922 lines
27 KiB
Plaintext
922 lines
27 KiB
Plaintext
<!-- $PostgreSQL: pgsql/doc/src/sgml/typeconv.sgml,v 1.48 2006/09/18 19:54:01 tgl Exp $ -->
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<chapter Id="typeconv">
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<title>Type Conversion</title>
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<indexterm zone="typeconv">
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<primary>data type</primary>
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<secondary>conversion</secondary>
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</indexterm>
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<para>
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<acronym>SQL</acronym> statements can, intentionally or not, require
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mixing of different data types in the same expression.
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<productname>PostgreSQL</productname> has extensive facilities for
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evaluating mixed-type expressions.
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</para>
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<para>
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In many cases a user will not need
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to understand the details of the type conversion mechanism.
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However, the implicit conversions done by <productname>PostgreSQL</productname>
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can affect the results of a query. When necessary, these results
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can be tailored by using <emphasis>explicit</emphasis> type conversion.
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</para>
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<para>
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This chapter introduces the <productname>PostgreSQL</productname>
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type conversion mechanisms and conventions.
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Refer to the relevant sections in <xref linkend="datatype"> and <xref linkend="functions">
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for more information on specific data types and allowed functions and
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operators.
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</para>
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<sect1 id="typeconv-overview">
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<title>Overview</title>
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<para>
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<acronym>SQL</acronym> is a strongly typed language. That is, every data item
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has an associated data type which determines its behavior and allowed usage.
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<productname>PostgreSQL</productname> has an extensible type system that is
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much more general and flexible than other <acronym>SQL</acronym> implementations.
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Hence, most type conversion behavior in <productname>PostgreSQL</productname>
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is governed by general rules rather than by <foreignphrase>ad hoc</>
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heuristics. This allows
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mixed-type expressions to be meaningful even with user-defined types.
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</para>
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<para>
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The <productname>PostgreSQL</productname> scanner/parser divides lexical
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elements into only five fundamental categories: integers, non-integer numbers,
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strings, identifiers, and key words. Constants of most non-numeric types are
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first classified as strings. The <acronym>SQL</acronym> language definition
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allows specifying type names with strings, and this mechanism can be used in
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<productname>PostgreSQL</productname> to start the parser down the correct
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path. For example, the query
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<screen>
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SELECT text 'Origin' AS "label", point '(0,0)' AS "value";
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label | value
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--------+-------
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Origin | (0,0)
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(1 row)
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</screen>
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has two literal constants, of type <type>text</type> and <type>point</type>.
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If a type is not specified for a string literal, then the placeholder type
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<type>unknown</type> is assigned initially, to be resolved in later
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stages as described below.
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</para>
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<para>
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There are four fundamental <acronym>SQL</acronym> constructs requiring
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distinct type conversion rules in the <productname>PostgreSQL</productname>
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parser:
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<variablelist>
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<varlistentry>
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<term>
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Function calls
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</term>
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<listitem>
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<para>
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Much of the <productname>PostgreSQL</productname> type system is built around a
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rich set of functions. Functions can have one or more arguments.
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Since <productname>PostgreSQL</productname> permits function
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overloading, the function name alone does not uniquely identify the function
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to be called; the parser must select the right function based on the data
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types of the supplied arguments.
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</para>
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</listitem>
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</varlistentry>
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<varlistentry>
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<term>
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Operators
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</term>
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<listitem>
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<para>
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<productname>PostgreSQL</productname> allows expressions with
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prefix and postfix unary (one-argument) operators,
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as well as binary (two-argument) operators. Like functions, operators can
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be overloaded, and so the same problem of selecting the right operator
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exists.
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</para>
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</listitem>
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</varlistentry>
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<varlistentry>
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<term>
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Value Storage
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</term>
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<listitem>
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<para>
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<acronym>SQL</acronym> <command>INSERT</command> and <command>UPDATE</command> statements place the results of
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expressions into a table. The expressions in the statement must be matched up
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with, and perhaps converted to, the types of the target columns.
