typeconv.sgml

PostgreSQL 8.1.4的源码 适用于Linux下的开源数据库系统

<!--
$PostgreSQL: pgsql/doc/src/sgml/typeconv.sgml,v 1.45 2005/11/04 23:14:02 petere Exp $
-->

<chapter Id="typeconv">
<title>Type Conversion</title>

<indexterm zone="typeconv">
 <primary>data type</primary>
 <secondary>conversion</secondary>
</indexterm>

<para>
<acronym>SQL</acronym> statements can, intentionally or not, require
mixing of different data types in the same expression. 
<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>PostgreSQL</productname>
can affect the results of a query.  When necessary, these results
can be tailored by using <emphasis>explicit</emphasis> type conversion.
</para>

<para>
This chapter introduces the <productname>PostgreSQL</productname>
type conversion mechanisms and conventions.
Refer to the relevant sections in <xref linkend="datatype"> and <xref linkend="functions">
for more information on specific data types and allowed functions and
operators.
</para>

<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>PostgreSQL</productname> has an extensible type system that is
much more general and flexible than other <acronym>SQL</acronym> implementations.
Hence, most type conversion behavior in <productname>PostgreSQL</productname>
is governed by general rules rather than by <foreignphrase>ad hoc</>
heuristics.  This allows
mixed-type expressions to be meaningful even with user-defined types.
</para>

<para>
The <productname>PostgreSQL</productname> scanner/parser divides lexical
elements into only five fundamental categories: integers, non-integer numbers,
strings, identifiers, and key words.  Constants of most non-numeric types are
first classified as strings. The <acronym>SQL</acronym> language definition
allows specifying type names with strings, and this mechanism can be used in
<productname>PostgreSQL</productname> to start the parser down the correct
path. For example, the query

<screen>
SELECT text 'Origin' AS "label", point '(0,0)' AS "value";

 label  | value
--------+-------
 Origin | (0,0)
(1 row)
</screen>

has two literal constants, of type <type>text</type> and <type>point</type>.
If a type is not specified for a string literal, then the placeholder type
<type>unknown</type> is assigned initially, to be resolved in later
stages as described below.
</para>

<para>
There are four fundamental <acronym>SQL</acronym> constructs requiring
distinct type conversion rules in the <productname>PostgreSQL</productname>
parser:

<variablelist>
<varlistentry>
<term>
Function calls
</term>
<listitem>
<para>
Much of the <productname>PostgreSQL</productname> type system is built around a
rich set of functions. Functions can have one or more arguments.
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
types of the supplied arguments.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>
Operators
</term>
<listitem>
<para>
<productname>PostgreSQL</productname> allows expressions with
prefix and postfix unary (one-argument) operators,
as well as binary (two-argument) operators.  Like functions, operators can
be overloaded, and so the same problem of selecting the right operator
exists.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>
Value Storage
</term>
<listitem>
<para>
<acronym>SQL</acronym> <command>INSERT</command> and <command>UPDATE</command> statements place the results of
expressions into a table. The expressions in the statement must be matched up
with, and perhaps converted to, the types of the target columns.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>
<literal>UNION</literal>, <literal>CASE</literal>, and related constructs
</term>
<listitem>
<para>
Since all query results from a unionized <command>SELECT</command> statement
must appear in a single set of columns, the types of the results of each
<command>SELECT</> clause must be matched up and converted to a uniform set.
Similarly, the result expressions of a <literal>CASE</> construct must be
converted to a common type so that the <literal>CASE</> expression as a whole
has a known output type.  The same holds for <literal>ARRAY</> constructs,
and for the <function>GREATEST</> and <function>LEAST</> functions.
</para>
</listitem>
</varlistentry>
</variablelist>
</para>

<para>
The system catalogs store information about which conversions, called
<firstterm>casts</firstterm>, between data types are valid, and how to
perform those conversions.  Additional casts can be added by the user
with the <command>CREATE CAST</command> command.  (This is usually
done in conjunction with defining new data types.  The set of casts
between the built-in types has been carefully crafted and is best not
altered.)
</para>

