[SPARK-3491] [MLlib] [PySpark] use pickle to serialize data in MLlib

Currently, we serialize the data between JVM and Python case by case manually, this cannot scale to support so many APIs in MLlib.

This patch will try to address this problem by serialize the data using pickle protocol, using Pyrolite library to serialize/deserialize in JVM. Pickle protocol can be easily extended to support customized class.

All the modules are refactored to use this protocol.

This patch depends on #2365 to support serialze array.array in Python2.6 (included it for testing)
Just wondering: Is it inefficient to have to convert types by calling toArray()?  Does that mean multiple passes over (or copies of) the data?