val spreadOutApps = conf.getBoolean("spark.deploy.spreadOut", true)

  /**
   * Can an app use the given worker? True if the worker has enough memory and we haven't already
   * launched an executor for the app on it (right now the standalone backend doesn't like having
   * two executors on the same worker).
   */
  def canUse(app: ApplicationInfo, worker: WorkerInfo): Boolean = {
    worker.memoryFree >= app.desc.memoryPerSlave && !worker.hasExecutor(app)
  }

SpreadOut分配策略：

// Right now this is a very simple FIFO scheduler. We keep trying to fit in the first app
    // in the queue, then the second app, etc.
    if (spreadOutApps) {
      // Try to spread out each app among all the nodes, until it has all its cores
      for (app <- waitingApps if app.coresLeft > 0) { //对还未被完全分配资源的apps处理
        val usableWorkers = workers.toArray.filter(_.state == WorkerState.ALIVE)
          .filter(canUse(app, _)).sortBy(_.coresFree).reverse //根据core Free对可用Worker进行降序排序。
        val numUsable = usableWorkers.length //可用worker的个数 eg:可用5个worker
        val assigned = new Array[Int](numUsable) //候选Worker，每个Worker一个下标，是一个数组，初始化默认都是0
        var toAssign = math.min(app.coresLeft, usableWorkers.map(_.coresFree).sum)//还要分配的cores = 集群中可用Worker的可用cores总和（10）， 当前未分配core（5）中找最小的
        var pos = 0
        while (toAssign > 0) { 
          if (usableWorkers(pos).coresFree - assigned(pos) > 0) { //以round robin方式在所有可用Worker里判断当前worker空闲cpu是否大于当前数组已经分配core值
            toAssign -= 1
            assigned(pos) += 1 //当前下标pos的Worker分配1个core +1
          }
          pos = (pos + 1) % numUsable //round-robin轮询寻找有资源的Worker
        }
        // Now that we've decided how many cores to give on each node, let's actually give them
        for (pos <- 0 until numUsable) {
          if (assigned(pos) > 0) { //如果assigned数组中的值>0，将启动一个executor在，指定下标的机器上。
            val exec = app.addExecutor(usableWorkers(pos), assigned(pos)) //更新app里的Executor信息
            launchExecutor(usableWorkers(pos), exec)  //通知可用Worker去启动Executor
            app.state = ApplicationState.RUNNING
          }
        }
      }
    } else {

非SpreadOut分配策略：

 } else {
      // Pack each app into as few nodes as possible until we've assigned all its cores
      for (worker <- workers if worker.coresFree > 0 && worker.state == WorkerState.ALIVE) {
        for (app <- waitingApps if app.coresLeft > 0) {
          if (canUse(app, worker)) { //直接问当前worker是有空闲的core
            val coresToUse = math.min(worker.coresFree, app.coresLeft) //有则取，不管多少
            if (coresToUse > 0) { //有
              val exec = app.addExecutor(worker, coresToUse) //直接启动
              launchExecutor(worker, exec)
              app.state = ApplicationState.RUNNING
            }
          }
        }
      }
    }
  }