1.2. Value Expressions

1.2.1. Column References

A column can be referenced in the form

correlation.columnname

or

correlation.columnname[subscript]

(Here, the brackets [ ] are meant to appear literally.)

correlation is the name of a table (possibly qualified), or an alias for a table defined by means of a FROM clause, or the key words NEW or OLD. (NEW and OLD can only appear in rewrite rules, while other correlation names can be used in any SQL statement.) The correlation name and separating dot may be omitted if the column name is unique across all the tables being used in the current query. (See also Chapter 4.)

If column is of an array type, then the optional subscript selects a specific element or elements in the array. If no subscript is provided, then the whole array is selected. (See Section 5.12 for more about arrays.)

1.2.2. Positional Parameters

A positional parameter reference is used to indicate a parameter that is supplied externally to an SQL statement. Parameters are used in SQL function definitions and in prepared queries. The form of a parameter reference is:

$number

For example, consider the definition of a function, dept, as

CREATE FUNCTION dept(text) RETURNS dept
    AS 'SELECT * FROM dept WHERE name = $1'
    LANGUAGE SQL;

Here the $1 will be replaced by the first function argument when the function is invoked.

1.2.3. Operator Invocations

There are three possible syntaxes for an operator invocation:

OPERATOR(schema.operatorname)

Which particular operators exist and whether they are unary or binary depends on what operators have been defined by the system or the user. Chapter 6 describes the built-in operators.

1.2.4. Function Calls

The syntax for a function call is the name of a function (possibly qualified with a schema name), followed by its argument list enclosed in parentheses:

function ([expression [, expression ... ]] )

For example, the following computes the square root of 2:

sqrt(2)

The list of built-in functions is in Chapter 6. Other functions may be added by the user.

1.2.5. Aggregate Expressions

An aggregate expression represents the application of an aggregate function across the rows selected by a query. An aggregate function reduces multiple inputs to a single output value, such as the sum or average of the inputs. The syntax of an aggregate expression is one of the following:

aggregate_name (expression)
aggregate_name (ALL expression)
aggregate_name (DISTINCT expression)
aggregate_name ( * )

where aggregate_name is a previously defined aggregate (possibly a qualified name), and expression is any value expression that does not itself contain an aggregate expression.

The first form of aggregate expression invokes the aggregate across all input rows for which the given expression yields a non-null value. (Actually, it is up to the aggregate function whether to ignore null values or not --- but all the standard ones do.) The second form is the same as the first, since ALL is the default. The third form invokes the aggregate for all distinct non-null values of the expression found in the input rows. The last form invokes the aggregate once for each input row regardless of null or non-null values; since no particular input value is specified, it is generally only useful for the count() aggregate function.

For example, count(*) yields the total number of input rows; count(f1) yields the number of input rows in which f1 is non-null; count(distinct f1) yields the number of distinct non-null values of f1.

The predefined aggregate functions are described in Section 6.14. Other aggregate functions may be added by the user.

1.2.6. Type Casts

A type cast specifies a conversion from one data type to another. PostgreSQL accepts two equivalent syntaxes for type casts:

CAST ( expression AS type )
expression::type

The CAST syntax conforms to SQL; the syntax with :: is historical PostgreSQL usage.

When a cast is applied to a value expression of a known type, it represents a run-time type conversion. The cast will succeed only if a suitable type conversion function is available. Notice that this is subtly different from the use of casts with constants, as shown in Section 1.1.2.4. A cast applied to an unadorned string literal represents the initial assignment of a type to a literal constant value, and so it will succeed for any type (if the contents of the string literal are acceptable input syntax for the data type).

An explicit type cast may usually be omitted if there is no ambiguity as to the type that a value expression must produce (for example, when it is assigned to a table column); the system will automatically apply a type cast in such cases. However, automatic casting is only done for casts that are marked "OK to apply implicitly" in the system catalogs. Other casts must be invoked with explicit casting syntax. This restriction is intended to prevent surprising conversions from being applied silently.

It is also possible to specify a type cast using a function-like syntax:

typename ( expression )

However, this only works for types whose names are also valid as function names. For example, double precision can't be used this way, but the equivalent float8 can. Also, the names interval, time, and timestamp can only be used in this fashion if they are double-quoted, because of syntactic conflicts. Therefore, the use of the function-like cast syntax leads to inconsistencies and should probably be avoided in new applications. (The function-like syntax is in fact just a function call. When one of the two standard cast syntaxes is used to do a run-time conversion, it will internally invoke a registered function to perform the conversion. By convention, these conversion functions have the same name as their output type, but this is not something that a portable application should rely on.)

1.2.7. Scalar Subqueries

A scalar subquery is an ordinary SELECT query in parentheses that returns exactly one row with one column. (See Chapter 4 for information about writing queries.) The SELECT query is executed and the single returned value is used in the surrounding value expression. It is an error to use a query that returns more than one row or more than one column as a scalar subquery. (But if, during a particular execution, the subquery returns no rows, there is no error; the scalar result is taken to be null.) The subquery can refer to variables from the surrounding query, which will act as constants during any one evaluation of the subquery. See also Section 6.15.

For example, the following finds the largest city population in each state:

SELECT name, (SELECT max(pop) FROM cities WHERE cities.state = states.name)
    FROM states;

1.2.8. Expression Evaluation

The order of evaluation of subexpressions is not defined. In particular, the inputs of an operator or function are not necessarily evaluated left-to-right or in any other fixed order.

Furthermore, if the result of an expression can be determined by evaluating only some parts of it, then other subexpressions might not be evaluated at all. For instance, if one wrote

SELECT true OR somefunc();

then somefunc() would (probably) not be called at all. The same would be the case if one wrote

SELECT somefunc() OR true;

Note that this is not the same as the left-to-right "short-circuiting" of Boolean operators that is found in some programming languages.

As a consequence, it is unwise to use functions with side effects as part of complex expressions. It is particularly dangerous to rely on side effects or evaluation order in WHERE and HAVING clauses, since those clauses are extensively reprocessed as part of developing an execution plan. Boolean expressions (AND/OR/NOT combinations) in those clauses may be reorganized in any manner allowed by the laws of Boolean algebra.

When it is essential to force evaluation order, a CASE construct (see Section 6.12) may be used. For example, this is an untrustworthy way of trying to avoid division by zero in a WHERE clause:

SELECT ... WHERE x <> 0 AND y/x > 1.5;

But this is safe:

SELECT ... WHERE CASE WHEN x <> 0 THEN y/x > 1.5 ELSE false END;

A CASE construct used in this fashion will defeat optimization attempts, so it should only be done when necessary.