<!-- doc/src/sgml/query.sgml -->
<chapter id="tutorial-sql">
<title>The <acronym>SQL</acronym> Language</title>
<sect1 id="tutorial-sql-intro">
<title>Introduction</title>
<para>
This chapter provides an overview of how to use
<acronym>SQL</acronym> to perform simple operations. This
tutorial is only intended to give you an introduction and is in no
way a complete tutorial on <acronym>SQL</acronym>. Numerous books
have been written on <acronym>SQL</acronym>, including <xref
linkend="melt93"/> and <xref linkend="date97"/>.
You should be aware that some <productname>PostgreSQL</productname>
language features are extensions to the standard.
</para>
<para>
In the examples that follow, we assume that you have created a
database named <literal>mydb</literal>, as described in the previous
chapter, and have been able to start <application>psql</application>.
</para>
<para>
Examples in this manual can also be found in the
<productname>PostgreSQL</productname> source distribution
in the directory <filename>src/tutorial/</filename>. (Binary
distributions of <productname>PostgreSQL</productname> might not
provide those files.) To use those
files, first change to that directory and run <application>make</application>:
<screen>
<prompt>$</prompt> <userinput>cd <replaceable>...</replaceable>/src/tutorial</userinput>
<prompt>$</prompt> <userinput>make</userinput>
</screen>
This creates the scripts and compiles the C files containing user-defined
functions and types. Then, to start the tutorial, do the following:
<screen>
<prompt>$</prompt> <userinput>psql -s mydb</userinput>
<computeroutput>
...
</computeroutput>
<prompt>mydb=&gt;</prompt> <userinput>\i basics.sql</userinput>
</screen>
The <literal>\i</literal> command reads in commands from the
specified file. <command>psql</command>'s <literal>-s</literal> option puts you in
single step mode which pauses before sending each statement to the
server. The commands used in this section are in the file
<filename>basics.sql</filename>.
</para>
</sect1>
<sect1 id="tutorial-concepts">
<title>Concepts</title>
<para>
<indexterm><primary>relational database</primary></indexterm>
<indexterm><primary>hierarchical database</primary></indexterm>
<indexterm><primary>object-oriented database</primary></indexterm>
<indexterm><primary>relation</primary></indexterm>
<indexterm><primary>table</primary></indexterm>
<productname>PostgreSQL</productname> is a <firstterm>relational
database management system</firstterm> (<acronym>RDBMS</acronym>).
That means it is a system for managing data stored in
<firstterm>relations</firstterm>. Relation is essentially a
mathematical term for <firstterm>table</firstterm>. The notion of
storing data in tables is so commonplace today that it might
seem inherently obvious, but there are a number of other ways of
organizing databases. Files and directories on Unix-like
operating systems form an example of a hierarchical database. A
more modern development is the object-oriented database.
</para>
<para>
<indexterm><primary>row</primary></indexterm>
<indexterm><primary>column</primary></indexterm>
Each table is a named collection of <firstterm>rows</firstterm>.
Each row of a given table has the same set of named
<firstterm>columns</firstterm>,
and each column is of a specific data type. Whereas columns have
a fixed order in each row, it is important to remember that SQL
does not guarantee the order of the rows within the table in any
way (although they can be explicitly sorted for display).
</para>
<para>
<indexterm><primary>database cluster</primary></indexterm>
<indexterm><primary>cluster</primary><secondary>of databases</secondary><see>database cluster</see></indexterm>
Tables are grouped into databases, and a collection of databases
managed by a single <productname>PostgreSQL</productname> server
instance constitutes a database <firstterm>cluster</firstterm>.
