Overview

Task scheduler is a REEF application similar to the YARN's Distributed shell example. It executes shell commands on a configurable number of machines.
By submitting subsequent commands to retained Evaluators, the scheduler avoids the latency of spawning new containers. The application provides a RESTful API for Evaluator management and Task submission.

How to launch Task Scheduler

Prerequisites

You have compiled REEF locally, and have tried out HelloREEFHttp.

Task Scheduler runs on the local and on the YARN runtime. The commands to launch are similar to the ones in HelloREEF.

Local runtime

> java -cp lang/java/reef-examples/target/reef-examples-{$REEF_VERSION}-shaded.jar org.apache.reef.examples.scheduler.SchedulerREEF

YARN runtime

> yarn jar lang/java/reef-examples/target/reef-examples-{$REEF_VERSION}-shaded.jar org.apache.reef.examples.scheduler.SchedulerREEFYarn

How it works

RESTful

API

Users can send the HTTP request to the server via URL :

http://{address}:{port}/reef-example-scheduler/v1

And the The possible requests are as follows:

• /list: lists all the Tasks’ statuses.
• /clear: clears  clears all the Tasks that are waiting in the queue, and returns the number of removed Tasks that have been removed.
• /submit?cmd=COMMAND: submits a Task to execute COMMAND, and returns the Task id.
• /status?id=ID: returns the status of the Task with the id, “ID”whose id is ID.
• /cancel?id=ID: cancels the Task with the id, “ID”whose id is ID.
• /max-eval?num={num}: sets  limits the maximum number of Evaluators.

The result of each task is written in the log files - both in the driver’s and the evaluators’submitted tasks are executed sequentially. Each task runs on an evaluator, and the maximum number of evaluators is specified by the max-eval request. You can find the result of a task in the evaluator's log.

Reusing the Evaluators

 

When a Task completes, CompletedTaskHandler.onNext() is called, which can be found at SchedulerDriver.java. This is because the handler is bound to ON_TASK_COMPLETED in the driver configuration. (see SchedulerREEF.java)

 You can find the method retainEvaluator() in SchedulerDriver:

final class CompletedTaskHandler implements EventHandler<CompletedTask> {
  @Override
  public void onNext(final CompletedTask task) {
    final int taskId = Integer.valueOf(task.getId());
    synchronized (SchedulerDriver.this) {
      .../**
   * Retain the completefinal evaluatorsActiveContext submittingcontext another task= task.getActiveContext();
      if (retainable) {
        retainEvaluator(context);
      } else {
        reallocateEvaluator(context);
      }
      ...
    }
  } 

In the CompletedTaskHandler, the active Context can be accessed from the `CompletedTask` object, which makes it possible to reuse the Evaluator.

* until there is no need to reuse them.
   */
private synchronized void retainEvaluator(final ActiveContext context) {
  if (scheduler.hasPendingTasks()) {
    scheduler.submitTask(context);
  } else if (nActiveEval > 1) {
    nActiveEval--;
    context.close();
  } else {
    state = State.READY;
    waitForCommands(context);
  }
}

In the `ratainEvaluator()` method, `scheduler.submitTask(context)` makes the Evaluator run another Task if there is a pending Task. Otherwise, the Evaluator is relaesed by closing the active Context, or waits until a new command arrives.

To turn off this feature, add command line argument `-retain false` when you launch the application: Evaluators are released when Tasks end, and a new Evaluator is allocated whenever a Task starts.

 Using the -retain false argument disables this functionality and allocates a new Evaluator for every Task.