How to Efficiently Optimize a SQL Query with Multiple Joins and Subqueries?

Hello SQL Experts,

I'm currently facing performance issues with a complex SQL query that involves multiple joins and subqueries. I would appreciate any advice on how to optimize it for better performance.

Here are the details of my query:

SELECT 
    a.column1, 
    b.column2, 
    c.column3,
    (SELECT COUNT(*) FROM table_d d WHERE d.foreign_key = a.primary_key) as subquery_count
FROM 
    table_a a
JOIN 
    table_b b ON a.foreign_key_b = b.primary_key
LEFT JOIN 
    table_c c ON a.foreign_key_c = c.primary_key
WHERE 
    a.condition_column = 'some_value'
  AND b.another_condition_column = 'another_value'
ORDER BY 
    a.sort_column DESC
LIMIT 100;

Here are my specific questions:

What are the best practices for optimizing queries with multiple joins? Are there specific indexing strategies that would improve performance in this scenario?How can I optimize the subquery in the SELECT clause? The subquery is currently slowing down the overall query performance. Would using a different approach, like a CTE or a join, be more efficient?Are there any tools or techniques to analyze and identify bottlenecks in my query? I've used EXPLAIN to get the execution plan, but I'm looking for more insights on interpreting the results and taking actionable steps.Would partitioning the tables help in this case? If so, what are the best practices for implementing partitioning to improve query performance?Can you suggest any general tips or methods for reducing the execution time of complex queries?

Any examples, references to relevant documentation, or personal experiences would be highly valuable!

Reference: ht

Thank you in advance for your assistance!

Best regards, Mark Williams

On your table_d.foreign_key column you should create an index, so the server can scan its values quicker.

If you are running MySQL or MariaDB, you can fire EXPLAIN SELECT ... to get an idea of the cost of your WHERE conditions.