</para>
</sect1>
<sect1 id="tutorial-table">
<title>Creating a New Table</title>
<indexterm zone="tutorial-table">
<primary>CREATE TABLE</primary>
</indexterm>
<para>
You can create a new table by specifying the table
name, along with all column names and their types:
<programlisting>
CREATE TABLE weather (
city varchar(80),
temp_lo int, -- low temperature
temp_hi int, -- high temperature
prcp real, -- precipitation
date date
);
</programlisting>
You can enter this into <command>psql</command> with the line
breaks. <command>psql</command> will recognize that the command
is not terminated until the semicolon.
</para>
<para>
White space (i.e., spaces, tabs, and newlines) can be used freely
in SQL commands. That means you can type the command aligned
differently than above, or even all on one line. Two dashes
(<quote><literal>--</literal></quote>) introduce comments.
Whatever follows them is ignored up to the end of the line. SQL
is case-insensitive about key words and identifiers, except
when identifiers are double-quoted to preserve the case (not done
above).
</para>
<para>
<type>varchar(80)</type> specifies a data type that can store
arbitrary character strings up to 80 characters in length.
<type>int</type> is the normal integer type. <type>real</type> is
a type for storing single precision floating-point numbers.
<type>date</type> should be self-explanatory. (Yes, the column of
type <type>date</type> is also named <structfield>date</structfield>.
This might be convenient or confusing &mdash; you choose.)
</para>
<para>
<productname>PostgreSQL</productname> supports the standard
<acronym>SQL</acronym> types <type>int</type>,
<type>smallint</type>, <type>real</type>, <type>double
precision</type>, <type>char(<replaceable>N</replaceable>)</type>,
<type>varchar(<replaceable>N</replaceable>)</type>, <type>date</type>,
<type>time</type>, <type>timestamp</type>, and
<type>interval</type>, as well as other types of general utility
and a rich set of geometric types.
<productname>PostgreSQL</productname> can be customized with an
arbitrary number of user-defined data types. Consequently, type
names are not key words in the syntax, except where required to
support special cases in the <acronym>SQL</acronym> standard.
</para>
<para>
The second example will store cities and their associated
geographical location:
<programlisting>
CREATE TABLE cities (
name varchar(80),
location point
);
</programlisting>
The <type>point</type> type is an example of a
<productname>PostgreSQL</productname>-specific data type.
</para>
<para>
<indexterm>
<primary>DROP TABLE</primary>
</indexterm>
Finally, it should be mentioned that if you don't need a table any
longer or want to recreate it differently you can remove it using
the following command:
<synopsis>
DROP TABLE <replaceable>tablename</replaceable>;
</synopsis>
</para>
</sect1>
<sect1 id="tutorial-populate">
<title>Populating a Table With Rows</title>
<indexterm zone="tutorial-populate">
<primary>INSERT</primary>
</indexterm>
<para>
The <command>INSERT</command> statement is used to populate a table with
rows:
<programlisting>
INSERT INTO weather VALUES ('San Francisco', 46, 50, 0.25, '1994-11-27');
</programlisting>
Note that all data types use rather obvious input formats.
Constants that are not simple numeric values usually must be
surrounded by single quotes (<literal>'</literal>), as in the example.
The
<type>date</type> type is actually quite flexible in what it
accepts, but for this tutorial we will stick to the unambiguous
format shown here.
</para>
<para>
The <type>point</type> type requires a coordinate pair as input,
as shown here:
<programlisting>
INSERT INTO cities VALUES ('San Francisco', '(-194.0, 53.0)');
</programlisting>
</para>
<para>
The syntax used so far requires you to remember the order of the
columns. An alternative syntax allows you to list the columns
explicitly:
<programlisting>
INSERT INTO weather (city, temp_lo, temp_hi, prcp, date)
VALUES ('San Francisco', 43, 57, 0.0, '1994-11-29');
</programlisting>
You can list the columns in a different order if you wish or
even omit some columns, e.g., if the precipitation is unknown:
<programlisting>
INSERT INTO weather (date, city, temp_hi, temp_lo)
VALUES ('1994-11-29', 'Hayward', 54, 37);
</programlisting>
Many developers consider explicitly listing the columns better
style than relying on the order implicitly.
