0
$\begingroup$

I'm trying to apply classification algorithms to KDD Cup 2012 track2 data using R http://www.kddcup2012.org/c/kddcup2012-track2

It seems not possible to work with this 10GB training data on my local system with 4GB RAM. Can anyone work on this data using this kind of a local system ? Or is using a cluster the norm ?
It would be great if anyone could provide me with any guidance on how to get started with working on a cluster and the normally used type of cluster for such tasks

$\endgroup$
1
$\begingroup$

I think that you have, at least, the following major options for your data analysis scenario:

  1. Use big data-enabling R packages on your local system. You can find most of them via the corresponding CRAN Task View that I reference in this answer (see point #3).

  2. Use the same packages on a public cloud infrastructure, such as Amazon Web Services (AWS) EC2. If your analysis is non-critical and tolerant to potential restarts, consider using AWS Spot Instances, as their pricing allows for significant financial savings.

  3. Use the above mention public cloud option with R standard platform, but on more powerful instances (for example, on AWS you can opt for memory-optimized EC2 instances or general purpose on-demand instances with more memory).

In some cases, it is possible to tune a local system (or a cloud on-demand instance) to enable R to work with big(ger) data sets. For some help in this regard, see my relevant answer.

For both above-mentioned cloud (AWS) options, you can find more convenient to use R-focused pre-built VM images. See my relevant answer for details. You may also find useful this excellent comprehensive list of big data frameworks.

|improve this answer|||||
$\endgroup$
  • $\begingroup$ Thanks for the answer. I have access to some local systems, can you give me a start on how to set up a cluster using these systems without any cloud services ? Looks like everywhere AWS is being used. $\endgroup$ – abhivij Apr 13 '15 at 10:15
  • 1
    $\begingroup$ @abhivij: You're welcome. Setting up a cluster is not a rocket science, but might be not trivial, depending on the requirements and your current skills. You can read this blog post and this blog post as a starting point. (to be continued) $\endgroup$ – Aleksandr Blekh Apr 13 '15 at 10:37
  • 1
    $\begingroup$ @abhivij: (cont'd) Also, you'd have to refer to documentation on multiprocessing R packages that you will decide to use, for example this tutorial. A more high-level overview and example of an R-based cluster can be found in this working paper. Hope this helps. $\endgroup$ – Aleksandr Blekh Apr 13 '15 at 10:38

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.