[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).
Probably just want to allow "true" to be similar to the way it works in Java and Scala. So just check `self.ctx._conf.get("spark.shuffle.spill", "true") == "true"`