srowen commented on a change in pull request #24374: [SPARK-27366][CORE]
Support GPU Resources in Spark job scheduling
URL: https://github.com/apache/spark/pull/24374#discussion_r275375783
##########
File path:
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
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@@ -209,7 +217,11 @@ class CoarseGrainedSchedulerBackend(scheduler:
TaskSchedulerImpl, val rpcEnv: Rp
totalCoreCount.addAndGet(cores)
totalRegisteredExecutors.addAndGet(1)
val data = new ExecutorData(executorRef, executorAddress, hostname,
- cores, cores, logUrlHandler.applyPattern(logUrls, attributes),
attributes)
+ cores, cores, logUrlHandler.applyPattern(logUrls, attributes),
attributes, resources,
+ mutable.Map.empty[String, SchedulerResourceInformation] ++=
resources.mapValues(v =>
Review comment:
This might be clearer if broken out into a new `val`. Does it need to be
mutable and if it does, create it directly rather than make an empty one and
append
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