[SPARK-2321] Stable pull-based progress / status API

This pull request is a first step towards the implementation of a stable, pull-based progress / status API for Spark (see [SPARK-2321](https://issues.apache.org/jira/browse/SPARK-2321)).  For now, I'd like to discuss the basic implementation, API names, and overall interface design.  Once we arrive at a good design, I'll go back and add additional methods to expose more information via these API.

#### Design goals:

- Pull-based API
- Usable from Java / Scala / Python (eventually, likely with a wrapper)
- Can be extended to expose more information without introducing binary incompatibilities.
- Returns immutable objects.
- Don't leak any implementation details, preserving our freedom to change the implementation.

#### Implementation:

- Add public methods (`getJobInfo`, `getStageInfo`) to SparkContext to allow status / progress information to be retrieved.
- Add public interfaces (`SparkJobInfo`, `SparkStageInfo`) for our API return values.  These interfaces consist entirely of Java-style getter methods.  The interfaces are currently implemented in Java.  I decided to explicitly separate the interface from its implementation (`SparkJobInfoImpl`, `SparkStageInfoImpl`) in order to prevent users from constructing these responses themselves.
-Allow an existing JobProgressListener to be used when constructing a live SparkUI.  This allows us to re-use this listeners in the implementation of this status API.  There are a few reasons why this listener re-use makes sense:
   - The status API and web UI are guaranteed to show consistent information.
   - These listeners are already well-tested.
   - The same garbage-collection / information retention configurations can apply to both this API and the web UI.
- Extend JobProgressListener to maintain `jobId -> Job` and `stageId -> Stage` mappings.

The progress API methods are implemented in a separate trait that's mixed into SparkContext.  This helps to avoid SparkContext.scala from becoming larger and more difficult to read.
If you want to look at code:
https://github.com/vanzin/spark/blob/yarn-timeline/yarn/timeline/src/main/scala/org/apache/spark/deploy/yarn/timeline/YarnTimelineProvider.scala#L107

Short story: ReplayListenerBus is very tightly coupled with EventLoggingListener and the idea that events come from a file in a specific format. So unless you're reading a file created by EventLoggingListener, it's not very useful at the moment.

But my main point is that the Spark UI code does not depend on that instance being a ReplayListenerBus, so I don't see the point in making the API enforce that.