Detailed explanation of MyBatis cache mechanism: understand the cache storage principle in one article

Detailed explanation of MyBatis caching mechanism: understand the cache storage principle in one article

Introduction
When using MyBatis for database access, caching is a very important mechanism that can Effectively reduce access to the database and improve system performance. This article will introduce the caching mechanism of MyBatis in detail, including cache classification, storage principles and specific code examples.

1. Cache classification
MyBatis’ cache is mainly divided into two types: first-level cache and second-level cache.

1. First-level cache
   The first-level cache is a SqlSession-level cache. When the same SQL statement is executed in the same SqlSession, the result will be obtained directly from the cache without accessing it again. database. The scope of the first-level cache is within the SqlSession. Multiple queries started in the same SqlSession will share the same cache.
2. Second-level cache
   The second-level cache is a Mapper-level cache, and multiple SqlSession shares the same cache. When multiple SqlSession queries the same SQL statement, the data will be obtained from the second-level cache first. If it does not exist in the cache, the data will be queried in the database and the results will be stored in the cache. The second-level cache can be used across SqlSession and transactions, providing a wider cache scope.

2. Cache storage principle
The cache storage principle of MyBatis mainly includes cache key generation and cache update strategy.

1. Cache key generation
   The cache key usually consists of SQL statements and parameters. MyBatis will splice the SQL statements and parameters into a unique key, and use the query results as key-value The form is stored in cache. Different SQL statements and parameter combinations will generate different keys, thereby achieving cache management of different query results.
2. Cache update strategy
   MyBatis provides various cache update strategies, including FIFO (first in, first out), LRU (least recently used), SWITCH (switching), etc. According to different update strategies, the cache storage method and elimination strategy can be controlled to improve the cache hit rate and efficiency.

3. Specific code examples
The following is a simple example to demonstrate the caching mechanism of MyBatis:

1. First, create a User entity class:

public class User { private Long id; private String name; private Integer age; // 省略getter和setter方法 }

2. Write the UserMapper interface:

public interface UserMapper { User getUserById(Long id); }

3. Write the UserMapper.xml file:

    select * from user where id = #{id}  

4. Configure in MyBatis Enable caching in the file:

In the above example, query is performed through the getUserById method of the UserMapper interface. The query results will be cached. Under the same query conditions, the second query will be directly from the cache. Get data from the database without accessing the database.

Conclusion
Through the introduction of this article, I believe that readers will have a deeper understanding of the caching mechanism of MyBatis. Reasonable use of the caching mechanism can improve system performance and reduce access to the database, thereby improving system stability and response speed. It is recommended that developers use MyBatis' caching mechanism flexibly based on specific business scenarios to achieve more efficient data access.

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