Q:

data.table join (multiple) selected columns with new names

I like to join two tables that have some identical columns (names and values) and others that are not. I'm only interested in joining those that are not identical and I would like to determine a new name for them. The way I currently do it seems verbose and hard to handle for the real tables I have with 100+ columns, i.e. I would like to determine the columns to be joined in advance and not in join statement. Reproducible example:
# create table 1
DT1 = data.table(id = 1:5, x=letters[1:5], a=11:15, b=21:25)
# create table 2 with changed values for a, b via pre-determined cols
DT2 = copy(DT1)
cols <- c("a", "b")
DT2[, (cols) := lapply(.SD, function(x) x*2), .SDcols = cols]

# this both works but is verbose for many columns
DT1[DT2, c("a_new", "b_new") := list(i.a, i.b), on=c(id="id")]
DT1[DT2, `:=` (a_new=i.a, b_new=i.b), on = c(id="id")]

I was thinking about something like this (doesn't work):
cols_new <- c("a_new", "b_new")
cols <- c("a", "b")
DT1[DT2, cols_new := i.cols, on=c(id="id")]

A:

Updated answer based on Arun's recommendation:
cols_old <- c('i.a', 'i.b')
DT1[DT2, (cols_new) := mget(cols_old), on = c(id = "id")]

you could also generate the cols_old by doing: 
paste0('i.', gsub('_new', '', cols_new, fixed = TRUE))

See history for the old answer.

