Start Validating user calculating server

Validating user calculating server

We’re now collecting job metrics, which can be very useful for monitoring and validating job history, but we can do much more with this data.

All in all, both languages, when doing statistical and predictive analysis, also have couple of annoyances that should also be addressed: So next time, when you ask yourself or overhear the conversation in the community, which one is better (bigger, faster, stable,…), start asking the questions on your needs and effort to adopt it. It does not hurt to learn and use both (for at least the statistical and predictive purposes).

Once collected, job performance metrics can be used for a variety of reporting needs, from locating jobs that are not performing well to finding optimal release windows, scheduling maintenance, or trending over time.

Using these tools & metrics, we can look at past data, in order to observe trends and forecast future job runtimes, allowing us to solve a performance problem before it becomes serious.

We can use this data to alert on rogue jobs, or those that are performing well out of their typical boundaries.

And expressing taste through someone else taste is even harder.

My initial reaction is a counter-question, why are you asking this?

Obviously, Python in comparison to R is more general purpose scripting and programming language, therefore the number of packages is 10x higher, when compared to R.