MyBatis緩存介紹
MyBatis支持聲明式數據緩存(declarative data caching)。當一條SQL語句被標記爲「可緩存」後,首次執行它時從數據庫獲取的全部數據會被存儲在一段高速緩存中,從此執行這條語句時就會從高速緩存中讀取結果,而不是再次命中數據庫。MyBatis提供了默認下基於Java HashMap的緩存實現,以及用於與OSCache、Ehcache、Hazelcast和Memcached鏈接的默認鏈接器。MyBatis還提供API供其餘緩存實現使用。html
重點的那句話就是:MyBatis執行SQL語句以後,這條語句就是被緩存,之後再執行這條語句的時候,會直接從緩存中拿結果,而不是再次執行SQLjava
這也就是你們常說的MyBatis一級緩存,一級緩存的做用域scope是SqlSession。node
MyBatis同時還提供了一種全局做用域global scope的緩存,這也叫作二級緩存,也稱做全局緩存。sql
一級緩存
測試
同個session進行兩次相同查詢:數據庫
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@Test public void test() { SqlSession sqlSession = sqlSessionFactory.openSession(); try { User user = (User)sqlSession.selectOne( "org.format.mybatis.cache.UserMapper.getById" , 1 ); log.debug(user); User user2 = (User)sqlSession.selectOne( "org.format.mybatis.cache.UserMapper.getById" , 1 ); log.debug(user2); } finally { sqlSession.close(); } } |
MyBatis只進行1次數據庫查詢:
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==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 1 (Integer) <== Total: 1 User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } |
同個session進行兩次不一樣的查詢:
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@Test public void test() { SqlSession sqlSession = sqlSessionFactory.openSession(); try { User user = (User)sqlSession.selectOne( "org.format.mybatis.cache.UserMapper.getById" , 1 ); log.debug(user); User user2 = (User)sqlSession.selectOne( "org.format.mybatis.cache.UserMapper.getById" , 2 ); log.debug(user2); } finally { sqlSession.close(); } } |
MyBatis進行兩次數據庫查詢:
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==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 1 (Integer) <== Total: 1 User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } ==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 2 (Integer) <== Total: 1 User{id= 2 , name= 'FFF' , age= 50 , birthday=Sat Dec 06 17 : 12 : 01 CST 2014 } |
不一樣session,進行相同查詢:
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@Test public void test() { SqlSession sqlSession = sqlSessionFactory.openSession(); SqlSession sqlSession2 = sqlSessionFactory.openSession(); try { User user = (User)sqlSession.selectOne( "org.format.mybatis.cache.UserMapper.getById" , 1 ); log.debug(user); User user2 = (User)sqlSession2.selectOne( "org.format.mybatis.cache.UserMapper.getById" , 1 ); log.debug(user2); } finally { sqlSession.close(); sqlSession2.close(); } } |
MyBatis進行了兩次數據庫查詢:
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==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 1 (Integer) <== Total: 1 User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } ==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 1 (Integer) <== Total: 1 User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } |
同個session,查詢以後更新數據,再次查詢相同的語句:
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@Test public void test() { SqlSession sqlSession = sqlSessionFactory.openSession(); try { User user = (User)sqlSession.selectOne( "org.format.mybatis.cache.UserMapper.getById" , 1 ); log.debug(user); user.setAge( 100 ); sqlSession.update( "org.format.mybatis.cache.UserMapper.update" , user); User user2 = (User)sqlSession.selectOne( "org.format.mybatis.cache.UserMapper.getById" , 1 ); log.debug(user2); sqlSession.commit(); } finally { sqlSession.close(); } } |
更新操做以後緩存會被清除:
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==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 1 (Integer) <== Total: 1 User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } ==> Preparing: update USERS SET NAME = ? , AGE = ? , BIRTHDAY = ? where ID = ? ==> Parameters: format(String), 23 (Integer), 2014 - 10 - 12 23 : 20 : 13.0 (Timestamp), 1 (Integer) <== Updates: 1 ==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 1 (Integer) <== Total: 1 User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } |
