7.1.2.5.1. User-Defined Functions
PostgreSQL provides four kinds of functions:
query language functions (functions written in SQL) (xfunc-sql)
procedural language functions (functions written in, for example, PL/pgSQL or PL/Tcl) (xfunc-pl)
internal functions (xfunc-internal)
C-language functions (xfunc-c)
Every kind of function can take base types, composite types, or combinations of these as arguments (parameters). In addition, every kind of function can return a base type or a composite type. Functions can also be defined to return sets of base or composite values.
Many kinds of functions can take or return certain pseudo-types (such as polymorphic types), but the available facilities vary. Consult the description of each kind of function for more details.
It’s easiest to define SQL functions, so we’ll start by discussing those. Most of the concepts presented for SQL functions will carry over to the other types of functions.
Throughout this chapter, it can be useful to look at the reference page of the linkend=»sql-createfunction»>**CREATE FUNCTION** command to understand the examples better. Some examples from this chapter can be found in funcs.sql and funcs.c in the src/tutorial directory in the PostgreSQL source distribution.
7.1.2.5.2. User-Defined Procedures
A procedure is a database object similar to a function. The key differences are:
Procedures are defined with the linkend=»sql-createprocedure»>**CREATE PROCEDURE** command, not CREATE FUNCTION.
Procedures do not return a function value; hence CREATE PROCEDURE lacks a RETURNS clause. However, procedures can instead return data to their callers via output parameters.
While a function is called as part of a query or DML command, a procedure is called in isolation using the linkend=»sql-call»>**CALL** command.
A procedure can commit or roll back transactions during its execution (then automatically beginning a new transaction), so long as the invoking CALL command is not part of an explicit transaction block. A function cannot do that.
Certain function attributes, such as strictness, don’t apply to procedures. Those attributes control how the function is used in a query, which isn’t relevant to procedures.
The explanations in the following sections about how to define user-defined functions apply to procedures as well, except for the points made above.
Collectively, functions and procedures are also known as routines There are commands such as linkend=»sql-alterroutine»>**ALTER ROUTINE** and linkend=»sql-droproutine»>**DROP ROUTINE** that can operate on functions and procedures without having to know which kind it is. Note, however, that there is no CREATE ROUTINE command.
7.1.2.5.3. Query Language (SQL) Functions
SQL functions execute an arbitrary list of SQL statements, returning the result of the last query in the list. In the simple (non-set) case, the first row of the last query’s result will be returned. (Bear in mind that the first row of a multirow result is not well-defined unless you use ORDER BY.) If the last query happens to return no rows at all, the null value will be returned.
Alternatively, an SQL function can be declared to return a set (that is, multiple rows) by specifying the function’s return type as SETOF sometype, or equivalently by declaring it as RETURNS TABLE(columns). In this case all rows of the last query’s result are returned. Further details appear below.
The body of an SQL function must be a list of SQL statements separated by semicolons. A semicolon after the last statement is optional. Unless the function is declared to return void, the last statement must be a SELECT, or an INSERT, UPDATE, or DELETE that has a RETURNING clause.
Any collection of commands in the SQL language can be packaged together and defined as a function. Besides SELECT queries, the commands can include data modification queries (INSERT, UPDATE, and DELETE), as well as other SQL commands. (You cannot use transaction control commands, e.g., COMMIT, SAVEPOINT, and some utility commands, e.g., VACUUM, in SQL functions.) However, the final command must be a SELECT or have a RETURNING clause that returns whatever is specified as the function’s return type. Alternatively, if you want to define an SQL function that performs actions but has no useful value to return, you can define it as returning void. For example, this function removes rows with negative salaries from the emp table:
CREATE FUNCTION clean_emp() RETURNS void AS '
DELETE FROM emp
WHERE salary < 0;
' LANGUAGE SQL;
SELECT clean_emp();
clean_emp
-----------
(1 row)
You can also write this as a procedure, thus avoiding the issue of the return type. For example:
CREATE PROCEDURE clean_emp() AS '
DELETE FROM emp
WHERE salary < 0;
' LANGUAGE SQL;
CALL clean_emp();
In simple cases like this, the difference between a function returning
void and a procedure is mostly stylistic. However, procedures offer additional functionality such as transaction control that is not available in functions. Also, procedures are SQL standard whereas returning void is a PostgreSQL extension.
Примечание
The entire body of an SQL function is parsed before any of it is executed. While an SQL function can contain commands that alter the system catalogs (e.g., CREATE TABLE), the effects of such commands will not be visible during parse analysis of later commands in the function. Thus, for example, CREATE TABLE foo (…); INSERT INTO foo VALUES(…); will not work as desired if packaged up into a single SQL function, since foo won’t exist yet when the INSERT command is parsed. It’s recommended to use PL/pgSQL instead of an SQL function in this type of situation.
The syntax of the CREATE FUNCTION command requires the function body to be written as a string constant. It is usually most convenient to use dollar quoting (see sql-syntax-dollar-quoting) for the string constant. If you choose to use regular single-quoted string constant syntax, you must double single quote marks (“) and backslashes (****) (assuming escape string syntax) in the body of the function (see sql-syntax-strings).
7.1.2.5.3.1. Arguments for SQL Functions
Arguments of an SQL function can be referenced in the function body using either names or numbers. Examples of both methods appear below.
To use a name, declare the function argument as having a name, and then just write that name in the function body. If the argument name is the same as any column name in the current SQL command within the function, the column name will take precedence. To override this, qualify the argument name with the name of the function itself, that is function_name.argument_name. (If this would conflict with a qualified column name, again the column name wins. You can avoid the ambiguity by choosing a different alias for the table within the SQL command.)
In the older numeric approach, arguments are referenced using the syntax $n: $1 refers to the first input argument, $2 to the second, and so on. This will work whether or not the particular argument was declared with a name.
If an argument is of a composite type, then the dot notation, e.g., argname.fieldname or $1.fieldname, can be used to access attributes of the argument. Again, you might need to qualify the argument’s name with the function name to make the form with an argument name unambiguous.
SQL function arguments can only be used as data values, not as identifiers. Thus for example this is reasonable:
INSERT INTO mytable VALUES ($1);
but this will not work:
INSERT INTO $1 VALUES (42);
Примечание
The ability to use names to reference SQL function arguments was added in PostgreSQL 9.2. Functions to be used in older servers must use the $n notation.
7.1.2.5.3.2. SQL Functions on Base Types
The simplest possible SQL function has no arguments and simply returns a base type, such as integer:
CREATE FUNCTION one() RETURNS integer AS $$
SELECT 1 AS result;
$$ LANGUAGE SQL;
-- Alternative syntax for string literal:
CREATE FUNCTION one() RETURNS integer AS '
SELECT 1 AS result;
' LANGUAGE SQL;
SELECT one();
one
-----
1
Notice that we defined a column alias within the function body for the result of the function (with the name result), but this column alias is not visible outside the function. Hence, the result is labeled one instead of result.
It is almost as easy to define SQL functions that take base types as arguments:
CREATE FUNCTION add_em(x integer, y integer) RETURNS integer AS $$
SELECT x + y;
$$ LANGUAGE SQL;
SELECT add_em(1, 2) AS answer;
answer
--------
3
Alternatively, we could dispense with names for the arguments and use numbers:
CREATE FUNCTION add_em(integer, integer) RETURNS integer AS $$
SELECT $1 + $2;
$$ LANGUAGE SQL;
SELECT add_em(1, 2) AS answer;
answer
--------
3
Here is a more useful function, which might be used to debit a bank account:
CREATE FUNCTION tf1 (accountno integer, debit numeric) RETURNS numeric AS $$
UPDATE bank
SET balance = balance - debit
WHERE accountno = tf1.accountno;
SELECT 1;
$$ LANGUAGE SQL;
A user could execute this function to debit account 17 by $100.00 as follows:
SELECT tf1(17, 100.0);
In this example, we chose the name accountno for the first argument, but this is the same as the name of a column in the bank table. Within the UPDATE command, accountno refers to the column bank.accountno, so tf1.accountno must be used to refer to the argument. We could of course avoid this by using a different name for the argument.
In practice one would probably like a more useful result from the function than a constant 1, so a more likely definition is:
CREATE FUNCTION tf1 (accountno integer, debit numeric) RETURNS numeric AS $$
UPDATE bank
SET balance = balance - debit
WHERE accountno = tf1.accountno;
SELECT balance FROM bank WHERE accountno = tf1.accountno;
$$ LANGUAGE SQL;
which adjusts the balance and returns the new balance. The same thing could be done in one command using RETURNING:
CREATE FUNCTION tf1 (accountno integer, debit numeric) RETURNS numeric AS $$
UPDATE bank
SET balance = balance - debit
WHERE accountno = tf1.accountno
RETURNING balance;
$$ LANGUAGE SQL;
If the final SELECT or RETURNING clause in an SQL function does not return exactly the function’s declared result type, PostgreSQL will automatically cast the value to the required type, if that is possible with an implicit or assignment cast. Otherwise, you must write an explicit cast. For example, suppose we wanted the previous add_em function to return type float8 instead. It’s sufficient to write
CREATE FUNCTION add_em(integer, integer) RETURNS float8 AS $$
SELECT $1 + $2;
$$ LANGUAGE SQL;
since the integer sum can be implicitly cast to float8. (See typeconv or sql-createcast for more about casts.)
7.1.2.5.3.3. SQL Functions on Composite Types
When writing functions with arguments of composite types, we must not only specify which argument we want but also the desired attribute (field) of that argument. For example, suppose that emp is a table containing employee data, and therefore also the name of the composite type of each row of the table. Here is a function double_salary that computes what someone’s salary would be if it were doubled:
CREATE TABLE emp (
name text,
salary numeric,
age integer,
cubicle point
);
INSERT INTO emp VALUES ('Bill', 4200, 45, '(2,1)');
CREATE FUNCTION double_salary(emp) RETURNS numeric AS $$
SELECT $1.salary * 2 AS salary;
$$ LANGUAGE SQL;
SELECT name, double_salary(emp.*) AS dream
FROM emp
WHERE emp.cubicle ~= point '(2,1)';
name | dream
------+-------
Bill | 8400
Notice the use of the syntax $1.salary to select one field of the argument row value. Also notice how the calling SELECT command uses table_name**.*** to select the entire current row of a table as a composite value. The table row can alternatively be referenced using just the table name, like this:
SELECT name, double_salary(emp) AS dream
FROM emp
WHERE emp.cubicle ~= point '(2,1)';
but this usage is deprecated since it's easy to get confused.
