How to randomly select rows in SQL?

sql

randomness

performance-tuning

database-management

byAnton Shumikhin·Oct 31, 2024

Retrieve 10 random rows by applying the following statements in the corresponding SQL platforms:

SQL Server:

SELECT TOP 10 * FROM TableName ORDER BY NEWID();  -- Shuffle it like you're in Vegas!

MySQL/SQLite:

SELECT * FROM TableName ORDER BY RAND() LIMIT 10;  -- Randomizing rows as if you're picking lottery numbers.

PostgreSQL:

SELECT * FROM TableName ORDER BY RANDOM() LIMIT 10;  -- Spins the wheel of randomness and fetches 10 rows.

Understand that each script above will give you 10 randomly selected entries from TableName.

How SQL generates randomness

Random row selection is a feature provided by SQL, which is supported differently depending on the database management system (DBMS) you use. The results can be entirely unpredictable, akin to plucking a mystery book from a library shelf.

Diversity in SQL randomness

Oracle: Oracle uses dbms_random.value within a subquery to bring randomness. You can limit the rows returned using rownum.

SELECT * FROM (SELECT * FROM TableName ORDER BY dbms_random.value) WHERE rownum <= 10; -- Oracle's magic trick for shuffling rows.

IBM DB2: DB2 uses ORDER BY RAND() and limits the rows selected with FETCH FIRST n ROWS ONLY.

SELECT * FROM TableName ORDER BY RAND() FETCH FIRST 10 ROWS ONLY;  -- IBM DB2's version of "Pick a card, any card!"

Tuning the engine for better performance

Large tables can pose performance challenges when randomized functions like RAND() or NEWID() are applied on every row. SQL Server provides an efficient alternative: the TABLESAMPLE clause.

SELECT * FROM TableName TABLESAMPLE (10 PERCENT);  -- It's like getting a lucky dip from the DBMS bucket!

Bear in mind, the TABLESAMPLE may result in unevenly distributed selection in large datasets. Thus, it requires fine-tuning to achieve true randomness.

Optimize performance on big data tables by limiting the rows before shuffling.

SELECT TOP 10 * FROM (SELECT * FROM TableName WHERE SomeCondition = true) AS FilteredTable ORDER BY NEWID(); --A little pre-shuffling filtering never hurt anyone!

Test variations of SQL commands and assimilate them with your specific dataset and schema to ensure optimal balance between speed and randomness.

Team up with indexes

Remember, indexes can fast-track your database lookups and significantly improve your query performance. While indexes do not contribute to direct random selection, they are instrumental in pre-filtering rows before applying a randomizing function.

Practicality and variations of SQL randomness

Randomness in SQL finds utility in a range of practical scenarios:

Testing software components

Random row selection can help cover different aspects and edge cases when testing database operations or functionality, akin to randomly picking bugs from a bug jar.

Leveling up game development

Randomness is a crucial element in game development, required for unpredictable event triggers or loot drops. SQL's random functions can be a game-changer, literally!

Tapping into data science

Random sampling in data science can help obtain a diverse data set for statistical analysis or algorithm training in machine learning. It's like randomly picking brains for your AI!

Steering clear of pitfalls

Missteps lurk around the corner when dealing with SQL randomness:

Overuse of ORDER BY RAND() and similar functions can lead to performance inefficiency.
Functions like RAND() and RANDOM() behave differently across DBMSs; watch out for differences in seed behavior.
Be extra wary while utilizing randomly sorted subqueries in joins. They can be a double-edged sword if not handled carefully.