[R] Processing large datasets

[Jonathan Daily]

In cases where I have to parse through large datasets that will not
fit into R's memory, I will grab relevant data using SQL and then
analyze said data using R. There are several packages designed to do
this, like [1] and [2] below, that allow you to query a database using
SQL and end up with that data in an R data.frame.

[1] http://cran.cnr.berkeley.edu/web/packages/RMySQL/index.html
[2] http://cran.cnr.berkeley.edu/web/packages/RSQLite/index.html

On Wed, May 25, 2011 at 12:29 AM, Roman Naumenko <roman at bestroman.com> wrote:
> Hi R list,
>
> I'm new to R software, so I'd like to ask about it is capabilities.
> What I'm looking to do is to run some statistical tests on quite big
> tables which are aggregated quotes from a market feed.
>
> This is a typical set of data.
> Each day contains millions of records (up to 10 non filtered).
>
> 2011-05-24      750     Bid     DELL    14130770        400
> 15.4800         BATS    35482391        Y       1       1       0       0
> 2011-05-24      904     Bid     DELL    14130772        300
> 15.4800         BATS    35482391        Y       1       0       0       0
> 2011-05-24      904     Bid     DELL    14130773        135
> 15.4800         BATS    35482391        Y       1       0       0       0
>
> I'll need to filter it out first based on some criteria.
> Since I keep it mysql database, it can be done through by query. Not
> super efficient, checked it already.
>
> Then I need to aggregate dataset into different time frames (time is
> represented in ms from midnight, like 35482391).
> Again, can be done through a databases query, not sure what gonna be faster.
> Aggregated tables going to be much smaller, like thousands rows per
> observation day.
>
> Then calculate basic statistic: mean, standard deviation, sums etc.
> After stats are calculated, I need to perform some statistical
> hypothesis tests.
>
> So, my question is: what tool faster for data aggregation and filtration
> on big datasets: mysql or R?
>
> Thanks,
> --Roman N.
>
>        [[alternative HTML version deleted]]
>
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-- 
===============================================
Jon Daily
Technician
===============================================
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