Mybatis深入源码分析之SqlSessionFactory二级缓存原理分析

须臾之余

发布于 2019-07-30 14:45:43

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发布于 2019-07-30 14:45:43

文章被收录于专栏：须臾之余须臾之余

这里再概括下上篇源码分析内容：

一：Mybatis一级缓存

mybatis的一级缓存是SqlSession缓存，在操作数据库的时候需要先创建SQL会话对象，在对象中有个HashMap用于存储缓存数据，此HashMap是当前对象私有的，其它SqlSession会话对象无法访问。

具体流程：

第一次执行select完毕会将查到的数据写入SqlSession内的HashMap中缓存起来
第二次执行select会从缓存中查数据，如果select相同且传参数一样，那么就能从缓存中返回数据，不用去查询数据库了，从而提高程序执行效率。

注意事项：

如果SqlSession执行了DML操作（insert、update、delete），并commit了，那么mybatis就会清空当前SqlSession缓存中所有的缓存数据，这样可以保证缓存中的缓存数据永远和数据库中的一致，避免出现脏读。
当一个SqlSession结束后，那么它里面的一级缓存也就不存在了，Mybatis默认是开启一级缓存，不需要配置。
mybatis缓存是基于【namespzce:sql语句：参数】来进行缓存的，意思就是：sqlSession的HashMap存储缓存数据时，是使用【namespace:sql:参数】作为key
注意服务器集群的时候，每个sqlSession都有自己独立的缓存且互不共享，所以在服务器集群的时候容易产生数据冲突问题。

如何禁止一级缓存

方案1 在sql语句上随机生成不同的参数存在缺点：map集合可能爆内存溢出的问题
方案2 开启二级缓存
方案3 使用sqlSession强制清除缓存
方案4 创建新的sqlSession连接。

二：Mybatis二级缓存SessionFactory

MyBatis使用Redis作为二级缓存

二级缓存默认是没有开启的，需要在setting全局参数中配置开启二级缓存，还需要对实体类实现序列化接口

<settings>
    <setting name="logImpl" value="STDOUT_LOGGING"/>
    <setting name="cacheEnabled" value="true"/>  开启二级缓存
</settings>

在mapper配置文件中加入下面这段配置：表示缓存淘汰策略，和指定缓存类型

<cache eviction="LRU" type="org.mybatis.cache.MybatisRedisCache" />

在源码中，是如何解析配置的缓存呢？下面我们找到这段源码：

private void configurationElement(XNode context) {
    try {
        String namespace = context.getStringAttribute("namespace");
        if (namespace != null && !namespace.equals("")) {
            this.builderAssistant.setCurrentNamespace(namespace);
            this.cacheRefElement(context.evalNode("cache-ref"));
            this.cacheElement(context.evalNode("cache"));    //解析mapper配置文件中配置的缓存结点cache
            this.parameterMapElement(context.evalNodes("/mapper/parameterMap"));
            this.resultMapElements(context.evalNodes("/mapper/resultMap"));
            this.sqlElement(context.evalNodes("/mapper/sql"));
            this.buildStatementFromContext(context.evalNodes("select|insert|update|delete"));
        } else {
            throw new BuilderException("Mapper's namespace cannot be empty");
        }
    } catch (Exception var3) {
        throw new BuilderException("Error parsing Mapper XML. Cause: " + var3, var3);
    }
}

private void cacheElement(XNode context) throws Exception {
    if (context != null) {
        String type = context.getStringAttribute("type", "PERPETUAL");
        Class<? extends Cache> typeClass = this.typeAliasRegistry.resolveAlias(type);
        String eviction = context.getStringAttribute("eviction", "LRU");    //淘汰策略
        Class<? extends Cache> evictionClass = this.typeAliasRegistry.resolveAlias(eviction);
        Long flushInterval = context.getLongAttribute("flushInterval");
        Integer size = context.getIntAttribute("size");
        boolean readWrite = !context.getBooleanAttribute("readOnly", false);
        boolean blocking = context.getBooleanAttribute("blocking", false);
        Properties props = context.getChildrenAsProperties();
        this.builderAssistant.useNewCache(typeClass, evictionClass, flushInterval, size, readWrite, blocking, props);//使用Java的反射机制初始化
    }
}

