tgravescs 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_r287148845
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File path:
core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
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@@ -335,9 +339,10 @@ private[spark] class TaskSchedulerImpl(
for (i <- 0 until shuffledOffers.size) {
val execId = shuffledOffers(i).executorId
val host = shuffledOffers(i).host
- if (availableCpus(i) >= CPUS_PER_TASK) {
+ if (availableCpus(i) >= CPUS_PER_TASK &&
+ resourceMeetTaskRequirements(availableResources(i))) {
try {
- for (task <- taskSet.resourceOffer(execId, host, maxLocality)) {
+ for (task <- taskSet.resourceOffer(execId, host, maxLocality,
availableResources(i))) {
tasks(i) += task
val tid = task.taskId
taskIdToTaskSetManager.put(tid, taskSet)
Review comment:
I think its a bit out of place that we are decrementing the addresses
available in the resourceOffer function since everything else does its
bookkeeping right here. I don't think that is a blocker for this though and
the way
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