</para>
<para>
Please enter all the commands shown above so you have some data to
work with in the following sections.
</para>
<para>
<indexterm>
<primary>COPY</primary>
</indexterm>
You could also have used <command>COPY</command> to load large
amounts of data from flat-text files. This is usually faster
because the <command>COPY</command> command is optimized for this
application while allowing less flexibility than
<command>INSERT</command>. An example would be:
<programlisting>
COPY weather FROM '/home/user/weather.txt';
</programlisting>
where the file name for the source file must be available on the
machine running the backend process, not the client, since the backend process
reads the file directly. You can read more about the
<command>COPY</command> command in <xref linkend="sql-copy"/>.
</para>
</sect1>
<sect1 id="tutorial-select">
<title>Querying a Table</title>
<para>
<indexterm><primary>query</primary></indexterm>
<indexterm><primary>SELECT</primary></indexterm>
To retrieve data from a table, the table is
<firstterm>queried</firstterm>. An <acronym>SQL</acronym>
<command>SELECT</command> statement is used to do this. The
statement is divided into a select list (the part that lists the
columns to be returned), a table list (the part that lists the
tables from which to retrieve the data), and an optional
qualification (the part that specifies any restrictions). For
example, to retrieve all the rows of table
<structname>weather</structname>, type:
<programlisting>
SELECT * FROM weather;
</programlisting>
Here <literal>*</literal> is a shorthand for <quote>all columns</quote>.
<footnote>
<para>
While <literal>SELECT *</literal> is useful for off-the-cuff
queries, it is widely considered bad style in production code,
since adding a column to the table would change the results.
</para>
</footnote>
So the same result would be had with:
<programlisting>
SELECT city, temp_lo, temp_hi, prcp, date FROM weather;
</programlisting>
The output should be:
<screen>
city | temp_lo | temp_hi | prcp | date
---------------+---------+---------+------+------------
San Francisco | 46 | 50 | 0.25 | 1994-11-27
San Francisco | 43 | 57 | 0 | 1994-11-29
Hayward | 37 | 54 | | 1994-11-29
(3 rows)
</screen>
</para>
<para>
You can write expressions, not just simple column references, in the
select list. For example, you can do:
<programlisting>
SELECT city, (temp_hi+temp_lo)/2 AS temp_avg, date FROM weather;
</programlisting>
This should give:
<screen>
city | temp_avg | date
---------------+----------+------------
San Francisco | 48 | 1994-11-27
San Francisco | 50 | 1994-11-29
Hayward | 45 | 1994-11-29
(3 rows)
</screen>
Notice how the <literal>AS</literal> clause is used to relabel the
output column. (The <literal>AS</literal> clause is optional.)
</para>
<para>
A query can be <quote>qualified</quote> by adding a <literal>WHERE</literal>
clause that specifies which rows are wanted. The <literal>WHERE</literal>
clause contains a Boolean (truth value) expression, and only rows for
which the Boolean expression is true are returned. The usual
Boolean operators (<literal>AND</literal>,
<literal>OR</literal>, and <literal>NOT</literal>) are allowed in
the qualification. For example, the following
retrieves the weather of San Francisco on rainy days:
<programlisting>
SELECT * FROM weather
WHERE city = 'San Francisco' AND prcp &gt; 0.0;
</programlisting>
Result:
<screen>
city | temp_lo | temp_hi | prcp | date
---------------+---------+---------+------+------------
San Francisco | 46 | 50 | 0.25 | 1994-11-27
(1 row)
</screen>
</para>
<para>
<indexterm><primary>ORDER BY</primary></indexterm>
You can request that the results of a query
be returned in sorted order:
<programlisting>
SELECT * FROM weather
ORDER BY city;
</programlisting>
<screen>
city | temp_lo | temp_hi | prcp | date
---------------+---------+---------+------+------------
Hayward | 37 | 54 | | 1994-11-29
San Francisco | 43 | 57 | 0 | 1994-11-29
San Francisco | 46 | 50 | 0.25 | 1994-11-27
</screen>
In this example, the sort order isn't fully specified, and so you
might get the San Francisco rows in either order. But you'd always
get the results shown above if you do:
<programlisting>
SELECT * FROM weather
ORDER BY city, temp_lo;
</programlisting>
</para>
<para>
<indexterm><primary>DISTINCT</primary></indexterm>
<indexterm><primary>duplicate</primary></indexterm>
You can request that duplicate rows be removed from the result of
a query:
<programlisting>
SELECT DISTINCT city
FROM weather;
</programlisting>
<screen>
city
---------------
Hayward
San Francisco
(2 rows)
</screen>
Here again, the result row ordering might vary.
