Github user rxin commented on a diff in the pull request:

    https://github.com/apache/spark/pull/15218#discussion_r83545544
  
    --- Diff: core/src/main/scala/org/apache/spark/scheduler/TaskAssigner.scala 
---
    @@ -0,0 +1,154 @@
    +/*
    + * 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) {
    +  var maxHeap: PriorityQueue[OfferState] = _
    +  var current: OfferState = _
    +
    +  override def construct(workOffer: Seq[WorkerOffer]): Unit = {
    +    offer = Random.shuffle(workOffer.map(o => OfferState(o, o.cores)))
    +  }
    +  implicit val ord: Ordering[OfferState] = new Ordering[OfferState] {
    +    def compare(x: OfferState, y: OfferState): Int = {
    +      return Ordering[Int].compare(x.cores, y.cores)
    +    }
    +  }
    +  def init(): Unit = {
    +    maxHeap = new PriorityQueue[OfferState]()
    +    offer.filter(_.cores >= CPUS_PER_TASK).foreach(maxHeap.enqueue(_))
    +  }
    +  override def hasNext: Boolean = {
    +    maxHeap.size > 0
    +  }
    +  override def getNext(): OfferState = {
    +    current = maxHeap.dequeue()
    +    current
    +  }
    +
    +  override def taskAssigned(assigned: Boolean): Unit = {
    +    if (current.cores >= CPUS_PER_TASK && assigned) {
    +      maxHeap.enqueue(current)
    +    }
    +  }
    +  override def reset: Unit = {
    +    super.reset
    +    maxHeap = null
    +    current = null
    +  }
    +}
    +
    +class PackedAssigner(conf: SparkConf) extends TaskAssigner(conf) {
    +
    +  var sorted: Seq[OfferState] = _
    --- End diff --
    
    all these variables should be private


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