标签：springmvc+mybatis dubbo+zookeeper restful redis分布式缓存 kafka bootstrap html5
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。MyBatis 避免了几乎所有的 JDBC 代码和手工设置参数以及抽取结果集。MyBatis 使用简单的 XML 或注解来配置和映射基本体，将接口和 Java 的 POJOs(Plain Old Java Objects,普通的 Java对象)映射成数据库中的记录。
虽然在使用MyBatis时一般都会使用XML文件，但是本文为了分析程序的简单性，简单的测试程序将不包含XML配置，该测试程序包含一个接口、一个启动类：
public interface UserMapper {
@Select("SELECT * FROM user WHERE id = #{id}") User selectUser(int id);
}public class Test2 { public static void main(String[] args) {
SqlSessionFactory sqlSessionFactory = initSqlSessionFactory();
SqlSession session = sqlSessionFactory.openSession(); try {
User user = (User) session.selectOne( "org.mybatis.example.UserMapper.selectUser", 1);
System.out.println(user.getUserAddress());
System.out.println(user.getUserName());
} finally {
session.close();
}
} private static SqlSessionFactory initSqlSessionFactory() {
DataSource dataSource = new PooledDataSource("com.mysql.jdbc.Driver", "jdbc:mysql://127.0.0.1:3306/jdbc", "root", "");
TransactionFactory transactionFactory = new JdbcTransactionFactory();
Environment environment = new Environment("development",
transactionFactory, dataSource);
Configuration configuration = new Configuration(environment);
configuration.addMapper(UserMapper.class);
SqlSessionFactory sqlSessionFactory = new SqlSessionFactoryBuilder()
.build(configuration); return sqlSessionFactory;
}
}UserMapper是一个接口，我们在构建sqlSessionFactory时通过configuration.addMapper(UserMapper.class)把该接口注册进了sqlSessionFactory中。从上面的代码中我们可以看出，要使用MyBatis，我们应该经过以下步骤：1、创建sqlSessionFactory（一次性操作）；2、用sqlSessionFactory对象构造sqlSession对象；3、调用sqlSession的相应方法；4、关闭sqlSession对象。
在main方法中，我们没有配置sql，也没有根据查询结果拼接对象，只需在调用sqlSession方法时传入一个命名空间以及方法参数参数即可，所有的操作都是面向对象的。在UserMapper接口中，我们定制了自己的sql，MyBatis把书写sql的权利给予了我们，方便我们进行sql优化及sql排错。
直接使用JDBC是很痛苦的，JDBC连接数据库包含以下几个基本步骤：1、注册驱动 ；2、建立连接(Connection)；3、创建SQL语句(Statement)；4、执行语句；5、处理执行结果(ResultSet)；6、释放资源，示例代码如下：
test() SQLException{
.forName();
Connection conn = DriverManager.getConnection(, , );
Statement st = conn.createStatement();
ResultSet rs = st.executeQuery();
(rs.()) {
User user = User(rs.getObject(), rs.getObject());
}
rs.close();
st.close();
conn.close();
}可以看到与直接使用JDBC相比，MyBatis为我们简化了很多工作：
1、把创建连接相关工作抽象成一个sqlSessionFactory对象，一次创建多次使用；
2、把sql语句从业务层剥离，代码逻辑更加清晰，增加可维护性；
3、自动完成结果集处理，不需要我们编写重复代码。
但是，我们应该知道的是，框架虽然能够帮助我们简化工作，但是框架底层的代码肯定还是最基础的JDBC代码，因为这是Java平台连接数据库的通用方法，今天我将分析一下MyBatis源码，看看MyBatis是如何把这些基础代码封装成一个框架的。
我们最终调用的是sqlSession对象上的方法，所以我们先跟踪sqlSession的创建方法：sqlSessionFactory.openSession()，最终这个方法会调用到DefaultSqlSessionFactory的以下方法：
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();
}
}最终返回的对象是一个DefaultSqlSession对象，在调试模式下， 我们看到autoCommit为false，executor为CachingExecutor类型，在CachingExecutor里面有属性delegate，其类型为simpleExecutor：
现在，我们跟进DefaultSqlSession的selectOne()方法，查看该方法的调用流程，selectOne()方法又会调用selectList()方法：
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();
}
}可以看到要得到查询结果，最终还是要调用executor上的query方法，这里的executor是CachingExecutor实例，跟进程序得到如下代码：
public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler) throws SQLException {
