Ngone51 commented on code in PR #36162:
URL: https://github.com/apache/spark/pull/36162#discussion_r895722949
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core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala:
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@@ -1218,6 +1249,71 @@ private[spark] class TaskSetManager(
def executorAdded(): Unit = {
recomputeLocality()
}
+
+ /**
+ * A class for checking inefficient tasks to be speculated, the inefficient
tasks come from
+ * the tasks which may be speculated by the previous strategy.
+ */
+ private[TaskSetManager] class TaskProcessRateCalculator {
+ private var totalRecordsRead = 0L
+ private var totalExecutorRunTime = 0L
+ private var avgTaskProcessRate = 0.0D
+ private val runingTasksProcessRate = new ConcurrentHashMap[Long, Double]()
+
+ private[TaskSetManager] def updateAvgTaskProcessRate(
+ taskId: Long,
+ result: DirectTaskResult[_]): Unit = {
+ var recordsRead = 0L
+ var executorRunTime = 0L
+ result.accumUpdates.foreach { a =>
+ if (a.name == Some(shuffleRead.RECORDS_READ) ||
+ a.name == Some(input.RECORDS_READ)) {
+ val acc = a.asInstanceOf[LongAccumulator]
+ recordsRead += acc.value
+ } else if (a.name == Some(InternalAccumulator.EXECUTOR_RUN_TIME)) {
+ val acc = a.asInstanceOf[LongAccumulator]
+ executorRunTime = acc.value
+ }
+ }
+ totalRecordsRead += recordsRead
+ totalExecutorRunTime += executorRunTime
+ if (totalRecordsRead > 0 && totalExecutorRunTime > 0) {
+ avgTaskProcessRate = totalRecordsRead / (totalExecutorRunTime / 1000.0)
+ }
+ runingTasksProcessRate.remove(taskId)
+ }
+
+ private[scheduler] def updateRuningTaskProcessRate(
+ taskId: Long,
+ taskProcessRate: Double): Unit = {
+ runingTasksProcessRate.put(taskId, taskProcessRate)
+ }
+
+ private[TaskSetManager] def isInefficient(
+ tid: Long,
+ runtimeMs: Long,
+ taskInfo: TaskInfo): Boolean = {
+ // Only check inefficient tasks when avgTaskProcessRate > 0, because
some stage
+ // tasks may have neither input records nor shuffleRead records, so the
+ // avgTaskProcessRate may be zero all the time, this case we should make
sure
+ // it can be speculated. eg: some spark-sql like that 'msck repair
table' or 'drop table'
+ // and so on.
+ if (avgTaskProcessRate <= 0.0) return true
+ val currentTaskProcessRate = runingTasksProcessRate.getOrDefault(tid,
0.0)
+ if (currentTaskProcessRate <= 0.0) {
+ true
+ } else {
+ val taskProcessThreshold = avgTaskProcessRate *
efficientTaskProcessMultiplier
+ val isInefficientTask = currentTaskProcessRate < taskProcessThreshold
+ if (isInefficientTask) {
+ logInfo(s"Marking task ${taskInfo.index} in stage ${taskSet.id} " +
+ s"(on ${taskInfo.host}) as speculatable because it ran
${runtimeMs}ms and " +
Review Comment:
"as speculatable" -> "as inenfficient"?
I think only the caller should decide whether this task should be
specaluted or not.
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