SPARK-2387: remove stage barrier

This PR is a PoC implementation of [SPARK-2387](https://issues.apache.org/jira/browse/SPARK-2387).

When a ShuffleMapTask finishes, DAGScheduler will check resource usage. And if there’re free slots, DAGScheduler chooses a stage from the waiting list whose parent stages have all started, and pre-starts this waiting stage. All the in-progress parent stages will then register the map outputs progressively with MapOutputTrackerMaster. A flag is added to MapOutputTracker to indicate whether the map statuses for a shuffle is partial or not, so that we can distinguish partial registration from failed shuffle map stage.
When the downstream task tries to fetch shuffle blocks, it will get an array of map outputs that has “holes” (unfinished map tasks) in it. We created PartialBlockFetcherIterator to handle this map output array. PartialBlockFetcherIterator keeps an array of conventional iterators (BasicBlockFetcherIterator or NettyBlockFetcherIterator). When some new map outputs become available, PartialBlockFetcherIterator will delegate these outputs to a new conventional iterator and relies on these conventional iterators for “hasNext” and “next” methods. When all the delegated map statuses run out, PartialBlockFetcherIterator contacts local MapOutputTrackerWorker for updated map outputs. MapOutputTrackerWorker uses an "updater" thread to communicate with MapOutputTrackerMaster to update the map statuses and informs the downstream tasks to continue when the map statuses get updated.

This PoC feature is mainly intended and tested against standalone cluster. I used a 7-node cluster for performance test. Each node runs an executor with 32 CPUs and 90GB memory. I used graphx.SynthBenchmark for the test and the testcase used is:
graphx.SynthBenchmark -partStrategy=EdgePartition2D -numEPart=112 -nverts=10000000 -niter=3
The feature improves the whole job by roughly 10% (reduces the creation time from 128s to 116s and run time from 126s to 115s).