BoundSql boundSql = ms.getBoundSql(parameterObject);
CacheKey key = createCacheKey(ms, parameterObject, rowBounds, boundSql); return 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) {
flushCacheIfRequired(ms); if (ms.isUseCache() && resultHandler == null) {
ensureNoOutParams(ms, parameterObject, boundSql);
@SuppressWarnings("unchecked") List<E> list = (List<E>) tcm.getObject(cache, key); if (list == null) { 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);
}MyBatis框架首先生成了一个boundSql和CacheKey，在boundSql中包含有我们传入的sql语句：
生成boundSql和CacheKey后会调用一个重载函数，在重载函数中，我们会检测是否有缓存，这个缓存是MyBatis的二级缓存，我们没有配置，那么直接调用最后一句delegate.<E> query(ms, parameterObject, rowBounds, resultHandler, key, boundSql)，前面说过这个delagate其实就是simpleExecutor，跟进去查看一下：
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++; list = resultHandler == null ? (List<E>) localCache.getObject(key) : null; if (list != null) {
handleLocallyCachedOutputParameters(ms, key, parameter, boundSql);
} else { list = queryFromDatabase(ms, parameter, rowBounds, resultHandler, key, boundSql);
}
} finally {
queryStack--;
} if (queryStack == 0) { for (DeferredLoad deferredLoad : deferredLoads) {
deferredLoad.load();
}
deferredLoads.clear(); // issue #601
if (configuration.getLocalCacheScope() == LocalCacheScope.STATEMENT) {
clearLocalCache(); // issue #482
}
} return list;
}关键代码是以下三行：
list = resultHandler == null ? (List<E>) localCache.getObject(key) : null; if (list != null) {
handleLocallyCachedOutputParameters(ms, key, parameter, boundSql);
} else { list = queryFromDatabase(ms, parameter, rowBounds, resultHandler, key, boundSql);
}首先尝试从localCache中根据key得到List，这里的localCache是MyBatis的一级缓存，如果得不到则调用queryFromDatabase()从数据库中查询：
private <E> List<E> queryFromDatabase(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException { List<E> list;
localCache.putObject(key, EXECUTION_PLACEHOLDER); try { list = doQuery(ms, parameter, rowBounds, resultHandler, boundSql);
} finally {
localCache.removeObject(key);
}
localCache.putObject(key, list); if (ms.getStatementType() == StatementType.CALLABLE) {
localOutputParameterCache.putObject(key, parameter);
} return list;
}其中关键代码是调用doQuery()代码，SimpleExecutor的doQuery()方法如下：
public <E> List<E> doQuery(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, BoundSql boundSql) throws SQLException {
Statement stmt = null; try {
Configuration configuration = ms.getConfiguration();
StatementHandler handler = configuration.newStatementHandler(wrapper, ms, parameter, rowBounds, resultHandler, boundSql);
stmt = prepareStatement(handler, ms.getStatementLog()); return handler.<E>query(stmt, resultHandler);
} finally {
closeStatement(stmt);
}
}调用了prepareStatement方法，该方法如下：
private Statement prepareStatement(StatementHandler handler, Log statementLog) throws SQLException {
Statement stmt;
Connection connection = getConnection(statementLog);
stmt = handler.prepare(connection);
handler.parameterize(stmt); return stmt;
}终于，我们看到熟悉的代码了，首先得到Connection，然后从Connection中得到Statement，同时在调试模式下我们看到，我们的sql语句已经被设置到stmt中了：
现在Statement对象有了，sql也设置进去了，就只差执行以及对象映射了，继续跟进代码，我们会跟踪到org.apache.ibatis.executor.statement.
