In Spark 2.0.0, a new pluggable cluster manager interface, ExternalClusterManager was introduced.  See the Jira ticket below

https://issues.apache.org/jira/browse/SPARK-13904

This allows us to introduce new cluster managers other than Yarn, Mesos, and Spark standalone by implementing the ExternalClusterManager trait. These are the required methods in the trait. createTaskScheduler method is to create a task scheduler and createSchedulerBackend method is to create a scheduler backend.

def canCreate(masterURL: String): Boolean
def createTaskScheduler(sc: SparkContext, masterURL: String): TaskScheduler<span 				data-mce-type="bookmark" 				id="mce_SELREST_start" 				data-mce-style="overflow:hidden;line-height:0" 				style="overflow:hidden;line-height:0" 			></span>
def createSchedulerBackend(sc: SparkContext,
      masterURL: String,
      scheduler: TaskScheduler): SchedulerBackend
def initialize(scheduler: TaskScheduler, backend: SchedulerBackend): Unit<span 				data-mce-type="bookmark" 				id="mce_SELREST_start" 				data-mce-style="overflow:hidden;line-height:0" 				style="overflow:hidden;line-height:0" 			></span>

ClusterManager is used in SparkContext to create scheduler backend and task scheduler.

Currently, there are two existing implementations of ExternalClusterManager. YarnClusterManager is the implementation for Yarn. As you can see in the codes, it returns YarnClusterScheduler when deploy mode is cluster. For client deploy mode, it returns YarnScheduler. For scheduler backend, it creates YarnClusterSchedulerBackend and YarnClientSchdulerBackend for cluster deploy mode and client deploy mode respectively.

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 * 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
 *
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package org.apache.spark.scheduler.cluster

import org.apache.spark.{SparkContext, SparkException}
import org.apache.spark.scheduler.{ExternalClusterManager, SchedulerBackend, TaskScheduler, TaskSchedulerImpl}

/**
 * Cluster Manager for creation of Yarn scheduler and backend
 */
private[spark] class YarnClusterManager extends ExternalClusterManager {

  override def canCreate(masterURL: String): Boolean = {
    masterURL == "yarn"
  }

  override def createTaskScheduler(sc: SparkContext, masterURL: String): TaskScheduler = {
    sc.deployMode match {
      case "cluster" => new YarnClusterScheduler(sc)
      case "client" => new YarnScheduler(sc)
      case _ => throw new SparkException(s"Unknown deploy mode '${sc.deployMode}' for Yarn")
    }
  }

  override def createSchedulerBackend(sc: SparkContext,
      masterURL: String,
      scheduler: TaskScheduler): SchedulerBackend = {
    sc.deployMode match {
      case "cluster" =>
        new YarnClusterSchedulerBackend(scheduler.asInstanceOf[TaskSchedulerImpl], sc)
      case "client" =>
        new YarnClientSchedulerBackend(scheduler.asInstanceOf[TaskSchedulerImpl], sc)
      case  _ =>
        throw new SparkException(s"Unknown deploy mode '${sc.deployMode}' for Yarn")
    }
  }

  override def initialize(scheduler: TaskScheduler, backend: SchedulerBackend): Unit = {
    scheduler.asInstanceOf[TaskSchedulerImpl].initialize(backend)
  }
}

MesosClusterManager is the implementation for Mesos.

/*
 * 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.cluster.mesos

import org.apache.spark.{SparkContext, SparkException}
import org.apache.spark.internal.config._
import org.apache.spark.scheduler.{ExternalClusterManager, SchedulerBackend, TaskScheduler, TaskSchedulerImpl}

/**
 * Cluster Manager for creation of Mesos scheduler and backend
 */
private[spark] class MesosClusterManager extends ExternalClusterManager {
  private val MESOS_REGEX = """mesos://(.*)""".r

  override def canCreate(masterURL: String): Boolean = {
    masterURL.startsWith("mesos")
  }

  override def createTaskScheduler(sc: SparkContext, masterURL: String): TaskScheduler = {
    new TaskSchedulerImpl(sc)
  }

  override def createSchedulerBackend(sc: SparkContext,
      masterURL: String,
      scheduler: TaskScheduler): SchedulerBackend = {
    require(!sc.conf.get(IO_ENCRYPTION_ENABLED),
      "I/O encryption is currently not supported in Mesos.")

    val mesosUrl = MESOS_REGEX.findFirstMatchIn(masterURL).get.group(1)
    val coarse = sc.conf.getBoolean("spark.mesos.coarse", defaultValue = true)
    if (coarse) {
      new MesosCoarseGrainedSchedulerBackend(
        scheduler.asInstanceOf[TaskSchedulerImpl],
        sc,
        mesosUrl,
        sc.env.securityManager)
    } else {
      new MesosFineGrainedSchedulerBackend(
        scheduler.asInstanceOf[TaskSchedulerImpl],
        sc,
        mesosUrl)
    }
  }

  override def initialize(scheduler: TaskScheduler, backend: SchedulerBackend): Unit = {
    scheduler.asInstanceOf[TaskSchedulerImpl].initialize(backend)
  }
}

java.util.ServiceLoader mechanism is used to register and auto load any new external cluster manager implementation.