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 _________________________________________________________________ ÌìÁ¹ÁË£¬ÌíÒÂÁË£¬ÐĶ¯ÁË£¬¡°Æß¼þ¡±ÁË http://get.live.cn [[alternative HTML version deleted]]
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