How to Optimize Queries in MySQL

Galaxy Glossary

How do you optimize slow MySQL queries?

Optimization in MySQL means analyzing execution plans, adding indexes, rewriting SQL, and tuning server settings to reduce execution time and resource usage.

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Description

What makes a MySQL query slow?

Large table scans, missing indexes, non-sargable conditions, and poor JOIN order force MySQL to read more rows than necessary, increasing latency.

How do I inspect the execution plan?

Use EXPLAIN or EXPLAIN ANALYZE before your SELECT. The output shows table access order, index usage, filtered rows, and cost, helping you spot full scans.

When should I add an index?

Create indexes on columns used in WHERE, JOIN, and ORDER BY clauses with high selectivity.Composite indexes should follow the column order of the most common predicates.

Which query rewrite tricks speed things up?

Replace SELECT * with specific columns, avoid functions on indexed columns, split OR conditions into UNION ALL, and use EXISTS instead of IN for correlated subqueries.

How do I optimize joins in ecommerce schemas?

Ensure Orders.customer_id and OrderItems.order_id, product_id have foreign-key indexes.Join smaller, filtered result sets first to reduce intermediate rows.

Can configuration changes help?

Increase innodb_buffer_pool_size to 70-80% of RAM, set query_cache_type=0 on 5.7+, and adjust tmp_table_size to avoid disk-based temp tables.

Best practice checklist

• Always run EXPLAIN
• Cover queries with indexes
• Limit result sets
• Monitor with slow query log
• Refactor queries after schema growth

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Why How to Optimize Queries in MySQL is important

How to Optimize Queries in MySQL Example Usage


-- Speed up a daily revenue report
EXPLAIN ANALYZE
SELECT DATE(o.order_date)   AS day,
       SUM(oi.quantity * p.price) AS revenue
FROM Orders      o
JOIN OrderItems  oi ON oi.order_id   = o.id
JOIN Products    p  ON p.id         = oi.product_id
WHERE o.order_date >= CURDATE() - INTERVAL 7 DAY
GROUP BY day
ORDER BY day;

How to Optimize Queries in MySQL Syntax


-- 1. Inspect a query
EXPLAIN [ANALYZE] SELECT o.id, o.total_amount
FROM Orders o
WHERE o.order_date >= '2024-01-01';

-- 2. Create single-column index
CREATE INDEX idx_orders_order_date ON Orders(order_date);

-- 3. Create composite index for a join + filter
CREATE INDEX idx_orderitems_order_product
    ON OrderItems(order_id, product_id);

-- 4. Rewrite with EXISTS for better optimization
SELECT c.id, c.name
FROM Customers c
WHERE EXISTS (
  SELECT 1 FROM Orders o
  WHERE o.customer_id = c.id
    AND o.total_amount > 100
);

Common Mistakes

Ignoring EXPLAIN output. Many developers add indexes blindly without checking if the optimizer already uses an efficient plan. Always read rows_examined and access type first.
Creating too many overlapping indexes. Each extra index slows writes and consumes memory. Consolidate into composite indexes that match real query patterns.

Frequently Asked Questions (FAQs)

Does adding an index always make a query faster?

No. Indexes help read performance but slow down INSERT and UPDATE. Evaluate with EXPLAIN and benchmark before committing.

How can I find problematic queries automatically?

Enable the slow_query_log and set long_query_time (e.g., 0.5 s). Review the log or use performance_schema events_statements_summary_by_digest.

Is ANALYZE TABLE needed after large imports?

Yes. ANALYZE TABLE updates index statistics so the optimizer chooses the best plan after significant data changes.

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