[SPARK-3478] [PySpark] Profile the Python tasks

This patch add profiling support for PySpark, it will show the profiling results
before the driver exits, here is one example:

```
============================================================
Profile of RDD<id=3>
============================================================
         5146507 function calls (5146487 primitive calls) in 71.094 seconds

   Ordered by: internal time, cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
  5144576   68.331    0.000   68.331    0.000 statcounter.py:44(merge)
       20    2.735    0.137   71.071    3.554 statcounter.py:33(__init__)
       20    0.017    0.001    0.017    0.001 {cPickle.dumps}
     1024    0.003    0.000    0.003    0.000 t.py:16(<lambda>)
       20    0.001    0.000    0.001    0.000 {reduce}
       21    0.001    0.000    0.001    0.000 {cPickle.loads}
       20    0.001    0.000    0.001    0.000 copy_reg.py:95(_slotnames)
       41    0.001    0.000    0.001    0.000 serializers.py:461(read_int)
       40    0.001    0.000    0.002    0.000 serializers.py:179(_batched)
       62    0.000    0.000    0.000    0.000 {method 'read' of 'file' objects}
       20    0.000    0.000   71.072    3.554 rdd.py:863(<lambda>)
       20    0.000    0.000    0.001    0.000 serializers.py:198(load_stream)
    40/20    0.000    0.000   71.072    3.554 rdd.py:2093(pipeline_func)
       41    0.000    0.000    0.002    0.000 serializers.py:130(load_stream)
       40    0.000    0.000   71.072    1.777 rdd.py:304(func)
       20    0.000    0.000   71.094    3.555 worker.py:82(process)
       40    0.000    0.000    0.001    0.000 rdd.py:741(func)
       20    0.000    0.000    0.018    0.001 serializers.py:137(_write_with_length)
       20    0.000    0.000    0.020    0.001 serializers.py:195(dump_stream)
       20    0.000    0.000    0.000    0.000 serializers.py:201(_load_stream_without_unbatching)
       20    0.000    0.000    0.000    0.000 {hasattr}
       41    0.000    0.000    0.002    0.000 serializers.py:145(_read_with_length)
       40    0.000    0.000    0.000    0.000 {built-in method from_iterable}
       20    0.000    0.000    0.000    0.000 serializers.py:468(write_int)
       20    0.000    0.000    0.018    0.001 serializers.py:355(dumps)
       20    0.000    0.000    0.020    0.001 serializers.py:126(dump_stream)
       20    0.000    0.000    0.000    0.000 {method 'get' of 'dictproxy' objects}
       20    0.000    0.000    0.000    0.000 rdd.py:291(func)
       40    0.000    0.000    0.000    0.000 {method 'write' of 'file' objects}
       20    0.000    0.000    0.000    0.000 {_struct.pack}
       21    0.000    0.000    0.000    0.000 {_struct.unpack}
       20    0.000    0.000    0.000    0.000 {iter}
       20    0.000    0.000    0.000    0.000 {method 'append' of 'list' objects}
       20    0.000    0.000    0.000    0.000 {len}
       20    0.000    0.000    0.000    0.000 {next}
       20    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler' objects}
```

The profiling is disabled by default, can be enabled by "spark.python.profile=true".

Also, users can dump the results into disks for future analysis, by "spark.python.profile.dump=path_to_dump"

PS: will update the docs later.