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</para>
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</listitem>
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</varlistentry>
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<varlistentry>
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<term>
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<literal>UNION</literal>, <literal>CASE</literal>, and related constructs
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</term>
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<listitem>
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<para>
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Since all query results from a unionized <command>SELECT</command> statement
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must appear in a single set of columns, the types of the results of each
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<command>SELECT</> clause must be matched up and converted to a uniform set.
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Similarly, the result expressions of a <literal>CASE</> construct must be
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converted to a common type so that the <literal>CASE</> expression as a whole
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has a known output type. The same holds for <literal>ARRAY</> constructs,
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and for the <function>GREATEST</> and <function>LEAST</> functions.
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</para>
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</listitem>
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</varlistentry>
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</variablelist>
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</para>
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<para>
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The system catalogs store information about which conversions, called
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<firstterm>casts</firstterm>, between data types are valid, and how to
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perform those conversions. Additional casts can be added by the user
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with the <command>CREATE CAST</command> command. (This is usually
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done in conjunction with defining new data types. The set of casts
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between the built-in types has been carefully crafted and is best not
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altered.)
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</para>
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<indexterm>
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<primary>data type</primary>
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<secondary>category</secondary>
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</indexterm>
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<para>
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An additional heuristic is provided in the parser to allow better guesses
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at proper behavior for <acronym>SQL</acronym> standard types. There are
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several basic <firstterm>type categories</firstterm> defined: <type>boolean</type>,
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<type>numeric</type>, <type>string</type>, <type>bitstring</type>, <type>datetime</type>, <type>timespan</type>, <type>geometric</type>, <type>network</type>,
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and user-defined. Each category, with the exception of user-defined, has
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one or more <firstterm>preferred types</firstterm> which are preferentially
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selected when there is ambiguity.
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In the user-defined category, each type is its own preferred type.
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Ambiguous expressions (those with multiple candidate parsing solutions)
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can therefore often be resolved when there are multiple possible built-in types, but
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they will raise an error when there are multiple choices for user-defined
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types.
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</para>
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<para>
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All type conversion rules are designed with several principles in mind:
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<itemizedlist>
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<listitem>
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<para>
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Implicit conversions should never have surprising or unpredictable outcomes.
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</para>
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</listitem>
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<listitem>
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<para>
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User-defined types, of which the parser has no <foreignphrase>a priori</> knowledge, should be
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<quote>higher</quote> in the type hierarchy. In mixed-type expressions, native types shall always
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be converted to a user-defined type (of course, only if conversion is necessary).
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</para>
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</listitem>
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<listitem>
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<para>
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User-defined types are not related. Currently, <productname>PostgreSQL</productname>
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does not have information available to it on relationships between types, other than
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hardcoded heuristics for built-in types and implicit relationships based on
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available functions and casts.
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</para>
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</listitem>
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<listitem>
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<para>
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There should be no extra overhead from the parser or executor
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if a query does not need implicit type conversion.
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That is, if a query is well formulated and the types already match up, then the query should proceed
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without spending extra time in the parser and without introducing unnecessary implicit conversion
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calls into the query.
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</para>
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<para>
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Additionally, if a query usually requires an implicit conversion for a function, and
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if then the user defines a new function with the correct argument types, the parser
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should use this new function and will no longer do the implicit conversion using the old function.
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</para>
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</listitem>
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</itemizedlist>
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</para>
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</sect1>
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<sect1 id="typeconv-oper">
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<title>Operators</title>
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<indexterm zone="typeconv-oper">
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<primary>operator</primary>
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<secondary>type resolution in an invocation</secondary>
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</indexterm>
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<para>
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The specific operator to be used in an operator invocation is determined
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by following
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the procedure below. Note that this procedure is indirectly affected
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by the precedence of the involved operators. See <xref
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linkend="sql-precedence"> for more information.
