<chapter Id="typeconv">
<title>Type Conversion</title>
+ <sect1 id="typeconv-intro">
+ <title>Introduction</title>
+
<para>
<acronym>SQL</acronym> queries can, intentionally or not, require
mixing of different data types in the same expression.
-<productname>Postgres</productname> has extensive facilities for
+<productname>PostgreSQL</productname> has extensive facilities for
evaluating mixed-type expressions.
</para>
<para>
In many cases a user will not need
to understand the details of the type conversion mechanism.
-However, the implicit conversions done by <productname>Postgres</productname>
+However, the implicit conversions done by <productname>PostgreSQL</productname>
can affect the results of a query. When necessary, these results
can be tailored by a user or programmer
using <emphasis>explicit</emphasis> type coercion.
</para>
<para>
-This chapter introduces the <productname>Postgres</productname>
+This chapter introduces the <productname>PostgreSQL</productname>
type conversion mechanisms and conventions.
-Refer to the relevant sections in the User's Guide and Programmer's Guide
+Refer to the relevant sections in the <xref linkend="datatype"> and <xref linkend="functions">
for more information on specific data types and allowed functions and
operators.
</para>
<para>
-The Programmer's Guide has more details on the exact algorithms used for
+The <citetitle>Programmer's Guide</citetitle> has more details on the exact algorithms used for
implicit type conversion and coercion.
</para>
+ </sect1>
<sect1 id="typeconv-overview">
<title>Overview</title>
<para>
<acronym>SQL</acronym> is a strongly typed language. That is, every data item
has an associated data type which determines its behavior and allowed usage.
-<productname>Postgres</productname> has an extensible type system that is
+<productname>PostgreSQL</productname> has an extensible type system that is
much more general and flexible than other <acronym>RDBMS</acronym> implementations.
-Hence, most type conversion behavior in <productname>Postgres</productname>
+Hence, most type conversion behavior in <productname>PostgreSQL</productname>
should be governed by general rules rather than by ad-hoc heuristics to allow
mixed-type expressions to be meaningful, even with user-defined types.
</para>
<para>
-The <productname>Postgres</productname> scanner/parser decodes lexical
+The <productname>PostgreSQL</productname> scanner/parser decodes lexical
elements into only five fundamental categories: integers, floats, strings,
names, and keywords. Most extended types are first tokenized into
strings. The <acronym>SQL</acronym> language definition allows specifying type
names with strings, and this mechanism can be used in
-<productname>Postgres</productname> to start the parser down the correct
+<productname>PostgreSQL</productname> to start the parser down the correct
path. For example, the query
-<programlisting>
+<screen>
tgl=> SELECT text 'Origin' AS "Label", point '(0,0)' AS "Value";
Label | Value
--------+-------
Origin | (0,0)
(1 row)
-</programlisting>
+</screen>
has two strings, of type <type>text</type> and <type>point</type>.
If a type is not specified for a string, then the placeholder type
<para>
There are four fundamental <acronym>SQL</acronym> constructs requiring
-distinct type conversion rules in the <productname>Postgres</productname>
+distinct type conversion rules in the <productname>PostgreSQL</productname>
parser:
</para>
</term>
<listitem>
<para>
-<productname>Postgres</productname> allows expressions with
-left- and right-unary (one argument) operators,
+<productname>PostgreSQL</productname> allows expressions with
+prefix and postfix unary (one argument) operators,
as well as binary (two argument) operators.
</para>
</listitem>
</term>
<listitem>
<para>
-Much of the <productname>Postgres</productname> type system is built around a
+Much of the <productname>PostgreSQL</productname> type system is built around a
rich set of functions. Function calls have one or more arguments which, for
any specific query, must be matched to the functions available in the system
-catalog. Since <productname>Postgres</productname> permits function
+catalog. Since <productname>PostgreSQL</productname> permits function
overloading, the function name alone does not uniquely identify the function
-to be called --- the parser must select the right function based on the data
+to be called; the parser must select the right function based on the data
types of the supplied arguments.
</para>
</listitem>
</term>
<listitem>
<para>
-<acronym>SQL</acronym> INSERT and UPDATE statements place the results of
+<acronym>SQL</acronym> <command>INSERT</command> and <command>UPDATE</command> statements place the results of
expressions into a table. The expressions in the query must be matched up
with, and perhaps converted to, the types of the target columns.