很明顯,結果驗證了一級緩存的概念,在同個SqlSession中,查詢語句相同的sql會被緩存,可是一旦執行新增或更新或刪除操做,緩存就會被清除
源碼分析
在分析MyBatis的一級緩存以前,咱們先簡單看下MyBatis中幾個重要的類和接口:
org.apache.ibatis.session.Configuration類:MyBatis全局配置信息類
org.apache.ibatis.session.SqlSessionFactory接口:操做SqlSession的工廠接口,具體的實現類是DefaultSqlSessionFactory
org.apache.ibatis.session.SqlSession接口:執行sql,管理事務的接口,具體的實現類是DefaultSqlSession
org.apache.ibatis.executor.Executor接口:sql執行器,SqlSession執行sql最終是經過該接口實現的,經常使用的實現類有SimpleExecutor和CachingExecutor,這些實現類都使用了裝飾者設計模式
一級緩存的做用域是SqlSession,那麼咱們就先看一下SqlSession的select過程:
這是DefaultSqlSession(SqlSession接口實現類,MyBatis默認使用這個類)的selectList源碼(咱們例子上使用的是selectOne方法,調用selectOne方法最終會執行selectList方法):
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public <E> List<E> selectList(String statement, Object parameter, RowBounds rowBounds) { try { MappedStatement ms = configuration.getMappedStatement(statement); List<E> result = executor.query(ms, wrapCollection(parameter), rowBounds, Executor.NO_RESULT_HANDLER); return result; } catch (Exception e) { throw ExceptionFactory.wrapException( "Error querying database. Cause: " + e, e); } finally { ErrorContext.instance().reset(); } } |
咱們看到SqlSession最終會調用Executor接口的方法。
接下來咱們看下DefaultSqlSession中的executor接口屬性具體是哪一個實現類。
DefaultSqlSession的構造過程(DefaultSqlSessionFactory內部):
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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, autoCommit); return new DefaultSqlSession(configuration, executor); } 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(); } } |
咱們看到DefaultSqlSessionFactory構造DefaultSqlSession的時候,Executor接口的實現類是由Configuration構造的:
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public Executor newExecutor(Transaction transaction, ExecutorType executorType, boolean autoCommit) { executorType = executorType == null ? defaultExecutorType : executorType; executorType = executorType == null ? ExecutorType.SIMPLE : executorType; Executor 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 (cacheEnabled) { executor = new CachingExecutor(executor, autoCommit); } executor = (Executor) interceptorChain.pluginAll(executor); return executor; } |
Executor根據ExecutorType的不一樣而建立,最經常使用的是SimpleExecutor,本文的例子也是建立這個實現類。 最後咱們發現若是cacheEnabled這個屬性爲true的話,那麼executor會被包一層裝飾器,這個裝飾器是CachingExecutor。其中cacheEnabled這個屬性是mybatis總配置文件中settings節點中cacheEnabled子節點的值,默認就是true,也就是說咱們在mybatis總配置文件中不配cacheEnabled的話,它也是默認爲打開的。
如今,問題就剩下一個了,CachingExecutor執行sql的時候到底作了什麼?
帶着這個問題,咱們繼續走下去(CachingExecutor的query方法):
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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 ) { flushCacheIfRequired(ms); if (ms.isUseCache() && resultHandler == null ) { ensureNoOutParams(ms, parameterObject, boundSql); if (!dirty) { cache.getReadWriteLock().readLock().lock(); try { @SuppressWarnings ( "unchecked" ) List<E> cachedList = (List<E>) cache.getObject(key); if (cachedList != null ) return cachedList; } finally { cache.getReadWriteLock().readLock().unlock(); } } List<E> list = delegate.<E> query(ms, parameterObject, rowBounds, resultHandler, key, boundSql); tcm.putObject(cache, key, list); // issue #578. Query must be not synchronized to prevent deadlocks return list; } } return delegate.<E>query(ms, parameterObject, rowBounds, resultHandler, key, boundSql); } |
其中Cache cache = ms.getCache();這句代碼中,這個cache實際上就是個二級緩存,因爲咱們沒有開啓二級緩存(二級緩存的內容下面會分析),所以這裏執行了最後一句話。這裏的delegate也就是SimpleExecutor,SimpleExecutor沒有Override父類的query方法,所以最終執行了SimpleExecutor的父類BaseExecutor的query方法。
因此一級緩存最重要的代碼就是BaseExecutor的query方法!
![](http://static.javashuo.com/static/loading.gif)
BaseExecutor的屬性localCache是個PerpetualCache類型的實例,PerpetualCache類是實現了MyBatis的Cache緩存接口的實現類之一,內部有個Map類型的屬性用來存儲緩存數據。 這個localCache的類型在BaseExecutor內部是寫死的。 這個localCache就是一級緩存!