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</para>
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<procedure>
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<title>Operator Type Resolution</title>
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<step performance="required">
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<para>
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Select the operators to be considered from the
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<classname>pg_operator</classname> system catalog. If an unqualified
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operator name was used (the usual case), the operators
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considered are those of the right name and argument count that are
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visible in the current search path (see <xref linkend="ddl-schemas-path">).
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If a qualified operator name was given, only operators in the specified
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schema are considered.
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</para>
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<substeps>
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<step performance="optional">
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<para>
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If the search path finds multiple operators of identical argument types,
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only the one appearing earliest in the path is considered. But operators of
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different argument types are considered on an equal footing regardless of
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search path position.
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</para>
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</step>
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</substeps>
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</step>
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<step performance="required">
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<para>
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Check for an operator accepting exactly the input argument types.
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If one exists (there can be only one exact match in the set of
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operators considered), use it.
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</para>
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<substeps>
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<step performance="optional">
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<para>
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If one argument of a binary operator invocation is of the <type>unknown</type> type,
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then assume it is the same type as the other argument for this check.
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Other cases involving <type>unknown</type> will never find a match at
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this step.
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</para>
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</step>
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</substeps>
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</step>
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<step performance="required">
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<para>
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Look for the best match.
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</para>
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<substeps>
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<step performance="required">
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<para>
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Discard candidate operators for which the input types do not match
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and cannot be converted (using an implicit conversion) to match.
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<type>unknown</type> literals are
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assumed to be convertible to anything for this purpose. If only one
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candidate remains, use it; else continue to the next step.
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</para>
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</step>
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<step performance="required">
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<para>
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Run through all candidates and keep those with the most exact matches
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on input types. (Domains are considered the same as their base type
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for this purpose.) Keep all candidates if none have any exact matches.
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If only one candidate remains, use it; else continue to the next step.
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</para>
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</step>
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<step performance="required">
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<para>
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Run through all candidates and keep those that accept preferred types (of the
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input data type's type category) at the most positions where type conversion
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will be required.
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Keep all candidates if none accept preferred types.
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If only one candidate remains, use it; else continue to the next step.
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</para>
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</step>
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<step performance="required">
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<para>
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If any input arguments are <type>unknown</type>, check the type
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categories accepted at those argument positions by the remaining
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candidates. At each position, select the <type>string</type> category
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if any
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candidate accepts that category. (This bias towards string is appropriate
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since an unknown-type literal does look like a string.) Otherwise, if
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all the remaining candidates accept the same type category, select that
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category; otherwise fail because the correct choice cannot be deduced
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without more clues. Now discard
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candidates that do not accept the selected type category. Furthermore,
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if any candidate accepts a preferred type at a given argument position,
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discard candidates that accept non-preferred types for that argument.
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</para>
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</step>
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<step performance="required">
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<para>
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If only one candidate remains, use it. If no candidate or more than one
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candidate remains,
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then fail.
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</para>
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</step>
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</substeps>
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</step>
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</procedure>
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<para>
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Some examples follow.
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</para>
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<example>
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<title>Exponentiation Operator Type Resolution</title>
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<para>
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There is only one exponentiation
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operator defined in the catalog, and it takes arguments of type
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<type>double precision</type>.
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The scanner assigns an initial type of <type>integer</type> to both arguments
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of this query expression:
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<screen>
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SELECT 2 ^ 3 AS "exp";
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exp
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-----
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8
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(1 row)
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</screen>
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So the parser does a type conversion on both operands and the query
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is equivalent to
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<screen>
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SELECT CAST(2 AS double precision) ^ CAST(3 AS double precision) AS "exp";
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</screen>
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</para>
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</example>
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<example>
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<title>String Concatenation Operator Type Resolution</title>
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<para>
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A string-like syntax is used for working with string types as well as for
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working with complex extension types.
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Strings with unspecified type are matched with likely operator candidates.
