我知道对于spark，我们可以将不同的池设置为Fair或FIFO，并且行为可以不同。然而，在fairscheduler.xml中，我们也可以将单个池设置为Fair或FIFO，我测试了几次，因为它们的行为似乎是相同的。然后我看了一下spark源代码，schedulingAlgorithm是这样的：

/**
 * An interface for sort algorithm
 * FIFO: FIFO algorithm between TaskSetManagers
 * FS: FS algorithm between Pools, and FIFO or FS within Pools
 */
private[spark] trait SchedulingAlgorithm {
  def comparator(s1: Schedulable, s2: Schedulable): Boolean
}

private[spark] class FIFOSchedulingAlgorithm extends SchedulingAlgorithm{
  override def comparator(s1: Schedulable, s2: Schedulable): Boolean = {
    val priority1 = s1.priority
    val priority2 = s2.priority
    var res = math.signum(priority1 - priority2)
    if (res == 0) {
      val stageId1 = s1.stageId
      val stageId2 = s2.stageId
      res = math.signum(stageId1 - stageId2)
    }
    res < 0
  }
}

private[spark] class FairSchedulingAlgorithm extends SchedulingAlgorithm{
  override def comparator(s1: Schedulable, s2: Schedulable): Boolean = {
    val minShare1 = s1.minShare
    val minShare2 = s2.minShare
    val runningTasks1 = s1.runningTasks
    val runningTasks2 = s2.runningTasks
    val s1Needy = runningTasks1 < minShare1
    val s2Needy = runningTasks2 < minShare2
    val minShareRatio1 = runningTasks1.toDouble / math.max(minShare1, 1.0)
    val minShareRatio2 = runningTasks2.toDouble / math.max(minShare2, 1.0)
    val taskToWeightRatio1 = runningTasks1.toDouble / s1.weight.toDouble
    val taskToWeightRatio2 = runningTasks2.toDouble / s2.weight.toDouble

    var compare = 0
    if (s1Needy && !s2Needy) {
      return true
    } else if (!s1Needy && s2Needy) {
      return false
    } else if (s1Needy && s2Needy) {
      compare = minShareRatio1.compareTo(minShareRatio2)
    } else {
      compare = taskToWeightRatio1.compareTo(taskToWeightRatio2)
    }
    if (compare < 0) {
      true
    } else if (compare > 0) {
      false
    } else {
      s1.name < s2.name
    }
  }
}

字符串
在fairSchedulingAlgorithm中，如果s1和s2来自同一个池，则minshare、runningtask和weight应该是相同的值，这样我们总是可以得到返回值为false。所以他们不是公平的，而是先进先出。我的fairscheduler.xml是这样的：

<allocations>
  <pool name="default">
    <schedulingMode>FAIR</schedulingMode>
    <weight>3</weight>
    <minShare>2</minShare>
  </pool>
  <pool name="cubepublishing">
      <schedulingMode>FAIR</schedulingMode>
      <weight>1</weight>
      <minShare>0</minShare>
  </pool>
</allocations>

型
而spark.scheduler.mode是：

# job scheduler
spark.scheduler.mode              FAIR
spark.scheduler.allocation.file   conf/fairscheduler.xml

型
谢谢你的帮助！