Github user nishkamravi2 commented on a diff in the pull request:
https://github.com/apache/spark/pull/7274#discussion_r34867770
--- Diff: core/src/main/scala/org/apache/spark/deploy/master/Master.scala
---
@@ -544,58 +544,82 @@ private[master] class Master(
* has enough cores and memory. Otherwise, each executor grabs all the
cores available on the
* worker by default, in which case only one executor may be launched on
each worker.
*/
- private def startExecutorsOnWorkers(): Unit = {
- // Right now this is a very simple FIFO scheduler. We keep trying to
fit in the first app
- // in the queue, then the second app, etc.
+
+ private[master] def scheduleExecutorsOnWorkers(app: ApplicationInfo,
+ usableWorkers: Array[WorkerInfo], spreadOutApps: Boolean): Array[Int]
= {
+ val coresPerExecutor = app.desc.coresPerExecutor.getOrElse(1)
+ val memoryPerExecutor = app.desc.memoryPerExecutorMB
+ val numUsable = usableWorkers.length
+ val assignedCores = new Array[Int](numUsable) // Number of cores to
give to each worker
+ val assignedMemory = new Array[Int](numUsable) // Amount of memory to
give to each worker
+ var toAssign = math.min(app.coresLeft,
usableWorkers.map(_.coresFree).sum)
+ var pos = 0
if (spreadOutApps) {
- // Try to spread out each app among all the workers, until it has
all its cores
- for (app <- waitingApps if app.coresLeft > 0) {
- val usableWorkers = workers.toArray.filter(_.state ==
WorkerState.ALIVE)
- .filter(worker => worker.memoryFree >=
app.desc.memoryPerExecutorMB &&
- worker.coresFree >= app.desc.coresPerExecutor.getOrElse(1))
- .sortBy(_.coresFree).reverse
- val numUsable = usableWorkers.length
- val assigned = new Array[Int](numUsable) // Number of cores to
give on each node
- var toAssign = math.min(app.coresLeft,
usableWorkers.map(_.coresFree).sum)
- var pos = 0
- while (toAssign > 0) {
- if (usableWorkers(pos).coresFree - assigned(pos) > 0) {
- toAssign -= 1
- assigned(pos) += 1
- }
- pos = (pos + 1) % numUsable
- }
- // Now that we've decided how many cores to give on each node,
let's actually give them
- for (pos <- 0 until numUsable if assigned(pos) > 0) {
- allocateWorkerResourceToExecutors(app, assigned(pos),
usableWorkers(pos))
+ // Try to spread out executors among workers (sparse scheduling)
+ while (toAssign > 0) {
+ if (usableWorkers(pos).coresFree - assignedCores(pos) >=
coresPerExecutor &&
+ usableWorkers(pos).memoryFree - assignedMemory(pos) >=
memoryPerExecutor) {
+ toAssign -= coresPerExecutor
+ assignedCores(pos) += coresPerExecutor
+ assignedMemory(pos) += memoryPerExecutor
}
+ pos = (pos + 1) % numUsable
}
} else {
- // Pack each app into as few workers as possible until we've
assigned all its cores
- for (worker <- workers if worker.coresFree > 0 && worker.state ==
WorkerState.ALIVE) {
- for (app <- waitingApps if app.coresLeft > 0) {
- allocateWorkerResourceToExecutors(app, app.coresLeft, worker)
+ // Pack executors into as few workers as possible (dense scheduling)
+ while (toAssign > 0) {
+ while (usableWorkers(pos).coresFree - assignedCores(pos) >=
coresPerExecutor &&
+ usableWorkers(pos).memoryFree - assignedMemory(pos) >=
memoryPerExecutor &&
+ toAssign > 0) {
+ toAssign -= coresPerExecutor
+ assignedCores(pos) += coresPerExecutor
+ assignedMemory(pos) += memoryPerExecutor
}
+ pos = (pos + 1) % numUsable
+ }
+ }
+ assignedCores
+ }
+
+ /**
+ * Schedule and launch executors on workers
+ */
+ private def startExecutorsOnWorkers(): Unit = {
+ // Right now this is a very simple FIFO scheduler. We keep trying to
fit in the first app
+ // in the queue, then the second app, etc.
+ for (app <- waitingApps if app.coresLeft > 0) {
+ val coresPerExecutor = app.desc.coresPerExecutor.getOrElse(1)
+ val usableWorkers = workers.toArray.filter(_.state ==
WorkerState.ALIVE)
+ .filter(worker => worker.memoryFree >=
app.desc.memoryPerExecutorMB &&
+ worker.coresFree >= coresPerExecutor)
+ .sortBy(_.coresFree).reverse
+ val assignedCores = scheduleExecutorsOnWorkers(app, usableWorkers,
spreadOutApps)
+
+ // Now that we've decided how many cores to allocate on each worker,
let's allocate them
+ var pos = 0
+ for (pos <- 0 until usableWorkers.length if assignedCores(pos) > 0) {
+ allocateWorkerResourceToExecutors(app, assignedCores(pos),
coresPerExecutor,
+ usableWorkers(pos))
}
}
}
/**
- * Allocate a worker's resources to one or more executors.
+ * Allocate a worker's resources to one or more executors
* @param app the info of the application which the executors belong to
- * @param coresToAllocate cores on this worker to be allocated to this
application
+ * @param assignedCores number of cores on this worker for this
application
+ * @param coresPerExecutor number of cores per executor
* @param worker the worker info
*/
private def allocateWorkerResourceToExecutors(
app: ApplicationInfo,
- coresToAllocate: Int,
+ assignedCores: Int,
+ coresPerExecutor: Int,
worker: WorkerInfo): Unit = {
- val memoryPerExecutor = app.desc.memoryPerExecutorMB
- val coresPerExecutor =
app.desc.coresPerExecutor.getOrElse(coresToAllocate)
- var coresLeft = coresToAllocate
- while (coresLeft >= coresPerExecutor && worker.memoryFree >=
memoryPerExecutor) {
+
+ var numExecutors = assignedCores/coresPerExecutor
+ for (i <- 1 to numExecutors) {
--- End diff --
Assignment of cores per worker is done by the time this method is invoked.
coresPerExecutor is 1 by default. If we have N workers and N executors with
coresPerExecutor = 1 and we are spreading out, assignedCores = 1 and we would
launch 1 executor per worker with 1 core each, as expected.
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