This section describes group (aggregate) functions that operate on sets of values. Unless otherwise stated, group functions ignore NULL values.

If you use a group function in a statement containing no GROUP BY clause, it is equivalent to grouping on all rows.

For numeric arguments, the variance and standard deviation functions return a DOUBLE value. The SUM() and AVG() functions return a DECIMAL value for exact-value arguments (integer or DECIMAL), and a DOUBLE value for approximate-value arguments (FLOAT or DOUBLE). (Before MySQL 5.0.3, SUM() and AVG() return DOUBLE for all numeric arguments.)

The SUM() and AVG() aggregate functions do not work with temporal values. (They convert the values to numbers, losing everything after the first non-numeric character.) To work around this problem, you can convert to numeric units, perform the aggregate operation, and convert back to a temporal value. Examples:

SELECT SEC_TO_TIME(SUM(TIME_TO_SEC(time_col))) FROM tbl_name;
SELECT FROM_DAYS(SUM(TO_DAYS(date_col))) FROM tbl_name;

The GROUP BY clause allows a WITH ROLLUP modifier that causes extra rows to be added to the summary output. These rows represent higher-level (or super-aggregate) summary operations. ROLLUP thus allows you to answer questions at multiple levels of analysis with a single query. It can be used, for example, to provide support for OLAP (Online Analytical Processing) operations.

Suppose that a table named sales has year, country, product, and profit columns for recording sales profitability:

CREATE TABLE sales
(
    year    INT NOT NULL,
    country VARCHAR(20) NOT NULL,
    product VARCHAR(32) NOT NULL,
    profit  INT
);

The table's contents can be summarized per year with a simple GROUP BY like this:

mysql> SELECT year, SUM(profit) FROM sales GROUP BY year;
+------+-------------+
| year | SUM(profit) |
+------+-------------+
| 2000 |        4525 |
| 2001 |        3010 |
+------+-------------+

This output shows the total profit for each year, but if you also want to determine the total profit summed over all years, you must add up the individual values yourself or run an additional query.

Or you can use ROLLUP, which provides both levels of analysis with a single query. Adding a WITH ROLLUP modifier to the GROUP BY clause causes the query to produce another row that shows the grand total over all year values:

mysql> SELECT year, SUM(profit) FROM sales GROUP BY year WITH ROLLUP;
+------+-------------+
| year | SUM(profit) |
+------+-------------+
| 2000 |        4525 |
| 2001 |        3010 |
| NULL |        7535 |
+------+-------------+

The grand total super-aggregate line is identified by the value NULL in the year column.

ROLLUP has a more complex effect when there are multiple GROUP BY columns. In this case, each time there is a “break” (change in value) in any but the last grouping column, the query produces an extra super-aggregate summary row.

For example, without ROLLUP, a summary on the sales table based on year, country, and product might look like this:

mysql> SELECT year, country, product, SUM(profit)
    -> FROM sales
    -> GROUP BY year, country, product;
+------+---------+------------+-------------+
| year | country | product    | SUM(profit) |
+------+---------+------------+-------------+
| 2000 | Finland | Computer   |        1500 |
| 2000 | Finland | Phone      |         100 |
| 2000 | India   | Calculator |         150 |
| 2000 | India   | Computer   |        1200 |
| 2000 | USA     | Calculator |          75 |
| 2000 | USA     | Computer   |        1500 |
| 2001 | Finland | Phone      |          10 |
| 2001 | USA     | Calculator |          50 |
| 2001 | USA     | Computer   |        2700 |
| 2001 | USA     | TV         |         250 |
+------+---------+------------+-------------+

The output indicates summary values only at the year/country/product level of analysis. When ROLLUP is added, the query produces several extra rows:

mysql> SELECT year, country, product, SUM(profit)
    -> FROM sales
    -> GROUP BY year, country, product WITH ROLLUP;
+------+---------+------------+-------------+
| year | country | product    | SUM(profit) |
+------+---------+------------+-------------+
| 2000 | Finland | Computer   |        1500 |
| 2000 | Finland | Phone      |         100 |
| 2000 | Finland | NULL       |        1600 |
| 2000 | India   | Calculator |         150 |
| 2000 | India   | Computer   |        1200 |
| 2000 | India   | NULL       |        1350 |
| 2000 | USA     | Calculator |          75 |
| 2000 | USA     | Computer   |        1500 |
| 2000 | USA     | NULL       |        1575 |
| 2000 | NULL    | NULL       |        4525 |
| 2001 | Finland | Phone      |          10 |
| 2001 | Finland | NULL       |          10 |
| 2001 | USA     | Calculator |          50 |
| 2001 | USA     | Computer   |        2700 |
| 2001 | USA     | TV         |         250 |
| 2001 | USA     | NULL       |        3000 |
| 2001 | NULL    | NULL       |        3010 |
| NULL | NULL    | NULL       |        7535 |
+------+---------+------------+-------------+

