MySQL is a commonly used open source relational database management system. It has many users and developers who are constantly developing and optimizing it. However, in the case of large-scale data processing and high concurrency, its default configuration and performance may not meet application needs. In order to improve the performance and stability of the MySQL database, we need to optimize it.
MySQL optimization can be roughly divided into three aspects: hardware optimization, configuration optimization and query optimization. Below we will learn more about the optimization principles and methods in these three aspects.
Hardware optimization:
First of all, hardware optimization is the first step in MySQL optimization. Because no matter how the configuration and query are optimized, if the hardware does not meet the requirements, the performance will still not be improved.
1. Choose hardware with better performance
Choose hardware with better performance, such as metaphysics dedicated servers, SSD solid state drives, high-speed memory and other hardware can significantly improve the performance of MySQL.
2. Use RAID technology
RAID technology is "Redundant Array of Independent Disks", which can improve the data security and hard disk read and write performance of the MySQL system. Commonly used ones include RAID0, RAID1, RAID5 and RAID10. Choosing different RAID technologies can make corresponding options according to the actual situation.
3. Reasonably allocate disk space
Allocate reasonable disk space to MySQL to avoid excessive or insufficient disk space usage. It is recommended to install MySQL on a separate disk partition to avoid conflicts with other applications.
4. Network equipment optimization
The equipment and configuration related to MySQL network communication need to be optimized. For example, the larger the network bandwidth, the faster the data transmission speed, which will improve performance to a certain extent.
Configuration optimization:
1. Modify MySQL configuration parameters
On the MySQL server, there are many configuration parameters that can be adjusted, such as cache settings, number of connections, thread pool size, Temporary file directory location, etc. By adjusting these parameters, MySQL can be made to run more stably and efficiently.
Some common MySQL configuration parameters are listed below:
- innodb_buffer_pool_size: InnoDB buffer size. This parameter is usually set to 70% to 80% of the total memory.
- key_buffer_size: The size of the MyISAM index buffer.
- max_connections: The maximum number of connections handled by the MySQL server at the same time.
- query_cache_size: Query cache size, usually set to 5% of the total memory.
2. Database table design and tuning
The quality of database design can significantly affect the performance of MySQL. Therefore, we need to consider the actual application scenarios when designing data tables, and use appropriate data types and constraints, appropriate prefix lengths, and multi-table, multi-column indexes to improve query efficiency and response speed.
3. Server parameter tuning
Server parameter tuning is essential, as it can adjust the server’s concurrent processing capabilities and improve throughput and performance.
- Close unnecessary services. Disabling unused network services and service processes can reduce system load and memory consumption.
- Adjust Linux kernel parameters. If MySQL is running on Linux, you can adjust the Linux kernel parameters to better coordinate system resources.
- Use connection pool and utilize cache.
Query optimization:
- Execution plan optimization
The core of query optimization is to improve query efficiency by optimizing query statements. Sometimes, optimizing the execution plan of a query statement can yield huge performance gains from query efficiency.
- Try to avoid using "*" in query statements to specify the columns to be queried;
- Avoid using subqueries;
- If multi-table queries are used, use Joint queries can improve efficiency;
- Use the correct index;
- Cache optimization
The query cache in MySQL can cache query statements and The result set can significantly improve query efficiency. However, caching can also cause MySQL performance problems. Therefore, the query cache needs to be cleared regularly.
- Data Partitioning
Data partitioning is a technology that distributes data on different partitions and can optimize different partitions. For example, data can be partitioned according to time, effectively reducing disk IO and database lock competition.
To sum up, MySQL optimization methods mainly include hardware optimization, configuration optimization and query optimization. By adjusting and optimizing these three aspects, the performance and stability of MySQL can be improved to meet application needs.
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