接下來咱們看下爲什麼執行新增或更新或刪除操做,一級緩存就會被清除這個問題。
首先MyBatis處理新增或刪除的時候,最終都是調用update方法,也就是說新增或者刪除操做在MyBatis眼裏都是一個更新操做。
咱們看下DefaultSqlSession的update方法:
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public int update(String statement, Object parameter) { try { dirty = true ; MappedStatement ms = configuration.getMappedStatement(statement); return executor.update(ms, wrapCollection(parameter)); } catch (Exception e) { throw ExceptionFactory.wrapException( "Error updating database. Cause: " + e, e); } finally { ErrorContext.instance().reset(); } } |
很明顯,這裏調用了CachingExecutor的update方法:
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public int update(MappedStatement ms, Object parameterObject) throws SQLException { flushCacheIfRequired(ms); return delegate.update(ms, parameterObject); } |
這裏的flushCacheIfRequired方法清除的是二級緩存,咱們以後會分析。 CachingExecutor委託給了(以前已經分析過)SimpleExecutor的update方法,SimpleExecutor沒有Override父類BaseExecutor的update方法,所以咱們看BaseExecutor的update方法:
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public int update(MappedStatement ms, Object parameter) throws SQLException { ErrorContext.instance().resource(ms.getResource()).activity( "executing an update" ).object(ms.getId()); if (closed) throw new ExecutorException( "Executor was closed." ); clearLocalCache(); return doUpdate(ms, parameter); } |
咱們看到了關鍵的一句代碼: clearLocalCache(); 進去看看:
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public void clearLocalCache() { if (!closed) { localCache.clear(); localOutputParameterCache.clear(); } } |
沒錯,就是這條,sqlsession沒有關閉的話,進行新增、刪除、修改操做的話就是清除一級緩存,也就是SqlSession的緩存。
二級緩存
二級緩存的做用域是全局,換句話說,二級緩存已經脫離SqlSession的控制了。
在測試二級緩存以前,我先把結論說一下:
二級緩存的做用域是全局的,二級緩存在SqlSession關閉或提交以後纔會生效。
在分析MyBatis的二級緩存以前,咱們先簡單看下MyBatis中一個關於二級緩存的類(其餘相關的類和接口以前已經分析過):
org.apache.ibatis.mapping.MappedStatement:
MappedStatement類在Mybatis框架中用於表示XML文件中一個sql語句節點,即一個<select />、<update />或者<insert />標籤。Mybatis框架在初始化階段會對XML配置文件進行讀取,將其中的sql語句節點對象化爲一個個MappedStatement對象。
配置
二級緩存跟一級緩存不一樣,一級緩存不須要配置任何東西,且默認打開。 二級緩存就須要配置一些東西。
本文就說下最簡單的配置,在mapper文件上加上這句配置便可:
其實二級緩存跟3個配置有關:
- mybatis全局配置文件中的setting中的cacheEnabled須要爲true(默認爲true,不設置也行)
- mapper配置文件中須要加入<cache>節點
- mapper配置文件中的select節點須要加上屬性useCache須要爲true(默認爲true,不設置也行)
測試
不一樣SqlSession,查詢相同語句,第一次查詢以後commit SqlSession:
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@Test public void testCache2() { SqlSession sqlSession = sqlSessionFactory.openSession(); SqlSession sqlSession2 = sqlSessionFactory.openSession(); try { String sql = "org.format.mybatis.cache.UserMapper.getById" ; User user = (User)sqlSession.selectOne(sql, 1 ); log.debug(user); // 注意,這裏必定要提交。 不提交仍是會查詢兩次數據庫 sqlSession.commit(); User user2 = (User)sqlSession2.selectOne(sql, 1 ); log.debug(user2); } finally { sqlSession.close(); sqlSession2.close(); } } |
MyBatis僅進行了一次數據庫查詢:
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==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 1 (Integer) <== Total: 1 User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } |
不一樣SqlSession,查詢相同語句,第一次查詢以後close SqlSession:
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@Test public void testCache2() { SqlSession sqlSession = sqlSessionFactory.openSession(); SqlSession sqlSession2 = sqlSessionFactory.openSession(); try { String sql = "org.format.mybatis.cache.UserMapper.getById" ; User user = (User)sqlSession.selectOne(sql, 1 ); log.debug(user); sqlSession.close(); User user2 = (User)sqlSession2.selectOne(sql, 1 ); log.debug(user2); } finally { sqlSession2.close(); } } |
MyBatis僅進行了一次數據庫查詢:
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==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 1 (Integer) <== Total: 1 User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } |
不一樣SqlSesson,查詢相同語句。 第一次查詢以後SqlSession不提交:
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@Test public void testCache2() { SqlSession sqlSession = sqlSessionFactory.openSession(); SqlSession sqlSession2 = sqlSessionFactory.openSession(); try { String sql = "org.format.mybatis.cache.UserMapper.getById" ; User user = (User)sqlSession.selectOne(sql, 1 ); log.debug(user); User user2 = (User)sqlSession2.selectOne(sql, 1 ); log.debug(user2); } finally { sqlSession.close(); sqlSession2.close(); } } |
MyBatis執行了兩次數據庫查詢:
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==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 1 (Integer) <== Total: 1 User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } ==> Preparing: select * from USERS WHERE ID = ? ==> Parameters: 1 (Integer) <== Total: 1 User{id= 1 , name= 'format' , age= 23 , birthday=Sun Oct 12 23 : 20 : 13 CST 2014 } |
源碼分析
咱們從在mapper文件中加入的<cache/>中開始分析源碼,關於MyBatis的SQL解析請參考另一篇博客Mybatis解析動態sql原理分析。接下來咱們看下這個cache的解析:
XMLMappedBuilder(解析每一個mapper配置文件的解析類,每個mapper配置都會實例化一個XMLMapperBuilder類)的解析方法:
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private void configurationElement(XNode context) { try { String namespace = context.getStringAttribute( "namespace" ); if (namespace.equals( "" )) { throw new BuilderException( "Mapper's namespace cannot be empty" ); } builderAssistant.setCurrentNamespace(namespace); cacheRefElement(context.evalNode( "cache-ref" )); cacheElement(context.evalNode( "cache" )); parameterMapElement(context.evalNodes( "/mapper/parameterMap" )); resultMapElements(context.evalNodes( "/mapper/resultMap" )); sqlElement(context.evalNodes( "/mapper/sql" )); buildStatementFromContext(context.evalNodes( "select|insert|update|delete" )); } catch (Exception e) { throw new BuilderException( "Error parsing Mapper XML. Cause: " + e, e); } } |
咱們看到了解析cache的那段代碼:
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private void cacheElement(XNode context) throws Exception { if (context != null ) { String type = context.getStringAttribute( "type" , "PERPETUAL" ); Class<? extends Cache> typeClass = typeAliasRegistry.resolveAlias(type); String eviction = context.getStringAttribute( "eviction" , "LRU" ); Class<? extends Cache> evictionClass = typeAliasRegistry.resolveAlias(eviction); Long flushInterval = context.getLongAttribute( "flushInterval" ); Integer size = context.getIntAttribute( "size" ); boolean readWrite = !context.getBooleanAttribute( "readOnly" , false ); Properties props = context.getChildrenAsProperties(); builderAssistant.useNewCache(typeClass, evictionClass, flushInterval, size, readWrite, props); } } |
解析完cache標籤以後會使用builderAssistant的userNewCache方法,這裏的builderAssistant是一個MapperBuilderAssistant類型的幫助類,每一個XMLMappedBuilder構造的時候都會實例化這個屬性,MapperBuilderAssistant類內部有個Cache類型的currentCache屬性,這個屬性也就是mapper配置文件中cache節點所表明的值:
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public Cache useNewCache(Class<? extends Cache> typeClass, Class<? extends Cache> evictionClass, Long flushInterval, Integer size, boolean readWrite, Properties props) { typeClass = valueOrDefault(typeClass, PerpetualCache. class ); evictionClass = valueOrDefault(evictionClass, LruCache. class ); Cache cache = new CacheBuilder(currentNamespace) .implementation(typeClass) .addDecorator(evictionClass) .clearInterval(flushInterval) .size(size) .readWrite(readWrite) .properties(props) .build(); configuration.addCache(cache); currentCache = cache; return cache; } |
ok,如今mapper配置文件中的cache節點被解析到了XMLMapperBuilder實例中的builderAssistant屬性中的currentCache值裏。
接下來XMLMapperBuilder會解析select節點,解析select節點的時候使用XMLStatementBuilder進行解析(也包括其餘insert,update,delete節點):