</para>
</varlistentry>
<varlistentry>
<term>
-UNION and CASE constructs
+<literal>UNION</literal> and <literal>CASE</literal> constructs
</term>
<listitem>
<para>
-Since all select results from a UNION SELECT statement must appear in a single
+Since all select results from a unionized <literal>SELECT</literal> statement must appear in a single
set of columns, the types of the results
-of each SELECT clause must be matched up and converted to a uniform set.
-Similarly, the result expressions of a CASE construct must be coerced to
-a common type so that the CASE expression as a whole has a known output type.
+of each <literal>SELECT</> clause must be matched up and converted to a uniform set.
+Similarly, the result expressions of a <literal>CASE</> construct must be coerced to
+a common type so that the <literal>CASE</> expression as a whole has a known output type.
</para>
</listitem>
</varlistentry>
<para>
Many of the general type conversion rules use simple conventions built on
-the <productname>Postgres</productname> function and operator system tables.
+the <productname>PostgreSQL</productname> function and operator system tables.
There are some heuristics included in the conversion rules to better support
-conventions for the <acronym>SQL92</acronym> standard native types such as
-<type>smallint</type>, <type>integer</type>, and <type>float</type>.
+conventions for the <acronym>SQL</acronym> standard native types such as
+<type>smallint</type>, <type>integer</type>, and <type>real</type>.
</para>
<para>
-The <productname>Postgres</productname> parser uses the convention that all
+The <productname>PostgreSQL</productname> parser uses the convention that all
type conversion functions take a single argument of the source type and are
named with the same name as the target type. Any function meeting these
criteria is considered to be a valid conversion function, and may be used
types.
</para>
-<sect2>
-<title>Guidelines</title>
-
<para>
All type conversion rules are designed with several principles in mind:
<listitem>
<para>
-User-defined types are not related. Currently, <productname>Postgres</productname>
+User-defined types are not related. Currently, <productname>PostgreSQL</productname>
does not have information available to it on relationships between types, other than
hardcoded heuristics for built-in types and implicit relationships based on available functions
in the catalog.
</listitem>
</itemizedlist>
</para>
-</sect2>
+
</sect1>
<sect1 id="typeconv-oper">
<title>Operators</title>
+ <para>
+ The operand types of an operator invocation are resolved following
+ to the procedure below. Note that this procedure is indirectly affected
+ by the precedence of the involved operators. See <xref
+ linkend="sql-precedence"> for more information.
+ </para>
+
<procedure>
-<title>Operator Type Resolution</title>
+<title>Operand Type Resolution</title>
<step performance="required">
<para>
-Check for an exact match in the pg_operator system catalog.
+Check for an exact match in the <classname>pg_operator</classname> system catalog.
</para>
<substeps>
</step>
</procedure>
-<sect2>
-<title>Examples</title>
+<bridgehead renderas="sect2">Examples</bridgehead>
-<sect3>
-<title>Exponentiation Operator</title>
+<example>
+<title>Exponentiation Operator Type Resolution</title>
<para>
There is only one exponentiation
operator defined in the catalog, and it takes arguments of type
<type>double precision</type>.
-The scanner assigns an initial type of <type>int4</type> to both arguments
+The scanner assigns an initial type of <type>integer</type> to both arguments
of this query expression:
-<programlisting>
+<screen>
tgl=> select 2 ^ 3 AS "Exp";
Exp
-----
8
(1 row)
-</programlisting>
+</screen>
So the parser does a type conversion on both operands and the query
is equivalent to
-<programlisting>
+<screen>
tgl=> select CAST(2 AS double precision) ^ CAST(3 AS double precision) AS "Exp";
Exp
-----
8
(1 row)
-</programlisting>
+</screen>
or
-<programlisting>
+<screen>
tgl=> select 2.0 ^ 3.0 AS "Exp";
Exp
-----
8
(1 row)
-</programlisting>
+</screen>
<note>
<para>
</para>
</note>
</para>
-</sect3>
+</example>
-<sect3>
-<title>String Concatenation</title>
+<example>
+<title>String Concatenation Operator Type Resolution</title>
<para>
A string-like syntax is used for working with string types as well as for
<para>
One unspecified argument:
-<programlisting>
+<screen>
tgl=> SELECT text 'abc' || 'def' AS "Text and Unknown";
Text and Unknown
------------------
abcdef
(1 row)
-</programlisting>
+</screen>
</para>
<para>
<para>
Concatenation on unspecified types:
-<programlisting>
+<screen>
tgl=> SELECT 'abc' || 'def' AS "Unspecified";
Unspecified
-------------
abcdef
(1 row)
-</programlisting>
+</screen>
</para>
<para>
<quote>preferred type</quote> for strings, <type>text</type>, is used as the specific
type to resolve the unknown literals to.
