In-depth understanding of Mybatis second-level cache

The previous article introduced you to the mybatis first-level cache. Friends in need can refer to it.

Compared with the first-level cache, the second-level cache has a larger scope and can be shared by multiple SqlSession.

Similarly, if you send the same query sql, it will first search in the cache. If it cannot find it, it will query the database again.

Each namespace mapper will have its own cache space.

If the namespaces of the two mappers are the same, the data queried by executing the mapper will be stored in the same second-level cache.

Similarly, if a sqlSession executes commit, the second-level cache will be cleared.

Configuration file (it is enabled by default without configuration):

In sqlMapConfig.xml:

In the corresponding mapper.xml:

If you don’t need the second-level cache, you can disable the second-level cache in the settings

In this way, it will be retrieved from the database every time Medium read

The cache will be refreshed (cleared cache) after executing insert, update, and delete. You can set it not to refresh.

Generally not set, the setting may cause dirty reading.

Small example:

SqlSession session1 = factory.openSession();
   SqlSession session2 = factory.openSession();
   SqlSession session3 = factory.openSession();
   UserMapper mapper1 = session1.getMapper(UserMapper.class);
   UserMapper mapper2 = session2.getMapper(UserMapper.class);
   UserMapper mapper3 = session3.getMapper(UserMapper.class);
   //第一次请求,查询id为1的用户
   User user1 = mapper1.findUserById(1);
   System.out.println(user1);
   //close 将数据写入二级缓存
   session1.close();
   //清空二级缓存,UserMapper下的
   user1.setUsername("mmm");
   mapper3.updateUser(user1);
   session3.commit();
   //第二次查询会从缓存中找
   User user2 = mapper2.findUserById(1);
   System.out.println(user2);
   session2.close();

Note that the objects to be cached here must implement the Serilizable interface, because these caches Data may be deserialized and written to hard disk or elsewhere.

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