How to implement MySQL underlying optimization: best practices for parameter configuration and adjustment

How to realize MySQL underlying optimization: best practices for parameter configuration and adjustment

Abstract:

MySQL is the most commonly used open source relational database management One of the systems whose performance and stability are crucial to most businesses. However, to realize the full potential of MySQL, some low-level optimizations are required. This article will introduce some common parameter configuration and tuning best practices to improve the performance and stability of MySQL.

1. Best practices for parameter configuration

1.1 Buffer pool parameters

The buffer pool is a key part of MySQL memory management and plays an important role in query performance. Influence. The following are some commonly used buffer pool parameter adjustment suggestions:

innodb_buffer_pool_size: Set the buffer pool size of the InnoDB storage engine. It is usually recommended to set it to 70%~80% of the physical memory.

key_buffer_size: Set the buffer pool size of the MyISAM storage engine. It is usually recommended to set it to 10% of the physical memory.

query_cache_size: Set the query result cache size, but note that the query cache is not suitable for all types of queries. Improper use will lead to performance degradation.

1.2 Connection and thread parameters

Concurrent connections and thread control are also important aspects of MySQL performance optimization. The following are some common suggestions for adjusting connection and thread parameters:

max_connections: Set the maximum number of concurrent connections allowed by the database, which needs to be adjusted according to the concurrent access of the application. Excessive number of connections may lead to resource exhaustion.

thread_cache_size: Set the thread cache size for reusing closed connections. A larger thread cache can reduce connection establishment and closing overhead.

1.3 Log parameters

MySQL’s logging system is crucial for troubleshooting and recovery. The following are some common log parameter adjustment suggestions:

log_slow_queries: Enable slow query logging, which is used to record query statements whose execution time exceeds the specified threshold. Adjust the slow query time threshold according to the actual situation. It is recommended to set it to tens of milliseconds.

log_bin: Enable binary logging, which is very important for data recovery and master-slave replication. It needs to be configured according to actual needs.

2. Best practices for parameter adjustment

When adjusting MySQL parameters, there are some best practices worth noting:

2.1 Benchmark test

Before adjusting parameters, it is best to conduct a benchmark test to understand the current performance bottlenecks and what areas need improvement. Benchmark testing can use tools such as MySQL Benchmark, sysbench, etc.

2.2 Adjust parameters one by one

Do not adjust multiple parameters at once, but adjust them one by one and observe the impact of each adjustment on performance. This allows for a better understanding of the role of individual parameters and their relationship to each other.

2.3 Monitoring and Analysis

After adjusting parameters, continuous monitoring and analysis are required to determine the effect of the adjustment. You can use tools such as MySQL Performance Schema, pt-query-digest, etc. for performance analysis.

3. Code Example

The following is an example that shows how to improve MySQL performance through parameter configuration:

-- Buffer pool parameter configuration
SET innodb_buffer_pool_size = 8G;
SET key_buffer_size = 1G;
SET query_cache_size = 512M;

--Connection and thread parameter configuration
SET max_connections = 1000;
SET thread_cache_size = 100 ;

-- Log parameter configuration
SET log_slow_queries = ON;
SET long_query_time = 50;

Summary:

Through reasonable parameter configuration and adjustment, Can improve MySQL performance and stability. However, it should be noted that parameter configuration is not once and for all and needs to be continuously optimized and adjusted according to the actual situation. In addition, it is necessary to combine other optimization measures, such as index optimization, query optimization, etc., to truly realize the potential of MySQL.

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