While I have a preference for Scala ( not surprising as a Typesafe person), the
DataFrame API gives feature and performance parity for Python. The RDD API
gives feature parity.
So, use what makes you most successful for other reasons ;)
Sent from my rotary phone.
> On Oct 6, 2015, at 4:14 PM, dant wrote:
>
> Hi,
> I'm hearing a common theme running that I should only do serious programming
> in Scala on Spark (1.5.1). Real power users use Scala. It is said that
> Python is great for analytics but in the end the code should be written to
> Scala to finalise. There are a number of reasons I'm hearing:
>
> 1. Spark is written in Scala so will always be faster than any other
> language implementation on top of it.
> 2. Spark releases always favour more features being visible and enabled for
> Scala API than Python API.
>
> Are there any truth's to the above? I'm a little sceptical.
>
> Thanks
> Dan
>
>
>
> --
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> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
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