[R] SQL implementations (was: Are you experienced in SAS and R ...)

[Vadim Ogranovich]

On Fri, 23 Nov 2001, Dirk Eddelbuettel wrote:

>
>   "Vadim" == Vadim Ogranovich <vograno at arbitrade.com> writes:
>   Vadim> A related question. Prof. Ripley mentioned few times that one of
his
>   Vadim> approaches is to generate random samples from databases, which
are
>   Vadim> then analyzed in R (one doesn't need any sort of embedding for
>   Vadim> this). Are there other techniques?
>
> You might be overlooking the fact that random subsampling from timeseries
can
> severely distory the dynamic structure of the series.

This is yet another reason I don't see the advantage of databases over
multi-pass algorithms. If you read a time series as a stream you can easily
stratify it, like Prof. Ripley mentioned in his other posting, and convert
it into another STREAM that looks like a DATASET of possibly large number of
columns. You can then feed this stream, which takes const memory, into the
multi-pass algorithm to model the temporal structure.
I don't know how one can practically do it with a database (certainly not
using SQL).

I believe I am missing the point behind the use of databases for modelling
very large data sets and would be grateful for any insight.

Thanks, Vadim

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