(See rowtypes-usage for details about these two notations for the composite value of a table row.)
Sometimes it is handy to construct a composite argument value on-the-fly. This can be done with the ROW construct. For example, we could adjust the data being passed to the function:
SELECT name, double_salary(ROW(name, salary*1.1, age, cubicle)) AS dream
FROM emp;
It is also possible to build a function that returns a composite type. This is an example of a function that returns a single emp row:
CREATE FUNCTION new_emp() RETURNS emp AS $$
SELECT text 'None' AS name,
1000.0 AS salary,
25 AS age,
point '(2,2)' AS cubicle;
$$ LANGUAGE SQL;
In this example we have specified each of the attributes with a constant value, but any computation could have been substituted for these constants.
Note two important things about defining the function:
The select list order in the query must be exactly the same as that in which the columns appear in the composite type. (Naming the columns, as we did above, is irrelevant to the system.)
We must ensure each expression’s type can be cast to that of the corresponding column of the composite type. Otherwise we’ll get errors like this:
ERROR: return type mismatch in function declared to return emp DETAIL: Final statement returns text instead of point at column 4. As with the base-type case, the system will not insert explicit
casts automatically, only implicit or assignment casts.
A different way to define the same function is:
CREATE FUNCTION new_emp() RETURNS emp AS $$
SELECT ROW('None', 1000.0, 25, '(2,2)')::emp;
$$ LANGUAGE SQL;
Here we wrote a SELECT that returns just a single column of the correct composite type. This isn’t really better in this situation, but it is a handy alternative in some cases — for example, if we need to compute the result by calling another function that returns the desired composite value. Another example is that if we are trying to write a function that returns a domain over composite, rather than a plain composite type, it is always necessary to write it as returning a single column, since there is no way to cause a coercion of the whole row result.
We could call this function directly either by using it in a value expression:
SELECT new_emp();
new_emp
--------------------------
(None,1000.0,25,"(2,2)")
or by calling it as a table function:
SELECT * FROM new_emp();
name | salary | age | cubicle
------+--------+-----+---------
None | 1000.0 | 25 | (2,2)
The second way is described more fully in xfunc-sql-table-functions.
When you use a function that returns a composite type, you might want only one field (attribute) from its result. You can do that with syntax like this:
SELECT (new_emp()).name;
name
------
None
The extra parentheses are needed to keep the parser from getting confused. If you try to do it without them, you get something like this:
SELECT new_emp().name;
ERROR: syntax error at or near "."
LINE 1: SELECT new_emp().name;
^
Another option is to use functional notation for extracting an attribute:
SELECT name(new_emp());
name
------
None
As explained in rowtypes-usage, the field notation and functional notation are equivalent.
Another way to use a function returning a composite type is to pass the result to another function that accepts the correct row type as input:
CREATE FUNCTION getname(emp) RETURNS text AS $$
SELECT $1.name;
$$ LANGUAGE SQL;
SELECT getname(new_emp());
getname
---------
None
(1 row)
7.1.2.5.3.4. SQL Functions with Output Parameters
An alternative way of describing a function’s results is to define it with output parameters, as in this example:
CREATE FUNCTION add_em (IN x int, IN y int, OUT sum int)
AS 'SELECT x + y'
LANGUAGE SQL;
SELECT add_em(3,7);
add_em
--------
10
(1 row)
This is not essentially different from the version of add_em shown in xfunc-sql-base-functions. The real value of output parameters is that they provide a convenient way of defining functions that return several columns. For example,
CREATE FUNCTION sum_n_product (x int, y int, OUT sum int, OUT product int)
AS 'SELECT x + y, x * y'
LANGUAGE SQL;
SELECT * FROM sum_n_product(11,42);
sum | product
-----+---------
53 | 462
(1 row)
What has essentially happened here is that we have created an anonymous composite type for the result of the function. The above example has the same end result as
CREATE TYPE sum_prod AS (sum int, product int);
CREATE FUNCTION sum_n_product (int, int) RETURNS sum_prod
AS 'SELECT $1 + $2, $1 * $2'
LANGUAGE SQL;
but not having to bother with the separate composite type definition is often handy. Notice that the names attached to the output parameters are not just decoration, but determine the column names of the anonymous composite type. (If you omit a name for an output parameter, the system will choose a name on its own.)
Notice that output parameters are not included in the calling argument list when invoking such a function from SQL. This is because PostgreSQL considers only the input parameters to define the function’s calling signature. That means also that only the input parameters matter when referencing the function for purposes such as dropping it. We could drop the above function with either of
DROP FUNCTION sum_n_product (x int, y int, OUT sum int, OUT product int);
DROP FUNCTION sum_n_product (int, int);
Parameters can be marked as IN (the default), OUT, INOUT, or VARIADIC. An INOUT parameter serves as both an input parameter (part of the calling argument list) and an output parameter (part of the result record type). VARIADIC parameters are input parameters, but are treated specially as described below.
7.1.2.5.3.5. SQL Procedures with Output Parameters
Output parameters are also supported in procedures, but they work a bit differently from functions. In CALL commands, output parameters must be included in the argument list. For example, the bank account debiting routine from earlier could be written like this:
CREATE PROCEDURE tp1 (accountno integer, debit numeric, OUT new_balance numeric) AS $$
UPDATE bank
SET balance = balance - debit
WHERE accountno = tp1.accountno
RETURNING balance;
$$ LANGUAGE SQL;
To call this procedure, an argument matching the **OUT**
parameter must be included. It’s customary to write NULL:
CALL tp1(17, 100.0, NULL);
If you write something else, it must be an expression that is implicitly
coercible to the declared type of the parameter, just as for input parameters. Note however that such an expression will not be evaluated.
When calling a procedure from PL/pgSQL, instead of writing NULL you must write a variable that will receive the procedure’s output. See plpgsql-statements-calling-procedure for details.
7.1.2.5.3.6. SQL Functions with Variable Numbers of Arguments
SQL functions can be declared to accept variable numbers of arguments, so long as all the optional arguments are of the same data type. The optional arguments will be passed to the function as an array. The function is declared by marking the last parameter as VARIADIC; this parameter must be declared as being of an array type. For example:
CREATE FUNCTION mleast(VARIADIC arr numeric[]) RETURNS numeric AS $$
SELECT min($1[i]) FROM generate_subscripts($1, 1) g(i);
$$ LANGUAGE SQL;
SELECT mleast(10, -1, 5, 4.4);
mleast
--------
-1
(1 row)
Effectively, all the actual arguments at or beyond the VARIADIC position are gathered up into a one-dimensional array, as if you had written
SELECT mleast(ARRAY[10, -1, 5, 4.4]); -- doesn't work
You can’t actually write that, though — or at least, it will not match this function definition. A parameter marked VARIADIC matches one or more occurrences of its element type, not of its own type.
Sometimes it is useful to be able to pass an already-constructed array to a variadic function; this is particularly handy when one variadic function wants to pass on its array parameter to another one. Also, this is the only secure way to call a variadic function found in a schema that permits untrusted users to create objects; see typeconv-func. You can do this by specifying VARIADIC in the call:
SELECT mleast(VARIADIC ARRAY[10, -1, 5, 4.4]);
This prevents expansion of the function’s variadic parameter into its element type, thereby allowing the array argument value to match normally. VARIADIC can only be attached to the last actual argument of a function call.
Specifying VARIADIC in the call is also the only way to pass an empty array to a variadic function, for example:
SELECT mleast(VARIADIC ARRAY[]::numeric[]);
Simply writing SELECT mleast() does not work because a variadic parameter must match at least one actual argument. (You could define a second function also named mleast, with no parameters, if you wanted to allow such calls.)
The array element parameters generated from a variadic parameter are treated as not having any names of their own. This means it is not possible to call a variadic function using named arguments (sql-syntax-calling-funcs), except when you specify VARIADIC. For example, this will work:
SELECT mleast(VARIADIC arr => ARRAY[10, -1, 5, 4.4]);
but not these:
SELECT mleast(arr => 10);
SELECT mleast(arr => ARRAY[10, -1, 5, 4.4]);
7.1.2.5.3.7. SQL Functions with Default Values for Arguments
Functions can be declared with default values for some or all input arguments. The default values are inserted whenever the function is called with insufficiently many actual arguments. Since arguments can only be omitted from the end of the actual argument list, all parameters after a parameter with a default value have to have default values as well. (Although the use of named argument notation could allow this restriction to be relaxed, it’s still enforced so that positional argument notation works sensibly.) Whether or not you use it, this capability creates a need for precautions when calling functions in databases where some users mistrust other users; see typeconv-func.
For example:
CREATE FUNCTION foo(a int, b int DEFAULT 2, c int DEFAULT 3)
RETURNS int
LANGUAGE SQL
AS $$
SELECT $1 + $2 + $3;
$$;
SELECT foo(10, 20, 30);
foo
-----
60
(1 row)
SELECT foo(10, 20);
foo
-----
33
(1 row)
SELECT foo(10);
foo
-----
15
(1 row)
SELECT foo(); -- fails since there is no default for the first argument
ERROR: function foo() does not exist
The **=** sign can also be used in place of the
key word DEFAULT.
7.1.2.5.3.8. SQL Functions as Table Sources
All SQL functions can be used in the FROM clause of a query, but it is particularly useful for functions returning composite types. If the function is defined to return a base type, the table function produces a one-column table. If the function is defined to return a composite type, the table function produces a column for each attribute of the composite type.
