for a project i'm working on, i have a single table with two dates meaning a range of dates and i needed a way to "multiply" my rows for every day in between the two dates.
So for instance i have start 2017-07-10, end 2017-07-14 I needed to have 4 lines with 2017-07-10, 2017-07-11, 2017-07-12, 2017-07-13
In order to do this i found here someone mentioning using a "calendar table" with all the dates for years.
So i built it, now i have these two simple tables:
CREATE TABLE `time_sample` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`start` varchar(16) DEFAULT NULL,
`end` varchar(16) DEFAULT NULL,
PRIMARY KEY (`societa_id`),
KEY `start_idx` (`start`),
KEY `end_idx` (`end`)
) ENGINE=MyISAM AUTO_INCREMENT=222 DEFAULT CHARSET=latin1;
This table contains my date ranges, start and end are indexed, the primary key is an incremental int. Sample Row:
id start end
1 2015-05-13 2015-05-18
Second table:
CREATE TABLE `time_dimension` (
`id` int(11) NOT NULL,
`db_date` date NOT NULL,
PRIMARY KEY (`id`),
UNIQUE KEY `td_dbdate_idx` (`db_date`)
) ENGINE=MyISAM DEFAULT CHARSET=latin1;
This has a date indexed for every day for many years to come. Sample row:
id db_date
20120101 2012-01-01
Now, i made the join:
select * from time_sample s join time_dimension t on (t.db_date >= start and t.db_date < end);
This takes 3ms. Even if my first table is HUGE, this query will always be very quick (max i've seen was 50ms with a lot of records).
The issue i have is while grouping results (i need them grouped for my application):
select * from time_sample s join time_dimension t on (t.db_date >= start and t.db_date < end) group by db_date;
This takes more than one second with not so many rows in the first table, increasing dramatically. Why is this happening and how can i avoid this?
Changing the data types doesn't help, having the second table with just one column doesn't help.
Can i have suggestions, please :(
I cannot replicate this result...
I have a calendar table with lots of dates: calendar(dt) where dt is a PRIMARY KEY DATE data type.
Even with a GROUP BY, I'm struggling to reproduce the problem. Here's a simple COUNT...