What's the Difference Between SQL's `IS NULL` and `= NULL` Operators?
In-depth understanding of the IS NULL
and = NULL
operators in SQL
The IS NULL
and = NULL
operators in SQL behave differently when dealing with NULL values, which often confuses beginners. This article explains the key differences between them in detail.
= NULL
Contrary to the literal meaning, = NULL
does not return true when the value being checked is NULL. It operates based on three-valued logic, where NULL represents an unknown value. In a WHERE
clause, = NULL
is interpreted as false, causing the corresponding row to be excluded from the result set.
IS NULL
In contrast, IS NULL
explicitly tests for NULL values and returns true if the value being checked is NULL and false otherwise. This behavior is consistent with the actual situation where NULL represents an unknown or missing value.
When to use which operator
Now that you understand these differences, here are the appropriate scenarios for using each operator:
-
= NULL
: Use when you need to exclude rows with unknown values from the result set. This includes rows where the value is NULL or may be NULL. -
IS NULL
: Use this operator to specifically check if a value is NULL. It is particularly useful when you want to retrieve rows that explicitly contain NULL values.
Example
Consider a table containing the following data:
ID | Name | Age |
---|---|---|
1 | John | 25 |
2 | Mary | NULL |
3 | Bob | 30 |
Query 1:
SELECT * FROM Table WHERE Age = NULL;
Result:
returns no rows because the WHERE
clause treats the = NULL
condition as false, thus eliminating rows with NULL values.
Query 2:
SELECT * FROM Table WHERE Age IS NULL;
Result:
returns row 2 (Mary) because the WHERE
clause uses IS NULL
to only check for NULL values.
Conclusion
When writing SQL queries, it is crucial to understand the difference between IS NULL
and = NULL
. Choosing the right operator based on your specific needs ensures accurate and meaningful results.
The above is the detailed content of What's the Difference Between SQL's `IS NULL` and `= NULL` Operators?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

Full table scanning may be faster in MySQL than using indexes. Specific cases include: 1) the data volume is small; 2) when the query returns a large amount of data; 3) when the index column is not highly selective; 4) when the complex query. By analyzing query plans, optimizing indexes, avoiding over-index and regularly maintaining tables, you can make the best choices in practical applications.

Yes, MySQL can be installed on Windows 7, and although Microsoft has stopped supporting Windows 7, MySQL is still compatible with it. However, the following points should be noted during the installation process: Download the MySQL installer for Windows. Select the appropriate version of MySQL (community or enterprise). Select the appropriate installation directory and character set during the installation process. Set the root user password and keep it properly. Connect to the database for testing. Note the compatibility and security issues on Windows 7, and it is recommended to upgrade to a supported operating system.

InnoDB's full-text search capabilities are very powerful, which can significantly improve database query efficiency and ability to process large amounts of text data. 1) InnoDB implements full-text search through inverted indexing, supporting basic and advanced search queries. 2) Use MATCH and AGAINST keywords to search, support Boolean mode and phrase search. 3) Optimization methods include using word segmentation technology, periodic rebuilding of indexes and adjusting cache size to improve performance and accuracy.

The difference between clustered index and non-clustered index is: 1. Clustered index stores data rows in the index structure, which is suitable for querying by primary key and range. 2. The non-clustered index stores index key values and pointers to data rows, and is suitable for non-primary key column queries.

MySQL is an open source relational database management system. 1) Create database and tables: Use the CREATEDATABASE and CREATETABLE commands. 2) Basic operations: INSERT, UPDATE, DELETE and SELECT. 3) Advanced operations: JOIN, subquery and transaction processing. 4) Debugging skills: Check syntax, data type and permissions. 5) Optimization suggestions: Use indexes, avoid SELECT* and use transactions.

MySQL and MariaDB can coexist, but need to be configured with caution. The key is to allocate different port numbers and data directories to each database, and adjust parameters such as memory allocation and cache size. Connection pooling, application configuration, and version differences also need to be considered and need to be carefully tested and planned to avoid pitfalls. Running two databases simultaneously can cause performance problems in situations where resources are limited.

In MySQL database, the relationship between the user and the database is defined by permissions and tables. The user has a username and password to access the database. Permissions are granted through the GRANT command, while the table is created by the CREATE TABLE command. To establish a relationship between a user and a database, you need to create a database, create a user, and then grant permissions.

Data Integration Simplification: AmazonRDSMySQL and Redshift's zero ETL integration Efficient data integration is at the heart of a data-driven organization. Traditional ETL (extract, convert, load) processes are complex and time-consuming, especially when integrating databases (such as AmazonRDSMySQL) with data warehouses (such as Redshift). However, AWS provides zero ETL integration solutions that have completely changed this situation, providing a simplified, near-real-time solution for data migration from RDSMySQL to Redshift. This article will dive into RDSMySQL zero ETL integration with Redshift, explaining how it works and the advantages it brings to data engineers and developers.