this.builderAssistant.useNewCache(typeClass, evictionClass, flushInterval, size, readWrite, blocking, props);

public Cache useNewCache(Class<? extends Cache> typeClass, Class<? extends Cache> evictionClass, Long flushInterval, Integer size, boolean readWrite, boolean blocking, Properties props) {
    Cache cache = (new CacheBuilder(this.currentNamespace)).implementation((Class)this.valueOrDefault(typeClass, PerpetualCache.class)).addDecorator((Class)this.valueOrDefault(evictionClass, LruCache.class)).clearInterval(flushInterval).size(size).readWrite(readWrite).blocking(blocking).properties(props).build();
    this.configuration.addCache(cache);    //将cache配置添加到configura中
    this.currentCache = cache;
    return cache;
}

测试代码

// 4.获取Session
SqlSession sqlSession = sqlSessionFactory.openSession();
SqlSession sqlSession2 = sqlSessionFactory.openSession();
// 5.操作Mapper接口
UserMapper mapper = sqlSession.getMapper(UserMapper.class);

System.out.println("第一次调用....");
UserEntity o = sqlSession.selectOne("com.mayikt.mapper.UserMapper.getUser", 1);    //断点①
System.out.println(o.getName());

System.out.println("第二次调用....");
UserEntity o2 = sqlSession2.selectOne("com.mayikt.mapper.UserMapper.getUser", 1);    //断点②
System.out.println(o2.getName());

public <T> T selectOne(String statement, Object parameter) {
    List<T> list = this.selectList(statement, parameter);//进入这里
    if (list.size() == 1) {
        return list.get(0);
    } else if (list.size() > 1) {
        throw new TooManyResultsException("Expected one result (or null) to be returned by selectOne(), but found: " + list.size());
    } else {
        return null;
    }
}

public <E> List<E> selectList(String statement, Object parameter) {
    return this.selectList(statement, parameter, RowBounds.DEFAULT);//进入这里
}

public <E> List<E> selectList(String statement, Object parameter, RowBounds rowBounds) {
    List var5;
    try {
        MappedStatement ms = this.configuration.getMappedStatement(statement);//拿到sql语句的对象
        var5 = this.executor.query(ms, this.wrapCollection(parameter), rowBounds, Executor.NO_RESULT_HANDLER);//到这里
    } catch (Exception var9) {
        throw ExceptionFactory.wrapException("Error querying database.  Cause: " + var9, var9);
    } finally {
        ErrorContext.instance().reset();
    }
    return var5;
}

因为我们配置了外置缓存Redis缓存所以先走CacheExecutor执行器（代表二级缓存）

public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler) throws SQLException {
    BoundSql boundSql = ms.getBoundSql(parameterObject);    //拿到SQL语句
    CacheKey key = this.createCacheKey(ms, parameterObject, rowBounds, boundSql);    //创建缓存key
    return this.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
}

CacheKey key = this.createCacheKey(ms, parameterObject, rowBounds, boundSql);//创建缓存key

执行query方法：

return this.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);

public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException {
    Cache cache = ms.getCache();
    if (cache != null) {
        this.flushCacheIfRequired(ms);    //缓存不为空，刷新缓存配置，清除缓存
        if (ms.isUseCache() && resultHandler == null) {
            this.ensureNoOutParams(ms, parameterObject, boundSql);
            List<E> list = (List)this.tcm.getObject(cache, key);    //查询二级缓存数据
            if (list == null) {    //第一次查询肯定没有。执行下面代码
                list = this.delegate.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
                this.tcm.putObject(cache, key, list);
            }
            return list;
        }
    }

cache不为空：

private void flushCacheIfRequired(MappedStatement ms) {
    Cache cache = ms.getCache();
    if (cache != null && ms.isFlushCacheRequired()) {
        this.tcm.clear(cache);    //缓存不为空，清空缓存
    }
}

list = this.delegate.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);

