Github user zsxwing commented on a diff in the pull request: https://github.com/apache/spark/pull/19763#discussion_r151801786 --- Diff: core/src/main/scala/org/apache/spark/MapOutputTracker.scala --- @@ -472,17 +474,36 @@ private[spark] class MapOutputTrackerMaster( shuffleStatuses.get(shuffleId).map(_.findMissingPartitions()) } + /** + * Try to equally divide Range(0, num) to divisor slices + */ + def equallyDivide(num: Int, divisor: Int): Iterator[Seq[Int]] = { + assert(divisor > 0, "Divisor should be positive") + val (each, remain) = (num / divisor, num % divisor) + val (smaller, bigger) = (0 until num).splitAt((divisor-remain) * each) + if (each != 0) { + smaller.grouped(each) ++ bigger.grouped(each + 1) + } else { + bigger.grouped(each + 1) + } + } + /** * Return statistics about all of the outputs for a given shuffle. */ def getStatistics(dep: ShuffleDependency[_, _, _]): MapOutputStatistics = { shuffleStatuses(dep.shuffleId).withMapStatuses { statuses => val totalSizes = new Array[Long](dep.partitioner.numPartitions) - for (s <- statuses) { - for (i <- 0 until totalSizes.length) { - totalSizes(i) += s.getSizeForBlock(i) + val parallelism = conf.getInt("spark.adaptive.map.statistics.cores", 8) + + val mapStatusSubmitTasks = equallyDivide(totalSizes.length, parallelism).map { --- End diff -- Doing this is not cheap. I would add a config and only run this in multiple threads when `#mapper * #shuffle_partitions` is large.
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