PreparedStatementHandler类的executor方法：
public <E> List<E> query(Statement statement, ResultHandler resultHandler) throws SQLException {
PreparedStatement ps = (PreparedStatement) statement;
ps.execute(); return resultSetHandler.<E> handleResultSets(ps);
}在这里，调用了ps.execute()方法执行sql，接下来调用的resultSetHandler.<E> handleResultSets(ps)方法明显是对结果集进行封装，我就不继续跟进了。
上面一部分介绍了MyBatis执行的整体流程，这一部分打算讨论一个具体话题：MyBatis的数据库连接池。
我们知道，每次连接数据库时都创建Connection是十分耗费性能的，所以我们在写JDBC代码时，一般都会使用数据库连接池，把用过的Connection不是直接关闭，而是放入数据库连接池中，方便下次复用，开源的数据库连接池有DBCP、C3P0等，MyBatis也实现了自己的数据库连接池，在这一节我将探索一下MyBatis实现的数据库连接池源码。
跟进上一节的getConnection()方法，我们最终会进入JdbcTransaction的getConnection()方法，getConnection()方法又会调用openConnection()方法，而openConnection()又将调用dataSource的getConnection()方法：
public Connection getConnection() throws SQLException { if (connection == null) {
openConnection();
} return connection;
}protected void openConnection() throws SQLException { if (log.isDebugEnabled()) {
log.debug("Opening JDBC Connection");
}
connection = dataSource.getConnection(); if (level != null) {
connection.setTransactionIsolation(level.getLevel());
}
setDesiredAutoCommit(autoCommmit);
}这里的dataSource是PooledDataSource类型，跟进查看源码如下：
public Connection getConnection() throws SQLException { return popConnection(dataSource.getUsername(), dataSource.getPassword()).getProxyConnection();
} private PooledConnection popConnection(String username, String password) throws SQLException { //暂不分析
}可以看到，在这里我们返回的对象其实已经不是原生的Connection对象了，而是一个动态代理对象，是PooledConnection的一个属性，所有对对Connection对象的操作都将被PooledConnection拦截，我们可以查看PooledConnection的定义如下：
class PooledConnection implements InvocationHandler { private static final String CLOSE = "close"; private static final Class<?>[] IFACES = new Class<?>[] { Connection.class }; private int hashCode = 0; private PooledDataSource dataSource; private Connection realConnection; private Connection proxyConnection; private long checkoutTimestamp; private long createdTimestamp; private long lastUsedTimestamp; private int connectionTypeCode; private boolean valid; public PooledConnection(Connection connection, PooledDataSource dataSource) { this.hashCode = connection.hashCode(); this.realConnection = connection; this.dataSource = dataSource; this.createdTimestamp = System.currentTimeMillis(); this.lastUsedTimestamp = System.currentTimeMillis(); this.valid = true; this.proxyConnection = (Connection) Proxy.newProxyInstance(
Connection.class.getClassLoader(), IFACES, this);
} public void invalidate() {
valid = false;
} public boolean isValid() { return valid && realConnection != null
&& dataSource.pingConnection(this);
} public Connection getRealConnection() { return realConnection;
} public Connection getProxyConnection() { return proxyConnection;
} public int getRealHashCode() { if (realConnection == null) { return 0;
} else { return realConnection.hashCode();
}
} public int getConnectionTypeCode() { return connectionTypeCode;
} public void setConnectionTypeCode(int connectionTypeCode) { this.connectionTypeCode = connectionTypeCode;
} public long getCreatedTimestamp() { return createdTimestamp;
} public void setCreatedTimestamp(long createdTimestamp) { this.createdTimestamp = createdTimestamp;
} public long getLastUsedTimestamp() { return lastUsedTimestamp;
} public void setLastUsedTimestamp(long lastUsedTimestamp) { this.lastUsedTimestamp = lastUsedTimestamp;
