Direct Explanation
IS NULL and IS NOT NULL are SQL operators used to check whether a column’s value is missing (NULL) or present (not NULL). A NULL in a database represents the absence of a value—it is not the same as an empty string, zero, or any default value. IS NULL filters rows where the specified column has no value, while IS NOT NULL filters rows where the column contains any non-NULL value. For example, in a table storing user data with an optional phone_number column, WHERE phone_number IS NULL would return users who haven’t provided a phone number, while WHERE phone_number IS NOT NULL would return those who have.
Use Cases and Examples
These operators are essential for data validation, cleanup, and conditional logic. Suppose you have an orders table with a shipped_date column. Using WHERE shipped_date IS NULL could help identify unshipped orders that require action. Conversely, WHERE shipped_date IS NOT NULL might be used to calculate average shipping times. Another example involves joins: if a customer_id in an orders table is nullable, IS NULL could identify orphaned orders (e.g., guest checkouts), while IS NOT NULL ensures only orders linked to valid customers are included.
Common Pitfalls and Best Practices
A common mistake is using = NULL or != NULL instead of IS NULL/IS NOT NULL. In SQL, equality checks like = NULL always return NULL (effectively false), making the operators mandatory for accurate filtering. Additionally, NULL values are excluded from aggregate functions like SUM() or AVG(), so combining IS NOT NULL with these functions is redundant. For instance, SELECT AVG(price) FROM products WHERE price IS NOT NULL is equivalent to SELECT AVG(price) FROM products since AVG() inherently skips NULLs. Always use IS NULL/IS NOT NULL explicitly to avoid logical errors in queries.