• Post Reply Bookmark Topic Watch Topic
  • New Topic
programming forums Java Mobile Certification Databases Caching Books Engineering Micro Controllers OS Languages Paradigms IDEs Build Tools Frameworks Application Servers Open Source This Site Careers Other Pie Elite all forums
this forum made possible by our volunteer staff, including ...
Marshals:
  • Campbell Ritchie
  • Ron McLeod
  • Paul Clapham
  • Jeanne Boyarsky
  • Liutauras Vilda
Sheriffs:
  • Rob Spoor
  • Bear Bibeault
  • Tim Cooke
Saloon Keepers:
  • Tim Moores
  • Stephan van Hulst
  • Tim Holloway
  • Carey Brown
  • Piet Souris
Bartenders:
  • Frits Walraven
  • Himai Minh

Question: liveProject: How to Think about Manipulating Data -- performance

 
Ranch Hand
Posts: 54
  • Mark post as helpful
  • send pies
    Number of slices to send:
    Optional 'thank-you' note:
  • Quote
  • Report post to moderator
Hello Ana,
I am very new to pandas library, but not new to Spark. Here is my question:
Since Spark is written (mostly) in Scala, does an application performance written in Python suffer from having to convert Scala datatypes to Python and back?

Regards,
Alex
 
Author
Posts: 3
5
  • Likes 1
  • Mark post as helpful
  • send pies
    Number of slices to send:
    Optional 'thank-you' note:
  • Quote
  • Report post to moderator
I am not familiar with Scala or Spark too much, so I'm not sure how much I can help. But as far as I can tell, pandas is a lot slower than something like pyspark -- much of this performance comes from the fact that spark is multi-threaded and pandas is single-threaded.
 
This tiny ad is wafer thin:
Thread Boost feature
https://coderanch.com/t/674455/Thread-Boost-feature
reply
    Bookmark Topic Watch Topic
  • New Topic