SQL Techniques: Identifying Empty and Missing Information

1. NULL Values: These represent missing information or data that isn't applicable.
2. Empty Strings: These are strings that contain nothing, but they are different from NULL.

Here's how to check for each:

• Checking for NULL:

  • You cannot use the equal (=) or not equal (<>) operators with NULL.
  • Instead, use the IS NULL operator.
  • For example: SELECT * FROM table_name WHERE column_name IS NULL will return rows where column_name has no value assigned.
  • To check for the opposite (not NULL), use IS NOT NULL.

• Checking for Empty Strings:

  • There are a few ways to handle empty strings:
    • Simplest approach: column_name <> '' (This checks if the column value is not equal to an empty string).
    • Alternative: (column_name = '') IS NOT FALSE (This achieves the same result but might be less readable).
  • Important Note: Don't use column_name = '' directly. This can be misleading with char(n) data types where empty strings are padded with spaces.

Here are some additional points to consider:

• Coalesce function: This function allows you to provide a default value if the column is NULL. For example: COALESCE(column_name, 'default_value') will return 'default_value' if column_name is NULL.
• Clarity and Readability: Choose the approach that makes your code easiest to understand for yourself and others.

This query selects all rows from the "users" table where the "email" column is NULL:

SELECT * FROM users WHERE email IS NULL;

This query selects the "username" and "id" from "users" where "country" is not NULL:

SELECT username, id FROM users WHERE country IS NOT NULL;

This query selects all rows from "products" where the "description" column is an empty string:

SELECT * FROM products WHERE description = '';

Alternative (might be less readable):

SELECT * FROM products WHERE (description = '') IS NOT FALSE;

This query retrieves the "product_id" and "name" from "products" where the "description" is not an empty string:

SELECT product_id, name FROM products WHERE description <> '';

Using COALESCE function:

This query selects "username" and applies COALESCE. If "nickname" is NULL, "No Nickname" is displayed:

SELECT username, COALESCE(nickname, 'No Nickname') AS full_name
FROM users;

This function takes two arguments. It returns the first argument if the second argument is NULL, otherwise it returns NULL. Here's an example:

SELECT * FROM users
WHERE NULLIF(email, '') IS NOT NULL;  -- Selects rows with non-empty email addresses

This query selects all rows from "users" where the "email" column is not an empty string. It achieves this by checking if NULLIF(email, '') is not NULL. If the email is empty, NULLIF would return NULL, making the entire condition false.

CASE expression:

You can leverage a CASE expression to handle NULL and empty string scenarios together. Here's an example:

SELECT * FROM products
CASE WHEN description IS NULL THEN 'No Description'
     WHEN description = '' THEN 'Empty Description'
     ELSE description
END AS description_status
FROM products;

This query selects all rows from "products" and creates a new column "description_status". It uses a CASE expression to check for NULL and empty string conditions. It assigns labels like "No Description" or "Empty Description" accordingly. Otherwise, it returns the original description.

Custom function (for specific needs):

For complex scenarios, you can create a custom function that defines your specific logic for handling empty or null values. This function could perform additional checks or manipulations based on your data types and requirements.

Choosing the right method:

The best method depends on your specific needs and the complexity of your logic.

• For simple checks, IS NULL and string comparisons are sufficient.
• For replacing NULL values with defaults, COALESCE is a good option.
• For more intricate logic or data manipulation, NULLIF or a CASE expression might be suitable.
• For highly customized handling, a custom function could be the way to go.