|Oracle9i SQL Reference
Release 2 (9.2)
Part Number A96540-01
Functions, 2 of 177
SQL functions are built into Oracle and are available for use in various appropriate SQL statements. Do not confuse SQL functions with user functions written in PL/SQL.
If you call a SQL function with an argument of a datatype other than the datatype expected by the SQL function, then Oracle implicitly converts the argument to the expected datatype before performing the SQL function. If you call a SQL function with a null argument, then the SQL function automatically returns null. The only SQL functions that do not necessarily follow this behavior are
In the syntax diagrams for SQL functions, arguments are indicated by their datatypes. When the parameter "function" appears in SQL syntax, replace it with one of the functions described in this section. Functions are grouped by the datatypes of their arguments and their return values.
When you apply SQL functions to LOB columns, Oracle creates temporary LOBs during SQL and PL/SQL processing. You should ensure that temporary tablespace quota is sufficient for storing these temporary LOBs for your application.
The syntax showing the categories of functions follows:
The sections that follow list the built-in SQL functions in each of the groups illustrated in the preceding diagrams except user-defined functions. All of the built-in SQL functions are then described in alphabetical order. User-defined functions are described at the end of this chapter.
Single-row functions return a single result row for every row of a queried table or view. These functions can appear in select lists,
BY clauses, and
Number functions accept numeric input and return numeric values. Most of these functions return values that are accurate to 38 decimal digits. The transcendental functions
TANH are accurate to 36 decimal digits. The transcendental functions
ATAN2 are accurate to 30 decimal digits. The number functions are:
Character functions that return character values return values of the same datatype as the input argument.
CHARvalues are limited in length to 2000 bytes.
VARCHAR2values are limited in length to 4000 bytes.
For both of these types of functions, if the length of the return value exceeds the limit, then Oracle truncates it and returns the result without an error message.
CLOBvalues are limited to 4 GB.
CLOB functions, if the length of the return values exceeds the limit, then Oracle raises an error and returns no data.
The character functions that return character values are:
Character functions that return number values can take as their argument any character datatype.
The character functions that return number values are:
Datetime functions operate on values of the
DATE datatype. All datetime functions return a datetime or interval value of
DATE datatype, except the
MONTHS_BETWEEN function, which returns a number. The datetime functions are:
Conversion functions convert a value from one datatype to another. Generally, the form of the function names follows the convention
datatype. The first datatype is the input datatype. The second datatype is the output datatype. The SQL conversion functions are:
The following single-row functions do not fall into any of the other single-row function categories:
Aggregate functions return a single result row based on groups of rows, rather than on single rows. Aggregate functions can appear in select lists and in
HAVING clauses. They are commonly used with the
BY clause in a
SELECT statement, where Oracle divides the rows of a queried table or view into groups. In a query containing a
BY clause, the elements of the select list can be aggregate functions,
BY expressions, constants, or expressions involving one of these. Oracle applies the aggregate functions to each group of rows and returns a single result row for each group.
If you omit the
BY clause, then Oracle applies aggregate functions in the select list to all the rows in the queried table or view. You use aggregate functions in the
HAVING clause to eliminate groups from the output based on the results of the aggregate functions, rather than on the values of the individual rows of the queried table or view.
Many (but not all) aggregate functions that take a single argument accept these clauses:
DISTINCTcauses an aggregate function to consider only distinct values of the argument expression.
ALLcauses an aggregate function to consider all values, including all duplicates.
For example, the
DISTINCT average of 1, 1, 1, and 3 is 2. The
ALL average is 1.5. If you specify neither, then the default is
All aggregate functions except
GROUPING ignore nulls. You can use the
NVL function in the argument to an aggregate function to substitute a value for a null.
COUNT never returns null, but returns either a number or zero. For all the remaining aggregate functions, if the data set contains no rows, or contains only rows with nulls as arguments to the aggregate function, then the function returns null.
You can nest aggregate functions. For example, the following example calculates the average of the maximum salaries of all the departments in the sample schema
SELECT AVG(MAX(salary)) FROM employees GROUP BY department_id; AVG(MAX(SALARY)) ---------------- 10925
This calculation evaluates the inner aggregate (
salary)) for each group defined by the
BY clause (
department_id), and aggregates the results again.
The aggregate functions are:
Analytic functions compute an aggregate value based on a group of rows. They differ from aggregate functions in that they return multiple rows for each group. The group of rows is called a window and is defined by the analytic clause. For each row, a "sliding" window of rows is defined. The window determines the range of rows used to perform the calculations for the "current row". Window sizes can be based on either a physical number of rows or a logical interval such as time.
