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

    https://github.com/apache/spark/pull/15541#discussion_r84590835
  
    --- Diff: core/src/main/scala/org/apache/spark/scheduler/TaskAssigner.scala 
---
    @@ -0,0 +1,218 @@
    +/*
    + * 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.internal.{config, Logging}
    +import org.apache.spark.SparkConf
    +import org.apache.spark.util.Utils
    +
    +/** Tracks the current state of the workers with available cores and 
assigned task list. */
    +private[scheduler] class OfferState(val workOffer: WorkerOffer) {
    +  /** The current remaining cores that can be allocated to tasks. */
    +  var coresAvailable: Int = workOffer.cores
    +  /** The list of tasks that are assigned to this WorkerOffer. */
    +  val tasks = new ArrayBuffer[TaskDescription](coresAvailable)
    +}
    +
    +/**
    + * TaskAssigner is the base class for all task assigner implementations, 
and can be
    + * extended to implement different task scheduling algorithms.
    + * Together with [[org.apache.spark.scheduler.TaskScheduler 
TaskScheduler]], TaskAssigner
    + * is used to assign tasks to workers with available cores. Internally, 
when TaskScheduler
    + * performs task assignment given available workers, it first sorts the 
candidate tasksets,
    + * and then for each taskset, it takes a number of rounds to request 
TaskAssigner for task
    + * assignment with different locality restrictions until there is either 
no qualified
    + * workers or no valid tasks to be assigned.
    + *
    + * TaskAssigner is responsible to maintain the worker availability state 
and task assignment
    + * information. The contract between 
[[org.apache.spark.scheduler.TaskScheduler TaskScheduler]]
    + * and TaskAssigner is as follows.
    + *
    + * First, TaskScheduler invokes construct() of TaskAssigner to initialize 
the its internal
    + * worker states at the beginning of resource offering.
    + *
    + * Second, before each round of task assignment for a taskset, 
TaskScheduler invokes the init()
    + * of TaskAssigner to initialize the data structure for the round.
    + *
    + * Third, when performing real task assignment, hasNext()/getNext() is 
used by TaskScheduler
    + * to check the worker availability and retrieve current offering from 
TaskAssigner.
    + *
    + * Fourth, then offerAccepted is used by TaskScheduler to notify the 
TaskAssigner so that
    + * TaskAssigner can decide whether the current offer is valid or not for 
the next request.
    + *
    + * Fifth, After task assignment is done, TaskScheduler invokes the tasks() 
to
    + * retrieve all the task assignment information.
    + */
    +
    +private[scheduler] abstract class TaskAssigner {
    +  protected var offer: Seq[OfferState] = _
    +  protected var cpuPerTask = 1
    +
    +  protected def withCpuPerTask(cpuPerTask: Int): Unit = {
    +    this.cpuPerTask = cpuPerTask
    +  }
    +
    +  /** The final assigned offer returned to TaskScheduler. */
    --- End diff --
    
    Here, the implementation of this function does not guarantee the offer 
assignment is final or not. Thus, maybe we can change the description to `The 
currently assigned offers`


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