Github user zhzhan commented on a diff in the pull request:
https://github.com/apache/spark/pull/15218#discussion_r82321008
--- Diff: core/src/main/scala/org/apache/spark/scheduler/TaskAssigner.scala
---
@@ -0,0 +1,151 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.scheduler
+
+import scala.collection.mutable.ArrayBuffer
+import scala.collection.mutable.PriorityQueue
+import scala.util.Random
+
+import org.apache.spark.SparkConf
+
+case class OfferState(workOffer: WorkerOffer, var cores: Int) {
+ // Build a list of tasks to assign to each worker.
+ val tasks = new ArrayBuffer[TaskDescription](cores)
+}
+
+abstract class TaskAssigner(conf: SparkConf) {
+ var offer: Seq[OfferState] = _
+ val CPUS_PER_TASK = conf.getInt("spark.task.cpus", 1)
+
+ // The final assigned offer returned to TaskScheduler.
+ def tasks(): Seq[ArrayBuffer[TaskDescription]] = offer.map(_.tasks)
+
+ // construct the assigner by the workoffer.
+ def construct(workOffer: Seq[WorkerOffer]): Unit = {
+ offer = workOffer.map(o => OfferState(o, o.cores))
+ }
+
+ // Invoked in each round of Taskset assignment to initialize the
internal structure.
+ def init(): Unit
+
+ // Indicating whether there is offer available to be used by one round
of Taskset assignment.
+ def hasNext(): Boolean
+
+ // Next available offer returned to one round of Taskset assignment.
+ def getNext(): OfferState
+
+ // Called by the TaskScheduler to indicate whether the current offer is
accepted
+ // In order to decide whether the current is valid for the next offering.
+ def taskAssigned(assigned: Boolean): Unit
+
+ // Release internally maintained resources. Subclass is responsible to
+ // release its own private resources.
+ def reset: Unit = {
+ offer = null
+ }
+}
+
+class RoundRobinAssigner(conf: SparkConf) extends TaskAssigner(conf) {
+ var i = 0
+ override def construct(workOffer: Seq[WorkerOffer]): Unit = {
+ offer = Random.shuffle(workOffer.map(o => OfferState(o, o.cores)))
+ }
+ override def init(): Unit = {
+ i = 0
+ }
+ override def hasNext: Boolean = {
+ i < offer.size
+ }
+ override def getNext(): OfferState = {
+ offer(i)
+ }
+ override def taskAssigned(assigned: Boolean): Unit = {
+ i += 1
+ }
+ override def reset: Unit = {
+ super.reset
+ i = 0
+ }
+}
+
+class BalancedAssigner(conf: SparkConf) extends TaskAssigner(conf) {
--- End diff --
@mridulm Thanks for the comments. But I am lost here. My understanding is
Ordering-wise, x is equal to y if x.cores == y.cores. This ordering is used by
priority queue to construct the data structure. Following is an example from
trait Ordering. PersonA will be equal to PersionB if they are the same age. Do
I miss anything?
* import scala.util.Sorting
*
* case class Person(name:String, age:Int)
* val people = Array(Person("bob", 30), Person("ann", 32), Person("carl",
19))
*
* // sort by age
* object AgeOrdering extends Ordering[Person] {
* def compare(a:Person, b:Person) = a.age compare b.age
* }
* Sorting.quickSort(people)(AgeOrdering)
* }}}
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