[datatable-help] Cannot access cols of y when doing x[y, ...]

[Matthew Dowle]

Welcome to the list.
You're right, the FAQ is wrong.
FR#1095 is "Turn back on 'join inherited scope'".
This was a known problem in NEWS at v1.4 and still is.
When the grouping code was moved from R into C in v1.4 that feature
wasn't something that made it into the port.

Glad you appreciate the neater syntax and yes it should be faster (the
more columns in x and y the faster the speed up could be, over a merge
followed by a query).

I'll try and take a look soon.

Matthew


On Sat, 2011-01-22 at 10:41 -0500, Prasad Chalasani wrote:
> 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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