} public long getTimeElapsedSinceLastUse() { return System.currentTimeMillis() - lastUsedTimestamp;
} public long getAge() { return System.currentTimeMillis() - createdTimestamp;
} public long getCheckoutTimestamp() { return checkoutTimestamp;
} public void setCheckoutTimestamp(long timestamp) { this.checkoutTimestamp = timestamp;
} public long getCheckoutTime() { return System.currentTimeMillis() - checkoutTimestamp;
} public int hashCode() { return hashCode;
} public boolean equals(Object obj) { if (obj instanceof PooledConnection) { return realConnection.hashCode() == (((PooledConnection) obj).realConnection
.hashCode());
} else if (obj instanceof Connection) { return hashCode == obj.hashCode();
} else { return false;
}
} public Object invoke(Object proxy, Method method, Object[] args)
throws Throwable {
String methodName = method.getName(); if (CLOSE.hashCode() == methodName.hashCode()
&& CLOSE.equals(methodName)) {
dataSource.pushConnection(this); return null;
} else { try { if (!Object.class.equals(method.getDeclaringClass())) {
checkConnection();
} return method.invoke(realConnection, args);
} catch (Throwable t) { throw ExceptionUtil.unwrapThrowable(t);
}
}
} private void checkConnection() throws SQLException { if (!valid) { throw new SQLException( "Error accessing PooledConnection. Connection is invalid.");
}
}
}可以看到这个类暴露了很多接口检测Connection状态，例如连接是否有效，连接创建时间最近使用连接等：
这个类实现了InvocationHandler接口，最主要的一个方法如下：
public Object invoke(Object proxy, Method method, Object[] args) throws Throwable { String methodName = method.getName(); if (CLOSE.hashCode() == methodName.hashCode() && CLOSE.equals(methodName)) {
dataSource.pushConnection(this); return null;
} else { try { if (!Object.class.equals(method.getDeclaringClass())) {
checkConnection();
} return method.invoke(realConnection, args);
} catch (Throwable t) { throw ExceptionUtil.unwrapThrowable(t);
}
}
}可以看到，PooledConnection会拦截close方法，当客户端调用close()方法时，程序不会关闭Connection，而是会调用dataSource.pushConnection(this)方法，该方法的实现如下：
protected void pushConnection(PooledConnection conn) throws SQLException {
synchronized (state) {
state.activeConnections.remove(conn); if (conn.isValid()) { if (state.idleConnections.size() < poolMaximumIdleConnections && conn.getConnectionTypeCode() == expectedConnectionTypeCode) {
state.accumulatedCheckoutTime += conn.getCheckoutTime(); if (!conn.getRealConnection().getAutoCommit()) {
conn.getRealConnection().rollback();
}
PooledConnection newConn = new PooledConnection(conn.getRealConnection(), this);
state.idleConnections.add(newConn);
newConn.setCreatedTimestamp(conn.getCreatedTimestamp());
newConn.setLastUsedTimestamp(conn.getLastUsedTimestamp());
conn.invalidate(); if (log.isDebugEnabled()) { log.debug("Returned connection " + newConn.getRealHashCode() + " to pool.");
}
state.notifyAll();
} else {
state.accumulatedCheckoutTime += conn.getCheckoutTime(); if (!conn.getRealConnection().getAutoCommit()) {
conn.getRealConnection().rollback();
}
conn.getRealConnection().close(); if (log.isDebugEnabled()) { log.debug("Closed connection " + conn.getRealHashCode() + ".");
}
conn.invalidate();
}
} else { if (log.isDebugEnabled()) { log.debug("A bad connection (" + conn.getRealHashCode() + ") attempted to return to the pool, discarding connection.");
}
state.badConnectionCount++;
}
}
}可以看到，首先会把Connection从活跃列表中删除，然后检测空闲列表的长度有没有达到最大长度（默认为5），若没有达到，把Connection放入空闲链表，否则关闭连接。这里的state是一个PoolState对象，该对象定义如下：
