There is an approach that can do this in pure SQL but it has limitations.
First you need to have a number sequence 1,2,3...n as rows (assume select row from rows
return that).
Then you can left join on this and convert to dates based on number of days between min and max.
select @min_join_on := (select min(join_on) from user);
select @no_rows := (select datediff(max(join_on), @min_join_on) from user)+1;
will give you the required number of rows, which then you can use to
select adddate(@min_join_on, interval row day) from rows where row <= @no_rows;
will return a required sequence of dates on which then you can do a left join back to the users table.
Using variables can be avoided if you use sub queries, I broke it down for readability.
Now, the problem is that the number of rows in table rows
has to be bigger then @no_rows.
For 10,000 rows you can work with date ranges of up to 27 years, with 100,000 rows you can work with date ranges of up to 273 years (this feels really bad, but I am afraid that if you don't want to use stored procedures it will have to look and feel awkward).
So, if you can work with such fixed date ranges you can even substitute the table with the query, such as this
SELECT @row := @row + 1 as row FROM (select 0 union all select 1 union all select 3 union all select 4 union all select 5 union all select 6 union all select 6 union all select 7 union all select 8 union all select 9) t, (select 0 union all select 1 union all select 3 union all select 4 union all select 5 union all select 6 union all select 6 union all select 7 union all select 8 union all select 9) t2, (select 0 union all select 1 union all select 3 union all select 4 union all select 5 union all select 6 union all select 6 union all select 7 union all select 8 union all select 9) t3, (select 0 union all select 1 union all select 3 union all select 4 union all select 5 union all select 6 union all select 6 union all select 7 union all select 8 union all select 9) t4, (SELECT @row:=0) r
which will produce 10,000 rows going from 1 to 10,000 and it will not be terribly inefficient at it.
So at the end it is doable in a single query.
create table user(id INT NOT NULL AUTO_INCREMENT, name varchar(100), join_on date, PRIMARY KEY(id));
mysql> select * from user;
+----+-------+------------+
| id | name | join_on |
+----+-------+------------+
| 1 | user1 | 2010-04-02 |
| 2 | user2 | 2010-04-04 |
| 3 | user3 | 2010-04-08 |
| 4 | user4 | 2010-04-08 |
+----+-------+------------+
4 rows in set (0.00 sec)
insert into user values (null, 'user1', '2010-04-02'), (null, 'user2', '2010-04-04'), (null, 'user3', '2010-04-08'), (null, 'user4', '2010-04-08')
SELECT date, count(id)
FROM (
SELECT adddate((select min(join_on) from user), row-1) as date
FROM (
SELECT @row := @row + 1 as row FROM (select 0 union all select 1 union all select 3 union all select 4 union all select 5 union all select 6 union all select 6 union all select 7 union all select 8 union all select 9) t, (select 0 union all select 1 union all select 3 union all select 4 union all select 5 union all select 6 union all select 6 union all select 7 union all select 8 union all select 9) t2, (SELECT @row:=0) r ) n
WHERE n.row <= ( select datediff(max(join_on), min(join_on)) from user) + 1
) dr LEFT JOIN user u ON dr.date = u.join_on
GROUP BY dr.date
+------------+-----------+
| date | count(id) |
+------------+-----------+
| 2010-04-02 | 1 |
| 2010-04-03 | 0 |
| 2010-04-04 | 1 |
| 2010-04-05 | 0 |
| 2010-04-06 | 0 |
| 2010-04-07 | 0 |
| 2010-04-08 | 2 |
+------------+-----------+
7 rows in set (0.00 sec)
date
and[sql]
or[mysql]
). See, e.g., #1047365 – Chela