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

Querying a Random Sample from a MySQL Database with Efficiency

Initial Approach and Limitations:

The straightforward method of generating a random sample using SELECT * FROM table ORDER BY RAND() LIMIT 10000 faces performance bottlenecks with large tables. This approach is computationally intensive due to the requirement to sort the entire table, making it impractical for tables with hundreds of thousands of rows.

Optimized Sampling Technique:

An efficient alternative is to utilize the following query:

SELECT * FROM table WHERE rand() <= .3

This query employs the following principles:

• Random Number Generation: The rand() function generates a random number between 0 and 1 for each row.
• Conditional Selection: Each row is then evaluated to determine if it should be included in the sample based on whether the random number is less than or equal to 0.3.

Advantages of this Approach:

• It is O(n), as no sorting is necessary.
• MySQL's random number generation mechanism ensures a uniform distribution of values.
• By contrast, the ORDER BY RAND() approach is O(n lg n), making it significantly slower for large datasets.

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