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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8" /><title>2.7. Aggregate Functions</title><link rel="stylesheet" type="text/css" href="stylesheet.css" /><link rev="made" href="pgsql-docs@lists.postgresql.org" /><meta name="generator" content="DocBook XSL Stylesheets Vsnapshot" /><link rel="prev" href="tutorial-join.html" title="2.6. Joins Between Tables" /><link rel="next" href="tutorial-update.html" title="2.8. Updates" /></head><body id="docContent" class="container-fluid col-10"><div class="navheader"><table width="100%" summary="Navigation header"><tr><th colspan="5" align="center">2.7. Aggregate Functions</th></tr><tr><td width="10%" align="left"><a accesskey="p" href="tutorial-join.html" title="2.6. Joins Between Tables">Prev</a> </td><td width="10%" align="left"><a accesskey="u" href="tutorial-sql.html" title="Chapter 2. The SQL Language">Up</a></td><th width="60%" align="center">Chapter 2. The <acronym class="acronym">SQL</acronym> Language</th><td width="10%" align="right"><a accesskey="h" href="index.html" title="PostgreSQL 16.3 Documentation">Home</a></td><td width="10%" align="right"> <a accesskey="n" href="tutorial-update.html" title="2.8. Updates">Next</a></td></tr></table><hr /></div><div class="sect1" id="TUTORIAL-AGG"><div class="titlepage"><div><div><h2 class="title" style="clear: both">2.7. Aggregate Functions <a href="#TUTORIAL-AGG" class="id_link">#</a></h2></div></div></div><a id="id-1.4.4.8.2" class="indexterm"></a><p>
Like most other relational database products,
<span class="productname">PostgreSQL</span> supports
<em class="firstterm">aggregate functions</em>.
An aggregate function computes a single result from multiple input rows.
For example, there are aggregates to compute the
<code class="function">count</code>, <code class="function">sum</code>,
<code class="function">avg</code> (average), <code class="function">max</code> (maximum) and
<code class="function">min</code> (minimum) over a set of rows.
</p><p>
As an example, we can find the highest low-temperature reading anywhere
with:
</p><pre class="programlisting">
SELECT max(temp_lo) FROM weather;
</pre><p>
</p><pre class="screen">
max
-----
46
(1 row)
</pre><p>
</p><p>
<a id="id-1.4.4.8.5.1" class="indexterm"></a>
If we wanted to know what city (or cities) that reading occurred in,
we might try:
</p><pre class="programlisting">
SELECT city FROM weather WHERE temp_lo = max(temp_lo); <em class="lineannotation"><span class="lineannotation">WRONG</span></em>
</pre><p>
but this will not work since the aggregate
<code class="function">max</code> cannot be used in the
<code class="literal">WHERE</code> clause. (This restriction exists because
the <code class="literal">WHERE</code> clause determines which rows will be
included in the aggregate calculation; so obviously it has to be evaluated
before aggregate functions are computed.)
However, as is often the case
the query can be restated to accomplish the desired result, here
by using a <em class="firstterm">subquery</em>:
</p><pre class="programlisting">
SELECT city FROM weather
WHERE temp_lo = (SELECT max(temp_lo) FROM weather);
</pre><p>
</p><pre class="screen">
city
---------------
San Francisco
(1 row)
</pre><p>
This is OK because the subquery is an independent computation
that computes its own aggregate separately from what is happening
in the outer query.
</p><p>
<a id="id-1.4.4.8.6.1" class="indexterm"></a>
<a id="id-1.4.4.8.6.2" class="indexterm"></a>
Aggregates are also very useful in combination with <code class="literal">GROUP
BY</code> clauses. For example, we can get the number of readings
and the maximum low temperature observed in each city with:
</p><pre class="programlisting">
SELECT city, count(*), max(temp_lo)
FROM weather
GROUP BY city;
</pre><p>
</p><pre class="screen">
city | count | max
---------------+-------+-----
Hayward | 1 | 37
San Francisco | 2 | 46
(2 rows)
</pre><p>
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 <code class="literal">HAVING</code>:
</p><pre class="programlisting">
SELECT city, count(*), max(temp_lo)
FROM weather
GROUP BY city
HAVING max(temp_lo) < 40;
</pre><p>
</p><pre class="screen">
city | count | max
---------+-------+-----
Hayward | 1 | 37
(1 row)
</pre><p>
which gives us the same results for only the cities that have all
<code class="structfield">temp_lo</code> values below 40. Finally, if we only care about
cities whose
names begin with <span class="quote">“<span class="quote"><code class="literal">S</code></span>”</span>, we might do:
</p><pre class="programlisting">
SELECT city, count(*), max(temp_lo)
FROM weather
WHERE city LIKE 'S%' -- <span id="co.tutorial-agg-like"></span>(1)
GROUP BY city;
</pre><p>
</p><pre class="screen">
city | count | max
---------------+-------+-----
San Francisco | 2 | 46
(1 row)
</pre><p>
</p><div class="calloutlist"><table border="0" summary="Callout list"><tr><td width="5%" valign="top" align="left"><p><a href="#co.tutorial-agg-like">(1)</a> </p></td><td valign="top" align="left"><p>
The <code class="literal">LIKE</code> operator does pattern matching and
is explained in <a class="xref" href="functions-matching.html" title="9.7. Pattern Matching">Section 9.7</a>.
</p></td></tr></table></div><p>
</p><p>
It is important to understand the interaction between aggregates and
<acronym class="acronym">SQL</acronym>'s <code class="literal">WHERE</code> and <code class="literal">HAVING</code> clauses.
The fundamental difference between <code class="literal">WHERE</code> and
<code class="literal">HAVING</code> is this: <code class="literal">WHERE</code> selects
input rows before groups and aggregates are computed (thus, it controls
which rows go into the aggregate computation), whereas
<code class="literal">HAVING</code> selects group rows after groups and
aggregates are computed. Thus, the
<code class="literal">WHERE</code> 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, the
<code class="literal">HAVING</code> clause always contains aggregate functions.
(Strictly speaking, you are allowed to write a <code class="literal">HAVING</code>
clause that doesn't use aggregates, but it's seldom useful. The same
condition could be used more efficiently at the <code class="literal">WHERE</code>
stage.)
</p><p>
In the previous example, we can apply the city name restriction in
<code class="literal">WHERE</code>, since it needs no aggregate. This is
more efficient than adding the restriction to <code class="literal">HAVING</code>,
because we avoid doing the grouping and aggregate calculations
for all rows that fail the <code class="literal">WHERE</code> check.
</p><p>
Another way to select the rows that go into an aggregate
computation is to use <code class="literal">FILTER</code>, which is a
per-aggregate option:
</p><pre class="programlisting">
SELECT city, count(*) FILTER (WHERE temp_lo < 45), max(temp_lo)
FROM weather
GROUP BY city;
</pre><p>
</p><pre class="screen">
city | count | max
---------------+-------+-----
Hayward | 1 | 37
San Francisco | 1 | 46
(2 rows)
</pre><p>
<code class="literal">FILTER</code> is much like <code class="literal">WHERE</code>,
except that it removes rows only from the input of the particular
aggregate function that it is attached to.
Here, the <code class="literal">count</code> aggregate counts only
rows with <code class="literal">temp_lo</code> below 45; but the
<code class="literal">max</code> aggregate is still applied to all rows,
so it still finds the reading of 46.
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