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</para>
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<para>
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An example with one unspecified argument:
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<screen>
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SELECT text 'abc' || 'def' AS "text and unknown";
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text and unknown
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------------------
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abcdef
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(1 row)
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</screen>
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</para>
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<para>
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In this case the parser looks to see if there is an operator taking <type>text</type>
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for both arguments. Since there is, it assumes that the second argument should
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be interpreted as of type <type>text</type>.
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</para>
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<para>
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Here is a concatenation on unspecified types:
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<screen>
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SELECT 'abc' || 'def' AS "unspecified";
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unspecified
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-------------
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abcdef
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(1 row)
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</screen>
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</para>
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<para>
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In this case there is no initial hint for which type to use, since no types
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are specified in the query. So, the parser looks for all candidate operators
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and finds that there are candidates accepting both string-category and
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bit-string-category inputs. Since string category is preferred when available,
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that category is selected, and then the
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preferred type for strings, <type>text</type>, is used as the specific
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type to resolve the unknown literals to.
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</para>
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</example>
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<example>
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<title>Absolute-Value and Negation Operator Type Resolution</title>
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<para>
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The <productname>PostgreSQL</productname> operator catalog has several
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entries for the prefix operator <literal>@</>, all of which implement
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absolute-value operations for various numeric data types. One of these
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entries is for type <type>float8</type>, which is the preferred type in
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the numeric category. Therefore, <productname>PostgreSQL</productname>
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will use that entry when faced with a non-numeric input:
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<screen>
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SELECT @ '-4.5' AS "abs";
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abs
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-----
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4.5
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(1 row)
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</screen>
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Here the system has performed an implicit conversion from <type>text</type> to <type>float8</type>
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before applying the chosen operator. We can verify that <type>float8</type> and
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not some other type was used:
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<screen>
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SELECT @ '-4.5e500' AS "abs";
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ERROR: "-4.5e500" is out of range for type double precision
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</screen>
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</para>
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<para>
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On the other hand, the prefix operator <literal>~</> (bitwise negation)
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is defined only for integer data types, not for <type>float8</type>. So, if we
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try a similar case with <literal>~</>, we get:
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<screen>
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SELECT ~ '20' AS "negation";
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ERROR: operator is not unique: ~ "unknown"
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HINT: Could not choose a best candidate operator. You may need to add explicit
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type casts.
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</screen>
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This happens because the system can't decide which of the several
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possible <literal>~</> operators should be preferred. We can help
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it out with an explicit cast:
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<screen>
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SELECT ~ CAST('20' AS int8) AS "negation";
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negation
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----------
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-21
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(1 row)
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</screen>
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</para>
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</example>
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</sect1>
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|
|
<sect1 id="typeconv-func">
|
|
<title>Functions</title>
|
|
|
|
<indexterm zone="typeconv-func">
|
|
<primary>function</primary>
|
|
<secondary>type resolution in an invocation</secondary>
|
|
</indexterm>
|
|
|
|
<para>
|
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The specific function to be used in a function invocation is determined
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according to the following steps.
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</para>
|
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|
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<procedure>
|
|
<title>Function Type Resolution</title>
|
|
|
|
<step performance="required">
|
|
<para>
|
|
Select the functions to be considered from the
|
|
<classname>pg_proc</classname> system catalog. If an unqualified
|
|
function name was used, the functions
|
|
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 function name was given, only functions in the specified
|
|
schema are considered.
|
|
</para>
|
|
|
|
<substeps>
|
|
<step performance="optional">
|
|
<para>
|
|
If the search path finds multiple functions of identical argument types,
|
|
only the one appearing earliest in the path is considered. But functions 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 a function accepting exactly the input argument types.
|
|
If one exists (there can be only one exact match in the set of
|
|
functions considered), use it.
|
|
(Cases involving <type>unknown</type> will never find a match at
|
|
this step.)
|
|
</para>
|
|
</step>
|
|
|
|
<step performance="required">
|
|
<para>
|
|
If no exact match is found, see whether the function call appears
|
|
to be a trivial type conversion request. This happens if the function call
|
|
has just one argument and the function name is the same as the (internal)
|
|
name of some data type. Furthermore, the function argument must be either
|
|
an unknown-type literal or a type that is binary-compatible with the named
|
|
data type. When these conditions are met, the function argument is converted
|
|
to the named data type without any actual function call.