Here is an example:
CREATE TABLE foo (fooid int, foosubid int, fooname text);
INSERT INTO foo VALUES (1, 1, 'Joe');
INSERT INTO foo VALUES (1, 2, 'Ed');
INSERT INTO foo VALUES (2, 1, 'Mary');
CREATE FUNCTION getfoo(int) RETURNS foo AS $$
SELECT * FROM foo WHERE fooid = $1;
$$ LANGUAGE SQL;
SELECT *, upper(fooname) FROM getfoo(1) AS t1;
fooid | foosubid | fooname | upper
-------+----------+---------+-------
1 | 1 | Joe | JOE
(1 row)
As the example shows, we can work with the columns of the function’s result just the same as if they were columns of a regular table.
Note that we only got one row out of the function. This is because we did not use SETOF. That is described in the next section.
7.1.2.5.3.9. SQL Functions Returning Sets
When an SQL function is declared as returning SETOF sometype, the function’s final query is executed to completion, and each row it outputs is returned as an element of the result set.
This feature is normally used when calling the function in the FROM clause. In this case each row returned by the function becomes a row of the table seen by the query. For example, assume that table foo has the same contents as above, and we say:
CREATE FUNCTION getfoo(int) RETURNS SETOF foo AS $$
SELECT * FROM foo WHERE fooid = $1;
$$ LANGUAGE SQL;
SELECT * FROM getfoo(1) AS t1;
Then we would get:
fooid | foosubid | fooname
-------+----------+---------
1 | 1 | Joe
1 | 2 | Ed
(2 rows)
It is also possible to return multiple rows with the columns defined by output parameters, like this:
CREATE TABLE tab (y int, z int);
INSERT INTO tab VALUES (1, 2), (3, 4), (5, 6), (7, 8);
CREATE FUNCTION sum_n_product_with_tab (x int, OUT sum int, OUT product int)
RETURNS SETOF record
AS $$
SELECT $1 + tab.y, $1 * tab.y FROM tab;
$$ LANGUAGE SQL;
SELECT * FROM sum_n_product_with_tab(10);
sum | product
-----+---------
11 | 10
13 | 30
15 | 50
17 | 70
(4 rows)
The key point here is that you must write RETURNS SETOF record to indicate that the function returns multiple rows instead of just one. If there is only one output parameter, write that parameter’s type instead of record.
It is frequently useful to construct a query’s result by invoking a set-returning function multiple times, with the parameters for each invocation coming from successive rows of a table or subquery. The preferred way to do this is to use the LATERAL key word, which is described in queries-lateral. Here is an example using a set-returning function to enumerate elements of a tree structure:
SELECT * FROM nodes;
name | parent
-----------+--------
Top |
Child1 | Top
Child2 | Top
Child3 | Top
SubChild1 | Child1
SubChild2 | Child1
(6 rows)
CREATE FUNCTION listchildren(text) RETURNS SETOF text AS $$
SELECT name FROM nodes WHERE parent = $1
$$ LANGUAGE SQL STABLE;
SELECT * FROM listchildren('Top');
listchildren
--------------
Child1
Child2
Child3
(3 rows)
SELECT name, child FROM nodes, LATERAL listchildren(name) AS child;
name | child
--------+-----------
Top | Child1
Top | Child2
Top | Child3
Child1 | SubChild1
Child1 | SubChild2
(5 rows)
This example does not do anything that we couldn’t have done with a simple join, but in more complex calculations the option to put some of the work into a function can be quite convenient.
Functions returning sets can also be called in the select list of a query. For each row that the query generates by itself, the set-returning function is invoked, and an output row is generated for each element of the function’s result set. The previous example could also be done with queries like these:
SELECT listchildren('Top');
listchildren
--------------
Child1
Child2
Child3
(3 rows)
SELECT name, listchildren(name) FROM nodes;
name | listchildren
--------+--------------
Top | Child1
Top | Child2
Top | Child3
Child1 | SubChild1
Child1 | SubChild2
(5 rows)
In the last SELECT, notice that no output row appears for Child2, Child3, etc. This happens because listchildren returns an empty set for those arguments, so no result rows are generated. This is the same behavior as we got from an inner join to the function result when using the LATERAL syntax.
PostgreSQL’s behavior for a set-returning function in a query’s select list is almost exactly the same as if the set-returning function had been written in a LATERAL FROM-clause item instead. For example,
SELECT x, generate_series(1,5) AS g FROM tab;
is almost equivalent to
SELECT x, g FROM tab, LATERAL generate_series(1,5) AS g;
It would be exactly the same, except that in this specific example,
the planner could choose to put g on the outside of the nested-loop join, since g has no actual lateral dependency on tab. That would result in a different output row order. Set-returning functions in the select list are always evaluated as though they are on the inside of a nested-loop join with the rest of the FROM clause, so that the function(s) are run to completion before the next row from the FROM clause is considered.
If there is more than one set-returning function in the query’s select list, the behavior is similar to what you get from putting the functions into a single LATERAL ROWS FROM( … ) FROM-clause item. For each row from the underlying query, there is an output row using the first result from each function, then an output row using the second result, and so on. If some of the set-returning functions produce fewer outputs than others, null values are substituted for the missing data, so that the total number of rows emitted for one underlying row is the same as for the set-returning function that produced the most outputs. Thus the set-returning functions run in lockstep until they are all exhausted, and then execution continues with the next underlying row.
Set-returning functions can be nested in a select list, although that is not allowed in FROM-clause items. In such cases, each level of nesting is treated separately, as though it were a separate LATERAL ROWS FROM( … ) item. For example, in
SELECT srf1(srf2(x), srf3(y)), srf4(srf5(z)) FROM tab;
the set-returning functions **srf2**, **srf3**,
and srf5 would be run in lockstep for each row of tab, and then srf1 and srf4 would be applied in lockstep to each row produced by the lower functions.
Set-returning functions cannot be used within conditional-evaluation constructs, such as CASE or COALESCE. For example, consider
SELECT x, CASE WHEN x > 0 THEN generate_series(1, 5) ELSE 0 END FROM tab;
It might seem that this should produce five repetitions of input rows
that have x > 0, and a single repetition of those that do not; but actually, because generate_series(1, 5) would be run in an implicit LATERAL FROM item before the CASE expression is ever evaluated, it would produce five repetitions of every input row. To reduce confusion, such cases produce a parse-time error instead.
Примечание
If a function’s last command is INSERT, UPDATE, or DELETE with RETURNING, that command will always be executed to completion, even if the function is not declared with SETOF or the calling query does not fetch all the result rows. Any extra rows produced by the RETURNING clause are silently dropped, but the commanded table modifications still happen (and are all completed before returning from the function).
Примечание
Before PostgreSQL 10, putting more than one set-returning function in the same select list did not behave very sensibly unless they always produced equal numbers of rows. Otherwise, what you got was a number of output rows equal to the least common multiple of the numbers of rows produced by the set-returning functions. Also, nested set-returning functions did not work as described above; instead, a set-returning function could have at most one set-returning argument, and each nest of set-returning functions was run independently. Also, conditional execution (set-returning functions inside CASE etc.) was previously allowed, complicating things even more. Use of the LATERAL syntax is recommended when writing queries that need to work in older PostgreSQL versions, because that will give consistent results across different versions. If you have a query that is relying on conditional execution of a set-returning function, you may be able to fix it by moving the conditional test into a custom set-returning function. For example,
SELECT x, CASE WHEN y > 0 THEN generate_series(1, z) ELSE 5 END FROM tab;
could become
CREATE FUNCTION case_generate_series(cond bool, start int, fin int, els int)
RETURNS SETOF int AS $$
BEGIN
IF cond THEN
RETURN QUERY SELECT generate_series(start, fin);
ELSE
RETURN QUERY SELECT els;
END IF;
END$$ LANGUAGE plpgsql;
SELECT x, case_generate_series(y > 0, 1, z, 5) FROM tab;
This formulation will work the same in all versions
of PostgreSQL.
7.1.2.5.3.10. SQL Functions Returning TABLE
There is another way to declare a function as returning a set, which is to use the syntax RETURNS TABLE(columns). This is equivalent to using one or more OUT parameters plus marking the function as returning SETOF record (or SETOF a single output parameter’s type, as appropriate). This notation is specified in recent versions of the SQL standard, and thus may be more portable than using SETOF.
For example, the preceding sum-and-product example could also be done this way:
CREATE FUNCTION sum_n_product_with_tab (x int)
RETURNS TABLE(sum int, product int) AS $$
SELECT $1 + tab.y, $1 * tab.y FROM tab;
$$ LANGUAGE SQL;
It is not allowed to use explicit OUT or INOUT parameters with the RETURNS TABLE notation — you must put all the output columns in the TABLE list.
7.1.2.5.3.11. Polymorphic SQL Functions
SQL functions can be declared to accept and return the polymorphic types described in extend-types-polymorphic. Here is a polymorphic function make_array that builds up an array from two arbitrary data type elements:
CREATE FUNCTION make_array(anyelement, anyelement) RETURNS anyarray AS $$
SELECT ARRAY[$1, $2];
$$ LANGUAGE SQL;
SELECT make_array(1, 2) AS intarray, make_array('a'::text, 'b') AS textarray;
intarray | textarray
----------+-----------
{1,2} | {a,b}
(1 row)
Notice the use of the typecast „a“::text to specify that the argument is of type text. This is required if the argument is just a string literal, since otherwise it would be treated as type unknown, and array of unknown is not a valid type. Without the typecast, you will get errors like this:
ERROR: could not determine polymorphic type because input has type unknown
With make_array declared as above, you must provide two arguments that are of exactly the same data type; the system will not attempt to resolve any type differences. Thus for example this does not work:
SELECT make_array(1, 2.5) AS numericarray;
ERROR: function make_array(integer, numeric) does not exist
An alternative approach is to use the common family of
polymorphic types, which allows the system to try to identify a suitable common type:
CREATE FUNCTION make_array2(anycompatible, anycompatible)
RETURNS anycompatiblearray AS $$
SELECT ARRAY[$1, $2];
$$ LANGUAGE SQL;
SELECT make_array2(1, 2.5) AS numericarray;
numericarray
--------------
{1,2.5}
(1 row)
Because the rules for common type resolution default to choosing
type text when all inputs are of unknown types, this also works:
SELECT make_array2('a', 'b') AS textarray;
textarray
-----------
{a,b}
(1 row)
It is permitted to have polymorphic arguments with a fixed return type, but the converse is not. For example:
CREATE FUNCTION is_greater(anyelement, anyelement) RETURNS boolean AS $$
SELECT $1 > $2;
$$ LANGUAGE SQL;
SELECT is_greater(1, 2);
is_greater
------------
f
(1 row)
CREATE FUNCTION invalid_func() RETURNS anyelement AS $$
SELECT 1;
$$ LANGUAGE SQL;
ERROR: cannot determine result data type
DETAIL: A result of type anyelement requires at least one input of type anyelement, anyarray, anynonarray, anyenum, or anyrange.