二级缓存没有数据，就执行BaseExecutor查询一级缓存数据

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 (this.closed) {
        throw new ExecutorException("Executor was closed.");
    } else {
        if (this.queryStack == 0 && ms.isFlushCacheRequired()) {
            this.clearLocalCache();
        }
        List list;
        try {
            ++this.queryStack;
            list = resultHandler == null ? (List)this.localCache.getObject(key) : null; //判断一级缓存是否有数据，这里第一次查询也是没有的
            if (list != null) {
                this.handleLocallyCachedOutputParameters(ms, key, parameter, boundSql);
            } else {    //进入这块
                list = this.queryFromDatabase(ms, parameter, rowBounds, resultHandler, key, boundSql);    //先去查询数据库
            }
        } finally {
            --this.queryStack;
        }
        if (this.queryStack == 0) {
            Iterator i$ = this.deferredLoads.iterator();

            while(i$.hasNext()) {
                BaseExecutor.DeferredLoad deferredLoad = (BaseExecutor.DeferredLoad)i$.next();
                deferredLoad.load();
            }

            this.deferredLoads.clear();
            if (this.configuration.getLocalCacheScope() == LocalCacheScope.STATEMENT) {
                this.clearLocalCache();
            }
        }
        return list;
    }
}

list = this.queryFromDatabase(ms, parameter, rowBounds, resultHandler, key, boundSql);//查询数据库

private <E> List<E> queryFromDatabase(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException {
    this.localCache.putObject(key, ExecutionPlaceholder.EXECUTION_PLACEHOLDER); //先使用占位符去缓存一个key,表示我现在要去查询数据库了
    List list;
    try {
        list = this.doQuery(ms, parameter, rowBounds, resultHandler, boundSql);    //去查询数据库数据
    } finally {
        this.localCache.removeObject(key);    //将之前缓存的占位符key删除了
    }
    this.localCache.putObject(key, list);    //再将查询到的数据缓存到一级缓存中
    if (ms.getStatementType() == StatementType.CALLABLE) {
        this.localOutputParameterCache.putObject(key, parameter);
    }
    return list;
}

this.tcm.putObject(cache, key, list);再把一级缓存数据放入二级缓存中

发现第二次查询的时候：二级缓存还是没有数据，这是为什么？

我们地清除地知道，每次调用openSession地时候，开启了二级缓存，每次都会new CacheExecutor执行器（二级缓存）

Executor executor = this.configuration.newExecutor(tx, execType);

public Executor newExecutor(Transaction transaction, ExecutorType executorType) {
    executorType = executorType == null ? this.defaultExecutorType : executorType;
    executorType = executorType == null ? ExecutorType.SIMPLE : executorType;
    Object executor;
    if (ExecutorType.BATCH == executorType) {
        executor = new BatchExecutor(this, transaction);
    } else if (ExecutorType.REUSE == executorType) {
        executor = new ReuseExecutor(this, transaction);
    } else {
        executor = new SimpleExecutor(this, transaction);
    }
    if (this.cacheEnabled) {
        executor = new CachingExecutor((Executor)executor);    //每次开启了二级缓存，都会器new 一个CachingExecutor二级缓存执行器
    }
    Executor executor = (Executor)this.interceptorChain.pluginAll(executor);
    return executor;
}

我们可以知道了：每次new一个CachingExecutor二级缓存执行器，都会new TransactionalCacheManager()