<indexterm>
 <primary>data type</primary>
 <secondary>category</secondary>
</indexterm>

<para>
An additional heuristic is provided in the parser to allow better guesses
at proper behavior for <acronym>SQL</acronym> standard types. There are
several basic <firstterm>type categories</firstterm> defined: <type>boolean</type>,
<type>numeric</type>, <type>string</type>, <type>bitstring</type>, <type>datetime</type>, <type>timespan</type>, <type>geometric</type>, <type>network</type>,
and user-defined. Each category, with the exception of user-defined, has
one or more <firstterm>preferred types</firstterm> which are preferentially
selected when there is ambiguity.
In the user-defined category, each type is its own preferred type.
Ambiguous expressions (those with multiple candidate parsing solutions)
can therefore often be resolved when there are multiple possible built-in types, but
they will raise an error when there are multiple choices for user-defined
types.
</para>

<para>
All type conversion rules are designed with several principles in mind:

<itemizedlist>
<listitem>
<para>
Implicit conversions should never have surprising or unpredictable outcomes.
</para>
</listitem>

<listitem>
<para>
User-defined types, of which the parser has no <foreignphrase>a priori</> knowledge, should be
<quote>higher</quote> in the type hierarchy. In mixed-type expressions, native types shall always
be converted to a user-defined type (of course, only if conversion is necessary).
</para>
</listitem>

<listitem>
<para>
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 and casts.
</para>
</listitem>

<listitem>
<para>
There should be no extra overhead from the parser or executor
if a query does not need implicit type conversion.
That is, if a query is well formulated and the types already match up, then the query should proceed
without spending extra time in the parser and without introducing unnecessary implicit conversion
calls into the query.
</para>

<para>
Additionally, if a query usually requires an implicit conversion for a function, and
if then the user defines a new function with the correct argument types, the parser
should use this new function and will no longer do the implicit conversion using the old function.
</para>
</listitem>
</itemizedlist>
</para>

</sect1>

<sect1 id="typeconv-oper">
<title>Operators</title>

<indexterm zone="typeconv-oper">
 <primary>operator</primary>
 <secondary>type resolution in an invocation</secondary>
</indexterm>

  <para>
   The specific operator to be used in an operator invocation is determined
   by following
   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>

<step performance="required">
<para>
Select the operators to be considered from the
<classname>pg_operator</classname> system catalog.  If an unqualified
operator name was used (the usual case), the operators
considered are those of the right name and argument count that are
visible in the current search path (see <xref linkend="ddl-schemas-path">).
If a qualified operator name was given, only operators in the specified
schema are considered.
</para>

<substeps>
<step performance="optional">
<para>
If the search path finds multiple operators of identical argument types,
only the one appearing earliest in the path is considered.  But operators of
different argument types are considered on an equal footing regardless of
search path position.
</para>
</step>
</substeps>
</step>

<step performance="required">
<para>
Check for an operator accepting exactly the input argument types.
If one exists (there can be only one exact match in the set of
operators considered), use it.
</para>

<substeps>
<step performance="optional">
<para>
If one argument of a binary operator invocation is of the <type>unknown</type> type,
then assume it is the same type as the other argument for this check.
Other cases involving <type>unknown</type> will never find a match at
this step.
</para>
</step>
</substeps>
</step>