Analytic functions are the last set of operations performed in a query except for the final
BY clause. All joins and all
HAVING clauses are completed before the analytic functions are processed. Therefore, analytic functions can appear only in the select list or
Analytic functions are commonly used to compute cumulative, moving, centered, and reporting aggregates.
The keywords and parameters of this syntax are discussed in the sections that follow.
Specify the name of an analytic function (see the listing of analytic functions following this discussion of keywords and parameters).
Analytic functions take 0 to 3 arguments.
analytic_clause to indicate that the function operates on a query result set. That is, it is computed after the
HAVING clauses. You can specify analytic functions with this clause in the select list or
BY clause. To filter the results of a query based on an analytic function, nest these functions within the parent query, and then filter the results of the nested subquery.
BY clause to partition the query result set into groups based on one or more value_expr. If you omit this clause, then the function treats all rows of the query result set as a single group.
You can specify multiple analytic functions in the same query, each with the same or different
If the objects being queried have the parallel attribute, and if you specify an analytic function with the query_partition_clause, then the function computations are parallelized as well.
Valid values of value_expr are constants, columns, nonanalytic functions, function expressions, or expressions involving any of these.
Use the order_by_clause to specify how data is ordered within a partition. For all analytic functions except
PERCENTILE_DISC (which take only a single key), you can order the values in a partition on multiple keys, each defined by a value_expr and each qualified by an ordering sequence.
Within each function, you can specify multiple ordering expressions. Doing so is especially useful when using functions that rank values, because the second expression can resolve ties between identical values for the first expression.
Whenever the order_by_clause results in identical values for multiple rows, the function returns the same result for each of those rows. Please refer to the analytic example for SUM for an illustration of this behavior.
Restriction: When used in an analytic function, the order_by_clause must take an expression (expr). The
SIBLINGS keyword is not valid (it is relevant only in hierarchical queries). Position (position) and column aliases (c_alias) are invalid. Otherwise this order_by_clause is the same as that used to order the overall query or subquery.
Specify the ordering sequence (ascending or descending).
ASC is the default.
Specify whether returned rows containing nulls should appear first or last in the ordering sequence.
LAST is the default for ascending order, and
FIRST is the default for descending order.
Analytic functions always operate on rows in the order specified in the order_by_clause of the function. However, the order_by_clause of the function does not guarantee the order of the result. Use the order_by_clause of the query to guarantee the final result ordering.
Some analytic functions allow the
windowing_clause. In the listing of analytic functions at the end of this section, the functions that allow the
windowing_clause are followed by an asterisk (*).
These keywords define for each row a "window" (a physical or logical set of rows) used for calculating the function result. The function is then applied to all the rows in the window. The window "slides" through the query result set or partition from top to bottom.
You cannot specify this clause unless you have specified the order_by_clause.
The value returned by an analytic function with a logical offset is always deterministic. However, the value returned by an analytic function with a physical offset may produce nondeterministic results unless the ordering expression results in a unique ordering. You may have to specify multiple columns in the order_by_clause to achieve this unique ordering.
AND clause to specify a start point and end point for the window. The first expression (before
AND) defines the start point and the second expression (after
AND) defines the end point.
If you omit
BETWEEN and specify only one end point, then Oracle considers it the start point, and the end point defaults to the current row.
PRECEDING to indicate that the window starts at the first row of the partition. This is the start point specification and cannot be used as an end point specification.
FOLLOWING to indicate that the window ends at the last row of the partition. This is the end point specification and cannot be used as a start point specification.
As a start point,
ROW specifies that the window begins at the current row or value (depending on whether you have specified
RANGE, respectively). In this case the end point cannot be value_expr
As an end point,
ROW specifies that the window ends at the current row or value (depending on whether you have specified
RANGE, respectively). In this case the start point cannot be value_expr
FOLLOWINGis the start point, then the end point must be value_expr
PRECEDINGis the end point, then the start point must be value_expr
If you are defining a logical window defined by an interval of time in numeric format, then you may need to use conversion functions.
If you specified
If you specified
"Literals" for information on interval literals
exprmust be a
exprmust be a
If you omit the windowing_clause entirely, then the default is
Analytic functions are commonly used in data warehousing environments. The analytic functions follow. Functions followed by an asterisk (*) allow the full syntax, including the
Oracle9i Data Warehousing Guide for more information on these functions, and for scenarios illustrating their use
Object reference functions manipulate REFs, which are references to objects of specified object types. The object reference functions are:
Oracle9i Database Concepts and Oracle9i Application Developer's Guide - Fundamentals for more information about REFs
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