1.7. Aggregate Functions

Like most other relational database products, EnterpriseDB supports aggregate functions. An aggregate function computes a single result from multiple input rows. For example, there are aggregates to compute the count, sum, avg (average), max (maximum) and min (minimum) over a set of rows.

As an example, we can find the highest and lowest salaries with

SELECT MAX(sal) AS Highest_Salary, MIN(sal) AS Lowest_Salary
FROM emp

 highest_salary | lowest_salary
----------------+---------------
        5000.00 |        800.00
(1 row)
 

If we wanted to know who the highest paid employee in the organization was, we might try

SELECT ename FROM emp WHERE sal = MAX(sal);     WRONG

but this will not work since the aggregate max cannot be used in the WHERE clause. (This restriction exists because the WHERE clause determines the rows that will go into the aggregation stage; so it has to be evaluated before aggregate functions are computed.) However, as is often the case the query can be restated to accomplish the intended result, here by using a subquery:

SELECT ename FROM emp
WHERE sal = (SELECT MAX(sal) FROM emp);

 ename
-------
 KING
(1 row)

This is OK because the subquery is an independent computation that computes its own aggregate separately from what is happening in the outer query.

Aggregates are also very useful in combination with GROUP BY clauses. For example, we can get the highest salary for each department with

SELECT deptno, MAX(sal)
FROM emp
GROUP BY deptno;

 deptno |   max
--------+---------
     30 | 2850.00
     20 | 3000.00
     10 | 5000.00
(3 rows)

which gives us one output row per department. Each aggregate result is computed over the table rows matching that department. We can filter these grouped rows using HAVING:

SELECT deptno, MAX(sal)
FROM emp
GROUP BY deptno
HAVING AVG(sal) > 2000;

 deptno |   max
--------+---------
     30 | 2850.00
     20 | 3000.00
     10 | 5000.00
(3 rows)

which gives us the same results for only those departments that have an average salary greater than 2000. Finally, if we only care about the highest paid employees for each department whose names begin with "K", we might do

SELECT deptno, MAX(sal)
FROM emp
WHERE ename LIKE 'K%'
GROUP BY deptno
HAVING AVG(sal) > 2000;

It is important to understand the interaction between aggregates and SQL's WHERE and HAVING clauses. The fundamental difference between WHERE and HAVING is this: WHERE selects input rows before groups and aggregates are computed (thus, it controls which rows go into the aggregate computation), whereas HAVING selects group rows after groups and aggregates are computed. Thus, the WHERE clause must not contain aggregate functions; it makes no sense to try to use an aggregate to determine which rows will be inputs to the aggregates. On the other hand, HAVING clause always contains aggregate functions. (Strictly speaking, you are allowed to write a HAVING clause that doesn't use aggregates, but it's wasteful: The same condition could be used more efficiently at the WHERE stage.)

Observe that we can apply the employee name restriction in WHERE clause since it needs no aggregate. This is more efficient than adding the restriction to HAVING, because we avoid doing the grouping and aggregate calculations for all rows that fail the WHERE check.