<step performance="required">
<para>
Look for the best match.
</para>
<substeps>
<step performance="required">
<para>
Discard candidate operators for which the input types do not match
and cannot be converted (using an implicit conversion) to match.
<type>unknown</type> literals are
assumed to be convertible to anything for this purpose.  If only one
candidate remains, use it; else continue to the next step.
</para>
</step>
<step performance="required">
<para>
Run through all candidates and keep those with the most exact matches
on input types.  (Domains are considered the same as their base type
for this purpose.)  Keep all candidates if none have any exact matches.
If only one candidate remains, use it; else continue to the next step.
</para>
</step>
<step performance="required">
<para>
Run through all candidates and keep those that accept preferred types (of the
input data type's type category) at the most positions where type conversion
will be required.
Keep all candidates if none accept preferred types.
If only one candidate remains, use it; else continue to the next step.
</para>
</step>
<step performance="required">
<para>
If any input arguments are <type>unknown</type>, check the type
categories accepted at those argument positions by the remaining
candidates.  At each position, select the <type>string</type> category
if any
candidate accepts that category.  (This bias towards string is appropriate
since an unknown-type literal does look like a string.) Otherwise, if
all the remaining candidates accept the same type category, select that
category; otherwise fail because the correct choice cannot be deduced
without more clues.  Now discard
candidates that do not accept the selected type category.  Furthermore,
if any candidate accepts a preferred type at a given argument position,
discard candidates that accept non-preferred types for that argument.
</para>
</step>
<step performance="required">
<para>
If only one candidate remains, use it.  If no candidate or more than one
candidate remains,
then fail.
</para>
</step>
</substeps>
</step>
</procedure>

<para>
Some examples follow.
</para>

<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>integer</type> to both arguments
of this query expression:
<screen>
SELECT 2 ^ 3 AS "exp";

 exp
-----
   8
(1 row)
</screen>

So the parser does a type conversion on both operands and the query
is equivalent to

<screen>
SELECT CAST(2 AS double precision) ^ CAST(3 AS double precision) AS "exp";
</screen>
</para>
</example>

<example>
<title>String Concatenation Operator Type Resolution</title>

<para>
A string-like syntax is used for working with string types as well as for
working with complex extension types.
Strings with unspecified type are matched with likely operator candidates.
</para>

<para>
An example with one unspecified argument:
<screen>
SELECT text 'abc' || 'def' AS "text and unknown";

 text and unknown
------------------
 abcdef
(1 row)
</screen>
</para>

<para>
In this case the parser looks to see if there is an operator taking <type>text</type>
for both arguments. Since there is, it assumes that the second argument should
be interpreted as of type <type>text</type>.
</para>

<para>
Here is a concatenation on unspecified types:
<screen>
SELECT 'abc' || 'def' AS "unspecified";

 unspecified
-------------
 abcdef
(1 row)
</screen>
</para>

<para>
In this case there is no initial hint for which type to use, since no types
are specified in the query. So, the parser looks for all candidate operators
and finds that there are candidates accepting both string-category and
bit-string-category inputs.  Since string category is preferred when available,
that category is selected, and then the 
preferred type for strings, <type>text</type>, is used as the specific
type to resolve the unknown literals to.
</para>
</example>

<example>
<title>Absolute-Value and Negation Operator Type Resolution</title>

<para>
The <productname>PostgreSQL</productname> operator catalog has several
entries for the prefix operator <literal>@</>, all of which implement
absolute-value operations for various numeric data types.  One of these
entries is for type <type>float8</type>, which is the preferred type in
the numeric category.  Therefore, <productname>PostgreSQL</productname>
will use that entry when faced with a non-numeric input:
<screen>
SELECT @ '-4.5' AS "abs";
 abs
-----
 4.5
(1 row)
</screen>
Here the system has performed an implicit conversion from <type>text</type> to <type>float8</type>
before applying the chosen operator.  We can verify that <type>float8</type> and
not some other type was used:
<screen>
SELECT @ '-4.5e500' AS "abs";

ERROR:  "-4.5e500" is out of range for type double precision
</screen>
</para>

<para>
On the other hand, the prefix operator <literal>~</> (bitwise negation)
is defined only for integer data types, not for <type>float8</type>.  So, if we
try a similar case with <literal>~</>, we get:
<screen>
SELECT ~ '20' AS "negation";

ERROR:  operator is not unique: ~ "unknown"
HINT:  Could not choose a best candidate operator. You may need to add explicit
type casts.
</screen>
This happens because the system can't decide which of the several
possible <literal>~</> operators should be preferred.  We can help
it out with an explicit cast:
<screen>
SELECT ~ CAST('20' AS int8) AS "negation";

 negation
----------
      -21
(1 row)
</screen>
</para>
</example>