所以：TransactionalCacheManager管理我们地TransactionalCache和SQLSession绑定

我们执行下代码：发现执行了两次SQL查询

第一次调用.... 11:08:35.474 [main] DEBUG com.mayikt.cache.MybatisRedisCache - >>>>>>>>>>>>>>>>>>>>>>>>getObject:-978696591:1452564226:com.mayikt.mapper.UserMapper.getUser:0:2147483647:select * from user where id=?:1:development=null Cache Hit Ratio [com.mayikt.mapper.UserMapper]: 0.0 Opening JDBC Connection Created connection 294184992. Setting autocommit to false on JDBC Connection [com.mysql.jdbc.JDBC4Connection@1188e820] ==> Preparing: select * from user where id=? ==> Parameters: 1(Integer) <== Columns: id, name, update_time <== Row: 1, xuyu, 2019-03-13 14:27:49.0 <== Total: 1 xuyu 第二次调用.... 11:08:35.704 [main] DEBUG com.mayikt.cache.MybatisRedisCache - >>>>>>>>>>>>>>>>>>>>>>>>getObject:-978696591:1452564226:com.mayikt.mapper.UserMapper.getUser:0:2147483647:select * from user where id=?:1:development=null Cache Hit Ratio [com.mayikt.mapper.UserMapper]: 0.0 Opening JDBC Connection Created connection 1268959798. Setting autocommit to false on JDBC Connection [com.mysql.jdbc.JDBC4Connection@4ba2ca36] ==> Preparing: select * from user where id=? ==> Parameters: 1(Integer) <== Columns: id, name, update_time <== Row: 1, xuyu, 2019-03-13 14:27:49.0 <== Total: 1 xuyu

假如我们在查询中间添加：

sqlSession.close();

结果如下：我们发现，第一次查询了数据库，第二次直接走缓存了，没有再去查询数据库，缓存生效了，这是为什么呢？下面我们开始源码分析

第一次调用.... 11:10:06.121 [main] DEBUG com.mayikt.cache.MybatisRedisCache - >>>>>>>>>>>>>>>>>>>>>>>>getObject:-978696591:1452564226:com.mayikt.mapper.UserMapper.getUser:0:2147483647:select * from user where id=?:1:development=null Cache Hit Ratio [com.mayikt.mapper.UserMapper]: 0.0 Opening JDBC Connection Created connection 294184992. Setting autocommit to false on JDBC Connection [com.mysql.jdbc.JDBC4Connection@1188e820] ==> Preparing: select * from user where id=? ==> Parameters: 1(Integer) <== Columns: id, name, update_time <== Row: 1, xuyu, 2019-03-13 14:27:49.0 <== Total: 1 xuyu 11:10:06.350 [main] DEBUG com.mayikt.cache.MybatisRedisCache - >>>>>>>>>>>>>>>>>>>>>>>>putObject:-978696591:1452564226:com.mayikt.mapper.UserMapper.getUser:0:2147483647:select * from user where id=?:1:development=[com.mayikt.entity.UserEntity@1dd02175] Resetting autocommit to true on JDBC Connection [com.mysql.jdbc.JDBC4Connection@1188e820] Closing JDBC Connection [com.mysql.jdbc.JDBC4Connection@1188e820] Returned connection 294184992 to pool. 第二次调用.... 11:10:06.404 [main] DEBUG com.mayikt.cache.MybatisRedisCache - >>>>>>>>>>>>>>>>>>>>>>>>getObject:-978696591:1452564226:com.mayikt.mapper.UserMapper.getUser:0:2147483647:select * from user where id=?:1:development=[com.mayikt.entity.UserEntity@2357d90a] Cache Hit Ratio [com.mayikt.mapper.UserMapper]: 0.5 xuyu

重点来看下这段代码：

先看下tcm指什么？指的是TransactionalCacheManager，作为二级缓存查询

public Object getObject(Cache cache, CacheKey key) {
    return this.getTransactionalCache(cache).getObject(key);
}

public Object getObject(Object key) {
    Object object = this.delegate.getObject(key);
    if (object == null) {
        this.entriesMissedInCache.add(key);
    }
    return this.clearOnCommit ? null : object;
}

private Set<Object> entriesMissedInCache;//代表一级缓存存放数据到二级缓存数据

下面我们来debug源码分析下：

List<E> list = (List)this.tcm.getObject(cache, key);

public Object getObject(Cache cache, CacheKey key) {
    return this.getTransactionalCache(cache).getObject(key);
}

private TransactionalCache getTransactionalCache(Cache cache) {
    TransactionalCache txCache = (TransactionalCache)this.transactionalCaches.get(cache);    //
    if (txCache == null) {
        txCache = new TransactionalCache(cache);    //二级缓存没有数据，就创建一个新的TransactionalCache
        this.transactionalCaches.put(cache, txCache);    //把缓存数据添加到TransactionalCache里
    }
    return txCache;
}

