MyBatis源码阅读——MyBatis缓存的原理解析

前言

MyBatis 包含一个非常强大的查询缓存特性,它可以非常方便地配置和定制。除了局部的 session 缓存,默认情况下是没有二级开启缓存的。那么MyBatis的一级缓存跟二级缓存在它的框架内部是如何实现的?我们去一探究竟吧。

一级缓存

一级缓存是默认开启的。当然你也可以关闭。在SQL 映射文件中,设置语句参数即可:

flushCache 将其设置为 true,任何时候只要语句被调用,都会导致本地缓存和二级缓存都会被清空,默认值:false。

使用

因为,前面我们已经知道,一级缓存是基于SqlSession生命周期的所以,我们使用同一个例子,来看一级缓存的效果。记得开启日志。< setting name=”logImpl” value=”STDOUT_LOGGING” />

public static void main(String[] args) throws IOException {
        String resource = "mybatis/conf/mybatis-config.xml";
        InputStream inputStream = Resources.getResourceAsStream(resource);
        SqlSessionFactory sqlSessionFactory = new SqlSessionFactoryBuilder().build(inputStream);
        SqlSession session = sqlSessionFactory.openSession();
        try {
            BlogMapper mapper = session.getMapper(BlogMapper.class);
            Blog blog = mapper.selectBlog(1L);
            System.out.println(blog);
            blog = mapper.selectBlog(1L);
            System.out.println(blog);
        } finally {
            session.close();
        }
    }

运行结果:

Opening JDBC Connection
Created connection 2050462663.
Setting autocommit to false on JDBC Connection [com.mysql.jdbc.JDBC4Connection@7a3793c7]
==> Preparing: select blog_id,blog_title,blog_content,create_time from blog where blog_id = ?
==> Parameters: 1(Long)
<== Columns: blog_id, blog_title, blog_content, create_time
<== Row: 1, 什么是mybatis, MyBatis是支持定制化SQL、存储过程以及高级映射的优秀的持久层框架。
, 2018-05-25 14:28:35.0
<== Total: 1
Blog{blogId=1, blogTitle=’什么是mybatis’, blogContent=’MyBatis是支持定制化SQL、存储过程以及高级映射的优秀的持久层框架。
‘, createTime=Fri May 25 14:28:35 CST 2018}
Blog{blogId=1, blogTitle=’什么是mybatis’, blogContent=’MyBatis是支持定制化SQL、存储过程以及高级映射的优秀的持久层框架。
‘, createTime=Fri May 25 14:28:35 CST 2018}
Resetting autocommit to true on JDBC Connection [com.mysql.jdbc.JDBC4Connection@7a3793c7]
Closing JDBC Connection [com.mysql.jdbc.JDBC4Connection@7a3793c7]
Returned connection 2050462663 to pool.
在日志中,我们只看到了一次查询。

源码

在之前的文章中,我们知道Executor是最终执行者,在实现类BaseExecutor中,有个 PerpetualCache localCache;
这是存放本地缓存(一级缓存的地方),我们看下查询的代码:

  public <E> List<E> query(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException {
    ErrorContext.instance().resource(ms.getResource()).activity("executing a query").object(ms.getId());
    if (closed) {
      throw new ExecutorException("Executor was closed.");
    }
    if (queryStack == 0 && ms.isFlushCacheRequired()) {
      clearLocalCache();
    }
    List<E> list;
    try {
      queryStack++;
      //首先从缓存中读取
      list = resultHandler == null ? (List<E>) localCache.getObject(key) : null;
      if (list != null) {
        handleLocallyCachedOutputParameters(ms, key, parameter, boundSql);
      } else {
        //缓存中没有,则从数据库中读取
        list = queryFromDatabase(ms, parameter, rowBounds, resultHandler, key, boundSql);
      }
    } finally {
      queryStack--;
    }
    if (queryStack == 0) {
      for (DeferredLoad deferredLoad : deferredLoads) {
        deferredLoad.load();
      }
      // issue #601
      deferredLoads.clear();
      if (configuration.getLocalCacheScope() == LocalCacheScope.STATEMENT) {
        // issue #482
        clearLocalCache();
      }
    }
    return list;
  }

localCache的作用域是BaseExecutor,而SqlSession的产生是独立的,且每次都是自己new了一个Executor
这里写图片描述
故,这个localCache缓存只在同一session下产生作用。
一级缓存在update等操作时,会清空缓存。

  public void clearLocalCache() {
    if (!closed) {
      localCache.clear();
      localOutputParameterCache.clear();
    }
  }

