Github user cloud-fan commented on a diff in the pull request: https://github.com/apache/spark/pull/12899#discussion_r62410420 --- Diff: core/src/main/scala/org/apache/spark/scheduler/Task.scala --- @@ -155,7 +155,13 @@ private[spark] abstract class Task[T]( */ def collectAccumulatorUpdates(taskFailed: Boolean = false): Seq[AccumulatorV2[_, _]] = { if (context != null) { - context.taskMetrics.accumulators().filter { a => !taskFailed || a.countFailedValues } + context.taskMetrics.internalAccums.filter { a => + // RESULT_SIZE accumulator is always zero at executor, we need to send it back as its + // value will be updated at driver side. + !a.isZero || a.name == Some(InternalAccumulator.RESULT_SIZE) + // zero value external accumulators may still be useful, e.g. SQLMetrics, we should not filter --- End diff -- There are 2 concepts: 1. internal accumulators: like GCtime, resultSize, which are internal to DAGScheduler. 2. `countFailedValues` accumulator: `countFailedValues` is an internal flag that can only be set by us. All internal accumulators are `countFailedValues` accumulators, and SQLMetrics are also `countFailedValues` accumulators.
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