Keeping Data Clean: How to Change Column Type and Set Not Null in PostgreSQL

Combining these actions:

While it's not strictly necessary to specify the type again, PostgreSQL allows you to combine these operations into a single statement. This can be useful when you want to change the data type and also ensure all existing data has a valid value for the new type.

Here's the syntax for this combined operation:

ALTER TABLE table_name ALTER COLUMN column_name SET DATA_TYPE USING (expression), SET NOT NULL;

Explanation of the syntax:

• ALTER TABLE table_name: This identifies the table you want to modify.
• ALTER COLUMN column_name: This specifies the particular column you're working with.
• SET DATA_TYPE USING (expression): This clause defines the new data type for the column. The expression tells PostgreSQL how to convert existing data to the new format. This is crucial to ensure data integrity during the conversion.
• SET NOT NULL: This enforces the not null constraint on the column after the data type conversion.

Important points to remember:

• Before setting not null, you must ensure there are no existing null values in that column. PostgreSQL will verify this before allowing the change.
• The USING (expression) part is essential for data type conversion. It defines how to handle potentially incompatible data during the change.

This example changes a column named "age" from text format to integer format and also sets it to not null. We assume all existing values in the "age" column can be converted to integers without errors.

ALTER TABLE users ALTER COLUMN age SET DATA_TYPE INT USING (age::int), SET NOT NULL;

In this example, the USING (age::int) part converts the existing text values in the "age" column to integers using type casting (::int).

This example changes a column named "name" from varchar (variable character length) format to varchar(50) format, limiting the length to 50 characters. It also sets the column to not null.

ALTER TABLE customers ALTER COLUMN name SET DATA_TYPE VARCHAR(50) USING (name), SET NOT NULL;

Here, the USING (name) part simply copies the existing data in the "name" column to the new varchar(50) format.

Example 3 (potential issue): Changing integer to boolean without proper conversion

This example attempts to change a column named "is_active" from integer to boolean format and set not null. However, it might encounter issues if the existing integer values don't represent clear true/false states (e.g., 1 for active, 0 for inactive).

ALTER TABLE accounts ALTER COLUMN is_active SET DATA_TYPE BOOLEAN USING (is_active::bool), SET NOT NULL;

1. Add a new column: Define a new column with the desired data type and not null constraint.
2. Migrate data: Write a separate query to copy data from the old column to the new column, potentially applying any necessary conversions during the copy process.
3. Drop old column and rename new one: Once all data is migrated, you can drop the old column and rename the new column to the original name.

This method offers more control over data conversion and allows handling potential issues with existing data before enforcing the not null constraint.

Example:

-- Add new column with desired type (assuming conversion to integer is possible)
ALTER TABLE users ADD COLUMN age_int INT NOT NULL;

-- Migrate data with conversion (assuming 1 represents active and 0 represents inactive)
UPDATE users SET age_int = CASE WHEN is_active = 1 THEN 1 ELSE 0 END;

-- Drop old column and rename new one
ALTER TABLE users DROP COLUMN is_active;
RENAME COLUMN age_int TO is_active;

Method 2: Use CHECK constraint (limited applicability)

In specific situations, you can use a CHECK constraint instead of setting not null. A CHECK constraint defines a condition that every value in the column must satisfy.

This example enforces that the "price" column must have a positive value:

ALTER TABLE products ADD CONSTRAINT check_price CHECK (price > 0);