How to implement MySQL underlying optimization: Advanced use and performance analysis of query cache

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

Abstract:
MySQL is a widely used relational database management system. Its query caching function can effectively improve query performance. This article will introduce the advanced usage and performance analysis of MySQL query cache, including enabling query cache, using query cache instances, causes and solutions of query cache failure, etc., and also gives specific code examples to help readers better understand and practice .

Keywords: MySQL, query cache, optimization, performance analysis, code examples

1. Introduction
   MySQL's query cache is a very useful feature that can query The results are cached, and the same query can be obtained directly from the cache next time, avoiding the need to execute the actual query statement, thereby improving query performance. However, in actual use, query caching does not always bring performance improvements, so we need to perform some advanced usage and performance analysis work.
2. Enable query cache
   First, we need to ensure that the query cache is enabled. In the MySQL configuration file my.cnf, you can find the following configuration items:
   query_cache_type = 1
   query_cache_size = 64M
   query_cache_limit = 2M

Set query_cache_type to 1 to enable it Query cache, query_cache_size indicates the cache size, query_cache_limit indicates the upper limit of a single query result cache.

After enabling the query cache, you need to restart the MySQL service for the configuration to take effect. In the command line, you can use the following command to restart the MySQL service:
sudo service mysql restart

3. Use query cache instance
   In the actual query, we can add SQL feature comments to Controls whether query caching is used. Just add the following comment before the query statement:
   SELECT /SELECT_WITHOUT_CACHE/ * FROM table;

If you want the query to not go through the query cache, you can use the SELECT_NO_CACHE comment:
SELECT /SELECT_NO_CACHE/ * FROM table;

4. Causes and solutions for query cache failure
   The performance improvement of query cache is not always what we want. There are some common reasons that lead to query cache failure. Let's analyze them below and give corresponding solutions.

4.1. The data table is modified
The query cache mechanism is based on the data table. If the data table is updated, inserted or deleted, the cache related to the data table will be cleared. . In order to reduce invalid cache clearing and minimize modifications to the data table, you can use some advanced features, such as INSERT DELAYED, HANDLER, etc.

4.2. The data table uses a storage engine that does not support query caching
Some storage engines of MySQL do not support query caching, such as the MEMORY storage engine. Therefore, when designing data tables, try to choose a storage engine that supports query caching, such as InnoDB, MyISAM, etc.

4.3. The query statement is very complex
The query cache is cached based on the query statement. If the query statement is particularly complex, the effect of the query cache will be greatly reduced. Therefore, when designing query statements, try to simplify the query conditions and split them into multiple simple query statements for querying.

4.4. The hit rate of the query cache is low
The hit rate of the query cache indicates the proportion of the number of queries that hit the cache to the number of all queries. If the hit rate of the query cache is very low, the effectiveness of the query cache will be greatly reduced. You can get the current query cache hit rate by checking the MySQL status variable:
SHOW STATUS LIKE 'Qcache_hits';

If the hit rate is low, you can consider increasing the value of query_cache_size and increasing the cache size.

5. Performance Analysis
   In addition to using MySQL's query cache, we also need to analyze its performance. You can obtain detailed information about slow query statements and perform performance optimization by viewing MySQL's slow query log.

In the MySQL configuration file my.cnf, you can find the following configuration items:
slow_query_log = 1
slow_query_log_file = /var/log/mysql/slow-query.log
long_query_time = 2

Set slow_query_log to 1 to enable the slow query log, slow_query_log_file to indicate the path of the slow query log file, and long_query_time to indicate that queries exceeding this time will be recorded.

After enabling the slow query log, you need to restart the MySQL service for the configuration to take effect. In the command line, you can use the following command to view the slow query log:
sudo tail -f /var/log/mysql/slow-query.log

Conclusion:
MySQL’s query cache is a This is a very useful function. Proper use and optimization can greatly improve query performance. This article introduces the advanced use and performance analysis methods of query cache, including enabling query cache, using query cache instances, causes and solutions of query cache failure, etc., and gives specific code examples to help readers better understand and practice . Through the optimization and performance analysis of MySQL query cache, the stability and response speed of the application can be improved to meet the needs of users.

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