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|
</para>
|
|
</step>
|
|
<step performance="required">
|
|
<para>
|
|
Look for the best match.
|
|
</para>
|
|
<substeps>
|
|
<step performance="required">
|
|
<para>
|
|
Discard candidate functions 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>
|
|
Note that the <quote>best match</> rules are identical for operator and
|
|
function type resolution.
|
|
Some examples follow.
|
|
</para>
|
|
|
|
<example>
|
|
<title>Rounding Function Argument Type Resolution</title>
|
|
|
|
<para>
|
|
There is only one <function>round</function> function with two
|
|
arguments. (The first is <type>numeric</type>, the second is
|
|
<type>integer</type>.) So the following query automatically converts
|
|
the first argument of type <type>integer</type> to
|
|
<type>numeric</type>:
|
|
|
|
<screen>
|
|
SELECT round(4, 4);
|
|
|
|
round
|
|
--------
|
|
4.0000
|
|
(1 row)
|
|
</screen>
|
|
|
|
That query is actually transformed by the parser to
|
|
<screen>
|
|
SELECT round(CAST (4 AS numeric), 4);
|
|
</screen>
|
|
</para>
|
|
|
|
<para>
|
|
Since numeric constants with decimal points are initially assigned the
|
|
type <type>numeric</type>, the following query will require no type
|
|
conversion and may therefore be slightly more efficient:
|
|
<screen>
|
|
SELECT round(4.0, 4);
|
|
</screen>
|
|
</para>
|
|
</example>
|
|
|
|
<example>
|
|
<title>Substring Function Type Resolution</title>
|
|
|
|
<para>
|
|
There are several <function>substr</function> functions, one of which
|
|
takes types <type>text</type> and <type>integer</type>. If called
|
|
with a string constant of unspecified type, the system chooses the
|
|
candidate function that accepts an argument of the preferred category
|
|
<literal>string</literal> (namely of type <type>text</type>).
|
|
|
|
<screen>
|
|
SELECT substr('1234', 3);
|
|
|
|
substr
|
|
--------
|
|
34
|
|
(1 row)
|
|
</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 convert it to become <type>text</type>:
|
|
<screen>
|
|
SELECT substr(varchar '1234', 3);
|
|
|
|
substr
|
|
--------
|
|
34
|
|
(1 row)
|
|
</screen>
|
|
|
|
This is transformed by the parser to effectively become
|
|
<screen>
|
|
SELECT substr(CAST (varchar '1234' AS text), 3);
|
|
</screen>
|
|
</para>
|
|
<para>
|
|
<note>
|
|
<para>
|
|
The parser learns from the <structname>pg_cast</> catalog that
|
|
<type>text</type> and <type>varchar</type>
|
|
are binary-compatible, meaning that one can be passed to a function that
|
|
accepts the other without doing any physical conversion. Therefore, no
|
|
explicit type conversion call is really inserted in this case.
|
|
</para>
|
|
</note>
|
|
</para>
|
|
|
|
<para>
|
|
And, if the function is called with an argument of type <type>integer</type>, the parser will
|
|
try to convert that to <type>text</type>:
|
|
<screen>
|
|
SELECT substr(1234, 3);
|
|
|
|
substr
|
|
--------
|
|
34
|
|
(1 row)
|
|
</screen>
|
|
|
|
This actually executes as
|
|
<screen>
|
|
SELECT substr(CAST (1234 AS text), 3);
|
|
</screen>
|
|
This automatic transformation can succeed because there is an
|
|
implicitly invocable cast from <type>integer</type> to
|
|
<type>text</type>.
