How can you implement caching in MyBatis to improve application performance?

In MyBatis, caching can significantly improve the performance of your application by reducing the number of database queries executed, especially for frequently requested data. MyBatis provides two levels of caching: first level (session cache) and second level (mapper cache).

First Level Cache

Scope: This is the default cache and is associated with a SqlSession. It is also sometimes referred to as the Session cache.
Lifetime: The first level cache exists during the duration of a SqlSession. Once the session is closed, the cache is cleared.
Properties: It is enabled by default and works out-of-the-box.
Usage: The first-level caching is automatic. When you query for the same data with the same session, MyBatis will first check its local cache to see if it can skip the database call.

Second Level Cache

Scope: This cache is associated with a particular namespace or mapper. It can be shared across multiple sessions.
Lifetime: It lasts as long as the application is running, provided it is not cleared manually or by some cache eviction policy.
Configuration: Second-level caching must be explicitly enabled.

Here’s how to implement the second-level cache in MyBatis:

Enable Caching Globally: Ensure that caching is enabled globally in the MyBatis configuration by setting the cacheEnabled property to true.
```
<settings>  
   <setting name="cacheEnabled" value="true"/>  
</settings>  
```
Enable Caching in Mapper Files: Specify cache settings in individual mapper XML files for each statement or namespace you wish to cache.
```
<cache/>  
```
or use more advanced configurations:
```
<cache  
   eviction="LRU"  
   flushInterval="60000"  
   size="512"  
   readOnly="true"/>  
```

eviction: Specifies the cache eviction policy. Common options are LRU (Least Recently Used), FIFO (First In First Out), SOFT, WEAK.
flushInterval: Specifies an interval (in milliseconds) at which the cache will be flushed.
size: The number of objects that can be stored in the cache.
readOnly: If set to true, MyBatis returns cached objects that are read-only, which can improve performance. If false, MyBatis makes a deep copy of the cached object before returning it.

Using @CacheNamespace: When using MyBatis with annotations, you can use the @CacheNamespace annotation on your mapper interfaces.

import org.apache.ibatis.annotations.CacheNamespace;  
import org.apache.ibatis.annotations.Mapper;  
@Mapper  
@CacheNamespace(  
   eviction = LruCache.class,  
   flushInterval = 60000,  
   size = 512,  
   readWrite = false  
)  
public interface MyMapper {  
   // Methods  
}

Invalidate Cache: Cache invalidation is crucial to ensure data consistency. Use statements that modify the data (INSERT, UPDATE, DELETE) to include <selectKey> or custom invalidation strategies as needed to clear cache entries.

<insert id="insertItem" parameterType="item">  
    <!-- Insert statement -->  
</insert>  
<!-- This automatically flushes the cache after the operation -->

External Cache Integration: MyBatis supports integration with external caching frameworks such as Ehcache, Hazelcast, or Redis. You need to configure MyBatis to use these caching solutions by setting up the corresponding cache provider in your configuration.

Considerations

Ensure cache coherence: Your application logic should handle cases where the cache might become stale.
Handle transactions: Be careful while using caches in applications where transactions impact the visibility of data.
Memory usage: Consider the memory implications of enabling large caches, and structure caches to assist eviction when limits are reached.

By configuring these caching levels appropriately, MyBatis can significantly speed up data access patterns in your Java-based applications.

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<configuration> <settings> <setting name="localCacheScope" value="SESSION"/> </settings> <mappers> <mapper resource="path/to/your/mapper.xml"> <cache/> </mapper> </mappers> </configuration>

<resultMap id="UserResultMap" type="com.example.User"> <id property="id" column="user_id"/> <result property="name" column="user_name"/> <result property="email" column="user_email"/> </resultMap>

<update id="updateUser" parameterType="User"> UPDATE users SET name = #{name}, age = #{age} WHERE id = #{id} <selectKey resultType="int" keyProperty="id" order="AFTER"> SELECT LAST_INSERT_ID() </selectKey> <flushCache/> </update>

<settings> <setting name="cacheEnabled" value="true"/> </settings> <mapper namespace="com.example.Mapper"> <cache/> <select id="selectUser" resultType="User"> SELECT * FROM users WHERE id = #{id} </select> </mapper>

SqlSession session = sqlSessionFactory.openSession(); try { UserMapper mapper = session.getMapper(UserMapper.class); User user = mapper.selectUserById(1); user.setName("New Name"); mapper.updateUser(user); // 清除缓存 session.clearCache(); User updatedUser = mapper.selectUserById(1); // 这次查询会重新从数据库获取最新数据 } finally { session.close(); }

SqlSession sqlSession = sqlSessionFactory.openSession(); UserMapper userMapper = sqlSession.getMapper(UserMapper.class); User user1 = userMapper.getUserById(1); // 第一次查询 User user2 = userMapper.getUserById(1); // 第二次查询，使用缓存