The Data-table FAQ 1.11 states:
"When you write x[y,foo*boo], data.table automatically inspects the j
expression to see which columns it uses.
It will only subset, or group, those columns only. Memory is only created
for the columns the j uses.
Let’s say foo is in x, and boo is in y (along with 20 other columns in y).
Isn’t x[y,foo*boo] quicker to program and quicker to run than a merge step
followed by another subset step ?"
Contrary to what it says above, I get an error when I try to access a
y-column in the "j" argument of x[y,j].
See the sequence of code below.
> x <- data.table( foo = c(1,1,1,2,2,3), a = 1:6, key = 'foo')
> y <- data.table( foo = c(1,2), boo = 10:11, key = 'foo')
# the below works as expected
> x[y]
foo a
[1,] 1 1
[2,] 2 4
> with( merge(x,y), foo*boo)
[1] 10 10 10 22 22
# I want to acheive the same result as the above using the
# syntactically more compact (and faster?) code below:
> x[y, foo * boo ]
Error in eval(expr, envir, enclos) : object 'boo' not found
So is the FAQ just wrong, or am I misunderstanding something?
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