Deduplicate Local and Cluster schedulers.

The code in LocalScheduler/LocalTaskSetManager was nearly identical
to the code in ClusterScheduler/ClusterTaskSetManager. The redundancy
made making updating the schedulers unnecessarily painful and error-
prone. This commit combines the two into a single TaskScheduler/
TaskSetManager.
Fixed most issues with unit tests
Cleaned up imports and fixed test bug
Extracted TaskScheduler interface.

Also changed the default maximum number of task failures to be
0 when running in local mode.
Fixed naming issues and added back ability to specify max task failures.
Changed local backend to use Akka actor
Fix bug where scheduler could hang after task failure.

When a task fails, we need to call reviveOffers() so that the
task can be rescheduled on a different machine. In the current code,
the state in ClusterTaskSetManager indicating which tasks are
pending may be updated after revive offers is called (there's a
race condition here), so when revive offers is called, the task set
manager does not yet realize that there are failed tasks that need
to be relaunched.
Don't retry tasks if result wasn't serializable
Fixed error message in ClusterScheduler to be consistent with the old LocalScheduler
Added stageId <--> jobId mapping in DAGScheduler
  ...and make sure that DAGScheduler data structures are cleaned up on job completion.
  Initial effort and discussion at https://github.com/mesos/spark/pull/842
Actor instead of eventQueue for LocalJobCompleted
Fixed intended side-effects
private[scheduler] for removeAllRunningTasks
Fixed mis-merge
Improved comment
Removed redundant residual re: reverted refactoring.
Refactoring to make job removal, stage removal, task cancellation clearer
Cleaned up job cancellation handling
Tightly couple stageIdToJobIds and jobIdToStageIds
Avoid losing the race in DAGScedulerSuite "local job"