Hi. You don't need to download the whole of the output database table to look for an already generated answer. You can write a SQL query to do that instead. ie. give me any rows with these parameters... Get the database to do the work - it is what they are designed to do.
So the procedure is: 1. Get input parameters 2. Query the output database to see whether analysis has already been done (select * from output_table where...) 3. If not already done, do the calculation and insert result into output table Note: you don't have to use sqlSave to save data. One can add single rows by running arbitrary SQL. Mark 2008/12/12 Brigid Mooney <bkmoo...@gmail.com>: > I am using R as a data manipulation tool for a SQL database. So in some of > my R scripts I use the RODBC package to retreive data, then run analysis, > and use the sqlSave function in the RODBC package to store the results in a > database. > > There are two problems I want to avoid, and they are highly related: (1) > having R rerun analysis which has already been done and saved into output > database table, and (2) ending up with more than one identical row in > my output database table. > > ------------------------------------- > The analysis I am running allows the user to input a large number of > variables, for example: > date, version, a, b, c, d, e, f, g, ... > > After R completes its analysis, I write the results to a database table in > the format: > Value, date, version, a, b, c, d, e, f, g, ... > > where Value is the result of the R analysis, and the rest of the columns are > the criteria that was used to get that value. > -------------------------------------- > > Can anyone think of a way to address these problems? The only thing I can > think of so far is to run an sqlQuery to get a table of all the variable > combinations that are saved at the start, and then simply avoid computing > and re-outputing those results. However, my results database table > currently has over 200K rows (and will grow very quickly as I keep going > with this project), so I think that would not be the most expeditious answer > as I think just the SQL query to download 200K rows x 10+ columns is going > to be time consuming in and of itself. > > I know this is kindof a weird problem, and am open to all sorts of ideas... > > Thanks! > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > > ______________________________________________________________________ > This email has been scanned by the MessageLabs Email Security System. > For more information please visit http://www.messagelabs.com/email > ______________________________________________________________________ > -- Dr. Mark Wardle Specialist registrar, Neurology Cardiff, UK ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