You can ensure consistent results by using <literal>DISTINCT</literal> and
<literal>ORDER BY</literal> together:
<footnote>
<para>
In some database systems, including older versions of
<productname>PostgreSQL</productname>, the implementation of
<literal>DISTINCT</literal> automatically orders the rows and
so <literal>ORDER BY</literal> is unnecessary. But this is not
required by the SQL standard, and current
<productname>PostgreSQL</productname> does not guarantee that
<literal>DISTINCT</literal> causes the rows to be ordered.
</para>
</footnote>
<programlisting>
SELECT DISTINCT city
FROM weather
ORDER BY city;
</programlisting>
</para>
</sect1>
<sect1 id="tutorial-join">
<title>Joins Between Tables</title>
<indexterm zone="tutorial-join">
<primary>join</primary>
</indexterm>
<para>
Thus far, our queries have only accessed one table at a time.
Queries can access multiple tables at once, or access the same
table in such a way that multiple rows of the table are being
processed at the same time. Queries that access multiple tables
(or multiple instances of the same table) at one time are called
<firstterm>join</firstterm> queries. They combine rows from one table
with rows from a second table, with an expression specifying which rows
are to be paired. For example, to return all the weather records together
with the location of the associated city, the database needs to compare
the <structfield>city</structfield>
column of each row of the <structname>weather</structname> table with the
<structfield>name</structfield> column of all rows in the <structname>cities</structname>
table, and select the pairs of rows where these values match.<footnote>
<para>
This is only a conceptual model. The join is usually performed
in a more efficient manner than actually comparing each possible
pair of rows, but this is invisible to the user.
</para>
</footnote>
This would be accomplished by the following query:
<programlisting>
SELECT * FROM weather JOIN cities ON city = name;
</programlisting>
<screen>
city | temp_lo | temp_hi | prcp | date | name | location
---------------+---------+---------+------+------------+---------------+-----------
San Francisco | 46 | 50 | 0.25 | 1994-11-27 | San Francisco | (-194,53)
San Francisco | 43 | 57 | 0 | 1994-11-29 | San Francisco | (-194,53)
(2 rows)
</screen>
</para>
<para>
Observe two things about the result set:
<itemizedlist>
<listitem>
<para>
There is no result row for the city of Hayward. This is
because there is no matching entry in the
<structname>cities</structname> table for Hayward, so the join
ignores the unmatched rows in the <structname>weather</structname> table. We will see
shortly how this can be fixed.
</para>
</listitem>
<listitem>
<para>
There are two columns containing the city name. This is
correct because the lists of columns from the
<structname>weather</structname> and
<structname>cities</structname> tables are concatenated. In
practice this is undesirable, though, so you will probably want
to list the output columns explicitly rather than using
<literal>*</literal>:
<programlisting>
SELECT city, temp_lo, temp_hi, prcp, date, location
FROM weather JOIN cities ON city = name;
</programlisting>
</para>
</listitem>
</itemizedlist>
</para>
<para>
Since the columns all had different names, the parser
automatically found which table they belong to. If there
were duplicate column names in the two tables you'd need to
<firstterm>qualify</firstterm> the column names to show which one you
meant, as in:
<programlisting>
SELECT weather.city, weather.temp_lo, weather.temp_hi,
weather.prcp, weather.date, cities.location
FROM weather JOIN cities ON weather.city = cities.name;
</programlisting>
It is widely considered good style to qualify all column names
in a join query, so that the query won't fail if a duplicate
column name is later added to one of the tables.
