[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).
Unfortunately memory_info only works in psutil 2.0. I tried the Anaconda Python distribution on Mac, which has psutil 1.2.1, and it doesn't work there. In there you have to use get_memory_info() instead.