</para>
-</sect3>
+</example>
-<sect3>
-<title>Factorial</title>
+<example>
+<title>Factorial Operator Type Resolution</title>
<para>
This example illustrates an interesting result. Traditionally, the
-factorial operator is defined for integers only. The <productname>Postgres</productname>
+factorial operator is defined for integers only. The <productname>PostgreSQL</productname>
operator catalog has only one entry for factorial, taking an integer operand.
-If given a non-integer numeric argument, <productname>Postgres</productname>
+If given a non-integer numeric argument, <productname>PostgreSQL</productname>
will try to convert that argument to an integer for evaluation of the
factorial.
-<programlisting>
+<screen>
tgl=> select (4.3 !);
?column?
----------
24
(1 row)
-</programlisting>
+</screen>
<note>
<para>
since in principle the factorial of a non-integer is not defined.
However, the role of a database is not to teach mathematics, but
to be a tool for data manipulation. If a user chooses to take the
-factorial of a floating point number, <productname>Postgres</productname>
+factorial of a floating point number, <productname>PostgreSQL</productname>
will try to oblige.
</para>
</note>
</para>
-</sect3>
-</sect2>
+</example>
+
</sect1>
<sect1 id="typeconv-func">
<title>Functions</title>
+ <para>
+ The argument types of function calls are resolved according to the
+ following steps.
+ </para>
+
<procedure>
-<title>Function Call Type Resolution</title>
+<title>Function Argument Type Resolution</title>
<step performance="required">
<para>
</step>
</procedure>
-<sect2>
-<title>Examples</title>
+<bridgehead renderas="sect2">Examples</bridgehead>
-<sect3>
-<title>Factorial Function</title>
+<example>
+<title>Factorial Function Argument Type Resolution</title>
<para>
There is only one factorial function defined in the <classname>pg_proc</classname> catalog.
So the following query automatically converts the <type>int2</type> argument
to <type>int4</type>:
-<programlisting>
+<screen>
tgl=> select int4fac(int2 '4');
int4fac
---------
24
(1 row)
-</programlisting>
+</screen>
and is actually transformed by the parser to
-<programlisting>
+<screen>
tgl=> select int4fac(int4(int2 '4'));
int4fac
---------
24
(1 row)
-</programlisting>
+</screen>
</para>
-</sect3>
+</example>
-<sect3>
-<title>Substring Function</title>
+<example>
+<title>Substring Function Type Resolution</title>
<para>
There are two <function>substr</function> functions declared in <classname>pg_proc</classname>. However,
<para>
If called with a string constant of unspecified type, the type is matched up
directly with the only candidate function type:
-<programlisting>
+<screen>
tgl=> select substr('1234', 3);
substr
--------
34
(1 row)
-</programlisting>
+</screen>
</para>
<para>
If the string is declared to be of type <type>varchar</type>, as might be the case
if it comes from a table, then the parser will try to coerce it to become <type>text</type>:
-<programlisting>
+<screen>
tgl=> select substr(varchar '1234', 3);
substr
--------
34
(1 row)
-</programlisting>
+</screen>
which is transformed by the parser to become
-<programlisting>
+<screen>
tgl=> select substr(text(varchar '1234'), 3);
substr
--------
34
(1 row)
-</programlisting>
+</screen>
</para>
+<para>
<note>
<para>
Actually, the parser is aware that <type>text</type> and <type>varchar</type>
explicit type conversion call is really inserted in this case.
</para>
</note>
+</para>
<para>
And, if the function is called with an <type>int4</type>, the parser will
try to convert that to <type>text</type>:
-<programlisting>
+<screen>
tgl=> select substr(1234, 3);
substr
--------
34
(1 row)
-</programlisting>
+</screen>
actually executes as
-<programlisting>
+<screen>
tgl=> select substr(text(1234), 3);
substr
--------
34
(1 row)
-</programlisting>
+</screen>
This succeeds because there is a conversion function text(int4) in the
system catalog.
