NULL / NVL / NVL2

Nulls

If a column in a row has no value, then the column is said to be null, or to contain null. Nulls can appear in columns of any datatype that are not restricted by NOT NULL or PRIMARY KEY integrity constraints. Use a null when the actual value is not known or when a value would not be meaningful.

Oracle Database treats a character value with a length of zero as null. However, do not use null to represent a numeric value of zero, because they are not equivalent.

Note:

Oracle Database currently treats a character value with a length of zero as null. However, this may not continue to be true in future releases, and Oracle recommends that you do not treat empty strings the same as nulls.

Any arithmetic expression containing a null always evaluates to null. For example, null added to 10 is null. In fact, all operators (except concatenation) return null when given a null operand.

Nulls in SQL Functions

Most scalar functions return null when given a null argument. You can use the NVL function to return a value when a null occurs. For example, the expression NVL(commission_pct,0) returns 0 if commission_pct is null or the value of commission_pct if it is not null.

For information on how aggregate functions handle nulls, see "Aggregate Functions".

Nulls with Comparison Conditions

To test for nulls, use only the comparison conditions IS NULL and IS NOT NULL. If you use any other condition with nulls and the result depends on the value of the null, then the result is UNKNOWN. Because null represents a lack of data, a null cannot be equal or unequal to any value or to another null. However, Oracle considers two nulls to be equal when evaluating a DECODE function. Refer to DECODE for syntax and additional information.

Oracle also considers two nulls to be equal if they appear in compound keys. That is, Oracle considers identical two compound keys containing nulls if all the non-null components of the keys are equal.

Nulls in Conditions

A condition that evaluates to UNKNOWN acts almost like FALSE. For example, a SELECT statement with a condition in the WHERE clause that evaluates to UNKNOWN returns no rows. However, a condition evaluating to UNKNOWN differs from FALSE in that further operations on an UNKNOWN condition evaluation will evaluate to UNKNOWN. Thus, NOT FALSE evaluates to TRUE, but NOT UNKNOWN evaluates to UNKNOWN.

Table 2-20 shows examples of various evaluations involving nulls in conditions. If the conditions evaluating to UNKNOWN were used in a WHERE clause of a SELECT statement, then no rows would be returned for that query.

Table 2-20 Conditions Containing Nulls

Condition	Value of A	Evaluation
a IS NULL	10	FALSE
a IS NOT NULL	10	TRUE
a IS NULL	NULL	TRUE
a IS NOT NULL	NULL	FALSE
a = NULL	10	UNKNOWN
a != NULL	10	UNKNOWN
a = NULL	NULL	UNKNOWN
a != NULL	NULL	UNKNOWN
a = 10	NULL	UNKNOWN
a != 10	NULL	UNKNOWN

NVL

Syntax

Description of the illustration nvl.gif

Purpose

NVL lets you replace null (returned as a blank) with a string in the results of a query. If expr1 is null, then NVL returns expr2. If expr1 is not null, then NVL returns expr1.

The arguments expr1 and expr2 can have any datatype. If their datatypes are different, then Oracle Database implicitly converts one to the other. If they are cannot be converted implicitly, the database returns an error. The implicit conversion is implemented as follows:

• If expr1 is character data, then Oracle Database converts expr2 to the datatype of expr1 before comparing them and returns VARCHAR2 in the character set of expr1.

• If expr1 is numeric, then Oracle determines which argument has the highest numeric precedence, implicitly converts the other argument to that datatype, and returns that datatype.

  See Also:

  Table 2-10, "Implicit Type Conversion Matrix" for more information on implicit conversion and "Numeric Precedence" for information on numeric precedence

Examples

The following example returns a list of employee names and commissions, substituting "Not Applicable" if the employee receives no commission:

SELECT last_name, NVL(TO_CHAR(commission_pct), 'Not Applicable')
   "COMMISSION" FROM employees
   WHERE last_name LIKE 'B%'
   ORDER BY last_name;
 
LAST_NAME                 COMMISSION
------------------------- ----------------------------------------
Baer                      Not Applicable
Baida                     Not Applicable
Banda                     .1
Bates                     .15
Bell                      Not Applicable
Bernstein                 .25
Bissot                    Not Applicable
Bloom                     .2
Bull                      Not Applicable
 

NVL2 
Syntax

Description of the illustration nvl2.gif

Purpose
NVL2 lets you determine the value returned by a query based on 
whether a specified expression is null or not null. If expr1 is not null, then NVL2 
returns expr2. If expr1 is null, then NVL2 
returns expr3.
The argument expr1 can have 
any datatype. The arguments expr2 and expr3 can have any datatypes except 
LONG.
If the datatypes of expr2 
and expr3 are different:


If expr2 is character data, 
then Oracle Database converts expr3 to the datatype of expr2 before comparing them unless 
expr3 is a null constant. In 
that case, a datatype conversion is not necessary. Oracle returns 
VARCHAR2 in the character set of expr2.

If expr2 is numeric, then 
Oracle determines which argument has the highest numeric precedence, implicitly 
converts the other argument to that datatype, and returns that datatype.

See Also:
Table 2-10, 
"Implicit Type Conversion Matrix" for more information on implicit 
conversion and "Numeric Precedence" 
for information on numeric precedence
Examples
The following example shows whether the income of some employees is made up 
of salary plus commission, or just salary, depending on whether the 
commission_pct column of employees is null or not.

SELECT last_name, salary, NVL2(commission_pct, 
   salary + (salary * commission_pct), salary) income
   FROM employees WHERE last_name like 'B%'
   ORDER BY last_name;

LAST_NAME                     SALARY     INCOME
------------------------- ---------- ----------
Baer                           10000      10000
Baida                           2900       2900
Banda                           6200       6882
Bates                           7300       8468
Bell                            4000       4000
Bernstein                       9500      11970
Bissot                          3300       3300
Bloom                          10000      12100
Bull                            4100       4100