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.
As an example, we can find the highest low-temperature reading anywhere
with
SELECT max(temp_lo) FROM weather;
max
-----
46
(1 row)
If we wanted to know what city (or cities) that reading occurred in,
we might try
SELECT city FROM weather WHERE temp_lo = max(temp_lo); 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 city FROM weather
WHERE temp_lo = (SELECT max(temp_lo) FROM weather);
city
---------------
San Francisco
(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 maximum low
temperature observed in each city with
SELECT city, max(temp_lo)
FROM weather
GROUP BY city;
city | max
---------------+-----
Hayward | 37
San Francisco | 46
(2 rows)
which gives us one output row per city. Each aggregate result is
computed over the table rows matching that city.
We can filter these grouped
rows using HAVING:
SELECT city, max(temp_lo)
FROM weather
GROUP BY city
HAVING max(temp_lo) < 40;
city | max
---------+-----
Hayward | 37
(1 row)
which gives us the same results for only the cities that have all
temp_lo values below 40. Finally, if we only care about
cities whose
names begin with "S", we might do
SELECT city, max(temp_lo)
FROM weather
WHERE city LIKE 'S%'(1)
GROUP BY city
HAVING max(temp_lo) < 40;
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 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.)
Observe 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.
