MySQL 8.0 now supports windowing functions, like almost all popular SQL implementations. With this standard syntax, we can write greatest-n-per-group queries:
WITH ranked_messages AS (
SELECT m.*, ROW_NUMBER() OVER (PARTITION BY name ORDER BY id DESC) AS rn
FROM messages AS m
)
SELECT * FROM ranked_messages WHERE rn = 1;
Below is the original answer I wrote for this question in 2009:
I write the solution this way:
SELECT m1.*
FROM messages m1 LEFT JOIN messages m2
ON (m1.name = m2.name AND m1.id < m2.id)
WHERE m2.id IS NULL;
Regarding performance, one solution or the other can be better, depending on the nature of your data. So you should test both queries and use the one that is better at performance given your database.
For example, I have a copy of the StackOverflow August data dump. I’ll use that for benchmarking. There are 1,114,357 rows in the Posts
table. This is running on MySQL 5.0.75 on my Macbook Pro 2.40GHz.
I’ll write a query to find the most recent post for a given user ID (mine).
First using the technique shown with the GROUP BY
in a subquery:
SELECT p1.postid
FROM Posts p1
INNER JOIN (SELECT pi.owneruserid, MAX(pi.postid) AS maxpostid
FROM Posts pi GROUP BY pi.owneruserid) p2
ON (p1.postid = p2.maxpostid)
WHERE p1.owneruserid = 20860;
1 row in set (1 min 17.89 sec)
Even the EXPLAIN
analysis takes over 16 seconds:
+----+-------------+------------+--------+----------------------------+-------------+---------+--------------+---------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+--------+----------------------------+-------------+---------+--------------+---------+-------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 76756 | |
| 1 | PRIMARY | p1 | eq_ref | PRIMARY,PostId,OwnerUserId | PRIMARY | 8 | p2.maxpostid | 1 | Using where |
| 2 | DERIVED | pi | index | NULL | OwnerUserId | 8 | NULL | 1151268 | Using index |
+----+-------------+------------+--------+----------------------------+-------------+---------+--------------+---------+-------------+
3 rows in set (16.09 sec)
Now produce the same query result using my technique with LEFT JOIN
:
SELECT p1.postid
FROM Posts p1 LEFT JOIN posts p2
ON (p1.owneruserid = p2.owneruserid AND p1.postid < p2.postid)
WHERE p2.postid IS NULL AND p1.owneruserid = 20860;
1 row in set (0.28 sec)
The EXPLAIN
analysis shows that both tables are able to use their indexes:
+----+-------------+-------+------+----------------------------+-------------+---------+-------+------+--------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+----------------------------+-------------+---------+-------+------+--------------------------------------+
| 1 | SIMPLE | p1 | ref | OwnerUserId | OwnerUserId | 8 | const | 1384 | Using index |
| 1 | SIMPLE | p2 | ref | PRIMARY,PostId,OwnerUserId | OwnerUserId | 8 | const | 1384 | Using where; Using index; Not exists |
+----+-------------+-------+------+----------------------------+-------------+---------+-------+------+--------------------------------------+
2 rows in set (0.00 sec)
Here’s the DDL for my Posts
table:
CREATE TABLE `posts` (
`PostId` bigint(20) unsigned NOT NULL auto_increment,
`PostTypeId` bigint(20) unsigned NOT NULL,
`AcceptedAnswerId` bigint(20) unsigned default NULL,
`ParentId` bigint(20) unsigned default NULL,
`CreationDate` datetime NOT NULL,
`Score` int(11) NOT NULL default '0',
`ViewCount` int(11) NOT NULL default '0',
`Body` text NOT NULL,
`OwnerUserId` bigint(20) unsigned NOT NULL,
`OwnerDisplayName` varchar(40) default NULL,
`LastEditorUserId` bigint(20) unsigned default NULL,
`LastEditDate` datetime default NULL,
`LastActivityDate` datetime default NULL,
`Title` varchar(250) NOT NULL default '',
`Tags` varchar(150) NOT NULL default '',
`AnswerCount` int(11) NOT NULL default '0',
`CommentCount` int(11) NOT NULL default '0',
`FavoriteCount` int(11) NOT NULL default '0',
`ClosedDate` datetime default NULL,
PRIMARY KEY (`PostId`),
UNIQUE KEY `PostId` (`PostId`),
KEY `PostTypeId` (`PostTypeId`),
KEY `AcceptedAnswerId` (`AcceptedAnswerId`),
KEY `OwnerUserId` (`OwnerUserId`),
KEY `LastEditorUserId` (`LastEditorUserId`),
KEY `ParentId` (`ParentId`),
CONSTRAINT `posts_ibfk_1` FOREIGN KEY (`PostTypeId`) REFERENCES `posttypes` (`PostTypeId`)
) ENGINE=InnoDB;
Note to commenters: If you want another benchmark with a different version of MySQL, a different dataset, or different table design, feel free to do it yourself. I have shown the technique above. Stack Overflow is here to show you how to do software development work, not to do all the work for you.
The above solution works fine when item count within groups is rather small, but the performance of the query becomes bad when the groups are rather large, since the solution requires about n*n/2 + n/2
of only IS NULL
comparisons.
How to retrieve the last record in each group in MySQL?
