

BUT, if you select more than one column in the query, then the DISTINCT is essentially different! Because in this case it will compare ALL columns of all rows, instead of just one column.

So if you have something like:

// This will NOT return unique by [id], but unique by (id,name)
SELECT DISTINCT id, name FROM some_query_with_joins

// This will select unique by [id].
SELECT id, name FROM some_query_with_joins GROUP BY id



It is a common mistake to think that DISTINCT keyword distinguishes rows by the first column you specified, but the DISTINCT is a general keyword in this manner.

So people you have to be careful not to take the answers above as correct for all cases… You might get confused and get the wrong results while all you wanted was to optimize!

17 people think this answer is useful

Go for the simplest and shortest if you can — DISTINCT seems to be more what you are looking for only because it will give you EXACTLY the answer you need and only that!

7 people think this answer is useful

Group by is expensive than Distinct since Group by does a sort on the result while distinct avoids it. But if you want to make group by yield the same result as distinct give order by null ..

SELECT DISTINCT u.profession FROM users u



is equal to

SELECT u.profession FROM users u GROUP BY u.profession order by null



7 people think this answer is useful

well distinct can be slower than group by on some occasions in postgres (dont know about other dbs).

tested example:

postgres=# select count(*) from (select distinct i from g) a;

count

10001
(1 row)

Time: 1563,109 ms

postgres=# select count(*) from (select i from g group by i) a;

count
10001
(1 row)

Time: 594,481 ms



http://www.pgsql.cz/index.php/PostgreSQL_SQL_Tricks_I

so be careful … 🙂

5 people think this answer is useful

It seems that the queries are not exactly the same. At least for MySQL.

Compare:

1. describe select distinct productname from northwind.products
2. describe select productname from northwind.products group by productname

The second query gives additionally “Using filesort” in Extra.

3 people think this answer is useful

In MySQL, “Group By” uses an extra step: filesort. I realize DISTINCT is faster than GROUP BY, and that was a surprise.

3 people think this answer is useful

After heavy testing we came to the conclusion that GROUP BY is faster

SELECT sql_no_cache opnamegroep_intern FROM telwerken WHERE opnemergroep IN (7,8,9,10,11,12,13) group by opnamegroep_intern

635 totaal 0.0944 seconds Weergave van records 0 – 29 ( 635 totaal, query duurde 0.0484 sec)

SELECT sql_no_cache distinct (opnamegroep_intern) FROM telwerken WHERE opnemergroep IN (7,8,9,10,11,12,13)

635 totaal 0.2117 seconds ( almost 100% slower ) Weergave van records 0 – 29 ( 635 totaal, query duurde 0.3468 sec)

2 people think this answer is useful

(more of a functional note)

There are cases when you have to use GROUP BY, for example if you wanted to get the number of employees per employer:

SELECT u.employer, COUNT(u.id) AS "total employees" FROM users u GROUP BY u.employer



In such a scenario DISTINCT u.employer doesn’t work right. Perhaps there is a way, but I just do not know it. (If someone knows how to make such a query with DISTINCT please add a note!)

2 people think this answer is useful

Here is a simple approach which will print the 2 different elapsed time for each query.

DECLARE @t1 DATETIME;
DECLARE @t2 DATETIME;

SET @t1 = GETDATE();
SELECT DISTINCT u.profession FROM users u; --Query with DISTINCT
SET @t2 = GETDATE();
PRINT 'Elapsed time (ms): ' + CAST(DATEDIFF(millisecond, @t1, @t2) AS varchar);

SET @t1 = GETDATE();
SELECT u.profession FROM users u GROUP BY u.profession; --Query with GROUP BY
SET @t2 = GETDATE();
PRINT 'Elapsed time (ms): ' + CAST(DATEDIFF(millisecond, @t1, @t2) AS varchar);


SET STATISTICS TIME ON;
SELECT DISTINCT u.profession FROM users u; --Query with DISTINCT
SELECT u.profession FROM users u GROUP BY u.profession; --Query with GROUP BY
SET STATISTICS TIME OFF;



It simply displays the number of milliseconds required to parse, compile, and execute each statement as below:

 SQL Server Execution Times:
CPU time = 0 ms,  elapsed time = 2 ms.



1 people think this answer is useful

This is not a rule

For each query …. try separately distinct and then group by … compare the time to complete each query and use the faster ….

In my project sometime I use group by and others distinct

0 people think this answer is useful

If you don’t have to do any group functions (sum, average etc in case you want to add numeric data to the table), use SELECT DISTINCT. I suspect it’s faster, but i have nothing to show for it.

In any case, if you’re worried about speed, create an index on the column.

0 people think this answer is useful

SELECT DISTINCT will always be the same, or faster, than a GROUP BY. On some systems (i.e. Oracle), it might be optimized to be the same as DISTINCT for most queries. On others (such as SQL Server), it can be considerably faster.

0 people think this answer is useful

If the problem allows it, try with EXISTS, since it’s optimized to end as soon as a result is found (And don’t buffer any response), so, if you are just trying to normalize data for a WHERE clause like this

SELECT FROM SOMETHING S WHERE S.ID IN ( SELECT DISTINCT DCR.SOMETHING_ID FROM DIFF_CARDINALITY_RELATIONSHIP DCR ) -- to keep same cardinality



A faster response would be:

SELECT FROM SOMETHING S WHERE EXISTS ( SELECT 1 FROM DIFF_CARDINALITY_RELATIONSHIP DCR WHERE DCR.SOMETHING_ID = S.ID )



This isn’t always possible but when available you will see a faster response.