Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/7461#discussion_r38596921
--- Diff: core/src/main/scala/org/apache/spark/rdd/RDD.scala ---
@@ -1080,6 +1080,21 @@ abstract class RDD[T: ClassTag](
var partiallyAggregated = mapPartitions(it =>
Iterator(aggregatePartition(it)))
var numPartitions = partiallyAggregated.partitions.length
val scale = math.max(math.ceil(math.pow(numPartitions, 1.0 /
depth)).toInt, 2)
+
+ // Do one level of aggregation based on executorId before starting
the tree
+ // NOTE: exclude the driver from list of executors
+ val numExecutors = math.max(context.getExecutorStorageStatus.length
- 1, 1)
+ partiallyAggregated = partiallyAggregated.mapPartitionsWithIndex {
case (idx, iter) =>
+ def isAllDigits(x: String) = x forall Character.isDigit
+ val execId = SparkEnv.get.executorId
+ if (isAllDigits(execId)) {
+ iter.map((execId.toInt, _))
+ } else {
+ iter.map((execId.hashCode, _))
--- End diff --
I think executor ID is always an integer except maybe during tests, but
given that it's a string everywhere that assumption may not be correct, and we
should certainly not fail when that happens.
Actually why do we need to convert it to an int? As long as they are
distinct then reduceByKey should do the right thing, no?
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