Apache spark spark中每个工作节点运行多少个executor进程？

Spark中每个工作节点将启动多少个执行器？我能知道它背后的数学原理吗

例如，我有6个工作节点和1个主节点，如果我通过spark submit提交作业，将为作业启动多少个最大执行者？

两个可能的答案：

• 如果在调用

  spark submit

  时指定了执行者的数量，则应获得您要求的数量

  --num executors X

• 如果您没有指定，那么默认情况下Spark应该使用动态分配，这将在需要时启动更多执行器。在这种情况下，您可以配置行为，例如执行器的最大数量，请参阅

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每个工作节点的执行者数量将取决于可用资源。

以@LiMuBei的答案为基础

首先，它是你告诉它是什么 如果使用动态分配，那么这就是它为您做出的决定 根据这份文件（）

Spark如何计算通过挂起和运行任务所需的最大执行者数量：

 private def maxNumExecutorsNeeded(): Int = {
    val numRunningOrPendingTasks = listener.totalPendingTasks + listener.totalRunningTasks
    (numRunningOrPendingTasks + tasksPerExecutor - 1) / tasksPerExecutor
 }

 // The target number exceeds the number we actually need, so stop adding new
 // executors and inform the cluster manager to cancel the extra pending requests
 val oldNumExecutorsTarget = numExecutorsTarget
 numExecutorsTarget = math.max(maxNeeded, minNumExecutors)
 numExecutorsToAdd = 1

 // If the new target has not changed, avoid sending a message to the cluster manager
 if (numExecutorsTarget < oldNumExecutorsTarget) {
   client.requestTotalExecutors(numExecutorsTarget, localityAwareTasks, hostToLocalTaskCount)
   logDebug(s"Lowering target number of executors to $numExecutorsTarget (previously " +
     s"$oldNumExecutorsTarget) because not all requested executors are actually needed")
 }
 numExecutorsTarget - oldNumExecutorsTarget

 val oldNumExecutorsTarget = numExecutorsTarget

 // There's no point in wasting time ramping up to the number of executors we already have, so
 // make sure our target is at least as much as our current allocation:
 numExecutorsTarget = math.max(numExecutorsTarget, executorIds.size)

 // Boost our target with the number to add for this round:
 numExecutorsTarget += numExecutorsToAdd

 // Ensure that our target doesn't exceed what we need at the present moment:
 numExecutorsTarget = math.min(numExecutorsTarget, maxNumExecutorsNeeded)

 // Ensure that our target fits within configured bounds:
 numExecutorsTarget = math.max(math.min(numExecutorsTarget, maxNumExecutors), minNumExecutors)
 val delta = numExecutorsTarget - oldNumExecutorsTarget

 // If our target has not changed, do not send a message
 // to the cluster manager and reset our exponential growth
 if (delta == 0) {
   numExecutorsToAdd = 1
   return 0
 }
 val addRequestAcknowledged = testing ||
   client.requestTotalExecutors(numExecutorsTarget, localityAwareTasks, hostToLocalTaskCount)
 if (addRequestAcknowledged) {
   val executorsString = "executor" + { if (delta > 1) "s" else "" }
   logInfo(s"Requesting $delta new $executorsString because tasks are backlogged" +
     s" (new desired total will be $numExecutorsTarget)")
   numExecutorsToAdd = if (delta == numExecutorsToAdd) {
     numExecutorsToAdd * 2
   } else {
     1
   }
   delta
 } else {
   logWarning(
     s"Unable to reach the cluster manager to request $numExecutorsTarget total executors!")
   0
 }

如果当前执行者人数超过预期人数：

 private def maxNumExecutorsNeeded(): Int = {
    val numRunningOrPendingTasks = listener.totalPendingTasks + listener.totalRunningTasks
    (numRunningOrPendingTasks + tasksPerExecutor - 1) / tasksPerExecutor
 }

 // The target number exceeds the number we actually need, so stop adding new
 // executors and inform the cluster manager to cancel the extra pending requests
 val oldNumExecutorsTarget = numExecutorsTarget
 numExecutorsTarget = math.max(maxNeeded, minNumExecutors)
 numExecutorsToAdd = 1

 // If the new target has not changed, avoid sending a message to the cluster manager
 if (numExecutorsTarget < oldNumExecutorsTarget) {
   client.requestTotalExecutors(numExecutorsTarget, localityAwareTasks, hostToLocalTaskCount)
   logDebug(s"Lowering target number of executors to $numExecutorsTarget (previously " +
     s"$oldNumExecutorsTarget) because not all requested executors are actually needed")
 }
 numExecutorsTarget - oldNumExecutorsTarget

 val oldNumExecutorsTarget = numExecutorsTarget

 // There's no point in wasting time ramping up to the number of executors we already have, so
 // make sure our target is at least as much as our current allocation:
 numExecutorsTarget = math.max(numExecutorsTarget, executorIds.size)

 // Boost our target with the number to add for this round:
 numExecutorsTarget += numExecutorsToAdd

 // Ensure that our target doesn't exceed what we need at the present moment:
 numExecutorsTarget = math.min(numExecutorsTarget, maxNumExecutorsNeeded)

 // Ensure that our target fits within configured bounds:
 numExecutorsTarget = math.max(math.min(numExecutorsTarget, maxNumExecutors), minNumExecutors)
 val delta = numExecutorsTarget - oldNumExecutorsTarget

 // If our target has not changed, do not send a message
 // to the cluster manager and reset our exponential growth
 if (delta == 0) {
   numExecutorsToAdd = 1
   return 0
 }
 val addRequestAcknowledged = testing ||
   client.requestTotalExecutors(numExecutorsTarget, localityAwareTasks, hostToLocalTaskCount)
 if (addRequestAcknowledged) {
   val executorsString = "executor" + { if (delta > 1) "s" else "" }
   logInfo(s"Requesting $delta new $executorsString because tasks are backlogged" +
     s" (new desired total will be $numExecutorsTarget)")
   numExecutorsToAdd = if (delta == numExecutorsToAdd) {
     numExecutorsToAdd * 2
   } else {
     1
   }
   delta
 } else {
   logWarning(
     s"Unable to reach the cluster manager to request $numExecutorsTarget total executors!")
   0
 }