Not currently in Spark. However, there are systems out there that can share DataFrame between languages on top of Spark - it’s not calling the python UDF directly but you can pass the DataFrame to python and then .map(UDF) that way.
________________________________ From: Fiske, Danny <danny.fi...@ext.ons.gov.uk> Sent: Monday, July 15, 2019 6:58:32 AM To: user@spark.apache.org Subject: [PySpark] [SparkR] Is it possible to invoke a PySpark function with a SparkR DataFrame? Hi all, Forgive this naïveté, I’m looking for reassurance from some experts! In the past we created a tailored Spark library for our organisation, implementing Spark functions in Scala with Python and R “wrappers” on top, but the focus on Scala has alienated our analysts/statisticians/data scientists and collaboration is important for us (yeah… we’re aware that your SDKs are very similar across languages… :/ ). We’d like to see if we could forego the Scala facet in order to present the source code in a language more familiar to users and internal contributors. We’d ideally write our functions with PySpark and potentially create a SparkR “wrapper” over the top, leading to the question: Given a function written with PySpark that accepts a DataFrame parameter, is there a way to invoke this function using a SparkR DataFrame? Is there any reason to pursue this? Is it even possible? Many thanks, Danny For the latest data on the economy and society, consult our website at http://www.ons.gov.uk<http://www.ons.gov.uk/> *********************************************************************************************** Please Note: Incoming and outgoing email messages are routinely monitored for compliance with our policy on the use of electronic communications *********************************************************************************************** Legal Disclaimer: Any views expressed by the sender of this message are not necessarily those of the Office for National Statistics ***********************************************************************************************
