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From ayan guha <guha.a...@gmail.com>
Subject Re: Scala Vs Python
Date Thu, 01 Sep 2016 21:20:59 GMT
Thanks All for your replies.

Feature Parity:

MLLib, RDD and dataframes features are totally comparable. Streaming is now
at par in functionality too, I believe. However, what really worries me is
not having Dataset APIs at all in Python. I think thats a deal breaker.

Performance:
I do  get this bit when RDDs are involved, but not when Data frame is the
only construct I am operating on.  Dataframe supposed to be
language-agnostic in terms of performance.  So why people think python is
slower? is it because of using UDF? Any other reason?

*Is there any kind of benchmarking/stats around Python UDF vs Scala UDF
comparison? like the one out there  b/w RDDs.*

@Kant:  I am not comparing ANY applications. I am comparing SPARK
applications only. I would be glad to hear your opinion on why pyspark
applications will not work, if you have any benchmarks please share if
possible.





On Fri, Sep 2, 2016 at 12:57 AM, kant kodali <kanth909@gmail.com> wrote:

> c'mon man this is no Brainer..Dynamic Typed Languages for Large Code Bases
> or Large Scale Distributed Systems makes absolutely no sense. I can write a
> 10 page essay on why that wouldn't work so great. you might be wondering
> why would spark have it then? well probably because its ease of use for ML
> (that would be my best guess).
>
>
>
> On Wed, Aug 31, 2016 11:45 PM, AssafMendelson assaf.mendelson@rsa.com
> wrote:
>
>> 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:[hidden email]
>> <http:///user/SendEmail.jtp?type=node&node=27637&i=0>]
>> *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: RE: Scala Vs Python
>> <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
>> <http://apache-spark-user-list.1001560.n3.nabble.com/> at Nabble.com.
>>
>


-- 
Best Regards,
Ayan Guha

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