Polymorphism can be used with functions that have output arguments. For example:
CREATE FUNCTION dup (f1 anyelement, OUT f2 anyelement, OUT f3 anyarray)
AS 'select $1, array[$1,$1]' LANGUAGE SQL;
SELECT * FROM dup(22);
f2 | f3
----+---------
22 | {22,22}
(1 row)
Polymorphism can also be used with variadic functions. For example:
CREATE FUNCTION anyleast (VARIADIC anyarray) RETURNS anyelement AS $$
SELECT min($1[i]) FROM generate_subscripts($1, 1) g(i);
$$ LANGUAGE SQL;
SELECT anyleast(10, -1, 5, 4);
anyleast
----------
-1
(1 row)
SELECT anyleast('abc'::text, 'def');
anyleast
----------
abc
(1 row)
CREATE FUNCTION concat_values(text, VARIADIC anyarray) RETURNS text AS $$
SELECT array_to_string($2, $1);
$$ LANGUAGE SQL;
SELECT concat_values('|', 1, 4, 2);
concat_values
---------------
1|4|2
(1 row)
7.1.2.5.3.12. SQL Functions with Collations
When an SQL function has one or more parameters of collatable data types, a collation is identified for each function call depending on the collations assigned to the actual arguments, as described in collation. If a collation is successfully identified (i.e., there are no conflicts of implicit collations among the arguments) then all the collatable parameters are treated as having that collation implicitly. This will affect the behavior of collation-sensitive operations within the function. For example, using the anyleast function described above, the result of
SELECT anyleast('abc'::text, 'ABC');
will depend on the database's default collation. In **C** locale
the result will be ABC, but in many other locales it will be abc. The collation to use can be forced by adding a COLLATE clause to any of the arguments, for example
SELECT anyleast('abc'::text, 'ABC' COLLATE "C");
Alternatively, if you wish a function to operate with a particular
collation regardless of what it is called with, insert COLLATE clauses as needed in the function definition. This version of anyleast would always use en_US locale to compare strings:
CREATE FUNCTION anyleast (VARIADIC anyarray) RETURNS anyelement AS $$
SELECT min($1[i] COLLATE "en_US") FROM generate_subscripts($1, 1) g(i);
$$ LANGUAGE SQL;
But note that this will throw an error if applied to a non-collatable
data type.
If no common collation can be identified among the actual arguments, then an SQL function treats its parameters as having their data types“ default collation (which is usually the database’s default collation, but could be different for parameters of domain types).
The behavior of collatable parameters can be thought of as a limited form of polymorphism, applicable only to textual data types.
7.1.2.5.4. Function Overloading
More than one function can be defined with the same SQL name, so long as the arguments they take are different. In other words, function names can be overloaded. Whether or not you use it, this capability entails security precautions when calling functions in databases where some users mistrust other users; see typeconv-func. When a query is executed, the server will determine which function to call from the data types and the number of the provided arguments. Overloading can also be used to simulate functions with a variable number of arguments, up to a finite maximum number.
When creating a family of overloaded functions, one should be careful not to create ambiguities. For instance, given the functions:
CREATE FUNCTION test(int, real) RETURNS ...
CREATE FUNCTION test(smallint, double precision) RETURNS ...
it is not immediately clear which function would be called with
some trivial input like test(1, 1.5). The currently implemented resolution rules are described in typeconv, but it is unwise to design a system that subtly relies on this behavior.
A function that takes a single argument of a composite type should generally not have the same name as any attribute (field) of that type. Recall that attribute(table) is considered equivalent to table.attribute. In the case that there is an ambiguity between a function on a composite type and an attribute of the composite type, the attribute will always be used. It is possible to override that choice by schema-qualifying the function name (that is, **schema.func(table) **) but it’s better to avoid the problem by not choosing conflicting names.
Another possible conflict is between variadic and non-variadic functions. For instance, it is possible to create both foo(numeric) and foo(VARIADIC numeric[]). In this case it is unclear which one should be matched to a call providing a single numeric argument, such as foo(10.1). The rule is that the function appearing earlier in the search path is used, or if the two functions are in the same schema, the non-variadic one is preferred.
When overloading C-language functions, there is an additional constraint: The C name of each function in the family of overloaded functions must be different from the C names of all other functions, either internal or dynamically loaded. If this rule is violated, the behavior is not portable. You might get a run-time linker error, or one of the functions will get called (usually the internal one). The alternative form of the AS clause for the SQL CREATE FUNCTION command decouples the SQL function name from the function name in the C source code. For instance:
CREATE FUNCTION test(int) RETURNS int
AS 'filename', 'test_1arg'
LANGUAGE C;
CREATE FUNCTION test(int, int) RETURNS int
AS 'filename', 'test_2arg'
LANGUAGE C;
The names of the C functions here reflect one of many possible conventions.
7.1.2.5.5. Function Volatility Categories
Every function has a volatility classification, with the possibilities being VOLATILE, STABLE, or IMMUTABLE. VOLATILE is the default if the
linkend=»sql-createfunction»>**CREATE FUNCTION**
command does not specify a category. The volatility category is a promise to the optimizer about the behavior of the function:
A VOLATILE function can do anything, including modifying the database. It can return different results on successive calls with the same arguments. The optimizer makes no assumptions about the behavior of such functions. A query using a volatile function will re-evaluate the function at every row where its value is needed.
A STABLE function cannot modify the database and is guaranteed to return the same results given the same arguments for all rows within a single statement. This category allows the optimizer to optimize multiple calls of the function to a single call. In particular, it is safe to use an expression containing such a function in an index scan condition. (Since an index scan will evaluate the comparison value only once, not once at each row, it is not valid to use a VOLATILE function in an index scan condition.)
An IMMUTABLE function cannot modify the database and is guaranteed to return the same results given the same arguments forever. This category allows the optimizer to pre-evaluate the function when a query calls it with constant arguments. For example, a query like SELECT … WHERE x = 2 + 2 can be simplified on sight to SELECT … WHERE x = 4, because the function underlying the integer addition operator is marked IMMUTABLE.
For best optimization results, you should label your functions with the strictest volatility category that is valid for them.
Any function with side-effects must be labeled VOLATILE, so that calls to it cannot be optimized away. Even a function with no side-effects needs to be labeled VOLATILE if its value can change within a single query; some examples are random(), currval(), timeofday().
Another important example is that the current_timestamp family of functions qualify as STABLE, since their values do not change within a transaction.
There is relatively little difference between STABLE and IMMUTABLE categories when considering simple interactive queries that are planned and immediately executed: it doesn’t matter a lot whether a function is executed once during planning or once during query execution startup. But there is a big difference if the plan is saved and reused later. Labeling a function IMMUTABLE when it really isn’t might allow it to be prematurely folded to a constant during planning, resulting in a stale value being re-used during subsequent uses of the plan. This is a hazard when using prepared statements or when using function languages that cache plans (such as PL/pgSQL).
For functions written in SQL or in any of the standard procedural languages, there is a second important property determined by the volatility category, namely the visibility of any data changes that have been made by the SQL command that is calling the function. A VOLATILE function will see such changes, a STABLE or IMMUTABLE function will not. This behavior is implemented using the snapshotting behavior of MVCC (see mvcc): STABLE and IMMUTABLE functions use a snapshot established as of the start of the calling query, whereas VOLATILE functions obtain a fresh snapshot at the start of each query they execute.
Примечание
Functions written in C can manage snapshots however they want, but it’s usually a good idea to make C functions work this way too.
Because of this snapshotting behavior, a function containing only SELECT commands can safely be marked STABLE, even if it selects from tables that might be undergoing modifications by concurrent queries. PostgreSQL will execute all commands of a STABLE function using the snapshot established for the calling query, and so it will see a fixed view of the database throughout that query.
The same snapshotting behavior is used for SELECT commands within IMMUTABLE functions. It is generally unwise to select from database tables within an IMMUTABLE function at all, since the immutability will be broken if the table contents ever change. However, PostgreSQL does not enforce that you do not do that.
A common error is to label a function IMMUTABLE when its results depend on a configuration parameter. For example, a function that manipulates timestamps might well have results that depend on the guc-timezone setting. For safety, such functions should be labeled STABLE instead.
Примечание
PostgreSQL requires that STABLE and IMMUTABLE functions contain no SQL commands other than SELECT to prevent data modification. (This is not a completely bulletproof test, since such functions could still call VOLATILE functions that modify the database. If you do that, you will find that the STABLE or IMMUTABLE function does not notice the database changes applied by the called function, since they are hidden from its snapshot.)
7.1.2.5.6. Procedural Language Functions
PostgreSQL allows user-defined functions to be written in other languages besides SQL and C. These other languages are generically called procedural languages (PLs). Procedural languages aren’t built into the PostgreSQL server; they are offered by loadable modules. See xplang and following chapters for more information.
