[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).
It's weird that this is so similar to `_spill`. Is there a way to make them the same? If not, can you give them more descriptive names and a comment that explains when each one is called (i.e. that the second one is when we recurse)?