//transactionalCaches为map集合 private Map<Cache, TransactionalCache> transactionalCaches = new HashMap();

这个cache指的是我们自定义Redis二级缓存

最后回到getObject方法：

public Object getObject(Object key) {
    Object object = this.delegate.getObject(key);
    if (object == null) {
        this.entriesMissedInCache.add(key);
    }
    return this.clearOnCommit ? null : object;
}

public Object getObject(Object key) {
    ++this.requests;    //记录每次查询次数
    Object value = this.delegate.getObject(key);
    if (value != null) {
        ++this.hits;
    }
    if (this.log.isDebugEnabled()) {
        this.log.debug("Cache Hit Ratio [" + this.getId() + "]: " + this.getHitRatio());
    }
    return value;
}

由上图可知，开始调用我们自定义的MybatisRedisCache外置缓存方法

public Object getObject(Object key) {
    Object value = SerializeUtil.unserialize(redisClient.get(SerializeUtil.serialize(key.toString())));
    logger.debug(">>>>>>>>>>>>>>>>>>>>>>>>getObject:" + key + "=" + value);
    return value;
}

我们知道了，我们第一次查询，二级缓存是没有数据的，最后进入entriesMissedInCache去添加我们的缓存数据

最后返回到

再去一级缓存查询数据

一级缓存没有数据，就查询数据库，查询到数据，将结果返回给一级缓存，一级缓存再把数据缓存给二级缓存

public void putObject(Cache cache, CacheKey key, Object value) {
    this.getTransactionalCache(cache).putObject(key, value);
}

就回去调用getTransactionalCache方法创建事务的缓存

private TransactionalCache getTransactionalCache(Cache cache) {
    TransactionalCache txCache = (TransactionalCache)this.transactionalCaches.get(cache);
    if (txCache == null) {
        txCache = new TransactionalCache(cache);
        this.transactionalCaches.put(cache, txCache);
    }

    return txCache;
}

调用

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

private Map<Object, Object> entriesToAddOnCommit;

我们知道了entriesToAddOnCommit集合为临时存储的事务缓存（一级缓存数据添加到二级缓存先添加到entriesToAddOnCommit集合临时缓存起来）

List<E> list = (List)this.tcm.getObject(cache, key);//会从redis中获取缓存数据

this.tcm.putObject(cache, key, list);//只是将数据存放到getTransactionalCache的entriesToAddOnCommit的map集合中

那什么时候去取出getTransactionalCache中的缓存数据呢？下面我们代码进入sqlSession.close()方法

public void close(boolean forceRollback) {
    try {
        if (forceRollback) {    //是否需要强制回滚，我们是不需要的
            this.tcm.rollback();
        } else {
            this.tcm.commit();    //这块重点了，表示要提交数据到redis了
        }
    } finally {
        this.delegate.close(forceRollback);
    }

}

public void commit() {
    Iterator i$ = this.transactionalCaches.values().iterator();
    while(i$.hasNext()) {    //循环迭代TransactionalCache
        TransactionalCache txCache = (TransactionalCache)i$.next();
        txCache.commit();
    }
}

public void commit() {
    if (this.clearOnCommit) {
        this.delegate.clear();
    }

    this.flushPendingEntries();
    this.reset();
}

private void flushPendingEntries() {
    Iterator i$ = this.entriesToAddOnCommit.entrySet().iterator();

    while(i$.hasNext()) {
        Entry<Object, Object> entry = (Entry)i$.next();
        this.delegate.putObject(entry.getKey(), entry.getValue());    //遍历entriesToAddOnCommit，把数据刷新到redis中
    }

    i$ = this.entriesMissedInCache.iterator();

    while(i$.hasNext()) {
        Object entry = i$.next();
        if (!this.entriesToAddOnCommit.containsKey(entry)) {
            this.delegate.putObject(entry, (Object)null);
        }
    }

