Understanding the Key Differences Between 'IS NULL' and ' NULL' in SQL
In the context of SQL, the correct way to handle null values is crucial for accurate data retrieval. Misunderstanding or misuse can lead to incorrect queries and logical flaws. This article will explore the nuances between 'IS NULL' and ' NULL', providing a comprehensive guide for SQL practitioners.
The Correct Usage of 'IS NULL'
When working with null values in SQL, it is imperative to use 'IS NULL' for checking whether a column or value is null. This is the preferred and correct syntax because it accurately evaluates to true when a value is null, ensuring that the query performs as intended.
Syntax for Using 'IS NULL'
The correct syntax for checking null values using 'IS NULL' is as follows:
SELECT * FROM table_name WHERE column_name IS NULLThis syntax is essential for filtering out rows where the specified column contains a null value, ensuring that only records with null values in the column are included in the result set.
The Misuse of ' NULL'
On the other hand, using ' NULL' for checking null values is incorrect and will always return false. This is due to the nature of null values in SQL, which represent an unknown or undefined value. Any comparison involving null using '', including 'column_name NULL', will evaluate to null, not true or false.
Explanation of Why ' NULL' Fails
Comparing a known value with null using '' is logically flawed. In SQL, the comparison operator '' checks for equality. If one of the operands is null, the entire expression evaluates to null, which is neither true nor false. This can be understood through the concept of unknown values.
Consider a simple example: Is 113 equal to 'unknown'? The answer is clearly no, as 113 is a known value, and equal to an unknown is impossible. Similarly, SQL does not allow for a comparison with null using '' because null is not a value but a state of uncertainty.
Replacng NULL with "UNKNOWN"
To better understand this concept, imagine replacing 'NULL' with 'UNKNOWN' in your mind. The logic remains the same: it is meaningless to assert that a known value is equal to an unknown value. For instance, if you encounter two strangers on the street, they both may have a primary phone number, but we do not know what it is, making both unknown. It is unrealistic to assume they share the same phone number simply because both values are unknown.
This framework helps to clarify why 'NULL NULL' is false. Both unknown values cannot be compared and are non-equal, leading to a result of null (UNKNOWN).
SQL Best Practices
To avoid logical mistakes and ensure accurate query results, always use 'IS NULL' for checking null values. This approach ensures that your SQL queries are both correct and efficient, providing the expected results.
Example of a Correct Query Using 'IS NULL'
Here is an example of a correctly written query using 'IS NULL':
SELECT * FROM employees WHERE phone_number IS NULLThis query will return all employees who do not have a phone number recorded in the 'phone_number' column, reflecting the true state of the data.
Additional Insights
It is important to understand that in SQL, NULL is not a traditional value but a special state representing the absence of information or an unknown value. This distinction can be confusing when comparing it to its counterparts in many programming languages, where NULL typically means 'no value.' In SQL, NULL is a state of uncertainty, which is why comparisons using '' with NULL are always false.
For example, in Java, Python, or TypeScript, 'null' is used to indicate that a variable has no value. However, in SQL, NULL is used to denote a state of unknown data. This difference is crucial for understanding how SQL handles data and queries, especially when dealing with null values.
Conclusion
In summary, the correct way to handle null values in SQL is to use the 'IS NULL' clause. Misusing ' NULL' can lead to incorrect and inefficient queries. By adopting best practices and understanding the nuances of SQL's handling of null values, you can write more robust and accurate queries.