Isn't interpreter in python a problem for data analysis?

Question

let's say we have a code that interpreter has no issues with, when we run the code over a large data set, we can get a lot of logical errors,so waste of time and computation Power, is there a way around this or should we just accept the fact code according?

Answer 1

A good code will have lots of safety checks, try/except clauses, data completion mechanisms and other tricks to prevent it from failing on errors.

Still, it may happen regardless the language. Scripting ones don't make it a tedious process after all. Now imagine having to debug, fix and tailor a compiled application everytime there is a non-fitting stream of data... 😱

Answer 2

Try scala or spark for big data ?

Answer 3

sure thing that scala or spark with hadoop can do everything regarding big data, I just had the doubts as companies like Google have switched over to python, and I wonder how they manage analsis using python?

Answer 4

Got it, thanks Kuba. one has ensure that there are safety mechanism in thee code to handle exception errors!