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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