Preface

In my previous article, I outlined eight fundamental SQL optimization techniques. Today, I will delve into seven advanced strategies aimed at further enhancing your skills in efficient data retrieval.

Chapter 1: Leveraging Joins Over Subqueries

When querying data from multiple tables in MySQL, you can typically choose between subqueries and join queries.

Suboptimal Example:

SELECT * FROM order WHERE user_id IN (SELECT id FROM user WHERE status=1);

A subquery utilizes the IN clause, which executes the inner query first before processing the outer query. While subqueries can be straightforward and well-structured with fewer tables, they may lead to performance issues due to the creation of temporary tables.

Optimal Example:

SELECT o.* FROM order o INNER JOIN user u ON o.user_id = u.id WHERE u.status=1;

In this case, using join queries can streamline performance by avoiding unnecessary temporary tables.

Avoiding Excessive Joins

According to the Alibaba Developer Handbook, it's advisable to limit join tables to a maximum of three.

Suboptimal Example:

SELECT a.name, b.name, c.name, d.name FROM a INNER JOIN b ON a.id = b.a_id

INNER JOIN c ON c.b_id = b.id INNER JOIN d ON d.c_id = c.id

INNER JOIN e ON e.d_id = d.id INNER JOIN f ON f.e_id = e.id

INNER JOIN g ON g.f_id = f.id;

Excessive joins complicate index selection and can lead to inefficient nested loop joins with a complexity of n².

Optimal Example:

SELECT a.name, b.name, c.name, a.d_name FROM a

INNER JOIN b ON a.id = b.a_id

INNER JOIN c ON c.b_id = b.id;

To simplify queries, consider adding redundant fields to tables when necessary.

Chapter 2: Understanding Join Types

When querying multiple tables, you generally use the JOIN keyword. The two most common types are:

• Left Join: Yields all rows from the left table and matched rows from the right table.
• Inner Join: Returns only rows with matching values in both tables.

Inner Join Example:

SELECT o.id, o.code, u.name FROM order o

INNER JOIN user u ON o.user_id = u.id WHERE u.status=1;

MySQL optimally chooses the smaller table as the driving table for efficiency.

Left Join Example:

SELECT o.id, o.code, u.name FROM order o

LEFT JOIN user u ON o.user_id = u.id WHERE u.status=1;

Be cautious with left joins; they can lead to performance issues if the left table is significantly larger than the right.

Chapter 3: Managing Indexes Effectively

While indexes are crucial for enhancing SQL query performance, having too many can be detrimental. Each index requires additional storage and can slow down insert, update, or delete operations.

According to the Alibaba Developer Handbook, maintain no more than five indexes per table, with each index containing no more than five fields.

For high-concurrency systems, limit the number of indexes strictly. Composite indexes can be a solution, as they combine multiple fields into a single index, reducing the overall index count.

Choosing Appropriate Data Types

Using the right field types can also impact performance:

• Char vs. Varchar: Use CHAR for fixed-length strings and VARCHAR for variable-length strings to optimize space.
• Numeric vs. String: Prefer numeric types, as they generally process faster than strings.

Improving Group By Efficiency

Utilizing the GROUP BY keyword can be resource-intensive.

Suboptimal Example:

SELECT user_id, user_name FROM order GROUP BY user_id HAVING user_id <= 200;

This query performs poorly as it groups all orders first before filtering.

Optimal Example:

SELECT user_id, user_name FROM order WHERE user_id <= 200 GROUP BY user_id;

By applying filters prior to grouping, you enhance query efficiency.

Chapter 4: Index Optimization Techniques

Index optimization is crucial for SQL performance. The first step is to verify index usage with the EXPLAIN command:

EXPLAIN SELECT * FROM order WHERE code='002';

If an index isn't being used, it may have become invalid due to various reasons, requiring further investigation.

Sometimes, MySQL may select an incorrect index based on input parameters. You can explicitly specify an index using the FORCE INDEX directive when necessary.

SQL Performance Tips - Learn how to optimize your SQL queries for better performance.

SQL Tips & Tricks Every Data Professional Should Know | Best Coding Practices 2022 - Essential tips for effective SQL programming.

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