这里是Druid的三个核心线程的交互逻辑图 ⚠️这里是init();初始化在这一步：主要核心就是创建这几个线程
createAndLogThread(); //打印日志线程其实就是统计监控信息 createAndStartCreatorThread(); //创建连接的线程 createAndStartDestroyThread(); //销毁连接的线程首先第一大步骤就是先去获取DruidPooledConnection，通过getConnectionInternal（）方法
进入到方法内：
先进行一个for死循环当createDirect = true时跳出循环，首次为false，所以下一步重要的就是创建ScheduledThreadPoolExecutor 对象，条件就是当：【poolingCount（池子中的值为0时） && 活跃的连接 < maxActive && createScheduler != null && createScheduler instanceof ScheduledThreadPoolExecutor】 , 然后ScheduledThreadPoolExecutor中的getQueue().size() > 0 时，把createDirect = true，然后继续往下走，然后通过我们设置的setMaxWait 时间进行判断，如果MaxWait > 0 ,就会从LRU的队列中的尾部取出一个connection使用方法 pollLast(nanos); 否则走takeLast();如果DruidConnectionHolder 不为null ，把【connection】活跃的ActiveCount++，然后跳出循环此时的createDirect = true，所以会去创建一个物理连接 赋值给 DruidConnectionHolder对象 PhysicalConnectionInfo pyConnInfo = DruidDataSource.this.createPhysicalConnection(); holder = new DruidConnectionHolder(this, pyConnInfo); 然后加锁，判断 activeCount < maxActive ，如果为True就把活跃的Connection连接进行➕1，跳出循环，如果 activeCount > maxActive，则需要丢弃创建好的这个创建好的物理连接 JdbcUtils.close(pyConnInfo.getPhysicalConnection());如果成功继续走到下一步
如果失败捕获住错误的话，就继续尝试获取DruidPooledConnection
然后回到getConnectionDirect()方法中，走到第二个步骤中，先判断配置参数testOnBorrow是不是为True，然后去进行对连接进行校验，如果校验成功就继续往下走，
boolean validate = testConnectionInternal(poolableConnection.holder, poolableConnection.conn); if (!validate) { Connection realConnection = poolableConnection.conn; discardConnection(realConnection); continue; }如果配置参数testOnBorrow为True的话会先进行一次上面代码的校验，如果testOnBorrow为False的话，并且 testWhileIdle参数为True的话，会再进行判断，如果【timeBetweenEvictionRunsMillis <= 0】直接使用 60s 进行填充
继续走，如果当前连接的空闲时间【idleMillis >= timeBetweenEvictionRunsMillis || idleMillis < 0】时，会继续进行校验当前连接的健康情况，和上面代码一样，如果校验不成功就会discard当前的Connection
继续，然后判断配置参数removeAbandoned是不是为True，如果是就以当前连接poolableConnection 为Key，PRESENT作为Value放到activeConnections的Map集合中
Map<DruidPooledConnection, Object> activeConnections = new IdentityHashMap<DruidPooledConnection, Object>(); //这里是判断逻辑 if (removeAbandoned) { StackTraceElement[] stackTrace = Thread.currentThread().getStackTrace(); poolableConnection.connectStackTrace = stackTrace; poolableConnection.setConnectedTimeNano(); poolableConnection.traceEnable = true; activeConnectionLock.lock(); try { activeConnections.put(poolableConnection, PRESENT); } finally { activeConnectionLock.unlock(); } } 继续，如果配置的defaultAutoCommit参数是不是为False，如果为False，执行，poolableConnection.setAutoCommit(false);最后 getConnectionDirect(long maxWaitMillis)方法 返回DruidPooledConnection 对象 poolableConnection⚠️这里补充一下第一大步的第2小步中的pollLast(nanos)和takeLast(nanos)方法中如果没有从LRU队列中的尾部获取到Connection时，就会发送图中的notify信号，去通知创建连接的线程去创建连接**
1. 先进入到getConnection方法中
public DruidPooledConnection getConnection(long maxWaitMillis) throws SQLException { init(); if (filters.size() > 0) { FilterChainImpl filterChain = new FilterChainImpl(this); return filterChain.dataSource_connect(this, maxWaitMillis); } else { return getConnectionDirect(maxWaitMillis); } } 然后进入到getConnectionDirect()方法中： public DruidPooledConnection getConnectionDirect(long maxWaitMillis) throws SQLException { int notFullTimeoutRetryCnt = 0; for (;;) { // handle notFullTimeoutRetry DruidPooledConnection poolableConnection; try { //这里的getConnectionInternal方法，其实对应的就是上面分析中的第一大步里面的逻辑 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; } if (testOnBorrow) { boolean validate = testConnectionInternal(poolableConnection.holder, poolableConnection.conn); if (!validate) { if (LOG.isDebugEnabled()) { LOG.debug("skip not validate connection."); } Connection realConnection = poolableConnection.conn; discardConnection(realConnection); continue; } } else { Connection realConnection = poolableConnection.conn; if (poolableConnection.conn.isClosed()) { discardConnection(null); // 传入null，避免重复关闭 continue; } if (testWhileIdle) { final DruidConnectionHolder holder = poolableConnection.holder; long currentTimeMillis = System.currentTimeMillis(); long lastActiveTimeMillis = holder.lastActiveTimeMillis; long lastKeepTimeMillis = holder.lastKeepTimeMillis; if (lastKeepTimeMillis > lastActiveTimeMillis) { lastActiveTimeMillis = lastKeepTimeMillis; } long idleMillis = currentTimeMillis - lastActiveTimeMillis; long timeBetweenEvictionRunsMillis = this.timeBetweenEvictionRunsMillis; if (timeBetweenEvictionRunsMillis <= 0) { timeBetweenEvictionRunsMillis = DEFAULT_TIME_BETWEEN_EVICTION_RUNS_MILLIS; } if (idleMillis >= timeBetweenEvictionRunsMillis || idleMillis < 0 // unexcepted branch ) { boolean validate = testConnectionInternal(poolableConnection.holder, poolableConnection.conn); if (!validate) { if (LOG.isDebugEnabled()) { LOG.debug("skip not validate connection."); } discardConnection(realConnection); continue; } } } } if (removeAbandoned) { StackTraceElement[] stackTrace = Thread.currentThread().getStackTrace(); poolableConnection.connectStackTrace = stackTrace; poolableConnection.setConnectedTimeNano(); poolableConnection.traceEnable = true; activeConnectionLock.lock(); try { activeConnections.put(poolableConnection, PRESENT); } finally { activeConnectionLock.unlock(); } } if (!this.defaultAutoCommit) { poolableConnection.setAutoCommit(false); } return poolableConnection; } }参考文章：http://zhengjianglong.cn/2019/07/14/framework/druid-db-connection/