</para>
<para>
Join queries of the kind seen thus far can also be written in this
form:
<programlisting>
SELECT *
FROM weather, cities
WHERE city = name;
</programlisting>
This syntax pre-dates the <literal>JOIN</literal>/<literal>ON</literal>
syntax, which was introduced in SQL-92. The tables are simply listed in
the <literal>FROM</literal> clause, and the comparison expression is added
to the <literal>WHERE</literal> clause. The results from this older
implicit syntax and the newer explicit
<literal>JOIN</literal>/<literal>ON</literal> syntax are identical. But
for a reader of the query, the explicit syntax makes its meaning easier to
understand: The join condition is introduced by its own key word whereas
previously the condition was mixed into the <literal>WHERE</literal>
clause together with other conditions.
</para>
<indexterm><primary>join</primary><secondary>outer</secondary></indexterm>
<para>
Now we will figure out how we can get the Hayward records back in.
What we want the query to do is to scan the
<structname>weather</structname> table and for each row to find the
matching <structname>cities</structname> row(s). If no matching row is
found we want some <quote>empty values</quote> to be substituted
for the <structname>cities</structname> table's columns. This kind
of query is called an <firstterm>outer join</firstterm>. (The
joins we have seen so far are <firstterm>inner joins</firstterm>.)
The command looks like this:
<programlisting>
SELECT *
FROM weather LEFT OUTER JOIN cities ON weather.city = cities.name;
</programlisting>
<screen>
city | temp_lo | temp_hi | prcp | date | name | location
---------------+---------+---------+------+------------+---------------+-----------
Hayward | 37 | 54 | | 1994-11-29 | |
San Francisco | 46 | 50 | 0.25 | 1994-11-27 | San Francisco | (-194,53)
San Francisco | 43 | 57 | 0 | 1994-11-29 | San Francisco | (-194,53)
(3 rows)
</screen>
This query is called a <firstterm>left outer
join</firstterm> because the table mentioned on the left of the
join operator will have each of its rows in the output at least
once, whereas the table on the right will only have those rows
output that match some row of the left table. When outputting a
left-table row for which there is no right-table match, empty (null)
values are substituted for the right-table columns.
</para>
<formalpara>
<title>Exercise:</title>
<para>
There are also right outer joins and full outer joins. Try to
find out what those do.
</para>
</formalpara>
<indexterm><primary>join</primary><secondary>self</secondary></indexterm>
<indexterm><primary>alias</primary><secondary>for table name in query</secondary></indexterm>
<para>
We can also join a table against itself. This is called a
<firstterm>self join</firstterm>. As an example, suppose we wish
to find all the weather records that are in the temperature range
of other weather records. So we need to compare the
<structfield>temp_lo</structfield> and <structfield>temp_hi</structfield> columns of
each <structname>weather</structname> row to the
<structfield>temp_lo</structfield> and
<structfield>temp_hi</structfield> columns of all other
<structname>weather</structname> rows. We can do this with the
following query:
<programlisting>
SELECT w1.city, w1.temp_lo AS low, w1.temp_hi AS high,
w2.city, w2.temp_lo AS low, w2.temp_hi AS high
FROM weather w1 JOIN weather w2
ON w1.temp_lo &lt; w2.temp_lo AND w1.temp_hi &gt; w2.temp_hi;
</programlisting>
<screen>
city | low | high | city | low | high
---------------+-----+------+---------------+-----+------
San Francisco | 43 | 57 | San Francisco | 46 | 50
Hayward | 37 | 54 | San Francisco | 46 | 50
(2 rows)
</screen>
Here we have relabeled the weather table as <literal>w1</literal> and
<literal>w2</literal> to be able to distinguish the left and right side
of the join. You can also use these kinds of aliases in other
queries to save some typing, e.g.:
<programlisting>
SELECT *
FROM weather w JOIN cities c ON w.city = c.name;
</programlisting>
You will encounter this style of abbreviating quite frequently.