7.1.2.5.7. Internal Functions
Internal functions are functions written in C that have been statically linked into the PostgreSQL server. The body of the function definition specifies the C-language name of the function, which need not be the same as the name being declared for SQL use. (For reasons of backward compatibility, an empty body is accepted as meaning that the C-language function name is the same as the SQL name.)
Normally, all internal functions present in the server are declared during the initialization of the database cluster (see creating-cluster), but a user could use CREATE FUNCTION to create additional alias names for an internal function. Internal functions are declared in CREATE FUNCTION with language name internal. For instance, to create an alias for the sqrt function:
CREATE FUNCTION square_root(double precision) RETURNS double precision
AS 'dsqrt'
LANGUAGE internal
STRICT;
(Most internal functions expect to be declared strict.)
Примечание
Not all predefined functions are internal in the above sense. Some predefined functions are written in SQL.
7.1.2.5.8. C-Language Functions
User-defined functions can be written in C (or a language that can be made compatible with C, such as C++). Such functions are compiled into dynamically loadable objects (also called shared libraries) and are loaded by the server on demand. The dynamic loading feature is what distinguishes C language functions from internal functions — the actual coding conventions are essentially the same for both. (Hence, the standard internal function library is a rich source of coding examples for user-defined C functions.)
Currently only one calling convention is used for C functions (version 1). Support for that calling convention is indicated by writing a PG_FUNCTION_INFO_V1() macro call for the function, as illustrated below.
7.1.2.5.8.1. Dynamic Loading
The first time a user-defined function in a particular loadable object file is called in a session, the dynamic loader loads that object file into memory so that the function can be called. The CREATE FUNCTION for a user-defined C function must therefore specify two pieces of information for the function: the name of the loadable object file, and the C name (link symbol) of the specific function to call within that object file. If the C name is not explicitly specified then it is assumed to be the same as the SQL function name.
The following algorithm is used to locate the shared object file based on the name given in the CREATE FUNCTION command:
If the name is an absolute path, the given file is loaded.
If the name starts with the string $libdir, that part is replaced by the PostgreSQL package library directory name, which is determined at build time.
If the name does not contain a directory part, the file is searched for in the path specified by the configuration variable guc-dynamic-library-path.
Otherwise (the file was not found in the path, or it contains a non-absolute directory part), the dynamic loader will try to take the name as given, which will most likely fail. (It is unreliable to depend on the current working directory.)
If this sequence does not work, the platform-specific shared library file name extension (often .so) is appended to the given name and this sequence is tried again. If that fails as well, the load will fail.
It is recommended to locate shared libraries either relative to $libdir or through the dynamic library path. This simplifies version upgrades if the new installation is at a different location. The actual directory that $libdir stands for can be found out with the command pg_config –pkglibdir.
The user ID the PostgreSQL server runs as must be able to traverse the path to the file you intend to load. Making the file or a higher-level directory not readable and/or not executable by the postgres user is a common mistake.
In any case, the file name that is given in the CREATE FUNCTION command is recorded literally in the system catalogs, so if the file needs to be loaded again the same procedure is applied.
Примечание
PostgreSQL will not compile a C function automatically. The object file must be compiled before it is referenced in a CREATE FUNCTION command. See dfunc for additional information.
To ensure that a dynamically loaded object file is not loaded into an incompatible server, PostgreSQL checks that the file contains a magic block with the appropriate contents. This allows the server to detect obvious incompatibilities, such as code compiled for a different major version of PostgreSQL. To include a magic block, write this in one (and only one) of the module source files, after having included the header fmgr.h:
PG_MODULE_MAGIC;
After it is used for the first time, a dynamically loaded object file is retained in memory. Future calls in the same session to the function(s) in that file will only incur the small overhead of a symbol table lookup. If you need to force a reload of an object file, for example after recompiling it, begin a fresh session.
Optionally, a dynamically loaded file can contain an initialization function. If the file includes a function named _PG_init, that function will be called immediately after loading the file. The function receives no parameters and should return void. There is presently no way to unload a dynamically loaded file.
7.1.2.5.8.2. Base Types in C-Language Functions
To know how to write C-language functions, you need to know how PostgreSQL internally represents base data types and how they can be passed to and from functions. Internally, PostgreSQL regards a base type as a blob of memory. The user-defined functions that you define over a type in turn define the way that PostgreSQL can operate on it. That is, PostgreSQL will only store and retrieve the data from disk and use your user-defined functions to input, process, and output the data.
Base types can have one of three internal formats:
pass by value, fixed-length
pass by reference, fixed-length
pass by reference, variable-length
By-value types can only be 1, 2, or 4 bytes in length (also 8 bytes, if sizeof(Datum) is 8 on your machine). You should be careful to define your types such that they will be the same size (in bytes) on all architectures. For example, the long type is dangerous because it is 4 bytes on some machines and 8 bytes on others, whereas int type is 4 bytes on most Unix machines. A reasonable implementation of the int4 type on Unix machines might be:
/* 4-byte integer, passed by value */
typedef int int4;
(The actual PostgreSQL C code calls this type int32, because it is a convention in C that intXX means XX bits. Note therefore also that the C type int8 is 1 byte in size. The SQL type int8 is called int64 in C. See also xfunc-c-type-table.)
On the other hand, fixed-length types of any size can be passed by-reference. For example, here is a sample implementation of a PostgreSQL type:
/* 16-byte structure, passed by reference */
typedef struct
{
double x, y;
} Point;
Only pointers to such types can be used when passing them in and out of PostgreSQL functions. To return a value of such a type, allocate the right amount of memory with palloc, fill in the allocated memory, and return a pointer to it. (Also, if you just want to return the same value as one of your input arguments that’s of the same data type, you can skip the extra palloc and just return the pointer to the input value.)
Finally, all variable-length types must also be passed by reference. All variable-length types must begin with an opaque length field of exactly 4 bytes, which will be set by SET_VARSIZE; never set this field directly! All data to be stored within that type must be located in the memory immediately following that length field. The length field contains the total length of the structure, that is, it includes the size of the length field itself.
Another important point is to avoid leaving any uninitialized bits within data type values; for example, take care to zero out any alignment padding bytes that might be present in structs. Without this, logically-equivalent constants of your data type might be seen as unequal by the planner, leading to inefficient (though not incorrect) plans.
Предупреждение
Never modify the contents of a pass-by-reference input value. If you do so you are likely to corrupt on-disk data, since the pointer you are given might point directly into a disk buffer. The sole exception to this rule is explained in xaggr.
As an example, we can define the type text as follows:
typedef struct {
int32 length;
char data[FLEXIBLE_ARRAY_MEMBER];
} text;
The [FLEXIBLE_ARRAY_MEMBER] notation means that the actual length of the data part is not specified by this declaration.
When manipulating variable-length types, we must be careful to allocate the correct amount of memory and set the length field correctly. For example, if we wanted to store 40 bytes in a text structure, we might use a code fragment like this:
#include "postgres.h"
...
char buffer[40]; /* our source data */
...
text *destination = (text *) palloc(VARHDRSZ + 40);
SET_VARSIZE(destination, VARHDRSZ + 40);
memcpy(destination->data, buffer, 40);
...
VARHDRSZ is the same as sizeof(int32), but it’s considered good style to use the macro VARHDRSZ to refer to the size of the overhead for a variable-length type. Also, the length field must be set using the SET_VARSIZE macro, not by simple assignment.
xfunc-c-type-table shows the C types corresponding to many of the built-in SQL data types of PostgreSQL. The Defined In column gives the header file that needs to be included to get the type definition. (The actual definition might be in a different file that is included by the listed file. It is recommended that users stick to the defined interface.) Note that you should always include postgres.h first in any source file of server code, because it declares a number of things that you will need anyway, and because including other headers first can cause portability issues.
Equivalent C Types for Built-in SQL Types
Now that we’ve gone over all of the possible structures for base types, we can show some examples of real functions.
7.1.2.5.8.3. Version 1 Calling Conventions
The version-1 calling convention relies on macros to suppress most of the complexity of passing arguments and results. The C declaration of a version-1 function is always:
Datum funcname(PG_FUNCTION_ARGS)
In addition, the macro call:
PG_FUNCTION_INFO_V1(funcname);
must appear in the same source file. (Conventionally, it's
written just before the function itself.) This macro call is not needed for internal-language functions, since PostgreSQL assumes that all internal functions use the version-1 convention. It is, however, required for dynamically-loaded functions.
In a version-1 function, each actual argument is fetched using a PG_GETARG_xxx() macro that corresponds to the argument’s data type. (In non-strict functions there needs to be a previous check about argument null-ness using PG_ARGISNULL(); see below.) The result is returned using a PG_RETURN_xxx() macro for the return type. PG_GETARG_xxx() takes as its argument the number of the function argument to fetch, where the count starts at 0. PG_RETURN_xxx() takes as its argument the actual value to return.
Here are some examples using the version-1 calling convention:
#include "postgres.h"
#include <string.h>
#include "fmgr.h"
#include "utils/geo_decls.h"
PG_MODULE_MAGIC;
/* by value */
PG_FUNCTION_INFO_V1(add_one);
Datum
add_one(PG_FUNCTION_ARGS)
{
int32 arg = PG_GETARG_INT32(0);
PG_RETURN_INT32(arg + 1);
}
/* by reference, fixed length */
PG_FUNCTION_INFO_V1(add_one_float8);
Datum
add_one_float8(PG_FUNCTION_ARGS)
{
/* The macros for FLOAT8 hide its pass-by-reference nature. */
float8 arg = PG_GETARG_FLOAT8(0);
PG_RETURN_FLOAT8(arg + 1.0);
}
PG_FUNCTION_INFO_V1(makepoint);
Datum
makepoint(PG_FUNCTION_ARGS)
{
/* Here, the pass-by-reference nature of Point is not hidden. */
Point *pointx = PG_GETARG_POINT_P(0);
Point *pointy = PG_GETARG_POINT_P(1);
Point *new_point = (Point *) palloc(sizeof(Point));
new_point->x = pointx->x;
new_point->y = pointy->y;
PG_RETURN_POINT_P(new_point);
}
/* by reference, variable length */
PG_FUNCTION_INFO_V1(copytext);
Datum
copytext(PG_FUNCTION_ARGS)
{
text *t = PG_GETARG_TEXT_PP(0);
/*
* VARSIZE_ANY_EXHDR is the size of the struct in bytes, minus the
* VARHDRSZ or VARHDRSZ_SHORT of its header. Construct the copy with a
* full-length header.
