Mastering Null Values in MariaDB: Filtering and Handling Techniques

• You cannot directly compare NULL with other values using standard comparison operators (=, >, <, etc.) because any comparison with NULL always results in NULL.
• In MariaDB, NULL represents missing or inapplicable data. It's distinct from empty strings, zeros, or other values.

Why a Null Query Variable Returns No Results

When you use a variable in a MariaDB WHERE clause to filter data, and the variable has a NULL value, the query behaves as if no filtering condition exists. This means all rows are included in the result set, potentially leading to an empty set if the table itself has no rows.

Example:

CREATE TABLE users (id INT PRIMARY KEY, name VARCHAR(255));

INSERT INTO users (id, name) VALUES (1, 'Alice'), (2, 'Bob'), (3, NULL);

-- Set a variable with a NULL value
SET @user_id = NULL;

-- This query will return all rows because the WHERE clause effectively becomes WHERE 1 = 1 (always true)
SELECT * FROM users WHERE id = @user_id;

-- This query, however, will return only the row with id = 2
SELECT * FROM users WHERE id IS NULL;

How to Handle Null Values in Queries

Here are common approaches to deal with null values in MariaDB queries:

1. IS NULL Operator:

   • Use IS NULL to check if a variable or column is null.
   • Example: SELECT * FROM users WHERE id IS NULL; (returns the row with id = NULL)

2. COALESCE Function:

   • Provides a default value if the variable or column is null.
   • Example: SELECT COALESCE(@user_id, 0) AS user_id; (returns 0 if @user_id is null)

3. IFNULL Function (similar to COALESCE):

   • Offers a more concise way to handle null values.
   • Example: SELECT IFNULL(@user_id, 0) AS user_id;

Choosing the Right Approach

The best method depends on your specific needs:

• If you want a default value in place of null, choose COALESCE or IFNULL.
• If you only need to check for null values, use IS NULL.

CREATE TABLE users (id INT PRIMARY KEY, name VARCHAR(255), age INT);

INSERT INTO users (id, name, age) VALUES (1, 'Alice', 30), (2, 'Bob', 25), (3, NULL, NULL);

-- Set a variable with a NULL value
SET @user_id = 2;

-- This query filters rows where the 'id' column matches the variable value (id = 2)
SELECT * FROM users WHERE id = @user_id;

-- This query filters rows where the 'age' column is NULL
SELECT * FROM users WHERE age IS NULL;

Using COALESCE Function:

-- Same table structure and data as above

-- This query selects user ID, using 0 as the default value if @user_id is NULL
SELECT id, COALESCE(@user_id, 0) AS user_id FROM users;

Using IFNULL Function:

-- Same table structure and data as above

-- This query selects user ID, using 0 as the default value if @user_id is NULL (similar to COALESCE)
SELECT id, IFNULL(@user_id, 0) AS user_id FROM users;

These examples demonstrate how you can adapt your queries based on the scenario:

• Use COALESCE or IFNULL to provide a substitute value when a variable or column is null, helping to prevent unexpected results like empty sets.
• Use IS NULL to filter or check for null values in specific columns.

• Provide a way to define different logic based on whether a value is null or not.

CREATE TABLE orders (id INT PRIMARY KEY, customer_id INT, status VARCHAR(255));

INSERT INTO orders (id, customer_id, status) VALUES (1, 123, 'Placed'), (2, NULL, 'Pending');

SELECT id, customer_id,
  CASE WHEN customer_id IS NULL THEN 'Unknown Customer'
       ELSE customer_id
  END AS customer_info
FROM orders;

This query uses a CASE expression to display "Unknown Customer" if customer_id is null, otherwise, it displays the actual customer ID.

User-Defined Functions (UDFs):

• UDFs are more complex to implement but offer flexibility for specific needs.
• Allow you to create custom logic for handling null values in a reusable way.

GREATEST or LEAST Functions:

• Useful for selecting the non-null value between multiple expressions (including variables).

CREATE TABLE products (id INT PRIMARY KEY, price DECIMAL(10,2), discount DECIMAL(5,2));

INSERT INTO products (id, price, discount) VALUES (1, 100.00, 10.00), (2, NULL, 5.00);

-- Selects the highest price (either from the 'price' column or the discount if price is null)
SELECT id, GREATEST(price, discount) AS effective_price
FROM products;

Filtering in the Application Layer:

• This approach can be suitable for simple scenarios, but may not be efficient for complex queries or large datasets.
• Instead of handling null values entirely within the database, you can retrieve all data and perform null checks in your application code.

The best method depends on several factors:

• Application Logic: If your application has specific null handling requirements, filtering in the application layer might be more suitable.
• Performance: For large datasets, database-level filtering (using IS NULL, COALESCE, etc.) can be more efficient than application-layer filtering.
• Reusability: UDFs are ideal for reusable logic across multiple queries.
• Complexity: Case expressions and GREATEST/LEAST functions are generally simpler to implement than UDFs.