Using plyr::dply more (memory) efficiently?

Thanks for directing me to the data.table package. I read through some
of the vignettes, and it looks quite nice.

While your sample code would provide answer if I wanted to just
compute some summary statistic/function of groups of my data.frame
(using `by=symbol`), what's the best way to produces several pieces of
info per subset.

For instance, I see that I can do something like this:

summaries[, list(counts=sum(counts), width=sum(exon.width)), by=symbol]

But what if I need to do some more complex processing within the
subsets defined in `by=symbol` -- like several lines of programming
logic for 1 result, say.

I guess I can open a new block that just returns a data.table? Like:

summaries[, {
 cnts <- sum(counts)
 ew <- sum(exon.width)
 # ... some complex things
 complex <- # .. result of complex things
 data.table(counts=cnts, width=ew, cplx=complex)
}, by=symbol]

Is that right? (I mean, it looks like it's working, but maybe there's
a more idiomatic way(?))