How Can I Efficiently Perform Simple Random Sampling in MySQL?

Efficient Simple Random Sampling in MySQL Databases

Sampling data from large databases is often necessary for statistical analysis or subsampling for further processing. One commonly encountered problem is selecting a simple random sample from a MySQL database containing millions of rows.

The naive approach of SELECT * FROM table ORDER BY RAND() LIMIT 10000 has a significant performance overhead due to the necessity of sorting the entire table. As the table size increases, this approach becomes prohibitively slow.

Efficient Solution

A more efficient approach is to leverage MySQL's ability to generate random numbers. The query SELECT * FROM table WHERE rand() <= .3 provides a straightforward solution:

• rand(): Generates a random float between 0 and 1.
• <= .3: Filters rows where the random number is less than or equal to 0.3, effectively selecting a sample of approximately 30% of the table.

This approach has several advantages:

• O(n) Complexity: It iterates over the table only once, without requiring sorting.
• Uniform Distribution: rand() generates numbers in a uniform distribution, ensuring a fair representation of the entire table.
• MySQL Optimization: MySQL is optimized for generating random numbers efficiently.

By sampling a larger subset of the table (e.g., 2-5x the desired sample size), indexing a random column on insertion or update, and then filtering on that index, it is possible to further optimize the sampling process. This method offers the benefits of index scan performance and allows for greater precision in sample size.

In summary, the SELECT * FROM table WHERE rand() <= .3 query provides an efficient and accurate way to extract a simple random sample from MySQL tables. This approach is particularly suitable for datasets containing millions of rows or more.

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