[SPARK-2538] [PySpark] Hash based disk spilling aggregation

During aggregation in Python worker, if the memory usage is above spark.executor.memory, it will do disk spilling aggregation. 

It will split the aggregation into multiple stage, in each stage, it will partition the aggregated data by hash and dump them into disks. After all the data are aggregated, it will merge all the stages together (partition by partition).
This only implements external merging in the reduce tasks, but we need it in the map tasks too. For that you'll need to modify the Merger interface to take `createCombiner`, `mergeValue` and `mergeCombiners` together. Please add those there and add tests for the richer interface.