Github user felixcheung commented on the issue:
https://github.com/apache/spark/pull/16708
@rxin this was as suggested by @cloud-fan in more details in this thread
[here](https://github.com/apache/spark/pull/16668#discussion_r97254989)
The original concerns were around the overhead with the extra conversion
needed in Python and R (to PythonRDD, RRDD) and that it would be much lighter
weight to have a method in Scala for this.
Now that we have a simple workaround in R (by just calling the Scala method
without conversion), I'm not feeling strongly about this so I'm ok to close
this.
I do agree with the optimizer behavior but this has been a very frequently
requested method and its uses as `x.rdd.getNumPartitions` is all over PySpark
code and documentation.
Perhaps it is worthwhile to explain this is a number to expect but can be
optimized out.
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