Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/6607#discussion_r31858980
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala
---
@@ -308,12 +305,41 @@ class ReceiverTracker(ssc: StreamingContext,
skipReceiverLaunch: Boolean = false
supervisor.start()
supervisor.awaitTermination()
}
+
// Run the dummy Spark job to ensure that all slaves have registered.
// This avoids all the receivers to be scheduled on the same node.
if (!ssc.sparkContext.isLocal) {
ssc.sparkContext.makeRDD(1 to 50, 50).map(x => (x,
1)).reduceByKey(_ + _, 20).collect()
}
+ // Right now, we only honor preferences if all receivers have them
+ val hasLocationPreferences =
receivers.map(_.preferredLocation.isDefined).reduce(_ && _)
+
+ // If no location preferences are specified, set host location for
each receiver
+ // so as to distribute them evenly over executors in a round-robin
fashion
+ var roundRobin = false;
+ if (!hasLocationPreferences && !ssc.sparkContext.isLocal) {
+ val executors = getExecutors(ssc)
+ if (!executors.isEmpty) {
+ var i = 0;
+ for (i <- 0 to (receivers.length - 1)) {
+ receivers(i).host = Some(executors(i % executors.length))
+ }
+ roundRobin = true
+ }
+ }
+
+ val tempRDD =
+ if (hasLocationPreferences) {
--- End diff --
Well, we want to make as little assumption as possible. Users may want to
mix Flume receivers (which may have preferred locations) with Kafka Receivers
(without any preferred location). So when we are fixing things, its best to fix
it in the right way.
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