Github user markhamstra commented on a diff in the pull request:
https://github.com/apache/incubator-spark/pull/641#discussion_r10006949
--- Diff: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
---
@@ -272,8 +272,10 @@ class DAGScheduler(
if (mapOutputTracker.has(shuffleDep.shuffleId)) {
val serLocs =
mapOutputTracker.getSerializedMapOutputStatuses(shuffleDep.shuffleId)
val locs = MapOutputTracker.deserializeMapStatuses(serLocs)
- for (i <- 0 until locs.size) stage.outputLocs(i) = List(locs(i))
- stage.numAvailableOutputs = locs.size
+ for (i <- 0 until locs.size) {
+ stage.outputLocs(i) = Option(locs(i)).toList // locs(i) will be
null if missing
--- End diff --
Yup, as long as the underlying data structure is an array of length
numTasks, null is as good as any other "missing output" flag. Changing to a
Map containing only valid locations instead of an array might make sense if the
need to get the output statuses grows beyond the present cases in
MapOutputTracker and DAGScheduler (and if the performance difference is
acceptable), but now that we're handling the nulls properly in those existing
cases, we're good at least for now.
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