}

public void putObject(Object key, Object value) {
    logger.debug(">>>>>>>>>>>>>>>>>>>>>>>>putObject:" + key + "=" + value);
    redisClient.set(SerializeUtil.serialize(key.toString()), SerializeUtil.serialize(value));
}

我们可知：最后将临时缓存数据提交到了redis缓存中

再次查询

就直接从redis缓存中取出数据了。

结果：

第一次调用.... 12:57:19.090 [main] DEBUG com.mayikt.cache.MybatisRedisCache - >>>>>>>>>>>>>>>>>>>>>>>>getObject:-978696591:1452564226:com.mayikt.mapper.UserMapper.getUser:0:2147483647:select * from user where id=?:1:development=null Cache Hit Ratio [com.mayikt.mapper.UserMapper]: 0.0 Opening JDBC Connection Created connection 294184992. Setting autocommit to false on JDBC Connection [com.mysql.jdbc.JDBC4Connection@1188e820] ==> Preparing: select * from user where id=? ==> Parameters: 1(Integer) <== Columns: id, name, update_time <== Row: 1, xuyu, 2019-03-13 14:27:49.0 <== Total: 1 xuyu 12:57:19.318 [main] DEBUG com.mayikt.cache.MybatisRedisCache - >>>>>>>>>>>>>>>>>>>>>>>>putObject:-978696591:1452564226:com.mayikt.mapper.UserMapper.getUser:0:2147483647:select * from user where id=?:1:development=[com.mayikt.entity.UserEntity@1dd02175] 第二次调用.... 12:57:19.360 [main] DEBUG com.mayikt.cache.MybatisRedisCache - >>>>>>>>>>>>>>>>>>>>>>>>getObject:-978696591:1452564226:com.mayikt.mapper.UserMapper.getUser:0:2147483647:select * from user where id=?:1:development=[com.mayikt.entity.UserEntity@2357d90a] Cache Hit Ratio [com.mayikt.mapper.UserMapper]: 0.5 xuyu

我们思考下，我们要使得缓存生效，每次都要调用close()方法，这样不是很麻烦？

如果使用相同的sqlsession缓存，那么也是查询一次，但是使用的缓存只是一级缓存，那么我们有没有办法调用同一个sqlsession，也使得二级缓存生效。

sqlSession.close();
//sqlSession.commit();

我们先看下二级缓存回收策略

　LRU：最近最少使用的策略，移除最长时间不被使用的对象。
　FIFO：先进先出策略，按对象进入缓存的顺序来移除它们。
　SOFT：软引用策略，移除基于垃圾回收器状态和软引用规则的对象。
　WEAK：弱引用策略，更积极地移除基于垃圾收集器状态和弱引用规则的对象。

软引用与弱引用的区别:

软引用: 软引用是用来描述一些有用但并不是必需的对象, 对于软引用关联着的对象，只有在内存不足的时候JVM才会回收该对象
弱引用: 弱引用也是用来描述非必需对象的，当JVM进行垃圾回收时，无论内存是否充足，都会回收被弱引用关联的对象

回到我们实际springboot项目中整合redis缓存

mapper层：

@CacheNamespace(implementation = MybatisRedisCache.class)
public interface OrderMapper {
   @Insert("insert order_info values (null,#{orderName},#{orderDes})")
   public int addOrder(OrderEntity OrderEntity);

   @Select("SELECT * FROM order_info;")
   public List<OrderEntity> findByOrder();
}

redis

@Component
public class RedisToken {
    @Autowired
    private StringRedisTemplate stringRedisTemplate;
    /**
     * 获取Token
     */
    public String getToken() {
        //1. 使用uuid生成Token
        String token = UUID.randomUUID().toString().replace("-", "");
        //2. 将Token存放到Redis中
        setString(token, token, 7200l);
        return token;
    }
    public Boolean findByToken(String token) {
        if (StringUtils.isEmpty(token)) {
            return false;
        }
        String redisToken = getString(token);
        if(StringUtils.isEmpty(redisToken)){
            return  false;
        }
        delKey(redisToken);
        return  true;
    }
    private void setString(String key, Object data, Long timeout) {
        if (data instanceof String) {
            String value = (String) data;
            stringRedisTemplate.opsForValue().set(key, value);
        }
        if (timeout != null) {
            stringRedisTemplate.expire(key, timeout, TimeUnit.SECONDS);
        }
    }
    private String getString(String key) {
        return stringRedisTemplate.opsForValue().get(key);
    }
    private void delKey(String key) {
        stringRedisTemplate.delete(key);
    }
}