public class PoolState { protected PooledDataSource dataSource; protected final List<PooledConnection> idleConnections = new ArrayList<PooledConnection>(); protected final List<PooledConnection> activeConnections = new ArrayList<PooledConnection>(); protected long requestCount = 0; protected long accumulatedRequestTime = 0; protected long accumulatedCheckoutTime = 0; protected long claimedOverdueConnectionCount = 0; protected long accumulatedCheckoutTimeOfOverdueConnections = 0; protected long accumulatedWaitTime = 0; protected long hadToWaitCount = 0; protected long badConnectionCount = 0; public PoolState(PooledDataSource dataSource) { this.dataSource = dataSource;
} public synchronized long getRequestCount() { return requestCount;
} public synchronized long getAverageRequestTime() { return requestCount == 0 ? 0 : accumulatedRequestTime / requestCount;
} public synchronized long getAverageWaitTime() { return hadToWaitCount == 0 ? 0 : accumulatedWaitTime / hadToWaitCount;
} public synchronized long getHadToWaitCount() { return hadToWaitCount;
} public synchronized long getBadConnectionCount() { return badConnectionCount;
} public synchronized long getClaimedOverdueConnectionCount() { return claimedOverdueConnectionCount;
} public synchronized long getAverageOverdueCheckoutTime() { return claimedOverdueConnectionCount == 0 ? 0 : accumulatedCheckoutTimeOfOverdueConnections / claimedOverdueConnectionCount;
} public synchronized long getAverageCheckoutTime() { return requestCount == 0 ? 0 : accumulatedCheckoutTime / requestCount;
} public synchronized int getIdleConnectionCount() { return idleConnections.size();
} public synchronized int getActiveConnectionCount() { return activeConnections.size();
}
}可以看到最终我们的Connection对象是放在ArrayList中的，该类还提供一些接口返回连接池基本信息。
好了，现在我们可以回去看看PooledDataSource的popConnection方法了：
private PooledConnection popConnection(String username, String password) throws SQLException {
boolean countedWait = false;
PooledConnection conn = null; long t = System.currentTimeMillis(); int localBadConnectionCount = 0; while (conn == null) {
synchronized (state) { if (state.idleConnections.size() > 0) { // Pool has available connection
conn = state.idleConnections.remove(0); if (log.isDebugEnabled()) { log.debug("Checked out connection " + conn.getRealHashCode() + " from pool.");
}
} else { // Pool does not have available connection
if (state.activeConnections.size() < poolMaximumActiveConnections) { // Can create new connection
conn = new PooledConnection(dataSource.getConnection(), this);
@SuppressWarnings("unused") //used in logging, if enabled
Connection realConn = conn.getRealConnection(); if (log.isDebugEnabled()) { log.debug("Created connection " + conn.getRealHashCode() + ".");
}
} else { // Cannot create new connection
PooledConnection oldestActiveConnection = state.activeConnections.get(0); long longestCheckoutTime = oldestActiveConnection.getCheckoutTime(); if (longestCheckoutTime > poolMaximumCheckoutTime) { // Can claim overdue connection
state.claimedOverdueConnectionCount++;
state.accumulatedCheckoutTimeOfOverdueConnections += longestCheckoutTime;
state.accumulatedCheckoutTime += longestCheckoutTime;
state.activeConnections.remove(oldestActiveConnection); if (!oldestActiveConnection.getRealConnection().getAutoCommit()) {
oldestActiveConnection.getRealConnection().rollback();
