mybatis 一级缓存 源码解析

mybatis 内置一级缓存（session 会话级别的缓存）， 默认情况下是开启的。官方文档说明如下：

cache
-- 默认情况下，只启用了本地的会话缓存，它仅仅对一个会话中的数据进行缓存。要启用全局的二级缓存，只需要在你的 SQL 映射文件中添加一行：
By default, just local session caching is enabled that is used solely to cache data for the duration of a session. 
To enable a global second level of caching you simply need to add one line to your SQL Mapping file:

接下来我们通过源码来看看mybatis 一级缓存具体实现。下图是简单的查询时序图 (画的不好，将就看看)

    如上图知道mybatis的SQL执行最后是交给了Executor执行器来完成的，我们看下BaseExecutor的源码

  @SuppressWarnings("unchecked")
  @Override
  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++;
      // 从本地缓存中取数据
      list = resultHandler == null ? (List<E>) localCache.getObject(key) : null;
      if (list != null) {
        // 处理本地缓存的输出参数 如果是存储过程，把输出参数保存起来
        handleLocallyCachedOutputParameters(ms, key, parameter, boundSql);
      } else {
        // 查询数据库数据
        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;
  }

  protected BaseExecutor(Configuration configuration, Transaction transaction) {
    this.transaction = transaction;
    this.deferredLoads = new ConcurrentLinkedQueue<>();
    this.localCache = new PerpetualCache("LocalCache");
    this.localOutputParameterCache = new PerpetualCache("LocalOutputParameterCache");
    this.closed = false;
    this.configuration = configuration;
    this.wrapper = this;
  }

/**
 * @author Clinton Begin
 */
public class PerpetualCache implements Cache {

  private final String id;

  private Map<Object, Object> cache = new HashMap<>();

  public PerpetualCache(String id) {
    this.id = id;
  }

  @Override
  public String getId() {
    return id;
  }

  @Override
  public int getSize() {
    return cache.size();
  }

  @Override
  public void putObject(Object key, Object value) {
    cache.put(key, value);
  }

  @Override
  public Object getObject(Object key) {
    return cache.get(key);
  }

  @Override
  public Object removeObject(Object key) {
    return cache.remove(key);
  }

  @Override
  public void clear() {
    cache.clear();
  }

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

  @Override
  public boolean equals(Object o) {
    if (getId() == null) {
      throw new CacheException("Cache instances require an ID.");
    }
    if (this == o) {
      return true;
    }
    if (!(o instanceof Cache)) {
      return false;
    }

    Cache otherCache = (Cache) o;
    return getId().equals(otherCache.getId());
  }

  @Override
  public int hashCode() {
    if (getId() == null) {
      throw new CacheException("Cache instances require an ID.");
    }
    return getId().hashCode();
  }

}

以上：

一级缓存存储在BaseExecutor对象中的localCache属性中,localCache的实现类是perpetualCache,其底层是用HashMap存储缓存对象,CacheKey对象作为HashMap的key,缓存对象作为HashMap作为value;因此CacheKey对象的hashcode将决定存储位置;

我们可以看一下CacheKey的生成规则：

  @Override
  public CacheKey createCacheKey(MappedStatement ms, Object parameterObject, RowBounds rowBounds, BoundSql boundSql) {
    if (closed) {
      throw new ExecutorException("Executor was closed.");
    }
    CacheKey cacheKey = new CacheKey();
    cacheKey.update(ms.getId());
    cacheKey.update(rowBounds.getOffset());
    cacheKey.update(rowBounds.getLimit());
    cacheKey.update(boundSql.getSql());
    List<ParameterMapping> parameterMappings = boundSql.getParameterMappings();
    TypeHandlerRegistry typeHandlerRegistry = ms.getConfiguration().getTypeHandlerRegistry();
    // mimic DefaultParameterHandler logic
    for (ParameterMapping parameterMapping : parameterMappings) {
      if (parameterMapping.getMode() != ParameterMode.OUT) {
        Object value;
        String propertyName = parameterMapping.getProperty();
        if (boundSql.hasAdditionalParameter(propertyName)) {
          value = boundSql.getAdditionalParameter(propertyName);
        } else if (parameterObject == null) {
          value = null;
        } else if (typeHandlerRegistry.hasTypeHandler(parameterObject.getClass())) {
          value = parameterObject;
        } else {
          MetaObject metaObject = configuration.newMetaObject(parameterObject);
          value = metaObject.getValue(propertyName);
        }
        cacheKey.update(value);
      }
    }
    if (configuration.getEnvironment() != null) {
      // issue #176
      cacheKey.update(configuration.getEnvironment().getId());
    }
    return cacheKey;
  }

创建cacheKey主要依据以下几个条件:

1. MappedStatement的id也就是select标签所在mapper文件的namespace+select的id相同；
2. RowBounds的offset属性和limit()属性相同;
3. BoundSql中的sql语句相同；
4. 遍历输入参数列表必须满足每个参数相同;
5. 获取Environment的id,保证数据源相同;

本文地址：https://blog.csdn.net/qq_16708327/article/details/85784475