Indexing Strategies
Types of Indexes
graph TD
A[MySQL Indexes] --> B[Single-Column Index]
A --> C[Composite Index]
A --> D[Unique Index]
A --> E[Full-Text Index]
Index Creation Best Practices
-- Create Single Column Index
CREATE INDEX idx_username ON users(username);
-- Create Composite Index
CREATE INDEX idx_name_email ON users(last_name, email);
Query Optimization Techniques
1. Query Rewriting
Inefficient Query |
Optimized Query |
SELECT * FROM users |
SELECT id, name FROM users |
SELECT DISTINCT column |
SELECT column FROM table GROUP BY column |
2. Avoiding Subqueries
-- Less Efficient
SELECT * FROM orders
WHERE customer_id IN (SELECT id FROM customers WHERE status = 'active');
-- More Efficient
SELECT o.* FROM orders o
JOIN customers c ON o.customer_id = c.id
WHERE c.status = 'active';
Caching Strategies
graph TD
A[MySQL Caching] --> B[Query Cache]
A --> C[Buffer Pool]
A --> D[Key Cache]
B --> B1[Stores Result Sets]
C --> C1[Caches Table Data]
D --> D1[Caches Index Blocks]
Configuring MySQL Cache
## Edit MySQL configuration
sudo nano /etc/mysql/mysql.conf.d/mysqld.cnf
## Add cache settings
query_cache_type = 1
query_cache_size = 256M
query_cache_limit = 2M
Connection Management
Connection Pooling Configuration
## Install connection pooling library
sudo apt-get install libmysqlclient-dev
## Sample Python Connection Pooling
import mysql.connector.pooling
connection_pool = mysql.connector.pooling.MySQLConnectionPool(
pool_name = "mypool",
pool_size = 5,
host = 'localhost',
user = 'username',
password = 'password'
)
Hardware and Configuration Optimization
Key MySQL Configuration Parameters
Parameter |
Recommended Setting |
Purpose |
innodb_buffer_pool_size |
50-80% of RAM |
Caches data and indexes |
max_connections |
Based on concurrent users |
Limits simultaneous connections |
sort_buffer_size |
256K - 2M |
Memory for sorting operations |
- MySQL Workbench
- LabEx Performance Monitor
- Percona Monitoring and Management
- pt-query-digest
#!/bin/bash
## MySQL Performance Check
## Check current status
mysqladmin status
## Show process list
mysql -u root -p -e "SHOW PROCESSLIST;"
## Analyze slow queries
pt-query-digest /var/log/mysql/slow.log
Advanced Optimization Techniques
- Implement vertical and horizontal partitioning
- Use proper data types
- Normalize database schema
- Regularly update statistics
- Consider denormalization for read-heavy systems
By implementing these performance optimization techniques, developers can significantly improve MySQL database efficiency and response times.