|
|
</para>
|
|
</example>
|
|
|
|
</sect1>
|
|
|
|
<sect1 id="typeconv-query">
|
|
<title>Value Storage</title>
|
|
|
|
<para>
|
|
Values to be inserted into a table are converted to the destination
|
|
column's data type according to the
|
|
following steps.
|
|
</para>
|
|
|
|
<procedure>
|
|
<title>Value Storage Type Conversion</title>
|
|
|
|
<step performance="required">
|
|
<para>
|
|
Check for an exact match with the target.
|
|
</para>
|
|
</step>
|
|
|
|
<step performance="required">
|
|
<para>
|
|
Otherwise, try to convert the expression to the target type. This will succeed
|
|
if there is a registered cast between the two types.
|
|
If the expression is an unknown-type literal, the contents of
|
|
the literal string will be fed to the input conversion routine for the target
|
|
type.
|
|
</para>
|
|
</step>
|
|
|
|
<step performance="required">
|
|
<para>
|
|
Check to see if there is a sizing cast for the target type. A sizing
|
|
cast is a cast from that type to itself. If one is found in the
|
|
<structname>pg_cast</> catalog, apply it to the expression before storing
|
|
into the destination column. The implementation function for such a cast
|
|
always takes an extra parameter of type <type>integer</type>, which receives
|
|
the destination column's declared length (actually, its
|
|
<structfield>atttypmod</> value; the interpretation of
|
|
<structfield>atttypmod</> varies for different data types). The cast function
|
|
is responsible for applying any length-dependent semantics such as size
|
|
checking or truncation.
|
|
</para>
|
|
</step>
|
|
|
|
</procedure>
|
|
|
|
<example>
|
|
<title><type>character</type> Storage Type Conversion</title>
|
|
|
|
<para>
|
|
For a target column declared as <type>character(20)</type> the following statement
|
|
ensures that the stored value is sized correctly:
|
|
|
|
<screen>
|
|
CREATE TABLE vv (v character(20));
|
|
INSERT INTO vv SELECT 'abc' || 'def';
|
|
SELECT v, length(v) FROM vv;
|
|
|
|
v | length
|
|
----------------------+--------
|
|
abcdef | 20
|
|
(1 row)
|
|
</screen>
|
|
</para>
|
|
|
|
<para>
|
|
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 converted to <type>bpchar</type> (<quote>blank-padded
|
|
char</>, the internal name of the <type>character</type> data type) to match the target
|
|
column type. (Since the types <type>text</type> and
|
|
<type>bpchar</type> are binary-compatible, this conversion does
|
|
not insert any real function call.) Finally, the sizing function
|
|
<literal>bpchar(bpchar, integer)</literal> is found in the system catalog
|
|
and applied to the operator's result and the stored column length. This
|
|
type-specific function performs the required length check and addition of
|
|
padding spaces.
