ALTER COLUMN

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The ALTER COLUMN statement is part of ALTER TABLE and can be used to:

Note:

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

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

ALTER TABLE IF EXISTS table_name ALTER COLUMN column_name SET DEFAULT a_expr NOT NULL DATA TYPE typename COLLATE collation_name USING a_expr DROP DEFAULT NOT NULL STORED TYPE typename COLLATE collation_name USING a_expr

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, altered type you want to use.
In CockroachDB versions < v21.1, support for altering column types is limited to increasing the precision of the current column type. For details, see Altering column types.
USING a_expr New in v20.2: 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 types

In CockroachDB versions < v21.1, support for altering column types is limited to increasing the precision of the current type of a column. You cannot convert the column type to another data type, or decrease the precision of the column type. Changing the column type from its current type to the same type and precision will result in a no-op, with no error.

You can use ALTER COLUMN TYPE if the following conditions are met:

  • The on-disk representation of the column remains unchanged. For example, you cannot change the column data type from STRING to an INT.
  • The existing data remains valid. For example, you can change the column data type from STRING[10] to STRING[20], but not to STRING [5] since that will invalidate the existing data.

The following are equivalent in CockroachDB:

  • ALTER TABLE ... ALTER ... TYPE
  • ALTER TABLE ... ALTER COLUMN TYPE
  • ALTER TABLE ... ALTER COLUMN SET DATA TYPE

For an example of ALTER COLUMN TYPE, see Increase a column type's precision.

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.

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> 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.

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> 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.

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> 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.

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> 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:

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> 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:

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> INSERT INTO office_dogs (id, first_name, last_name) VALUES
    (1, 'Petee', 'Hirata'),
    (2, 'Carl', 'Kimball'),
    (3, 'Ernie', 'Narayan');
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> 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:

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> 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:

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> ALTER TABLE office_dogs ALTER COLUMN full_name DROP STORED;

Check that the computed column was converted:

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> 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:

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> INSERT INTO office_dogs (id, first_name, last_name, full_name) VALUES (4, 'Lola', 'McDog', 'This is not computed');
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> 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)

Increase a column type's precision

The TPC-C database contains a customer table with a column c_credit_lim of type DECIMAL(10,2). Suppose you want to increase the precision of the column's data type to DECIMAL (12,2):

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> ALTER TABLE customer ALTER c_credit_lim type DECIMAL (12,2);
ALTER TABLE

Time: 80.814044ms

See also

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