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public void parseStatementNode() { String id = context.getStringAttribute( "id" ); String databaseId = context.getStringAttribute( "databaseId" ); if (!databaseIdMatchesCurrent(id, databaseId, this .requiredDatabaseId)) return ; Integer fetchSize = context.getIntAttribute( "fetchSize" ); Integer timeout = context.getIntAttribute( "timeout" ); String parameterMap = context.getStringAttribute( "parameterMap" ); String parameterType = context.getStringAttribute( "parameterType" ); Class<?> parameterTypeClass = resolveClass(parameterType); String resultMap = context.getStringAttribute( "resultMap" ); String resultType = context.getStringAttribute( "resultType" ); String lang = context.getStringAttribute( "lang" ); LanguageDriver langDriver = getLanguageDriver(lang); Class<?> resultTypeClass = resolveClass(resultType); String resultSetType = context.getStringAttribute( "resultSetType" ); StatementType statementType = StatementType.valueOf(context.getStringAttribute( "statementType" , StatementType.PREPARED.toString())); ResultSetType resultSetTypeEnum = resolveResultSetType(resultSetType); String nodeName = context.getNode().getNodeName(); SqlCommandType sqlCommandType = SqlCommandType.valueOf(nodeName.toUpperCase(Locale.ENGLISH)); boolean isSelect = sqlCommandType == SqlCommandType.SELECT; boolean flushCache = context.getBooleanAttribute( "flushCache" , !isSelect); boolean useCache = context.getBooleanAttribute( "useCache" , isSelect); boolean resultOrdered = context.getBooleanAttribute( "resultOrdered" , false ); // Include Fragments before parsing XMLIncludeTransformer includeParser = new XMLIncludeTransformer(configuration, builderAssistant); includeParser.applyIncludes(context.getNode()); // Parse selectKey after includes and remove them. processSelectKeyNodes(id, parameterTypeClass, langDriver); // Parse the SQL (pre: <selectKey> and <include> were parsed and removed) SqlSource sqlSource = langDriver.createSqlSource(configuration, context, parameterTypeClass); String resultSets = context.getStringAttribute( "resultSets" ); String keyProperty = context.getStringAttribute( "keyProperty" ); String keyColumn = context.getStringAttribute( "keyColumn" ); KeyGenerator keyGenerator; String keyStatementId = id + SelectKeyGenerator.SELECT_KEY_SUFFIX; keyStatementId = builderAssistant.applyCurrentNamespace(keyStatementId, true ); if (configuration.hasKeyGenerator(keyStatementId)) { keyGenerator = configuration.getKeyGenerator(keyStatementId); } else { keyGenerator = context.getBooleanAttribute( "useGeneratedKeys" , configuration.isUseGeneratedKeys() && SqlCommandType.INSERT.equals(sqlCommandType)) ? new Jdbc3KeyGenerator() : new NoKeyGenerator(); } builderAssistant.addMappedStatement(id, sqlSource, statementType, sqlCommandType, fetchSize, timeout, parameterMap, parameterTypeClass, resultMap, resultTypeClass, resultSetTypeEnum, flushCache, useCache, resultOrdered, keyGenerator, keyProperty, keyColumn, databaseId, langDriver, resultSets); } |
這段代碼前面都是解析一些標籤的屬性,咱們看到了最後一行使用builderAssistant添加MappedStatement,其中builderAssistant屬性是構造XMLStatementBuilder的時候經過XMLMappedBuilder傳入的,咱們繼續看builderAssistant的addMappedStatement方法:
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進入setStatementCache:
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private void setStatementCache( boolean isSelect, boolean flushCache, boolean useCache, Cache cache, MappedStatement.Builder statementBuilder) { flushCache = valueOrDefault(flushCache, !isSelect); useCache = valueOrDefault(useCache, isSelect); statementBuilder.flushCacheRequired(flushCache); statementBuilder.useCache(useCache); statementBuilder.cache(cache); } |
最終mapper配置文件中的<cache/>被設置到了XMLMapperBuilder的builderAssistant屬性中,XMLMapperBuilder中使用XMLStatementBuilder遍歷CRUD節點,遍歷CRUD節點的時候將這個cache節點設置到這些CRUD節點中,這個cache就是所謂的二級緩存!