|
|
</para>
|
|
</example>
|
|
</sect1>
|
|
|
|
<sect1 id="typeconv-union-case">
|
|
<title><literal>UNION</literal>, <literal>CASE</literal>, and Related Constructs</title>
|
|
|
|
<indexterm zone="typeconv-union-case">
|
|
<primary>UNION</primary>
|
|
<secondary>determination of result type</secondary>
|
|
</indexterm>
|
|
|
|
<indexterm zone="typeconv-union-case">
|
|
<primary>CASE</primary>
|
|
<secondary>determination of result type</secondary>
|
|
</indexterm>
|
|
|
|
<indexterm zone="typeconv-union-case">
|
|
<primary>ARRAY</primary>
|
|
<secondary>determination of result type</secondary>
|
|
</indexterm>
|
|
|
|
<indexterm zone="typeconv-union-case">
|
|
<primary>VALUES</primary>
|
|
<secondary>determination of result type</secondary>
|
|
</indexterm>
|
|
|
|
<indexterm zone="typeconv-union-case">
|
|
<primary>GREATEST</primary>
|
|
<secondary>determination of result type</secondary>
|
|
</indexterm>
|
|
|
|
<indexterm zone="typeconv-union-case">
|
|
<primary>LEAST</primary>
|
|
<secondary>determination of result type</secondary>
|
|
</indexterm>
|
|
|
|
<para>
|
|
SQL <literal>UNION</> 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 query. The
|
|
<literal>INTERSECT</> and <literal>EXCEPT</> constructs resolve
|
|
dissimilar types in the same way as <literal>UNION</>. The
|
|
<literal>CASE</>, <literal>ARRAY</>, <literal>VALUES</>,
|
|
<function>GREATEST</> and <function>LEAST</> constructs use the identical
|
|
algorithm to match up their component expressions and select a result
|
|
data type.
|
|
</para>
|
|
|
|
<procedure>
|
|
<title>Type Resolution for <literal>UNION</literal>, <literal>CASE</literal>,
|
|
and Related Constructs</title>
|
|
|
|
<step performance="required">
|
|
<para>
|
|
If all inputs are of type <type>unknown</type>, resolve as type
|
|
<type>text</type> (the preferred type of the string category).
|
|
Otherwise, ignore the <type>unknown</type> inputs while choosing the result type.
|
|
</para>
|
|
</step>
|
|
|
|
<step performance="required">
|
|
<para>
|
|
If the non-unknown inputs are not all of the same type category, fail.
|
|
</para>
|
|
</step>
|
|
|
|
<step performance="required">
|
|
<para>
|
|
Choose the first non-unknown input type which is a preferred type in
|
|
that category or allows all the non-unknown inputs to be implicitly
|
|
converted to it.
|
|
</para>
|
|
</step>
|
|
|
|
<step performance="required">
|
|
<para>
|
|
Convert all inputs to the selected type.
|
|
</para>
|
|
</step>
|
|
</procedure>
|
|
|
|
<para>
|
|
Some examples follow.
|
|
</para>
|
|
|
|
<example>
|
|
<title>Type Resolution with Underspecified Types in a Union</title>
|
|
|
|
<para>
|
|
<screen>
|
|
SELECT text 'a' AS "text" UNION SELECT 'b';
|
|
|
|
text
|
|
------
|
|
a
|
|
b
|
|
(2 rows)
|
|
</screen>
|
|
Here, the unknown-type literal <literal>'b'</literal> will be resolved as type <type>text</type>.
|
|
</para>
|
|
</example>
|
|
|
|
<example>
|
|
<title>Type Resolution in a Simple Union</title>
|
|
|
|
<para>
|
|
<screen>
|
|
SELECT 1.2 AS "numeric" UNION SELECT 1;
|
|
|
|
numeric
|
|
---------
|
|
1
|
|
1.2
|
|
(2 rows)
|
|
</screen>
|
|
The literal <literal>1.2</> is of type <type>numeric</>,
|
|
and the <type>integer</type> value <literal>1</> can be cast implicitly to
|
|
<type>numeric</>, so that type is used.
|
|
</para>
|
|
</example>
|
|
|
|
<example>
|
|
<title>Type Resolution in a Transposed Union</title>
|
|
|
|
<para>
|
|
<screen>
|
|
SELECT 1 AS "real" UNION SELECT CAST('2.2' AS REAL);
|
|
|
|
real
|
|
------
|
|
1
|
|
2.2
|
|
(2 rows)
|
|
</screen>
|
|
Here, since type <type>real</> cannot be implicitly cast to <type>integer</>,
|
|
but <type>integer</> can be implicitly cast to <type>real</>, the union
|
|
result type is resolved as <type>real</>.
|
|
</para>
|
|
</example>
|
|
|
|
</sect1>
|
|
</chapter>
|