How Can I Efficiently Extract a Simple Random Sample from a Large MySQL Database?

Utilizing Efficient Simple Random Sampling in MySQL

Problem Statement:

Extracting a Simple Random Sample (SRS) from a large MySQL database efficiently can be challenging using the "obvious" approach (SELECT * FROM table ORDER BY RAND() LIMIT n). This method's inefficiency stems from its usage of RAND() for each row and subsequent sorting, resulting in resource-intensive O(n lg n) complexity.

Efficient Solution:

To overcome this hurdle, consider employing a more efficient approach:

SELECT * FROM table WHERE RAND() <= 0.3

This solution outperforms the "obvious" method due to its ability to generate a random number for each row between 0 and 1, then evaluate whether to display that row based on a probability threshold (0.3 in this case).

Explanation:

• O(n) Complexity: This method operates in O(n) time, as it does not require sorting the rows compared to the O(n lg n) complexity of the naive approach.
• MySQL's Random Number Generation: MySQL is well-equipped to generate unique random numbers for each row, making this method a viable option.
• Assumption: The randomness assumption underlies this solution, assuming that RAND() generates numbers uniformly distributed.

Additional Considerations:

• Limit Sampling: To ensure a sample of a desired size, adjust the probability threshold accordingly. For instance, to obtain a sample of 10,000 rows from a table with 200,000 rows, use: SELECT * FROM table WHERE RAND() <= 0.05
• Index Optimization: If your data is frequently updated, consider indexing the result of RAND() on insert/update to improve performance.

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