Apache Spark Mesos Resource Manager

// Standard Spark imports for Mesos integration
import org.apache.spark.{SparkConf, SparkContext}

// Configuration constants (if needed for advanced configuration)
import org.apache.spark.deploy.mesos.config._

import org.apache.spark.{SparkConf, SparkContext}

// Configure Spark to use Mesos with coarse-grained mode
val conf = new SparkConf()
  .setAppName("MySparkApp")
  .setMaster("mesos://mesos-master:5050")      // Mesos master URL
  .set("spark.mesos.coarse", "true")           // Enable coarse-grained mode (default)
  .set("spark.mesos.executor.home", "/opt/spark") // Required: Spark installation path
  .set("spark.executor.memory", "2g")
  .set("spark.executor.cores", "2")
  .set("spark.mesos.executor.memoryOverhead", "512m") // Additional memory overhead

// Optional: Configure constraints and Docker
// .set("spark.mesos.constraints", "os:linux")
// .set("spark.mesos.executor.docker.image", "spark:latest")

// Create SparkContext - automatically uses MesosClusterManager
val sc = new SparkContext(conf)

// Your Spark application code
val data = sc.parallelize(1 to 1000)
val result = data.map(_ * 2).collect()

sc.stop()

val conf = new SparkConf()
  .setAppName("MySparkApp")
  .setMaster("mesos://mesos-master:5050")
  .set("spark.mesos.coarse", "false")           // Enable fine-grained mode
  .set("spark.mesos.executor.home", "/opt/spark")
  .set("spark.mesos.mesosExecutor.cores", "1.0") // Cores for executor backend

val sc = new SparkContext(conf)
// Application code...
sc.stop()

private[spark] class MesosClusterManager extends ExternalClusterManager {
  def canCreate(masterURL: String): Boolean
  def createTaskScheduler(sc: SparkContext, masterURL: String): TaskScheduler
  def createSchedulerBackend(
    sc: SparkContext, 
    masterURL: String, 
    scheduler: TaskScheduler
  ): SchedulerBackend
  def initialize(scheduler: TaskScheduler, backend: SchedulerBackend): Unit
}

private[spark] class MesosCoarseGrainedSchedulerBackend(
  scheduler: TaskSchedulerImpl,
  sc: SparkContext,
  master: String,
  securityManager: SecurityManager
) extends CoarseGrainedSchedulerBackend with org.apache.mesos.Scheduler {
  def start(): Unit
  def stop(): Unit
  def applicationId(): String
  def sufficientResourcesRegistered(): Boolean
  def doRequestTotalExecutors(requestedTotal: Int): Future[Boolean]
  def doKillExecutors(executorIds: Seq[String]): Future[Boolean]
}

private[spark] class MesosFineGrainedSchedulerBackend(
  scheduler: TaskSchedulerImpl,
  sc: SparkContext,
  master: String
) extends SchedulerBackend with org.apache.mesos.Scheduler {
  def start(): Unit
  def stop(): Unit
  def reviveOffers(): Unit
  def killTask(taskId: Long, executorId: String, interruptThread: Boolean, reason: String): Unit
  def defaultParallelism(): Int
  def applicationId(): String
}

private[spark] class MesosClusterScheduler(
  engineFactory: MesosClusterPersistenceEngineFactory,
  conf: SparkConf
) extends Scheduler with MesosSchedulerUtils {
  def submitDriver(desc: MesosDriverDescription): CreateSubmissionResponse
  def killDriver(submissionId: String): KillSubmissionResponse
  def getDriverStatus(submissionId: String): SubmissionStatusResponse
  def start(): Unit
  def stop(): Unit
}

private[mesos] class MesosClusterDispatcher(
  args: MesosClusterDispatcherArguments,
  conf: SparkConf
) {
  def start(): Unit
  def stop(): Unit
  def awaitShutdown(): Unit
}

trait MesosSchedulerUtils {
  def createSchedulerDriver(
    masterUrl: String,
    scheduler: Scheduler,
    sparkUser: String,
    appName: String,
    conf: SparkConf,
    webuiUrl: Option[String] = None,
    checkpoint: Option[Boolean] = None,
    failoverTimeout: Option[Double] = None,
    frameworkId: Option[String] = None
  ): SchedulerDriver
  
  def getResource(res: JList[Resource], name: String): Double
  def partitionResources(
    resources: JList[Resource],
    resourceName: String,
    amountToUse: Double
  ): (List[Resource], List[Resource])
  def matchesAttributeRequirements(
    slaveOfferConstraints: Map[String, Set[String]],
    offerAttributes: Map[String, GeneratedMessage]
  ): Boolean
}

private[mesos] class MesosExternalShuffleService extends ExternalShuffleService {
  def start(): Unit
  def stop(): Unit
}

private[mesos] class MesosExternalShuffleBlockHandler(
  transportConf: TransportConf,
  cleanerIntervalS: Long
) extends ExternalShuffleBlockHandler with Logging {
  def registerApplication(appShuffleInfo: ApplicationShuffleInfo): Unit
  def applicationRemoved(appId: String, cleanupLocalDirs: Boolean): Unit
}

## Types

```scala { .api }
// Required imports for types
import java.util.Date
import org.apache.spark.deploy.Command
import org.apache.mesos.Protos.{TaskID, SlaveID, TaskStatus}
import org.apache.spark.scheduler.cluster.mesos.MesosClusterRetryState
import org.apache.spark.internal.config.ConfigEntry

// Driver submission and state (internal classes)
private[spark] class MesosDriverDescription(
  name: String,
  jarUrl: String,
  mem: Int,
  cores: Double,
  supervise: Boolean,
  command: Command,
  schedulerProperties: Map[String, String],
  submissionId: String,
  submissionDate: Date,
  retryState: Option[MesosClusterRetryState] = None
)

private[spark] class MesosClusterSubmissionState(
  val driverDescription: MesosDriverDescription,
  val taskId: TaskID,
  val slaveId: SlaveID,
  var mesosTaskStatus: Option[TaskStatus],
  var startDate: Date,
  var finishDate: Option[Date],
  val frameworkId: String
) extends Serializable

// Configuration objects
package object config {
  val RECOVERY_MODE: ConfigEntry[String]
  val DISPATCHER_WEBUI_URL: ConfigEntry[Option[String]]
  val ZOOKEEPER_URL: ConfigEntry[Option[String]]
  val HISTORY_SERVER_URL: ConfigEntry[Option[String]]
  val DRIVER_CONSTRAINTS: ConfigEntry[String]
}