二级缓存

使用

 <setting name="cacheEnabled" value="true"/>

要开启二级缓存,在配置中开启的清空下,你还需要在你的 SQL 映射文件中添加一行:

<cache/>

现在,我们写个demo看下其作用:

public class Demo3CacheSecond {
    public static void main(String[] args) throws IOException {
        String resource = "mybatis/conf/mybatis-config.xml";
        InputStream inputStream = Resources.getResourceAsStream(resource);
        SqlSessionFactory sqlSessionFactory = new SqlSessionFactoryBuilder().build(inputStream);

        SqlSession session1 = sqlSessionFactory.openSession();
        try {
            BlogMapper mapper1 = session1.getMapper(BlogMapper.class);
            Blog blog1 = mapper1.selectBlog(1L);
            System.out.println("blog1:" + blog1);
            session1.commit();
        } finally {
            session1.close();
        }

        SqlSession session2 = sqlSessionFactory.openSession();
        try {
            BlogMapper mapper2 = session2.getMapper(BlogMapper.class);
            Blog blog2 = mapper2.selectBlog(1L);
            System.out.println("blog2:" + blog2);
            session2.commit();
        } finally {
            session2.close();
        }
    }
}

运行结果:

Cache Hit Ratio [top.yuyufeng.learn.mybatis.mapper.BlogMapper]: 0.0
Opening JDBC Connection
Created connection 1241569743.
Setting autocommit to false on JDBC Connection [com.mysql.jdbc.JDBC4Connection@4a00d9cf]
==> Preparing: select blog_id,blog_title,blog_content,create_time from blog where blog_id = ?
==> Parameters: 1(Long)
<== Columns: blog_id, blog_title, blog_content, create_time
<== Row: 1, 什么是mybatis, MyBatis是支持定制化SQL、存储过程以及高级映射的优秀的持久层框架。
, 2018-05-25 14:28:35.0
<== Total: 1
blog1:Blog{blogId=1, blogTitle=’什么是mybatis’, blogContent=’MyBatis是支持定制化SQL、存储过程以及高级映射的优秀的持久层框架。
‘, createTime=Fri May 25 14:28:35 CST 2018}
Resetting autocommit to true on JDBC Connection [com.mysql.jdbc.JDBC4Connection@4a00d9cf]
Closing JDBC Connection [com.mysql.jdbc.JDBC4Connection@4a00d9cf]
Returned connection 1241569743 to pool.
Cache Hit Ratio [top.yuyufeng.learn.mybatis.mapper.BlogMapper]: 0.5
blog2:Blog{blogId=1, blogTitle=’什么是mybatis’, blogContent=’MyBatis是支持定制化SQL、存储过程以及高级映射的优秀的持久层框架。
‘, createTime=Fri May 25 14:28:35 CST 2018}

从日志中分析,在第二次查询过程中,是从缓存中读取的。现在是两个session,所以是从二级缓存中读取的。

源码

开启二级缓存后,执行器Executor会被CachingExecutor包装一层。(这里用到了装饰器模式)
这里写图片描述
那么,我们看下它是如何用 CachingExecutor来进行二级缓存的操作的:

  public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql)
      throws SQLException {
     //从MappedStatement 拿到Cache
    Cache cache = ms.getCache();
    if (cache != null) {
      flushCacheIfRequired(ms);
      if (ms.isUseCache() && resultHandler == null) {
        ensureNoOutParams(ms, parameterObject, boundSql);
        //首先从二级缓存中获取
        List<E> list = (List<E>) tcm.getObject(cache, key);
        if (list == null) {
          //二级缓存中没有,则跟原来一样获取。
          list = delegate.<E> query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
          //存入二级缓存中
          tcm.putObject(cache, key, list); // issue #578 and #116
        }
        return list;
      }
    }
    return delegate.<E> query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
  }