接下來咱們回過頭來看查詢的源碼,CachingExecutor的query方法:
![](http://static.javashuo.com/static/loading.gif)
進入TransactionalCacheManager的putObject方法:
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public void putObject(Cache cache, CacheKey key, Object value) { getTransactionalCache(cache).putObject(key, value); } private TransactionalCache getTransactionalCache(Cache cache) { TransactionalCache txCache = transactionalCaches.get(cache); if (txCache == null ) { txCache = new TransactionalCache(cache); transactionalCaches.put(cache, txCache); } return txCache; } |
TransactionalCache的putObject方法:
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public void putObject(Object key, Object object) { entriesToRemoveOnCommit.remove(key); entriesToAddOnCommit.put(key, new AddEntry(delegate, key, object)); } |
咱們看到,數據被加入到了entriesToAddOnCommit中,這個entriesToAddOnCommit是什麼東西呢,它是TransactionalCache的一個Map屬性:
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private Map<Object, AddEntry> entriesToAddOnCommit; |
AddEntry是TransactionalCache內部的一個類:
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private static class AddEntry { private Cache cache; private Object key; private Object value; public AddEntry(Cache cache, Object key, Object value) { this .cache = cache; this .key = key; this .value = value; } public void commit() { cache.putObject(key, value); } } |
好了,如今咱們發現使用二級緩存以後:查詢數據的話,先從二級緩存中拿數據,若是沒有的話,去一級緩存中拿,一級緩存也沒有的話再查詢數據庫。有了數據以後在丟到TransactionalCache這個對象的entriesToAddOnCommit屬性中。
接下來咱們來驗證爲何SqlSession commit或close以後,二級緩存纔會生效這個問題。
DefaultSqlSession的commit方法:
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public void commit( boolean force) { try { executor.commit(isCommitOrRollbackRequired(force)); dirty = false ; } catch (Exception e) { throw ExceptionFactory.wrapException( "Error committing transaction. Cause: " + e, e); } finally { ErrorContext.instance().reset(); } } |
CachingExecutor的commit方法:
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public void commit( boolean required) throws SQLException { delegate.commit(required); tcm.commit(); dirty = false ; } |
tcm.commit即 TransactionalCacheManager的commit方法:
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public void commit() { for (TransactionalCache txCache : transactionalCaches.values()) { txCache.commit(); } } |
TransactionalCache的commit方法:
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public void commit() { delegate.getReadWriteLock().writeLock().lock(); try { if (clearOnCommit) { delegate.clear(); } else { for (RemoveEntry entry : entriesToRemoveOnCommit.values()) { entry.commit(); } } for (AddEntry entry : entriesToAddOnCommit.values()) { entry.commit(); } reset(); } finally { delegate.getReadWriteLock().writeLock().unlock(); } } |
發現調用了AddEntry的commit方法:
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public void commit() { cache.putObject(key, value); } |
發現了! AddEntry的commit方法會把數據丟到cache中,也就是丟到二級緩存中!
關於爲什麼調用close方法後,二級緩存纔會生效,由於close方法內部會調用commit方法。本文就不具體說了。 讀者有興趣的話看一看源碼就知道爲何了。
其餘
Cache接口簡介
org.apache.ibatis.cache.Cache是MyBatis的緩存接口,想要實現自定義的緩存須要實現這個接口。
MyBatis中關於Cache接口的實現類也使用了裝飾者設計模式。
咱們看下它的一些實現類
![](http://static.javashuo.com/static/loading.gif)
簡單說明:
LRU – 最近最少使用的:移除最長時間不被使用的對象。
FIFO – 先進先出:按對象進入緩存的順序來移除它們。
SOFT – 軟引用:移除基於垃圾回收器狀態和軟引用規則的對象。
WEAK – 弱引用:更積極地移除基於垃圾收集器狀態和弱引用規則的對象。
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< cache eviction = "FIFO" flushInterval = "60000" size = "512" readOnly = "true" /> |
能夠經過cache節點的eviction屬性設置,也能夠設置其餘的屬性。
cache-ref節點
mapper配置文件中還能夠加入cache-ref節點,它有個屬性namespace。
若是每一個mapper文件都是用cache-ref,且namespace都同樣,那麼就表明着真正意義上的全局緩存。
若是隻用了cache節點,那僅表明這個這個mapper內部的查詢被緩存了,其餘mapper文件的不起做用,這並非所謂的全局緩存。
總結
整體來講,MyBatis的源碼看起來仍是比較輕鬆的,本文從實踐和源碼方面深刻分析了MyBatis的緩存原理,但願對讀者有幫助
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