*/
text *new_t = (text *) palloc(VARSIZE_ANY_EXHDR(t) + VARHDRSZ);
SET_VARSIZE(new_t, VARSIZE_ANY_EXHDR(t) + VARHDRSZ);
/*
* VARDATA is a pointer to the data region of the new struct. The source
* could be a short datum, so retrieve its data through VARDATA_ANY.
*/
memcpy((void *) VARDATA(new_t), /* destination */
(void *) VARDATA_ANY(t), /* source */
VARSIZE_ANY_EXHDR(t)); /* how many bytes */
PG_RETURN_TEXT_P(new_t);
}
PG_FUNCTION_INFO_V1(concat_text);
Datum
concat_text(PG_FUNCTION_ARGS)
{
text *arg1 = PG_GETARG_TEXT_PP(0);
text *arg2 = PG_GETARG_TEXT_PP(1);
int32 arg1_size = VARSIZE_ANY_EXHDR(arg1);
int32 arg2_size = VARSIZE_ANY_EXHDR(arg2);
int32 new_text_size = arg1_size + arg2_size + VARHDRSZ;
text *new_text = (text *) palloc(new_text_size);
SET_VARSIZE(new_text, new_text_size);
memcpy(VARDATA(new_text), VARDATA_ANY(arg1), arg1_size);
memcpy(VARDATA(new_text) + arg1_size, VARDATA_ANY(arg2), arg2_size);
PG_RETURN_TEXT_P(new_text);
}
Supposing that the above code has been prepared in file funcs.c and compiled into a shared object, we could define the functions to PostgreSQL with commands like this:
CREATE FUNCTION add_one(integer) RETURNS integer
AS 'DIRECTORY/funcs', 'add_one'
LANGUAGE C STRICT;
-- note overloading of SQL function name "add_one"
CREATE FUNCTION add_one(double precision) RETURNS double precision
AS 'DIRECTORY/funcs', 'add_one_float8'
LANGUAGE C STRICT;
CREATE FUNCTION makepoint(point, point) RETURNS point
AS 'DIRECTORY/funcs', 'makepoint'
LANGUAGE C STRICT;
CREATE FUNCTION copytext(text) RETURNS text
AS 'DIRECTORY/funcs', 'copytext'
LANGUAGE C STRICT;
CREATE FUNCTION concat_text(text, text) RETURNS text
AS 'DIRECTORY/funcs', 'concat_text'
LANGUAGE C STRICT;
Here, DIRECTORY stands for the directory of the shared library file (for instance the PostgreSQL tutorial directory, which contains the code for the examples used in this section). (Better style would be to use just „funcs“ in the AS clause, after having added DIRECTORY to the search path. In any case, we can omit the system-specific extension for a shared library, commonly .so.)
Notice that we have specified the functions as strict, meaning that the system should automatically assume a null result if any input value is null. By doing this, we avoid having to check for null inputs in the function code. Without this, we’d have to check for null values explicitly, using PG_ARGISNULL().
The macro PG_ARGISNULL(n) allows a function to test whether each input is null. (Of course, doing this is only necessary in functions not declared strict.) As with the PG_GETARG_xxx() macros, the input arguments are counted beginning at zero. Note that one should refrain from executing PG_GETARG_xxx() until one has verified that the argument isn’t null. To return a null result, execute PG_RETURN_NULL(); this works in both strict and nonstrict functions.
At first glance, the version-1 coding conventions might appear to be just pointless obscurantism, compared to using plain C calling conventions. They do however allow us to deal with **NULL**able arguments/return values, and toasted (compressed or out-of-line) values.
Other options provided by the version-1 interface are two variants of the PG_GETARG_xxx() macros. The first of these, PG_GETARG_xxx_COPY(), guarantees to return a copy of the specified argument that is safe for writing into. (The normal macros will sometimes return a pointer to a value that is physically stored in a table, which must not be written to. Using the PG_GETARG_xxx_COPY() macros guarantees a writable result.) The second variant consists of the PG_GETARG_xxx_SLICE() macros which take three arguments. The first is the number of the function argument (as above). The second and third are the offset and length of the segment to be returned. Offsets are counted from zero, and a negative length requests that the remainder of the value be returned. These macros provide more efficient access to parts of large values in the case where they have storage type external. (The storage type of a column can be specified using ALTER TABLE tablename ALTER COLUMN colname SET STORAGE storagetype. storagetype is one of plain, external, extended, or main.)
Finally, the version-1 function call conventions make it possible to return set results (xfunc-c-return-set) and implement trigger functions (triggers) and procedural-language call handlers (plhandler). For more details see src/backend/utils/fmgr/README in the source distribution.
7.1.2.5.8.4. Writing Code
Before we turn to the more advanced topics, we should discuss some coding rules for PostgreSQL C-language functions. While it might be possible to load functions written in languages other than C into PostgreSQL, this is usually difficult (when it is possible at all) because other languages, such as C++, FORTRAN, or Pascal often do not follow the same calling convention as C. That is, other languages do not pass argument and return values between functions in the same way. For this reason, we will assume that your C-language functions are actually written in C.
The basic rules for writing and building C functions are as follows:
Use pg_config –includedir-server to find out where the PostgreSQL server header files are installed on your system (or the system that your users will be running on).
Compiling and linking your code so that it can be dynamically loaded into PostgreSQL always requires special flags. See dfunc for a detailed explanation of how to do it for your particular operating system.
Remember to define a magic block for your shared library, as described in xfunc-c-dynload.
When allocating memory, use the PostgreSQL functions palloc**and **pfree instead of the corresponding C library functions malloc and free. The memory allocated by palloc will be freed automatically at the end of each transaction, preventing memory leaks.
Always zero the bytes of your structures using memset (or allocate them with palloc0 in the first place). Even if you assign to each field of your structure, there might be alignment padding (holes in the structure) that contain garbage values. Without this, it’s difficult to support hash indexes or hash joins, as you must pick out only the significant bits of your data structure to compute a hash. The planner also sometimes relies on comparing constants via bitwise equality, so you can get undesirable planning results if logically-equivalent values aren’t bitwise equal.
Most of the internal PostgreSQL types are declared in postgres.h, while the function manager interfaces (PG_FUNCTION_ARGS, etc.) are in fmgr.h, so you will need to include at least these two files. For portability reasons it’s best to include postgres.h first, before any other system or user header files. Including postgres.h will also include elog.h and palloc.h for you.
Symbol names defined within object files must not conflict with each other or with symbols defined in the PostgreSQL server executable. You will have to rename your functions or variables if you get error messages to this effect.
7.1.2.5.8.5. Composite-Type Arguments
Composite types do not have a fixed layout like C structures. Instances of a composite type can contain null fields. In addition, composite types that are part of an inheritance hierarchy can have different fields than other members of the same inheritance hierarchy. Therefore, PostgreSQL provides a function interface for accessing fields of composite types from C.
Suppose we want to write a function to answer the query:
SELECT name, c_overpaid(emp, 1500) AS overpaid
FROM emp
WHERE name = 'Bill' OR name = 'Sam';
Using the version-1 calling conventions, we can define c_overpaid as:
#include "postgres.h"
#include "executor/executor.h" /* for GetAttributeByName() */
PG_MODULE_MAGIC;
PG_FUNCTION_INFO_V1(c_overpaid);
Datum
c_overpaid(PG_FUNCTION_ARGS)
{
HeapTupleHeader t = PG_GETARG_HEAPTUPLEHEADER(0);
int32 limit = PG_GETARG_INT32(1);
bool isnull;
Datum salary;
salary = GetAttributeByName(t, "salary", &isnull);
if (isnull)
PG_RETURN_BOOL(false);
/* Alternatively, we might prefer to do PG_RETURN_NULL() for null salary. */
PG_RETURN_BOOL(DatumGetInt32(salary) > limit);
}
GetAttributeByName is the PostgreSQL system function that returns attributes out of the specified row. It has three arguments: the argument of type HeapTupleHeader passed into the function, the name of the desired attribute, and a return parameter that tells whether the attribute is null. GetAttributeByName returns a Datum value that you can convert to the proper data type by using the appropriate DatumGetXXX() macro. Note that the return value is meaningless if the null flag is set; always check the null flag before trying to do anything with the result.
There is also GetAttributeByNum, which selects the target attribute by column number instead of name.
The following command declares the function c_overpaid in SQL:
CREATE FUNCTION c_overpaid(emp, integer) RETURNS boolean
AS 'DIRECTORY/funcs', 'c_overpaid'
LANGUAGE C STRICT;
Notice we have used STRICT so that we did not have to check whether the input arguments were NULL.
7.1.2.5.8.6. Returning Rows (Composite Types)
To return a row or composite-type value from a C-language function, you can use a special API that provides macros and functions to hide most of the complexity of building composite data types. To use this API, the source file must include:
#include "funcapi.h"
There are two ways you can build a composite data value (henceforth a tuple): you can build it from an array of Datum values, or from an array of C strings that can be passed to the input conversion functions of the tuple’s column data types. In either case, you first need to obtain or construct a TupleDesc descriptor for the tuple structure. When working with Datums, you pass the TupleDesc to BlessTupleDesc, and then call heap_form_tuple for each row. When working with C strings, you pass the TupleDesc to TupleDescGetAttInMetadata, and then call BuildTupleFromCStrings for each row. In the case of a function returning a set of tuples, the setup steps can all be done once during the first call of the function.
