title | summary | toc |
---|---|---|
ALTER COLUMN |
Use the ALTER COLUMN statement to set, change, or drop a column's DEFAULT constraint or to drop the NOT NULL constraint. |
true |
The ALTER COLUMN
statement is part of ALTER TABLE
and can be used to:
- Set, change, or drop a column's
DEFAULT
constraint - Set or drop a column's
NOT NULL
constraint - Change a column's data type
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To manage other constraints, see ADD CONSTRAINT
and DROP CONSTRAINT
.
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{{site.data.alerts.callout_info}} Support for altering column types is experimental, with certain limitations. For details, see Altering column data types. {{site.data.alerts.end}}
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The user must have the CREATE
privilege on the table.
Parameter | Description |
---|---|
table_name |
The name of the table with the column you want to modify. |
column_name |
The name of the column you want to modify. |
SET DEFAULT a_expr |
The new Default Value you want to use. |
typename |
The new data type you want to use. Support for altering column types is experimental, with certain limitations. For details, see Altering column data types. |
USING a_expr |
Specifies how to compute a new column value from the old column value. |
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Support for altering column data types is experimental, with certain limitations. To enable column type altering, set the enable_experimental_alter_column_type_general
session variable to true
.
The following are equivalent in CockroachDB:
ALTER TABLE ... ALTER ... TYPE
ALTER TABLE ... ALTER COLUMN TYPE
ALTER TABLE ... ALTER COLUMN SET DATA TYPE
For examples of ALTER COLUMN TYPE
, Examples.
You cannot alter the data type of a column if:
- The column is part of an index.
- The column has
CHECK
constraints. - The column owns a sequence.
- The
ALTER COLUMN TYPE
statement is part of a combinedALTER TABLE
statement. - The
ALTER COLUMN TYPE
statement is inside an explicit transaction.
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Most ALTER COLUMN TYPE
changes are finalized asynchronously. Schema changes on the table with the altered column may be restricted, and writes to the altered column may be rejected until the schema change is finalized.
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Setting the DEFAULT
value constraint inserts the value when data's written to the table without explicitly defining the value for the column. If the column already has a DEFAULT
value set, you can use this statement to change it.
The below example inserts the Boolean value true
whenever you inserted data to the subscriptions
table without defining a value for the newsletter
column.
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> ALTER TABLE subscriptions ALTER COLUMN newsletter SET DEFAULT true;
If the column has a defined DEFAULT
value, you can remove the constraint, which means the column will no longer insert a value by default if one is not explicitly defined for the column.
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> ALTER TABLE subscriptions ALTER COLUMN newsletter DROP DEFAULT;
Setting the NOT NULL
constraint specifies that the column cannot contain NULL
values.
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> ALTER TABLE subscriptions ALTER COLUMN newsletter SET NOT NULL;
If the column has the NOT NULL
constraint applied to it, you can remove the constraint, which means the column becomes optional and can have NULL values written into it.
{% include_cached copy-clipboard.html %}
> ALTER TABLE subscriptions ALTER COLUMN newsletter DROP NOT NULL;
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The TPC-C database has a customer
table with a column c_credit_lim
of type DECIMAL(10,2)
:
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> SELECT column_name, data_type FROM [SHOW COLUMNS FROM customer] WHERE column_name='c_credit_lim';
column_name | data_type
---------------+----------------
c_credit_lim | DECIMAL(10,2)
(1 row)
Suppose you want to change the data type from DECIMAL
to STRING
.
First, set the enable_experimental_alter_column_type_general
session variable to true
:
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> SET enable_experimental_alter_column_type_general = true;
Then, alter the column type:
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> ALTER TABLE customer ALTER c_credit_lim TYPE STRING;
NOTICE: ALTER COLUMN TYPE changes are finalized asynchronously; further schema changes on this table may be restricted until the job completes; some writes to the altered column may be rejected until the schema change is finalized
{% include_cached copy-clipboard.html %}
> SELECT column_name, data_type FROM [SHOW COLUMNS FROM customer] WHERE column_name='c_credit_lim';
column_name | data_type
---------------+------------
c_credit_lim | STRING
(1 row)
The TPC-C customer
table contains a column c_balance
of type DECIMAL(12,2)
:
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> SELECT column_name, data_type FROM [SHOW COLUMNS FROM customer] WHERE column_name='c_balance';
column_name | data_type
--------------+----------------
c_balance | DECIMAL(12,2)
(1 row)
Suppose you want to increase the precision of the c_balance
column from DECIMAL(12,2)
to DECIMAL(14,2)
:
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> ALTER TABLE customer ALTER c_balance TYPE DECIMAL(14,2);
{% include_cached copy-clipboard.html %}
> SELECT column_name, data_type FROM [SHOW COLUMNS FROM customer] WHERE column_name='c_balance';
column_name | data_type
--------------+----------------
c_balance | DECIMAL(14,2)
(1 row)
You can change the data type of a column and create a new, computed value from the old column values, with a USING
clause. For example:
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> SELECT column_name, data_type FROM [SHOW COLUMNS FROM customer] WHERE column_name='c_discount';
column_name | data_type
--------------+---------------
c_discount | DECIMAL(4,4)
(1 row)
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> SELECT c_discount FROM customer LIMIT 10;
c_discount
--------------
0.1569
0.4629
0.2932
0.0518
0.3922
0.1106
0.0622
0.4916
0.3072
0.0316
(10 rows)
{% include_cached copy-clipboard.html %}
> ALTER TABLE customer ALTER c_discount TYPE STRING USING ((c_discount*100)::DECIMAL(4,2)::STRING || ' percent');
NOTICE: ALTER COLUMN TYPE changes are finalized asynchronously; further schema changes on this table may be restricted until the job completes; some writes to the altered column may be rejected until the schema change is finalized
{% include_cached copy-clipboard.html %}
> SELECT column_name, data_type FROM [SHOW COLUMNS FROM customer] WHERE column_name='c_discount';
column_name | data_type
--------------+------------
c_discount | STRING
(1 row)
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> SELECT c_discount FROM customer LIMIT 10;
c_discount
-----------------
15.69 percent
46.29 percent
29.32 percent
5.18 percent
39.22 percent
11.06 percent
6.22 percent
49.16 percent
30.72 percent
3.16 percent
(10 rows)