The specific operator that is referenced by an operator expression is determined using the following procedure. Note that this procedure is indirectly affected by the precedence of the operators involved, since that will determine which sub-expressions are taken to be the inputs of which operators. See Section 4.1.6 for more information.
Operator Type Resolution
Select the operators to be considered from the
pg_operator
system catalog. If a non-schema-qualified
operator name was used (the usual case), the operators
considered are those with the matching name and argument count that are
visible in the current search path (see Section 5.9.3).
If a qualified operator name was given, only operators in the specified
schema are considered.
If the search path finds multiple operators with identical argument types, only the one appearing earliest in the path is considered. Operators with different argument types are considered on an equal footing regardless of search path position.
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. Lack of an exact match creates a security hazard when calling, via qualified name [8] (not typical), any operator found in a schema that permits untrusted users to create objects. In such situations, cast arguments to force an exact match.
If one argument of a binary operator invocation is of the unknown
type,
then assume it is the same type as the other argument for this check.
Invocations involving two unknown
inputs, or a unary operator
with an unknown
input, will never find a match at this step.
If one argument of a binary operator invocation is of the unknown
type and the other is of a domain type, next check to see if there is an
operator accepting exactly the domain's base type on both sides; if so, use it.
Look for the best match.
Discard candidate operators for which the input types do not match
and cannot be converted (using an implicit conversion) to match.
unknown
literals are
assumed to be convertible to anything for this purpose. If only one
candidate remains, use it; else continue to the next step.
If any input argument is of a domain type, treat it as being of the domain's base type for all subsequent steps. This ensures that domains act like their base types for purposes of ambiguous-operator resolution.
Run through all candidates and keep those with the most exact matches on input types. Keep all candidates if none have exact matches. If only one candidate remains, use it; else continue to the next step.
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.
If any input arguments are unknown
, check the type
categories accepted at those argument positions by the remaining
candidates. At each position, select the string
category
if any
candidate accepts that category. (This bias towards string is appropriate
since an unknown-type literal looks 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 in that category,
discard candidates that accept non-preferred types for that argument.
Keep all candidates if none survive these tests.
If only one candidate remains, use it; else continue to the next step.
If there are both unknown
and known-type arguments, and all
the known-type arguments have the same type, assume that the
unknown
arguments are also of that type, and check which
candidates can accept that type at the unknown
-argument
positions. If exactly one candidate passes this test, use it.
Otherwise, fail.
Some examples follow.
Example 10.1. Square Root Operator Type Resolution
There is only one square root operator (prefix |/
)
defined in the standard catalog, and it takes an argument of type
double precision
.
The scanner assigns an initial type of integer
to the argument
in this query expression:
SELECT |/ 40 AS "square root of 40"; square root of 40 ------------------- 6.324555320336759 (1 row)
So the parser does a type conversion on the operand and the query is equivalent to:
SELECT |/ CAST(40 AS double precision) AS "square root of 40";
Example 10.2. String Concatenation Operator Type Resolution
A string-like syntax is used for working with string types and for working with complex extension types. Strings with unspecified type are matched with likely operator candidates.
An example with one unspecified argument:
SELECT text 'abc' || 'def' AS "text and unknown"; text and unknown ------------------ abcdef (1 row)
In this case the parser looks to see if there is an operator taking text
for both arguments. Since there is, it assumes that the second argument should
be interpreted as type text
.
Here is a concatenation of two values of unspecified types:
SELECT 'abc' || 'def' AS "unspecified"; unspecified ------------- abcdef (1 row)
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, text
, is used as the specific
type to resolve the unknown-type literals as.
Example 10.3. Absolute-Value and Negation Operator Type Resolution
The PostgreSQL operator catalog has several
entries for the prefix operator @
, all of which implement
absolute-value operations for various numeric data types. One of these
entries is for type float8
, which is the preferred type in
the numeric category. Therefore, PostgreSQL
will use that entry when faced with an unknown
input:
SELECT @ '-4.5' AS "abs"; abs ----- 4.5 (1 row)
Here the system has implicitly resolved the unknown-type literal as type
float8
before applying the chosen operator. We can verify that
float8
and not some other type was used:
SELECT @ '-4.5e500' AS "abs"; ERROR: "-4.5e500" is out of range for type double precision
On the other hand, the prefix operator ~
(bitwise negation)
is defined only for integer data types, not for float8
. So, if we
try a similar case with ~
, we get:
SELECT ~ '20' AS "negation"; ERROR: operator is not unique: ~ "unknown" HINT: Could not choose a best candidate operator. You might need to add explicit type casts.
This happens because the system cannot decide which of the several
possible ~
operators should be preferred. We can help
it out with an explicit cast:
SELECT ~ CAST('20' AS int8) AS "negation"; negation ---------- -21 (1 row)
Example 10.4. Array Inclusion Operator Type Resolution
Here is another example of resolving an operator with one known and one unknown input:
SELECT array[1,2] <@ '{1,2,3}' as "is subset"; is subset ----------- t (1 row)
The PostgreSQL operator catalog has several
entries for the infix operator <@
, but the only two that
could possibly accept an integer array on the left-hand side are
array inclusion (anyarray
<@
anyarray
)
and range inclusion (anyelement
<@
anyrange
).
Since none of these polymorphic pseudo-types (see Section 8.21) are considered preferred, the parser cannot
resolve the ambiguity on that basis.
However, Step 3.f tells
it to assume that the unknown-type literal is of the same type as the other
input, that is, integer array. Now only one of the two operators can match,
so array inclusion is selected. (Had range inclusion been selected, we would
have gotten an error, because the string does not have the right format to be
a range literal.)
Example 10.5. Custom Operator on a Domain Type
Users sometimes try to declare operators applying just to a domain type. This is possible but is not nearly as useful as it might seem, because the operator resolution rules are designed to select operators applying to the domain's base type. As an example consider
CREATE DOMAIN mytext AS text CHECK(...); CREATE FUNCTION mytext_eq_text (mytext, text) RETURNS boolean AS ...; CREATE OPERATOR = (procedure=mytext_eq_text, leftarg=mytext, rightarg=text); CREATE TABLE mytable (val mytext); SELECT * FROM mytable WHERE val = 'foo';
This query will not use the custom operator. The parser will first see if
there is a mytext
=
mytext
operator
(Step 2.a), which there is not;
then it will consider the domain's base type text
, and see if
there is a text
=
text
operator
(Step 2.b), which there is;
so it resolves the unknown
-type literal as text
and
uses the text
=
text
operator.
The only way to get the custom operator to be used is to explicitly cast
the literal:
SELECT * FROM mytable WHERE val = text 'foo';
so that the mytext
=
text
operator is found
immediately according to the exact-match rule. If the best-match rules
are reached, they actively discriminate against operators on domain types.
If they did not, such an operator would create too many ambiguous-operator
failures, because the casting rules always consider a domain as castable
to or from its base type, and so the domain operator would be considered
usable in all the same cases as a similarly-named operator on the base type.
[8] The hazard does not arise with a non-schema-qualified name, because a search path containing schemas that permit untrusted users to create objects is not a secure schema usage pattern.