PostgreSQL 7.4.11 Documentation
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# 10.2. Operators

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 Section 4.1.6 for more information.

Operator Type Resolution

1. Select the operators to be considered from the `pg_operator` 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 Section 5.8.3). If a qualified operator name was given, only operators in the specified schema are considered.

   1. 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.

2. 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.

   1. 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. Other cases involving `unknown` will never find a match at this step.

3. Look for the best match.

   1. 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.

   2. 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.

   3. 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.

   4. 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 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.

   5. If only one candidate remains, use it. If no candidate or more than one candidate remains, then fail.

Some examples follow.

Example 10-1. Exponentiation Operator Type Resolution

There is only one exponentiation operator defined in the catalog, and it takes arguments of type `double precision`. The scanner assigns an initial type of `integer` to both arguments of this query expression:

    SELECT 2 ^ 3 AS "exp";

     exp
    -----
       8
    (1 row)

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

    SELECT CAST(2 AS double precision) ^ CAST(3 AS double precision) AS "exp";

Example 10-2. String Concatenation Operator Type Resolution

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.

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 of type `text`.

Here is a concatenation on 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 literals to.

Example 10-3. Absolute-Value and Factorial 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 a non-numeric input:

    SELECT @ '-4.5' AS "abs";
     abs
    -----
     4.5
    (1 row)

Here the system has performed an implicit conversion from `text` to `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 postfix operator `!` (factorial) is defined only for integer data types, not for `float8`. So, if we try a similar case with `!`, we get:

    SELECT '20' ! AS "factorial";

    ERROR:  operator is not unique: "unknown" !
    HINT:  Could not choose a best candidate operator. You may need to add explicit
    type casts.

This happens because the system can't 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 "factorial";

          factorial
    ---------------------
     2432902008176640000
    (1 row)

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