Недопустимый .internal.selfref в data.table

Мне нужно было назначить "второй" id для группировки некоторых значений внутри моего исходного id. это мои данные образца:

dt<-structure(list(id = c("aaaa", "aaaa", "aaas", "aaas", "bbbb", "bbbb"),
                   period = c("start", "end", "start", "end", "start", "end"),
                   date = structure(c(15401L, 15401L, 15581L, 15762L, 15430L, 15747L), class = c("IDate", "Date"))),
              class = c("data.table", "data.frame"),
              .Names = c("id", "period", "date"),
              sorted = "id")
> dt
     id period       date
1: aaaa  start 2012-03-02
2: aaaa    end 2012-03-05
3: aaas  start 2012-08-21
4: aaas    end 2013-02-25
5: bbbb  start 2012-03-31
6: bbbb    end 2013-02-11

column id необходимо сгруппировать (используя то же значение в say id2) в соответствии с этим списком:

> groups
[[1]]
[1] "aaaa" "aaas"

[[2]]
[1] "bbbb"

Я использовал следующий код, который, кажется, работает, дает следующее warning:

    > dt[, id2 := which(vapply(groups, function(x,y) any(x==y), .BY[[1]], FUN.VALUE=T)), by=id]
    Warning message:
    In `[.data.table`(dt, , `:=`(id2, which(vapply(groups, function(x,  :
      Invalid .internal.selfref detected and fixed by taking a copy of the whole table,
so that := can add this new column by reference. At an earlier point, this data.table has
been copied by R (or been created manually using structure() or similar). Avoid key<-,
names<- and attr<- which in R currently (and oddly) may copy the whole data.table. Use
set* syntax instead to avoid copying: setkey(), setnames() and setattr(). Also,
list (DT1,DT2) will copy the entire DT1 and DT2 (R list() copies named objects),
use reflist() instead if needed (to be implemented). If this message doesn't help,
please report to datatable-help so the root cause can be fixed.
    > dt
         id period       date id2
    1: aaaa  start 2012-03-02   1
    2: aaaa    end 2012-03-02   1
    3: aaas  start 2012-08-29   1
    4: aaas    end 2013-02-26   1
    5: bbbb  start 2012-03-31   2
    6: bbbb    end 2013-02-11   2

может кто-нибудь кратко объяснить природу этого предупреждения и любое возможное последствие окончательных результатов (если таковые имеются)? спасибо

ИЗМЕНИТЬ:

фактический код фактически показывает, когда создается dt и как передается функция, которая дает предупреждение:

f.main <- function(){
      f2 <- function(x){
      groups <- list(c("aaaa", "aaas"), "bbbb") # actually generated depending on the similarity between values of x$id
      x <- x[, id2 := which(vapply(groups, function(x,y) any(x==y), .BY[[1]], FUN.VALUE=T)), by=id]
      return(x)
  }
  x <- f1()
  if(!is.null(x[["res"]])){
    x <- f2(x[["res"]])
    return(x)
  } else {
    # something else
  }
}

f1 <- function(){
  dt<-data.table(id = c("aaaa", "aaaa", "aaas", "aaas", "bbbb", "bbbb"),
                 period = c("start", "end", "start", "end", "start", "end"),
                 date = structure(c(15401L, 15401L, 15581L, 15762L, 15430L, 15747L), class = c("IDate", "Date")))
  return(list(res=dt, other_results=""))
}

> f.main()
     id period       date id2
1: aaaa  start 2012-03-02   1
2: aaaa    end 2012-03-02   1
3: aaas  start 2012-08-29   1
4: aaas    end 2013-02-26   1
5: bbbb  start 2012-03-31   2
6: bbbb    end 2013-02-11   2
Warning message:
In `[.data.table`(x, , `:=`(id2, which(vapply(groups, function(x,  :
  Invalid .internal.selfref detected and fixed by taking a copy of the whole table,
so that := can add this new column by reference. At an earlier point, this data.table
has been copied by R (or been created manually using structure() or similar).
Avoid key<-, names<- and attr<- which in R currently (and oddly) may copy the whole
data.table. Use set* syntax instead to avoid copying: setkey(), setnames() and setattr().
Also, list(DT1,DT2) will copy the entire DT1 and DT2 (R list() copies named objects),
use reflist() instead if needed (to be implemented). If this message doesn't help,
please report to datatable-help so the root cause can be fixed.

Ответы

DT <- data.table(1:5)
mylist1 <- list(DT,"a")
mylist1[[1]][,id:=.I]
#warning

mylist2 <- list(data.table(1:5),"a")
mylist2[[1]][,id:=.I]
#no warning

f1 <- function(){
  mylist <- list(res=data.table(id = c("aaaa", "aaaa", "aaas", "aaas", "bbbb", "bbbb"),
                 period = c("start", "end", "start", "end", "start", "end"),
                 date = structure(c(15401L, 15401L, 15581L, 15762L, 15430L, 15747L), class = c("IDate", "Date"))))
  other_results <- ""
  mylist$other_results <- other_results
  mylist
}

set.seed(45)
ss <- function() {
    tt <- sample(1:10, 1e6, replace=TRUE)
}
tt <- replicate(100, ss(), simplify=FALSE)
tt <- as.data.table(tt)

system.time( {
    ll <- list(d1 = { # shallow copy here...
        data.table:::settruelength(tt, 0)
        invisible(alloc.col(tt))
    }, "a")
})
user  system elapsed
   0       0       0
> system.time(tt[, bla := 2])
   user  system elapsed
  0.012   0.000   0.013
> system.time(ll[[1]][, bla :=2 ])
   user  system elapsed
  0.008   0.000   0.010

# From:

      x <- x[, id2 := which(vapply(groups, function(x,y) any(x==y), .BY[[1]], FUN.VALUE=T)), by=id]

# To something along the lines of:
      x$id2 <- findInterval( match( x$id, unlist(groups)), cumsum(c(0,sapply(groups, length)))+1)

Performance Comparison:
Unit: milliseconds
                       expr      min       lq   median       uq      max neval
                   f.main() 2.896716 2.982045 3.034334 3.137628 7.542367   100
 suppressWarnings(f.main()) 3.005142 3.081811 3.133137 3.210126 5.363575   100
            f.main.direct() 1.279303 1.384521 1.413713 1.486853 5.684363   100