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
To manage other constraints, see ADD CONSTRAINT
and DROP CONSTRAINT
.
Support for altering column types is experimental, with certain limitations. For details, see Altering column data types.
This command can be combined with other ALTER TABLE
commands in a single statement. For a list of commands that can be combined, see ALTER TABLE
. For a demonstration, see Add and rename columns atomically.
Synopsis
Required privileges
The user must have the CREATE
privilege on the table.
Parameters
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. |
Viewing schema changes
This schema change statement is registered as a job. You can view long-running jobs with SHOW JOBS
.
Altering column data types
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.
Limitations on altering data types
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.
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.
Examples
Set or change a DEFAULT
value
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.
> ALTER TABLE subscriptions ALTER COLUMN newsletter SET DEFAULT true;
Remove DEFAULT
constraint
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.
> ALTER TABLE subscriptions ALTER COLUMN newsletter DROP DEFAULT;
Set NOT NULL
constraint
Setting the NOT NULL
constraint specifies that the column cannot contain NULL
values.
> ALTER TABLE subscriptions ALTER COLUMN newsletter SET NOT NULL;
Remove NOT NULL
constraint
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.
> ALTER TABLE subscriptions ALTER COLUMN newsletter DROP NOT NULL;
Convert a computed column into a regular column
You can convert a stored, computed column into a regular column by using ALTER TABLE
.
In this example, create a simple table with a computed column:
> CREATE TABLE office_dogs (
id INT PRIMARY KEY,
first_name STRING,
last_name STRING,
full_name STRING AS (CONCAT(first_name, ' ', last_name)) STORED
);
Then, insert a few rows of data:
> INSERT INTO office_dogs (id, first_name, last_name) VALUES
(1, 'Petee', 'Hirata'),
(2, 'Carl', 'Kimball'),
(3, 'Ernie', 'Narayan');
> SELECT * FROM office_dogs;
+----+------------+-----------+---------------+
| id | first_name | last_name | full_name |
+----+------------+-----------+---------------+
| 1 | Petee | Hirata | Petee Hirata |
| 2 | Carl | Kimball | Carl Kimball |
| 3 | Ernie | Narayan | Ernie Narayan |
+----+------------+-----------+---------------+
(3 rows)
The full_name
column is computed from the first_name
and last_name
columns without the need to define a view. You can view the column details with the SHOW COLUMNS
statement:
> SHOW COLUMNS FROM office_dogs;
+-------------+-----------+-------------+----------------+------------------------------------+-------------+
| column_name | data_type | is_nullable | column_default | generation_expression | indices |
+-------------+-----------+-------------+----------------+------------------------------------+-------------+
| id | INT | false | NULL | | {"primary"} |
| first_name | STRING | true | NULL | | {} |
| last_name | STRING | true | NULL | | {} |
| full_name | STRING | true | NULL | concat(first_name, ' ', last_name) | {} |
+-------------+-----------+-------------+----------------+------------------------------------+-------------+
(4 rows)
Now, convert the computed column (full_name
) to a regular column:
> ALTER TABLE office_dogs ALTER COLUMN full_name DROP STORED;
Check that the computed column was converted:
> SHOW COLUMNS FROM office_dogs;
+-------------+-----------+-------------+----------------+-----------------------+-------------+
| column_name | data_type | is_nullable | column_default | generation_expression | indices |
+-------------+-----------+-------------+----------------+-----------------------+-------------+
| id | INT | false | NULL | | {"primary"} |
| first_name | STRING | true | NULL | | {} |
| last_name | STRING | true | NULL | | {} |
| full_name | STRING | true | NULL | | {} |
+-------------+-----------+-------------+----------------+-----------------------+-------------+
(4 rows)
The computed column is now a regular column and can be updated as such:
> INSERT INTO office_dogs (id, first_name, last_name, full_name) VALUES (4, 'Lola', 'McDog', 'This is not computed');
> SELECT * FROM office_dogs;
+----+------------+-----------+----------------------+
| id | first_name | last_name | full_name |
+----+------------+-----------+----------------------+
| 1 | Petee | Hirata | Petee Hirata |
| 2 | Carl | Kimball | Carl Kimball |
| 3 | Ernie | Narayan | Ernie Narayan |
| 4 | Lola | McDog | This is not computed |
+----+------------+-----------+----------------------+
(4 rows)
Alter the formula for a computed column
To alter the formula for a computed column, you must DROP
and ADD
the column back with the new definition. Take the following table for instance:
> CREATE TABLE x (
a INT NULL,
b INT NULL AS (a * 2) STORED,
c INT NULL AS (a + 4) STORED,
FAMILY "primary" (a, b, rowid, c)
);
CREATE TABLE
Time: 4ms total (execution 4ms / network 0ms)
Add a computed column d
:
> ALTER TABLE x ADD COLUMN d INT AS (a // 2) STORED;
ALTER TABLE
Time: 199ms total (execution 199ms / network 0ms)
If you try to alter it, you'll get an error:
> ALTER TABLE x ALTER COLUMN d INT AS (a // 3) STORED;
invalid syntax: statement ignored: at or near "int": syntax error
SQLSTATE: 42601
DETAIL: source SQL:
ALTER TABLE x ALTER COLUMN d INT AS (a // 3) STORED
^
HINT: try \h ALTER TABLE
However, you can drop it and then add it with the new definition:
> SET sql_safe_updates = false;
> ALTER TABLE x DROP COLUMN d;
> ALTER TABLE x ADD COLUMN d INT AS (a // 3) STORED;
> SET sql_safe_updates = true;
SET
Time: 1ms total (execution 0ms / network 0ms)
ALTER TABLE
Time: 195ms total (execution 195ms / network 0ms)
ALTER TABLE
Time: 186ms total (execution 185ms / network 0ms)
SET
Time: 0ms total (execution 0ms / network 0ms)
Convert to a different data type
The TPC-C database has a customer
table with a column c_credit_lim
of type DECIMAL(10,2)
:
> 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
:
> SET enable_experimental_alter_column_type_general = true;
Then, alter the column type:
> 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
> 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)
Change a column type's precision
The TPC-C customer
table contains a column c_balance
of type DECIMAL(12,2)
:
> 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)
:
> ALTER TABLE customer ALTER c_balance TYPE DECIMAL(14,2);
> 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)
Change a column's type using an expression
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:
> 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)
> 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)
> 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
> SELECT column_name, data_type FROM [SHOW COLUMNS FROM customer] WHERE column_name='c_discount';
column_name | data_type
--------------+------------
c_discount | STRING
(1 row)
> 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)