I have a data table with non-unique keys:
> dput(sv)
structure(list(kwd = c("a", "a", "b", "b", "c"), pixel = c(1,
2, 1, 2, 2), kpN = c(2L, 2L, 2L, 1L, 1L)), row.names = c(NA,
-5L), class = c("data.table", "data.frame"), .Names = c("kwd",
"pixel", "kpN"), .internal.selfref = <pointer: 0x7fc4aa800778>, sorted = "kwd")
> dput(kwd)
structure(list(kwd = c("a", "b", "c", "z"), kwdN = c(3L, 2L,
1L, 1L)), row.names = c(NA, -4L), class = c("data.table", "data.frame"
), .Names = c("kwd", "kwdN"), .internal.selfref = <pointer: 0x7fc4aa800778>, sorted = "kwd")
why am I getting this error:
> sv[kwd,kwdN:=kwdN]
Starting bmerge ...done in 0 secs
Error in vecseq(f__, len__, if (allow.cartesian || notjoin) NULL else as.integer(max(nrow(x),  :
  Join results in 6 rows; more than 5 = max(nrow(x),nrow(i)). Check for duplicate key values in i, each of which join to the same group in x over and over again. If that's ok, try including `j` and dropping `by` (by-without-by) so that j runs for each group to avoid the large allocation. If you are sure you wish to proceed, rerun with allow.cartesian=TRUE. Otherwise, please search for this error message in the FAQ, Wiki, Stack Overflow and datatable-help for advice.
Calls: [ -> [.data.table -> vecseq
I expected something like this (note that the keys are :
   kwd pixel kpN kwdN
1:   a     1   2    3
2:   a     2   2    3
3:   b     1   2    2
4:   b     2   1    2
5:   c     2   1    1
Moreover, I am pretty sure that it worked like that before.
Is this something that changed in data.table 1.9.4?
How do I get what I want? (kwd[sv] appears to work, is that the new way?)
 
     
    