When working with databases, sometimes we need randomness—whether it’s for selecting random records, generating random values, or shuffling data. SQL provides different ways to generate randomness depending on the database system being used. In this article, I’ll walk you through how RANDOM works in SQL, the best methods for using it, and practical examples across different database engines.
Understanding RANDOM in Different SQL Databases
There is no universal RANDOM() function that works identically across all SQL databases. Different engines implement randomness in their own way. Here’s a quick breakdown of how the randomization function is named and used in some popular database systems:
| Database System | Random Function |
|---|---|
| PostgreSQL | RANDOM() |
| MySQL | RAND() |
| SQLite | RANDOM() |
| SQL Server | NEWID() (for random row selection) |
Selecting Random Records from a Table
One common use case for randomness in SQL is selecting a random row. Here’s how you can achieve that in different database management systems:
MySQL and MariaDB
To fetch a random row in MySQL, you can use the ORDER BY RAND() clause:
SELECT * FROM users ORDER BY RAND() LIMIT 1;However, ordering a large dataset with RAND() can be very inefficient, as it forces all rows to be sorted. A more efficient method might involve using a random primary key approach.
PostgreSQL
In PostgreSQL, a similar method is achieved using RANDOM():
SELECT * FROM users ORDER BY RANDOM() LIMIT 1;Unlike MySQL, this does not suffer from significant performance issues in small to medium datasets.
SQL Server
SQL Server works differently—it doesn’t have a RANDOM() function for sorting results directly. Instead, we can use NEWID():
SELECT TOP 1 * FROM users ORDER BY NEWID();This randomizes the order based on unique identifiers but is not truly “random” in the mathematical sense.
Generating Random Numbers in SQL
Generating random numbers can be useful for various applications, such as assigning temporary unique values or creating test data.
Random Number in PostgreSQL
SELECT RANDOM();This returns a random float number between 0 and 1. To generate a number in a specific range, you can scale it like this:
SELECT FLOOR(RANDOM() * 10) + 1 AS random_number;Random Number in MySQL
MySQL’s RAND() works similarly:
SELECT RAND();To get an integer within a range:
SELECT FLOOR(RAND() * 10) + 1 AS random_number;SQL Server’s Solution: Using CHECKSUM
SQL Server does not have a built-in RANDOM() function, but you can achieve the same result using:
SELECT ABS(CHECKSUM(NEWID())) % 10 + 1 AS random_number;Generating Random Strings
Sometimes, you need to generate random strings, such as unique identifiers for testing or token generation.
PostgreSQL
SELECT md5(RANDOM()::text) AS random_string;MySQL
SELECT UUID();While not truly random, UUID() in MySQL generates a unique identifier that is functionally similar.
Best Practices for Using RANDOM in SQL
Random functions in SQL should be used carefully, especially in large datasets. Here are some best practices:
- Avoid using
ORDER BY RAND()on very large tables due to performance issues. - For random selections in SQL Server, use
NEWID()wisely and consider indexed approaches. - If you frequently need random values, consider caching results instead of executing
RANDOM()on every query.
Conclusion
Understanding how RANDOM works in SQL allows you to make better decisions when working with databases. Whether you need random row selection, number generation, or unique tokens, different SQL engines have varying solutions. By optimizing queries and avoiding performance pitfalls, you can effectively incorporate randomness into your SQL workflows.
Other interesting article:
How EXP works in SQL? Best EXP examples