I made my tests on a InnoDB table of 18684446
rows with 1182
groups. The table contains testresults for functional tests and has the (test_id, request_id)
as the primary key. Thus, test_id
is a group and I was searching for the last request_id
for each test_id
.
The first solution has already been running for several hours on my dell e4310 and I do not know when it is going to finish even though it operates on a coverage index (hence using index
in EXPLAIN).
I have a couple of other solutions that are based on the same ideas:
- if the underlying index is BTREE index (which is usually the case), the largest
(group_id, item_value)
pair is the last value within eachgroup_id
, that is the first for eachgroup_id
if we walk through the index in descending order; - if we read the values which are covered by an index, the values are read in the order of the index;
- each index implicitly contains primary key columns appended to that (that is the primary key is in the coverage index). In solutions below I operate directly on the primary key, in you case, you will just need to add primary key columns in the result.
- in many cases it is much cheaper to collect the required row ids in the required order in a subquery and join the result of the subquery on the id. Since for each row in the subquery result MySQL will need a single fetch based on primary key, the subquery will be put first in the join and the rows will be output in the order of the ids in the subquery (if we omit explicit ORDER BY for the join)
Solution 1
This one is incredibly fast, it takes about 0,8 secs on my 18M+ rows:
SELECT test_id, MAX(request_id) AS request_id
FROM testresults
GROUP BY test_id DESC;
If you want to change the order to ASC, put it in a subquery, return the ids only and use that as the subquery to join to the rest of the columns:
SELECT test_id, request_id
FROM (
SELECT test_id, MAX(request_id) AS request_id
FROM testresults
GROUP BY test_id DESC) as ids
ORDER BY test_id;
This one takes about 1,2 secs on my data.
Solution 2
Here is another solution that takes about 19 seconds for my table:
SELECT test_id, request_id
FROM testresults, (SELECT @group:=NULL) as init
WHERE IF(IFNULL(@group, -1)=@group:=test_id, 0, 1)
ORDER BY test_id DESC, request_id DESC
It returns tests in descending order as well. It is much slower since it does a full index scan but it is here to give you an idea how to output N max rows for each group.
The disadvantage of the query is that its result cannot be cached by the query cache.
Answer #3:
Use your subquery to return the correct grouping, because you’re halfway there.
Try this:
select
a.*
from
messages a
inner join
(select name, max(id) as maxid from messages group by name) as b on
a.id = b.maxid
If it’s not id
you want the max of:
select
a.*
from
messages a
inner join
(select name, max(other_col) as other_col
from messages group by name) as b on
a.name = b.name
and a.other_col = b.other_col
This way, you avoid correlated subqueries and/or ordering in your subqueries, which tend to be very slow/inefficient.
Answer #4:
I arrived at a different solution, which is to get the IDs for the last post within each group, then select from the messages table using the result from the first query as the argument for a WHERE x IN
construct:
SELECT id, name, other_columns
FROM messages
WHERE id IN (
SELECT MAX(id)
FROM messages
GROUP BY name
);
I don’t know how this performs compared to some of the other solutions, but it worked spectacularly for my table with 3+ million rows. (4 second execution with 1200+ results)
This should work both on MySQL and SQL Server.
Answer #5:
Solution by sub query:
select * from messages where id in
(select max(id) from messages group by Name)
Solution By join condition:
select m1.* from messages m1
left outer join messages m2
on ( m1.id<m2.id and m1.name=m2.name )
where m2.id is null
Answer #6:
An approach with considerable speed is as follows.
SELECT *
FROM messages a
WHERE Id = (SELECT MAX(Id) FROM messages WHERE a.Name = Name)
Result
Id Name Other_Columns
3 A A_data_3
5 B B_data_2
6 C C_data_1
Answer #7:
Here are two suggestions. First, if mysql supports ROW_NUMBER(), it’s very simple:
WITH Ranked AS (
SELECT Id, Name, OtherColumns,
ROW_NUMBER() OVER (
PARTITION BY Name
ORDER BY Id DESC
) AS rk
FROM messages
)
SELECT Id, Name, OtherColumns
FROM messages
WHERE rk = 1;
I’m assuming by “last” you mean last in Id order. If not, change the ORDER BY clause of the ROW_NUMBER() window accordingly. If ROW_NUMBER() isn’t available, this is another solution:
Second, if it doesn’t, this is often a good way to proceed:
SELECT
Id, Name, OtherColumns
FROM messages
WHERE NOT EXISTS (
SELECT * FROM messages as M2
WHERE M2.Name = messages.Name
AND M2.Id > messages.Id
)
In other words, select messages where there is no later-Id message with the same Name.
Sample query explained:
There is a table messages
that contains data as shown below:
Id Name Other_Columns
-------------------------
1 A A_data_1
2 A A_data_2
3 A A_data_3
4 B B_data_1
5 B B_data_2
6 C C_data_1
If I run a query select * from messages group by name
, I will get the result as:
1 A A_data_1
4 B B_data_1
6 C C_data_1
What query will return the following result?
3 A A_data_3
5 B B_data_2
6 C C_data_1
That is, the last record in each group should be returned.
At present, this is the query that I use:
SELECT
*
FROM (SELECT
*
FROM messages
ORDER BY id DESC) AS x
GROUP BY name
But this looks highly inefficient. Any other ways to achieve the same result?
Hope you learned something from this post.
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