在代码中,tcm(TransactionalCacheManager )是二级缓存的关键点。它是缓存存放的地方。二级缓存是Mapper域共享的,就会涉及到线程安全问题更多,所以需要更好的去维护。

    public class CachingExecutor implements Executor {
      private Executor delegate;
      private TransactionalCacheManager tcm = new TransactionalCacheManager();
      }

而二级缓存是如何起作用的呢?看下如下源码:

public class TransactionalCache implements Cache {
  private Cache delegate;
  private boolean clearOnCommit;
  private Map<Object, Object> entriesToAddOnCommit;  
  private Set<Object> entriesMissedInCache;

  public TransactionalCache(Cache delegate) {
    this.delegate = delegate;
    this.clearOnCommit = false;
    this.entriesToAddOnCommit = new HashMap<Object, Object>();
    this.entriesMissedInCache = new HashSet<Object>();
  }

  @Override
  public Object getObject(Object key) {
    // issue #116 
    Object object = delegate.getObject(key);
    if (object == null) {
      //如果没拿到,那么加入失效缓存SET中
      entriesMissedInCache.add(key);
    }
    // issue #146
    if (clearOnCommit) {
      return null;
    } else {
      return object;
    }
  }

  @Override
  public ReadWriteLock getReadWriteLock() {
    return null;
  }

  @Override
  public void putObject(Object key, Object object) {
    entriesToAddOnCommit.put(key, object);
  }

  @Override
  public Object removeObject(Object key) {
    return null;
  }

  @Override
  public void clear() {
    clearOnCommit = true;
    entriesToAddOnCommit.clear();
  }

  public void commit() {
    if (clearOnCommit) {
      delegate.clear();
    }
    //刷新缓存
    flushPendingEntries();
    reset();
  }

  public void rollback() {
    unlockMissedEntries();
    reset();
  }

  private void reset() {
    clearOnCommit = false;
    entriesToAddOnCommit.clear();
    entriesMissedInCache.clear();
  }

    //刷新缓存的具体操作
  private void flushPendingEntries() {
    for (Map.Entry<Object, Object> entry : entriesToAddOnCommit.entrySet()) {
      delegate.putObject(entry.getKey(), entry.getValue());
    }
    for (Object entry : entriesMissedInCache) {
      if (!entriesToAddOnCommit.containsKey(entry)) {
        delegate.putObject(entry, null);
      }
    }
  }

    //移除缓存
  private void unlockMissedEntries() {
    for (Object entry : entriesMissedInCache) {
      try {
        delegate.removeObject(entry);
      } catch (Exception e) {
        log.warn("Unexpected exception while notifiying a rollback to the cache adapter."
            + "Consider upgrading your cache adapter to the latest version.  Cause: " + e);
      }
    }
  }

}

因为Cache是从MappedStatement 拿到的,而这个是在初始化的时候从xml或者注解中加载的,是全局共享的,所以二级缓存可以在不同的session的生效。

这里写图片描述

Cache是如何包装的

查看org.apache.ibatis.mapping.CacheBuilder中源码 即可知道。

public Cache build() {
    setDefaultImplementations();
    Cache cache = newBaseCacheInstance(implementation, id);
    setCacheProperties(cache);
    // issue #352, do not apply decorators to custom caches
    //加上一些装饰
    if (PerpetualCache.class.equals(cache.getClass())) {
      for (Class<? extends Cache> decorator : decorators) {
        cache = newCacheDecoratorInstance(decorator, cache);
        setCacheProperties(cache);
      }
      cache = setStandardDecorators(cache);
    } else if (!LoggingCache.class.isAssignableFrom(cache.getClass())) {
      cache = new LoggingCache(cache);
    }
    return cache;
  }

引用

http://www.mybatis.org/mybatis-3/zh/index.html

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转载自blog.csdn.net/qq_18860653/article/details/80608346