I believe this would greatly depend on your use case and your familiarity with the languages.
In general, scala would have a much better performance than python and not all interfaces are available in python. That said, if you are planning to use dataframes without any UDF then the performance hit is practically nonexistent. Even if you need UDF, it is possible to write those in scala and wrap them for python and still get away without the performance hit. Python does not have interfaces for UDAFs. I believe that if you have large structured data and do not generally need UDF/UDAF you can certainly work in python without losing too much. From: ayan guha [mailto:guha.a...@gmail.com] Sent: Thursday, September 01, 2016 5:03 AM To: user Subject: Scala Vs Python Hi Users Thought to ask (again and again) the question: While I am building any production application, should I use Scala or Python? I have read many if not most articles but all seems pre-Spark 2. Anything changed with Spark 2? Either pro-scala way or pro-python way? I am thinking performance, feature parity and future direction, not so much in terms of skillset or ease of use. Or, if you think it is a moot point, please say so as well. Any real life example, production experience, anecdotes, personal taste, profanity all are welcome :) -- Best Regards, Ayan Guha -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/RE-Scala-Vs-Python-tp27637.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
