How Can I Efficiently Retrieve Multiple Random Rows from MySQL without Using ORDER BY RAND()?

MySQL: High-throughput random sampling beyond ORDER BY RAND()

Explore alternatives for obtaining multiple random results

Although MySQL's ORDER BY RAND() function provides a method to directly obtain random results, it is unable to efficiently select multiple rows of random data. This article explores alternative techniques to optimize such queries.

Optimization solution: using index columns and subqueries

For queries seeking random results, optimizing performance is critical. One innovative approach that works well is to use a combination of indexed columns and subqueries. This technique significantly reduces processing overhead by isolating the randomization process to specific conditions.

Steps:

1. Determine the percentage of results to be randomized: Define the number of results to be randomized as a percentage of the total number of rows.
2. Create a subquery: Use the RAND() function and LIMIT clause to select row IDs that satisfy a specified percentage.
3. Join subquery: Use a join to merge the subquery with the main table, using the index column as the join key.
4. Retrieve full results: Retrieve the required columns from the main table using the rows identified by the subquery.

Example:

Consider the following query:

<code class="language-sql">SELECT u.id, 
       p.photo 
FROM users u, profiles p 
WHERE p.memberid = u.id 
  AND p.photo != '' 
  AND (u.ownership=1 OR u.stamp=1) 
ORDER BY RAND() 
LIMIT 18 </code>

Optimized query:

<code class="language-sql">SELECT 
    g.*
FROM
    table g
        JOIN
    (SELECT 
        id
    FROM
        table
    WHERE
        RAND() < (SELECT 
                ((4 / COUNT(*)) * 10)
            FROM
                table)
    ORDER BY RAND()
    LIMIT 4) AS z ON z.id= g.id</code>

Advantages:

• Execution speed optimization, much faster than ORDER BY RAND()
• Improving scalability for large data sets
• Applies to any table with indexed columns

Note:

This optimization method relies on consistency between the subquery and main query to ensure that they return accurate results. Additionally, choosing reasonable limits for the percentage of randomized results can help maintain performance.

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