mybatis一级缓存的实现

我们使用mybatis与数据库进行交互，每开启一次和数据库的会话，都会创建一个SqlSession。

 /**
     * 获取Session
     *
     * @return
     */
    public static SqlSession getSqlSession() {
        return sqlSessionFactory.openSession();
    }

在mybatis源码中DefaultSqlSessionFactory中，可以看到每次opensession都是new出来的。

 private SqlSession openSessionFromDataSource(ExecutorType execType, TransactionIsolationLevel level, boolean autoCommit) {
    Transaction tx = null;
    try {
      final Environment environment = configuration.getEnvironment();
      final TransactionFactory transactionFactory = getTransactionFactoryFromEnvironment(environment);
      tx = transactionFactory.newTransaction(environment.getDataSource(), level, autoCommit);
      final Executor executor = configuration.newExecutor(tx, execType);
      return new DefaultSqlSession(configuration, executor, autoCommit);
    } catch (Exception e) {
      closeTransaction(tx); // may have fetched a connection so lets call close()
      throw ExceptionFactory.wrapException("Error opening session.  Cause: " + e, e);
    } finally {
      ErrorContext.instance().reset();
    }
  }

在同一次会话中，如果我们执行相同的查询语句，mybatis并不会每次都去数据库中查询，query会先去一级缓存中根据cachekey拿到缓存，如果缓存为空，则再去数据库中查询。

为了更好的理解一级缓存的实现，我画了UML图例，涉及到其中几个主要接口和实现类。

从上图中我们可以看到，每个sqlsession拥有一个executor，sqlsession并不会自己去执行sql,而是交给executor去执行，executor 对象中有一个类型为PerpetualCache的localCache，PerpetualCache实现了Cache接口，localCache即为sqlsession的一级缓存，这个PerpetualCache也不是什么高大上的东西，我们看看内部实现。

package org.apache.ibatis.cache.impl;

import java.util.HashMap;
import java.util.Map;
import java.util.concurrent.locks.ReadWriteLock;

import org.apache.ibatis.cache.Cache;
import org.apache.ibatis.cache.CacheException;

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

  private final String id;

  private Map 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();
  }

}

PerpetualCache内部维护了一个map实现缓存，实现了cache的几个获取，移除方法。

打几个断点，执行一个查询方法，继续看看内部逻辑。

 

在DefaultSqlSession类中，select方法中将执行过程交给了executor。

 @Override
  public  List selectList(String statement, Object parameter, RowBounds rowBounds) {
    try {
      MappedStatement ms = configuration.getMappedStatement(statement);
      return executor.query(ms, wrapCollection(parameter), rowBounds, Executor.NO_RESULT_HANDLER);
    } catch (Exception e) {
      throw ExceptionFactory.wrapException("Error querying database.  Cause: " + e, e);
    } finally {
      ErrorContext.instance().reset();
    }
  }

继续往下走，进入executor的query方法。

 @SuppressWarnings("unchecked")
  @Override
  public  List 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.");
    }
    //清空缓存
    if (queryStack == 0 && ms.isFlushCacheRequired()) {
      clearLocalCache();
    }
    List list;
    try {
      queryStack++;
      //从一级缓存中获取数据
      list = resultHandler == null ? (List) localCache.getObject(key) : null;
      if (list != null) {
        handleLocallyCachedOutputParameters(ms, key, parameter, boundSql);
      } else {
        //缓存中没有数据，从数据库中获取数据
        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;
  }



 private  List queryFromDatabase(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException {
    List list;
    localCache.putObject(key, EXECUTION_PLACEHOLDER);
    try {
      list = doQuery(ms, parameter, rowBounds, resultHandler, boundSql);
    } finally {
      localCache.removeObject(key);
    }
    //将数据库中获取的数据放入一级缓存
    localCache.putObject(key, list);
    if (ms.getStatementType() == StatementType.CALLABLE) {
      localOutputParameterCache.putObject(key, parameter);
    }
    return list;
  }

以上就是mybatis一级缓存实现的大致逻辑。