r - find *all* duplicated records in data.table (not all-but-one)

Question

if I understand correctly, duplicated() function for data.table returns a logical vector which doesn't contain first occurrence of duplicated record. What is the best way to mark this first occurrence as well? In case of base::duplicated(), I solved this simply by disjunction with reversed order function: myDups <- (duplicated(x) | duplicated(x, fromLast=TRUE)) - but in data.table::duplicated(), fromLast=TRUE is not included (I don't know why)...

P.S. ok, here's a primitive example

myDT <- fread(
"id,fB,fC
 1, b1,c1
 2, b2,c2
 3, b1,c1
 4, b3,c3
 5, b1,c1
")
setkeyv(myDT, c('fB', 'fC'))
myDT[, fD:=duplicated(myDT)]

rows 1, 3 and 5 are all duplicates but only 3 and 5 will be included in duplicated while I need to mark all of them.

UPD. important notice: the answer I've accepted below works only for keyed table. If you want to find duplicate records considering all columns, you have to setkey all these columns explicitly. So far I use the following workaround specifically for this case:

dups1 <- duplicated(myDT);
dups2 <- duplicated(myDT, fromLast=T);
dups <- dups1 | dups2;

Answer 1

This appears to work:

> myDT[unique(myDT),fD:=.N>1]
> myDT
   id  fB fC    fD
1:  1  b1 c1  TRUE
2:  3  b1 c1  TRUE
3:  5  b1 c1  TRUE
4:  2  b2 c2 FALSE
5:  4  b3 c3 FALSE

Thanks to @flodel, the better way to do it is this:

> myDT[, fD := .N > 1, by = key(myDT)]
> myDT
   id  fB fC    fD
1:  1  b1 c1  TRUE
2:  3  b1 c1  TRUE
3:  5  b1 c1  TRUE
4:  2  b2 c2 FALSE
5:  4  b3 c3 FALSE

The difference in efficiency is substantial:

> microbenchmark(
    key=myDT[, fD := .N > 1, by = key(myDT)],
    unique=myDT[unique(myDT),fD:=.N>1])
Unit: microseconds
   expr      min       lq    median        uq       max neval
    key  679.874  715.700  735.0575  773.7595  1825.437   100
 unique 1417.845 1485.913 1522.7475 1567.9065 24053.645   100

Especially for the max. What's going on there?