4.10. Using Aggregate Functions

Like most other relational database products, PostgreSQL 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.

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 may 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 clauses always contain 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.)

As an example, we can find the highest low-temperature reading anywhere with

SELECT max(temp_lo) FROM weather;
    

If we want to know what city (or cities) that reading occurred in, we might try

SELECT city FROM weather WHERE temp_lo = max(temp_lo);
    

but this will not work since the aggregate max can't be used in WHERE. However, as is often the case the query can be restated to accomplish the intended result; here by using a subselect:

SELECT city FROM weather
    WHERE temp_lo = (SELECT max(temp_lo) FROM weather);
    

This is OK because the sub-select is an independent computation that computes its own aggregate separately from what's happening in the outer select.

Aggregates are also very useful in combination with GROUP BY clauses. For example, we can get the maximum low temperature observed in each city with

SELECT city, max(temp_lo)
    FROM weather
    GROUP BY city;
    

which gives us one output row per city. We can filter these grouped rows using HAVING:

SELECT city, max(temp_lo)
    FROM weather
    GROUP BY city
    HAVING min(temp_lo) < 0;
    

which gives us the same results for only the cities that have some below-zero readings. Finally, if we only care about cities whose names begin with "P", we might do

SELECT city, max(temp_lo)
    FROM weather
    WHERE city like 'P%'
    GROUP BY city
    HAVING min(temp_lo) < 0;
    

Note that we can apply the city-name restriction in WHERE, 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.