Mysql 查询组按日 / 月 / 年

GROUP BY YEAR(record_date), MONTH(record_date)

Check out the date and time functions in MySQL.

I tried using the 'WHERE' statement above, I thought its correct since nobody corrected it but I was wrong; after some searches I found out that this is the right formula for the WHERE statement so the code becomes like this:

SELECT COUNT(id)  
FROM stats  
WHERE YEAR(record_date) = 2009  
GROUP BY MONTH(record_date)

GROUP BY DATE_FORMAT(record_date, '%Y%m')

Note (primarily, to potential downvoters). Presently, this may not be as efficient as other suggestions. Still, I leave it as an alternative, and a one, too, that can serve in seeing how faster other solutions are. (For you can't really tell fast from slow until you see the difference.) Also, as time goes on, changes could be made to MySQL's engine with regard to optimisation so as to make this solution, at some (perhaps, not so distant) point in future, to become quite comparable in efficiency with most others.

If you want to group by date in MySQL then use the code below:

 SELECT COUNT(id)
 FROM stats
 GROUP BY DAYOFMONTH(record_date)

Hope this saves some time for the ones who are going to find this thread.

try this one

SELECT COUNT(id)
FROM stats
GROUP BY EXTRACT(YEAR_MONTH FROM record_date)

EXTRACT(unit FROM date) function is better as less grouping is used and the function return a number value.

Comparison condition when grouping will be faster than DATE_FORMAT function (which return a string value). Try using function|field that return non-string value for SQL comparison condition (WHERE, HAVING, ORDER BY, GROUP BY).

If your search is over several years, and you still want to group monthly, I suggest:

version #1:

SELECT SQL_NO_CACHE YEAR(record_date), MONTH(record_date), COUNT(*)
FROM stats
GROUP BY DATE_FORMAT(record_date, '%Y%m')

version #2 (more efficient):

SELECT SQL_NO_CACHE YEAR(record_date), MONTH(record_date), COUNT(*)
FROM stats
GROUP BY YEAR(record_date)*100 + MONTH(record_date)

I compared these versions on a big table with 1,357,918 rows (innodb), and the 2nd version appears to have better results.

version1 (average of 10 executes): 1.404 seconds
version2 (average of 10 executes): 0.780 seconds

(SQL_NO_CACHE key added to prevent MySQL from CACHING to queries.)

If you want to get a monthly statistics with row counts per month of each year ordered by latest month, then try this:

SELECT count(id),
      YEAR(record_date),
      MONTH(record_date) 
FROM `table` 
GROUP BY YEAR(record_date),
        MONTH(record_date) 
ORDER BY YEAR(record_date) DESC,
        MONTH(record_date) DESC

If you want to filter records for a particular year (e.g. 2000) then optimize the WHERE clause like this:

SELECT MONTH(date_column), COUNT(*)
FROM date_table
WHERE date_column >= '2000-01-01' AND date_column < '2001-01-01'
GROUP BY MONTH(date_column)
-- average 0.016 sec.

Instead of:

WHERE YEAR(date_column) = 2000
-- average 0.132 sec.

The results were generated against a table containing 300k rows and index on date column.

As for the GROUP BY clause, I tested the three variants against the above mentioned table; here are the results:

SELECT YEAR(date_column), MONTH(date_column), COUNT(*)
FROM date_table
GROUP BY YEAR(date_column), MONTH(date_column)
-- codelogic
-- average 0.250 sec.

SELECT YEAR(date_column), MONTH(date_column), COUNT(*)
FROM date_table
GROUP BY DATE_FORMAT(date_column, '%Y%m')
-- Andriy M
-- average 0.468 sec.

SELECT YEAR(date_column), MONTH(date_column), COUNT(*)
FROM date_table
GROUP BY EXTRACT(YEAR_MONTH FROM date_column)
-- fu-chi
-- average 0.203 sec.

The last one is the winner.

I prefer to optimize the one year group selection like so:

SELECT COUNT(*)
  FROM stats
 WHERE record_date >= :year 
   AND record_date <  :year + INTERVAL 1 YEAR;

This way you can just bind the year in once, e.g. '2009', with a named parameter and don't need to worry about adding '-01-01' or passing in '2010' separately.

Also, as presumably we are just counting rows and id is never NULL, I prefer COUNT(*) to COUNT(id).

The following query worked for me in Oracle Database 12c Release 12.1.0.1.0

SELECT COUNT(*)
FROM stats
GROUP BY 
extract(MONTH FROM TIMESTAMP),
extract(MONTH FROM TIMESTAMP),
extract(YEAR  FROM TIMESTAMP);

.... group by to_char(date, 'YYYY') --> 1989

.... group by to_char(date,'MM') -->05

.... group by to_char(date,'DD') --->23

.... group by to_char(date,'MON') --->MAY

.... group by to_char(date,'YY') --->89

You can do this simply Mysql DATE_FORMAT() function in GROUP BY. You may want to add an extra column for added clarity in some cases such as where records span several years then same month occurs in different years.Here so many option you can customize this. Please read this befor starting. Hope it should be very helpful for you. Here is sample query for your understanding

SELECT
    COUNT(id),
    DATE_FORMAT(record_date, '%Y-%m-%d') AS DAY,
    DATE_FORMAT(record_date, '%Y-%m') AS MONTH,
    DATE_FORMAT(record_date, '%Y') AS YEAR,

FROM
    stats
WHERE
    YEAR = 2009
GROUP BY
    DATE_FORMAT(record_date, '%Y-%m-%d ');

Complete and simple solution with similarly performing yet shorter and more flexible alternative currently active:

SELECT COUNT(*) FROM stats
-- GROUP BY YEAR(record_date), MONTH(record_date), DAYOFMONTH(record_date)
GROUP BY DATE_FORMAT(record_date, '%Y-%m-%d')