squito 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_r275601242
##########
File path:
core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala
##########
@@ -55,13 +58,32 @@ private[spark] class CoarseGrainedExecutorBackend(
// to be changed so that we don't share the serializer instance across
threads
private[this] val ser: SerializerInstance =
env.closureSerializer.newInstance()
+ private[this] val taskResources = new HashMap[Long, Map[String,
ResourceInformation]]
+
override def onStart() {
logInfo("Connecting to driver: " + driverUrl)
rpcEnv.asyncSetupEndpointRefByURI(driverUrl).flatMap { ref =>
// This is a very fast action so we can use "ThreadUtils.sameThread"
driver = Some(ref)
+
+ val resourceInfo = if (env.conf.get(GPUS_PER_TASK) > 0) {
+ val gpuResources = gpuDevices.map(ids => {
Review comment:
nit: `map { ids => `
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