MySQL is a commonly used relational database management system (RDBMS) that is widely used in various application scenarios. However, in the case of high concurrency and large data volume, the performance of the MySQL database is challenged, especially in scenarios with frequent read and write operations, performance bottlenecks are prone to occur.
In order to improve the performance of the MySQL database, you can reduce the IO operations of the database by setting the MySQL cache, thereby improving the query efficiency of MySQL. In this article, we'll cover how to improve performance by setting up MySQL cache.
1. MySQL cache strategy
MySQL cache is mainly divided into two types: query cache and InnoDB cache.
Query cache can cache query results to avoid repeated query operations in the database. MySQL version 8.0 and later versions have removed the query cache function, because the query cache can easily cause lock competition and lead to MySQL performance bottlenecks.
InnoDB cache is the main caching mechanism of MySQ. InnoDB cache uses the LRU algorithm to maintain the storage of data in the cache based on the frequency and time of data access. When a record is read, it will be cached in InnoDB. If the record does not hit the cache, it needs to be loaded from the disk, which increases the burden of IO operations.
2. Optimize InnoDB cache parameters
In order to improve the performance of the MySQL database, you can reduce disk IO operations by optimizing the InnoDB cache parameters. For the InnoDB cache, we need to set the following parameters:
innodb_buffer_pool_size is the most important parameter to control the size of the InnoDB cache pool. The size of this parameter determines how much data InnoDB can cache, and is usually set to 80% to 90% of system memory.
For example, if our system has 4GB of memory, we can set innodb_buffer_pool_size to 3GB:
innodb_buffer_pool_size=3G
innodb_buffer_pool_instances is a parameter that controls the number of InnoDB cache pool instances. This parameter specifies how many instances the cache pool is divided into. Dividing the cache pool into multiple instances can reduce lock contention and provide better linear scalability.
For example, if our system has 4 CPU cores, we can set innodb_buffer_pool_instances to 4:
innodb_buffer_pool_instances=4
innodb_flush_method is a parameter that specifies how the InnoDB write buffer is flushed to disk. The default value for this parameter is fdatasync, which is optimal for most environments. However, if your hardware and operating system support O_DIRECT, you can use this method to improve performance.
In addition to these parameters, we can also use MySQL's own performance analysis tools to monitor the system's cache hit rate, thread usage, lock waiting and other indicators for targeted optimization.
3. Reasonable allocation of server resources
In addition to optimizing the InnoDB cache parameters, you can also improve the performance of MySQL by reasonably allocating server resources. Specifically, we can consider the following measures:
Increasing the memory capacity of the server can increase the size of the InnoDB cache pool, thereby reducing disk IO operate.
Compared with mechanical hard disk, SSD hard disk has faster disk reading and writing speed, which can greatly improve the IO operation efficiency of MySQL database.
By increasing the number of CPU cores on the server, the ability to process concurrent requests can be improved, thereby improving the performance of the MySQL database.
Improve the bandwidth and response time of the network and separate the network and disk, which can reduce the response time and burden of network IO and speed up database query and response and processing speed.
4. Summary
Setting up the MySQL cache is an important step in improving the performance of the MySQL database. However, MySQL's cache optimization is not static. We need to always pay attention to system performance and optimize according to the actual situation. Through appropriate parameter settings and resource allocation, as well as timely cache cleaning, a good cache hit rate can be maintained, thereby improving database performance.
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