How to implement MySQL underlying optimization: query cache usage and performance analysis

How to realize the underlying optimization of MySQL: the use and performance analysis of query cache

MySQL is a commonly used relational database management system. In scenarios with large amounts of data, , optimizing database performance is very important. Among them, query cache is an important component that can help improve MySQL performance. This article explains how to use the query cache and perform performance analysis, and provides specific code examples.

1. The role of query cache

Query cache is a mechanism to cache query results. When the same query is executed, MySQL will obtain it from the cache results without executing the query again. This reduces database access and improves query response speed and overall performance.

2. Turn on query cache

In MySQL, the query cache is turned off by default and we need to turn it on manually. In the my.cnf configuration file, add the following configuration:

query_cache_type = 1
query_cache_size = 128M

The above configuration sets the query cache type to 1, which means the cache is enabled; the cache size is 128MB, which can be adjusted according to the actual situation.

3. Use of query cache

In order for the query results to be cached, the following conditions need to be met:

• The query statement does not contain variables ( Therefore, in actual applications, try to move the dynamic part to the application layer)
• The data in the table has not changed

When the above conditions are met, MySQL will store the query results in the cache in to wait for the same query next time.

4. Performance analysis of query cache

In order to analyze the performance of query cache, MySQL provides some system variables and commands. The following are some common examples of performance analysis-related operations:

• Query cache hit rate (Qcache_hits): Indicates the number of times query results are obtained from the cache.

SHOW VARIABLES LIKE 'Qcache%';

+-------------------------+---------+
| Variable_name           | Value   |
+-------------------------+---------+
| Qcache_free_blocks      | 1       |
| Qcache_free_memory      | 3353656 |
| Qcache_hits             | 292     |
| Qcache_inserts          | 408     |
| Qcache_lowmem_prunes    | 0       |
| Qcache_not_cached       | 63      |
| Qcache_queries_in_cache | 402     |
| Qcache_total_blocks     | 817     |
+-------------------------+---------+

• Query cache miss rate (Qcache_not_cached): Indicates the number of times that query results were not obtained from the cache.
• Query cache insertion times (Qcache_inserts): Indicates the number of times query results are inserted into the cache.
• Clear query cache: You can use the following command to clear the query cache, which is useful when there are data changes.

RESET QUERY CACHE;

Run the above command line in the MySQL terminal to clear the query cache.

5. Performance Analysis Case

The following is a specific case that demonstrates how to use the query cache and analyze the hit rate of the query cache:

-- 创建测试表
CREATE TABLE test_table (
    id INT PRIMARY KEY,
    name VARCHAR(255)
) ENGINE=InnoDB;

-- 插入测试数据
INSERT INTO test_table (id, name)
VALUES (1, 'John'), (2, 'Lily');

-- 优化前的查询
SELECT * FROM test_table WHERE id = 1;

-- 查看查询缓存命中率
SHOW STATUS LIKE 'Qcache%';

-- 开启查询缓存
SET GLOBAL query_cache_size = 128 * 1024 * 1024;
SET GLOBAL query_cache_type = 1;

-- 优化后的查询
SELECT * FROM test_table WHERE id = 1;

-- 查看查询缓存命中率
SHOW STATUS LIKE 'Qcache%';

Passed From the above case, you can learn about the use of query cache and how to perform performance analysis. However, it should be noted that query caching is not effective in all scenarios. When data changes frequently (for example, there are many write operations), query caching will bring some additional overhead. Therefore, performance testing and evaluation are required in specific applications to select appropriate optimization strategies.

Summary:

This article introduces an important component in the underlying optimization of MySQL - the use and performance analysis method of query cache, and provides specific code examples. In practical applications, reasonable use of query cache can effectively improve database performance. However, it should be noted that query caching is not applicable in all scenarios. It needs to be tested and evaluated based on specific business needs to select an appropriate optimization strategy. At the same time, you should also pay attention to clearing the cache in time to ensure the accuracy of query results.

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