</para>
</sect1>
<sect1 id="tutorial-agg">
<title>Aggregate Functions</title>
<indexterm zone="tutorial-agg">
<primary>aggregate function</primary>
</indexterm>
<para>
Like most other relational database products,
<productname>PostgreSQL</productname> supports
<firstterm>aggregate functions</firstterm>.
An aggregate function computes a single result from multiple input rows.
For example, there are aggregates to compute the
<function>count</function>, <function>sum</function>,
<function>avg</function> (average), <function>max</function> (maximum) and
<function>min</function> (minimum) over a set of rows.
</para>
<para>
As an example, we can find the highest low-temperature reading anywhere
with:
<programlisting>
SELECT max(temp_lo) FROM weather;
</programlisting>
<screen>
max
-----
46
(1 row)
</screen>
</para>
<para>
<indexterm><primary>subquery</primary></indexterm>
If we wanted to know what city (or cities) that reading occurred in,
we might try:
<programlisting>
SELECT city FROM weather WHERE temp_lo = max(temp_lo); <lineannotation>-- WRONG</lineannotation>
</programlisting>
but this will not work since the aggregate
<function>max</function> cannot be used in the
<literal>WHERE</literal> clause. (This restriction exists because
the <literal>WHERE</literal> 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 <firstterm>subquery</firstterm>:
<programlisting>
SELECT city FROM weather
WHERE temp_lo = (SELECT max(temp_lo) FROM weather);
</programlisting>
<screen>
city
---------------
San Francisco
(1 row)
</screen>
This is OK because the subquery is an independent computation
that computes its own aggregate separately from what is happening
in the outer query.
</para>
<para>
<indexterm><primary>GROUP BY</primary></indexterm>
<indexterm><primary>HAVING</primary></indexterm>
Aggregates are also very useful in combination with <literal>GROUP
BY</literal> clauses. For example, we can get the number of readings
and the maximum low temperature observed in each city with:
<programlisting>
SELECT city, count(*), max(temp_lo)
FROM weather
GROUP BY city;
</programlisting>
<screen>
city | count | max
---------------+-------+-----
Hayward | 1 | 37
San Francisco | 2 | 46
(2 rows)
</screen>
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 <literal>HAVING</literal>:
<programlisting>
SELECT city, count(*), max(temp_lo)
FROM weather
GROUP BY city
HAVING max(temp_lo) &lt; 40;
</programlisting>
<screen>
city | count | max
---------+-------+-----
Hayward | 1 | 37
(1 row)
</screen>
which gives us the same results for only the cities that have all
<structfield>temp_lo</structfield> values below 40. Finally, if we only care about
cities whose
names begin with <quote><literal>S</literal></quote>, we might do:
<programlisting>
SELECT city, count(*), max(temp_lo)
FROM weather
WHERE city LIKE 'S%' -- <co id="co.tutorial-agg-like"/>
GROUP BY city;
</programlisting>
<screen>
city | count | max
---------------+-------+-----
San Francisco | 2 | 46
(1 row)
</screen>
<calloutlist>
<callout arearefs="co.tutorial-agg-like">
<para>
The <literal>LIKE</literal> operator does pattern matching and
is explained in <xref linkend="functions-matching"/>.
</para>
</callout>
</calloutlist>
</para>
<para>
It is important to understand the interaction between aggregates and
<acronym>SQL</acronym>'s <literal>WHERE</literal> and <literal>HAVING</literal> clauses.