Several helper functions are available for setting up the needed TupleDesc. The recommended way to do this in most functions returning composite values is to call:
TypeFuncClass get_call_result_type(FunctionCallInfo fcinfo,
Oid *resultTypeId,
TupleDesc *resultTupleDesc)
passing the same **fcinfo** struct passed to the calling function
itself. (This of course requires that you use the version-1 calling conventions.) resultTypeId can be specified as NULL or as the address of a local variable to receive the function’s result type OID. resultTupleDesc should be the address of a local TupleDesc variable. Check that the result is TYPEFUNC_COMPOSITE; if so, resultTupleDesc has been filled with the needed TupleDesc. (If it is not, you can report an error along the lines of function returning record called in context that cannot accept type record.)
Совет
get_call_result_type can resolve the actual type of a polymorphic function result; so it is useful in functions that return scalar polymorphic results, not only functions that return composites. The resultTypeId output is primarily useful for functions returning polymorphic scalars.
Примечание
get_call_result_type has a sibling get_expr_result_type, which can be used to resolve the expected output type for a function call represented by an expression tree. This can be used when trying to determine the result type from outside the function itself. There is also get_func_result_type, which can be used when only the function’s OID is available. However these functions are not able to deal with functions declared to return record, and get_func_result_type cannot resolve polymorphic types, so you should preferentially use get_call_result_type.
Older, now-deprecated functions for obtaining **TupleDesc**s are:
TupleDesc RelationNameGetTupleDesc(const char *relname)
to get a **TupleDesc** for the row type of a named relation,
and:
TupleDesc TypeGetTupleDesc(Oid typeoid, List *colaliases)
to get a **TupleDesc** based on a type OID. This can
be used to get a TupleDesc for a base or composite type. It will not work for a function that returns record, however, and it cannot resolve polymorphic types.
Once you have a TupleDesc, call:
TupleDesc BlessTupleDesc(TupleDesc tupdesc)
if you plan to work with Datums, or:
AttInMetadata *TupleDescGetAttInMetadata(TupleDesc tupdesc)
if you plan to work with C strings. If you are writing a function
returning set, you can save the results of these functions in the FuncCallContext structure — use the tuple_desc or attinmeta field respectively.
When working with Datums, use:
HeapTuple heap_form_tuple(TupleDesc tupdesc, Datum *values, bool *isnull)
to build a **HeapTuple** given user data in Datum form.
When working with C strings, use:
HeapTuple BuildTupleFromCStrings(AttInMetadata *attinmeta, char **values)
to build a **HeapTuple** given user data
in C string form. values is an array of C strings, one for each attribute of the return row. Each C string should be in the form expected by the input function of the attribute data type. In order to return a null value for one of the attributes, the corresponding pointer in the values array should be set to NULL. This function will need to be called again for each row you return.
Once you have built a tuple to return from your function, it must be converted into a Datum. Use:
HeapTupleGetDatum(HeapTuple tuple)
to convert a **HeapTuple** into a valid Datum. This
Datum can be returned directly if you intend to return just a single row, or it can be used as the current return value in a set-returning function.
An example appears in the next section.
7.1.2.5.8.7. Returning Sets
C-language functions have two options for returning sets (multiple rows). In one method, called ValuePerCall mode, a set-returning function is called repeatedly (passing the same arguments each time) and it returns one new row on each call, until it has no more rows to return and signals that by returning NULL. The set-returning function (SRF) must therefore save enough state across calls to remember what it was doing and return the correct next item on each call. In the other method, called Materialize mode, an SRF fills and returns a tuplestore object containing its entire result; then only one call occurs for the whole result, and no inter-call state is needed.
When using ValuePerCall mode, it is important to remember that the query is not guaranteed to be run to completion; that is, due to options such as LIMIT, the executor might stop making calls to the set-returning function before all rows have been fetched. This means it is not safe to perform cleanup activities in the last call, because that might not ever happen. It’s recommended to use Materialize mode for functions that need access to external resources, such as file descriptors.
The remainder of this section documents a set of helper macros that are commonly used (though not required to be used) for SRFs using ValuePerCall mode. Additional details about Materialize mode can be found in src/backend/utils/fmgr/README. Also, the contrib modules in the PostgreSQL source distribution contain many examples of SRFs using both ValuePerCall and Materialize mode.
To use the ValuePerCall support macros described here, include funcapi.h. These macros work with a structure FuncCallContext that contains the state that needs to be saved across calls. Within the calling SRF, fcinfo->flinfo->fn_extra is used to hold a pointer to FuncCallContext across calls. The macros automatically fill that field on first use, and expect to find the same pointer there on subsequent uses.
typedef struct FuncCallContext
{
/*
* Number of times we've been called before
*
* call_cntr is initialized to 0 for you by SRF_FIRSTCALL_INIT(), and
* incremented for you every time SRF_RETURN_NEXT() is called.
*/
uint64 call_cntr;
/*
* OPTIONAL maximum number of calls
*
* max_calls is here for convenience only and setting it is optional.
* If not set, you must provide alternative means to know when the
* function is done.
*/
uint64 max_calls;
/*
* OPTIONAL pointer to miscellaneous user-provided context information
*
* user_fctx is for use as a pointer to your own data to retain
* arbitrary context information between calls of your function.
*/
void *user_fctx;
/*
* OPTIONAL pointer to struct containing attribute type input metadata
*
* attinmeta is for use when returning tuples (i.e., composite data types)
* and is not used when returning base data types. It is only needed
* if you intend to use BuildTupleFromCStrings() to create the return
* tuple.
*/
AttInMetadata *attinmeta;
/*
* memory context used for structures that must live for multiple calls
*
* multi_call_memory_ctx is set by SRF_FIRSTCALL_INIT() for you, and used
* by SRF_RETURN_DONE() for cleanup. It is the most appropriate memory
* context for any memory that is to be reused across multiple calls
* of the SRF.
*/
MemoryContext multi_call_memory_ctx;
/*
* OPTIONAL pointer to struct containing tuple description
*
* tuple_desc is for use when returning tuples (i.e., composite data types)
* and is only needed if you are going to build the tuples with
* heap_form_tuple() rather than with BuildTupleFromCStrings(). Note that
* the TupleDesc pointer stored here should usually have been run through
* BlessTupleDesc() first.
*/
TupleDesc tuple_desc;
} FuncCallContext;
The macros to be used by an SRF using this infrastructure are:
SRF_IS_FIRSTCALL()
Use this to determine if your function is being called for the first or a
subsequent time. On the first call (only), call:
SRF_FIRSTCALL_INIT()
to initialize the **FuncCallContext**. On every function call,
including the first, call:
SRF_PERCALL_SETUP()
to set up for using the **FuncCallContext**.
If your function has data to return in the current call, use:
SRF_RETURN_NEXT(funcctx, result)
to return it to the caller. (**result** must be of type
Datum, either a single value or a tuple prepared as described above.) Finally, when your function is finished returning data, use:
SRF_RETURN_DONE(funcctx)
to clean up and end the SRF.
The memory context that is current when the SRF is called is a transient context that will be cleared between calls. This means that you do not need to call pfree on everything you allocated using palloc; it will go away anyway. However, if you want to allocate any data structures to live across calls, you need to put them somewhere else. The memory context referenced by multi_call_memory_ctx is a suitable location for any data that needs to survive until the SRF is finished running. In most cases, this means that you should switch into multi_call_memory_ctx while doing the first-call setup. Use funcctx->user_fctx to hold a pointer to any such cross-call data structures. (Data you allocate in multi_call_memory_ctx will go away automatically when the query ends, so it is not necessary to free that data manually, either.)
Предупреждение
While the actual arguments to the function remain unchanged between calls, if you detoast the argument values (which is normally done transparently by the PG_GETARG_xxx macro) in the transient context then the detoasted copies will be freed on each cycle. Accordingly, if you keep references to such values in your user_fctx, you must either copy them into the multi_call_memory_ctx after detoasting, or ensure that you detoast the values only in that context.
A complete pseudo-code example looks like the following:
Datum
my_set_returning_function(PG_FUNCTION_ARGS)
{
FuncCallContext *funcctx;
Datum result;
further declarations as needed
if (SRF_IS_FIRSTCALL())
{
MemoryContext oldcontext;
funcctx = SRF_FIRSTCALL_INIT();
oldcontext = MemoryContextSwitchTo(funcctx->multi_call_memory_ctx);
/* One-time setup code appears here: */
user code
if returning composite
build TupleDesc, and perhaps AttInMetadata
endif returning composite
user code
MemoryContextSwitchTo(oldcontext);
}
/* Each-time setup code appears here: */
user code
funcctx = SRF_PERCALL_SETUP();
user code
/* this is just one way we might test whether we are done: */
if (funcctx->call_cntr < funcctx->max_calls)
{
/* Here we want to return another item: */
user code
obtain result Datum
SRF_RETURN_NEXT(funcctx, result);
}
else
{
/* Here we are done returning items, so just report that fact. */
/* (Resist the temptation to put cleanup code here.) */
SRF_RETURN_DONE(funcctx);
}
}
A complete example of a simple SRF returning a composite type looks like:
PG_FUNCTION_INFO_V1(retcomposite);
Datum
retcomposite(PG_FUNCTION_ARGS)
{
FuncCallContext *funcctx;
int call_cntr;
int max_calls;
TupleDesc tupdesc;
AttInMetadata *attinmeta;
/* stuff done only on the first call of the function */
if (SRF_IS_FIRSTCALL())
{
MemoryContext oldcontext;
/* create a function context for cross-call persistence */
funcctx = SRF_FIRSTCALL_INIT();
/* switch to memory context appropriate for multiple function calls */
oldcontext = MemoryContextSwitchTo(funcctx->multi_call_memory_ctx);
/* total number of tuples to be returned */
funcctx->max_calls = PG_GETARG_INT32(0);
/* Build a tuple descriptor for our result type */
if (get_call_result_type(fcinfo, NULL, &tupdesc) != TYPEFUNC_COMPOSITE)
ereport(ERROR,
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
errmsg("function returning record called in context "
"that cannot accept type record")));
/*
* generate attribute metadata needed later to produce tuples from raw
* C strings
*/
attinmeta = TupleDescGetAttInMetadata(tupdesc);
funcctx->attinmeta = attinmeta;
MemoryContextSwitchTo(oldcontext);
}
/* stuff done on every call of the function */
funcctx = SRF_PERCALL_SETUP();
call_cntr = funcctx->call_cntr;
max_calls = funcctx->max_calls;
attinmeta = funcctx->attinmeta;
if (call_cntr < max_calls) /* do when there is more left to send */
{
char **values;
HeapTuple tuple;
Datum result;
/*
* Prepare a values array for building the returned tuple.
