How does the it compare if you read it into R and then do your
aggregate with sqldf:
library(sqldf)
# example using builtin data set CO2
CO2agg <- sqldf("select Plant, Type, Treatment, avg(conc) from CO2
group by Plant, Type, Treatment")
# or using your data:
Xagg <- sqldf("select Group, Age, Type, avg(Salary) from X group by
Group, Age, Type")
On Jan 26, 2008 6:45 PM, zhihuali <[EMAIL PROTECTED]> wrote:
>
> Hi, netters,
>
> First of all, thanks a lot for all the prompt replies to my earlier question
> about "merging" data frames in R.
> Actually that's an equivalence to the "join" clause in mysql.
>
> Now I have another question. Suppose I have a data frame X with lots of
> columns/variables:
> Name, Age,Group, Type, Salary.
> I wanna do a subtotal of salaries:
> aggregate(X$Salary, by=list(X$Group,X$Age,X$Type),Fun=mean)
>
> When the levels of Group and Type are huge, it took R forever to finish the
> aggregation.
> And I used gc to find that the memory usage was big too.
>
> However, in mysql, it took seconds to finish a similar job:
> select Group,Age,Type ,avg(Salary) from X group by Group,Age,Type
>
> Is it because mysql is superior in doing such kind of things? Or my R command
> is not efficient enough? Why did R have to consume huge memories to do the
> aggregation?
>
> Thanks again!
>
> Zhihua Li
>
> _________________________________________________________________
> 天凉了，添衣了，心动了，"七件"了
> http://get.live.cn
> [[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.
>
>
______________________________________________
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.
