When faced with this issue I followed the approach taken by pyspark and used 
py4j. You have to:
- ensure your code is Java compatible
- use py4j to call the java (scala) code from python


> On Apr 18, 2016, at 10:29 AM, Holden Karau <hol...@pigscanfly.ca> wrote:
> 
> So if there is just a few python functions your interested in accessing you 
> can also use the pipe interface (you'll have to manually serialize your data 
> on both ends in ways that Python and Scala can respectively parse) - but its 
> a very generic approach and can work with many different languages.
> 
> On Mon, Apr 18, 2016 at 10:23 AM, Ndjido Ardo BAR <ndj...@gmail.com 
> <mailto:ndj...@gmail.com>> wrote:
> Hi Didier,
> 
> I think with PySpark you can wrap your legacy Python functions into UDFs and 
> use it in your DataFrames. But you have to use DataFrames instead of RDD. 
> 
> cheers,
> Ardo
> 
> On Mon, Apr 18, 2016 at 7:13 PM, didmar <marin.did...@gmail.com 
> <mailto:marin.did...@gmail.com>> wrote:
> Hi,
> 
> I have a Spark project in Scala and I would like to call some Python
> functions from within the program.
> Both parts are quite big, so re-coding everything in one language is not
> really an option.
> 
> The workflow would be:
> - Creating a RDD with Scala code
> - Mapping a Python function over this RDD
> - Using the result directly in Scala
> 
> I've read about PySpark internals, but that didn't help much.
> Is it possible to do so, and preferably in an efficent manner ?
> 
> Cheers,
> Didier
> 
> 
> 
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