</para>
-</sect3>
-</sect2>
+</example>
+
</sect1>
<sect1 id="typeconv-query">
</procedure>
-<sect2>
-<title>Examples</title>
-
-<sect3>
-<title><type>varchar</type> Storage</title>
+<example>
+<title><type>varchar</type> Storage Type Conversion</title>
<para>
For a target column declared as <type>varchar(4)</type> the following query
ensures that the target is sized correctly:
-<programlisting>
+<screen>
tgl=> CREATE TABLE vv (v varchar(4));
CREATE
tgl=> INSERT INTO vv SELECT 'abc' || 'def';
------
abcd
(1 row)
-</programlisting>
+</screen>
-What's really happened here is that the two unknown literals are resolved
-to text by default, allowing the <literal>||</literal> operator to be
-resolved as text concatenation. Then the text result of the operator
+What has really happened here is that the two unknown literals are resolved
+to <type>text</type> by default, allowing the <literal>||</literal> operator to be
+resolved as <type>text</type> concatenation. Then the <type>text</type> result of the operator
is coerced to <type>varchar</type> to match the target column type. (But, since the
-parser knows that text and <type>varchar</type> are binary-compatible, this coercion
+parser knows that <type>text</type> and <type>varchar</type> are binary-compatible, this coercion
is implicit and does not insert any real function call.) Finally, the
-sizing function <literal>varchar(varchar,int4)</literal> is found in the system
+sizing function <literal>varchar(varchar, integer)</literal> is found in the system
catalogs and applied to the operator's result and the stored column length.
This type-specific function performs the desired truncation.
</para>
-</sect3>
-</sect2>
+</example>
</sect1>
<sect1 id="typeconv-union-case">
-<title>UNION and CASE Constructs</title>
+<title><literal>UNION</> and <literal>CASE</> Constructs</title>
<para>
-The UNION and CASE constructs must match up possibly dissimilar types to
+The <literal>UNION</> and <literal>CASE</> constructs must match up possibly dissimilar types to
become a single result set. The resolution algorithm is applied separately to
-each output column of a UNION. CASE uses the identical algorithm to match
+each output column of a union. <literal>CASE</> uses the identical algorithm to match
up its result expressions.
</para>
<procedure>
-<title>UNION and CASE Type Resolution</title>
+<title><literal>UNION</> and <literal>CASE</> Type Resolution</title>
<step performance="required">
<para>
</para></step>
</procedure>
-<sect2>
-<title>Examples</title>
+<bridgehead renderas="sect2">Examples</bridgehead>
-<sect3>
-<title>Underspecified Types</title>
+<example>
+<title>Underspecified Types in a Union</title>
<para>
-<programlisting>
+<screen>
tgl=> SELECT text 'a' AS "Text" UNION SELECT 'b';
Text
------
a
b
(2 rows)
-</programlisting>
+</screen>
Here, the unknown-type literal <literal>'b'</literal> will be resolved as type text.
</para>
-</sect3>
+</example>
-<sect3>
-<title>Simple UNION</title>
+<example>
+<title>Type Conversion in a Simple Union</title>
<para>
-<programlisting>
+<screen>
tgl=> SELECT 1.2 AS "Double" UNION SELECT 1;
Double
--------
1
1.2
(2 rows)
-</programlisting>
+</screen>
</para>
-</sect3>
+</example>
-<sect3>
-<title>Transposed UNION</title>
+<example>
+<title>Type Conversion in a Transposed Union</title>
<para>
Here the output type of the union is forced to match the type of
the first/top clause in the union:
-<programlisting>
+<screen>
tgl=> SELECT 1 AS "All integers"
tgl-> UNION SELECT CAST('2.2' AS REAL);
All integers
1
2
(2 rows)
-</programlisting>
+</screen>
</para>
<para>
Since <type>REAL</type> is not a preferred type, the parser sees no reason
falls back on the use-the-first-alternative rule.
This example demonstrates that the preferred-type mechanism doesn't encode
as much information as we'd like. Future versions of
-<productname>Postgres</productname> may support a more general notion of
+<productname>PostgreSQL</productname> may support a more general notion of
type preferences.
</para>
-</sect3>
-</sect2>
+</example>
+
</sect1>
</chapter>
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