* This should be an array of C strings which will
* be processed later by the type input functions.
*/
values = (char **) palloc(3 * sizeof(char *));
values[0] = (char *) palloc(16 * sizeof(char));
values[1] = (char *) palloc(16 * sizeof(char));
values[2] = (char *) palloc(16 * sizeof(char));
snprintf(values[0], 16, "%d", 1 * PG_GETARG_INT32(1));
snprintf(values[1], 16, "%d", 2 * PG_GETARG_INT32(1));
snprintf(values[2], 16, "%d", 3 * PG_GETARG_INT32(1));
/* build a tuple */
tuple = BuildTupleFromCStrings(attinmeta, values);
/* make the tuple into a datum */
result = HeapTupleGetDatum(tuple);
/* clean up (this is not really necessary) */
pfree(values[0]);
pfree(values[1]);
pfree(values[2]);
pfree(values);
SRF_RETURN_NEXT(funcctx, result);
}
else /* do when there is no more left */
{
SRF_RETURN_DONE(funcctx);
}
}
One way to declare this function in SQL is:
CREATE TYPE __retcomposite AS (f1 integer, f2 integer, f3 integer);
CREATE OR REPLACE FUNCTION retcomposite(integer, integer)
RETURNS SETOF __retcomposite
AS 'filename', 'retcomposite'
LANGUAGE C IMMUTABLE STRICT;
A different way is to use OUT parameters:
CREATE OR REPLACE FUNCTION retcomposite(IN integer, IN integer,
OUT f1 integer, OUT f2 integer, OUT f3 integer)
RETURNS SETOF record
AS 'filename', 'retcomposite'
LANGUAGE C IMMUTABLE STRICT;
Notice that in this method the output type of the function is formally
an anonymous record type.
7.1.2.5.8.8. Polymorphic Arguments and Return Types
C-language functions can be declared to accept and return the polymorphic types described in extend-types-polymorphic. When a function’s arguments or return types are defined as polymorphic types, the function author cannot know in advance what data type it will be called with, or need to return. There are two routines provided in fmgr.h to allow a version-1 C function to discover the actual data types of its arguments and the type it is expected to return. The routines are called get_fn_expr_rettype(FmgrInfo *flinfo) and get_fn_expr_argtype(FmgrInfo *flinfo, int argnum). They return the result or argument type OID, or InvalidOid if the information is not available. The structure flinfo is normally accessed as fcinfo->flinfo. The parameter argnum is zero based. get_call_result_type can also be used as an alternative to get_fn_expr_rettype. There is also get_fn_expr_variadic, which can be used to find out whether variadic arguments have been merged into an array. This is primarily useful for VARIADIC «any» functions, since such merging will always have occurred for variadic functions taking ordinary array types.
For example, suppose we want to write a function to accept a single element of any type, and return a one-dimensional array of that type:
PG_FUNCTION_INFO_V1(make_array);
Datum
make_array(PG_FUNCTION_ARGS)
{
ArrayType *result;
Oid element_type = get_fn_expr_argtype(fcinfo->flinfo, 0);
Datum element;
bool isnull;
int16 typlen;
bool typbyval;
char typalign;
int ndims;
int dims[MAXDIM];
int lbs[MAXDIM];
if (!OidIsValid(element_type))
elog(ERROR, "could not determine data type of input");
/* get the provided element, being careful in case it's NULL */
isnull = PG_ARGISNULL(0);
if (isnull)
element = (Datum) 0;
else
element = PG_GETARG_DATUM(0);
/* we have one dimension */
ndims = 1;
/* and one element */
dims[0] = 1;
/* and lower bound is 1 */
lbs[0] = 1;
/* get required info about the element type */
get_typlenbyvalalign(element_type, &typlen, &typbyval, &typalign);
/* now build the array */
result = construct_md_array(&element, &isnull, ndims, dims, lbs,
element_type, typlen, typbyval, typalign);
PG_RETURN_ARRAYTYPE_P(result);
}
The following command declares the function make_array in SQL:
CREATE FUNCTION make_array(anyelement) RETURNS anyarray
AS 'DIRECTORY/funcs', 'make_array'
LANGUAGE C IMMUTABLE;
There is a variant of polymorphism that is only available to C-language functions: they can be declared to take parameters of type «any». (Note that this type name must be double-quoted, since it’s also an SQL reserved word.) This works like anyelement except that it does not constrain different «any» arguments to be the same type, nor do they help determine the function’s result type. A C-language function can also declare its final parameter to be VARIADIC «any». This will match one or more actual arguments of any type (not necessarily the same type). These arguments will not be gathered into an array as happens with normal variadic functions; they will just be passed to the function separately. The PG_NARGS() macro and the methods described above must be used to determine the number of actual arguments and their types when using this feature. Also, users of such a function might wish to use the VARIADIC keyword in their function call, with the expectation that the function would treat the array elements as separate arguments. The function itself must implement that behavior if wanted, after using get_fn_expr_variadic to detect that the actual argument was marked with VARIADIC.
7.1.2.5.8.10. Using C++ for Extensibility
Although the PostgreSQL backend is written in C, it is possible to write extensions in C++ if these guidelines are followed:
All functions accessed by the backend must present a C interface to the backend; these C functions can then call C++ functions. For example, extern C linkage is required for backend-accessed functions. This is also necessary for any functions that are passed as pointers between the backend and C++ code.
Free memory using the appropriate deallocation method. For example, most backend memory is allocated using palloc(), so use pfree() to free it. Using C++ delete in such cases will fail.
Prevent exceptions from propagating into the C code (use a catch-all block at the top level of all extern C functions). This is necessary even if the C++ code does not explicitly throw any exceptions, because events like out-of-memory can still throw exceptions. Any exceptions must be caught and appropriate errors passed back to the C interface. If possible, compile C++ with -fno-exceptions to eliminate exceptions entirely; in such cases, you must check for failures in your C++ code, e.g., check for NULL returned by new().
If calling backend functions from C++ code, be sure that the C++ call stack contains only plain old data structures (POD). This is necessary because backend errors generate a distant longjmp() that does not properly unroll a C++ call stack with non-POD objects.
In summary, it is best to place C++ code behind a wall of extern C functions that interface to the backend, and avoid exception, memory, and call stack leakage.
7.1.2.5.9. Function Optimization Information
By default, a function is just a black box that the database system knows very little about the behavior of. However, that means that queries using the function may be executed much less efficiently than they could be. It is possible to supply additional knowledge that helps the planner optimize function calls.
Some basic facts can be supplied by declarative annotations provided in the linkend=»sql-createfunction»>**CREATE FUNCTION** command. Most important of these is the function’s linkend=»xfunc-volatility»>volatility category (IMMUTABLE, STABLE, or VOLATILE); one should always be careful to specify this correctly when defining a function. The parallel safety property (PARALLEL UNSAFE, PARALLEL RESTRICTED, or PARALLEL SAFE) must also be specified if you hope to use the function in parallelized queries. It can also be useful to specify the function’s estimated execution cost, and/or the number of rows a set-returning function is estimated to return. However, the declarative way of specifying those two facts only allows specifying a constant value, which is often inadequate.
It is also possible to attach a planner support function to an SQL-callable function (called its target function), and thereby provide knowledge about the target function that is too complex to be represented declaratively. Planner support functions have to be written in C (although their target functions might not be), so this is an advanced feature that relatively few people will use.
A planner support function must have the SQL signature
supportfn(internal) returns internal
It is attached to its target function by specifying
the SUPPORT clause when creating the target function.
The details of the API for planner support functions can be found in file src/include/nodes/supportnodes.h in the PostgreSQL source code. Here we provide just an overview of what planner support functions can do. The set of possible requests to a support function is extensible, so more things might be possible in future versions.
Some function calls can be simplified during planning based on properties specific to the function. For example, int4mul(n, 1) could be simplified to just n. This type of transformation can be performed by a planner support function, by having it implement the SupportRequestSimplify request type. The support function will be called for each instance of its target function found in a query parse tree. If it finds that the particular call can be simplified into some other form, it can build and return a parse tree representing that expression. This will automatically work for operators based on the function, too — in the example just given, n * 1 would also be simplified to n. (But note that this is just an example; this particular optimization is not actually performed by standard PostgreSQL.) We make no guarantee that PostgreSQL will never call the target function in cases that the support function could simplify. Ensure rigorous equivalence between the simplified expression and an actual execution of the target function.
For target functions that return boolean, it is often useful to estimate the fraction of rows that will be selected by a WHERE clause using that function. This can be done by a support function that implements the SupportRequestSelectivity request type.
If the target function’s run time is highly dependent on its inputs, it may be useful to provide a non-constant cost estimate for it. This can be done by a support function that implements the SupportRequestCost request type.
For target functions that return sets, it is often useful to provide a non-constant estimate for the number of rows that will be returned. This can be done by a support function that implements the SupportRequestRows request type.
For target functions that return boolean, it may be possible to convert a function call appearing in WHERE into an indexable operator clause or clauses. The converted clauses might be exactly equivalent to the function’s condition, or they could be somewhat weaker (that is, they might accept some values that the function condition does not). In the latter case the index condition is said to be lossy; it can still be used to scan an index, but the function call will have to be executed for each row returned by the index to see if it really passes the WHERE condition or not. To create such conditions, the support function must implement the SupportRequestIndexCondition request type.