[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).
BTW I'd prefer to enforce the limit right now, the problem is that in environments like YARN your job just gets killed if it goes past it. It's better to have a low setting and ask users to increase it.