You have given information related to the number of rows that will be involved,
but have offered nothing about the number of columns. That is okay though...
you should attempt your algorithms on progressively larger datasets to gauge
how your problem scales and use your operating system to observe how much
memory is involved and extrapolate. You can also rent time on cloud servers
such as Amazon offers.
Any minimum number we tell you could turn out to be insufficient when you start
exploring your large data sets... it is better for you to make your own
estimate and safety margin so you don't blame us when it turns out to run
slowly or choke completely.
Also, please stop posting in HTML format as requested by the Posting Guide.
---
Jeff NewmillerThe . . Go Live...
DCN:Basics: ##.#. ##.#. Live Go...
Live: OO#.. Dead: OO#.. Playing
Research Engineer (Solar/BatteriesO.O#. #.O#. with
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---
Sent from my phone. Please excuse my brevity.
On May 30, 2014 6:15:53 AM PDT, Magdalena Kapelko
wrote:
>Dear R users,
>
>I am writing to ask your advice with regard to the computer
>requirements
>(RAM, architecture, processor, hard drive) in order to run R smoothly
>on
>large datasets.
>
>I will be running commands with many bootstrap replications (2000) on
>the
>datasets of 10 firms.
>
>Thank you in advance for your suggestions.
>Best regards,
>Magdalena
>
> [[alternative HTML version deleted]]
>
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>PLEASE do read the posting guide
>http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.
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