MybatisRedisCache

**
 * mybatis二级缓存整合Redis
 */
public class MybatisRedisCache implements Cache {
    private static Logger logger = LoggerFactory.getLogger(MybatisRedisCache.class);
    private Jedis redisClient = createReids();
    private final ReadWriteLock readWriteLock = new ReentrantReadWriteLock();
    private String id;
    public MybatisRedisCache(final String id) {
        if (id == null) {
            throw new IllegalArgumentException("Cache instances require an ID");
        }
        logger.debug(">>>>>>>>>>>>>>>>>>>>>>>>MybatisRedisCache:id=" + id);
        this.id = id;
    }
    public String getId() {
        return this.id;
    }
    public int getSize() {
        return Integer.valueOf(redisClient.dbSize().toString());
    }
    public void putObject(Object key, Object value) {
        logger.debug(">>>>>>>>>>>>>>>>>>>>>>>>putObject:" + key + "=" + value);
        redisClient.set(SerializeUtil.serialize(key.toString()), SerializeUtil.serialize(value));
    }
    public Object getObject(Object key) {
        Object value = SerializeUtil.unserialize(redisClient.get(SerializeUtil.serialize(key.toString())));
        logger.debug(">>>>>>>>>>>>>>>>>>>>>>>>getObject:" + key + "=" + value);
        return value;
    }
    public Object removeObject(Object key) {
        return redisClient.expire(SerializeUtil.serialize(key.toString()), 0);
    }
    public void clear() {
        redisClient.flushDB();
    }
    public ReadWriteLock getReadWriteLock() {
        return readWriteLock;
    }
    protected static Jedis createReids() {
        JedisPool pool = new JedisPool("127.0.0.1", 6379);
        return pool.getResource();
    }
}

启动类

@SpringBootApplication
@MapperScan("com.mayikt.api.mapper")
@EnableCaching
public class OrderApp {

    public static void main(String[] args) {
        SpringApplication.run(OrderApp.class);
    }
}

访问：http://127.0.0.1:8080/getOrderList

最终被SqlSessionInterceptor拦截器拦截了， sqlSession.commit(true);也被调用了

private class SqlSessionInterceptor implements InvocationHandler {
    private SqlSessionInterceptor() {
    }
    public Object invoke(Object proxy, Method method, Object[] args) throws Throwable {
        SqlSession sqlSession = SqlSessionUtils.getSqlSession(SqlSessionTemplate.this.sqlSessionFactory, SqlSessionTemplate.this.executorType, SqlSessionTemplate.this.exceptionTranslator);

        Object unwrapped;
        try {
            Object result = method.invoke(sqlSession, args);
            if (!SqlSessionUtils.isSqlSessionTransactional(sqlSession, SqlSessionTemplate.this.sqlSessionFactory)) {
                sqlSession.commit(true);
            }
            unwrapped = result;
        } catch (Throwable var11) {
            unwrapped = ExceptionUtil.unwrapThrowable(var11);
            if (SqlSessionTemplate.this.exceptionTranslator != null && unwrapped instanceof PersistenceException) {
                SqlSessionUtils.closeSqlSession(sqlSession, SqlSessionTemplate.this.sqlSessionFactory);
                sqlSession = null;
                Throwable translated = SqlSessionTemplate.this.exceptionTranslator.translateExceptionIfPossible((PersistenceException)unwrapped);
                if (translated != null) {
                    unwrapped = translated;
                }
            }

            throw (Throwable)unwrapped;
        } finally {
            if (sqlSession != null) {
                SqlSessionUtils.closeSqlSession(sqlSession, SqlSessionTemplate.this.sqlSessionFactory);
            }
        }
        return unwrapped;
    }
}

