Github user holdenk commented on a diff in the pull request: https://github.com/apache/spark/pull/11105#discussion_r56426605 --- Diff: core/src/main/scala/org/apache/spark/Accumulable.scala --- @@ -146,6 +212,32 @@ class Accumulable[R, T] private ( def merge(term: R) { value_ = param.addInPlace(value_, term)} /** + * Merge in pending updates for ac consistent accumulators or merge accumulated values for + * regular accumulators. This is only called on the driver when merging task results together. + */ + private[spark] def internalMerge(term: Any) { + if (!consistent) { + merge(term.asInstanceOf[R]) + } else { + mergePending(term.asInstanceOf[mutable.HashMap[(Int, Int, Int), R]]) + } + } + + /** + * Merge another Accumulable's pending updates, checks to make sure that each pending update has + * not already been processed before updating. + */ + private[spark] def mergePending(term: mutable.HashMap[(Int, Int, Int), R]) = { + term.foreach{case ((rddId, shuffleId, splitId), v) => + val splits = processed.getOrElseUpdate((rddId, shuffleId), new mutable.BitSet()) + if (!splits.contains(splitId)) { + splits += splitId + value_ = param.addInPlace(value_, v) + } --- End diff -- Sure we could do that - I'd kept the separate processed since I thought the space efficiency of a bitset might be worth it as well as it seemed like it might be more confusing to have one val with two different meanings between driver & worker.
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