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)
```

Also, use can show profile result manually by `sc.show_profiles()` or dump it into disk
by `sc.dump_profiles(path)`, such as

```python
>>> sc._conf.set("spark.python.profile", "true")
>>> rdd = sc.parallelize(range(100)).map(str)
>>> rdd.count()
100
>>> sc.show_profiles()
============================================================
Profile of RDD<id=1>
============================================================
         284 function calls (276 primitive calls) in 0.001 seconds

   Ordered by: internal time, cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        4    0.000    0.000    0.000    0.000 serializers.py:198(load_stream)
        4    0.000    0.000    0.000    0.000 {reduce}
     12/4    0.000    0.000    0.001    0.000 rdd.py:2092(pipeline_func)
        4    0.000    0.000    0.000    0.000 {cPickle.loads}
        4    0.000    0.000    0.000    0.000 {cPickle.dumps}
      104    0.000    0.000    0.000    0.000 rdd.py:852(<genexpr>)
        8    0.000    0.000    0.000    0.000 serializers.py:461(read_int)
       12    0.000    0.000    0.000    0.000 rdd.py:303(func)
```
The profiling is disabled by default, can be enabled by "spark.python.profile=true".

Also, users can dump the results into disks automatically for future analysis, by "spark.python.profile.dump=path_to_dump"

Author: Davies Liu <davies.liu@gmail.com>

Closes #2351 from davies/profiler and squashes the following commits:

7ef2aa0 [Davies Liu] bugfix, add tests for show_profiles and dump_profiles()
2b0daf2 [Davies Liu] fix docs
7a56c24 [Davies Liu] bugfix
cba9463 [Davies Liu] move show_profiles and dump_profiles to SparkContext
fb9565b [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler
116d52a [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler
09d02c3 [Davies Liu] Merge branch 'master' into profiler
c23865c [Davies Liu] Merge branch 'master' into profiler
15d6f18 [Davies Liu] add docs for two configs
dadee1a [Davies Liu] add docs string and clear profiles after show or dump
4f8309d [Davies Liu] address comment, add tests
0a5b6eb [Davies Liu] fix Python UDF
4b20494 [Davies Liu] add profile for python