For this query, adding ROLLUP causes the output to include summary information at four levels of analysis, not just one. Here's how to interpret the ROLLUP output:

Other Considerations When using ROLLUP

The following items list some behaviors specific to the MySQL implementation of ROLLUP:

When you use ROLLUP, you cannot also use an ORDER BY clause to sort the results. In other words, ROLLUP and ORDER BY are mutually exclusive. However, you still have some control over sort order. GROUP BY in MySQL sorts results, and you can use explicit ASC and DESC keywords with columns named in the GROUP BY list to specify sort order for individual columns. (The higher-level summary rows added by ROLLUP still appear after the rows from which they are calculated, regardless of the sort order.)

LIMIT can be used to restrict the number of rows returned to the client. LIMIT is applied after ROLLUP, so the limit applies against the extra rows added by ROLLUP. For example:

mysql> SELECT year, country, product, SUM(profit)
    -> FROM sales
    -> GROUP BY year, country, product WITH ROLLUP
    -> LIMIT 5;
+------+---------+------------+-------------+
| year | country | product    | SUM(profit) |
+------+---------+------------+-------------+
| 2000 | Finland | Computer   |        1500 |
| 2000 | Finland | Phone      |         100 |
| 2000 | Finland | NULL       |        1600 |
| 2000 | India   | Calculator |         150 |
| 2000 | India   | Computer   |        1200 |
+------+---------+------------+-------------+

Using LIMIT with ROLLUP may produce results that are more difficult to interpret, because you have less context for understanding the super-aggregate rows.

The NULL indicators in each super-aggregate row are produced when the row is sent to the client. The server looks at the columns named in the GROUP BY clause following the leftmost one that has changed value. For any column in the result set with a name that is a lexical match to any of those names, its value is set to NULL. (If you specify grouping columns by column number, the server identifies which columns to set to NULL by number.)

Because the NULL values in the super-aggregate rows are placed into the result set at such a late stage in query processing, you cannot test them as NULL values within the query itself. For example, you cannot add HAVING product IS NULL to the query to eliminate from the output all but the super-aggregate rows.

On the other hand, the NULL values do appear as NULL on the client side and can be tested as such using any MySQL client programming interface.

MySQL extends the use of GROUP BY so that you can use non-aggregated columns or calculations in the SELECT list that do not appear in the GROUP BY clause. You can use this feature to get better performance by avoiding unnecessary column sorting and grouping. For example, you do not need to group on customer.name in the following query:

SELECT order.custid, customer.name, MAX(payments)
  FROM order,customer
  WHERE order.custid = customer.custid
  GROUP BY order.custid;

In standard SQL, you would have to add customer.name to the GROUP BY clause. In MySQL, the name is redundant.

Do not use this feature if the columns you omit from the GROUP BY part are not constant in the group. The server is free to return any value from the group, so the results are indeterminate unless all values are the same.

A similar MySQL extension applies to the HAVING clause. The SQL standard does not allow the HAVING clause to name any column that is not found in the GROUP BY clause if it is not enclosed in an aggregate function. MySQL allows the use of such columns to simplify calculations. This extension assumes that the non-grouped columns will have the same group-wise values. Otherwise, the result is indeterminate.

If the ONLY_FULL_GROUP_BY SQL mode is enabled, the MySQL extension to GROUP BY does not apply. That is, columns not named in the GROUP BY clause cannot be used in the SELECT list or HAVING clause if not used in an aggregate function.

The select list extension also applies to ORDER BY. That is, you can use non-aggregated columns or calculations in the ORDER BY clause that do not appear in the GROUP BY clause. This extension does not apply if the ONLY_FULL_GROUP_BY SQL mode is enabled.

In some cases, you can use MIN() and MAX() to obtain a specific column value even if it isn't unique. The following gives the value of column from the row containing the smallest value in the sort column:

SUBSTR(MIN(CONCAT(RPAD(sort,6,' '),column)),7)

See Section 3.6.4, “The Rows Holding the Group-wise Maximum of a Certain Field”.

Note that if you are trying to follow standard SQL, you can't use expressions in GROUP BY clauses. You can work around this limitation by using an alias for the expression:

SELECT id,FLOOR(value/100) AS val
  FROM tbl_name
  GROUP BY id, val;

MySQL does allow expressions in GROUP BY clauses. For example:

SELECT id,FLOOR(value/100)
  FROM tbl_name
  GROUP BY id, FLOOR(value/100);