ALTER COLUMN

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

Note:

To manage other constraints, see ADD CONSTRAINT and DROP CONSTRAINT.

Note:

Support for altering column types is experimental, with certain limitations. For details, see Altering column data types.

Tip:

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 can alter the data type of a column if:

The column is not part of an index.
The column does not have CHECK constraints.
The column does not own a sequence.
The ALTER COLUMN TYPE statement is not part of a combined ALTER TABLE statement.
The ALTER COLUMN TYPE statement is not inside an explicit transaction.

Note:

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)

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)

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Synopsis

Required privileges

Parameters

Viewing schema changes

Altering column data types

Limitations on altering data types

Examples

Set or change a `DEFAULT` value

Remove `DEFAULT` constraint

Set `NOT NULL` constraint

Remove `NOT NULL` constraint

Convert a computed column into a regular column

Convert to a different data type

Change a column type's precision

Change a column's type using an expression

See also

CockroachDB

CockroachCloud

CockroachDB

CockroachCloud

ALTER COLUMN

Synopsis

Required privileges

Parameters

Viewing schema changes

Altering column data types

Limitations on altering data types

Examples

Set or change a DEFAULT value

Remove DEFAULT constraint

Set NOT NULL constraint

Remove NOT NULL constraint

Convert a computed column into a regular column

Convert to a different data type

Change a column type's precision

Change a column's type using an expression

See also

Set or change a `DEFAULT` value

Remove `DEFAULT` constraint

Set `NOT NULL` constraint

Remove `NOT NULL` constraint