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3.3.4.6 Working with NULL Values
The NULL
value can be surprising until you
get used to it. Conceptually, NULL
means
“a missing unknown value” and it is treated
somewhat differently from other values.
To test for NULL
, use the
IS NULL
and IS
NOT NULL
operators, as shown here:
- +-----------+---------------+
- +-----------+---------------+
- | 0 | 1 |
- +-----------+---------------+
You cannot use arithmetic comparison operators such as
=
,
<
, or
<>
to
test for NULL
. To demonstrate this for
yourself, try the following query:
- +----------+-----------+----------+----------+
- +----------+-----------+----------+----------+
- +----------+-----------+----------+----------+
Because the result of any arithmetic comparison with
NULL
is also NULL
, you
cannot obtain any meaningful results from such comparisons.
In MySQL, 0
or NULL
means false and anything else means true. The default truth
value from a boolean operation is 1
.
This special treatment of NULL
is why, in
the previous section, it was necessary to determine which
animals are no longer alive using death IS NOT
NULL
instead of death <>
NULL
.
Two NULL
values are regarded as equal in a
GROUP BY
.
When doing an ORDER BY
,
NULL
values are presented first if you do
ORDER BY ... ASC
and last if you do
ORDER BY ... DESC
.
A common error when working with NULL
is to
assume that it is not possible to insert a zero or an empty
string into a column defined as NOT NULL
,
but this is not the case. These are in fact values, whereas
NULL
means “not having a
value.” You can test this easily enough by using
IS [NOT] NULL
as shown:
- +-----------+---------------+------------+----------------+
- +-----------+---------------+------------+----------------+
- | 0 | 1 | 0 | 1 |
- +-----------+---------------+------------+----------------+
Thus it is entirely possible to insert a zero or empty string
into a NOT NULL
column, as these are in
fact NOT NULL
. See
Section B.4.4.3, “Problems with NULL Values”.
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Document créé le 26/06/2006, dernière modification le 26/10/2018
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