脚本宝典收集整理的这篇文章主要介绍了通过Druid连接池获取Connection，脚本宝典觉得挺不错的，现在分享给大家，也给大家做个参考。
从DataSource.getConnection入手来看一下通过druid获取连接时的内部逻辑。
首先进入DruidDataSource的这个方法
public DruidPooledConnection getConnection(long maxWaitMillis) throws SQLException { //初始化连接 数量为设置的InITilSize,如果没有配置则为0，MaxActive最大为8 init(); // 如果有FilterChain,走FilterChain的逻辑 if (filters.size() > 0) { FilterChainImpl filterChain = new FilterChainImpl(this); return filterChain.dataSource_connect(this, maxWaitMillis); } else { //真正的获取连接的方法 return getConnectionDirect(maxWaitMillis); } }
正常情况下通过getConnectionDirect来直接获取连接，里面传了一个最大等待时间，稍后我们分析这个参数的作用。
先看上部分逻辑：
int notFullTimeoutRetryCnt = 0; for (;;) { // handle notFullTimeoutRetry DruidPooledConnection poolableConnection; try { poolableConnection = getConnectionInternal(maxWaitMillis); } catch (GetConnectionTimeoutException ex) { if (notFullTimeoutRetryCnt <= this.notFullTimeoutRetryCount && !isFull()) { notFullTimeoutRetryCnt++; if (LOG.isWarnEnabled()) { LOG.warn("get connection timeout retry : " + notFullTimeoutRetryCnt); } continue; } throw ex; }
这一部分很好理解，一个for循环里面通过getConnectionInternal(maxWaitMillis)方法来获取一个真实的物理连接，
如果捕捉到获取连接超时的异常，去判断notFullTimeoutRetryCnt 这个参数是否小于设定的超时重试参数，并且
在连接池未满的情况下继续进行重试。如果重试次数已经足够或者此时连接池已经满了(其它线程获取到连接)则
将异常抛出去。isFull方法用来判断存在池子内的连接和活跃连接(已经被线程brrow走了)的数量是否大于等于最大
连接数MaxActiveCount。
进入getConnectionInternal内部：
PRivate DruidPooledConnection getConnectionInternal(long maxWait) throws SQLException { //如果当前连接池已经关闭 则抛出异常 if (closed) { connectErrorCountUpdater.incrementAndGet(this); throw new DataSourceClosedException("dataSource already closed at " + new Date(closeTimeMillis)); } //如果当期连接池状态为不可用 则抛出异常 if (!enable) { connectErrorCountUpdater.incrementAndGet(this); if (disableException != null) { throw disableException; } throw new DataSourceDisableException(); } final long nanos = TimeUnit.MILLISECONDS.toNanos(maxWait); final int maxWaitThreadCount = this.maxWaitThreadCount; DruIDConnectionHolder holder; for (boolean createDirect = false;;) { if (createDirect) { createstartNanosUpdater.set(this, System.nanoTime()); if (creatingCountUpdater.COMpareAndSet(this, 0, 1)) { PhysicalConnectionInfo pyConnInfo = DruidDataSource.this.createPhysicalConnection(); holder = new DruidConnectionHolder(this, pyConnInfo); holder.lastActiveTimeMillis = System.currentTimeMillis(); creatingCountUpdater.decrementAndGet(this); directCreateCountUpdater.incrementAndGet(this); if (LOG.isDebugEnabled()) { LOG.debug("conn-direct_create "); } boolean discard = false; lock.lock(); try { if (activeCount < maxActive) { activeCount++; holder.active = true; if (activeCount > activePEak) { activePeak = activeCount; activePeakTime = System.currentTimeMillis(); } break; } else { discard = true; } } finally { lock.unlock(); } if (discard) { JdbcUtils.close(pyConnInfo.getPhysicalConnection()); } } } try { lock.lockInterruptibly(); } catch (InterruptedException e) { connectErrorCountUpdater.incrementAndGet(this); throw new SQLException("interrupt", e); } try { if (maxWaitThreadCount > 0 && notEmptyWaitThreadCount >= maxWaitThreadCount) { connectErrorCountUpdater.incrementAndGet(this); throw new SQLException("maxWaitThreadCount " + maxWaitThreadCount + ", current wait Thread count " + lock.getQueueLength()); } if (onFatalError && onFatalErrorMaxActive > 0 && activeCount >= onFatalErrorMaxActive) { connectErrorCountUpdater.incrementAndGet(this); StringBuilder errorMsg = new StringBuilder(); errorMsg.append("onFatalError, activeCount ") .append(activeCount) .append(", onFatalErrorMaxActive ") .append(onFatalErrorMaxActive); if (lastFatalErrorTimeMillis > 0) { errorMsg.append(", time '") .append(StringUtils.formatDateTime19( lastFatalErrorTimeMillis, TimeZone.getDefault())) .append("'"); } if (lastFatalErrorSql != null) { errorMsg.append(", sql n") .append(lastFatalErrorSql); } throw new SQLException( errorMsg.toString(), lastFatalError); } connectCount++; if (createScheduler != null && poolingCount == 0 && activeCount < maxActive && creatingCountUpdater.get(this) == 0 && createScheduler instanceof ScheduledThreadPoolExecutor) { ScheduledThreadPoolExecutor executor = (ScheduledThreadPoolExecutor) createScheduler; if (executor.getQueue().size() > 0) { createDirect = true; continue; } } if (maxWait > 0) { holder = pollLast(nanos); } else { holder = takeLast(); } if (holder != null) { if (holder.discard) { continue; } activeCount++; holder.active = true; if (activeCount > activePeak) { activePeak = activeCount; activePeakTime = System.currentTimeMillis(); } } } catch (InterruptedException e) { connectErrorCountUpdater.incrementAndGet(this); throw new SQLException(e.getMessage(), e); } catch (SQLException e) { connectErrorCountUpdater.incrementAndGet(this); throw e; } finally { lock.unlock(); } break; } if (holder == null) { long waitNanos = waitNanosLocal.get(); StringBuilder buf = new StringBuilder(128); buf.append("wait millis ")// .append(waitNanos / (1000 * 1000))// .append(", active ").append(activeCount)// .append(", maxActive ").append(maxActive)// .append(", creating ").append(creatingCount)// ; if (creatingCount > 0 && createStartNanos > 0) { long createElapSEMillis = (System.nanoTime() - createStartNanos) / (1000 * 1000); if (createElapseMillis > 0) { buf.append(", createElapseMillis ").append(createElapseMillis); } } if (createErrorCount > 0) { buf.append(", createErrorCount ").append(createErrorCount); } List<JdbcSqlstatValue> sqlList = this.getDataSourceStat().getRuningSqlList(); for (int i = 0; i < sqlList.size(); ++i) { if (i != 0) { buf.append('n'); } else { buf.append(", "); } JdbcSqlStatValue sql = sqlList.get(i); buf.append("runningSqlCount ").append(sql.getRunningCount()); buf.append(" : "); buf.append(sql.getSql()); } String errorMessage = buf.toString(); if (this.createError != null) { throw new GetConnectionTimeoutException(errorMessage, createError); } else { throw new GetConnectionTimeoutException(errorMessage); } } holder.incrementUseCount(); DruidPooledConnection poolalbeConnection = new DruidPooledConnection(holder); return poolalbeConnection;
以上是脚本宝典为你收集整理的通过Druid连接池获取Connection全部内容，希望文章能够帮你解决通过Druid连接池获取Connection所遇到的问题。
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