The fundamental difference between <literal>WHERE</literal> and
<literal>HAVING</literal> is this: <literal>WHERE</literal> selects
input rows before groups and aggregates are computed (thus, it controls
which rows go into the aggregate computation), whereas
<literal>HAVING</literal> selects group rows after groups and
aggregates are computed. Thus, the
<literal>WHERE</literal> 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
<literal>HAVING</literal> clause always contains aggregate functions.
(Strictly speaking, you are allowed to write a <literal>HAVING</literal>
clause that doesn't use aggregates, but it's seldom useful. The same
condition could be used more efficiently at the <literal>WHERE</literal>
stage.)
</para>
<para>
In the previous example, we can apply the city name restriction in
<literal>WHERE</literal>, since it needs no aggregate. This is
more efficient than adding the restriction to <literal>HAVING</literal>,
because we avoid doing the grouping and aggregate calculations
for all rows that fail the <literal>WHERE</literal> check.
</para>
<para>
Another way to select the rows that go into an aggregate
computation is to use <literal>FILTER</literal>, which is a
per-aggregate option:
<programlisting>
SELECT city, count(*) FILTER (WHERE temp_lo &lt; 45), max(temp_lo)
FROM weather
GROUP BY city;
</programlisting>
<screen>
city | count | max
---------------+-------+-----
Hayward | 1 | 37
San Francisco | 1 | 46
(2 rows)
</screen>
<literal>FILTER</literal> is much like <literal>WHERE</literal>,
except that it removes rows only from the input of the particular
aggregate function that it is attached to.
Here, the <literal>count</literal> aggregate counts only
rows with <literal>temp_lo</literal> below 45; but the
<literal>max</literal> aggregate is still applied to all rows,
so it still finds the reading of 46.
</para>
</sect1>
<sect1 id="tutorial-update">
<title>Updates</title>
<indexterm zone="tutorial-update">
<primary>UPDATE</primary>
</indexterm>
<para>
You can update existing rows using the
<command>UPDATE</command> command.
Suppose you discover the temperature readings are
all off by 2 degrees after November 28. You can correct the
data as follows:
<programlisting>
UPDATE weather
SET temp_hi = temp_hi - 2, temp_lo = temp_lo - 2
WHERE date &gt; '1994-11-28';
</programlisting>
</para>
<para>
Look at the new state of the data:
<programlisting>
SELECT * FROM weather;
city | temp_lo | temp_hi | prcp | date
---------------+---------+---------+------+------------
San Francisco | 46 | 50 | 0.25 | 1994-11-27
San Francisco | 41 | 55 | 0 | 1994-11-29
Hayward | 35 | 52 | | 1994-11-29
(3 rows)
</programlisting>
</para>
</sect1>
<sect1 id="tutorial-delete">
<title>Deletions</title>
<indexterm zone="tutorial-delete">
<primary>DELETE</primary>
</indexterm>
<para>
Rows can be removed from a table using the <command>DELETE</command>
command.
Suppose you are no longer interested in the weather of Hayward.
Then you can do the following to delete those rows from the table:
<programlisting>
DELETE FROM weather WHERE city = 'Hayward';
</programlisting>
All weather records belonging to Hayward are removed.
<programlisting>
SELECT * FROM weather;
</programlisting>
<screen>
city | temp_lo | temp_hi | prcp | date
---------------+---------+---------+------+------------
San Francisco | 46 | 50 | 0.25 | 1994-11-27
San Francisco | 41 | 55 | 0 | 1994-11-29
(2 rows)
</screen>
</para>
<para>
One should be wary of statements of the form
<synopsis>
DELETE FROM <replaceable>tablename</replaceable>;
</synopsis>
Without a qualification, <command>DELETE</command> will
remove <emphasis>all</emphasis> rows from the given table, leaving it
empty. The system will not request confirmation before
doing this!
</para>
</sect1>
</chapter>