提交数据

public void commit(boolean force) {
    try {
        this.executor.commit(this.isCommitOrRollbackRequired(force));
        this.dirty = false;
    } catch (Exception var6) {
        throw ExceptionFactory.wrapException("Error committing transaction.  Cause: " + var6, var6);
    } finally {
        ErrorContext.instance().reset();
    }
}

private boolean isCommitOrRollbackRequired(boolean force) {
    return !this.autoCommit && this.dirty || force;
}

public void commit() {
    Iterator i$ = this.transactionalCaches.values().iterator();

    while(i$.hasNext()) {
        TransactionalCache txCache = (TransactionalCache)i$.next();
        txCache.commit();
    }

}

public void commit() {
    if (this.clearOnCommit) {
        this.delegate.clear();
    }

    this.flushPendingEntries();
    this.reset();
}

private void flushPendingEntries() {
    Iterator i$ = this.entriesToAddOnCommit.entrySet().iterator();

    while(i$.hasNext()) {
        Entry<Object, Object> entry = (Entry)i$.next();
        this.delegate.putObject(entry.getKey(), entry.getValue());
    }

    i$ = this.entriesMissedInCache.iterator();

    while(i$.hasNext()) {
        Object entry = i$.next();
        if (!this.entriesToAddOnCommit.containsKey(entry)) {
            this.delegate.putObject(entry, (Object)null);
        }
    }

}

public void putObject(Object key, Object value) {
    logger.debug(">>>>>>>>>>>>>>>>>>>>>>>>putObject:" + key + "=" + value);
    redisClient.set(SerializeUtil.serialize(key.toString()), SerializeUtil.serialize(value));
}

看下redis是否有数据了。

这里最终会把当前session关闭掉。

最后，我们来总结下上面的源码分析

总结：

TransactionalCache

继承自Cache接口，主要作用是保存SqlSession在事务中需要向某个二级缓存提交的缓存数据因为在事务过程中的数据可能会回滚，所以不能直接把数据提交给二级缓存，而是暂存于TransactionalCache中，在事务提交后再将存放在其中的数据提交给二级缓存，如果事务回滚，则将数据清除掉。

TransactionalCacheManager

用于管理CacheExecutor使用的二级缓存对象，只定义了一个transactionalCaches字段
private final Cache delegate; //对应的二级缓存对象
private boolean clearOnCommit; //是否在commit时清除二级缓存的标记
// 需要在commit时提交到二级缓存的数据
private final Map<Object, Object> entriesToAddOnCommit;
// 缓存未命中的数据，事务commit时，也会放入二级缓存（key,null）
private final Set<Object> entriesMissedInCache;

StatementHandler

StatementHandler接口的实现大致有四个，其中三个实现类都是和JDBC中的Statement响对应的：

SimpleStatementHandler，这个很简单了，就是对应我们JDBC中常用的Statement接口，用于简单SQL的处理；存在sql注入攻击问题
PreparedStatementHandler，这个对应JDBC中的PreparedStatement，预编译SQL的接口；防止sql注入
CallableStatementHandler，这个对应JDBC中CallableStatement，用于执行存储过程相关的接口；
RoutingStatementHandler，这个接口是以上三个接口的路由，没有实际操作，只是负责上面三个StatementHandler的创建及调用。

ResultSetHandler

就是将Statement实例执行之后返回的ResultSet结果集转换成我们需要的List结果集

一级缓存与二级缓存区别

①、一级缓存是SqlSession级别的缓存。在操作数据库时需要构造sqlSession对象，在对象中有一个数据结构（HashMap）用于存储缓存数据。不同的sqlSession之间的缓存数据区域（sqlHashMap）是互相不影响的。 ②、二级缓存是mapper级别的缓存，多个SqlSession去操作同一个Mapper的语句，多个SqlSession可以共用二级缓存，二级缓存是跨SqlSession的。注意：sqlSession缓存底层存在线程安全问题。

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