}
conn = new PooledConnection(oldestActiveConnection.getRealConnection(), this);
oldestActiveConnection.invalidate(); if (log.isDebugEnabled()) { log.debug("Claimed overdue connection " + conn.getRealHashCode() + ".");
}
} else { // Must wait
try { if (!countedWait) {
state.hadToWaitCount++;
countedWait = true;
} if (log.isDebugEnabled()) { log.debug("Waiting as long as " + poolTimeToWait + " milliseconds for connection.");
} long wt = System.currentTimeMillis();
state.wait(poolTimeToWait);
state.accumulatedWaitTime += System.currentTimeMillis() - wt;
} catch (InterruptedException e) { break;
}
}
}
} if (conn != null) { if (conn.isValid()) { if (!conn.getRealConnection().getAutoCommit()) {
conn.getRealConnection().rollback();
}
conn.setConnectionTypeCode(assembleConnectionTypeCode(dataSource.getUrl(), username, password));
conn.setCheckoutTimestamp(System.currentTimeMillis());
conn.setLastUsedTimestamp(System.currentTimeMillis());
state.activeConnections.add(conn);
state.requestCount++;
state.accumulatedRequestTime += System.currentTimeMillis() - t;
} else { if (log.isDebugEnabled()) { log.debug("A bad connection (" + conn.getRealHashCode() + ") was returned from the pool, getting another connection.");
}
state.badConnectionCount++;
localBadConnectionCount++;
conn = null; if (localBadConnectionCount > (poolMaximumIdleConnections + 3)) { if (log.isDebugEnabled()) { log.debug("PooledDataSource: Could not get a good connection to the database.");
} throw new SQLException("PooledDataSource: Could not get a good connection to the database.");
}
}
}
}
} if (conn == null) { if (log.isDebugEnabled()) { log.debug("PooledDataSource: Unknown severe error condition. The connection pool returned a null connection.");
} throw new SQLException("PooledDataSource: Unknown severe error condition. The connection pool returned a null connection.");
} return conn;
}可以看到获取Connection一共分以下几种情况：1、如果有空闲Connection，那么直接使用空闲Connection，否则2；2、如果活跃Connection没有达到活跃Connection的上限，那么创建一个新Connection并返回，否则3；3、如果达到活跃上限，且被检出的Connection检出时间过长，那么把该Connection置为失效，新创建一个Connection，否则4；4、等待空闲Connection。
至此，我们就把MyBatis的数据库连接池代码整理了一遍，其中有两个关键点：1、检出的Connection其实不是原生Connection，而是一个代理对象；2、存放Connection的容器是ArrayList，Connection的检出遵从先进先出原则。
这篇博客讲的很好，可以mark一下：minglisoft.cn/technology
首先回顾一下JDBC的事务知识。
JDBC可以操作Connection的setAutoCommit()方法，给它false参数，提示数据库启动事务，在下达一连串的SQL命令后，自行调用Connection的commit()方法，提示数据库确认(Commit)操作。如果中间发生错误，则调用rollback()，提示数据库撤销(ROLLBACK)所有执行。同时，如果仅想要撤回某个SQL执行点，则可以设置存储点(SAVEPOINT)。一个示范的事务流程如下：
Connection conn = ...;Savepoint point = null;try {
conn.setAutoCommit(false); Statement stmt = conn.createStatement();
stmt.executeUpdate("INSERT INTO ...");
...
point = conn.setSavepoint();
stmt.executeUpdate("INSERT INTO ...");
...
conn.commit();
} catch (SQLException e) {
e.printStackTrace(); if (conn != null) { try { if (point == null) {
conn.rollback();
} else {
conn.rollback(point);
conn.releaseSavepoint(point);
}
} catch (SQLException ex) {
ex.printStackTrace();
}
}
} finally {
... if (conn != null) { try {
conn.setAutoCommit(true);
conn.close();
} catch (SQLException ex) {
ex.printStackTrace();
}
}
}在MyBatis调用流程一节就写过，在调试模式下， 我们看到autoCommit为false， 所以每个sqlSession其实都是一个事务，这也是为什么每次做删、改、查时都必须调用commit的原因.
源码来源：minglisoft.cn/technology
标签：springmvc+mybatis dubbo+zookeeper restful redis分布式缓存 kafka bootstrap html5
原文地址：http://12819045.blog.51cto.com/12809045/1915294
